>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>>Alteryx is a company with a long history that goes all the way back to the late 1990s. Now the one consistent theme over 20 plus years has been that Ultrix has always been a data company early in the big data and Hadoop cycle. It saw the need to combine and prep different data types so that organizations could analyze data and take action Altrix and similar companies played a critical role in helping companies become data-driven. The problem was the decade of big data, brought a lot of complexities and required immense skills just to get the technology to work as advertised this in turn limited, the pace of adoption and the number of companies that could really lean in and take advantage of the cloud began to change all that and set the foundation for today's theme to Zuora of digital transformation. We hear that phrase a ton digital transformation. >>People used to think it was a buzzword, but of course we learned from the pandemic that if you're not a digital business, you're out of business and a key tenant of digital transformation is democratizing data, meaning enabling, not just hypo hyper specialized experts, but anyone business users to put data to work. Now back to Ultrix, the company has embarked on a major transformation of its own. Over the past couple of years, brought in new management, they've changed the way in which it engaged with customers with the new subscription model and it's topgraded its talent pool. 2021 was even more significant because of two acquisitions that Altrix made hyper Ana and trifecta. Why are these acquisitions important? Well, traditionally Altryx sold to business analysts that were part of the data pipeline. These were fairly technical people who had certain skills and were trained in things like writing Python code with hyper Ana Altryx has added a new persona, the business user, anyone in the business who wanted to gain insights from data and, or let's say use AI without having to be a deep technical expert. >>And then Trifacta a company started in the early days of big data by cube alum, Joe Hellerstein and his colleagues at Berkeley. They knocked down the data engineering persona, and this gives Altryx a complimentary extension into it where things like governance and security are paramount. So as we enter 2022, the post isolation economy is here and we do so with a digital foundation built on the confluence of cloud native technologies, data democratization and machine intelligence or AI, if you prefer. And Altryx is entering that new era with an expanded portfolio, new go-to market vectors, a recurring revenue business model, and a brand new outlook on how to solve customer problems and scale a company. My name is Dave Vellante with the cube and I'll be your host today. And the next hour, we're going to explore the opportunities in this new data market. And we have three segments where we dig into these trends and themes. First we'll talk to Jay Henderson, vice president of product management at Ultrix about cloud acceleration and simplifying complex data operations. Then we'll bring in Suresh Vetol who's the chief product officer at Altrix and Adam Wilson, the CEO of Trifacta, which of course is now part of Altrix. And finally, we'll hear about how Altryx is partnering with snowflake and the ecosystem and how they're integrating with data platforms like snowflake and what this means for customers. And we may have a few surprises sprinkled in as well into the conversation let's get started. >>We're kicking off the program with our first segment. Jay Henderson is the vice president of product management Altryx and we're going to talk about the trends and data, where we came from, how we got here, where we're going. We get some launch news. Well, Jay, welcome to the cube. >>Great to be here, really excited to share some of the things we're working on. >>Yeah. Thank you. So look, you have a deep product background, product management, product marketing, you've done strategy work. You've been around software and data, your entire career, and we're seeing the collision of software data cloud machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or data executive in an organization, w J what's your north star, where are you trying to take your company from a data and analytics point of view? >>Yeah, I mean, you know, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust, creating large volumes of data storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's, you know, drowning in data, but somehow still starving for insights. And so I think, uh, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics, um, and, you know, let the, the business users and the whole organization get value out of all that data they have. >>And we're going to dig into that throughout this program data, I like to say is plentiful insights, not always so much. Tell us about your launch today, Jay, and thinking about the trends that you just highlighted, the direction that your customers want to go and the problems that you're solving, what role does the cloud play in? What is what you're launching? How does that fit in? >>Yeah, we're, we're really excited today. We're launching the Altryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, um, and to take advantage of things like based access. So that it's really easy to give anyone access, including folks on a Mac. Um, it, you know, it also lets you take advantage of elastic compute so that you can do, you know, in database processing and cloud native, um, solutions that are gonna scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud, but we've got ultra to machine learning, which helps up-skill regular old analysts with advanced machine learning capabilities. We've got auto insights, which brings a business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition, which is Trifacta that helps data engineers do data pipelining and really, um, you know, create a lot of the underlying data sets that are used in some of this, uh, downstream analytics. >>Let's dig into some of those roles if we could a little bit, I mean, you've traditionally Altryx has served the business analysts and that's what designer cloud is fit for, I believe. And you've explained, you know, kind of the scope, sorry, you've expanded that scope into the, to the business user with hyper Anna. And we're in a moment we're going to talk to Adam Wilson and Suresh, uh, about Trifacta and that recent acquisition takes you, as you said, into the data engineering space in it. But in thinking about the business analyst role, what's unique about designer cloud cloud, and how does it help these individuals? >>Yeah, I mean, you know, really, I go back to some of the feedback we've had from our customers, which is, um, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product, you know, really, as they look to take the next step, they're trying to figure out how do I give access to that? Those types of analytics to thousands of people within the organization and designer cloud is, is really great for that. You've got the browser-based interface. So if folks are on a Mac, they can really easily just pop, open the browser and get access to all of those, uh, prep and blend capabilities to a lot of the analysis we're doing. Um, it's a great way to scale up access to the analytics and then start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >>Okay, great. So now then you add in the hyper Anna acquisition. So now you're targeting the business user Trifacta comes into the mix that deeper it angle that we talked about, how does this all fit together? How should we be thinking about the new Altryx portfolio? >>Yeah, I mean, I think it's pretty exciting. Um, you know, when you think about democratizing analytics and providing access to all these different groups of people, um, you've not been able to do it through one platform before. Um, you know, it's not going to be one interface that meets the, of all these different groups within the organization. You really do need purpose built specialized capabilities for each group. And finally, today with the announcement of the alternates analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single in the end application. So really finally delivering on the promise of providing analytics to all, >>How much of this you've been able to share with your customers and maybe your partners. I mean, I know OD is fairly new, but if you've been able to get any feedback from them, what are they saying about it? >>Uh, I mean, it's, it's pretty amazing. Um, we ran a early access, limited availability program that led us put a lot of this technology in the hands of over 600 customers, um, over the last few months. So we have gotten a lot of feedback. I tell you, um, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data. They've got, they're excited to be able to use analytics in every decision that they're making so that the decisions they have or more informed and produce better business outcomes. Um, and, and this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >>Yeah, those are good. Good, good numbers for, for preview mode. Let's, let's talk a little bit about vision. So it's democratizing data is the ultimate goal, which frankly has been elusive for most organizations over time. How's your cloud going to address the challenges of putting data to work across the entire enterprise? >>Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes, you know, in the, and these are really kind of enduring themes that you're going to see us making investments in over the next few years, the first is having cloud centricity. You know, the data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it, to provide cloud solution. So the first one is really around cloud centricity. The second is around big data fluency. Once you have all of the data, you need to be able to manipulate it in a performant manner. So having the elastic cloud infrastructure and in database processing is so important, the third is around making AI a strategic advantage. >>So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. Um, and then the fourth thing is really providing access across the entire organization. You know, it and data engineers, uh, as well as business owners and analysts. So, um, cloud centricity, big data fluency, um, AI is a strategic advantage and, uh, personas across the organization are really the four big themes you're going to see us, uh, working on over the next few months and, uh, coming coming year. >>That's good. Thank you for that. So, so on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know, monolithic organizations, uh, very specialized or I might even say hyper specialized roles and, and your, your mission of course is the customer. You, you, you, you and your customers, they want to democratize the data. And so it seems logical that domain leaders are going to take more responsibility for data, life cycles, data ownerships, low code becomes more important. And perhaps this kind of challenges, the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving and, and, and what role will Altryx play? >>Yeah. Um, you know, I think we'll see sort of a more federated systems start to emerge. Those centralized groups are going to continue to exist. Um, but they're going to start to empower, you know, in a much more de-centralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on, uh, problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model results in millions of dollars a day for the business. And then by pushing some of the analytics out to, uh, closer to the edge and closer to the business, you'll be able to apply those analytics in every single decision. So I think you're going to see, you know, both the decentralized and centralized models start to work in harmony and a little bit more about almost a federated sort of a way. And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, um, and drive business outcomes with the analytics they're using. >>Yeah. I mean, I think my take on another one, if you could comment is to me, the technology should be an operational detail and it has been the, the, the dog that wags the tail, or maybe the other way around, you mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operationals systems that then somehow, eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, users, those, those line of business experts get more access. That's your goal. And then even go beyond analytics, start to build data products that could be monetized, and that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >>Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications and to enable somebody who's an analyst or business user to create an application on top of the data and analytics layers that they have, um, really to help democratize the analytics, to help prepackage some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more. >>Yeah. And to your point, if you can federate the governance and automate that, then that can happen. I mean, that's a key part of it, obviously. So, all right, Jay, we have to leave it there up next. We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson who led Trifacta for more than seven years. It's the recipe. Tyler is the chief product officer at Altryx to explain the rationale behind the acquisition and how it's going to impact customers. Keep it right there. You're watching the cube. You're a leader in enterprise tech coverage. >>It's go time, get ready to accelerate your data analytics journey with a unified cloud native platform. That's accessible for everyone on the go from home to office and everywhere in between effortless analytics to help you go from ideas to outcomes and no time. It's your time to shine. It's Altryx analytics cloud time. >>Okay. We're here with. Who's the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate their businesses with that in mind, you know, we know designer and are the products that Altrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyper Rana now kind of renamed, um, Altrix auto. We even speak with the business owner and the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so fact made so much sense for us. >>Yeah. Thank you for that. I mean, you, look, you could have built it yourself would have taken, you know, who knows how long, you know, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birth Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical? And, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So, so a broader set of, of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I could use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company and I think is, as we, um, saw over the course of the last 5, 6, 7 years that, um, you know, uh, real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push-down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making is, is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making, because we've looked, we've contextualized most of our operational systems, but the big data pipeline is hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform for analytics, automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely Alcon's has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics, for AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. Um, and so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's applied and so multiple personas. Um, and we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now at least three personas the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that? How is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market is not crack the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. >>And you're really, you're obviously writing the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just what Adam said resonates with me deeply. Um, analytics is one of those, um, massive disciplines inside an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was all drinks and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altrix it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? Yeah, >>I think, I think you should think about them. And, uh, um, as, as very complimentary right designer cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, the really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with, um, Trifacta, um, I think we have to get deeper inside to think about what does the data engineer really need? What's the business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the trifecta on the amazing Trifacta cloud platform. >>You know, >>I think we're just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but one of the reasons I always liked Altrix is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the organization said, wow, this big data stuff has taken off, but we need security. We need governance. And it's interesting because you've got, you know, ETL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? Uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Um, thanks for asking about our sales kickoff. So we met for the first time and you've got a two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was a, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we added a Trifacta to, um, the, the potty such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for other the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working out him and I will, when he's so hot on, on the deal and the core hypotheses and so on. And then you step back and you're going to share the vision with the field organization, and it blows you away, the energy that it creates among our sellers out of partners. >>And I'm sure Madam will and his team were mocked, um, every single day, uh, with questions and opportunities to bring them in. But Adam, maybe you should share. Yeah, no, it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended, the story that we told was just, you have this opportunity to really cater to what the end users care about, which is a lot about interactivity and self-service, and at the same time. >>And that's, and that's a lot of the goodness that, um, that Altryx is, has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that jets. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube you're leader in enterprise tech coverage. >>This is your data housed neatly insecurely in the snowflake data cloud. And all of it has potential the potential to solve complex business problems, deliver personalized financial offerings, protect supply chains from disruption, cut costs, forecast, grow and innovate. All you need to do is put your data in the hands of the right people and give it an opportunity. Luckily for you. That's the easy part because snowflake works with Alteryx and Alteryx turns data into breakthroughs with just a click. Your organization can automate analytics with drag and drop building blocks, easily access snowflake data with both sequel and no SQL options, share insights, powered by Alteryx data science and push processing to snowflake for lightning, fast performance, you get answers you can put to work in your teams, get repeatable processes they can share in that's exciting because not only is your data no longer sitting around in silos, it's also mobilized for the next opportunity. Turn your data into a breakthrough Alteryx and snowflake >>Okay. We're back here in the queue, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest Terek do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to see >>Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security, and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer, you know, cloud migration momentum, and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central company's strategy. They always have been. We recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner community and strategy now addresses several kinds of partners, spanning solution providers to global SIS and technology partners, such as snowflake and together, we help our customers realize the business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform, guidance, deployment, support, and other professional services. >>Great. Let's get a little bit more into the relationship between Altrix and S in snowflake, the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing their costs. Um, Altrix proudly achieved. Snowflake's highest elite tier in their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the destroyed solution. We developed two great assets. One is the officer starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows, and videos, helping customers to get going more easily with an altered since snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Altryx and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems much faster. >>Cool. Kara, can you give us your perspective on the partnership? >>Yeah, definitely. Dave, so as Barb mentioned, we've got this standing very successful partnership going back years with hundreds of happy joint customers. And when I look at the beginning, Altrix has helped pioneer the concept of self-service analytics, especially with use cases that we worked on with for, for data prep for BI users like Tableau and as Altryx has evolved to now becoming from data prep to now becoming a full end to end data science platform. It's really opened up a lot more opportunities for our partnership. Altryx has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud, uh, with Alteryx orchestrating the end to end machine learning workflows Alteryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources, but so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful, um, that I can come up with today, the big challenges or trends for us, and Altrix really helps us across all of them. Um, there are three particular ones I'm going to talk about the first one being self-service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, um, you know, the, the technology users, but the business users, right? I think every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with Altrix is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So, um, with self-service analytics, with Ultrix designer they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst, um, report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now, with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. Um, and then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. Um, and with Altryx creating this platform so they can cater to both the everyday business user, the quote unquote, citizen data scientists, and making a code friendly for data scientists to be able to get at their notebooks and all the different tools that they want to use. Um, they fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution caring to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx um, if we look at mobilizing your data, getting access to third-party datasets, to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view, um, within their, their data applications. And so with Altryx alterations, we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with the snowflake data marketplace so that we can enrich these workflows, these great, great workflows that Altrix writing provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities, Dave. So those are three I see, uh, easily that we're going to be able to solve a lot of customer challenges with. >>So thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having imagine infrastructure to even be able to do it, to get applications off the ground. And so we created something to be cloud-native. We created to be a SAS managed service. So now that that Altrix is moving to the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster and they don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, um, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had two pre desktop products, and today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products were committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers, cloud and analytic >>Are. How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, gain efficiencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through discovery questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Dark. How do you see it? You'll go to market strategy. >>Yeah. Dave we've. Um, so we initially started selling, we initially sold snowflake as technology, right? Uh, looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we're starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Altrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so, um, Barb talked about these, these starter kits where it's prescriptive, you've got a demo and, um, a way that customers can get off the ground and running, right? >>Cause we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working in healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map two lines of business with Alteryx. >>Great. Thanks Derek. Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. Uh, we're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the ultra partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra score, providing our partners with earlier access to benefits, um, I could talk about our program for 30 minutes. I know we don't have time. The key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Tarik will give you the last word. What should we be looking for from, >>Yeah, thanks. Thanks, Dave. As BARR mentioned, Altrix has been the forefront of innovating with us. They've been integrating into, uh, making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before that extensibility is really what we're excited about. Um, the ability for Ultrix to plug into this extensibility framework that we call snow park and to be able to extend out, um, ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala, not Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right there probably day sets in, in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right? I think it's exciting to see what we're going to be able to do together with these upcoming innovations. Great >>Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with some closing thoughts in a summary, don't go away. >>1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops make that 2.3. The sector times out the wazoo, whites are much of this velocity's pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into insights, they turn to Altryx Qualtrics analytics, automation, >>Okay, let's summarize and wrap up the session. We can pretty much agree the data is plentiful, but organizations continue to struggle to get maximum value out of their data investments. The ROI has been elusive. There are many reasons for that complexity data, trust silos, lack of talent and the like, but the opportunity to transform data operations and drive tangible value is immense collaboration across various roles. And disciplines is part of the answer as is democratizing data. This means putting data in the hands of those domain experts that are closest to the customer and really understand where the opportunity exists and how to best address them. We heard from Jay Henderson that we have all this data exhaust and cheap storage. It allows us to keep it for a long time. It's true, but as he pointed out that doesn't solve the fundamental problem. Data is spewing out from our operational systems, but much of it lacks business context for the data teams chartered with analyzing that data. >>So we heard about the trend toward low code development and federating data access. The reason this is important is because the business lines have the context and the more responsibility they take for data, the more quickly and effectively organizations are going to be able to put data to work. We also talked about the harmonization between centralized teams and enabling decentralized data flows. I mean, after all data by its very nature is distributed. And importantly, as we heard from Adam Wilson and Suresh Vittol to support this model, you have to have strong governance and service the needs of it and engineering teams. And that's where the trifecta acquisition fits into the equation. Finally, we heard about a key partnership between Altrix and snowflake and how the migration to cloud data warehouses is evolving into a global data cloud. This enables data sharing across teams and ecosystems and vertical markets at massive scale all while maintaining the governance required to protect the organizations and individuals alike. >>This is a new and emerging business model that is very exciting and points the way to the next generation of data innovation in the coming decade. We're decentralized domain teams get more facile access to data. Self-service take more responsibility for quality value and data innovation. While at the same time, the governance security and privacy edicts of an organization are centralized in programmatically enforced throughout an enterprise and an external ecosystem. This is Dave Volante. All these videos are available on demand@theqm.net altrix.com. Thanks for watching accelerating automated analytics in the cloud made possible by Altryx. And thanks for watching the queue, your leader in enterprise tech coverage. We'll see you next time.

(bright upbeat music) >> Hello everyone, and welcome to the special exclusive CUBE Conversation, where we continue our coverage of the trends of the database market. With me is Nipun Agarwal, who's the vice president, MySQL HeatWave in advanced development at Oracle. Nipun, welcome. >> Thank you Dave. >> I love to have technical people on the Cube to educate, debate, inform, and we've extensively covered this market. We were all over the Snowflake IPO and at that time I remember, I challenged organizations bring your best people. Because I want to better understand what's happening at Database. After Oracle kind of won the Database wars 20 years ago, Database kind of got boring. And then it got really exciting with the big data movement, and all the, not only SQL stuff coming out, and Hadoop and blah, blah, blah. And now it's just exploding. You're seeing huge investments from many of your competitors, VCs are trying to get into the action. Meanwhile, as I've said many, many times, your chairman and head of technology, CTO, Larry Ellison, continues to invest to keep Oracle relevant. So it's really been fun to watch and I really appreciate you coming on. >> Sure thing. >> We have written extensively, we talked to a lot of Oracle customers. You get the leading mission critical database in the world. Everybody from Fortune 100, we evaluated what Gardner said about the operational databases. I think there's not a lot of question there. And we've written about that on WikiBound about you're converged databases, and the strategy there, and we're going to get into that. We've covered Autonomous Data Warehouse Exadata Cloud at Customer, and then we just want to really try to get into your area, which has been, kind of caught our attention recently. And I'm talking about the MySQL Database Service with HeatWave. I love the name, I laugh. It was an unveiled, I don't know, a few months ago. So Nipun, let's start the discussion today. Maybe you can update our viewers on what is HeatWave? What's the overall focus with Oracle? And how does it fit into the Cloud Database Service? >> Sure Dave. So HeatWave is a in-memory query accelerator for the MySQL Database Service for speeding up analytic queries as well as long running complex OLTP queries. And this is all done in the context of a single database which is the MySQL Database Service. Also, all existing MySQL applications or MySQL compatible tools and applications continue to work as is. So there is no change. And with this HeatWave, Oracle is delivering the only MySQL service which provides customers with a single unified platform for both analytic as well as transaction processing workloads. >> Okay, so, we've seen open source databases in the cloud growing very rapidly. I mentioned Snowflake, I think Google's BigQuery, get some mention, we'll talk, we'll maybe talk more about Redshift later on, but what I'm wondering, well let's talk about now, how does MySQL HeatWave service, how does that compare to MySQL-based services from other cloud vendors? I can get MySQL from others. In fact, I think we do. I think we run WikiBound on the LAMP stack. I think it's running on Amazon, but so how does your service compare? >> No other vendor, like, no other vendor offers this differentiated solution with an open source database namely, having a single database, which is optimized both for transactional processing and analytics, right? So the example is like MySQL. A lot of other cloud vendors provide MySQL service but MySQL has been optimized for transaction processing so when customs need to run analytics they need to move the data out of MySQL into some other database for any analytics, right? So we are the only vendor which is now offering this unified solution for both transactional processing analytics. That's the first point. Second thing is, most of the vendors out there have taken open source databases and they're basically hosting it in the cloud. Whereas HeatWave, has been designed from the ground up for the cloud, and it is a 100% compatible with MySQL applications. And the fact that we have designed it from the ground up for the cloud, maybe I'll spend 100s of person years of research and engineering means that we have a solution, which is very, very scalable, it's very optimized in terms of performance, and it is very inexpensive in terms of the cost. >> Are you saying, well, wait, are you saying that you essentially rewrote MySQL to create HeatWave but at the same time maintained compatibility with existing applications? >> Right. So we enhanced MySQL significantly and we wrote a whole bunch of new code which is brand new code optimized for the cloud in such a manner that yes, it is 100% compatible with all existing MySQL applications. >> What does it mean? And if I'm to optimize for the cloud, I mean, I hear that and I say, okay, it's taking advantage of cloud-native. I hear kind of the buzzwords, cloud-first, cloud-native. What does it specifically mean from a technical standpoint? >> Right. So first, let's talk about performance. What we have done is that we have looked at two aspects. We have worked with shapes like for instance, like, the compute shapes which provide the best performance for dollar, per dollar. So I'll give you a couple of examples. We have optimized for certain shifts. So, HeatWave is in-memory query accelerator. So the cost of the system is dominated by the cost. So we are working with chips which provide the cheapest cost per terabyte of memory. Secondly, we are using commodity cloud services in such a manner that it's in-optimized for both performance as well as performance per dollar. So, example is, we are not using any locally-attached SSDs. We use ObjectStore because it's very inexpensive. And then I guess at some point I will get into the details of the architecture. The system has been really, really designed for massive scalability. So as you add more compute, as you add more service, the system continues to scale almost perfectly linearly. So this is what I mean in terms of being optimized for the cloud. >> All right, great. >> And furthermore, (indistinct). >> Thank you. No, carry on. >> Over the next few months, you will see a bunch of other announcements where we're adding a whole bunch of machine learning and data driven-based automation which we believe is critical for the cloud. So optimized for performance, optimized for the cloud, and machine learning-based automation which we believe is critical for any good cloud-based service. >> All right, I want to come back and ask you more about the architecture, but you mentioned some of the others taking open source databases and shoving them into the cloud. Let's take the example of AWS. They have a series of specialized data stores and, for different workloads, Aurora is for OLTP I actually think it's based on MySQL Redshift which is based on ParAccel. And so, and I've asked Amazon about this, and their response is, actually kind of made sense to me. Look, we want the right tool for the right job, we want access to the primitives because when the market changes we can change faster as opposed to, if we put, if we start building bigger and bigger databases with more functionality, it's, we're not as agile. So that kind of made sense to me. I know we, again, we use a lot, we use, I think I said MySQL in Amazon we're using DynamoDB, works, that's cool. We're not huge. And I, we fully admit and we've researched this, when you start to get big that starts to get maybe expensive. But what do you think about that approach and why is your approach better? >> Right, we believe that there are multiple drawbacks of having different databases or different services, one, optimized for transactional processing and one for analytics and having to ETL between these different services. First of all, it's expensive because you have to manage different databases. Secondly, it's complex. From an application standpoint, applications need, now need to understand the semantics of two different databases. It's inefficient because you have to transfer data at some PRPC from one database to the other one. It's not secure because there is security aspects involved when your transferring data and also the identity of users in the two different databases is different. So it's, the approach which has been taken by Amazons and such, we believe, is more costly, complex, inefficient and not secure. Whereas with HeatWave, all the data resides in one database which is MySQL and it can run both transaction processing and analytics. So in addition to all the benefits I talked about, customers can also make their decisions in real time because there is no need to move the data. All the data resides in a single database. So as soon as you make any changes, those changes are visible to customers for queries right away, which is not the case when you have different siloed specialized databases. >> Okay, that, a lot of ways to skin a cat and that what you just said makes sense. By the way, we were saying before, companies have taken off the shelf or open source database has shoved them in the cloud. I have to give Amazon some props. They actually have done engineering to Aurora and Redshift. And they've got the engineering capabilities to do that. But you can see, for example, in Redshift the way they handle separating compute from storage it's maybe not as elegant as some of the other players like a Snowflake, for example, but they get there and they, maybe it's a little bit more brute force but so I don't want to just make it sound like they're just hosting off the shelf in the cloud. But is it fair to say that there's like a crossover point? So in other words, if I'm smaller and I'm not, like doing a bunch of big, like us, I mean, it's fine. It's easy, I spin it up. It's cheaper than having to host my own servers. So there's, presumably there's a sweet spot for that approach and a sweet spot for your approach. Is that fair or do you feel like you can cover a wider spectrum? >> We feel we can cover the entire spectrum, not wider, the entire spectrum. And we have benchmarks published which are actually available on GitHub for anyone to try. You will see that this approach you have taken with the MySQL Database Service in HeatWave, we are faster, we are cheaper without having to move the data. And the mileage or the amount of improvement you will get, surely vary. So if you have less data the amount of improvement you will get, maybe like say 100 times, right, or 500 times, but smaller data sizes. If you get to lots of data sizes this improvement amplifies to 1000 times or 10,000 times. And similarly for the cost, if the data size is smaller, the cost advantage you will have is less, maybe MySQL HeatWave is one third the cost. If the data size is larger, the cost advantage amplifies. So to your point, MySQL Database Service in HeatWave is going to be better for all sizes but the amount of mileage or the amount of benefit you will get increases as the size of the data increases. >> Okay, so you're saying you got better performance, better cost, better price performance. Let me just push back a little bit on this because I, having been around for awhile, I often see these performance and price comparisons. And what often happens is a vendor will take the latest and greatest, the one they just announced and they'll compare it to an N-1 or an N-2, running on old hardware. So, is, you're normalizing for that, is that the game you're playing here? I mean, how can you, give us confidence that this is easier kind of legitimate benchmarks in your GitHub repo. >> Absolutely. I'll give you a bunch of like, information. But let me preface this by saying that all of our scripts are available in the open source in the GitHub repo for anyone to try and we would welcome feedback otherwise. So we have taken, yes, the latest version of MySQL Database Service in HeatWave, we have optimized it, and we have run multiple benchmarks. For instance, TBC-H, TPC-DS, right? Because the amount of improvement a query will get depends upon the specific query, depends upon the predicates, it depends on the selectivity so we just wanted to use standard benchmarks. So it's not the case that if you're using certain classes of query, excuse me, benefit, get them more. So, standard benchmarks. Similarly, for the other vendors or other services like Redshift, we have run benchmarks on the latest shapes of Redshift the most optimized configuration which they recommend, running their scripts. So this is not something that, hey, we're just running out of the box. We have optimized Aurora, we have optimized (indistinct) to the best and possible extent we can based on their guidelines, based on their latest release, and that's what you're talking about in terms of the numbers. >> All right. Please continue. >> Now, for some other vendors, if we get to the benchmark section, we'll talk about, we are comparing with other services, let's say Snowflake. Well there, there are issues in terms of you can't legally run Snowflake numbers, right? So there, we have looked at some reports published by Gigaom report. and we are taking the numbers published by the Gigaom report for Snowflake, Google BigQuery and as you'll see maps numbers, right? So those, we have not won ourselves. But for AWS Redshift, as well as AWS Aurora, we have run the numbers and I believe these are the best numbers anyone can get. >> I saw that Gigaom report and I got to say, Gigaom, sometimes I'm like, eh, but I got to say that, I forget the guy's name, he knew what he was talking about. He did a good job, I thought. I was curious as to the workload. I always say, well, what's the workload. And, but I thought that report was pretty detailed. And Snowflake did not look great in that report. Oftentimes, and they've been marketing the heck out of it. I forget who sponsored it. It is, it was sponsored content. But, I did, I remember seeing that and thinking, hmm. So, I think maybe for Snowflake that sweet spot is not, maybe not that performance, maybe it's the simplicity and I think that's where they're making their mark. And most of their databases are small and a lot of read-only stuff. And so they've found a market there. But I want to come back to the architecture and really sort of understand how you've able, you've been able to get this range of both performance and cost you talked about. I thought I heard that you're optimizing the chips, you're using ObjectStore. You're, you've got an architecture that's not using SSD, it's using ObjectStore. So this, is their cashing there? I wonder if you could just give us some details of the architecture and tell us how you got to where you are. >> Right, so let me start off saying like, what are the kind of numbers we are talking about just to kind of be clear, like what the improvements are. So if you take the MySQL Database Service in HeatWave in Oracle Cloud and compare it with MySQL service in any other cloud, and if you look at smaller data sizes, say data sizes which are about half a terabyte or so, HeatWave is 400 times faster, 400 times faster. And as you get to... >> Sorry. Sorry to interrupt. What are you measuring there? Faster in terms of what? >> Latency. So we take TCP-H 22 queries, we run them on HeatWave, and we run the same queries on MySQL service on any other cloud, half a terabyte and the performance in terms of latency is 400 times faster in HeatWave. >> Thank you. Okay. >> If you go to a lot of other data sites, then the other data point of view, we're looking at say something like, 4 TB, there, we did two comparisons. One is with AWS Aurora, which is, as you said, they have taken MySQL. They have done a bunch of innovations over there and we are offering it as a premier service. So on 4 TB TPC-H, MySQL Database Service with HeatWave is 1100 times faster than Aurora. It is three times faster than the fastest shape of Redshift. So Redshift comes in different flavors some talking about dense compute too, right? And again, looking at the most recommended configuration from Redshift. So 1100 times faster that Aurora, three times faster than Redshift and at one third, the cost. So this where I just really want to point out that it is much faster and much cheaper. One third the cost. And then going back to the Gigaom report, there was a comparison done with Snowflake, Google BigQuery, Redshift, Azure Synapse. I wouldn't go into the numbers here but HeatWave was faster on both TPC-H as well as TPC-DS across all these products and cheaper compared to any of these products. So faster, cheaper on both the benchmarks across all these products. Now let's come to, like, what is the technology underneath? >> Great. >> So, basically there are three parts which you're going to see. One is, improve performance, very good scale, and improve a lower cost. So the first thing is that HeatWave has been optimized and, for the cloud. And when I say that, we talked about this a bit earlier. One is we are using the cheapest shapes which are available. We're using the cheapest services which are available without having to compromise the performance and then there is this machine learning-based automation. Now, underneath, in terms of the architecture of HeatWave there are basically, I would say, four key things. First is, HeatWave is an in-memory engine that a presentation which we have in memory is a hybrid columnar representation which is optimized for vector process. That's the first thing. And that's pretty table stakes these days for anyone who wants to do in-memory analytics except that it's hybrid columnar which is optimized for vector processing. So that's the first thing. The second thing which starts getting to be novel is that HeatWave has a massively parallel architecture which is enabled by a massively partitioned architecture. So we take the data, we read the data from MySQL into the memory of the HeatWave and we massively partition this data. So as we're reading the data, we're partitioning the data based on the workload, the sizes of these partitions is such that it fits in the cache of the underlying processor and then we're able to consume these partitions really, really fast. So that's the second bit which is like, massively parallel architecture enabled by massively partitioned architecture. Then the third thing is, that we have developed new state-of-art algorithms for distributed query processing. So for many of the workloads, we find that joints are the long pole in terms of the amount of time it takes. So we at Oracle have developed new algorithms for distributed joint processing and similarly for many other operators. And this is how we're being able to consume this data or process this data, which is in-memory really, really fast. And finally, and what we have, is that we have an eye for scalability and we have designed algorithms such that there's a lot of overlap between compute and communication, which means that as you're sending data across various nodes and there could be like, dozens of of nodes or 100s of nodes that they're able to overlap the computation time with the communication time and this is what gives us massive scalability in the cloud. >> Yeah, so, some hard core database techniques that you've brought to HeatWave, that's impressive. Thank you for that description. Let me ask you, just to go to quicker side. So, MySQL is open source, HeatWave is what? Is it like, open core? Is it open source? >> No, so, HeatWave is something which has been designed and optimized for the cloud. So it can't be open source. So any, it's not open service. >> It is a service. >> It is a service. That's correct. >> So it's a managed service that I pay Oracle to host for me. Okay. Got it. >> That's right. >> Okay, I wonder if you could talk about some of the use cases that you're seeing for HeatWave, any patterns that you're seeing with customers? >> Sure, so we've had the service, we had the HeatWave service in limited availability for almost 15 months and it's been about five months since we have gone G. And there's a very interesting trend of our customers we're seeing. The first one is, we are seeing many migrations from AWS specifically from Aurora. Similarly, we are seeing many migrations from Azure MySQL we're migrations from Google. And the number one reason customers are coming is because of ease of use. Because they have their databases currently siloed. As you were talking about some for optimized for transactional processing, some for analytics. Here, what customers find is that in a single database, they're able to get very good performance, they don't need to move the data around, they don't need to manage multiple databaes. So we are seeing many migrations from these services. And the number one reason is reduce complexity of ease of use. And the second one is, much better performance and reduced costs, right? So that's the first thing. We are very excited and delighted to see the number of migrations we're getting. The second thing which we're seeing is, initially, when we had the service announced, we were like, targeting really towards analytics. But now what are finding is, many of these customers, for instance, who have be running on Aurora, when they are moving from MySQL in HeatWave, they are finding that many of the OLTP queries as well, are seeing significant acceleration with the HeatWave. So now customers are moving their entire applications or, to HeatWave. So that's the second trend we're seeing. The third thing, and I think I kind of missed mentioning this earlier, one of the very key and unique value propositions we provide with the MySQL Database Service in HeatWave, is that we provide a mechanism where if customers have their data stored on premise they can still leverage the HeatWave service by enabling MySQL replication. So they can have their data on premise, they can replicate this data in the Oracle Cloud and then they can run analytics. So this deployment which we are calling the hybrid deployment is turning out to be very, very popular because there are customers, there are some customers who for various reasons, compliance or regulatory reasons cannot move the entire data to the cloud or migrate the data to the cloud completely. So this provides them a very good setup where they can continue to run their existing database and when it comes to getting benefits of HeatWave for query acceleration, they can set up this replication. >> And I can run that on anyone, any available server capacity or is there an appliance to facilitate that? >> No, this is just standard MySQL replication. So if a customer is running MySQL on premise they can just turn off this application. We have obviously enhanced it to support this inbound replication between on-premise and Oracle Cloud with something which can be enabled as long as the source and destination are both MySQL. >> Okay, so I want to come back to this sort of idea of the architecture a little bit. I mean, it's hard for me to go toe to toe with the, I'm not an engineer, but I'm going to try anyway. So you've talked about OLTP queries. I thought, I always thought HeatWave was optimized for analytics. But so, I want to push on this notion because people think of this the converged database, and what you're talking about here with HeatWave is sort of the Swiss army knife which is great 'cause you got a screwdriver and you got Phillips and a flathead and some scissors, maybe they're not as good. They're not as good necessarily as the purpose-built tool. But you're arguing that this is best of breed for OLTP and best of breed for analytics, both in terms of performance and cost. Am I getting that right or is this really a Swiss army knife where that flathead is really not as good as the big, long screwdriver that I have in my bag? >> Yes, so, you're getting it right but I did want to make a clarification. That HeatWave is definitely the accelerator for all your queries, all analytic queries and also for the long running complex transaction processing inquiries. So yes, HeatWave the uber query accelerator engine. However, when it comes to transaction processing in terms of your insert statements, delete statements, those are still all done and served by the MySQL database. So all, the transactions are still sent to the MySQL database and they're persistent there, it's the queries for which HeatWave is the accelerator. So what you said is correct. For all query acceleration, HeatWave is the engine. >> Makes sense. Okay, so if I'm a MySQL customer and I want to use HeatWave, what do I have to do? Do I have to make changes to my existing applications? You applied earlier that, no, it's just sort of plugs right in. But can you clarify that. >> Yes, there are absolutely no changes, which any MySQL or MySQL compatible application needs to make to take advantage of HeatWave. HeatWave is an in-memory accelerator and it's completely transparent to the application. So we have like, dozens and dozens of like, applications which have migrated to HeatWave, and they are seeing the same thing, similarly tools. So if you look at various tools which work for analytics like, Tableau, Looker, Oracle Analytics Cloud, all of them will work just seamlessly. And this is one of the reasons we had to do a lot of heavy lifting in the MySQL database itself. So the MySQL database engineering team was, has been very actively working on this. And one of the reasons is because we did the heavy lifting and we meet enhancements to the MySQL optimizer in the MySQL storage layer to do the integration of HeatWave in such a seamless manner. So there is absolutely no change which an application needs to make in order to leverage or benefit from HeatWave. >> You said earlier, Nipun, that you're seeing migrations from, I think you said Aurora and Google BigQuery, you might've said Redshift as well. Do you, what kind of tooling do you have to facilitate migrations? >> Right, now, there are multiple ways in which customers may want to do this, right? So the first tooling which we have is that customers, as I was talking about the replication or the inbound replication mechanism, customers can set up heat HeatWave in the Oracle Cloud and they can send the data, they can set up replication within their instances in their cloud and HeatWave. Second thing is we have various kinds of tools to like, facilitate the data migration in terms of like, fast ingestion sites. So there are a lot of such customers we are seeing who are kind of migrating and we have a plethora of like, tools and applications, in addition to like, setting up this inbound application, which is the most seamless way of getting customers started with HeatWave. >> So, I think you mentioned before, I have my notes, machine intelligence and machine learning. We've seen that with autonomous database it's a big, big deal obviously. How does HeatWave take advantage of machine intelligence and machine learning? >> Yeah, and I'm probably going to be talking more about this in the future, but what we have already is that HeatWave uses machine learning to intelligently automate many operations. So we know that when there's a service being offered in the cloud, our customers expect automation. And there're a lot of vendors and a lot of services which do a good job in automation. One of the places where we're going to be very unique is that HeatWave uses machine learning to automate many of these operations. And I'll give you one such example which is provisioning. Right now with HeatWave, when a customer wants to determine how many nodes are needed for running their workload, they don't need to make a guess. They invoke a provisioning advisor and this advisor uses machine learning to sample a very small percentage of the data. We're talking about, like, 0.1% sampling and it's able to predict the amount of memory with 95% accuracy, which this data is going to take. And based on that, it's able to make a prediction of how many servers are needed. So just a simple operation, the first step of provisioning, this is something which is done manually across, on any of the service, whereas at HeatWave, we have machine learning-based advisor. So this is an example of what we're doing. And in the future, we'll be offering many such innovations as a part of the MySQL Database and the HeatWave service. >> Well, I've got to say I was skeptic but I really appreciate it, you're, answering my questions. And, a lot of people when you made the acquisition and inherited MySQL, thought you were going to kill it because they thought it would be competitive to Oracle Database. I'm happy to see that you've invested and figured out a way to, hey, we can serve our community and continue to be the steward of MySQL. So Nipun, thanks very much for coming to the CUBE. Appreciate your time. >> Sure. Thank you so much for the time, Dave. I appreciate it. >> And thank you for watching everybody. This is Dave Vellante with another CUBE Conversation. We'll see you next time. (bright upbeat music)

>> Hello. My name is Ron Kafka, and I'm the senior director for Partner Scale Initiatives for HBE Ezmeral. Thanks for joining us today at Analytics Unleashed. By now, you've heard a lot about the Ezmeral portfolio and how it can help you accomplish objectives around big data analytics and containerization. I want to shift gears a bit and then discuss our Ezmeral Technology Partner Program. I've got two great guest speakers here with me today. And together, We're going to discuss how jointly we are solving data analytic challenges for our customers. Before I introduce them, I want to take a minute to talk to provide a little bit more insight into our ecosystem program. We've created a program with a realization based on customer feedback that even the most mature organizations are struggling with their data-driven transformation efforts. It turns out this is largely due to the pace of innovation with application vendors or ICS supporting data science and advanced analytic workloads. Their advancements are simply outpacing organization's ability to move workloads into production rapidly. Bottom line, organizations want a unified experience across environments where their entire application portfolio in essence provide a comprehensive application stack and not piece parts. So, let's talk about how our ecosystem program helps solve for this. For starters, we were leveraging HPEs long track record of forging technology partnerships and it created a best in class ISB partner program specific for the Ezmeral portfolio. We were doing this by developing an open concept marketplace where customers and partners can explore, learn, engage and collaborate with our strategic technology partners. This enables our customers to adopt, deploy validated applications from industry leading software vendors on HPE Ezmeral with a high degree of confidence. Also, it provides a very deep bench of leading ISVs for other groups inside of HPE to leverage for their solutioning efforts. Speaking of industry leading ISV, it's about time and introduce you to two of those industry leaders right now. Let me welcome Daniel Hladky from Dataiku, and Omri Geller from Run:AI. So I'd like to introduce Daniel Hladky. Daniel is with Dataiku. He's a great partner for HPE. Daniel, welcome. >> Thank you for having me here. >> That's great. Hey, would you mind just talking a bit about how your partnership journey has been with HPE? >> Yes, pleasure. So the journey started about five years ago and in 2018 we signed a worldwide reseller agreement with HPE. And in 2020, we actually started to work jointly on the integration between the Dataiku Data Science Studio called DSS and integrated that with the Ezmeral Container platform, and was a great success. And it was on behalf of some clear customer projects. >> It's been a long partnership journey with you for sure with HPE. And we welcome your partnership extremely well. Just a brief question about the Container Platform and really what that's meant for Dataiku. >> Yes, Ron. Thanks. So, basically I'd like the quote here Florian Douetteau, which is the CEO of Dataiku, who said that the combination of Dataiku with the HPE Ezmeral Container Platform will help the customers to successfully scale and put machine learning projects into production. And this basically is going to deliver real impact for their business. So, the combination of the two of us is a great success. >> That's great. Can you talk about what Dataiku is doing and how HPE Ezmeral Container Platform fits in a solution offering a bit more? >> Great. So basically Dataiku DSS is our product which is a end to end data science platform, and basically brings value to the project of customers on their past enterprise AI. In simple ways, we can say it could be as simple as building data pipelines, but it could be also very complex by having machine and deep learning models at scale. So the fast track to value is by having collaboration, orchestration online technologies and the models in production. So, all of that is part of the Data Science Studio and Ezmeral fits perfectly into the part where we design and then basically put at scale those project and put it into product. >> That's perfect. Can you be a bit more specific about how you see HPE and Dataiku really tightening up a customer outcome and value proposition? >> Yes. So what we see is also the challenge of the market that probably about 80% of the use cases really never make it to production. And this is of course a big challenge and we need to change that. And I think the combination of the two of us is actually addressing exactly this need. What we can say is part of the MLOps approach, Dataiku and the Ezmeral Container Platform will provide a frictionless approach, which means without scripting and coding, customers can put all those projects into the productive environment and don't have to worry any more and be more business oriented. >> That's great. So you mentioned you're seeing customers be a lot more mature with their AI workloads and deployment. What do you suggest for the other customers out there that are just starting this journey or just thinking about how to get started? >> Yeah. That's a very good question, Ron. So what we see there is actually the challenge that people need to go on a pass of maturity. And this starts with a simple data pipelines, et cetera, and then basically move up the ladder and basically build large complex project. And here I see a very interesting offer coming now from HPE which is called D3S, which is the data science startup pack. That's something I discussed together with HPE back in early 2020. And basically, it solves the three stages, which is explore, experiment and evolve and builds quickly MVPs for the customers. By doing so, basically you addressed business objectives, lay out in the proper architecture and also setting up the proper organization around it. So, this is a great combination by HPE and Dataiku through the D3S. >> And it's a perfect example of what I mentioned earlier about leveraging the ecosystem program that we built to do deeper solutioning efforts inside of HPE in this case with our AI business unit. So, congratulations on that and thanks for joining us today. I'm going to shift gears. I'm going to bring in Omri Geller from Run:AI. Omri, welcome. It's great to have you. You guys are killing it out there in the market today. And I just thought we could spend a few minutes talking about what is so unique and differentiated from your offerings. >> Thank you, Ron. It's a pleasure to be here. Run:AI creates a virtualization and orchestration layer for AI infrastructure. We help organizations to gain visibility and control over their GPO resources and help them deliver AI solutions to market faster. And we do that by managing granular scheduling, prioritization, allocation of compute power, together with the HPE Ezmeral Container Platform. >> That's great. And your partnership with HPE is a bit newer than Daniel's, right? Maybe about the last year or so we've been working together a lot more closely. Can you just talk about the HPE partnership, what it's meant for you and how do you see it impacting your business? >> Sure. First of all, Run:AI is excited to partner with HPE Ezmeral Container Platform and help customers manage appeals for their AI workloads. We chose HPE since HPE has years of experience partnering with AI use cases and outcomes with vendors who have strong footprint in this markets. HPE works with many partners that are complimentary for our use case such as Nvidia, and HPE Container Platform together with Run:AI and Nvidia deliver a world class solutions for AI accelerated workloads. And as you can understand, for AI speed is critical. Companies want to gather important AI initiatives into production as soon as they can. And the HPE Ezmeral Container Platform, running IGP orchestration solution enables that by enabling dynamic provisioning of GPU so that resources can be easily shared, efficiently orchestrated and optimal used. >> That's great. And you talked a lot about the efficiency of the solution. What about from a customer perspective? What is the real benefit that our customers are going to be able to gain from an HPE and Run:AI offering? >> So first, it is important to understand how data scientists and AI researchers actually build solution. They do it by running experiments. And if a data scientist is able to run more experiments per given time, they will get to the solution faster. With HPE Ezmeral Container Platform, Run:AI and users such as data scientists can actually do that and seamlessly and efficiently consume large amounts of GPU resources, run more experiments or given time and therefore accelerate their research. Together, we actually saw a customer that is running almost 7,000 jobs in parallel over GPUs with efficient utilization of those GPUs. And by running more experiments, those customers can be much more effective and efficient when it comes to bringing solutions to market >> Couldn't agree more. And I think we're starting to see a lot of joint success together as we go out and talk to the story. Hey, I want to thank you both one last time for being here with me today. It was very enlightening for our team to have you as part of the program. And I'm excited to extend this customer value proposition out to the rest of our communities. With that, I'd like to close today's session. I appreciate everyone's time. And keep an eye out on our ISP marketplace for Ezmeral We're continuing to expand and add new capabilities and new partners to our marketplace. We're excited to do a lot of great things and help you guys all be successful. Thanks for joining. >> Thank you, Ron. >> What a great panel discussion. And these partners they really do have a good understanding of the possibilities, working on the platform, and I hope and expect we'll see this ecosystem continue to grow. That concludes the main program, which means you can now pick one of three live demos to attend and chat live with experts. Now those three include day in the life of IT Admin, day in the life of a data scientist, and even a day in the life of the HPE Ezmeral Data Fabric, where you can see the many ways the data fabric is used in your life today. Wish you could attend all three, no worries. The recordings will be available on demand for you and your teams. Moreover, the show doesn't stop here, HPE has a growing and thriving tech community, you should check it out. It's really a solid starting point for learning more, talking to smart people about great ideas and seeing how Ezmeral can be part of your own data journey. Again, thanks very much to all of you for joining, until next time, keep unleashing the power of your data.

>> Hello. My name is Ron Kafka, and I'm the senior director for Partner Scale Initiatives for HBE Ezmeral. Thanks for joining us today at Analytics Unleashed. By now, you've heard a lot about the Ezmeral portfolio and how it can help you accomplish objectives around big data analytics and containerization. I want to shift gears a bit and then discuss our Ezmeral Technology Partner Program. I've got two great guest speakers here with me today. And together, We're going to discuss how jointly we are solving data analytic challenges for our customers. Before I introduce them, I want to take a minute to talk to provide a little bit more insight into our ecosystem program. We've created a program with a realization based on customer feedback that even the most mature organizations are struggling with their data-driven transformation efforts. It turns out this is largely due to the pace of innovation with application vendors or ICS supporting data science and advanced analytic workloads. Their advancements are simply outpacing organization's ability to move workloads into production rapidly. Bottom line, organizations want a unified experience across environments where their entire application portfolio in essence provide a comprehensive application stack and not piece parts. So, let's talk about how our ecosystem program helps solve for this. For starters, we were leveraging HPEs long track record of forging technology partnerships and it created a best in class ISB partner program specific for the Ezmeral portfolio. We were doing this by developing an open concept marketplace where customers and partners can explore, learn, engage and collaborate with our strategic technology partners. This enables our customers to adopt, deploy validated applications from industry leading software vendors on HPE Ezmeral with a high degree of confidence. Also, it provides a very deep bench of leading ISVs for other groups inside of HPE to leverage for their solutioning efforts. Speaking of industry leading ISV, it's about time and introduce you to two of those industry leaders right now. Let me welcome Daniel Hladky from Dataiku, and Omri Geller from Run:AI. So I'd like to introduce Daniel Hladky. Daniel is with Dataiku. He's a great partner for HPE. Daniel, welcome. >> Thank you for having me here. >> That's great. Hey, would you mind just talking a bit about how your partnership journey has been with HPE? >> Yes, pleasure. So the journey started about five years ago and in 2018 we signed a worldwide reseller agreement with HPE. And in 2020, we actually started to work jointly on the integration between the Dataiku Data Science Studio called DSS and integrated that with the Ezmeral Container platform, and was a great success. And it was on behalf of some clear customer projects. >> It's been a long partnership journey with you for sure with HPE. And we welcome your partnership extremely well. Just a brief question about the Container Platform and really what that's meant for Dataiku. >> Yes, Ron. Thanks. So, basically I like the quote here Florian Douetteau, which is the CEO of Dataiku, who said that the combination of Dataiku with the HPE Ezmeral Container Platform will help the customers to successfully scale and put machine learning projects into production. And this basically is going to deliver real impact for their business. So, the combination of the two of us is a great success. >> That's great. Can you talk about what Dataiku is doing and how HPE Ezmeral Container Platform fits in a solution offering a bit more? >> Great. So basically Dataiku DSS is our product which is a end to end data science platform, and basically brings value to the project of customers on their past enterprise AI. In simple ways, we can say it could be as simple as building data pipelines, but it could be also very complex by having machine and deep learning models at scale. So the fast track to value is by having collaboration, orchestration online technologies and the models in production. So, all of that is part of the Data Science Studio and Ezmeral fits perfectly into the part where we design and then basically put at scale those project and put it into product. >> That's perfect. Can you be a bit more specific about how you see HPE and Dataiku really tightening up a customer outcome and value proposition? >> Yes. So what we see is also the challenge of the market that probably about 80% of the use cases really never make it to production. And this is of course a big challenge and we need to change that. And I think the combination of the two of us is actually addressing exactly this need. What we can say is part of the MLOps approach, Dataiku and the Ezmeral Container Platform will provide a frictionless approach, which means without scripting and coding, customers can put all those projects into the productive environment and don't have to worry any more and be more business oriented. >> That's great. So you mentioned you're seeing customers be a lot more mature with their AI workloads and deployment. What do you suggest for the other customers out there that are just starting this journey or just thinking about how to get started? >> Yeah. That's a very good question, Ron. So what we see there is actually the challenge that people need to go on a pass of maturity. And this starts with a simple data pipelines, et cetera, and then basically move up the ladder and basically build large complex project. And here I see a very interesting offer coming now from HPE which is called D3S, which is the data science startup pack. That's something I discussed together with HPE back in early 2020. And basically, it solves the three stages, which is explore, experiment and evolve and builds quickly MVPs for the customers. By doing so, basically you addressed business objectives, lay out in the proper architecture and also setting up the proper organization around it. So, this is a great combination by HPE and Dataiku through the D3S. >> And it's a perfect example of what I mentioned earlier about leveraging the ecosystem program that we built to do deeper solutioning efforts inside of HPE in this case with our AI business unit. So, congratulations on that and thanks for joining us today. I'm going to shift gears. I'm going to bring in Omri Geller from Run:AI. Omri, welcome. It's great to have you. You guys are killing it out there in the market today. And I just thought we could spend a few minutes talking about what is so unique and differentiated from your offerings. >> Thank you, Ron. It's a pleasure to be here. Run:AI creates a virtualization and orchestration layer for AI infrastructure. We help organizations to gain visibility and control over their GPO resources and help them deliver AI solutions to market faster. And we do that by managing granular scheduling, prioritization, allocation of compute power, together with the HPE Ezmeral Container Platform. >> That's great. And your partnership with HPE is a bit newer than Daniel's, right? Maybe about the last year or so we've been working together a lot more closely. Can you just talk about the HPE partnership, what it's meant for you and how do you see it impacting your business? >> Sure. First of all, Run:AI is excited to partner with HPE Ezmeral Container Platform and help customers manage appeals for their AI workloads. We chose HPE since HPE has years of experience partnering with AI use cases and outcomes with vendors who have strong footprint in this markets. HPE works with many partners that are complimentary for our use case such as Nvidia, and HPE Ezmeral Container Platform together with Run:AI and Nvidia deliver a word about solution for AI accelerated workloads. And as you can understand, for AI speed is critical. Companies want to gather important AI initiatives into production as soon as they can. And the HPE Ezmeral Container Platform, running IGP orchestration solution enables that by enabling dynamic provisioning of GPU so that resources can be easily shared, efficiently orchestrated and optimal used. >> That's great. And you talked a lot about the efficiency of the solution. What about from a customer perspective? What is the real benefit that our customers are going to be able to gain from an HPE and Run:AI offering? >> So first, it is important to understand how data scientists and AI researchers actually build solution. They do it by running experiments. And if a data scientist is able to run more experiments per given time, they will get to the solution faster. With HPE Ezmeral Container Platform, Run:AI and users such as data scientists can actually do that and seamlessly and efficiently consume large amounts of GPU resources, run more experiments or given time and therefore accelerate their research. Together, we actually saw a customer that is running almost 7,000 jobs in parallel over GPUs with efficient utilization of those GPUs. And by running more experiments, those customers can be much more effective and efficient when it comes to bringing solutions to market >> Couldn't agree more. And I think we're starting to see a lot of joint success together as we go out and talk to the story. Hey, I want to thank you both one last time for being here with me today. It was very enlightening for our team to have you as part of the program. And I'm excited to extend this customer value proposition out to the rest of our communities. With that, I'd like to close today's session. I appreciate everyone's time. And keep an eye out on our ISP marketplace for Ezmeral We're continuing to expand and add new capabilities and new partners to our marketplace. We're excited to do a lot of great things and help you guys all be successful. Thanks for joining. >> Thank you, Ron. (bright upbeat music)

>>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to cube three 60 fives coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight. Today we are joined by a cube alum Karthik NurAin. He is Accenture senior managing director and lead Accenture cloud. First, welcome back to the show Karthik. >>Thank you. Thanks for having me here. >>Always a pleasure. So I want to talk to you. You are an industry veteran, you've been in Silicon Valley for decades. Um, I want to hear from your perspective what the impact of the COVID-19 pandemic has been, what are you hearing from clients? What are they struggling with? What are their challenges that they're facing day to day? >>I think, um, COVID-19 is being a eye-opener from, you know, various facets, you know, um, first and foremost, it's a, it's a head, um, situation that everybody's facing, which is not just, uh, highest economic bearings to it. It has enterprise, um, an organization with bedding to it. And most importantly, it's very personal to people, um, because they themselves and their friends, family near and dear ones are going to this challenge, uh, from various different dimension. But putting that aside, when you come to it from an organization enterprise standpoint, it has changed everything well, the behavior of organizations coming together, working in their campuses, working with each other as friends, family, and, uh, um, near and dear colleagues, all of them are operating differently. So that's what big change to get things done in a completely different way, from how they used to get things done. >>Number two, a lot of things that were planned for normal scenarios, like their global supply chain, how they interact with their client customers, how they coordinate with their partners on how that employees contribute to the success of an organization at all changed. And there are no data models that give them a hint of something like this for them to be prepared for this. So we are seeing organizations, um, that have adapted to this reasonably okay, and are, you know, launching to innovate faster in this. And there are organizations that have started with struggling, but are continuing to struggle. And the gap, uh, between the leaders and legs are widening. So this is creating opportunities in a different way for the leaders, um, with a lot of pivot their business, but it's also creating significant challenge for the lag guides, uh, as we defined in our future systems research that we did a year ago, uh, and those organizations are struggling further. So the gap is actually whitening. >>So you've just talked about the widening gap. I've talked about the tremendous uncertainty that so many companies, even the ones who have adapted reasonably well, uh, in this, in this time, talk a little bit about Accenture cloud first and why, why now? >>I think it's a great question. Um, we believe that for many of our clients COVID-19 has turned, uh, cloud from an experimentation aspiration to an origin mandate. What I mean by that is everybody has been doing something on the other end cloud. There's no company that says we don't believe in cloud. Uh, our, we don't want to do cloud. It was how much they did in cloud. And they were experimenting. They were doing the new things in cloud. Um, but they were operating a lot of their core business outside the cloud or not in the cloud. Those organizations have struggled to operate in this new normal, in a remote fashion as with us, uh, that ability to pivot to all the changes the pandemic has brought to them. But on the other hand, the organizations that had a solid foundation in cloud were able to collect faster and not actually gone into the stage of innovating faster and driving a new behavior in the market, new behavior within their organization. >>So we are seeing that spend to make is actually fast-forwarded something that we always believed was going to happen. This, uh, uh, moving to cloud over the next decade is fast, forwarded it to, uh, happen in the next three to five years. And it's created this moment where it's a once in an era, really replatforming of businesses in the cloud that we are going to see. And we see this moment as a cloud first moment where organizations will use cloud as the, the canvas and the foundation with which they're going to reimagine their business after they were born in the cloud. Uh, and this requires a whole new strategy. Uh, and as Accenture, we are getting a lot in cloud, but we thought that this is the moment where we bring all of that capabilities together because we need a strategy for addressing, moving to cloud are embracing cloud in a holistic fashion. And that's what Accenture cloud first brings together a holistic strategy, a team that's 70,000 plus people that's coming together with rich cloud skills, but investing to tie in all the various capabilities of cloud to Delaware, that holistic strategy to our clients. So I want you to >>Delve into a little bit more about what this strategy actually entails. I mean, it's clearly about embracing change and being willing to experiment and, and having capabilities to innovate. Can you tell us a little bit more about what this strategy entails? >>Yeah. The reason why we say that there's a need for the strategy is, like I said, COVID is not new. There's almost every customer client is doing something with the cloud, but all of them have taken different approaches to cloud and different boundaries to cloud. Some organizations say, I just need to consolidate my multiple data centers to a small data center footprint and move the nest to cloud. Certain other organizations say that well, I'm going to move certain workloads to cloud. Certain other organizations said, well, I'm going to build this Greenfield application or workload in cloud. Certain other said, um, I'm going to use the power of AI ML in the cloud to analyze my data and drive insights. But a cloud first strategy is all of this tied with the corporate strategy of the organization with an industry specific cloud journey to say, if in this current industry, if I were to be reborn in the cloud, would I do it in the exact same passion that I did in the past, which means that the products and services that they offer need to be the matching, how they interact with that customers and partners need to be revisited, how they bird and operate their IP systems need to be the, imagine how they unearthed the data from all the systems under which they attract need to be liberated so that you could drive insights of cloud. >>First strategy. Hans is a corporate wide strategy, and it's a C-suite responsibility. It doesn't take the ownership away from the CIO or CIO, but the CIO is, and CDI was felt that it was just their problem and they were to solve it. And everyone as being a customer, now, the center of gravity is elevated to it becoming a C-suite agenda on everybody's agenda, where probably the CDI is the instrument to execute that that's a holistic cloud-first strategy >>And it, and it's a strategy, but the way you're describing it, it sounds like it's also a mindset and an approach, as you were saying, this idea of being reborn in the cloud. So now how do I think about things? How do I communicate? How do I collaborate? How do I get done? What I need to get done. Talk a little bit about how this has changed, the way you support your clients and how Accenture cloud first is changing your approach to cloud services. >>Wonderful. Um, you know, I did not color one very important aspect in my previous question, but that's exactly what you just asked me now, which is to do all of this. I talked about all of the vehicles, uh, an organization or an enterprise is going to go to, but the good part is they have one constant. And what is that? That is their employees, uh, because you do, the employees are able to embrace this change. If they are able to, uh, change them, says, pivot them says retool and train themselves to be able to operate in this new cloud. First one, the ability to reimagine every function of the business would be happening at speed. And cloud first approach is to do all of this at speed, because innovation is deadly proposed there, do the rate of probability on experimentation. You need to experiment a lot for any kind of experimentation. >>There's a probability of success. Organizations need to have an ability and a mechanism for them to be able to innovate faster for which they need to experiment a lot. The more the experiment and the lower cost at which they experiment is going to help them experiment a lot and experiment demic speed, fail fast, succeed more. And hence, they're going to be able to operate this at speed. So the cloud-first mindset is all about speed. I'm helping the clients fast track that innovation journey, and this is going to happen. Like I said, across the enterprise and every function across every department, I'm the agent of this change is going to be the employee's weapon, race, this change through new skills and new grueling and new mindset that they need to adapt to. >>So Karthik what you're describing it, it sounds so exciting. And yet for a pandemic wary workforce, that's been working remotely that may be dealing with uncertainty if for their kid's school and for so many other aspects of their life, it sounds hard. So how are you helping your clients, employees get onboard with this? And because the change management is, is often the hardest part. >>Yeah, I think it's, again, a great question. A bottle has only so much capacity. Something got to come off for something else to go in. That's what you're saying is absolutely right. And that is again, the power of cloud. The reason why cloud is such a fundamental breakthrough technology and capability for us to succeed in this era, because it helps in various forms. What we talked so far is the power of innovation that could create, but cloud can also simplify the life of the employees in an enterprise. There are several activities and tasks that people do in managing their complex infrastructure, complex ID landscape. They used to do certain jobs and activities in a very difficult, uh, underground about with cloud has simplified. And democratised a lot of these activities. So that things which had to be done in the past, like managing the complexity of the infrastructure, keeping them up all the time, managing the, um, the obsolescence of the capabilities and technologies and infrastructure, all of that could be offloaded to the cloud. >>So that the time that is available for all of these employees can be used to further innovate. Every organization is good to spend almost the same amount of money, but rather than spending activities, by looking at the rear view mirror on keeping the lights on, they're going to spend more money, more time, more energy, and spend their skills on things that are going to add value to their organization. Because you, every innovation that an enterprise can give to their end customer need not come from that enterprise. The word of platform economy is about democratising innovation. And the power of cloud is to get all of these capabilities from outside the four walls of the enterprise, >>It will add value to the organization, but I would imagine also add value to that employee's life because that employee, the employee will be more engaged in his or her job and therefore bring more excitement and energy into her, his or her day-to-day activities too. >>Absolutely. Absolutely. And this is, this is a normal evolution we would have seen everybody would have seen in their lives, that they keep moving up the value chain of what activities that, uh, gets performed buying by those individuals. And there's this, um, you know, no more true than how the United States, uh, as an economy has operated where, um, this is the power of a powerhouse of innovation, where the work that's done inside the country keeps moving up to that. You change. And, um, us leverages the global economy for a lot of things that is required to power the United States and that global economic, uh, phenomenon is very proof for an enterprise as well. There are things that an enterprise needs to do them soon. There are things an employee needs to do themselves. Um, but there are things that they could leverage from the external innovation and the power of innovation that is coming from technologies like cloud. >>So at Accenture, you have long, long, deep Stan, sorry, you have deep and long standing relationships with many cloud service providers, including AWS. How does the Accenture cloud first strategy, how does it affect your relationships with those providers? >>Yeah, we have great relationships with cloud providers like AWS. And in fact, in the cloud world, it was one of the first, um, capability that we started about years ago, uh, when we started developing these capabilities. But five years ago, we hit a very important milestone where the two organizations came together and said that we are forging a pharma partnership with joint investments to build this partnership. And we named that as a Accenture, AWS business group ABG, uh, where we co-invest and brought skills together and develop solutions. And we will continue to do that. And through that investment, we've also made several acquisitions that you would have seen in the recent times, like, uh, an invoice and gecko that we made acquisitions in in Europe. But now we're taking this to the next level. What we are saying is two cloud first and the $3 billion investment that we are bringing in, uh, through cloud first, we are going to make specific investment to create unique joint solution and landing zones foundation, um, cloud packs with which clients can accelerate their innovation or their journey to cloud first. >>And one great example is what we are doing with Takeda, uh, billable, pharmaceutical giant, um, between we've signed a five-year partnership. And it was out in the media just a month ago or so, where we are, the two organizations are coming together. We have created a partnership as a power of three partnership where the three organizations are jointly hoarding hats and taking responsibility for the innovation and the leadership position that Decatur wants to get to with this. We are going to simplify their operating model and organization by providing it flexibility. We're going to provide a lot more insights. Tequila has a 230 year old organization. Imagine the amount of trapped data and intelligence that is there. How about bringing all of that together with the power of AWS and Accenture and Takeda to drive more customer insights, um, come up with breakthrough, uh, R and D uh, accelerate clinical trials and improve the patient experience using AI ML and edge technologies. So all of these things that we will do through this partnership with joint investment from Accenture cloud first, as well as partner like AWS, so that Takeda can realize their gain. And, uh, they're seeing you actually made a statement that five years from now, every ticket an employee will have an AI assistant. That's going to make that beginner employee move up the value chain on how they contribute and add value to the future of tequila with the AI assistant, making them even more equipped and smarter than what they could be otherwise. >>So, one last question to close this out here. What is your future vision for, for Accenture cloud first? What are we going to be talking about at next year's Accenture executive summit? Yeah, the future >>Is going to be, um, evolving, but the part that is exciting to me, and this is, uh, uh, a fundamental belief that we are entering a new era of industrial revolution from industry first, second, and third industry. The third happened probably 20 years ago with the advent of Silicon and computers and all of that stuff that happened here in the Silicon Valley. I think the fourth industrial revolution is going to be in the cross section of, uh, physical, digital and biological boundaries. And there's a great article, um, in what economic forum that, that people, uh, your audience can Google and read about it. Uh, but the reason why this is very, very important is we are seeing a disturbing phenomenon that over the last 10 years, they are seeing a Blackwing of the, um, labor productivity and innovation, which has dropped to about 2.1%. When you see that kind of phenomenon over that longer period of time, there has to be breakthrough innovation that needs to happen to come out of this barrier and get to the next base camp, as I would call it to further this productivity, um, lack that we are seeing, and that is going to happen in the intersection of the physical, digital and biological boundaries. >>And I think cloud is going to be the connective tissue between all of these three, to be able to provide that where it's the edge, especially is going to come closer to the human lives. It's going to come from cloud pick totally in your mind, you can think about cloud as central, either in a private cloud, in a data center or in a public cloud, you know, everywhere. But when you think about edge, it's going to be far reaching and coming close to where we live and maybe work and very, um, get entertained and so on and so forth. And there's going to be, uh, intervention in a positive way in the field of medicine, in the field of entertainment, in the field of, um, manufacturing in the field of, um, uh, you know, mobility. When I say mobility, human mobility, people, transportation, and so on and so forth with all of this stuff, cloud is going to be the connective tissue and the vision of cloud first is going to be, uh, you know, blowing through this big change that is going to happen. And the evolution that is going to happen where, you know, the human grace of mankind, um, our person kind of being very gender neutral in today's world. Um, go first needs to be that beacon of, uh, creating the next generation vision for enterprises to take advantage of that kind of an exciting future. And that's why it, Accenture. We say, let there be change as our, as a purpose. >>I genuinely believe that cloud first is going to be in the forefront of that change agenda, both for Accenture as well as for the rest of the world. Excellent. Let there be change, indeed. Thank you so much for joining us Karthik. A pleasure I'm Rebecca night's stay tuned for more of Q3 60 fives coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS >>Welcome everyone to the Q virtual and our coverage of the Accenture executive summit, which is part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the green, the cloud and joining me is Kishor Dirk. He is Accenture senior managing director cloud first global services lead. Thank you so much for coming on the show. Kishor nice to meet you. So I want to start by asking you what it is that we mean when we say green cloud, we know that sustainability is a business imperative. So many organizations around the world are committing to responsible innovation, lowering carbon emissions, but what's this, what is it? What does it mean when they talk about cloud from a sustainability perspective? I think it's about responsible innovation being cloud is a cloud first approach that has profits and benefit the clients by helping reduce carbon emissions. >>Think about it this way. You have a large number of data centers. Each of these data centers are increasing by 14% every year. And this double digit growth. What you're seeing is these data centers and the consumption is nearly coolant to the kind of them should have a country like Spain. So the magnitude of the problem that is out there and how do we pursue a green approach. If you look at this, our Accenture analysis, in terms of the migration to public cloud, we've seen that we can reduce that by 59 million tons of CO2 per year with just the 5.9% reduction in total ID emissions and equates this to 22 million cars off the road. And the magnitude of reduction can go a long way in meeting climate change commitments, particularly for data sensitive. >>Wow, that's incredible. What the numbers that you're putting forward are, are absolutely mind blowing. So how does it work? Is it a simple cloud migration? So, you know, when companies begin their cloud journey and then they confront, uh, with them a lot of questions, the decision to make, uh, this particular, uh, element sustainable in the solution and benefits they drive and they have to make wise choices, and then they will be unprecedented level of innovation leading to both a greener planet, as well as, uh, a greener balance sheet, I would say, uh, so effectively it's all about ambition data, the ambition, greater the reduction in carbon emissions. So from a cloud migration perspective, we look at it as a, as a simple solution with approaches and sustainability benefits, uh, that vary based on things it's about selecting the right cloud provider, a very carbon thoughtful provider and the first step towards a sustainable cloud journey. >>And here we're looking at cloud operators, obviously they have different corporate commitments towards sustainability, and that determines how they plan, how they build, uh, their, uh, uh, the data centers, how they are consumed and assumptions that operate there and how they, or they retire their data centers. Then, uh, the next element that you want to do is how do you build it ambition, you know, for some of the companies, uh, and average on-prem, uh, drives about 65% energy reduction and the carbon emissions and reduction number was 84%, which is kind of good, I would say. But then if you could go up to 98% by configuring applications to the cloud, that is significant benefit for, uh, for the board. And obviously it's a, a greener cloud that we're talking about. And then the question is, how far can you go? And, uh, you know, the, obviously the companies have to unlock greater financial societal environmental benefits, and Accenture has this cloud based circular operations and sustainable products and services that we bring into play. So it's a, it's a very thoughtful, broader approach that w bringing in, in terms of, uh, just a simple concept of cloud migration, >>We know that in the COVID era, shifting to the cloud has really become a business imperative. How is Accenture working with its clients at a time when all of this movement has been accelerated? How do you partner and what is your approach in terms of helping them with their migration? >>Yeah, I mean, let, let me talk a little bit about the pandemic and the crisis that is there today. And if you really look at that in terms of how we partnered with a lot of our clients in terms of the cloud first approach, I'll give you a couple of examples. We worked with rolls Royce, McLaren, DHL, and others, as part of the ventilator challenge consortium, again, to, uh, coordinate production of medical ventilator surgically needed for the UK health service. Many of these farms I've taken similar initiatives in, in terms of, uh, you know, from a few manufacturers hand sanitizers and to hand sanitizers, and again, leading passionate labels, making PPE, and again, at the UN general assembly, we launched the end-to-end integration guide that helps company essentially to have a sustainable development goals. And that's how we have parking at a very large scale. >>Uh, and, and if you really look at how we work with our clients and what is Accenture's role there, uh, you know, from, in terms of our clients, you know, there are multiple steps that we look at. One is about, uh, planning, building, deploying, and managing an optimal green cloud solution. And Accenture has this concept of, uh, helping clients with a platform to kind of achieve that goal. And here we are having, we are having a platform or a mine app, which has a module called BGR advisor. And this is a capability that helps you provide optimal green cloud, uh, you know, a business case, and obviously a blueprint for each of our clients and right from the start in terms of how do we complete cloud migration recommendation to an improved solution, accurate accuracy to obviously bringing in the end to end perspective, uh, you know, with this green card advisor capability, we're helping our clients capture what we call as a carbon footprint for existing data centers and provide, uh, I would say the current cloud CO2 emission score that, you know, obviously helps them, uh, with carbon credits that can further that green agenda. >>So essentially this is about recommending a green index score, reducing carbon footprint for migration migrating for green cloud. And if we look at how Accenture itself is practicing what we preach, 95% of our applications are in the cloud. And this migration has helped us, uh, to lead to about $14.5 million in benefit. And in the third year and another 3 million analytics costs that are saved through right-sizing a service consumption. So it's a very broad umbrella and a footprint in terms of how we engage societaly with the UN or our clients. And what is it that we exactly bring to our clients in solving a specific problem? >>Accenture isn't is walking the walk, as you say yes. >>So that's that instead of it, we practice what we preach, and that is something that we take it to heart. We want to have a responsible business and we want to practice it. And we want to advise our clients around that >>You are your own use case. And so they can, they know they can take your advice. So talk a little bit about, um, the global, the cooperation that's needed. We know that conquering this pandemic is going to take a coordinated global effort and talk a little bit about the great reset initiative. First of all, what is that? Why don't we, why don't we start there and then we can delve into it a little bit more. >>Okay. So before we get to how we are cooperating, the great reset, uh, initiative is about improving the state of the world. And it's about a group of global stakeholders cooperating to simultaneously manage the direct consequences of their COVID-19 crisis. Uh, and in spirit of this cooperation that we're seeing during COVID-19, uh, which will obviously either to post pandemic, to tackle the world's pressing issues. As I say, uh, we are increasing companies to realize a combined potential of technology and sustainable impact to use enterprise solutions, to address with urgency and scale, and, um, obviously, uh, multiple challenges that are facing our world. One of the ways that you're increasing, uh, companies to reach their readiness cloud with Accenture's cloud core strategy is to build a solid foundation that is resilient and will be able to faster to the current, as well as future times. Now, when you think of cloud as the foundation, uh, that drives the digital transformation, it's about scale speed, streamlining your operations, and obviously reducing costs. >>And as these businesses seize the construct of cloud first, they must remain obviously responsible and trusted. Now think about this, right, as part of our analysis, uh, that profitability can co-exist with responsible and sustainable practices. Let's say that all the data centers, uh, migrated from on-prem to cloud based, we estimate that would reduce carbon emissions globally by 60 million tons per year. Uh, and think about it this way, right? Easier metric would be taking out 22 million cars off the road. Um, the other examples that you've seen, right, in terms of the NHS work that they're doing, uh, in, in UK to build, uh, uh, you know, uh, Microsoft teams in based integration. And, uh, the platform rolled out for 1.2 million in interest users, uh, and got 16,000 users that we were able to secure, uh, instant messages, obviously complete audio video calls and host virtual meetings across India. So, uh, this, this work that we did with NHS is something that we have are collaborating with a lot of tools and powering businesses. >>Well, you're vividly describing the business case for sustainability. What do you see as the future of cloud when thinking about it from this lens of sustainability, and also going back to what you were talking about in terms of how you are helping your, your fostering cooperation within these organizations. >>Yeah, that's a very good question. So if you look at today, right, businesses are obviously environmentally aware and they are expanding efforts to decrease power consumption, carbon emissions, and they want to run a sustainable operational efficiency across all elements of their business. And this is an increasing trend, and there is that option of energy efficient infrastructure in the global market. And this trend is the cloud first thinking. And with the right cloud migration that we've been discussing is about unlocking new opportunity, like clean energy foundations enable enabled by cloud based geographic analysis, material, waste reductions, and better data insights. And this is something that, uh, uh, we'll we'll drive, uh, with obviously faster analytics platform that is out there. Now, the sustainability is actually the future of business, which is companies that are historically different, the financial security or agility benefits to cloud. Now sustainability becomes an imperative for them. And I would on expedience Accenture's experience with cloud migrations, we have seen 30 to 40% total cost of ownership savings. And it's driving a greater workload, flexibility, better service, your obligation, and obviously more energy efficient, uh, public clouds that cost we'll see that, that drive a lot of these enterprise own data centers. So in our view, what we are seeing is that this, this, uh, sustainable cloud position helps, uh, helps companies to, uh, drive a lot of the goals in addition to their financial and other goods. >>So what should organizations who are, who are watching this interview and saying, Hey, I need to know more, what, what do you recommend to them? And what, where should they go to get more information on Greenplum? >>No, if you you're, if you are a business leader and you're thinking about which cloud provider is good, or how, how should applications be modernized to meet our day-to-day needs, which cloud driven innovations should be priorities. Uh, you know, that's why Accenture, uh, formed up the cloud first organization and essentially to provide the full stack of cloud services to help our clients become a cloud first business. Um, you know, it's all about excavation, uh, the digital transformation innovating faster, creating differentiated, uh, and sustainable value for our clients. And we're powering it up at 70,000 cloud professionals, $3 billion investment, and, uh, bringing together and services for our clients in terms of cloud solutions. And obviously the ecosystem partnership that we have that we are seeing today, uh, and the assets that help our clients realize their goals. Um, and again, to do reach out to us, uh, we can help them determine obviously, an optimal, sustainable cloud for solution that meets the business needs and being unprecedented levels of innovation. Our experience will be our advantage. And now more than ever, Rebecca, >>Just closing us out here. Do you have any advice for these companies who are navigating a great deal of uncertainty? We, what, what do you think the next 12 to 24 months? What do you think that should be on the minds of CEOs as they go through? >>So, as CEO's are thinking about rapidly leveraging cloud, migrating to cloud, uh, one of the elements that we want them to be thoughtful about is can they do that, uh, with unprecedent level of innovation, but also build a greener planet and a greener balance sheet, if we can achieve this balance and kind of, uh, have a, have a world which is greener, I think the world will win. And we all along with Accenture clients will win. That's what I would say, uh, >>Optimistic outlook. And I will take it. Thank you so much. Kishor for coming on the show >>That was >>Accenture's Kishor Dirk, I'm Rebecca Knight stay tuned for more of the cube virtuals coverage of the Accenture executive summit >>Around the globe. >>It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtual and our coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. Today, we are talking about the power of three. And what happens when you bring together the scientific know-how of a global bias biopharmaceutical powerhouse in Takeda, a leading cloud services provider in AWS, and Accenture's ability to innovate, execute, and deliver innovation. Joining me to talk about these things. We have Aaron, sorry, Arjun, baby. He is the senior managing director and chairman of Accenture's diamond leadership council. Welcome Arjun Karl hick. He is the chief digital and information officer at Takeda. >>What is your bigger, thank you, Rebecca >>And Brian bowhead, global director, and head of the Accenture AWS business group at Amazon web services. Thanks so much for coming on. Thank you. So, as I said, we're talking today about this relationship between, uh, your three organizations. Carl, I want to talk with you. I know you're at the beginning of your cloud journey. What was the compelling reason? What, what, why, why move to the cloud and why now? >>Yeah, no, thank you for the question. So, you know, as a biopharmaceutical leader, we're committed to bringing better health and a brighter future to our patients. We're doing that by translating science into some really innovative and life transporting therapies, but throughout, you know, we believe that there's a responsible use of technology, of data and of innovation. And those three ingredients are really key to helping us deliver on that promise. And so, you know, while I think, uh, I'll call it, this cloud journey is already always been a part of our strategy. Um, and we've made some pretty steady progress over the last years with a number of I'll call it diverse approaches to the digital and AI. We just weren't seeing the impact at scale that we wanted to see. Um, and I think that, you know, there's a, there's a need ultimately to, you know, accelerate and, uh, broaden that shift. >>And, you know, we were commenting on this earlier, but there's, you know, it's been highlighted by a number of factors. One of those has been certainly a number of the large acquisitions we've made Shire, uh, being the most pressing example, uh, but also the global pandemic, both of those highlight the need for us to move faster, um, at the speed of cloud, ultimately. Uh, and so we started thinking outside of the box because it was taking us too long and we decided to leverage this strategic partner model. Uh, and it's giving us a chance to think about our challenges very differently. We call this the power of three, uh, and ultimately our focus is singularly on our patients. I mean, they're waiting for us. We need to get there faster. It can take years. And so I think that there is a focus on innovation, um, at a rapid speed, so we can move ultimately from treating conditions to keeping people healthy. >>So as you are embarking on this journey, what are some of the insights you want to share about, about what you're seeing so far? >>Yeah, no, it's a great question. So, I mean, look, maybe right before I highlight some of the key insights, uh, I would say that, you know, with cloud now as the, as the launchpad for innovation, you know, our vision all along has been that in less than 10 years, we want every single to kid, uh, associate we're employed to be empowered by an AI assistant. And I think that, you know, that's going to help us make faster, better decisions. That'll help us, uh, fundamentally deliver transformative therapies and better experiences to, to that ecosystem, to our patients, to physicians, to payers, et cetera, much faster than we previously thought possible. Um, and I think that technologies like cloud and edge computing together with a very powerful I'll call it data fabric is going to help us to create this, this real-time, uh, I'll call it the digital ecosystem. >>The data has to flow ultimately seamlessly between our patients and providers or partners or researchers, et cetera. Uh, and so we've been thinking about this, uh, I'll call it legal, hold up, sort of this pyramid, um, that helps us describe our vision. Uh, and a lot of it has to do with ultimately modernizing the foundation, modernizing and rearchitecting, the platforms that drive the company, uh, heightening our focus on data, which means that there's an accelerated shift towards enterprise data platforms and digital products. And then ultimately, uh, uh, P you know, really an engine for innovation sitting at the very top. Um, and so I think with that, you know, there's a few different, uh, I'll call it insights that, you know, are quickly kind of come zooming into focus. I would say one is this need to collaborate very differently. Um, you know, not only internally, but you know, how do we define ultimately, and build a connected digital ecosystem with the right partners and technologies externally? >>I think the second, uh, component that maybe people don't think as much about, but, you know, I find critically important is for us to find ways of really transforming our culture. We have to unlock talent and shift the culture certainly as a large biopharmaceutical very differently. And then lastly, you've touched on it already, which is, you know, innovation at the speed of cloud. How do we re-imagine that, you know, how do ideas go from getting tested and months to kind of getting tested in days? You know, how do we collaborate very differently? Uh, and so I think those are three, uh, perhaps of the larger I'll call it, uh, insights that, you know, the three of us are spending a lot of time thinking about right now. >>So Arjun, I want to bring you into this conversation a little bit. Let's, let's delve into those a bit. Talk first about the collaboration, uh, that Carl was referencing there. How, how have you seen that it is enabling, uh, colleagues and teams to communicate differently and interact in new and different ways? Uh, both internally and externally, as Carl said, >>No, th thank you for that. And, um, I've got to give call a lot of credit, because as we started to think about this journey, it was clear, it was a bold ambition. It was, uh, something that, you know, we had all to do differently. And so the, the concept of the power of three that Carl has constructed has become a label for us as a way to think about what are we going to do to collectively drive this journey forward. And to me, the unique ways of collaboration means three things. The first one is that, um, what is expected is that the three parties are going to come together and it's more than just the sum of our resources. And by that, I mean that we have to bring all of ourselves, all of our collective capabilities, as an example, Amazon has amazing supply chain capabilities. >>They're one of the best at supply chain. So in addition to resources, when we have supply chain innovations, uh, that's something that they're bringing in addition to just, uh, talent and assets, similarly for Accenture, right? We do a lot, uh, in the talent space. So how do we bring our thinking as to how we apply best practices for talent to this partnership? So, um, as we think about this, so that's, that's the first one, the second one is about shared success very early on in this partnership, we started to build some foundations and actually develop seven principles that all of us would look at as the basis for this success shared success model. And we continue to hold that sort of in the forefront, as we think about this collaboration. And maybe the third thing I would say is this one team mindset. So whether it's the three of our CEOs that get together every couple of months to think about, uh, this partnership, or it is the governance model that Carl has put together, which has all three parties in the governance and every level of leadership, we always think about this as a collective group, so that we can keep that front and center. >>And what I think ultimately has enabled us to do is it allowed us to move at speed, be more flexible. And ultimately all we're looking at the target the same way, the North side, the same way. >>Brian, what about you? What have you observed and what are you thinking about in terms of how this is helping teams collaborate differently? >>Yeah, absolutely. And RJ made some, some great points there. And I think if you really think about what he's talking about, it's that, that diversity of talent, diversity of skill and viewpoint and even culture, right? And so we see that in the power of three. And then I think if we drill down into what we see at Takeda, and frankly, Takeda was, was really, I think, pretty visionary and on their way here, right. And taking this kind of cross-functional approach and applying it to how they operate day to day. So moving from a more functional view of the world to more of a product oriented view of the world, right? So when you think about we're going to be organized around a product or a service or a capability that we're going to provide to our customers or our patients or donors in this case, it implies a different structure, although altogether, and a different way of thinking, right? >>Because now you've got technical people and business experts and marketing experts, all working together in this is sort of cross collaboration. And what's great about that is it's really the only way to succeed with cloud, right? Because the old ways of thinking where you've got application people and infrastructure, people in business, people is suboptimal, right? Because we can all access this tool was, and these capabilities and the best way to do that, isn't across kind of a cross collaborative way. And so this is product oriented mindset. It's a keto was already on. I think it's allowed us to move faster in those areas. >>Carl, I want to go back to this idea of unlocking talent and culture. And this is something that both Brian and Arjun have talked about too. People are, are an essential part of their, at the heart of your organization. How will their experience of work change and how are you helping re-imagine and reinforce a strong organizational culture, particularly at this time when so many people are working remotely. >>Yeah. It's a great question. And it's something that, you know, I think we all have to think a lot about, I mean, I think, um, you know, driving this, this call it, this, this digital and data kind of capability building, uh, takes a lot of, a lot of thinking. So, I mean, there's a few different elements in terms of how we're tackling this one is we're recognizing, and it's not just for the technology organization or for those actors that, that we're innovating with, but it's really across all of the Cato where we're working through ways of raising what I'll call the overall digital leaders literacy of the organization, you know, what are the, you know, what are the skills that are needed almost at a baseline level, even for a global bio-pharmaceutical company and how do we deploy, I'll call it those learning resources very broadly. >>And then secondly, I think that, you know, we're, we're very clear that there's a number of areas where there are very specialized skills that are needed. Uh, my organization is one of those. And so, you know, we're fostering ways in which, you know, we're very kind of quickly kind of creating, uh, avenues excitement for, for associates in that space. So one example specifically, as we use, you know, during these very much sort of remote, uh, sort of days, we, we use what we call global it days, and we set a day aside every single month and this last Friday, um, you know, we, we create during that time, it's time for personal development. Um, and we provide active seminars and training on things like, you know, robotic process automation, data analytics cloud, uh, in this last month we've been doing this for months and months now, but in his last month, more than 50% of my organization participated, and there's this huge positive shift, both in terms of access and excitement about really harnessing those new skills and being able to apply them. >>Uh, and so I think that that's, you know, one, one element that, uh, can be considered. And then thirdly, um, of course, every organization to work on, how do you prioritize talent, acquisition and management and competencies that you can't rescale? I mean, there are just some new capabilities that we don't have. And so there's a large focus that I have with our executive team and our CEO and thinking through those critical roles that we need to activate in order to kind of, to, to build on this, uh, this business led cloud transformation. And lastly, probably the hardest one, but the one that I'm most jazzed about is really this focus on changing the mindsets and behaviors. Um, and I think there, you know, this is where the power of three is, is really, uh, kind of coming together nicely. I mean, we're working on things like, you know, how do we create this patient obsessed curiosity, um, and really kind of unlock innovation with a real, kind of a growth mindset. >>Uh, and the level of curiosity that's needed, not to just continue to do the same things, but to really challenge the status quo. So that's one big area of focus we're having the agility to act just faster. I mean, to worry less, I guess I would say about kind of the standard chain of command, but how do you make more speedy, more courageous decisions? And this is places where we can emulate the way that a partner like AWS works, or how do we collaborate across the number of boundaries, you know, and I think, uh, Arjun spoke eloquently to a number of partnerships that we can build. So we can break down some of these barriers and use these networks, um, whether it's within our own internal ecosystem or externally to help, to create value faster. So a lot of energy around ways of working and we'll have to check back in, but I mean, we're early in on this mindset and behavioral shift, um, but a lot of good early momentum. >>Carl you've given me a good segue to talk to Brian about innovation, because you said a lot of the things that I was the customer obsession and this idea of innovating much more quickly. Obviously now the world has its eyes on drug development, and we've all learned a lot about it, uh, in the past few months and accelerating drug development is all, uh, is of great interest to all of us. Brian, how does a transformation like this help a company's, uh, ability to become more agile and more innovative and at a quicker speed to, >>Yeah, no, absolutely. And I think some of the things that Carl talked about just now are critical to that, right? I think where sometimes folks fall short is they think, you know, we're going to roll out the technology and the technology is going to be the silver bullet where we're, in fact it is the culture. It is, is the talent. And it's the focus on that. That's going to be, you know, the determinant of success. And I will say, you know, in this power of three arrangement and Carl talked a little bit about the pyramid, um, talent and culture and that change, and the kind of thinking about that has been a first-class citizen since the very beginning, right. That absolutely is critical for, for being there. Um, and, and so that's been, that's been key. And so we think about innovation at Amazon and AWS, and Carl mentioned some of the things that, you know, partner like AWS can bring to the table is we talk a lot about builders, right? >>So kind of obsessive about builders. Um, and, and we meet what we mean by that is we at Amazon, we hire for builders, we cultivate builders and we like to talk to our customers about it as well. And it also implies a different mindset, right? When you're a builder, you have that, that curiosity, you have that ownership, you have that stake in whatever I'm creating, I'm going to be a co-owner of this product or this service, right. Getting back to that kind of product oriented mindset. And it's not just the technical people or the it people who are builders. It is also the business people as, as Carl talked about. Right. So when we start thinking about, um, innovation again, where we see folks kind of get into a little bit of a innovation pilot paralysis, is that you can focus on the technology, but if you're not focusing on the talent and the culture and the processes and the mechanisms, you're going to be putting out technology, but you're not going to have an organization that's ready to take it and scale it and accelerate it. >>Right. And so that's, that's been absolutely critical. So just a couple of things we've been doing with, with Takeda and Decatur has really been leading the way is, think about a mechanism and a process. And it's really been working backward from the customer, right? In this case, again, the patient and the donor. And that was an easy one because the key value of Decatur is to be a patient focused bio-pharmaceutical right. So that was embedded in their DNA. So that working back from that, that patient, that donor was a key part of that process. And that's really deep in our DNA as well. And Accenture's, and so we were able to bring that together. The other one is, is, is getting used to experimenting and even perhaps failing, right. And being able to iterate and fail fast and experiment and understanding that, you know, some decisions, what we call it at Amazon or two-way doors, meaning you can go through that door, not like what you see and turn around and go back. And cloud really helps there because the costs of experimenting and the cost of failure is so much lower than it's ever been. You can do it much faster and the implications are so much less. So just a couple of things that we've been really driving, uh, with the cadence around innovation, that's been really critical. Carl, where are you already seeing signs of success? >>Yeah, no, it's a great question. And so we chose, you know, uh, with our focus on innovation to try to unleash maybe the power of data digital in, uh, in focusing on what I call sort of a Maven. And so we chose our, our, our plasma derived therapy business, um, and you know, the plasma-derived therapy business unit, it develops critical life-saving therapies for patients with rare and complex diseases. Um, but what we're doing is by bringing kind of our energy together, we're focusing on creating, I'll call it state of the art digitally connected donation centers. And we're really modernizing, you know, the, the, the donor experience right now, we're trying to, uh, improve also I'll call it the overall plasma collection process. And so we've, uh, selected a number of alcohol at a very high speed pilots that we're working through right now, specifically in this, in this area. And we're seeing >>Really great results already. Um, and so that's, that's one specific area of focus are Jen, I want you to close this out here. Any ideas, any best practices advice you would have for other pharmaceutical companies that are, that are at the early stage of their cloud journey? Yes. Sorry. Arjun. >>Yeah, no, I was breaking up a bit. No, I think they, um, the key is what what's sort of been great for me to see is that when people think about cloud, you know, you always think about infrastructure technology. The reality is that the cloud is really the true enabler for innovation and innovating at scale. And, and if you think about that, right, in all the components that you need, uh, ultimately that's where the value is for the company, right? Because yes, you're going to get some cost synergies and that's great, but the true value is in how do we transform the organization in the case of the Qaeda and the life sciences clients, right. We're trying to take a 14 year process of research and development that takes billions of dollars and compress that right. Tremendous amounts of innovation opportunity. You think about the commercial aspect, lots of innovation can come there. The plasma derived therapy is a great example of how we're going to really innovate to change the trajectory of that business. So I think innovation is at the heart of what most organizations need to do. And the formula, the cocktail that Takeda has constructed with this Fuji program really has all the ingredients, um, that are required for that success. >>Great. Well, thank you so much. Arjun, Brian and Carl was really an enlightening conversation. >>Thank you. Yeah, it's been fun. Thanks Rebecca. >>And thank you for tuning into the cube. Virtual is coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of Accenture executive summit here at AWS reinvent. I'm your host Rebecca Knight for this segment? We have two guests. First. We have Helen Davis. She is the senior director of cloud platform services, assistant director for it and digital for the West Midlands police. Thanks so much for coming on the show, Helen, and we also have Matthew lb. He is Accenture health and public service associate director and West Midlands police account lead. Thanks so much for coming on the show. Matthew, thank you for joining us. So we are going to be talking about delivering data-driven insights to the West Midlands police force. Helen, I want to start with >>You. Can you tell us a little bit about the West Midlands police force? How big is the force and also what were some of the challenges that you were grappling with prior to this initiative? >>Yeah, certainly. So Westerners police is the second largest police force in the UK, outside of the metropolitan police in London. Um, we have an excessive, um, 11,000 people work at Westman ins police serving communities, um, through, across the Midlands region. So geographically, we're quite a big area as well, as well as, um, being population, um, density, having that as a, at a high level. Um, so the reason we sort of embarked on the data-driven insights platform and it, which was a huge change for us was for a number of reasons. Um, namely we had a lot of disparate data, um, which was spread across a range of legacy systems that were many, many years old, um, with some duplication of what was being captured and no single view for offices or, um, support staff. Um, some of the access was limited. You have to be in a, in an actual police building on a desktop computer to access it. Um, other information could only reach the offices on the front line, through a telephone call back to one of our enabling services where they would do a manual checkup, um, look at the information, then call the offices back, um, and tell them what they needed to know. So it was a very long laborious, um, process and not very efficient. Um, and we certainly weren't exploiting the data that we had in a very productive way. >>So it sounds like as you're describing, and I'm old clunky system that needed a technological, uh, reimagination. So what was the main motivation for, for doing, for making this shift? >>It was really, um, about making us more efficient and more effective in how we do how we do business. So, um, you know, certainly as a, as an it leader and some of my operational colleagues, we recognize the benefits, um, that data analytics could bring in, uh, in a policing environment, not something that was, um, really done in the UK at the time. You know, we have a lot of data, so we're very data rich and the information that we have, but we needed to turn it into information that was actionable. So that's where we started looking for, um, technology partners and suppliers to help us and sort of help us really with what's the art of the possible, you know, this hasn't been done before. So what could we do in this space? That's appropriate, >>Helen. I love that idea. What is the art of the possible, can you tell us a little bit about why you chose AWS? >>I think really, you know, as with all things and when we're procuring a partner in the public sector that, you know, there are many rules and regulations quite rightly as you would expect that to be because we're spending public money. So we have to be very, very careful and, um, it's, it's a long process and we have to be open to public scrutiny. So, um, we sort of look to everything, everything that was available as part of that process, but we recognize the benefits that Clyde would provide in this space because, you know, we're like moving to a cloud environment. We would literally be replacing something that was legacy with something that was a bit more modern. Um, that's not what we wanted to do. Our ambition was far greater than that. So I think, um, in terms of AWS, really, it was around scalability, interoperability, you know, just us things like the disaster recovery service, the fact that we can scale up and down quickly, we call it dialing up and dialing back. Um, you know, it's it's page go. So it just sort of ticked all the boxes for us. And then we went through the full procurement process, fortunately, um, it came out on top for us. So we were, we were able to move forward, but it just sort of had everything that we were looking for in that space. >>Matthew, I want to bring you into the conversation a little bit here. How are you working with a wet with the West Midlands police, sorry. And helping them implement this cloud-first >>Yeah, so I guess, um, by January the West Midlands police started, um, favorite five years ago now. So, um, we set up a partnership with the fools. I wanted to operate in a way that was very different to a traditional supplier relationship. Um, secretary that the data difference insights program is, is one of many that we've been working with last on, um, over the last five years, um, as having said already, um, cloud gave a number of, uh, advantages certainly from a big data perspective and things that, that enabled us today. Um, I'm from an Accenture perspective that allowed us to bring in a number of the different teams that we have say, cloud teams, security teams, um, and drafted from an insurance perspective, as well as the more traditional services that people would associate with the country. >>I mean, so much of this is about embracing comprehensive change to experiment and innovate and try different things. Matthew, how, how do you help, uh, an entity like West Midlands police think differently when they are, there are these ways of doing things that people are used to, how do you help them think about what is the art of the possible, as Helen said, >>There's a few things to that enable those being critical is trying to co-create solutions together. Yeah. There's no point just turning up with, um, what we think is the right answer, try and say, um, collectively work three, um, the issues that the fullest is seeing and the outcomes they're looking to achieve rather than simply focusing on a long list of requirements, I think was critical and then being really open to working together to create the right solution. Um, rather than just, you know, trying to pick something off the shelf that maybe doesn't fit the forces requirements in the way that it should too, >>Right. It's not always a one size fits all. >>Obviously, you know, today what we believe is critical is making sure that we're creating something that met the forces needs, um, in terms of the outcomes they're looking to achieve the financial envelopes that were available, um, and how we can deliver those in a, uh, iterative agile way, um, rather than spending years and years, um, working towards an outcome, um, that is gonna update before you even get that. >>So Helen, how, how are things different? What kinds of business functions and processes have been re-imagined in, in light of this change and this shift >>It's, it's actually unrecognizable now, um, in certain areas of the business as it was before. So to give you a little bit of, of context, when we, um, started working with essentially an AWS on the data driven insights program, it was very much around providing, um, what was called locally, a wizzy tool for our intelligence analyst to interrogate data, look at data, you know, decide whether they could do anything predictive with it. And it was very much sort of a back office function to sort of tidy things up for us and make us a bit better in that, in that area or a lot better in that area. And it was rolled out to a number of offices, a small number on the front line. Um, and really it was, um, in line with a mobility strategy that we, hardware officers were getting new smartphones for the first time, um, to do sort of a lot of things on, on, um, policing apps and things like that to again, to avoid them, having to keep driving back to police stations, et cetera. >>And the pilot was so successful. Every officer now has access to this data, um, on their mobile devices. So it literally went from a handful of people in an office somewhere using it to do sort of clever whizzbang things to, um, every officer in the force, being able to access that level of data at their fingertips. Literally. So what they were touched we've done before is if they needed to check and address or check details of an individual, um, just as one example, they would either have to, in many cases, go back to a police station to look it up themselves on a desktop computer. Well, they would have to make a call back to a centralized function and speak to an operator, relay the questions, either, wait for the answer or wait for a call back with the answer when those people are doing the data interrogation manually. >>So the biggest change for us is the self-service nature of the data we now have available. So officers can do it themselves on their phone, wherever they might be. So the efficiency savings from that point of view are immense. And I think just parallel to that is the quality of our, because we had a lot of data, but just because you've got a lot of data and a lot of information doesn't mean it's big data and it's valuable necessarily. Um, so again, it was having the single source of truth as we, as we call it. So you know that when you are completing those safe searches and getting the responses back, that it is the most accurate information we hold. And also you're getting it back within minutes, as opposed to, you know, half an hour, an hour or a drive back to a station. So it's making officers more efficient and it's also making them safer. The more efficient they are, the more time they have to spend out with the public doing what they, you know, we all should be doing, >>Seen that kind of return on investment, because what you were just describing with all the steps that we needed to be taken in prior to this, to verify an address say, and those are precious seconds when someone's life is on the line in, in sort of in the course of everyday police work. >>Absolutely. Yeah, absolutely. It's difficult to put a price on it. It's difficult to quantify. Um, but all the, you know, the minutes here and that certainly add up to a significant amount of efficiency savings, and we've certainly been able to demonstrate the officers are spending less time up police stations as a result or more time out on the front frontline also they're safer because they can get information about what may or may not be and address what may or may not have occurred in an area before very, very quickly without having to wait. >>Thank you. I want to hear your observations of working so closely with this West Midlands police. Have you noticed anything about changes in its culture and its operating model in how police officers interact with one another? Have you seen any changes since this technology change? >>What's unique about the Western new misplaces, the buy-in from the top down, the chief and his exact team and Helen as the leader from an IOT perspective, um, the entire force is bought in. So what is a significant change program? Uh, I'm not trickles three. Um, everyone in the organization, um, change is difficult. Um, and there's a lot of time effort. That's been put into both the technical delivery and the business change and adoption aspects around each of the projects. Um, but you can see the step change that is making in each aspect to the organization, uh, and where that's putting West Midlands police as a leader in, um, technology I'm policing in the UK. And I think globally, >>And this is a question for both of you because Matthew, as you said, change is difficult and there is always a certain intransigence in workplaces about this is just the way we've always done things and we're used to this and don't try us to get us. Don't try to get us to do anything new here. It works. How do you get the buy-in that you need to do this kind of digital transformation? >>I think it, it would be wrong to say it was easy. Um, um, we also have to bear in mind that this was one program in a five-year program. So there was a lot of change going on, um, both internally for some of our back office functions, as well as front Tai, uh, frontline offices. So with DDI in particular, I think the stat change occurred when people could see what it could do for them. You know, we had lots of workshops and seminars where we all talk about, you know, big data and it's going to be great and it's data analytics and it's transformational, you know, and quite rightly people that are very busy doing a day job that not necessarily technologists in the main and, you know, are particularly interested quite rightly so in what we are not dealing with the cloud, you know? >>And it was like, yeah, okay. It's one more thing. And then when they started to see on that, on their phones and what teams could do, that's when it started to sell itself. And I think that's when we started to see, you know, to see the stat change, you know, and, and if we, if we have any issues now it's literally, you know, our help desks in meltdown. Cause everyone's like, well, we call it manage without this anymore. And I think that speaks for itself. So it doesn't happen overnight. It's sort of incremental changes and then that's a step change in attitude. And when they see it working and they see the benefits, they want to use it more. And that's how it's become fundamental to all policing by itself, really, without much selling >>You, Helen just made a compelling case for how to get buy in. Have you discovered any other best practices when you are trying to get everyone on board for this kind of thing? >>We've um, we've used a lot of the traditional techniques, things around comms and engagement. We've also used things like, um, the 30 day challenge and nudge theory around how can we gradually encourage people to use things? Um, I think there's a point where all of this around, how do we just keep it simple and keep it user centric from an end user perspective? I think DDI is a great example of where the, the technology is incredibly complex. The solution itself is, um, you know, extremely large and, um, has been very difficult to, um, get delivered. But at the heart of it is a very simple front end for the user to encourage it and take that complexity away from them. Uh, I think that's been critical through the whole piece of DDR. >>One final word from Helen. I want to hear, where do you go from here? What is the longterm vision? I know that this has made productivity, um, productivity savings equivalent to 154 full-time officers. Uh, what's next, >>I think really it's around, um, exploiting what we've got. Um, I use the phrase quite a lot, dialing it up, which drives my technical architects crazy. But so, because it's apparently not that simple, but, um, you know, we've, we've been through significant change in the last five years and we are still continuing to batch all of those changes into everyday, um, operational policing. But what we need to see is we need to exploit and build on the investments that we've made in terms of data and claims specifically, the next step really is about expanding our pool of data and our functions. Um, so that, you know, we keep getting better and better at this. And the more we do, the more data we have, the more refined we can be, the more precise we are with all of our actions. Um, you know, we're always being expected to, again, look after the public purse and do more for less. >>And I think this is certainly an and our cloud journey and, and cloud first by design, which is where we are now, um, is helping us to be future-proofed. So for us, it's very much an investment. And I see now that we have good at embedded in operational policing for me, this is the start of our journey, not the end. So it's really exciting to see where we can go from here. Exciting times. Indeed. Thank you so much. Lily, Helen and Matthew for joining us. I really appreciate it. Thank you. And you are watching the cube stay tuned for more of the cubes coverage of the AWS reinvent Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome to the cube virtual coverage of the executive summit at AWS reinvent 2020 virtual. This is the cube virtual. We can't be there in person like we are every year we have to be remote. This executive summit is with special programming supported by Accenture where the cube virtual I'm your host John for a year, we had a great panel here called uncloud first digital transformation from some experts, Stuart driver, the director of it and infrastructure and operates at lion Australia, Douglas Regan, managing director, client account lead at lion for Accenture as a deep Islam associate director application development lead for Centure gentlemen, thanks for coming on the cube virtual that's a mouthful, all that digital, but the bottom line it's cloud transformation. This is a journey that you guys have been on together for over 10 years to be really a digital company. Now, some things have happened in the past year that kind of brings all this together. This is about the next generation organization. So I want to ask Stuart you first, if you can talk about this transformation at lion has undertaken some of the challenges and opportunities and how this year in particular has brought it together because you know, COVID has been the accelerant of digital transformation. Well, if you're 10 years in, I'm sure you're there. You're in the, uh, on that wave right now. Take a minute to explain this transformation journey. >>Yeah, sure. So a number of years back, we, we looked at kind of our infrastructure in our landscape trying to figure out where we >>Wanted to go next. And we were very analog based and stuck in the old it groove of, you know, Capitol reef rash, um, struggling to transform, struggling to get to a digital platform and we needed to change it up so that we could become very different business to the one that we were back then obviously cloud is an accelerant to that. And we had a number of initiatives that needed a platform to build on. And a cloud infrastructure was the way that we started to do that. So we went through a number of transformation programs that we didn't want to do that in the old world. We wanted to do it in a new world. So for us, it was partnering up with a dried organizations that can take you on the journey and, uh, you know, start to deliver bit by bit incremental progress, uh, to get to the, uh, I guess the promise land. >>Um, we're not, not all the way there, but to where we're on the way along. And then when you get to some of the challenges like we've had this year, um, it makes all of the hard work worthwhile because you can actually change pretty quickly, um, provide capacity and, uh, and increase your environments and, you know, do the things that you need to do in a much more dynamic way than we would have been able to previously where we might've been waiting for the hardware vendors, et cetera, to deliver capacity. So for us this year, it's been a pretty strong year from an it perspective and delivering for the business needs >>Before I hit the Douglas. I want to just real quick, a redirect to you and say, you know, if all the people said, Oh yeah, you got to jump on cloud, get in early, you know, a lot of naysayers like, well, wait till to mature a little bit, really, if you got in early and you, you know, paying your dues, if you will taking that medicine with the cloud, you're really kind of peaking at the right time. Is that true? Is that one of the benefits that comes out of this getting in the cloud? Yeah, >>John, this has been an unprecedented year, right. And, um, you know, Australia, we had to live through Bush fires and then we had covert and, and then we actually had to deliver a, um, a project on very nice transformational project, completely remote. And then we also had had some, some cyber challenges, which is public as well. And I don't think if we weren't moved into and enabled through the cloud, we would have been able to achieve that this year. It would have been much different and would have been very difficult to do the backing. We're able to work and partner with Amazon through this year, which is unprecedented and actually come out the other end and we've delivered a brand new digital capability across the entire business. Um, in many, you know, wouldn't have been impossible if we could, I guess, stayed in the old world. The fact that we were moved into the new Naval by the new allowed us to work in this unprecedented year. >>Just quilt. What's your personal view on this? Because I've been saying on the Cuban reporting necessity is the mother of all invention and the word agility has been kicked around as kind of a cliche, Oh, it'd be agile. You know, we're going to get the city, you get a minute on specifically, but from your perspective, uh, Douglas, what does that mean to you? Because there is benefits there for being agile. And >>I mean, I think as Stuart mentioned, right, in a lot of these things we try to do and, you know, typically, you know, hardware and, uh, the last >>To be told and, and, and always on the critical path to be done, we really didn't have that in this case, what we were doing with our projects in our deployments, right. We were able to move quickly able to make decisions in line with the business and really get things going. Right. So you see a lot of times in a traditional world, you have these inhibitors, you have these critical path, it takes weeks and months to get things done as opposed to hours and days, and, and truly allowed us to, we had to, you know, VJ things, move things. And, you know, we were able to do that in this environment with AWS to support and the fact that they can kind of turn things off and on as quickly as we needed. >>Yeah. Cloud-scale is great for speed. So DECA, Gardez get your thoughts on this cloud first mission, you know, it, you know, the dev ops world, they saw this early, that jumping in there, they saw the, the, the agility. Now the theme this year is modern applications with the COVID pandemic pressure, there's real business pressure to make that happen. How did you guys learn to get there fast? And what specifically did you guys do at Accenture and how did it all come together? Can you take us inside kind of how it played out? >>Right. So, yeah, we started off with, as we do in most cases with a much more bigger group, and we worked with lions functional experts and, uh, the lost knowledge that allowed the infrastructure had. Um, we then applied our journey to cloud strategy, which basically revolves around the seminars and, and, uh, you know, the deep three steps from our perspective, uh, assessing the current and bottom and setting up the new cloud environment. And as we go modernizing and, and migrating these applications to the cloud now, you know, one of the key things that, uh, you know, we learned along this journey was that, you know, you can have the best plans, but bottom line that we were dealing with, we often than not have to make changes, uh, what a lot of agility and also work with a lot of collaboration with the, uh, lion team, as well as, uh, uh, AWS. I think the key thing for me was being able to really bring it all together. It's not just, uh, you know, we want to hear it's all of us working together to make this happen. >>What were some of the learnings real quick journey there? >>So I think perspective, the key learnings were that, you know, uh, you know, work, when you look back at, uh, the, the infrastructure that was that we were trying to migrate over to the cloud. A lot of the documentation, et cetera, was not, uh, available. We were having to, uh, figure out a lot of things on the fly. Now that really required us to have, uh, uh, people with deep expertise who could go into those environments and, and work out, uh, you know, the best ways to, to migrate the workloads to the cloud. Uh, I think, you know, the, the biggest thing for me was making sure all the had on that real SMEs across the board globally, that we could leverage across the various technologies, uh, uh, and, and, and, you know, that would really work in our collaborative and agile environment with line. >>Let's do what I got to ask you. How did you address your approach to the cloud and what was your experience? >>Yeah, for me, it's around getting the foundations right. To start with and then building on them. Um, so, you know, you've got to have your, your, your process and you've got to have your, your kind of your infrastructure there and your blueprints ready. Um, AWS do a great job of that, right. Getting the foundations right. And then building upon it, and then, you know, partnering with Accenture allows you to do that very successfully. Um, I think, um, you know, the one thing that was probably surprising to us when we started down this journey and kind of after we got a long way down the track and looking backwards is actually how much you can just turn off. Right? So a lot of stuff that you, uh, you get electric with a legacy in your environment, and when you start to work through it with the types of people that civic just mentioned, you know, the technical expertise working with the business, um, you can really rationalize your environment and, uh, you know, cloud is a good opportunity to do that, to drive that legacy out. >>Um, so you know, a few things there, the other thing is, um, you've got to try and figure out the benefits that you're going to get out of moving here. So there's no point in just taking something that is not delivering a huge amount of value in the traditional world, moving it into the cloud, and guess what is going to deliver the same limited amount of value. So you've got to transform it, and you've got to make sure that you build it for the future and understand exactly what you're trying to gain out of it. So again, you need a strong collaboration. You need a good partners to work with, and you need good engagement from the business as well, because the kind of, uh, you know, digital transformation, cloud transformation, isn't really an it project, I guess, fundamentally it is at the core, but it's a business project that you've got to get the whole business aligned on. You've got to make sure that your investment streams are appropriate and that's, uh, you're able to understand the benefits and the value that say, you're going to drive back towards the business. >>Let's do it. If you don't mind me asking, what was some of the obstacles you encountered or learnings, um, that might different from the expectation we all been there, Hey, you know, we're going to change the world. Here's the sales pitch, here's the outcome. And then obviously things happen, you know, you learn legacy, okay. Let's put some containerization around that cloud native, um, all that rational. You're talking about what are, and you're going to have obstacles. That's how you learn. That's how perfection has developed. How, what obstacles did you come up with and how are they different from your expectations going in? >>Yeah, they're probably no different from other people that have gone down the same journey. If I'm totally honest, the, you know, 70 or 80% of what you do is relatively easy of the known quantity. It's relatively modern architectures and infrastructures, and you can upgrade, migrate, move them into the cloud, whatever it is, rehost, replatform, rearchitect, whatever it is you want to do, it's the other stuff, right? It's the stuff that always gets left behind. And that's the challenge. It's, it's getting that last bit over the line and making sure that you haven't been invested in the future while still carrying all of your legacy costs and complexity within your environment. So, um, to be quite honest, that's probably taken longer and has been more of a challenge than we thought it would be. Um, the other piece I touched on earlier on in terms of what was surprising was actually how much of, uh, your environment is actually not needed anymore. >>When you start to put a critical eye across it and understand, um, uh, ask the tough questions and start to understand exactly what, what it is you're trying to achieve. So if you ask a part of a business, do they still need this application or this service a hundred percent of the time, they will say yes until you start to lay out to them, okay, now I'm going to cost you this to migrate it or this, to run it in the future. And, you know, here's your ongoing costs and, you know, et cetera, et cetera. And then, uh, for a significant amount of those answers, you get a different response when you start to layer on the true value of it. So you start to flush out those hidden costs within the business, and you start to make some critical decisions as a company based on, uh, based on that. So that was a little tougher than we first thought and probably broader than we thought there was more of that than we anticipated, um, which actually results in a much cleaner environment, post post migration, >>You know, the old expression, if it moves automated, you know, it's kind of a joke on government, how they want to tax everything, you know, you want to automate, that's a key thing in cloud, and you've got to discover those opportunities to create value Stuart and Siddique. Mainly if you can weigh in on this love to know the percentage of total cloud that you have now, versus when you started, because as you start to uncover whether it's by design for purpose, or you discover opportunity to innovate, like you guys have, I'm sure it kind of, you took on some territory inside Lyon, what percentage of cloud now versus start? >>Yeah. And at the start it was minimal, right. You know, close to zero, right. Single and single digits. Right. It was mainly SAS environments that we had, uh, sitting in clouds when we, uh, when we started, um, Doug mentioned earlier on a really significant transformation project, um, that we've undertaken and recently gone live on a multi-year one. Um, you know, that's all stood up on AWS and is a significant portion of our environment, um, in terms of what we can move to cloud. Uh, we're probably at about 80 or 90% now. And the balance bit is, um, legacy infrastructure that is just going to retire as we go through the cycle rather than migrate to the cloud. Um, so we are significantly cloud-based and, uh, you know, we're reaping the benefits of it in a year, like 2020, and makes you glad that you did all of the hard yards in the previous years when you started that business challenges thrown out as, >>So do you any common reaction still the cloud percentage penetration? >>Sorry, I didn't, I didn't guys don't, but I, I was going to say it was, I think it's like the 80 20 rule, right? We, we, we worked really hard in the, you know, I think 2018, 19 to get any person off, uh, after getting onto the cloud and, or the last year is the 20% that we have been migrating. And Stuart said like a non-athlete that is also, that's going to be the diet. And I think our next big step is going to be obviously, you know, the icing on the cake, which is to decommission all these apps as well. Right. So, you know, to get the real benefits out of, uh, the whole conservation program from a, uh, from a >>Douglas and Stewart, can you guys talk about the decision around the cloud because you guys have had success with AWS, why AWS how's that decision made? Can you guys give some insight into some of those thoughts? >>I can, I can start, start off. I think back when the decision was made and it was, Oh, it was a while back, um, you know, there's some clear advantages of moving relay, Ws, a lot of alignment with some of the significant projects and, uh, the trend, that particular one big transformation project that we've alluded to as well. Um, you know, we needed some, um, some very robust and, um, just future proof and, um, proven technology. And AWS gave that to us. We needed a lot of those blueprints to help us move down the path. We didn't want to reinvent everything. So, um, you know, having a lot of that legwork done for us and an AWS gives you that, right. And particularly when you partner up with, uh, with a company like Accenture as well, you get combinations of the technology and the skills and the knowledge to, to move you forward in that direction. >>So, um, you know, for us, it was a, uh, uh, it was a decision based on, you know, best of breed, um, you know, looking forward and, and trying to predict the future needs and, and, and kind of the environmental that we might need. Um, and, you know, partnering up with organizations that can take you on the journey. Yeah. And just to build on it. So obviously, you know, lion's like an NWS, but, you know, we knew it was a very good choice given that, um, uh, the skills and the capability that we had, as well as the assets and tools we had to get the most out of, um, out of AWS. And obviously our, our CEO globally is just spending, you know, announcement about a huge investment that we're making in cloud. Um, but you know, we've, we've worked very well. AWS, we've done some joint workshops and joint investments, um, some joint POC. So yeah, w we have a very good working relationship, AWS, and I think, um, one incident to reflect upon whether it's cyber it's and again, where we actually jointly, you know, dove in with, um, with Amazon and some of their security experts and our experts. And we're able to actually work through that with mine quite successful. So, um, you know, really good behaviors as an organization, but also really good capabilities. >>Yeah. As you guys, you're essential cloud outcomes, research shown, it's the cycle of innovation with the cloud. That's creating a lot of benefits, knowing what you guys know now, looking back certainly COVID is impacted a lot of people kind of going through the same process, knowing what you guys know now, would you advocate people to jump on this transformation journey? If so, how, and what tweaks they make, which changes, what would you advise? >>Uh, I might take that one to start with. Um, I hate to think where we would have been when, uh, COVID kicked off here in Australia and, you know, we were all sent home, literally were at work on the Friday, and then over the weekend. And then Monday, we were told not to come back into the office and all of a sudden, um, our capacity in terms of remote access and I quadrupled, or more four, five X, what we had on the Friday we needed on the Monday. And we were able to stand that up during the day Monday into Tuesday, because we were cloud-based and, uh, you know, we just spun up your instances and, uh, you know, sort of our licensing, et cetera. And we had all of our people working remotely, um, within, uh, you know, effectively one business day. Um, I know peers of mine in other organizations and industries that are relying on kind of a traditional wise and getting hardware, et cetera, that were weeks and months before they could get there the right hardware to be able to deliver to their user base. >>So, um, you know, one example where you're able to scale and, uh, um, get, uh, get value out of this platform beyond probably what was anticipated at the time you talk about, um, you know, less the, in all of these kinds of things. And you can also think of a few scenarios, but real world ones where you're getting your business back up and running in that period of time is, is just phenomenal. There's other stuff, right? There's these programs that we've rolled out, you do your sizing, um, and in the traditional world, you would just go out and buy more servers than you need. And, you know, probably never realize the full value of those, you know, the capability of those servers over the life cycle of them. Whereas, you know, in a cloud world, you put in what you think is right. And if it's not right, you pump it up a little bit when, when all of your metrics and so on, tell you that you need to bump it up. And conversely you scale it down at the same rate. So for us, with the types of challenges and programs and, uh, uh, and just business need, that's come at as this year, uh, we wouldn't have been able to do it without a strong cloud base, uh, to, uh, to move forward. >>You know, Douglas, one of the things I talked to, a lot of people on the right side of history who have been on the right wave with cloud, with the pandemic, and they're happy, they're like, and they're humble. Like, well, we're just lucky, you know, luck is preparation meets opportunity. And this is really about you guys getting in early and being prepared and readiness. This is kind of important as people realize, then you gotta be ready. I mean, it's not just, you don't get lucky by being in the right place, the right time. And there were a lot of companies were on the wrong side of history here who might get washed away. This is a super important, I think, >>To echo and kind of building on what Stewart said. I think that the reason that we've had success and I guess the momentum is we didn't just do it in isolation within it and technology. It was actually linked to broader business changes, you know, creating basically a digital platform for the entire business, moving the business, where are they going to be able to come back stronger after COVID, when they're actually set up for growth, um, and actually allows, you know, a line to achievements growth objectives, and also its ambitions as far as what it wants to do, uh, with growth in whatever they make, do with acquiring other companies and moving into different markets and launching new products. So we've actually done it in a way that is, you know, real and direct business benefit, uh, that actually enables line to grow >>General. I really appreciate you coming. I have one final question. If you can wrap up here, uh, Stuart and Douglas, you don't mind weighing in what's the priorities for the future. What's next for lion in a century >>Christmas holidays, I'll start Christmas holidays. I spent a good year and then a, and then a reset, obviously, right? So, um, you know, it's, it's figuring out, uh, transform what we've already transformed, if that makes sense. So God, a huge proportion of our services sitting in the cloud. Um, but we know we're not done even with the stuff that is in there. We need to take those next steps. We need more and more automation and orchestration. We need to, um, our environment is more future proof. We need to be able to work with the business and understand what's coming at them so that we can, um, you know, build that into, into our environment. So again, it's really transformation on top of transformation is the way that I'll describe it. And it's really an open book, right? Once you get it in and you've got the capabilities and the evolving tool sets that AWS continue to bring to the market based, um, you know, working with the partners to, to figure out how we unlock that value, um, you know, drive our costs down efficiency, uh, all of those kind of, you know, standard metrics. >>Um, but you know, we're looking for the next things to transform and showed value back out to our customer base, um, that, uh, that we continue to, you know, sell our products to and work with and understand how we can better meet their needs. Yeah, I think just to echo that, I think it's really leveraging this and then did you capability they have and getting the most out of that investment. And then I think it's also moving to, uh, and adopting more new ways of working as far as, you know, the speed of the business, um, is getting up to speed in the market is changing. So being able to launch and do things quickly and also, um, competitive and efficient operating costs, uh, now that they're in the cloud, right? So I think it's really leveraging the most out of the platform and then, you know, being efficient in launching things. So putting them with >>Siddique, any word from you on your priorities by you see this year in folding, >>There's got to say like e-learning squares, right, for me around, you know, just journey. This is a journey to the cloud, right? >>And, uh, you know, as well dug into sort of Saturday, it's getting all, you know, different parts of the organization along the journey business to it, to your, uh, product lenders, et cetera. Right. And it takes time. It is tough, but, uh, uh, you know, you got to get started on it. And, you know, once we, once we finish off, uh, it's the realization of the benefits now that, you know, looking forward, I think for, from Alliance perspective, it is, uh, you know, once we migrate all the workloads to the cloud, it is leveraging, uh, all stack drive. And as I think Stewart said earlier, uh, with, uh, you know, the latest and greatest stuff that AWS it's basically working to see how we can really, uh, achieve more better operational excellence, uh, from a, uh, from a cloud perspective. >>Well, Stewart, thanks for coming on with a and sharing your environment and what's going on and your journey you're on the right wave. Did the work you're in, it's all coming together with faster, congratulations for your success, and, uh, really appreciate Douglas with Steve for coming on as well from essential. Thank you for coming on. Thanks, John. Okay. Just the cubes coverage of executive summit at AWS reinvent. This is where all the thought leaders share their best practices, their journeys, and of course, special programming with Accenture and the cube. I'm Sean ferry, your host, thanks for watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cube virtuals coverage of the Accenture executive summit. Part of AWS reinvent 2020. I'm your host Rebecca Knight. We are talking today about reinventing the energy data platform. We have two guests joining us. First. We have Johan Krebbers. He is the GM digital emerging technologies and VP of it. Innovation at shell. Thank you so much for coming on the show, Johan you're welcome. And next we have Liz Dennett. She is the lead solution architect for O S D U on AWS. Thank you so much, Liz, maybe here. So I want to start our conversation by talking about OSD. You like so many great innovations. It started with a problem. Johann, what was the problem you were trying to solve at shell? We go back a couple of years, we started summer 2017, where we had a meeting with the guys from exploration in shell, and the main problem they had, of course, they got lots of lots of data, but are unable to find the right data. They need to work from all over the place and told him >>To, and we'll probably try to solve is how that person working exploration could find their proper date, not just a day, but also the date you really needed that we did probably talked about is summer 2017. And we said, okay, the only way ABC is moving forward is to start pulling that data into a single data platform. And that, that was at the time that we called it as the, you, the subsurface data universe in there was about the shell name was so in, in January, 2018, we started a project with Amazon to start grating a co fricking that building, that Stu environment, that the, the universe, so that single data level to put all your exploration and Wells data into that single environment that was intent. And every cent, um, already in March of that same year, we said, well, from Michele point of view, we will be far better off if we could make this an industry solution and not just a shelf solution, because Shelby, Shelby, if you can make an industry solution, but people are developing applications for it. >>It also is far better than for shell to say we haven't shell special solution because we don't make money out of how we start a day that we can make money out of it. We have access to the data, we can explore the data. So storing the data we should do as efficiently possibly can. So we monitor, we reach out to about eight or nine other last, uh, or I guess operators like the economics, like the tutorials, like the shepherds of this world and say, Hey, we inshallah doing this. Do you want to join this effort? And to our surprise, they all said, yes. And then in September, 2018, we had our kickoff meeting with your open group where we said, we said, okay, if you want to work together and lots of other companies, we also need to look at, okay, how, how we organize that. >>Or if you started working with lots of large companies, you need to have some legal framework around some framework around it. So that's why we went to the open group and say, okay, let's, let's form the old forum as we call it at the time. So it's September, 2080, where I did a Galleria in Houston, but the kickoff meeting for the OT four with about 10 members at the time. So that's just over two years ago, we started an exercise for me called ODU. They kicked it off. Uh, and so that's really them will be coming from and how we've got there. Also >>The origin story. Um, what, so what digging a little deeper there? What were some of the things you were trying to achieve with the OSU? >>Well, a couple of things we've tried to achieve with you, um, first is really separating data from applications for what is, what is the biggest problem we have in the subsurface space that the data and applications are all interlinked or tied together. And if, if you have them and a new company coming along and say, I have this new application and he's access to the data that is not possible because the data often interlinked with the application. So the first thing we did is really breaking the link between the application, the data as those levels, the first thing we did, secondly, put all the data to a single data platform, take the silos out what was happening in the sub-service space. They got all the data in what we call silos in small little islands out there. So what we're trying to do is first break the link to great, great. >>They put the data single day, the bathroom, and the third part, put a standard layer on top of that, it's an API layer on top to equate a platform. So we could create an ecosystem out of companies to start a valving Schoff application on top of dev data platform across you might have a data platform, but you're only successful if have a rich ecosystem of people start developing applications on top of that. And then you can export the data like small companies, last company, university, you name it, we're getting after create an ecosystem out here. So the three things were first break the link between application data, just break it and put data at the center and also make sure that data, this data structure would not be managed by one company, but it would only be met. It would be managed the data structures by the ODI forum. Secondly, then put a, the data, a single data platform certainly then has an API layer on top and then create an ecosystem. Really go for people, say, please start developing applications, because now you had access to the data. I've got the data no longer linked to somebody whose application was all freely available, but an API layer that was, that was all September, 2018, more or less. >>And hear a little bit. Can you talk a little bit about some of the imperatives from the AWS standpoint in terms of what you were trying to achieve with this? Yeah, absolutely. And this whole thing is Johann said started with a challenge that was really brought out at shell. The challenges that geoscientists spend up to 70% of their time looking for data. I'm a geologist I've spent more than 70% of my time trying to find data in these silos. And from there, instead of just figuring out how we could address that one problem, we worked together to really understand the root cause of these challenges and working backwards from that use case OSU and OSU on AWS has really enabled customers to create solutions that span, not just this in particular problem, but can really scale to be inclusive of the entire energy value chain and deliver value from these use cases to the energy industry and beyond. Thank you, Lee, uh, Johann. So talk a little bit about Accenture's cloud first approach and how it has, uh, helped shell work faster and better with speed. >>Well, of course, access a cloud first approach only works together. It's been an Amazon environment, AWS environment. So we're really looking at, uh, at, at Accenture and others altogether helping shell in this space. Now the combination of the two is what we're really looking at, uh, where access of course can be recent knowledge student to that environment operates support knowledge, do an environment. And of course, Amazon will be doing that to today's environment that underpinning their services, et cetera. So, uh, we would expect a combination, a lot of goods when we started rolling out and put in production, the old you are three and bug because we are anus. Then when the release feed comes to the market in Q1, next year of ODU have already started going to Audi production inside shell. But as the first release, which is ready for prime time production across an enterprise will be released just before Christmas, last year when he's still in may of this year. But really three is the first release we want to use for full scale production deployment inside shell, and also the operators around the world. And there is one Amazon, sorry, at that one. Um, extensive can play a role in the ongoing, in the, in deployment building up, but also support environment. >>So one of the other things that we talk a lot about here on the cube is sustainability. And this is a big imperative at so many organizations around the world in particular energy companies. How does this move to OSD you, uh, help organizations become, how is this a greener solution for companies? >>Well, first we make it's a greatest solution because you start making a much more efficient use of your resources, which is already an important one. The second thing we're doing is also, we started ODU in framers, in the oil and gas space in the expert development space. We've grown, uh, OTU in our strategy of growth. I was, you know, also do an alternative energy sociology. We'll all start supporting next year. Things like solar farms, wind farms, uh, the, the dermatomal environment hydration. So it becomes an and an open energy data platform, not just what I want to get into sleep. That's what new industry, any type of energy industry. So our focus is to create, bring the data of all those various energy data sources to get me to a single data platform you can to use AI and other technologies on top of that, to exploit the data, to meet again into a single data platform. >>Liz, I want to ask you about security because security is, is, is such a big concern when it comes to data. How secure is the data on OSD? You, um, actually, can I talk, can I do a follow up on this sustainability talking? Oh, absolutely. By all means. I mean, I want to interject though security is absolutely our top priority. I don't mean to move away from that, but with sustainability, in addition to the benefits of the OSU data platform, when a company moves from on-prem to the cloud, they're also able to leverage the benefits of scale. Now, AWS is committed to running our business in the most environmentally friendly way possible. And our scale allows us to achieve higher resource utilization and energy efficiency than a typical data center. >>Now, a recent study by four 51 research found that AWS is infrastructure is 3.6 times more energy efficient than the median of surveyed enterprise data centers. Two thirds of that advantage is due to higher, um, server utilization and a more energy efficient server population. But when you factor in the carbon intensity of consumed electricity and renewable energy purchases for 51 found that AWS performs the same task with an 88% lower carbon footprint. Now that's just another way that AWS and OSU are working to support our customers is they seek to better understand their workflows and make their legacy businesses less carbon intensive. >>That's that's incorrect. Those are those statistics are incredible. Do you want to talk a little bit now about security? Absolutely. And security will always be AWS is top priority. In fact, AWS has been architected to be the most flexible and secure cloud computing environment available today. Our core infrastructure is built to satisfy. There are the security requirements for the military, local banks and other high sensitivity organizations. And in fact, AWS uses the same secure hardware and software to build and operate each of our regions. So that customers benefit from the only commercial cloud that's hat hits service offerings and associated supply chain vetted and deemed secure enough for top secret workloads. That's backed by a deep set of cloud security tools with more than 200 security compliance and governmental service and key features as well as an ecosystem of partners like Accenture, that can really help our customers to make sure that their environments for their data meet and or exceed their security requirements. Johann, I want you to talk a little bit about how OSD you can be used today. Does it only handle subsurface data? >>Uh, today it's Honda's subserves or Wells data, we go to add to that production around the middle of next year. That means that the whole upstate business. So we've got goes from exploration all the way to production. You've made it together into a single data platform. So production will be added around Q3 of next year. Then a principal. We have a difficult, the elder data that single environment, and we want to extend them to other data sources or energy sources like solar farms, wind farms, uh, hydrogen, hydro, et cetera. So we're going to add a whore, a whole list of audit day energy source to them and be all the data together into a single data club. So we move from a falling guest data platform to an aniseed data platform. That's really what our objective is because the whole industry, if you look it over, look at our companies are all moving in. That same two acts of quantity of course, are very strong in oil and gas, but also increased the, got into the other energy sources like, like solar, like wind, like th like highly attended, et cetera. So we would be moving exactly. But that same method that, that, that the whole OSU can't really support at home. And as a spectrum of energy sources, >>Of course, and Liz and Johan. I want you to close us out here by just giving us a look into your crystal balls and talking about the five and 10 year plan for OSD. You we'll start with you, Liz. What do you, what do you see as the future holding for this platform? Um, honestly, the incredibly cool thing about working at AWS is you never know where the innovation and the journey is going to take you. I personally am looking forward to work with our customers, wherever their OSU journeys, take them, whether it's enabling new energy solutions or continuing to expand, to support use cases throughout the energy value chain and beyond, but really looking forward to continuing to partner as we innovate to slay tomorrow's challenges, Johann first, nobody can look at any more nowadays, especially 10 years own objective is really in the next five years, you will become the key backbone for energy companies for storing your data. You are efficient intelligence and optimize the whole supply energy supply chain in this world down here, you'll uncovers Liz Dennett. Thank you so much for coming on the cube virtual I'm Rebecca Knight stay tuned for more of our coverage of the Accenture executive summit >>From around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Welcome everyone to the cubes coverage of the Accenture executive summit. Part of AWS reinvent. I'm your host Rebecca Knight today we're welcoming back to Kubila. We have Kishor Dirk. He is the Accenture senior managing director cloud first global services lead. Welcome back to the show Kishore. Thank you very much. Nice to meet again. And, uh, Tristan moral horse set. He is the managing director, Accenture cloud first North America growth. Welcome back to you to trust and great to be back in grapes here again, Rebecca. Exactly. Even in this virtual format, it is good to see your faces. Um, today we're going to be talking about my nav and green cloud advisor capability. Kishor I want to start with you. So my nav is a platform that is really celebrating its first year in existence. Uh, November, 2019 is when Accenture introduced it. Uh, but it's, it has new relevance in light of this global pandemic that we are all enduring and suffering through. Tell us a little bit about the lineup platform, what it is that cloud platform to help our clients navigate the complexity of cloud and cloud decisions to make it faster. And obviously, you know, we have in the cloud, uh, you know, with >>The increased relevance and all the, especially over the last few months with the impact of COVID crisis and exhibition of digital transformation, you know, we are seeing the transformation or the acceleration to cloud much faster. This platform that you're talking about has enabled and 40 clients globally across different industries. You identify the right cloud solution, navigate the complexity, provide a cloud specific solution simulate for our clients to meet the strategy business needs, and the clients are loving it. >>I want to go to you now trust and tell us a little bit about how mine nav works and how it helps companies make good cloud choice. >>Yeah, so Rebecca, we we've talked about cloud is, is more than just infrastructure and that's what mine app tries to solve for it. It really looks at a variety of variables, including infrastructure operating model and fundamentally what client's business outcomes, um, uh, our clients are, are looking for and, and identifies the optimal solution for what they need. And we assign this to accelerate and we mentioned the pandemic. One of the big focus now is to accelerate. And so we worked through a three-step process. The first is scanning and assessing our client's infrastructure, their data landscape, their application. Second, we use our automated artificial intelligence engine to interact with. We have a wide variety and library of a collective plot expertise. And we look to recommend what is the enterprise architecture and solution. And then third, before we aligned with our clients, we look to simulate and test this scaled up model. And the simulation gives our clients a way to see what cloud is going to look like, feel like and how it's going to transform their business before they go there. >>Tell us a little bit about that in real life. Now as a company, so many of people are working remotely having to collaborate, uh, not in real life. How is that helping them right now? >>So, um, the, the pandemic has put a tremendous strain on systems, uh, because of the demand on those systems. And so we talk about resiliency. We also now need to collaborate across data across people. Um, I think all of us are calling from a variety of different places where our last year we were all at the VA cube itself. Um, and, and cloud technologies such as teams, zoom that we're we're leveraging now has fundamentally accelerated and clients are looking to onboard this for their capabilities. They're trying to accelerate their journey. They realize that now the cloud is what is going to become important for them to differentiate. Once we come out of the pandemic and the ability to collaborate with their employees, their partners, and their clients through these systems is becoming a true business differentiator for our clients. >>Keisha, I want to talk with you now about my navs multiple capabilities, um, and helping clients design and navigate their cloud journeys. Tell us a little bit about the green cloud advisor capability and its significance, particularly as so many companies are thinking more deeply and thoughtfully about sustainability. >>Yes. So since the launch of my lab, we continue to enhance, uh, capabilities for our clients. One of the significant, uh, capabilities that we have enabled is the being taught advisor today. You know, Rebecca, a lot of the businesses are more environmentally aware and are expanding efforts to decrease power consumption, uh, and obviously carbon emissions and, uh, and run a sustainable operations across every aspect of the enterprise. Uh, as a result, you're seeing an increasing trend in adoption of energy, efficient infrastructure in the global market. And one of the things that we did a lot of research we found out is that there's an ability to influence our client's carbon footprint through a better cloud solution. And that's what the internet brings to us, uh, in, in terms of a lot of the client connotation that you're seeing in Europe, North America and others, lot of our clients are accelerating to a green cloud strategy to unlock beta financial, societal and environmental benefit, uh, through obviously cloud-based circular, operational, sustainable products and services. That is something that we are enhancing my now, and we are having active client discussions at this point of time. >>So Tristan, tell us a little bit about how this capability helps clients make greener decisions. >>Yeah. Um, well, let's start about the investments from the cloud providers in renewable and sustainable energy. Um, they have most of the hyperscalers today, um, have been investing significantly on data centers that are run on renewable energy, some incredibly creative constructs on the how to do that. And sustainability is there for a key, um, key item of importance for the hyperscalers and also for our clients who now are looking for sustainable energy. And it turns out this marriage is now possible. I can, we marry the, the green capabilities of the comm providers with a sustainability agenda of our clients. And so what we look into the way the mine EF works is it looks at industry benchmarks and evaluates our current clients, um, capabilities and carpet footprint leveraging their existing data centers. We then look to model from an end-to-end perspective, how the, their journey to the cloud leveraging sustainable and, um, and data centers with renewable energy. We look at how their solution will look like and, and quantify carbon tax credits, um, improve a green index score and provide quantifiable, um, green cloud capabilities and measurable outcomes to our clients, shareholders, stakeholders, clients, and customers. Um, and our green plot advisers sustainability solutions already been implemented at three clients. And in many cases in two cases has helped them reduce the carbon footprint by up to 400% through migration from their existing data center to green cloud. Very, very, >>That is remarkable. Now tell us a little bit about the kinds of clients. Is this, is this more interesting to clients in Europe? Would you say that it's catching on in the United States? Where, what is the breakdown that you're seeing right now? >>Sustainability is becoming such a global agenda and we're seeing our clients, um, uh, tie this and put this at board level, um, uh, agenda and requirements across the globe. Um, Europe has specific constraints around data sovereignty, right, where they need their data in country, but from a green, a sustainability agenda, we see clients across all our markets, North America, Europe, and our growth markets adopt this. And we have seen case studies and all three months. >>Keisha, I want to bring you back into the conversation. Talk a little bit about how MindUP ties into Accenture's cloud first strategy, your Accenture's CEO, Julie Sweet has talked about post COVID leadership requiring every business to become a cloud first business. Tell us a little bit about how this ethos is in Accenture and how you're sort of looking outward with it too. >>So Rebecca mine is the launch pad, uh, to a cloud first transformation for our clients. Uh, Accenture, see your jewelry suite, uh, you know, shared the Accenture cloud first and our substantial investment demonstrate our commitment and is delivering greater value for our clients when they need it the most. And with the digital transformation requiring cloud at scale, you know, we're seeing that in the post COVID leadership, it requires that every business should become a cloud business. And my nap helps them get there by evaluating the cloud landscape, navigating the complexity, modeling architecting and simulating an optimal cloud solution for our clients. And as Justin was sharing a greener cloud. >>So Tristan, talk a little bit more about some of the real life use cases in terms of what are we, what are clients seeing? What are the results that they're having? >>Yes. Thank you, Rebecca. I would say two key things right around my neck. The first is the iterative process. Clients don't want to wait, um, until they get started, they want to get started and see what their journey is going to look like. And the second is fundamental acceleration, dependent make, as we talked about, has accelerated the need to move to cloud very quickly. And my nav is there to do that. So how do we do that? First is generating the business cases. Clients need to know in many cases that they have a business case by business case, we talk about the financial benefits, as well as the business outcomes, the green, green clot impact sustainability impacts with minus. We can build initial recommendations using a basic understanding of their environment and benchmarks in weeks versus months with indicative value savings in the millions of dollars arranges. >>So for example, very recently, we worked with a global oil and gas company, and in only two weeks, we're able to provide an indicative savings for $27 million over five years. This enabled the client to get started, knowing that there is a business case benefit and then iterate on it. And this iteration is, I would say the second point that is particularly important with my nav that we've seen in bank, the clients, which is, um, any journey starts with an understanding of what is the application landscape and what are we trying to do with those, these initial assessments that used to take six to eight weeks are now taking anywhere from two to four weeks. So we're seeing a 40 to 50% reduction in the initial assessment, which gets clients started in their journey. And then finally we've had discussions with all of the hyperscalers to help partner with Accenture and leverage mine after prepared their detailed business case module as they're going to clients. And as they're accelerating the client's journey, so real results, real acceleration. And is there a journey? Do I have a business case and furthermore accelerating the journey once we are by giving the ability to work in iterative approach. >>I mean, it sounds as though that the company that clients and and employees are sort of saying, this is an amazing time savings look at what I can do here in, in so much in a condensed amount of time, but in terms of getting everyone on board, one of the things we talked about last time we met, uh, Tristan was just how much, uh, how one of the obstacles is getting people to sign on and the new technologies and new platforms. Those are often the obstacles and struggles that companies face. Have you found that at all? Or what is sort of the feedback that you're getting from employers? >>Sorry. Yes. We clearly, there are always obstacles to a cloud journey. If there were an obstacles, all our clients would be, uh, already fully in the cloud. What man I gives the ability is to navigate through those, to start quickly. And then as we identify obstacles, we can simulate what things are going to look like. We can continue with certain parts of the journey while we deal with that obstacle. And it's a fundamental accelerator. Whereas in the past one, obstacle would prevent a class from starting. We can now start to address the obstacles one at a time while continuing and accelerating the contrary. That is the fundamental difference. >>Kishor I want to give you the final word here. Tell us a little bit about what is next for Accenture might have and what we'll be discussing next year at the Accenture executive summit >>Sort of echo, we are continuously evolving with our client needs and reinventing, reinventing for the future. For mine, as I've been taught advisor, our plan is to help our clients reduce carbon footprint and again, migrate to a green cloud. Uh, and additionally, we're looking at, you know, two capabilities, uh, which include sovereign cloud advisor, uh, with clients, especially in, in Europe and others are under pressure to meet, uh, stringent data norms that Kristen was talking about. And the sovereign cloud advisor health organization to create an architecture cloud architecture that complies with the green. Uh, I would say the data sovereignty norms that is out there. The other element is around data to cloud. We are seeing massive migration, uh, for, uh, for a lot of the data to cloud. And there's a lot of migration hurdles that come within that. Uh, we have expanded mine app to support assessment capabilities, uh, for, uh, assessing applications, infrastructure, but also covering the entire state, including data and the code level to determine the right cloud solution. So we are, we are pushing the boundaries on what mine app can do with mine. Have you created the ability to take the guesswork out of cloud navigate the complexity? We are roaring risks costs, and we are, you know, achieving client's static business objectives while building a sustainable alerts with being cloud >>Any platform that can take some of the guesswork out of the future. I'm I'm onboard with. Thank you so much, Tristin and Kishore. This has been a great conversation. >>Thank you. >>Stay tuned for more of the cubes coverage of the Accenture executive summit. I'm Rebecca Knight from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hey, welcome back to the cubes coverage of 80 us reinvent 2020 virtual centric executive summit. The two great guests here to break down the analysis of the relationship with cloud and essential Brian bowhead director ahead of a century 80. It was business group at Amazon web services. And Andy T a B G the M is essentially Amazon business group lead managing director at Accenture. Uh, I'm sure you're super busy and dealing with all the action, Brian. Great to see you. Thanks for coming on. So thank you. You guys essentially has been in the spotlight this week and all through the conference around this whole digital transformation, essentially as business group is celebrating its fifth anniversary. What's new, obviously the emphasis of next gen post COVID generation, highly digital transformation, a lot happening. You got your five-year anniversary, what's new. >>Yeah, it, you know, so if you look back, it's exciting. Um, you know, so it was five years ago. Uh, it was actually October where we, where we launched the Accenture AWS business group. And if we think back five years, I think we're still at the point where a lot of customers were making that transition from, you know, should I move to cloud to how do I move to cloud? Right? And so that was one of the reasons why we launched the business group. And since, since then, certainly we've seen that transition, right? Our conversations today are very much around how do I move to cloud, help me move, help me figure out the business case and then pull together all the different pieces so I can move more quickly, uh, you know, with less risk and really achieve my business outcomes. And I would say, you know, one of the things too, that's, that's really changed over the five years. >>And what we're seeing now is when we started, right, we were focused on migration data and IOT as the big three pillars that we launched with. And those are still incredibly important to us, but just the breadth of capability and frankly, the, the, the breadth of need that we're seeing from customers. And obviously as AWS has matured over the years and launched our new capabilities, we're Eva with Accenture and in the business group, we've broadened our capabilities and deepened our capabilities over the, over the last five years as well. For instance, this year with, with COVID, especially, it's really forced our customers to think differently about their own customers or their citizens, and how do they service those citizens? So we've seen a huge acceleration around customer engagement, right? And we powered that with Accenture customer engagement platform powered by ADA, Amazon connect. And so that's been a really big trend this year. And then, you know, that broadens our capability from just a technical discussion to one where we're now really reaching out and, and, um, and helping transform and modernize that customer and citizen experience as well, which has been exciting to see. >>Yeah, Andy, I want to get your thoughts here. We've been reporting and covering essentially for years. It's not like it's new to you guys. I mean, five years is a great anniversary. You know, check is good relationship, but you guys have been doing the work you've been on the trend line. And then this hits and Andy said on his keynote and I thought he said it beautifully. And he even said it to me in my one-on-one interview with them was it's on full display right now, the whole digital transformation, everything about it is on full display and you're either were prepared for it or you kind of word, and you can see who's there. You guys have been prepared. This is not new. So give us the update from your perspective, how you're taking advantage of this, of this massive shift, highly accelerated digital transformation. >>Well, I think, I think you can be prepared, but you've also got to be prepared to always sort of, I think what we're seeing in, in, um, in, in, in, in recent times and particularly 20 w what is it I think today there are, um, full sense of the enterprise workloads, the cloud, um, you know, that leaves 96 percentile now for him. Um, and I, over the next four to >>Five years, um, we're going to see that sort of, uh, acceleration to the, to the cloud pick up, um, this year is, as Andy touched on, I think, uh, uh, on Tuesday in his, I think the pandemic is a forcing function, uh, for companies to, to really pause and think about everything from, from, you know, how they, um, manage that technology to infrastructure, to just to carotenoids where the data sets to what insights and intelligence that getting from that data. And then eventually even to, to the talent, the talent they have in the organization and how they can be competitive, um, their culture, their culture of innovation, of invention and reinvention. And so I think, I think, you know, when you, when you think of companies out there faced with these challenges, it, it forces us, it forces AWS, it forces AEG to come together and think through how can we help create value for them? How can we help help them move from sort of just causing and rethinking to having real plans in an action and that taking them, uh, into, into implementation. And so that's, that's what we're working on. Um, I think over the next five years, we're looking to just continue to come together and help these, these companies get to the cloud and get the value from the cloud because it's beyond just getting to the cloud attached to them and living in the cloud and, and getting the value from it. >>It's interesting. Andy was saying, don't just put your toe in the water. You got to go beyond the toe in the water kind of approach. Um, I want to get to that large scale cause that's the big pickup this week that I kind of walked away with was it's large scale. Acceleration's not just toe in the water experimentation. Can you guys share, what's causing this large scale end to end enterprise transformation? And what are some of the success criteria have you seen for the folks who have done that? >>Yeah. And I'll, I'll, I'll start. And at the end you can buy a lawn. So, you know, it's interesting if I look back a year ago at re-invent and when I did the cube interview, then we were talking about how the ABG, we were starting to see this shift of customers. You know, we've been working with customers for years on a single of what I'll call a single-threaded programs, right. We can do a migration, we could do SAP, we can do a data program. And then even last year, we were really starting to see customers ask. The question is like, what kind of synergies and what kind of economies of scale do I get when I start bringing these different threads together, and also realizing that it's, you know, to innovate for the business and build new applications, new capabilities. Well, that then is going to inform what data you need to, to hydrate those applications, right? Which then informs your data strategy while a lot of that data is then also embedded in your underlying applications that sit on premises. So you should be thinking through how do you get those applications into the cloud? So you need to draw that line through all of those layers. And that was already starting last year. And so last year we launched the joint transformation program with AEG. And then, so we were ready when this year happened and then it was just an acceleration. So things have been happening faster than we anticipated, >>But we knew this was going to be happening. And luckily we've been in a really good position to help some of our customers really think through all those different layers of kind of pyramid as we've been calling it along with the talent and change pieces, which are also so important as you make this transformation to cloud >>Andy, what's the success factors. Andy Jassy came on stage during the partner day, a surprise fireside chat with Doug Hume and talking about this is really an opportunity for partners to, to change the business landscape with enablement from Amazon. You guys are in a pole position to do that in the marketplace. What's the success factors that you see, >>Um, really from three, three fronts, I'd say, um, w one is the people. Um, and, and I, I, again, I think Andy touched on sort of eight, uh, success factors, uh, early in the week. And for me, it's these three areas that it sort of boils down to these three areas. Um, one is the, the, the, the people, uh, from the leaders that it's really important to set those big, bold visions point the way. And then, and then, you know, set top down goals. How are we going to measure Z almost do get what you measure, um, to be, you know, beyond the leaders, to, to the right people in the right position across the company. We we're finding a key success factor for these end to end transformations is not just the leaders, but you haven't poached across the company, working in a, in a collaborative, shared, shared success model, um, and people who are not afraid to, to invent and fail. >>And so that takes me to perhaps the second point, which is the culture, um, it's important, uh, with finding for the right conditions to be set in the company that enabled, uh, people to move at pace, move at speed, be able to fail fast, um, keep things very, very simple and just keep iterating and that sort of culture of iteration and improvement versus seeking perfection is, is super important for, for success. And then the third part of maybe touch on is, is partners. Um, I think, you know, as we move forward over the next five years, we're going to see an increasing number of players in the ecosystem in the enterprise and state. Um, you're going to see more and more SAS providers. And so it's important for companies and our joint clients out there to pick partners like, um, like AWS or, or Accenture or others, but to pick partners who have all worked together and you have built solutions together, and that allows them to get speed to value quicker. It allows them to bring in pre-assembled solutions, um, and really just drive that transformation in a quicker, it sorts of manner. >>Yeah, that's a great point worth calling out, having that partnership model that's additive and has synergy in the cloud, because one of the things that came out of this this week, this year is reinvented, is there's new things going on in the public cloud, even though hybrid is an operating model, outpost and super relevant. There, there are benefits for being in the cloud and you've got partners API, for instance, and have microservices working together. This is all new, but I got, I got to ask that on that thread, Andy, where did you see your customers going? Because I think, you know, as you work backwards from the customers, you guys do, what's their needs, how do you see them? W you know, where's the puck going? Where can they skate where the puck's going, because you can almost look forward and say, okay, I've got to build modern apps. I got to do the digital transformation. Everything is a service. I get that, but what are they, what solutions are you building for them right now to get there? >>Yeah. And, and of course, with, with, you know, industries blurring and multiple companies, it's always hard to boil down to the exact situations, but you could probably look at it from a sort of a thematic lens. And what we're seeing is as the cloud transformation journey picks up, um, from us perspective, we've seen a material shift in the solutions and problems that we're trying to address with clients that they are asking for us, uh, to, to help, uh, address is no longer just the back office, where you're sort of looking at cost and efficiency and, um, uh, driving gains from that perspective. It's beyond that, it's now materially the top line. It's, how'd you get the driving to the, you know, speed to insights, how'd you get them decomposing, uh, their application set in order to derive those insights. Um, how'd you get them, um, to, to, um, uh, sort of adopt leading edge industry solutions that give them that jump start, uh, and that accelerant to winning the customers, winning the eyeballs. >>Um, and then, and then how'd, you help drive the customer experience. We're seeing a lot of push from clients, um, or ask for help on how do I optimize my customer experience in order to retain my eyeballs. And then how do I make sure I've got a soft self-learning ecosystem of play, um, where, uh, you know, it's not just a practical experience that I can sort of keep learning and iterating, um, how I treat my, my customers, um, and a lot of that, um, that still self-learning, that comes from, you know, putting in intelligence into your, into your systems, getting an AI and ML in there. And so, as a result of that work, we're seeing a lot of push and a lot of what we're doing, uh, is pouring investment into those areas. And then finally, maybe beyond the bottom line, and the top line is how do you harden that and protect that with, um, security and resilience? So I'll probably say those are the three areas. John, >>You know, the business model side, obviously the enablement is what Amazon has. Um, we see things like SAS factory coming on board and the partner network, obviously a century is a big, huge partner of you guys. Um, the business models there, you've got I, as, as doing great with chips, you have this data modeling this data opportunity to enable these modern apps. We heard about the partner strategy for me and D um, talking to me now about how can partners within even Accenture, w w what's the business model, um, side on your side that you're enabling this. Can you just share your thoughts on that? >>Yeah, yeah. And so it's, it's interesting. I think I'm going to build it and then build a little bit on some of the things that Andy really talked about there, right? And that we, if you think of that from the partnership, we are absolutely helping our customers with kind of that it modernization piece. And we're investing a lot and there's hard work that needs to get done there. And we're investing a lot as a partnership around the tools, the assets and the methodology. So in AWS and Accenture show up together as AEG, we are executing office single blueprint with a single set of assets, so we can move fast. So we're going to continue to do that with all the hybrid announcements from this past week, those get baked into that, that migration modernization theme, but the other really important piece here as we go up the stack, Andy mentioned it, right? >>The data piece, like so much of what we're talking about here is around data and insights. Right? I did a cube interview last week with, uh, Carl hick. Um, who's the CIO from Takeda. And if you hear Christophe Weber from Takeda talk, he talks about Takeda being a data company, data and insights company. So how do we, as a partnership, again, build the capabilities and the platforms like with Accenture's applied insights platform so that we can bootstrap and really accelerate our client's journey. And then finally, on the innovation on the business front, and Andy was touching on some of these, we are investing in industry solutions and accelerators, right? Because we know that at the end of the day, a lot of these are very similar. We're talking about ingesting data, using machine learning to provide insights and then taking action. So for instance, the cognitive insurance platform that we're working together on with Accenture, if they give out property and casualty claims and think about how do we enable touchless claims using machine learning and computer vision that can assess based on an image damage, and then be able to triage that and process it accordingly, right? >>Using all the latest machine learning capabilities from AWS with that deep, um, AI machine learning data science capability from Accenture, who knows all those algorithms that need to get built and build that library by doing that, we can really help these insurance companies accelerate their transformation around how they think about claims and how they can speed those claims on behalf of their policy holder. So that's an example of a, kind of like a bottom to top, uh, view of what we're doing in the partnership to address these new needs. >>That's awesome. Andy, I want to get back to your point about culture. You mentioned it twice now. Um, talent is a big part of the game here. Andy Jassy referenced Lambda. The next generation developers were using Lambda. He talked about CIO stories around, they didn't move fast enough. They lost three years. A new person came in and made it go faster. This is a new, this is a time for a certain kind of, um, uh, professional and individual, um, to, to be part of, um, this next generation. What's the talent strategy you guys have to attract and attain the best and retain the people. How do you do it? >>Um, you know, it's, it's, um, it's an interesting one. It's, it's, it's oftentimes a, it's, it's a significant point and often overlooked. Um, you know, people, people really matter and getting the right people, um, in not just in AWS or it, but then in our customers is super important. We often find that much of our discussions with, with our clients is centered around that. And it's really a key ingredient. As you touched on, you need people who are willing to embrace change, but also people who are willing to create new, um, to invent new, to reinvent, um, and to, to keep it very simple. Um, w we're we're we're seeing increasingly that you need people that have a sort of deep learning and a deep, uh, or deep desire to keep learning and to be very curious as, as they go along. Most of all, though, I find that, um, having people who are not willing or not afraid to fail is critical, absolutely critical. Um, and I think that that's, that's, uh, a necessary ingredient that we're seeing, um, our clients needing more off, um, because if you can't start and, and, and you can't iterate, um, you know, for fear of failure, you're in trouble. And, and I think Andy touched on that you, you know, where that CIO, that you referred to last three years, um, and so you really do need people who are willing to start not afraid to start, uh, and, uh, and not afraid to lead >>Was a gut check there. I just say, you guys have a great team over there. Everyone at the center I've interviewed strong, talented, and not afraid to lean in and, and into the trends. Um, I got to ask on that front cloud first was something that was a big strategic focus for Accenture. How does that fit into your business group? That's an Amazon focused, obviously they're cloud, and now hybrid everywhere, as I say, um, how does that all work it out? >>We're super excited about our cloud first initiative, and I think it fits it, um, really, uh, perfectly it's it's, it's what we needed. It's, it's, it's a, it's another accelerant. Um, if you think of count first, what we're doing is we're, we're putting together, um, uh, you know, capability set that will help enable him to and transformations as Brian touched on, you know, help companies move from just, you know, migrating to, to, to modernizing, to driving insights, to bringing in change, um, and, and, and helping on that, on that talent side. So that's sort of component number one is how does Accenture bring the best, uh, end to end transformation capabilities to our clients? Number two is perhaps, you know, how do we, um, uh, bring together pre-assembled as Brian touched on pre-assembled industry offerings to help as an accelerant, uh, for our, for our customers three years, as we touched on earlier is, is that sort of partnership with the ecosystem. >>We're going to see an increasing number of SAS providers in an estate, in the enterprise of snakes out there. And so, you know, panto wild cloud first, and our ABG strategy is to increase our touch points in our integrations and our solutions and our offerings with the ecosystem partners out there, the ISP partners out, then the SAS providers out there. And then number four is really about, you know, how do we, um, extend the definition of the cloud? I think oftentimes people thought of the cloud just as sort of on-prem and prem. Um, but, but as Andy touched on earlier this week, you know, you've, you've got this concept of hybrid cloud and that in itself, um, uh, is, is, is, you know, being redefined as well. You know, when you've got the intelligent edge and you've got various forms of the edge. Um, so that's the fourth part of, of, uh, of occupied for strategy. And for us was super excited because all of that is highly relevant for ABG, as we look to build those capabilities as industry solutions and others, and as when to enable our customers, but also how we, you know, as we, as we look to extend how we go to market, I'll join tele PS, uh, in, uh, in our respective skews and products. >>Well, what's clear now is that people now realize that if you contain that complexity, the upside is massive. And that's great opportunity for you guys. We got to get to the final question for you guys to weigh in on, as we wrap up next five years, Brian, Andy weigh in, how do you see that playing out? What do you see this exciting, um, for the partnership and the cloud first cloud, everywhere cloud opportunities share some perspective. >>Yeah, I, I think, you know, just kinda building on that cloud first, right? What cloud first, and we were super excited when cloud first was announced and you know, what it signals to the market and what we're seeing in our customers, which has cloud really permeates everything that we're doing now. Um, and so all aspects of the business will get infused with cloud in some ways, you know, it, it touches on, on all pieces. And I think what we're going to see is just a continued acceleration and getting much more efficient about pulling together the disparate, what had been disparate pieces of these transformations, and then using automation using machine learning to go faster. Right? And so, as we started thinking about the stack, right, well, we're going to get, I know we are, as a partnership is we're already investing there and getting better and more efficient every day as the migration pieces and the moving the assets to the cloud are just going to continue to get more automated, more efficient. And those will become the economic engines that allow us to fund the differentiated, innovative activities up the stack. So I'm excited to see us kind of invest to make those, those, um, those bets accelerated for customers so that we can free up capital and resources to invest where it's going to drive the most outcome for their end customers. And I think that's going to be a big focus and that's going to have the industry, um, you know, focus. It's going to be making sure that we can >>Consume the latest and greatest of AWS as capabilities and, you know, in the areas of machine learning and analytics, but then Andy's also touched on it bringing in ecosystem partners, right? I mean, one of the most exciting wins we had this year, and this year of COVID is looking at the universe, looking at Massachusetts, the COVID track and trace solution that we put in place is a partnership between Accenture, AWS, and Salesforce, right? So again, bringing together three really leading partners who can deliver value for our customers. I think we're going to see a lot more of that as customers look to partnerships like this, to help them figure out how to bring together the best of the ecosystem to drive solutions. So I think we're going to see more of that as well. >>All right, Andy final word, your take >>Thinks of innovation is, is picking up, um, dismiss things are just going faster and faster. I'm just super excited and looking forward to the next five years as, as you know, the technology invention, um, comes out and continues to sort of set new standards from AWS. Um, and as we, as Accenture wringing, our industry capabilities, we marry the two. We, we go and help our customers super exciting time. >>Well, congratulations on the partnership. I want to say thank you to you guys, because I've reported a few times some stories around real successes around this COVID pandemic that you guys worked together on with Amazon that really changed people's lives. Uh, so congratulations on that too as well. I want to call that out. Thanks for coming >>Up. Thank you. Thanks for coming on. >>Okay. This is the cubes coverage, essentially. AWS partnership, part of a century executive summit at Atrius reinvent 2020 I'm John for your host. Thanks. >>You're watching from around the globe. It's the cube with digital coverage of AWS reinvent executive summit 2020, sponsored by Accenture and AWS. >>Hello, and welcome back to the cubes coverage of AWS reinvent 2020. This is special programming for the century executive summit, where all the thought leaders going to extract the signal from the nose to share with you their perspective of this year's reinvent conference, as it respects the customers' digital transformation. Brian Bohan is the director and head of a center. ADA was business group at Amazon web services. Brian, great to see you. And Chris Wegman is the, uh, center, uh, Amazon business group technology lead at Accenture. Um, guys, this is about technology vision, this, this conversation, um, Chris, I want to start with you because you, Andy Jackson's keynote, you heard about the strategy of digital transformation, how you gotta lean into it. You gotta have the guts to go for it, and you got to decompose. He went everywhere. So what, what did you hear? What was striking about the keynote? Because he covered a lot of topics. Yeah. You know, it >>Was Epic, uh, as always for Mandy, a lot of topics, a lot to cover in the three hours. Uh, there was a couple of things that stood out for me, first of all, hybrid, uh, the concept, the new concept of hybrid and how Andy talked about it, you know, uh, bringing the compute and the power to all parts of the enterprise, uh, whether it be at the edge or are in the big public cloud, uh, whether it be in an outpost or wherever it might be right with containerization now, uh, you know, being able to do, uh, Amazon containerization in my data center and that that's, that's awesome. I think that's gonna make a big difference, all that being underneath the Amazon, uh, console and billing and things like that, which is great. Uh, I'll also say the, the chips, right. And I know compute is always something that, you know, we always kind of take for granted, but I think again, this year, uh, Amazon and Andy really focused on what they're doing with the chips and PR and compute, and the compute is still at the heart of everything in cloud. And that continued advancement is, is making an impact and will make a continue to make a big impact. >>Yeah, I would agree. I think one of the things that really, I mean, the container thing was, I think really kind of a nuanced point when you got Deepak sing on the opening day with Andy Jassy and he's, he runs a container group over there, you know, small little team he's on the front and front stage. That really is the key to the hybrid. And I think this showcases this new layer and taking advantage of the graviton two chips that, which I thought was huge. Brian, this is really a key part of the platform change, not change, but the continuation of AWS higher level servers building blocks that provide more capabilities, heavy lifting as they say, but the new services that are coming on top really speaks to hybrid and speaks to the edge. >>It does. Yeah. And it, it, you know, I think like Andy talks about, and we talk about, I, you know, we really want to provide choice to our customers, uh, first and foremost, and you can see that and they re uh, services. We have, we can see it in the, the hybrid options that Chris talked about, being able to run your containers through ECS or EKS anywhere I just get to the customer's choice. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things will certainly outpost. Um, right. So now I'll post those launched last year, but then with the new form factors, uh, and then you look at services like Panorama, right? Being able to take computer vision and embed machine learning and computer vision, and do that as a managed capability at the edge, um, for customers. >>And so we see this across a number of industries. And so what we're really thinking about is customers no longer have to make trade-offs and have to think about those, those choices that they can really deploy, uh, natively in the cloud. And then they can take those capabilities, train those models, and then deploy them where they need to, whether that's on premises or at the edge, you know, whether it be in a factory or retail environment. When we start, I think we're really well positioned when, um, you know, hopefully next year we started seeing the travel industry rebound, um, and the, the need, you know, more than ever really to, uh, to kind of rethink about how we kind of monitor and make those environments safe. Having this kind of capability at the edge is really going to help our customers as, as we come out of this year and hopefully rebound next year. >>Yeah. Chris, I want to go back to you for a second. It's hard to hard to pick your favorite innovation from the keynote, because, you know, just reminded me that Brian just reminded me of some things I forgot happened. It was like a buffet of innovation. Some keynotes have one or two, it was like 20, you got the industrial piece that was huge. Computer vision machine learning. That's just a game changer. The connect thing came out of nowhere, in my opinion, I mean, it's a call center technology. This is boring as hell. What are you gonna do with that? It turns out it's a game changer. It's not about the calls with the contact and that's discern intermediating, um, in the stack as well. So again, a feature that looks old is actually new and relevant. What's your, what was your favorite, um, innovation? >>Uh, it it's, it's, it's hard to say. I will say my personal favorite was the, the maca last. I, I just, I think that is a phenomenal, um, uh, just addition, right? And the fact that AWS is, has worked with Apple to integrate the Nitra chip into, into, uh, you know, the iMac and offer that out. Um, you know, a lot of people are doing development, uh, on for ILS and that stuff. And that there's just gonna be a huge benefit, uh, for the development teams. But, you know, I will say, I'll come back to connect you. You mentioned it. Um, you know, but you're right. It was a, it's a boring area, but it's an area that we've seen huge success with since, since connect was launched and the additional features and the Amazon continues to bring, you know, um, obviously with, with the pandemic and now that, you know, customer engagement through the phone, uh, through omni-channel has just been critical for companies, right. >>And to be able to have those agents at home, working from home versus being in the office, it was a huge, huge advantage for, for several customers that are using connect. You know, we, we did some great stuff with some different customers, but the continue technology, like you said, the, you know, the call translation and during a call to be able to pop up those key words and have a, have a supervisor, listen is awesome. And a lot of that was some of that was already being done, but we were stitching multiple services together. Now that's right out of the box. Um, and that Google's location is only going to make that go faster and make us to be able to innovate faster for that piece of the business. >>It's interesting, you know, not to get all nerdy and, and business school life, but you've got systems of records, systems of engagement. If you look at the call center and the connect thing, what got my attention was not only the model of disintermediating, that part of the engagement in the stack, but what actually cloud does to something that's a feature or something that could be an element, like say, call center, you old days of, you know, calling an 800 number, getting some support you got in chip, you have machine learning, you actually have stuff in the, in the stack that actually makes that different now. So you w you know, the thing that impressed me was Andy was saying, you could have machine learning, detect pauses, voice inflections. So now you have technology making that more relevant and better and different. So a lot going on, this is just one example of many things that are happening from a disruption innovation standpoint. W what do you guys, what do you guys think about that? And is that like getting it right? Can you share it? >>I think, I think, I think you are right. And I think what's implied there and what you're saying, and even in the, you know, the macro S example is the ability if we're talking about features, right. Which by themselves, you're saying, Oh, wow, what's, what's so unique about that, but because it's on AWS and now, because whether you're a developer working on, you know, w with Mac iOS and you have access to the 175 plus services, that you can then weave into your new applications, talk about the connect scenario. Now we're embedding that kind of inference and machine learning to do what you say, but then your data Lake is also most likely running in AWS, right? And then the other channels, whether they be mobile channels or web channels, or in store physical channels, that data can be captured in that same machine learning could be applied there to get that full picture across the spectrum. Right? So that's the, that's the power of bringing together on AWS to access to all those different capabilities of services, and then also the where the data is, and pulling all that together, that for that end to end view, okay, >>You guys give some examples of work you've done together. I know this stuff we've reported on. Um, in the last session we talked about some of the connect stuff, but that kind of encapsulates where this, where this is all going with respect to the tech. >>Yeah. I think one of the, you know, it was called out on Doug's partner summit was, you know, is there a, uh, an SAP data Lake accelerator, right? Almost every enterprise has SAP, right. And SAP getting data out of SAP has always been a challenge, right. Um, whether it be through, you know, data warehouses and AWS, sorry, SAP BW, you know, what we've focused on is, is getting that data when you're on have SAP on AWS getting that data into the data Lake, right. And getting it into, into a model that you can pull the value out of the customers can pull the value out, use those AI models. Um, so that was one thing we worked on in the last 12 months, super excited about seeing great success with customers. Um, you know, a lot of customers had ideas. They want to do this. They had different models. What we've done is, is made it very, uh, simplified, uh, framework that allows customers to do it very quickly, get the data out there and start getting value out of it and iterating on that data. Um, we saw customers are spending way too much time trying to stitch it all together and trying to get it to work technically. Uh, and we've now cut all that out and they can immediately start getting down to, to the data and taking advantage of those, those different, um, services are out there by AWS. >>Brian, you want to weigh in as things you see as relevant, um, builds that you guys done together that kind of tease out the future and connect the dots to what's coming. >>Uh, I, you know, I'm going to use a customer example. Uh, we worked with, um, and it just came out with, with Unilever around their blue air connected, smart air purifier. And what I think is interesting about that, I think it touches on some of the themes we're talking about, as well as some of the themes we talked about in the last session, which is we started that program before the pandemic. Um, and, but, you know, Unilever recognized that they needed to differentiate their product in the marketplace, move to more of a services oriented business, which we're seeing as a trend. We, uh, we enabled this capability. So now it's a smart air purifier that can be remote manage. And now in the pandemic head, they are in a really good position, obviously with a very relevant product and capability, um, to be used. And so that data then, as we were talking about is going to reside on the cloud. And so the learning that can now happen about usage and about, you know, filter changes, et cetera, can find its way back into future iterations of that valve, that product. And I think that's, that's keeping with, you know, uh, Chris was talking about where we might be systems of record, like in SAP, how do we bring those in and then start learning from that data so that we can get better on our future iterations? >>Hey, Chris, on the last segment we did on the business mission, um, session, Andy Taylor from your team, uh, talked about partnerships within a century and working with other folks. I want to take that now on the technical side, because one of the things that we heard from, um, Doug's, um, keynote and that during the partner day was integrations and data were two big themes. When you're in the cloud, technically the integrations are different. You're going to get unique things in the public cloud that you're just not going to get on premise access to other cloud native technologies and companies. How has that, how do you see the partnering of Accenture with people within your ecosystem and how the data and the integration play together? What's your vision? >>Yeah, I think there's two parts of it. You know, one there's from a commercial standpoint, right? So marketplace, you know, you, you heard Dave talk about that in the, in the partner summit, right? That marketplace is now bringing together this ecosystem, uh, in a very easy way to consume by the customers, uh, and by the users and bringing multiple partners together. And we're working with our ecosystem to put more products out in the marketplace that are integrated together, uh, already. Um, you know, I think one from a technical perspective though, you know, if you look at Salesforce, you know, we talked a little earlier about connect another good example, technically underneath the covers, how we've integrated connect and Salesforce, some of it being prebuilt by AWS and Salesforce, other things that we've added on top of it, um, I think are good examples. And I think as these ecosystems, these IFCs put their products out there and start exposing more and more API APIs, uh, on the Amazon platform, make opening it up, having those, those prebuilt network connections there between, you know, the different VPCs and the different areas within, within a customer's network. >>Um, and having them, having that all opened up and connected and having all that networking done underneath the covers. You know, it's one thing to call the API APIs. It's one thing to have access to those. And that's been a big focus of a lot of, you know, ISBNs and customers to build those API APIs and expose them, but having that network infrastructure and being able to stay within the cloud within AWS to make those connections, the past that data, we always talk about scale, right? It's one thing if I just need to pass like a, you know, a simple user ID back and forth, right? That's, that's fine. We're not talking massive data sets, whether it be seismic data or whatever it be passing those of those large, those large data sets between customers across the Amazon network is going to, is going to open up the world. >>Yeah. I see huge possibilities there and love to keep on this story. I think it's going to be important and something to keep track of. I'm sure you guys will be on top of it. You know, one of the things I want to, um, dig into with you guys now is Andy had kind of this philosophy philosophical thing in his keynote, talk about societal change and how tough the pandemic is. Everything's on full display. Um, and this kind of brings out kind of like where we are and the truth. You look at the truth, it's a virtual event. I mean, it's a website and you got some sessions out there with doing remote best weekend. Um, and you've got software and you've got technology and, you know, the concept of a mechanism it's software, it does something, it does a purpose. Essentially. You guys have a concept called living systems where growth strategy powered by technology. How do you take the concept of a, of a living organism or a system and replace the mechanism, staleness of computing and software. And this is kind of an interesting, because we're on the cusp of a, of a major inflection point post COVID. I get the digital transformation being slow that's yes, that's happening. There's other things going on in society. What do you guys think about this living systems concept? >>Yeah, so I, you know, I'll start, but, you know, I think the living system concept, um, you know, it started out very much thinking about how do you rapidly change the system, right? And, and because of cloud, because of, of dev ops, because of, you know, all these software technologies and processes that we've created, you know, that's where it started it, making it much easier to make it a much faster being able to change rapidly, but you're right. I think as you now bring in more technologies, the AI technology self-healing technologies, again, you're hurting Indian in his keynote, talk about, you know, the, the systems and services they're building to the tech problems and, and, and, and give, uh, resolve those problems. Right. Obviously automation is a big part of that living systems, you know, being able to bring that all together and to be able to react in real time to either what a customer, you know, asks, um, you know, either through the AI models that have been generated and turning those AI models around much faster, um, and being able to get all the information that came came in in the last 20 minutes, right. >>You know, society's moving fast and changing fast. And, you know, even in one part of the world, if, um, something, you know, in 10 minutes can change and being able to have systems to react to that, learn from that and be able to pass that on to the next country, especially in this world with COVID and, you know, things changing very quickly with quickly and, and, and, um, diagnosis and, and, um, medical response, all that so quickly to be able to react to that and have systems pass that information learned from that information is going to be critical. >>That's awesome. Brian, one of the things that comes up every year is, Oh, the cloud scalable this year. I think, you know, we've, we've talked on the cube before, uh, years ago, certainly with the censure and Amazon, I think it was like three or four years ago. Yeah. The clouds horizontally scalable, but vertically specialized at the application layer. But if you look at the data Lake stuff that you guys have been doing, where you have machine learning, the data's horizontally scalable, and then you got the specialization in the app changes that changes the whole vertical thing. Like you don't need to have a whole vertical solution or do you, so how has this year's um, cloud news impacted vertical industries because it used to be, Oh, the oil and gas financial services. They've got a team for that. We've got a stack for that. Not anymore. Is it going away? What's changing. Wow. >>I, you know, I think it's a really good question. And I don't think, I think what we're saying, and I was just on a call this morning talking about banking and capital markets. And I do think the, you know, the, the challenges are still pretty sector specific. Um, but what we do see is the, the kind of commonality, when we start looking at the, and we talked about it as the industry solutions that we're building as a partnership, most of them follow the pattern of ingesting data, analyzing that data, and then being able to, uh, provide insights and an actions. Right. So if you think about creating that yeah. That kind of common chassis of that ingest the data Lake and then the machine learning, can you talk about, you know, the announces around SageMaker and being able to manage these models, what changes then really are the very specific industries algorithms that you're, you're, you're writing right within that framework. And so we're doing a lot in connect is a good example of this too, where you look at it. Yeah. Customer service is a horizontal capability that we're building out, but then when you stop it into insurance or retail banking or utilities, there are nuances then that we then extend and build so that we meet the unique needs of those, those industries. And that's usually around those, those models. >>Yeah. And I think this year was the first reinvented. I saw real products coming out that actually solve that problem. And that was their last year SageMaker was kinda moving up the stack, but now you have apps embedding machine learning directly in, and users don't even know it's in there. I mean, Christmas is kind of where it's going. Right. I mean, >>Yeah. Announcements. Right. How many, how many announcements where machine learning is just embedded in? I mean, so, you know, code guru, uh, dev ops guru Panorama, we talked about, it's just, it's just there. >>Yeah. I mean, having that knowledge about the linguistics and the metadata, knowing the, the business logic, those are important specific use cases for the vertical and you can get to it faster. Right. Chris, how is this changing on the tech side, your perspective? Yeah. >>You know, I keep coming back to, you know, AWS and cloud makes it easier, right? None of this stuff, you know, all of this stuff can be done, uh, and has some of it has been, but you know, what Amazon continues to do is make it easier to consume by the developer, by the, by the customer and to actually embedded into applications much easier than it would be if I had to go set up the stack and build it all on that and, and, and, uh, embed it. Right. So it's, shortcutting that process. And again, as these products continue to mature, right. And some of the stuff is embedded, um, it makes that process so much faster. Uh, it makes it reduces the amount of work required by the developers, uh, the engineers to get there. So I I'm expecting, you're going to see more of this. >>Right. I think you're going to see more and more of these multi connected services by AWS that has a lot of the AIML, um, pre-configured data lakes, all that kind of stuff embedded in those services. So you don't have to do it yourself and continue to go up the stack. And we was talking about, Amazon's built for builders, right. But, you know, builders, you know, um, have been super specialized in, or we're becoming, you know, as engineers, we're being asked to be bigger and bigger and to be, you know, uh, be able to do more stuff. And I think, you know, these kinds of integrated services are gonna help us do that >>And certainly needed more. Now, when you have hybrid edge that are going to be operating with microservices on a cloud model, and with all those advantages that are going to come around the corner for being in the cloud, I mean, there's going to be, I think there's going to be a whole clarity around benefits in the cloud with all these capabilities and benefits cloud guru. Thanks my favorite this year, because it just points to why that could happen. I mean, that happens because of the cloud data. If you're on premise, you may not have a little cloud guru, you got to got to get more data. So, but they're all different edge certainly will come into your vision on the edge. Chris, how do you see that evolving for customers? Because that could be complex new stuff. How is it going to get easier? >>Yeah. It's super complex now, right? I mean, you gotta design for, you know, all the different, uh, edge 5g, uh, protocols are out there and, and, and solutions. Right. You know, Amazon's simplifying that again, to come back to simplification. Right. I can, I can build an app that, that works on any 5g network that's been integrated with AWS. Right. I don't have to set up all the different layers to get back to my cloud or back to my, my bigger data side. And I was kind of choking. I don't even know where to call the cloud anymore, big cloud, which is a central and I go down and then I've got a cloud at the edge. Right. So what do I call that? >>Exactly. So, you know, again, I think it is this next generation of technology with the edge comes, right. And we put more and more data at the edge. We're asking for more and more compute at the edge, right? Whether it be industrial or, you know, for personal use or consumer use, um, you know, that processing is gonna get more and more intense, uh, to be able to manage and under a single console, under a single platform and be able to move the code that I develop across that entire platform, whether I have to go all the way down to the, you know, to the very edge, uh, at the, at the 5g level, right? Or all the way into the bigger cloud and how that process, isn't there be able to do that. Seamlessly is going to be allow the speed of development that's needed. >>Well, you guys done a great job and no better time to be a techie or interested in technology or computer science or social science for that matter. This is a really perfect storm, a lot of problems to solve a lot of things, a lot of change happening, positive change opportunities, a lot of great stuff. Uh, final question guys, five years working together now on this partnership with AWS and Accenture, um, congratulations, you guys are in pole position for the next wave coming. Um, what's exciting. You guys, Chris, what's on your mind, Brian. What's, what's getting you guys pumped up >>Again. I come back to G you know, Andy mentioned it in his keynote, right? We're seeing customers move now, right. We're seeing, you know, five years ago we knew customers were going to get a new, this. We built a partnership to enable these enterprise customers to make that, that journey. Right. But now, you know, even more, we're seeing them move at such great speed. Right. Which is super excites me. Right. Because I can see, you know, being in this for a long time, now I can see the value on the other end. And I really, we've been wanting to push our customers as fast as they can through the journey. And now they're moving out of, they're getting, they're getting the religion, they're getting there. They see, they need to do it to change your business. So that's what excites me is just the excites me. >>It's just the speed at which we're, we're in a single movement. Yeah, yeah. I'd agree with, yeah, I'd agree with that. I mean, so, you know, obviously getting, getting customers to the cloud is super important work, and we're obviously doing that and helping accelerate that, it's it, it's what we've been talking about when we're there, all the possibilities that become available right. Through the common data capabilities, the access to the 175 some-odd AWS services. And I also think, and this is, this is kind of permeated through this week at re-invent is the opportunity, especially in those industries that do have an industrial aspect, a manufacturing aspect, or a really strong physical aspect of bringing together it and operational technology and the business with all these capabilities, then I think edge and pushing machine learning down to the edge and analytics at the edge is really going to help us do that. And so I'm super excited by all that possibility is I feel like we're just scratching the surface there, >>Great time to be building out. And you know, this is the time for re reconstruction. Re-invention big themes. So many storylines in the keynote, in the events. It's going to keep us busy here. It's looking at angle in the cube for the next year. Gentlemen, thank you for coming out. I really appreciate it. Thanks. Thank you. All right. Great conversation. You're getting technical. We could've go on another 30 minutes. Lot to talk about a lot of storylines here at AWS. Reinvent 2020 at the Centure executive summit. I'm John furrier. Thanks for watching.

>> Joy: Welcome to the Virtual Big Data Conference. Vertica is so excited to host this event. I'm Joy King, and I'll be your host for today's Big Data Conference Keynote Session. It's my honor and my genuine pleasure to lead Vertica's product and go-to-market strategy. And I'm so lucky to have a passionate and committed team who turned our Vertica BDC event, into a virtual event in a very short amount of time. I want to thank the thousands of people, and yes, that's our true number who have registered to attend this virtual event. We were determined to balance your health, safety and your peace of mind with the excitement of the Vertica BDC. This is a very unique event. Because as I hope you all know, we focus on engineering and architecture, best practice sharing and customer stories that will educate and inspire everyone. I also want to thank our top sponsors for the virtual BDC, Arrow, and Pure Storage. Our partnerships are so important to us and to everyone in the audience. Because together, we get things done faster and better. Now for today's keynote, you'll hear from three very important and energizing speakers. First, Colin Mahony, our SVP and General Manager for Vertica, will talk about the market trends that Vertica is betting on to win for our customers. And he'll share the exciting news about our Vertica 10 announcement and how this will benefit our customers. Then you'll hear from Amy Fowler, VP of strategy and solutions for FlashBlade at Pure Storage. Our partnership with Pure Storage is truly unique in the industry, because together modern infrastructure from Pure powers modern analytics from Vertica. And then you'll hear from John Yovanovich, Director of IT at AT&T, who will tell you about the Pure Vertica Symphony that plays live every day at AT&T. Here we go, Colin, over to you. >> Colin: Well, thanks a lot joy. And, I want to echo Joy's thanks to our sponsors, and so many of you who have helped make this happen. This is not an easy time for anyone. We were certainly looking forward to getting together in person in Boston during the Vertica Big Data Conference and Winning with Data. But I think all of you and our team have done a great job, scrambling and putting together a terrific virtual event. So really appreciate your time. I also want to remind people that we will make both the slides and the full recording available after this. So for any of those who weren't able to join live, that is still going to be available. Well, things have been pretty exciting here. And in the analytic space in general, certainly for Vertica, there's a lot happening. There are a lot of problems to solve, a lot of opportunities to make things better, and a lot of data that can really make every business stronger, more efficient, and frankly, more differentiated. For Vertica, though, we know that focusing on the challenges that we can directly address with our platform, and our people, and where we can actually make the biggest difference is where we ought to be putting our energy and our resources. I think one of the things that has made Vertica so strong over the years is our ability to focus on those areas where we can make a great difference. So for us as we look at the market, and we look at where we play, there are really three recent and some not so recent, but certainly picking up a lot of the market trends that have become critical for every industry that wants to Win Big With Data. We've heard this loud and clear from our customers and from the analysts that cover the market. If I were to summarize these three areas, this really is the core focus for us right now. We know that there's massive data growth. And if we can unify the data silos so that people can really take advantage of that data, we can make a huge difference. We know that public clouds offer tremendous advantages, but we also know that balance and flexibility is critical. And we all need the benefit that machine learning for all the types up to the end data science. We all need the benefits that they can bring to every single use case, but only if it can really be operationalized at scale, accurate and in real time. And the power of Vertica is, of course, how we're able to bring so many of these things together. Let me talk a little bit more about some of these trends. So one of the first industry trends that we've all been following probably now for over the last decade, is Hadoop and specifically HDFS. So many companies have invested, time, money, more importantly, people in leveraging the opportunity that HDFS brought to the market. HDFS is really part of a much broader storage disruption that we'll talk a little bit more about, more broadly than HDFS. But HDFS itself was really designed for petabytes of data, leveraging low cost commodity hardware and the ability to capture a wide variety of data formats, from a wide variety of data sources and applications. And I think what people really wanted, was to store that data before having to define exactly what structures they should go into. So over the last decade or so, the focus for most organizations is figuring out how to capture, store and frankly manage that data. And as a platform to do that, I think, Hadoop was pretty good. It certainly changed the way that a lot of enterprises think about their data and where it's locked up. In parallel with Hadoop, particularly over the last five years, Cloud Object Storage has also given every organization another option for collecting, storing and managing even more data. That has led to a huge growth in data storage, obviously, up on public clouds like Amazon and their S3, Google Cloud Storage and Azure Blob Storage just to name a few. And then when you consider regional and local object storage offered by cloud vendors all over the world, the explosion of that data, in leveraging this type of object storage is very real. And I think, as I mentioned, it's just part of this broader storage disruption that's been going on. But with all this growth in the data, in all these new places to put this data, every organization we talk to is facing even more challenges now around the data silo. Sure the data silos certainly getting bigger. And hopefully they're getting cheaper per bit. But as I said, the focus has really been on collecting, storing and managing the data. But between the new data lakes and many different cloud object storage combined with all sorts of data types from the complexity of managing all this, getting that business value has been very limited. This actually takes me to big bet number one for Team Vertica, which is to unify the data. Our goal, and some of the announcements we have made today plus roadmap announcements I'll share with you throughout this presentation. Our goal is to ensure that all the time, money and effort that has gone into storing that data, all the data turns into business value. So how are we going to do that? With a unified analytics platform that analyzes the data wherever it is HDFS, Cloud Object Storage, External tables in an any format ORC, Parquet, JSON, and of course, our own Native Roth Vertica format. Analyze the data in the right place in the right format, using a single unified tool. This is something that Vertica has always been committed to, and you'll see in some of our announcements today, we're just doubling down on that commitment. Let's talk a little bit more about the public cloud. This is certainly the second trend. It's the second wave maybe of data disruption with object storage. And there's a lot of advantages when it comes to public cloud. There's no question that the public clouds give rapid access to compute storage with the added benefit of eliminating data center maintenance that so many companies, want to get out of themselves. But maybe the biggest advantage that I see is the architectural innovation. The public clouds have introduced so many methodologies around how to provision quickly, separating compute and storage and really dialing-in the exact needs on demand, as you change workloads. When public clouds began, it made a lot of sense for the cloud providers and their customers to charge and pay for compute and storage in the ratio that each use case demanded. And I think you're seeing that trend, proliferate all over the place, not just up in public cloud. That architecture itself is really becoming the next generation architecture for on-premise data centers, as well. But there are a lot of concerns. I think we're all aware of them. They're out there many times for different workloads, there are higher costs. Especially if some of the workloads that are being run through analytics, which tend to run all the time. Just like some of the silo challenges that companies are facing with HDFS, data lakes and cloud storage, the public clouds have similar types of siloed challenges as well. Initially, there was a belief that they were cheaper than data centers, and when you added in all the costs, it looked that way. And again, for certain elastic workloads, that is the case. I don't think that's true across the board overall. Even to the point where a lot of the cloud vendors aren't just charging lower costs anymore. We hear from a lot of customers that they don't really want to tether themselves to any one cloud because of some of those uncertainties. Of course, security and privacy are a concern. We hear a lot of concerns with regards to cloud and even some SaaS vendors around shared data catalogs, across all the customers and not enough separation. But security concerns are out there, you can read about them. I'm not going to jump into that bandwagon. But we hear about them. And then, of course, I think one of the things we hear the most from our customers, is that each cloud stack is starting to feel even a lot more locked in than the traditional data warehouse appliance. And as everybody knows, the industry has been running away from appliances as fast as it can. And so they're not eager to get locked into another, quote, unquote, virtual appliance, if you will, up in the cloud. They really want to make sure they have flexibility in which clouds, they're going to today, tomorrow and in the future. And frankly, we hear from a lot of our customers that they're very interested in eventually mixing and matching, compute from one cloud with, say storage from another cloud, which I think is something that we'll hear a lot more about. And so for us, that's why we've got our big bet number two. we love the cloud. We love the public cloud. We love the private clouds on-premise, and other hosting providers. But our passion and commitment is for Vertica to be able to run in any of the clouds that our customers choose, and make it portable across those clouds. We have supported on-premises and all public clouds for years. And today, we have announced even more support for Vertica in Eon Mode, the deployment option that leverages the separation of compute from storage, with even more deployment choices, which I'm going to also touch more on as we go. So super excited about our big bet number two. And finally as I mentioned, for all the hype that there is around machine learning, I actually think that most importantly, this third trend that team Vertica is determined to address is the need to bring business critical, analytics, machine learning, data science projects into production. For so many years, there just wasn't enough data available to justify the investment in machine learning. Also, processing power was expensive, and storage was prohibitively expensive. But to train and score and evaluate all the different models to unlock the full power of predictive analytics was tough. Today you have those massive data volumes. You have the relatively cheap processing power and storage to make that dream a reality. And if you think about this, I mean with all the data that's available to every company, the real need is to operationalize the speed and the scale of machine learning so that these organizations can actually take advantage of it where they need to. I mean, we've seen this for years with Vertica, going back to some of the most advanced gaming companies in the early days, they were incorporating this with live data directly into their gaming experiences. Well, every organization wants to do that now. And the accuracy for clickability and real time actions are all key to separating the leaders from the rest of the pack in every industry when it comes to machine learning. But if you look at a lot of these projects, the reality is that there's a ton of buzz, there's a ton of hype spanning every acronym that you can imagine. But most companies are struggling, do the separate teams, different tools, silos and the limitation that many platforms are facing, driving, down sampling to get a small subset of the data, to try to create a model that then doesn't apply, or compromising accuracy and making it virtually impossible to replicate models, and understand decisions. And if there's one thing that we've learned when it comes to data, prescriptive data at the atomic level, being able to show end of one as we refer to it, meaning individually tailored data. No matter what it is healthcare, entertainment experiences, like gaming or other, being able to get at the granular data and make these decisions, make that scoring applies to machine learning just as much as it applies to giving somebody a next-best-offer. But the opportunity has never been greater. The need to integrate this end-to-end workflow and support the right tools without compromising on that accuracy. Think about it as no downsampling, using all the data, it really is key to machine learning success. Which should be no surprise then why the third big bet from Vertica is one that we've actually been working on for years. And we're so proud to be where we are today, helping the data disruptors across the world operationalize machine learning. This big bet has the potential to truly unlock, really the potential of machine learning. And today, we're announcing some very important new capabilities specifically focused on unifying the work being done by the data science community, with their preferred tools and platforms, and the volume of data and performance at scale, available in Vertica. Our strategy has been very consistent over the last several years. As I said in the beginning, we haven't deviated from our strategy. Of course, there's always things that we add. Most of the time, it's customer driven, it's based on what our customers are asking us to do. But I think we've also done a great job, not trying to be all things to all people. Especially as these hype cycles flare up around us, we absolutely love participating in these different areas without getting completely distracted. I mean, there's a variety of query tools and data warehouses and analytics platforms in the market. We all know that. There are tools and platforms that are offered by the public cloud vendors, by other vendors that support one or two specific clouds. There are appliance vendors, who I was referring to earlier who can deliver package data warehouse offerings for private data centers. And there's a ton of popular machine learning tools, languages and other kits. But Vertica is the only advanced analytic platform that can do all this, that can bring it together. We can analyze the data wherever it is, in HDFS, S3 Object Storage, or Vertica itself. Natively we support multiple clouds on-premise deployments, And maybe most importantly, we offer that choice of deployment modes to allow our customers to choose the architecture that works for them right now. It still also gives them the option to change move, evolve over time. And Vertica is the only analytics database with end-to-end machine learning that can truly operationalize ML at scale. And I know it's a mouthful. But it is not easy to do all these things. It is one of the things that highly differentiates Vertica from the rest of the pack. It is also why our customers, all of you continue to bet on us and see the value that we are delivering and we will continue to deliver. Here's a couple of examples of some of our customers who are powered by Vertica. It's the scale of data. It's the millisecond response times. Performance and scale have always been a huge part of what we have been about, not the only thing. I think the functionality all the capabilities that we add to the platform, the ease of use, the flexibility, obviously with the deployment. But if you look at some of the numbers they are under these customers on this slide. And I've shared a lot of different stories about these customers. Which, by the way, it still amaze me every time I talk to one and I get the updates, you can see the power and the difference that Vertica is making. Equally important, if you look at a lot of these customers, they are the epitome of being able to deploy Vertica in a lot of different environments. Many of the customers on this slide are not using Vertica just on-premise or just in the cloud. They're using it in a hybrid way. They're using it in multiple different clouds. And again, we've been with them on that journey throughout, which is what has made this product and frankly, our roadmap and our vision exactly what it is. It's been quite a journey. And that journey continues now with the Vertica 10 release. The Vertica 10 release is obviously a massive release for us. But if you look back, you can see that building on that native columnar architecture that started a long time ago, obviously, with the C-Store paper. We built it to leverage that commodity hardware, because it was an architecture that was never tightly integrated with any specific underlying infrastructure. I still remember hearing the initial pitch from Mike Stonebreaker, about the vision of Vertica as a software only solution and the importance of separating the company from hardware innovation. And at the time, Mike basically said to me, "there's so much R&D in innovation that's going to happen in hardware, we shouldn't bake hardware into our solution. We should do it in software, and we'll be able to take advantage of that hardware." And that is exactly what has happened. But one of the most recent innovations that we embraced with hardware is certainly that separation of compute and storage. As I said previously, the public cloud providers offered this next generation architecture, really to ensure that they can provide the customers exactly what they needed, more compute or more storage and charge for each, respectively. The separation of compute and storage, compute from storage is a major milestone in data center architectures. If you think about it, it's really not only a public cloud innovation, though. It fundamentally redefines the next generation data architecture for on-premise and for pretty much every way people are thinking about computing today. And that goes for software too. Object storage is an example of the cost effective means for storing data. And even more importantly, separating compute from storage for analytic workloads has a lot of advantages. Including the opportunity to manage much more dynamic, flexible workloads. And more importantly, truly isolate those workloads from others. And by the way, once you start having something that can truly isolate workloads, then you can have the conversations around autonomic computing, around setting up some nodes, some compute resources on the data that won't affect any of the other data to do some things on their own, maybe some self analytics, by the system, etc. A lot of things that many of you know we've already been exploring in terms of our own system data in the product. But it was May 2018, believe it or not, it seems like a long time ago where we first announced Eon Mode and I want to make something very clear, actually about Eon mode. It's a mode, it's a deployment option for Vertica customers. And I think this is another huge benefit that we don't talk about enough. But unlike a lot of vendors in the market who will dig you and charge you for every single add-on like hit-buy, you name it. You get this with the Vertica product. If you continue to pay support and maintenance, this comes with the upgrade. This comes as part of the new release. So any customer who owns or buys Vertica has the ability to set up either an Enterprise Mode or Eon Mode, which is a question I know that comes up sometimes. Our first announcement of Eon was obviously AWS customers, including the trade desk, AT&T. Most of whom will be speaking here later at the Virtual Big Data Conference. They saw a huge opportunity. Eon Mode, not only allowed Vertica to scale elastically with that specific compute and storage that was needed, but it really dramatically simplified database operations including things like workload balancing, node recovery, compute provisioning, etc. So one of the most popular functions is that ability to isolate the workloads and really allocate those resources without negatively affecting others. And even though traditional data warehouses, including Vertica Enterprise Mode have been able to do lots of different workload isolation, it's never been as strong as Eon Mode. Well, it certainly didn't take long for our customers to see that value across the board with Eon Mode. Not just up in the cloud, in partnership with one of our most valued partners and a platinum sponsor here. Joy mentioned at the beginning. We announced Vertica Eon Mode for Pure Storage FlashBlade in September 2019. And again, just to be clear, this is not a new product, it's one Vertica with yet more deployment options. With Pure Storage, Vertica in Eon mode is not limited in any way by variable cloud, network latency. The performance is actually amazing when you take the benefits of separate and compute from storage and you run it with a Pure environment on-premise. Vertica in Eon Mode has a super smart cache layer that we call the depot. It's a big part of our secret sauce around Eon mode. And combined with the power and performance of Pure's FlashBlade, Vertica became the industry's first advanced analytics platform that actually separates compute and storage for on-premises data centers. Something that a lot of our customers are already benefiting from, and we're super excited about it. But as I said, this is a journey. We don't stop, we're not going to stop. Our customers need the flexibility of multiple public clouds. So today with Vertica 10, we're super proud and excited to announce support for Vertica in Eon Mode on Google Cloud. This gives our customers the ability to use their Vertica licenses on Amazon AWS, on-premise with Pure Storage and on Google Cloud. Now, we were talking about HDFS and a lot of our customers who have invested quite a bit in HDFS as a place, especially to store data have been pushing us to support Eon Mode with HDFS. So as part of Vertica 10, we are also announcing support for Vertica in Eon Mode using HDFS as the communal storage. Vertica's own Roth format data can be stored in HDFS, and actually the full functionality of Vertica is complete analytics, geospatial pattern matching, time series, machine learning, everything that we have in there can be applied to this data. And on the same HDFS nodes, Vertica can actually also analyze data in ORC or Parquet format, using External tables. We can also execute joins between the Roth data the External table holds, which powers a much more comprehensive view. So again, it's that flexibility to be able to support our customers, wherever they need us to support them on whatever platform, they have. Vertica 10 gives us a lot more ways that we can deploy Eon Mode in various environments for our customers. It allows them to take advantage of Vertica in Eon Mode and the power that it brings with that separation, with that workload isolation, to whichever platform they are most comfortable with. Now, there's a lot that has come in Vertica 10. I'm definitely not going to be able to cover everything. But we also introduced complex types as an example. And complex data types fit very well into Eon as well in this separation. They significantly reduce the data pipeline, the cost of moving data between those, a much better support for unstructured data, which a lot of our customers have mixed with structured data, of course, and they leverage a lot of columnar execution that Vertica provides. So you get complex data types in Vertica now, a lot more data, stronger performance. It goes great with the announcement that we made with the broader Eon Mode. Let's talk a little bit more about machine learning. We've been actually doing work in and around machine learning with various extra regressions and a whole bunch of other algorithms for several years. We saw the huge advantage that MPP offered, not just as a sequel engine as a database, but for ML as well. Didn't take as long to realize that there's a lot more to operationalizing machine learning than just those algorithms. It's data preparation, it's that model trade training. It's the scoring, the shaping, the evaluation. That is so much of what machine learning and frankly, data science is about. You do know, everybody always wants to jump to the sexy algorithm and we handle those tasks very, very well. It makes Vertica a terrific platform to do that. A lot of work in data science and machine learning is done in other tools. I had mentioned that there's just so many tools out there. We want people to be able to take advantage of all that. We never believed we were going to be the best algorithm company or come up with the best models for people to use. So with Vertica 10, we support PMML. We can import now and export PMML models. It's a huge step for us around that operationalizing machine learning projects for our customers. Allowing the models to get built outside of Vertica yet be imported in and then applying to that full scale of data with all the performance that you would expect from Vertica. We also are more tightly integrating with Python. As many of you know, we've been doing a lot of open source projects with the community driven by many of our customers, like Uber. And so now with Python we've integrated with TensorFlow, allowing data scientists to build models in their preferred language, to take advantage of TensorFlow. But again, to store and deploy those models at scale with Vertica. I think both these announcements are proof of our big bet number three, and really our commitment to supporting innovation throughout the community by operationalizing ML with that accuracy, performance and scale of Vertica for our customers. Again, there's a lot of steps when it comes to the workflow of machine learning. These are some of them that you can see on the slide, and it's definitely not linear either. We see this as a circle. And companies that do it, well just continue to learn, they continue to rescore, they continue to redeploy and they want to operationalize all that within a single platform that can take advantage of all those capabilities. And that is the platform, with a very robust ecosystem that Vertica has always been committed to as an organization and will continue to be. This graphic, many of you have seen it evolve over the years. Frankly, if we put everything and everyone on here wouldn't fit on a slide. But it will absolutely continue to evolve and grow as we support our customers, where they need the support most. So, again, being able to deploy everywhere, being able to take advantage of Vertica, not just as a business analyst or a business user, but as a data scientists or as an operational or BI person. We want Vertica to be leveraged and used by the broader organization. So I think it's fair to say and I encourage everybody to learn more about Vertica 10, because I'm just highlighting some of the bigger aspects of it. But we talked about those three market trends. The need to unify the silos, the need for hybrid multiple cloud deployment options, the need to operationalize business critical machine learning projects. Vertica 10 has absolutely delivered on those. But again, we are not going to stop. It is our job not to, and this is how Team Vertica thrives. I always joke that the next release is the best release. And, of course, even after Vertica 10, that is also true, although Vertica 10 is pretty awesome. But, you know, from the first line of code, we've always been focused on performance and scale, right. And like any really strong data platform, the execution engine, the optimizer and the execution engine are the two core pieces of that. Beyond Vertica 10, some of the big things that we're already working on, next generation execution engine. We're already actually seeing incredible early performance from this. And this is just one example, of how important it is for an organization like Vertica to constantly go back and re-innovate. Every single release, we do the sit ups and crunches, our performance and scale. How do we improve? And there's so many parts of the core server, there's so many parts of our broader ecosystem. We are constantly looking at coverages of how we can go back to all the code lines that we have, and make them better in the current environment. And it's not an easy thing to do when you're doing that, and you're also expanding in the environment that we are expanding into to take advantage of the different deployments, which is a great segue to this slide. Because if you think about today, we're obviously already available with Eon Mode and Amazon, AWS and Pure and actually MinIO as well. As I talked about in Vertica 10 we're adding Google and HDFS. And coming next, obviously, Microsoft Azure, Alibaba cloud. So being able to expand into more of these environments is really important for the Vertica team and how we go forward. And it's not just running in these clouds, for us, we want it to be a SaaS like experience in all these clouds. We want you to be able to deploy Vertica in 15 minutes or less on these clouds. You can also consume Vertica, in a lot of different ways, on these clouds. As an example, in Amazon Vertica by the Hour. So for us, it's not just about running, it's about taking advantage of the ecosystems that all these cloud providers offer, and really optimizing the Vertica experience as part of them. Optimization, around automation, around self service capabilities, extending our management console, we now have products that like the Vertica Advisor Tool that our Customer Success Team has created to actually use our own smarts in Vertica. To take data from customers that give it to us and help them tune automatically their environment. You can imagine that we're taking that to the next level, in a lot of different endeavors that we're doing around how Vertica as a product can actually be smarter because we all know that simplicity is key. There just aren't enough people in the world who are good at managing data and taking it to the next level. And of course, other things that we all hear about, whether it's Kubernetes and containerization. You can imagine that that probably works very well with the Eon Mode and separating compute and storage. But innovation happens everywhere. We innovate around our community documentation. Many of you have taken advantage of the Vertica Academy. The numbers there are through the roof in terms of the number of people coming in and certifying on it. So there's a lot of things that are within the core products. There's a lot of activity and action beyond the core products that we're taking advantage of. And let's not forget why we're here, right? It's easy to talk about a platform, a data platform, it's easy to jump into all the functionality, the analytics, the flexibility, how we can offer it. But at the end of the day, somebody, a person, she's got to take advantage of this data, she's got to be able to take this data and use this information to make a critical business decision. And that doesn't happen unless we explore lots of different and frankly, new ways to get that predictive analytics UI and interface beyond just the standard BI tools in front of her at the right time. And so there's a lot of activity, I'll tease you with that going on in this organization right now about how we can do that and deliver that for our customers. We're in a great position to be able to see exactly how this data is consumed and used and start with this core platform that we have to go out. Look, I know, the plan wasn't to do this as a virtual BDC. But I really appreciate you tuning in. Really appreciate your support. I think if there's any silver lining to us, maybe not being able to do this in person, it's the fact that the reach has actually gone significantly higher than what we would have been able to do in person in Boston. We're certainly looking forward to doing a Big Data Conference in the future. But if I could leave you with anything, know this, since that first release for Vertica, and our very first customers, we have been very consistent. We respect all the innovation around us, whether it's open source or not. We understand the market trends. We embrace those new ideas and technologies and for us true north, and the most important thing is what does our customer need to do? What problem are they trying to solve? And how do we use the advantages that we have without disrupting our customers? But knowing that you depend on us to deliver that unified analytics strategy, it will deliver that performance of scale, not only today, but tomorrow and for years to come. We've added a lot of great features to Vertica. I think we've said no to a lot of things, frankly, that we just knew we wouldn't be the best company to deliver. When we say we're going to do things we do them. Vertica 10 is a perfect example of so many of those things that we from you, our customers have heard loud and clear, and we have delivered. I am incredibly proud of this team across the board. I think the culture of Vertica, a customer first culture, jumping in to help our customers win no matter what is also something that sets us massively apart. I hear horror stories about support experiences with other organizations. And people always seem to be amazed at Team Vertica's willingness to jump in or their aptitude for certain technical capabilities or understanding the business. And I think sometimes we take that for granted. But that is the team that we have as Team Vertica. We are incredibly excited about Vertica 10. I think you're going to love the Virtual Big Data Conference this year. I encourage you to tune in. Maybe one other benefit is I know some people were worried about not being able to see different sessions because they were going to overlap with each other well now, even if you can't do it live, you'll be able to do those sessions on demand. Please enjoy the Vertica Big Data Conference here in 2020. Please you and your families and your co-workers be safe during these times. I know we will get through it. And analytics is probably going to help with a lot of that and we already know it is helping in many different ways. So believe in the data, believe in data's ability to change the world for the better. And thank you for your time. And with that, I am delighted to now introduce Micro Focus CEO Stephen Murdoch to the Vertica Big Data Virtual Conference. Thank you Stephen. >> Stephen: Hi, everyone, my name is Stephen Murdoch. I have the pleasure and privilege of being the Chief Executive Officer here at Micro Focus. Please let me add my welcome to the Big Data Conference. And also my thanks for your support, as we've had to pivot to this being virtual rather than a physical conference. Its amazing how quickly we all reset to a new normal. I certainly didn't expect to be addressing you from my study. Vertica is an incredibly important part of Micro Focus family. Is key to our goal of trying to enable and help customers become much more data driven across all of their IT operations. Vertica 10 is a huge step forward, we believe. It allows for multi-cloud innovation, genuinely hybrid deployments, begin to leverage machine learning properly in the enterprise, and also allows the opportunity to unify currently siloed lakes of information. We operate in a very noisy, very competitive market, and there are people, who are in that market who can do some of those things. The reason we are so excited about Vertica is we genuinely believe that we are the best at doing all of those things. And that's why we've announced publicly, you're under executing internally, incremental investment into Vertica. That investments targeted at accelerating the roadmaps that already exist. And getting that innovation into your hands faster. This idea is speed is key. It's not a question of if companies have to become data driven organizations, it's a question of when. So that speed now is really important. And that's why we believe that the Big Data Conference gives a great opportunity for you to accelerate your own plans. You will have the opportunity to talk to some of our best architects, some of the best development brains that we have. But more importantly, you'll also get to hear from some of our phenomenal Roth Data customers. You'll hear from Uber, from the Trade Desk, from Philips, and from AT&T, as well as many many others. And just hearing how those customers are using the power of Vertica to accelerate their own, I think is the highlight. And I encourage you to use this opportunity to its full. Let me close by, again saying thank you, we genuinely hope that you get as much from this virtual conference as you could have from a physical conference. And we look forward to your engagement, and we look forward to hearing your feedback. With that, thank you very much. >> Joy: Thank you so much, Stephen, for joining us for the Vertica Big Data Conference. Your support and enthusiasm for Vertica is so clear, and it makes a big difference. Now, I'm delighted to introduce Amy Fowler, the VP of Strategy and Solutions for FlashBlade at Pure Storage, who was one of our BDC Platinum Sponsors, and one of our most valued partners. It was a proud moment for me, when we announced Vertica in Eon mode for Pure Storage FlashBlade and we became the first analytics data warehouse that separates compute from storage for on-premise data centers. Thank you so much, Amy, for joining us. Let's get started. >> Amy: Well, thank you, Joy so much for having us. And thank you all for joining us today, virtually, as we may all be. So, as we just heard from Colin Mahony, there are some really interesting trends that are happening right now in the big data analytics market. From the end of the Hadoop hype cycle, to the new cloud reality, and even the opportunity to help the many data science and machine learning projects move from labs to production. So let's talk about these trends in the context of infrastructure. And in particular, look at why a modern storage platform is relevant as organizations take on the challenges and opportunities associated with these trends. The answer is the Hadoop hype cycles left a lot of data in HDFS data lakes, or reservoirs or swamps depending upon the level of the data hygiene. But without the ability to get the value that was promised from Hadoop as a platform rather than a distributed file store. And when we combine that data with the massive volume of data in Cloud Object Storage, we find ourselves with a lot of data and a lot of silos, but without a way to unify that data and find value in it. Now when you look at the infrastructure data lakes are traditionally built on, it is often direct attached storage or data. The approach that Hadoop took when it entered the market was primarily bound by the limits of networking and storage technologies. One gig ethernet and slower spinning disk. But today, those barriers do not exist. And all FlashStorage has fundamentally transformed how data is accessed, managed and leveraged. The need for local data storage for significant volumes of data has been largely mitigated by the performance increases afforded by all Flash. At the same time, organizations can achieve superior economies of scale with that segregation of compute and storage. With compute and storage, you don't always scale in lockstep. Would you want to add an engine to the train every time you add another boxcar? Probably not. But from a Pure Storage perspective, FlashBlade is uniquely architected to allow customers to achieve better resource utilization for compute and storage, while at the same time, reducing complexity that has arisen from the siloed nature of the original big data solutions. The second and equally important recent trend we see is something I'll call cloud reality. The public clouds made a lot of promises and some of those promises were delivered. But cloud economics, especially usage based and elastic scaling, without the control that many companies need to manage the financial impact is causing a lot of issues. In addition, the risk of vendor lock-in from data egress, charges, to integrated software stacks that can't be moved or deployed on-premise is causing a lot of organizations to back off the all the way non-cloud strategy, and move toward hybrid deployments. Which is kind of funny in a way because it wasn't that long ago that there was a lot of talk about no more data centers. And for example, one large retailer, I won't name them, but I'll admit they are my favorites. They several years ago told us they were completely done with on-prem storage infrastructure, because they were going 100% to the cloud. But they just deployed FlashBlade for their data pipelines, because they need predictable performance at scale. And the all cloud TCO just didn't add up. Now, that being said, well, there are certainly challenges with the public cloud. It has also brought some things to the table that we see most organizations wanting. First of all, in a lot of cases applications have been built to leverage object storage platforms like S3. So they need that object protocol, but they may also need it to be fast. And the said object may be oxymoron only a few years ago, and this is an area of the market where Pure and FlashBlade have really taken a leadership position. Second, regardless of where the data is physically stored, organizations want the best elements of a cloud experience. And for us, that means two main things. Number one is simplicity and ease of use. If you need a bunch of storage experts to run the system, that should be considered a bug. The other big one is the consumption model. The ability to pay for what you need when you need it, and seamlessly grow your environment over time totally nondestructively. This is actually pretty huge and something that a lot of vendors try to solve for with finance programs. But no finance program can address the pain of a forklift upgrade, when you need to move to next gen hardware. To scale nondestructively over long periods of time, five to 10 years plus is a crucial architectural decisions need to be made at the outset. Plus, you need the ability to pay as you use it. And we offer something for FlashBlade called Pure as a Service, which delivers exactly that. The third cloud characteristic that many organizations want is the option for hybrid. Even if that is just a DR site in the cloud. In our case, that means supporting appplication of S3, at the AWS. And the final trend, which to me represents the biggest opportunity for all of us, is the need to help the many data science and machine learning projects move from labs to production. This means bringing all the machine learning functions and model training to the data, rather than moving samples or segments of data to separate platforms. As we all know, machine learning needs a ton of data for accuracy. And there is just too much data to retrieve from the cloud for every training job. At the same time, predictive analytics without accuracy is not going to deliver the business advantage that everyone is seeking. You can kind of visualize data analytics as it is traditionally deployed as being on a continuum. With that thing, we've been doing the longest, data warehousing on one end, and AI on the other end. But the way this manifests in most environments is a series of silos that get built up. So data is duplicated across all kinds of bespoke analytics and AI, environments and infrastructure. This creates an expensive and complex environment. So historically, there was no other way to do it because some level of performance is always table stakes. And each of these parts of the data pipeline has a different workload profile. A single platform to deliver on the multi dimensional performances, diverse set of applications required, that didn't exist three years ago. And that's why the application vendors pointed you towards bespoke things like DAS environments that we talked about earlier. And the fact that better options exists today is why we're seeing them move towards supporting this disaggregation of compute and storage. And when it comes to a platform that is a better option, one with a modern architecture that can address the diverse performance requirements of this continuum, and allow organizations to bring a model to the data instead of creating separate silos. That's exactly what FlashBlade is built for. Small files, large files, high throughput, low latency and scale to petabytes in a single namespace. And this is importantly a single rapid space is what we're focused on delivering for our customers. At Pure, we talk about it in the context of modern data experience because at the end of the day, that's what it's really all about. The experience for your teams in your organization. And together Pure Storage and Vertica have delivered that experience to a wide range of customers. From a SaaS analytics company, which uses Vertica on FlashBlade to authenticate the quality of digital media in real time, to a multinational car company, which uses Vertica on FlashBlade to make thousands of decisions per second for autonomous cars, or a healthcare organization, which uses Vertica on FlashBlade to enable healthcare providers to make real time decisions that impact lives. And I'm sure you're all looking forward to hearing from John Yavanovich from AT&T. To hear how he's been doing this with Vertica and FlashBlade as well. He's coming up soon. We have been really excited to build this partnership with Vertica. And we're proud to provide the only on-premise storage platform validated with Vertica Eon Mode. And deliver this modern data experience to our customers together. Thank you all so much for joining us today. >> Joy: Amy, thank you so much for your time and your insights. Modern infrastructure is key to modern analytics, especially as organizations leverage next generation data center architectures, and object storage for their on-premise data centers. Now, I'm delighted to introduce our last speaker in our Vertica Big Data Conference Keynote, John Yovanovich, Director of IT for AT&T. Vertica is so proud to serve AT&T, and especially proud of the harmonious impact we are having in partnership with Pure Storage. John, welcome to the Virtual Vertica BDC. >> John: Thank you joy. It's a pleasure to be here. And I'm excited to go through this presentation today. And in a unique fashion today 'cause as I was thinking through how I wanted to present the partnership that we have formed together between Pure Storage, Vertica and AT&T, I want to emphasize how well we all work together and how these three components have really driven home, my desire for a harmonious to use your word relationship. So, I'm going to move forward here and with. So here, what I'm going to do the theme of today's presentation is the Pure Vertica Symphony live at AT&T. And if anybody is a Westworld fan, you can appreciate the sheet music on the right hand side. What we're going to what I'm going to highlight here is in a musical fashion, is how we at AT&T leverage these technologies to save money to deliver a more efficient platform, and to actually just to make our customers happier overall. So as we look back, and back as early as just maybe a few years ago here at AT&T, I realized that we had many musicians to help the company. Or maybe you might want to call them data scientists, or data analysts. For the theme we'll stay with musicians. None of them were singing or playing from the same hymn book or sheet music. And so what we had was many organizations chasing a similar dream, but not exactly the same dream. And, best way to describe that is and I think with a lot of people this might resonate in your organizations. How many organizations are chasing a customer 360 view in your company? Well, I can tell you that I have at least four in my company. And I'm sure there are many that I don't know of. That is our problem because what we see is a repetitive sourcing of data. We see a repetitive copying of data. And there's just so much money to be spent. This is where I asked Pure Storage and Vertica to help me solve that problem with their technologies. What I also noticed was that there was no coordination between these departments. In fact, if you look here, nobody really wants to play with finance. Sales, marketing and care, sure that you all copied each other's data. But they actually didn't communicate with each other as they were copying the data. So the data became replicated and out of sync. This is a challenge throughout, not just my company, but all companies across the world. And that is, the more we replicate the data, the more problems we have at chasing or conquering the goal of single version of truth. In fact, I kid that I think that AT&T, we actually have adopted the multiple versions of truth, techno theory, which is not where we want to be, but this is where we are. But we are conquering that with the synergies between Pure Storage and Vertica. This is what it leaves us with. And this is where we are challenged and that if each one of our siloed business units had their own stories, their own dedicated stories, and some of them had more money than others so they bought more storage. Some of them anticipating storing more data, and then they really did. Others are running out of space, but can't put anymore because their bodies aren't been replenished. So if you look at it from this side view here, we have a limited amount of compute or fixed compute dedicated to each one of these silos. And that's because of the, wanting to own your own. And the other part is that you are limited or wasting space, depending on where you are in the organization. So there were the synergies aren't just about the data, but actually the compute and the storage. And I wanted to tackle that challenge as well. So I was tackling the data. I was tackling the storage, and I was tackling the compute all at the same time. So my ask across the company was can we just please play together okay. And to do that, I knew that I wasn't going to tackle this by getting everybody in the same room and getting them to agree that we needed one account table, because they will argue about whose account table is the best account table. But I knew that if I brought the account tables together, they would soon see that they had so much redundancy that I can now start retiring data sources. I also knew that if I brought all the compute together, that they would all be happy. But I didn't want them to tackle across tackle each other. And in fact that was one of the things that all business units really enjoy. Is they enjoy the silo of having their own compute, and more or less being able to control their own destiny. Well, Vertica's subclustering allows just that. And this is exactly what I was hoping for, and I'm glad they've brought through. And finally, how did I solve the problem of the single account table? Well when you don't have dedicated storage, and you can separate compute and storage as Vertica in Eon Mode does. And we store the data on FlashBlades, which you see on the left and right hand side, of our container, which I can describe in a moment. Okay, so what we have here, is we have a container full of compute with all the Vertica nodes sitting in the middle. Two loader, we'll call them loader subclusters, sitting on the sides, which are dedicated to just putting data onto the FlashBlades, which is sitting on both ends of the container. Now today, I have two dedicated storage or common dedicated might not be the right word, but two storage racks one on the left one on the right. And I treat them as separate storage racks. They could be one, but i created them separately for disaster recovery purposes, lashing work in case that rack were to go down. But that being said, there's no reason why I'm probably going to add a couple of them here in the future. So I can just have a, say five to 10, petabyte storage, setup, and I'll have my DR in another 'cause the DR shouldn't be in the same container. Okay, but I'll DR outside of this container. So I got them all together, I leveraged subclustering, I leveraged separate and compute. I was able to convince many of my clients that they didn't need their own account table, that they were better off having one. I eliminated, I reduced latency, I reduced our ticketing I reduce our data quality issues AKA ticketing okay. I was able to expand. What is this? As work. I was able to leverage elasticity within this cluster. As you can see, there are racks and racks of compute. We set up what we'll call the fixed capacity that each of the business units needed. And then I'm able to ramp up and release the compute that's necessary for each one of my clients based on their workloads throughout the day. And so while they compute to the right before you see that the instruments have already like, more or less, dedicated themselves towards all those are free for anybody to use. So in essence, what I have, is I have a concert hall with a lot of seats available. So if I want to run a 10 chair Symphony or 80, chairs, Symphony, I'm able to do that. And all the while, I can also do the same with my loader nodes. I can expand my loader nodes, to actually have their own Symphony or write all to themselves and not compete with any other workloads of the other clusters. What does that change for our organization? Well, it really changes the way our database administrators actually do their jobs. This has been a big transformation for them. They have actually become data conductors. Maybe you might even call them composers, which is interesting, because what I've asked them to do is morph into less technology and more workload analysis. And in doing so we're able to write auto-detect scripts, that watch the queues, watch the workloads so that we can help ramp up and trim down the cluster and subclusters as necessary. There has been an exciting transformation for our DBAs, who I need to now classify as something maybe like DCAs. I don't know, I have to work with HR on that. But I think it's an exciting future for their careers. And if we bring it all together, If we bring it all together, and then our clusters, start looking like this. Where everything is moving in harmonious, we have lots of seats open for extra musicians. And we are able to emulate a cloud experience on-prem. And so, I want you to sit back and enjoy the Pure Vertica Symphony live at AT&T. (soft music) >> Joy: Thank you so much, John, for an informative and very creative look at the benefits that AT&T is getting from its Pure Vertica symphony. I do really like the idea of engaging HR to change the title to Data Conductor. That's fantastic. I've always believed that music brings people together. And now it's clear that analytics at AT&T is part of that musical advantage. So, now it's time for a short break. And we'll be back for our breakout sessions, beginning at 12 pm Eastern Daylight Time. We have some really exciting sessions planned later today. And then again, as you can see on Wednesday. Now because all of you are already logged in and listening to this keynote, you already know the steps to continue to participate in the sessions that are listed here and on the previous slide. In addition, everyone received an email yesterday, today, and you'll get another one tomorrow, outlining the simple steps to register, login and choose your session. If you have any questions, check out the emails or go to www.vertica.com/bdc2020 for the logistics information. There are a lot of choices and that's always a good thing. Don't worry if you want to attend one or more or can't listen to these live sessions due to your timezone. All the sessions, including the Q&A sections will be available on demand and everyone will have access to the recordings as well as even more pre-recorded sessions that we'll post to the BDC website. Now I do want to leave you with two other important sites. First, our Vertica Academy. Vertica Academy is available to everyone. And there's a variety of very technical, self-paced, on-demand training, virtual instructor-led workshops, and Vertica Essentials Certification. And it's all free. Because we believe that Vertica expertise, helps everyone accelerate their Vertica projects and the advantage that those projects deliver. Now, if you have questions or want to engage with our Vertica engineering team now, we're waiting for you on the Vertica forum. We'll answer any questions or discuss any ideas that you might have. Thank you again for joining the Vertica Big Data Conference Keynote Session. Enjoy the rest of the BDC because there's a lot more to come

ladies and gentlemen this is your captain speaking we will soon be taking off on our way to altitude please keep your seatbelts fastened and remain in your seats we will be experiencing turbulence until we are above the clouds ladies and gentlemen we are now cruising at altitude sit back and enjoy the ride [Music] altitude is a community of thought leaders and pioneers cloud architects and enlightened network engineers who have individually and are now collectively leading their own IT teams and the industry on a path to lift cloud networking above the clouds empowering Enterprise IT to architect design and control their own cloud network regardless of the turbulent clouds beneath them it's time to gain altitude ladies and gentlemen Steve Mulaney president and CEO of aviatrix the leader of multi cloud networking [Music] [Applause] all right good morning everybody here in Santa Clara as well as to the what millions of people watching the livestream worldwide welcome to altitude 2020 alright so we've got a fantastic event today really excited about the speakers that we have today and the experts that we have and really excited to get started so one of the things I wanted to just share was this is not a one-time event this is not a one-time thing that we're gonna do sorry for the aviation analogy but you know sherry way aviatrix means female pilot so everything we do as an aviation theme this is a take-off for a movement this isn't an event this is a take-off of a movement a multi-cloud networking movement and community that we're inviting all of you to become part of and-and-and why we're doing that is we want to enable enterprises to rise above the clouds so to speak and build their network architecture regardless of which public cloud they're using whether it's one or more of these public clouds so the good news for today there's lots of good news but this is one good news is we don't have any powerpoint presentations no marketing speak we know that marketing people have their own language we're not using any of that in those sales pitches right so instead what are we doing we're going to have expert panels we've got Simone Rashard Gartner here we've got 10 different network architects cloud architects real practitioners they're going to share their best practices and there are real-world experiences on their journey to the multi cloud so before we start and everybody know what today is in the u.s. it's Super Tuesday I'm not gonna get political but Super Tuesday there was a bigger Super Tuesday that happened 18 months ago and maybe eight six employees know what I'm talking about 18 months ago on a Tuesday every enterprise said I'm gonna go to the cloud and so what that was was the Cambrian explosion for cloud for the price so Frank kibrit you know what a Cambrian explosion is he had to look it up on Google 500 million years ago what happened there was an explosion of life where it went from very simple single-cell organisms to very complex multi-celled organisms guess what happened 18 months ago on a Tuesday I don't really know why but every enterprise like I said all woke up that day and said now I'm really gonna go to cloud and that Cambrian explosion of cloud went meant that I'm moving from very simple single cloud single use case simple environment to a very complex multi cloud complex use case environment and what we're here today is we're gonna go and dress that and how do you handle those those those complexities and when you look at what's happening with customers right now this is a business transformation right people like to talk about transitions this is a transformation and it's actually not just the technology transformation it's a business transformation it started from the CEO and the boards of enterprise customers where they said I have an existential threat to the survival of my company if you look at every industry who they're worried about is not the other 30 year old enterprise what they're worried about is the three year old enterprise that's leveraging cloud that's leveraging AI and that's where they fear that they're going to actually get wiped out right and so because of this existential threat this is CEO lead this is board led this is not technology led it is mandated in the organization's we are going to digitally transform our enterprise because of this existential threat and the movement to cloud is going to enable us to go do that and so IT is now put back in charge if you think back just a few years ago in cloud it was led by DevOps it was led by the applications and it was like I said before their Cambrian explosion is very simple now with this Cambrian explosion and enterprises getting very serious and mission critical they care about visibility they care about control they care about compliance conformance everything governance IT is in charge and and and that's why we're here today to discuss that so what we're going to do today is much of things but we're gonna validate this journey with customers did they see the same thing we're gonna validate the requirements for multi-cloud because honestly I've never met an enterprise that is not going to be multi-cloud many are one cloud today but they all say I need to architect my network for multiple clouds because that's just what the network is there to support the applications and the applications will run and whatever cloud it runs best in and you have to be prepared for that the second thing is is architecture again with IT in charge you architecture matters whether it's your career whether it's how you build your house it doesn't matter horrible architecture your life is horrible forever good architecture your life is pretty good so we're gonna talk about architecture and how the most fundamental and critical part of that architecture and that basic infrastructure is the network if you don't get that right nothing works right way more important and compute way more important than storm dense storage network is the foundational element of your infrastructure then we're going to talk about day 2 operations what does that mean well day 1 is one day of your life that's who you wire things up they do and beyond I tell everyone in networking and IT it's every day of your life and if you don't get that right your life is bad forever and so things like operations visibility security things like that how do I get my operations team to be able to handle this in an automated way because it's not just about configuring it in the cloud it's actually about how do I operationalize it and that's a huge benefit that we bring as aviatrix and then the last thing we're going to talk and it's the last panel we have I always say you can't forget about the humans right so all this technology all these things that we're doing it's always enabled by the humans at the end of the day if the humans fight it it won't get deployed and we have a massive skills gap in cloud and we also have a massive skill shortage you have everyone in the world trying to hire cloud network architects right there's just not enough of them going around so at aviatrix we as leaders do we're gonna help address that issue and try to create more people we created a program and we call the ACE program again an aviation theme it stands for aviatrix certified engineer very similar to what Cisco did with CCI ease where Cisco taught you about IP networking a little bit of Cisco we're doing the same thing we're gonna teach network architects about multi-cloud networking and architecture and yeah you'll get a little bit of aviatrix training in there but this is the missing element for people's careers and also within their organization so we're gonna we're gonna go talk about that so great great event great show when to try to keep it moving I'd next want to introduce my my host he's the best in the business you guys have probably seen him multiple million times he's the co CEO and co-founder of tube Jon Fourier okay awesome great great speech they're awesome I'd totally agree with everything you said about the explosion happening and I'm excited here at the heart of Silicon Valley to have this event it's a special digital event with the cube and aviatrix were we live streaming to millions of people as you said maybe not a million maybe not really take this program to the world this is a little special for me because multi-cloud is the hottest wave and cloud and cloud native networking is fast becoming the key engine of the innovation so we got an hour and a half of action-packed programming we have a customer panel two customer panels before that Gartner is going to come on talk about the industry we have a global system integrators we talk about how they're advising and building these networks and cloud native networking and then finally the Aces the aviatrix certified engineer is gonna talk more about their certifications and the expertise needed so let's jump right in and let's ask someone rashard to come on stage from Gartner check it all up [Applause] okay so kicking things off sitting started gartner the industry experts on cloud really kind of more to your background talk about your background before you got the gardener yeah before because gardener was a chief network architect of a fortune five companies with thousands of sites over the world and I've been doing everything and IT from a C programmer in a 92 a security architect to a network engineer to finally becoming a network analyst so you rode the wave now you're covering at the marketplace with hybrid cloud and now moving quickly to multi cloud is really was talking about cloud natives been discussed but the networking piece is super important how do you see that evolving well the way we see Enterprise adapt in cloud first thing you do about networking the initial phases they either go in a very ad hoc way is usually led by non non IT like a shadow I to your application people are some kind of DevOps team and it's it just goes as it's completely unplanned decreed VP sees left and right with different account and they create mesh to manage them and their direct connect or Express route to any of them so that's what that's a first approach and on the other side again it within our first approach you see what I call the lift and shift way we see like enterprise IT trying to basically replicate what they have in a data center in the cloud so they spend a lot of time planning doing Direct Connect putting Cisco routers and f5 and Citrix and any checkpoint Palo Alto divides that the audinate that are sent removing that to that cloud and I ask you the aha moments gonna come up a lot of our panels is where people realize that it's a multi cloud world I mean they either inherit clouds certainly they're using public cloud and on-premises is now more relevant than ever when's that aha moment that you're seeing where people go well I got to get my act together and get on this well the first but even before multi-cloud so these two approach the first one like the ad hoc way doesn't scale at some point idea has to save them because they don't think about the two they don't think about operations they have a bunch of VPC and multiple clouds the other way that if you do the left and shift wake they cannot take any advantages of the cloud they lose elasticity auto-scaling pay by the drink these feature of agility features so they both realize okay neither of these ways are good so I have to optimize that so I have to have a mix of what I call the cloud native services within each cloud so they start adapting like other AWS constructor is your construct or Google construct then that's what I call the optimal phase but even that they realize after that they are very different all these approaches different the cloud are different identities is completely difficult to manage across clouds I mean for example AWS has accounts there's subscription and in adarand GCP their projects it's a real mess so they realize well I can't really like concentrate use the cloud the cloud product and every cloud that doesn't work so I have I'm doing multi cloud I like to abstract all of that I still wanna manage the cloud from an API to interview I don't necessarily want to bring my incumbent data center products but I have to do that in a more API driven cloud they're not they're not scaling piece and you were mentioning that's because there's too many different clouds yes that's the piece there so what are they doing whether they really building different development teams as its software what's the solution well this the solution is to start architecting the cloud that's the third phase I call that the multi cloud architect phase where they have to think about abstraction that works across cloud fact even across one cloud it might not scale as well if you start having like 10,000 security group in AWS that doesn't scale you have to manage that if you have multiple VPC it doesn't scale you need a third party identity provider so it barely scales within one cloud if you go multiple cloud it gets worse and worse see way in here what's your thoughts I thought we said this wasn't gonna be a sales pitch for aviatrix you just said exactly what we do so anyway I'm just a joke what do you see in terms of where people are in that multi-cloud so a lot of people you know everyone I talked to started in one cloud right but then they look and they say okay but I'm now gonna move to adjourn I'm gonna move do you see a similar thing well yes they are moving but they're not there's not a lot of application that use a tree cloud at once they move one app in deserve one app in individuals one get happen Google that's what we see so far okay yeah I mean one of the mistakes that people think is they think multi-cloud no one is ever gonna go multi-cloud for arbitrage they're not gonna go and say well today I might go into Azure because I got a better rate of my instance that's never do you agree with that's never going to happen what I've seen with enterprise is I'm gonna put the workload in the app the app decides where it runs best that may be a sure maybe Google and for different reasons and they're gonna stick there and they're not gonna move let me ask you infrastructure has to be able to support from a networking team be able to do that do you agree with that yes I agree and one thing is also very important is connecting to that cloud is kind of the easiest thing so though while their network part of the cloud connectivity to the cloud is kind of simple I agree IPSec VP and I reckon Express that's a simple part what's difficult and even a provisioning part is easy you can use terraform and create v pieces and v nets across which free cloud providers right what's difficult is the day-to-day operations so it's what to find a to operations what is that what does that actually mean this is the day-to-day operations after you know the natural let's add an app let's add a server let's troubleshoot a problem so so your life something changes how would he do so what's the big concerns I want to just get back to this cloud native networking because everyone kind of knows with cloud native apps are that's been a hot trend what is cloud native networking how do you how do you guys define that because that seems to be the oddest part of the multi cloud wave that's coming as cloud native networking well there's no you know official garner definition but I can create one on and if another spot is do it I just want to leverage the cloud construct and a cloud epi I don't want to have to install like like for example the first version was let's put a virtual router that doesn't even understand and then the cloud environment right if I have if I have to install a virtual machine it has to be cloud aware it has to understand the security group if it's a router it has to be programmable to the cloud API and and understand the cloud environment you know one things I hear a lot from either see Saussure CIOs or CXOs in general is this idea of I'm definitely on going API so it's been an API economy so API is key on that point but then they say okay I need to essentially have the right relationship with my suppliers aka clouds you call it above the clouds so the question is what do i do from an architecture standpoint do I just hire more developers and have different teams because you mentioned that's a scale point how do you solve this this problem of okay I got AWS I got GCP or Azure or whatever do I just have different teams or just expose api's where is that optimization where's the focus well I take what you need from an android point of view is a way a control plane across the three clouds and be able to use the api of the cloud to build networks but also to troubleshoot them and do they to operation so you need a view across a three cloud that takes care of routing connectivity that's you know that's the aviatrix plug of you right there so so how do you see so again your Gartner you you you you see the industry you've been a network architect how do you see this this plane out what are the what are the legacy incumbent client-server on-prem networking people gonna do well these versus people like aviatrix well how do you see that plane out well obviously all the incumbent like Arista cisco juniper NSX right they want to basically do the lift and ship or they want to bring and you know VM I want to bring in a section that cloud they call that NSX everywhere and cisco monks bring you star and the cloud recall that each guy anywhere right so everyone what and and then there's cloud vision for my red star and contrail is in the cloud so they just want to bring the management plane in the cloud but it's still based most of them it's still based on putting a VM them in controlling them right you you extend your management console to the cloud that's not truly cloud native right cloud native you almost have to build it from scratch we like to call that cloud naive clown that so close one letter yeah so that was a big con surgeon reinvent take the tea out of cloud native it's cloud naive that went super viral you guys got t-shirts now I know you love but yeah but that really ultimately is kind of double edged sword you got to be you can be naive on the on the architecture side and rolling out but also suppliers are can be naive so how would you define who's naive and who's not well in fact they're evolving as well so for example in Cisco you it's a little bit more native than other ones because they're really scr in the cloud you can't you you really like configure API so the cloud and NSX is going that way and so is Arista but they're incumbent they have their own tools is difficult for them they're moving slowly so it's much easier to start from scratch Avenue like and you know a network happiness started a few years ago there's only really two aviatrix was the first one they've been there for at least three or four years and there's other ones like al kira for example that just started now that doing more connectivity but they wanna create an overlay network across the cloud and start doing policies and trying abstracting all the clouds within one platform so I gotta ask you I interviewed an executive at VMware Sanjay Pune and he said to me at RSA last week oh the only b2 networking vendors left Cisco and VMware what's your respect what's your response to that obviously I mean when you have these waves as new brands that emerge like aviation others though I think there'll be a lot of startups coming out of the woodwork how do you respond to that comment well there's still a data center there's still like a lot of action on campus and there's the one but from the cloud provisioning and clown networking in general I mean they're behind I think you know in fact you don't even need them to start to it you can if you're small enough you can just keep if you're in AWS you can user it with us construct they have to insert themselves I mean they're running behind they're all certainly incumbents I love the term Andy Jesse's that Amazon Web Services uses old guard new guard to talk about the industry what does the new guard have to do the new and new brands that emerge in is it be more DevOps oriented neck Nets a cops is that net ops is the programmability these are some of the key discussions we've been having what's your view on how you this programmability their most important part is they have to make the network's simple for the dev teams and from you cannot have that you cannot make a phone call and get every line in two weeks anymore so if you move to that cloud you have to make the cloud construct as simple enough so that for example a dev team could say okay I'm going to create this VP see but this VP see automatically being associate to your account you cannot go out on the internet you have to go to the transit VP see so there's a lot of action in terms of the I am part and you have to put the control around them too so to make it as simple as possible you guys both I mean you're the COC aviatrix but also you guys a lot of experience going back to networking going back to I call the OSI mace which for us old folks know what that means but you guys know what this means I want to ask you the question as you look at the future of networking here a couple of objectives oh the cloud guys they got networking we're all set with them how do you respond to the fact that networking is changing and the cloud guys have their own networking what some of the pain points that's going on premises and these enterprises so are they good with the clouds what needs what are the key things that's going on in networking that makes it more than just the cloud networking what's your take on well as I said earlier that once you you could easily provision in the cloud you can easily connect to that cloud is when you start troubleshooting application in the cloud and try to scale so this that's where the problem occurs see what you're taking on it and you'll hear from the from the customers that that we have on stage and I think what happens is all the cloud the clouds by definition designed to the 80/20 rule which means they'll design 80% of the basic functionality and they'll lead to 20% extra functionality that of course every Enterprise needs they'll leave that to ISVs like aviatrix because why because they have to make money they have a service and they can't have huge instances for functionality that not everybody needs so they have to design to the common and that's they all do it right they have to and then the extra the problem is that Cambrian explosion that I talked about with enterprises that's holy that's what they need that they're the ones who need that extra 20% so that's that's what I see is is there's always gonna be that extra functionality the in in an automated and simple way that you talked about but yet powerful with up with the visible in control that they expect of on prep that that's that kind of combination that yin and the yang that people like us are providing some I want to ask you were gonna ask some of the cloud architect customer panels it's the same question this pioneers doing some work here and there's also the laggers who come in behind the early adopters what's gonna be the tipping point what are some of those conversations that the cloud architects are having out there or what's the signs that they need to be on this multi cloud or cloud native networking trend what are some the signals that are going on in their environment what are some of the thresholds or things that are going on that there can pay attention to well well once they have application and multiple cloud and they have they get wake up at 2:00 in the morning to troubleshoot them they don't know it's important so I think that's the that's where the robber will hit the road but as I said it's easier to prove it it's ok it's 80s it's easy use a transit gateway put a few V PCs and you're done and use create some presents like equinox and do Direct Connect and Express route with Azure that looks simple is the operations that's when they'll realize ok now I need to understand our car networking works I also need a tool that give me visibility and control not button tell me that I need to understand the basic underneath it as well what are some of the day in the life scenarios that you envision happening with multi Bob because you think about what's happening it kind of has that same vibe of interoperability choice multi-vendor because you have multi clouds essentially multi vendor these are kind of old paradigms that we've lived through the client server and internet working wave what are some of those scenarios of success and that might be possible it would be possible with multi cloud and cloud native networking well I think once you have good enough visibility to satisfy your customers you know not only like to keep the service running an application running but to be able to provision fast enough I think that's what you want to achieve small final question advice for folks watching on the live stream if they're sitting there as a cloud architect or a CXO what's your advice to them right now in this more because honestly public cloud check hybrid cloud they're working on that that gets on-premise is done now multi clouds right behind it what's your advice the first thing they should do is really try to understand cloud networking for each of their cloud providers and then understand the limitation and is what there's cloud service provider offers enough or you need to look to a third party but you don't look at a third party to start with especially an incumbent one so it's tempting to say on and I have a bunch of f5 experts nothing against that five I'm going to bring my five in the cloud when you can use a needle be that automatically understand Easy's and auto scaling and so on and you understand that's much simpler but sometimes you need you have five because you have requirements you have like AI rules and that kind of stuff that you use for years you cannot do it's okay I have requirement and that met I'm going to use legacy stuff and then you have to start thinking okay what about visibility control about the tree cloud but before you do that you have to understand the limitation of the existing cloud providers so first try to be as native as possible until things don't work after that you can start taking multi-cloud great insight somewhat thank you for coming someone in charge with Gardner thanks for sharing informatica is known as the leading enterprise cloud data management company we are known for being the top in our industry in at least five different products over the last few years especially we've been transforming into a cloud model which allows us to work better with the trends of our customers in order to see agile and effective in the business you need to make sure that your products and your offerings are just as relevant in all these different clouds than what you're used to and what you're comfortable with one of the most difficult challenges we've always had is that because we're a data company we're talking about data that a customer owns some of that data may be in the cloud some of that data may be on Prem some of that data may be actually in their data center in another region or even another country and having that data connect back to our systems that are located in the cloud has always been a challenge when we first started our engagement with aviatrix we only had one plan that was Amazon it wasn't till later that a jerk came up and all of a sudden we found hey the solution we already had in place for her aviatrix already working in Amazon and now works in Missouri as well before we knew what GCP came up but it really wasn't a big deal for us because we already had the same solution in Amazon and integer now just working in GCP by having a multi cloud approach we have access to all three of them but more commonly it's not just one it's actually integrations between multiple we have some data and ensure that we want to integrate with Amazon we have some data in GCP that we want to bring over to a data Lake assure one of the nice things about aviatrix is that it gives a very simple interface that my staff can understand and use and manage literally hundreds of VPNs around the world and while talking to and working with our customers who are literally around the world now that we've been using aviatrix for a couple years we're actually finding that even problems that we didn't realize we had were actually solved even before we came across the problem and it just worked cloud companies as a whole are based on reputation we need to be able to protect our reputation and part of that reputation is being able to protect our customers and being able to protect more importantly our customers data aviatrix has been helpful for us in that we only have one system that can manage this whole huge system in a simple easy direct model aviatrix is directly responsible for helping us secure and manage our customers not only across the world but across multiple clouds users don't have to be VPN or networking experts in order to be able to use the system all the members on my team can manage it all the members regardless of their experience can do different levels of it one of the unexpected advantages of aviatrix is that I don't have to sell it to my management the fact that we're not in the news at 3 o'clock in the morning or that we don't have to get calls in the middle of the night no news is good news especially in networking things that used to take weeks to build or done in hours I think the most important thing about a matrix is it provides me a Beatrix gives me a consistent model that I can use across multiple regions multiple clouds multiple customers okay welcome back to altitude 2020 for the folks on the livestream I'm John for Steve Mulaney with CEO of aviatrix for our first of two customer panels on cloud with cloud network architects we got Bobby Willoughby they gone Luis Castillo of National Instruments David should Nick with fact set guys welcome to the stage for this digital event come on up [Applause] [Music] hey good to see you thank you okay okay customer panelist is my favorite part we get to hear the real scoop gets a gardener given this the industry overview certainly multi clouds very relevant and cloud native networking is the hot trend with a live stream out there and the digital event so guys let's get into it the journey is you guys are pioneering this journey of multi cloud and cloud native networking and is soon gonna be a lot more coming so we want to get into the journey what's it been like is it real you got a lot of scar tissue and what are some of the learnings yeah absolutely so multi cloud is whether or not we we accepted as a network engineers is is a reality like Steve said about two years ago companies really decided to to just to just bite the bullet and and and move there whether or not whether or not we we accept that fact we need to now create a consistent architecture across across multiple clouds and that that is challenging without orchestration layers as you start managing different different tool sets and different languages across different clouds so that's it's really important that to start thinking about that guys on the other panelists here there's different phases of this journey some come at it from a networking perspective some come in from a problem troubleshooting which what's your experiences yeah so from a networking perspective it's been incredibly exciting it's kind of a once-in-a-generation 'el opportunity to look at how you're building out your network you can start to embrace things like infrastructure as code that maybe your peers on the systems teams have been doing for years but it just never really worked on bram so it's really it's really exciting to look at all the opportunities that we have and then all the interesting challenges that come up that you that you get to tackle an effect said you guys are mostly AWS right yep right now though we're we are looking at multiple clouds we have production workloads running in multiple clouds today but a lot of the initial work has been with Amazon and you've seen it from a networking perspective that's where you guys are coming at it from yep we evolved more from a customer requirement perspective started out primarily as AWS but as the customer needed more resources from Azure like HPC you know as your ad things like that even recently Google Google Analytics our journey has evolved into more of a multi cloud environment Steve weigh in on the architecture because this has been the big conversation I want you to lead this second yeah so I mean I think you guys agree the journey you know it seems like the journey started a couple years ago got real serious the need for multi cloud whether you're there today of course it's gonna be there in the future so that's really important I think the next thing is just architecture I'd love to hear what you you know had some comments about architecture matters it all starts I mean every Enterprise I talk to maybe talk about architecture and the importance of architecture maybe Bobby it's a fun architecture perspective we sorted a journey five years ago Wow okay and we're just now starting our fourth evolution of our network marketer and we call it networking security net SEC yeah versus Justice Network yeah and that fourth generation architectures be based primarily upon Palo Alto Networks an aviatrix I have Atrix doing the orchestration piece of it but that journey came because of the need for simplicity ok the need for a multi cloud orchestration without us having to go and do reprogramming efforts across every cloud as it comes along right I guess the other question I also had around architectures also Louis maybe just talk about I know we've talked a little bit about you know scripting right and some of your thoughts on that yeah absolutely so so for us we started we started creating the network constructs with cloud formation and we've we've stuck with that for the most part what's interesting about that is today on premise we have a lot of a lot of automation around around how we provision networks but cloud formation has become a little bit like the new manual for us so we we're now having issues with having the to automate that component and making it consistent with our on premise architecture making it consistent with Azure architecture and Google cloud so it's really interesting to see to see companies now bring that layer of abstraction that SEO and brought to the to the web side now it's going up into into the into the cloud networking architecture so on the fourth generation of you mentioned you're in the fourth gen architecture what do you guys what have you learned is there any lessons scar tissue what to avoid what worked what was some of the that's probably the biggest list and there is that when you think you finally figured it out you have it right Amazon will change something as you or change something you know transit gateways a game changer so in listening to the business requirements is probably the biggest thing we need to do up front but I think from a simplicity perspective we like I said we don't want to do things four times we want to do things one time we won't be able to write to an API which aviatrix has and have them do the orchestration for us so that we don't have to do it four times how important is architecture in the progression is it you guys get thrown in the deep end to solve these problems or you guys zooming out and looking at it it's that I mean how are you guys looking at the architecture I mean you can't get off the ground if you don't have the network there so all of those that we've gone through similar evolutions we're on our fourth or fifth evolution I think about what we started off with Amazon without a direct connect gate without a trans a gateway without a lot of the things that are available today kind of the 80/20 that Steve was talking about just because it wasn't there doesn't mean we didn't need it so we needed to figure out a way to do it we couldn't say oh you need to come back to the network team in a year and maybe Amazon will have a solution for it right you need to do it now and in evolve later and maybe optimize or change the way you're doing things in the future but don't sit around and wait you can't I'd love to have you guys each individually answer this question for the live stream because it comes up a lot a lot of cloud architects out in the community what should they be thinking about the folks that are coming into this proactively and/or realizing the business benefits are there what advice would you guys give them an architecture what should be they be thinking about and what are some guiding principles you could share so I would start with looking at an architecture model that that can that can spread and and give consistency they're different to different cloud vendors that you will absolutely have to support cloud vendors tend to want to pull you into using their native toolset and that's good if only it was realistic to talk about only one cloud but because it doesn't it's it's it's super important to talk about and have a conversation with the business and with your technology teams about a consistent model how do I do my day one work so that I'm not you know spending 80 percent of my time troubleshooting or managing my network because I'm doing that then I'm missing out on ways that I can make improvements or embrace new technologies so it's really important early on to figure out how do I make this as low maintenance as possible so that I can focus on the things that the team really should be focusing on Bobby your advice the architect I don't know what else I can do that simplicity operations is key right all right so the holistic view of j2 operation you mentioned let's can jump in day one is your your your getting stuff set up day two is your life after all right this is kind of what you're getting at David so what does that look like what are you envisioning as you look at that 20 mile stare at post multi-cloud world what are some of the things that you want in a day to operations yeah infrastructure is code is really important to us so how do we how do we design it so that we can fit start making network changes and fitting them into like a release pipeline and start looking at it like that rather than somebody logging into a router seoi and troubleshooting things on in an ad hoc nature so moving more towards the DevOps model yes anything on that day - yeah I would love to add something so in terms of day 2 operations you can you can either sort of ignore the day 2 operations for a little while where you get well you get your feet wet or you can start approaching it from the beginning the fact is that the the cloud native tools don't have a lot of maturity in that space and when you run into an issue you're gonna end up having a bad day going through millions and millions of logs just to try to understand what's going on so that's something that that the industry just now is beginning to realize it's it's such as such a big gap I think that's key because for us we're moving to more of an event-driven operations in the past monitoring got the job done it's impossible to modern monitor something there's nothing there when the event happens all right so the event-driven application and then detection is important yeah I think Gardiner was all about the cloud native wave coming into networking that's going to be here thing I want to get your guys perspectives I know you have different views of how you came on into the journey and how you're executing and I always say the beauties in the eye of the beholder and that kind of applies the network's laid out so Bobby you guys do a lot of high-performance encryption both on AWS and Azure that's kind of a unique thing for you how are you seeing that impact with multi cloud yeah and that's a new requirement for us to where we we have a requirement to encrypt and they never get the question should I encryption or not encrypt the answer is always yes you should encrypt when you can encrypt for our perspective we we need to migrate a bunch of data from our data centers we have some huge data centers and then getting that data to the cloud is the timely expense in some cases so we have been mandated that we have to encrypt everything leave from the data center so we're looking at using the aviatrix insane mode appliances to be able to encrypt you know 10 20 gigabits of data as it moves to the cloud itself David you're using terraform you got fire Ned you've got a lot of complexity in your network what do you guys look at the future for yours environment yeah so something exciting that or yeah now is fire net so for our security team they obviously have a lot of a lot of knowledge base around Palo Alto and with our commitments to our clients you know it's it's it's not very easy to shift your security model to a specific cloud vendor right so there's a lot of stuck to compliance of things like that where being able to take some of what you've you know you've worked on for years on Bram and put it in the cloud and have the same type of assurance that things are gonna work and be secured in the same way that they are on prem helps make that journey into the cloud a lot easier and Louis you guys got scripting and get a lot of things going on what's your what's your unique angle on this yeah no absolutely so full disclosure I'm not a not not an aviatrix customer yet it's okay we want to hear the truth that's good Ellis what are you thinking about what's on your mind no really when you when you talk about implementing the tool like this it's really just really important to talk about automation and focus on on value so when you talk about things like encryption and things like so you're encrypting tunnels and crypting the path and those things are it should it should should be second nature really when you when you look at building those back ends and managing them with your team it becomes really painful so tools like a Beatrix that that add a lot of automation it's out of out of sight out of mind you can focus on the value and you don't have to focus on so I gotta ask you guys I'll see aviatrix is here they're their supplier to this sector but you guys are customers everyone's pitching you stuff people are not going to buy my stuff how do you guys have that conversation with the suppliers like the cloud vendors and other folks what's that what's it like we're API all the way you got to support this what are some of the what are some of your requirements how do you talk to and evaluate people that walk in and want to knock on your door and pitch you something what's the conversation like it's definitely it's definitely API driven we we definitely look at the at the PAP i structure of the vendors provide before we select anything that that is always first in mind and also what a problem are we really trying to solve usually people try to sell or try to give us something that isn't really valuable like implementing a solution on the on the on the cloud isn't really it doesn't really add a lot of value that's where we go David what's your conversation like with suppliers you have a certain new way to do things as as becomes more agile and essentially the networking and more dynamic what are some of the conversation is with the either incumbents or new new vendors that you're having what do what do you require yeah so ease of use is definitely definitely high up there we've had some vendors come in and say you know hey you know when you go to set this up we're gonna want to send somebody on site and they're gonna sit with you for your day to configure it and that's kind of a red flag what wait a minute you know do we really if one of my really talented engineers can't figure it out on his own what's going on there and why is that so I you know having having some ease-of-use and the team being comfortable with it and understanding it is really important Bobby how about you I mean the old days was do a bake-off and you know the winner takes all I mean is it like that anymore but what's the Volvic a bake-off last year for us do you win so but that's different now because now when you when you get the product you can install the product and they double your energy or have it in a matter of minutes and so the key is is they can you be operational you know within hours or days instead of weeks but but do we also have the flexibility to customize it to meet your needs could you want to be you want to be put into a box with the other customers when you have needs that your pastor cut their needs yeah almost see the challenge that you guys are living where you've got the cloud immediate value depending how you can roll up any solutions but then you have might have other needs so you got to be careful not to buy into stuff that's not shipping so you're trying to be proactive at the same time deal with what you got I mean how do you guys see that evolving because multi-cloud to me is definitely relevant but it's not yet clear how to implement across how do you guys look at this baked versus you know future solutions coming how do you balance that so again so right now we we're we're taking the the ad hoc approach and experimenting with the different concepts of cloud and and really leveraging the the native constructs of each cloud but but there's a there's a breaking point for sure you don't you don't get to scale this like Alexa mom said and you have to focus on being able to deliver a developer they're their sandbox or they're their play area for the for the things that they're trying to build quickly and the only way to do that is with the with with some sort of consistent orchestration layer that allows you to so use a lot more stuff to be coming pretty quickly hides area I do expect things to start to start maturing quite quite quickly this year and you guys see similar trend new stuff coming fast yeah part of the biggest challenge we've got now is being able to segment within the network being able to provide segmentation between production on production workloads even businesses because we support many businesses worldwide and and isolation between those is a key criteria there so the ability to identify and quickly isolate those workloads is key so the CIOs that are watching or that are saying hey take that he'll do multi cloud and then you know the bottoms-up organization Nick pops you're kind of like off a little bit it's not how it works I mean what is the reality in terms of implementing you know in as fast as possible because the business benefits are but it's not always clear in the technology how to move that fast yeah what are some of the barriers one of the blockers what are the enablers I think the reality is is that you may not think you're multi-cloud but your business is right so I think the biggest barriers there is understanding what the requirements are and how best to meet those requirements and then secure manner because you need to make sure that things are working from a latency perspective that things work the way they did and get out of the mind shift that you know it was a cheery application in the data center it doesn't have to be a Tier three application in the cloud so lift and shift is is not the way to go yeah scale is a big part of what I see is the competitive advantage to a lot these clouds and needs to be proprietary network stacks in the old days and then open systems came that was a good thing but as clouds become bigger there's kind of an inherent lock in there with the scale how do you guys keep the choice open how're you guys thinking about interoperability what are some of the conversations and you guys are having around those key concepts well when we look at when we look at the upfront from a networking perspective it it's really key for you to just enable enable all the all the clouds to be to be able to communicate between them developers will will find a way to use the cloud that best suits their their business need and and like like you said it's whether whether you're in denial or not of the multi cloud fact that then your company is in already that's it becomes really important for you to move quickly yeah and I a lot of it also hinges on how well is the provider embracing what that specific cloud is doing so are they are they swimming with Amazon or Azure and just helping facilitate things they're doing the you know the heavy lifting API work for you or are they swimming upstream and they're trying to hack it all together in a messy way and so that helps you you know stay out of the lock-in because they're you know if they're doing if they're using Amazon native tools to help you get where you need to be it's not like Amazon's gonna release something in the future that completely you know makes you have designed yourself into a corner so the closer they're more than cloud native they are the more the easier it is to to deploy but you also need to be aligned in such a way that you can take advantage of those cloud native technologies will it make sense tgw is a game changer in terms of cost and performance right so to completely ignore that would be wrong but you know if you needed to have encryption you know teach Adobe's not encrypted so you need to have some type of a gateway to do the VPN encryption you know so the aviatrix tool give you the beauty of both worlds you can use tgw with a gateway Wow real quick in the last minute we have I want to just get a quick feedback from you guys I hear a lot of people say to me hey the I picked the best cloud for the workload you got and then figure out multi cloud behind the scenes so that seems to be do you guys agree with that I mean is it do I go Mull one cloud across the whole company or this workload works great on AWS that work was great on this from a cloud standpoint do you agree with that premise and then witness multi-cloud stitch them all together yeah from from an application perspective it it can be per workload but it can also be an economical decision certain enterprise contracts will will pull you in one direction that value but the the network problem is still the same doesn't go away yeah yeah yeah I mean you don't want to be trying to fit a square into a round Hall right so if it works better on that cloud provider then it's our job to make sure that that service is there and people can use it agree you just need to stay ahead of the game make sure that the network infrastructure is there secure is available and is multi cloud capable yeah I'm at the end of the day you guys just validating that it's the networking game now cloud storage compute check networking is where the action is awesome thanks for your insights guys appreciate you coming on the panel appreciate it thanks thank you [Applause] [Music] [Applause] okay welcome back on the live feed I'm John fritz T Blaney my co-host with aviatrix I'm with the cube for the special digital event our next customer panel got great another set of cloud network architects Justin Smith was aura Justin broadly with Ellie Mae and Amit Oh tree job with Koopa welcome to stage [Applause] all right thank you thank you okay he's got all the the cliff notes from the last session welcome back rinse and repeat yeah yeah we're going to go under the hood a little bit I think I think they nailed the what we've been reporting and we've been having this conversation around networking is where the action is because that's the end of the day you got a move a pack from A to B and you get workloads exchanging data so it's really killer so let's get started Amit what are you seeing as the journey of multi cloud as you go under the hood and say okay I got to implement this I have to engineer the network make it enabling make it programmable make it interoperable across clouds and that's like I mean almost sounds impossible to me what's your take yeah I mean it it seems impossible but if you are running an organization which is running infrastructure as a cordon all right it is easily doable like you can use tools out there that's available today you can use third-party products that can do a better job but but put your architecture first don't wait architecture may not be perfect put the best architecture that's available today and be agile to iterate and make improvements over the time we get to Justin's over here so I have to be careful when I point a question in Justin they both have the answer but okay journeys what's the journey been like I mean is there phases we heard that from Gartner people come in to multi cloud and cloud native networking from different perspectives what's your take on the journey Justin yeah I mean from our perspective we started out very much focused on one cloud and as we started doing errands we started doing new products the market the need for multi cloud comes very apparent very quickly for us and so you know having an architecture that we can plug in play into and be able to add and change things as it changes is super important for what we're doing in the space just in your journey yes for us we were very ad hoc oriented and the idea is that we were reinventing all the time trying to move into these new things and coming up with great new ideas and so rather than it being some iterative approach with our deployments that became a number of different deployments and so we shifted that tore in the network has been a real enabler of this is that it there's one network and it touches whatever cloud we want it to touch and it touches the data centers that we need it to touch and it touches the customers that we need it to touch our job is to make sure that the services that are available and one of those locations are available in all of the locations so the idea is not that we need to come up with this new solution every time it's that we're just iterating on what we've already decided to do before we get the architecture section I want to ask you guys a question I'm a big fan of you know let the app developers have infrastructure as code so check but having the right cloud run that workload I'm a big fan of that if it works great but we just heard from the other panel you can't change the network so I want to get your thoughts what is cloud native networking and is that the engine really that's the enabler for this multi cloud trend but you guys taken we'll start with Amit what do you think about that yeah so you are gonna have workloads running in different clouds and the workloads would have affinity to one cloud over other but how you expose that it matter of how you are going to build your networks how we are gonna run security how we are going to do egress ingress out of it so it's a big problem how do you split says what's the solution what's the end the key pain points and problem statement I mean the key pain point for most companies is how do you take your traditionally on-premise network and then blow that out to the cloud in a way that makes sense you know IP conflicts you have IP space you pub public eye peas and premise as well as in the cloud and how do you kind of make a sense of all of that and I think that's where tools like a v8 ryx make a lot of sense in that space from our site it's it's really simple its latency its bandwidth and availability these don't change whether we're talking about cloud or data center or even corporate IT networking so our job when when these all of these things are simplified into like s3 for instance and our developers want to use those we have to be able to deliver that and for a particular group or another group that wants to use just just GCP resources these aren't we have to support these requirements and these wants as opposed to saying hey that's not a good idea our job is to enable them not to disable them do you think you guys think infrastructure is code which I love that I think it's that's the future it is we saw that with DevOps but I do start getting the networking is it getting down to the network portion where it's network is code because storage and compute working really well is seeing all kubernetes and service master and network as code reality is it there is got work to do it's absolutely there I mean you mentioned net DevOps and it's it's very real I mean in Cooper we build our networks through terraform and on not only just out of fun build an API so that we can consistently build V nets and VPC all across in the same unit yeah and even security groups and then on top an aviatrix comes in we can peer the networks bridge bridge all the different regions through code same with you guys but yeah everything we deploy is done with automation and then we also run things like lambda on top to make changes in real time we don't make manual changes on our network in the data center funny enough it's still manual but the cloud has enabled us to move into this automation mindset and and all my guys that's what they focus on is bringing what now what they're doing in the cloud into the data center which is kind of opposite of what it should be that's full or what it used to be it's full DevOps then yes yeah I mean for us was similar on-premise still somewhat very manual although we're moving more Norton ninja and terraform concepts but everything in the production environment is colored Confirmation terraform code and now coming into the datacenter same I just wanted to jump in on a Justin Smith one of the comment that you made because it's something that we always talk about a lot is that the center of gravity of architecture used to be an on-prem and now it's shifted in the cloud and once you have your strategic architecture what you--what do you do you push that everywhere so what you used to see at the beginning of cloud was pushing the architecture on prem into cloud now I want to pick up on what you said to you others agree that the center of architect of gravity is here I'm now pushing what I do in the cloud back into on pram and and then so first that and then also in the journey where are you at from 0 to 100 of actually in the journey to cloud DUI you 50% there are you 10% yes I mean are you evacuating data centers next year I mean were you guys at yeah so there's there's two types of gravity that you typically are dealing with no migration first is data gravity and your data set and where that data lives and then the second is the network platform that interrupts all that together right in our case the data gravity sold mostly on Prem but our network is now extending out to the app tier that's going to be in cloud right eventually that data gravity will also move to cloud as we start getting more sophisticated but you know in our journey we're about halfway there about halfway through the process we're taking a handle of you know lift and shift and when did that start and we started about three years ago okay okay go by it's a very different story it started from a garage and one hundred percent on the clock it's a business spend management platform as a software-as-a-service one hundred percent on the cloud it was like ten years ago right yes yeah you guys are riding the wave love that architecture Justin I want to ask user you guys mentioned DevOps I mean obviously we saw the huge observability wave which is essentially network management for the cloud in my opinion right yeah it's more dynamic but this isn't about visibility we heard from the last panel you don't know what's being turned on or turned off from a services standpoint at any given time how is all this playing out when you start getting into the DevOps down well this this is the big challenge for all of us as visibility when you talk transport within a cloud you know we very interesting we we have moved from having a backbone that we bought that we own that would be data center connectivity we now I work for as or as a subscription billing company so we want to support the subscription mindset so rather than going and buying circuits and having to wait three months to install and then coming up with some way to get things connected and resiliency and redundancy I my backbone is in the cloud I use the cloud providers interconnections between regions to transport data across and and so if you do that with their native solutions you you do lose visibility there are areas in that that you don't get which is why controlling you know controllers and having some type of management plane is a requirement for us to do what we're supposed to do and provide consistency while doing it a great conversation I loved when you said earlier latency bandwidth I think availability with your sim pop3 things guys SLA I mean you just do ping times between clouds it's like you don't know what you're getting for round-trip times this becomes a huge kind of risk management black hole whatever you want to call blind spot how are you guys looking at the interconnects between clouds because you know I can see that working from you know ground to cloud I'm per cloud but when you start doing with multi clouds workload I mean SL leis will be all over the map won't they just inherently but how do you guys view that yeah I think we talked about workload and we know that the workloads are going to be different in different clouds but they are going to be calling each other so it's very important to have that visibility that you can see how data is flowing at what latency and what our ability is hour is there and our authority needs to operate on that so it's solely use the software dashboard look at the times and look at the latency in the old days strong so on open so on you try to figure it out and then your day is you have to figure out just and what's your answer to that because you're in the middle of it yeah I mean I think the the key thing there is that we have to plan for that failure we have to plan for that latency and our applications it's starting start tracking in your SLI something you start planning for and you loosely couple these services and a much more micro services approach so you actually can handle that kind of failure or that type of unknown latency and unfortunately the cloud has made us much better at handling exceptions a much better way you guys are all great examples of cloud native from day one and you guys had when did you have the tipping point moment or the Epiphany of saying a multi clouds real I can't ignore it I got to factor it into all my design design principles and and everything you're doing what's it was there a moment or was it was it from day one now there are two divisions one was the business so in business there was some affinity to not be in one cloud or to be in one cloud and that drove from the business side so it has a cloud architect our responsibility was to support that business and other is the technology some things are really running better in like if you are running dot network load or you are going to run machine learning or AI so that you have you would have that preference of one cloud over other so it was the bill that we got from AWS I mean that's that's what drives a lot of these conversations is the financial viability of what you're building on top of it which is so we this failure domain idea which is which is fairly interesting is how do I solve or guarantee against a failure domain you have methodologies with you know back-end direct connects or interconnect with GCP all of these ideas are something that you have to take into account but that transport layer should not matter to whoever we're building this for our job is to deliver the frames in the packets what that flows across how you get there we want to make that seamless and so whether it's a public internet API call or it's a back-end connectivity through Direct Connect it doesn't matter it just has to meet a contract that you signed with your application folks yeah that's the availability piece just on your thoughts on that I think any comment on that so actually multi clouds become something much more recent in the last six to eight months I'd say we always kind of had a very much an attitude of like moving to Amazon from our private cloud is hard enough why complicate it further but the realities of the business and as we start seeing you know improvements in Google and Asia and different technology spaces the need for multi cloud becomes much more important as well as those are acquisition strategies I matured we're seeing that companies that used to be on premise that we typically acquire are now very much already on a cloud and if they're on a cloud I need to plug them into our ecosystem and so that's really change our multi cloud story in a big way I'd love to get your thoughts on the clouds versus the clouds because you know you compare them Amazon's got more features they're rich with features I see the bills are haiku people using them but Google's got a great Network Google's networks pretty damn good and then you got a sure what's the difference between the clouds who where they've evolved something whether they peak in certain areas better than others what what are the characteristics which makes one cloud better do they have a unique feature that makes Azure better than Google and vice versa what do you guys think about the different clouds yeah to my experience I think there is the approach is different in many places Google has a different approach very devops friendly and you can run your workload like your network can spend regions time I mean but our application ready to accept that MS one is evolving I mean I remember ten years back Amazon's network was a flat network we will be launching servers and 10.0.0.0 mode multi-account came out so they are evolving as you are at a late start but because they have a late start they saw the pattern and they they have some mature set up on the I mean I think they're all trying to say they're equal in their own ways I think they all have very specific design philosophies that allow them to be successful in different ways and you have to kind of that in mine is your architectural and solution for example Amazon has a very much a very regional affinity they don't like to go cross region in their architecture whereas Google is very much it's a global network we're gonna think about as a global solution I think Google also has advantages there to market and so it has seen what asier did wrong it's seen what AWS did wrong and it's made those improvements and I think that's one of their big advantage at great scale to Justin thoughts on the cloud so yeah Amazon built from the system up and Google built from the network down so their ideas and approaches are from a global versus or regional I agree with you completely that that is the big number one thing but the if you look at it from the outset interestingly the the inability or the ability for Amazon to limit layer 2 broadcasting and and what that really means from a VPC perspective changed all the routing protocols you can use all the things that we have built inside of a data center to provide resiliency and and and make things seamless to users all of that disappeared and so because we had to accept that at the VPC level now we have to accept it at the LAN level Google's done a better job of being able to overcome those things and provide those traditional Network facilities to us it's just great panel can go all day here's awesome so I heard we could we'll get to the cloud native naive question so kind of think about what's not even what's cloud is that next but I got to ask you had a conversation with a friend he's like when is the new land so if you think about what the land was at a data center when is the new link you get talking about the cloud impact so that means st when the old st was kind of changing into the new land how do you guys look at that because if you think about it what lands were for inside a premises was all about networking high speed but now when you take the win and make essentially a land do you agree with that and how do you view this trend and is it good or bad or is it ugly and what's what you guys take on this yeah I think it's the it's a thing that you have to work with your application architect so if you are managing networks and if you're a sorry engineer you need to work with them to expose the unreliability that would bring in so the application has to hand a lot of this the difference in the Layton sees and and the reliability has to be worked through the application there land when same concept as it be yesterday I think we've been talking about for a long time the erosion of the edge and so is this is just a continuation of that journey we've been on for the last several years as we get more and more cloud native when we start about API is the ability to lock my data in place and not be able to access it really goes away and so I think this is just continuation that thing I think it has challenges we start talking about weighing scale versus land scale the tooling doesn't work the same the scale of that tooling is much larger and the need to automation is much much higher in a way than it was in a land that's what we're seeing so much infrastructure as code yeah yeah so for me I'll go back again to this its bandwidth and its latency right that bet define those two land versus win but the other thing that's comes up more and more with cloud deployments is where is our security boundary and where can I extend this secure aware appliance or set of rules to protect what's inside of it so for us we're able to deliver VRS or route forwarding tables for different segments wherever we're at in the world and so they're they're trusted to talk to each other but if they're gonna go to someplace that's outside of their their network then they have to cross a security boundary and where we enforce policy very heavily so for me there's it's not just land when it's it's how does environment get to environment more importantly that's a great point and security we haven't talked to yet but that's got to be baked in from the beginning that's architecture thoughts on security are you guys are dealing with it yeah start from the base have app to have security built in have TLS have encryption on the data I transit data at rest but as you bring the application to the cloud and they are going to go multi-cloud talking to over the Internet in some places well have apt web security I mean I mean our principals day Security's day zero every day and so we we always build it into our design we load entire architecture into our applications it's encrypt everything it's TLS everywhere it's make sure that that data is secured at all times yeah one of the cool trends at RSA just as a side note was the data in use encryption piece which is a homomorphic stuff was interesting all right guys final question you know we heard on the earlier panel was also trending at reinvent we take the tea out of cloud native it spells cloud naive okay they got shirts now he being sure he's gonna got this trend going what does that mean to be naive so if you're to your peers out there watching a live stream and also the suppliers that are trying to you know supply you guys with technology and services what's naive look like and what's native look like when is someone naive about implementing all this stuff so for me it's because we are in hundred-percent cloud for us its main thing is ready for the change and you will you will find new building blocks coming in and the network design will evolve and change so don't be naive and think that it's static you wall with the change I think the big naivety that people have is that well I've been doing it this way for twenty years and been successful it's going to be successful in cloud the reality is that's not the case you have to think some of the stuff a little bit differently and you need to think about it early enough so that you can become cloud native and really enable your business on cloud yeah for me it's it's being open minded right the the our industry the network industry as a whole has been very much I am smarter than everybody else and we're gonna tell everybody how it's going to be done and we have we fell into a lull when it came to producing infrastructure and and and so embracing this idea that we can deploy a new solution or a new environment in minutes as opposed to hours or weeks or four months in some cases is really important and and so you know it's are you being closed-minded native being open-minded exactly and and it took a for me it was that was a transformative kind of where I was looking to solve problems in a cloud way as opposed to looking to solve problems in this traditional old-school way all right I know we're out of time but I ask one more question so you guys so good it could be a quick answer what's the BS language when you the BS meter goes off when people talk to you about solutions what's the kind of jargon that you hear that's the BS meter going off what are people talking about that in your opinion you here you go that's total B yes what what triggers use it so that I have two lines out of movies that are really I can if the if I say them without actually thinking them it's like 1.21 jigowatts how you're out of your mind from Back to the Future right somebody's gonna be a bank and then and then Martin ball and and Michael Keaton and mr. mom when he goes to 22 21 whatever it takes yeah those two right there if those go off in my mind somebody's talking to me I know they're full of baloney so a lot of speeds would be a lot of speeds and feeds a lot of data did it instead of talking about what you're actually doing and solutioning for you're talking about well I does this this this and okay 220 221 anytime I start seeing the cloud vendor start benchmarking against each other it's your workload is your workload you need to benchmark yourself don't don't listen to the marketing on that that's that's all I'm a what triggers you and the bsp I think if somebody explains you a not simple they cannot explain you in simplicity then that's a good one all right guys thanks for the great insight great panel how about a round of applause practitioners DX easy solutions integrating company than we service customers from all industry verticals and we're helping them to move to the digital world so as a solutions integrator we interface with many many customers that have many different types of needs and they're on their IT journey to modernize their applications into the cloud so we encounter many different scenarios many different reasons for those migrations all of them seeking to optimize their IT solutions to better enable their business we have our CPS organization it's cloud platform services we support AWS does your Google Alibaba corkle will help move those workloads to wherever it's most appropriate no one buys the house for the plumbing equally no one buys the solution for the networking but if the plumbing doesn't work no one likes the house and if this network doesn't work no one likes a solution so network is ubiquitous it is a key component of every solution we do the network connectivity is the lifeblood of any architecture without network connectivity nothing works properly planning and building a scalable robust network that's gonna be able to adapt with the application needs its when encountering some network design and talking about speed the deployment aviatrix came up in discussion and we then further pursued an area DHT products that incorporated aviatrix is part of a new offering that we are in the process of developing that really enhances our ability to provide cloud connectivity for the lance cloud connectivity there's a new line of networking services that we're getting into as our clients move into hybrid cloud networking it is much different than our traditional based services an aviatrix provides a key component in that service before we found aviatrix we were using just native peering connections but there wasn't a way to visualize all those peering connections and with multiple accounts multiple contacts for security with a v8 church we were able to visualize those different peering connections of security groups it helped a lot especially in areas of early deployment scenarios were quickly able to then take those deployment scenarios and turn them into scripts that we can then deploy repeatedly their solutions were designed for work with the cloud native capabilities first and where those cloud native capabilities fall short they then have solution sets that augment those capabilities I was pleasantly surprised number one with the aviatrix team as a whole in their level of engagement with us you know we weren't only buying the product we were buying a team that came on board to help us implement and solution that was really good to work together to learn both what aviatrix had to offer as well as enhancements that we had to bring that aviatrix was able to put into their product and meet our needs even better aviatrix was a joy to find because they really provided us the technology that we needed in order to provide multi cloud connectivity that really added to the functionality that you can't get from the basic law providing services we're taking our customers on a journey to simplify and optimize their IT infrastructure aviatrix certainly has made my job much easier okay welcome back to altitude 2020 for the digital event for the live feed welcome back I'm John Ford with the cube with Steve Mulaney CEO aviatrix for the next panel from global system integrators the folks who are building and working with folks on their journey to multi cloud and cloud native networking we've got a great panel George Buckman with dxc and Derek Monahan with wwt welcome to the stage [Applause] [Music] okay you guys are the ones out there advising building and getting down and dirty with multi cloud and cloud native networking we heard from the customer panel you can see the diversity of where people come into the journey of cloud it kind of depends upon where you are but the trends are all clear cloud native networking DevOps up and down the stack this has been the main engine what's your guys take of the disk journey to multi cloud what do you guys seeing yeah it's it's critical I mean we're seeing all of our enterprise customers enter into this they've been through the migrations of the easy stuff you know now they're trying to optimize and get more improvement so now the tough stuffs coming on right and you know they need their data processing near where their data is so that's driving them to a multi cloud environment okay we heard some of the edge stuff I mean you guys are exactly you've seen this movie before but now it's a whole new ballgame what's your take yeah so I'll give you a hint so our practice it's not called the cloud practice it's the multi cloud practice and so if that gives you a hint of how we approach things it's very consultative and so when we look at what the trends are let's look a little year ago about a year ago we were having conversations with customers let's build a data center in the cloud let's put some VP C's let's throw some firewalls with some DNS and other infrastructure out there and let's hope it works this isn't a science project so what we're trying we're starting to see is customers are starting to have more of a vision and we're helping with that consultative nature but it's totally based on the business and you got to start understanding how the lines of business are using the apps and then we evolved into that next journey which is a foundational approach to what are some of the problem statement customers are solving when they come to you what are the top things that are on their my house or the ease of use of jelly all that stuff but what specifically they did digging into yeah some complexity I think when you look at multi cloud approach in my view is network requirements are complex you know I think they are but I think the approach can be let's simplify that so one thing that we try to do and this is how we talk to customers is let's just like you simplify an aviatrix simplifies the automation orchestration of cloud networking we're trying to simplify the design the planning implementation of infrastructure across multiple workloads across multiple platforms and so the way we do it is we sit down we look at not just use cases and not just the questions in common we anticipate we actually build out based on the business and function requirements we build out a strategy and then create a set of documents and guess what we actually build in the lab and that lab that we platform we built proves out this reference architecture actually works absolutely we implement similar concepts I mean we they're proven practices they work great so well George you mentioned that the hard part is now upon us are you referring to networking what is specifically were you getting at Tara so the easy parts done now so for the enterprises themselves migrating their more critical apps or more difficult apps into the environments you know they've just we've just scratched the surface I believe on what enterprises that are doing to move into the cloud to optimize their environments to take advantage of the scale and speed to deployment and to be able to better enable their businesses so they're just now really starting the >> so do you get you guys see what I talked about them in terms of their Cambrian explosion I mean you're both monster system integrators with you know top fortune enterprise customers you know really rely on you for for guidance and consulting and so forth and boy they're networks is that something that you you've seen I mean does that resonate did you notice a year and a half ago and all of a sudden the importance of cloud for enterprise shoot up yeah I mean we're seeing it okay in our internal environment as yeah you know we're a huge company or right customer zero or an IT so we're experiencing that internal okay and every one of our other customers so I have another question oh I don't know the answer to this and the lawyer never asks a question that you don't know the answer to but I'm gonna ask it anyway d XE @ wwt massive system integrators why aviatrix yep so great question Steve so I think the way we approach things I think we have a similar vision a similar strategy how you approach things how we approach things that it worldwide technology number one we want to simplify the complexity and so that's your number one priorities let's take the networking but simplify it and I think part of the other point I'm making is we have we see this automation piece as not just an afterthought anymore if you look at what customers care about visibility and automation is probably the at the top three maybe the third on the list and I think that's where we see the value and I think the partnership that we're building and what I what I get excited about is not just putting yours in our lab and showing customers how it works it's Co developing a solution with you figuring out hey how can we make this better right mr. piller is a huge thing Jenna insecurity alone Network everything's around visibility what automation do you see happening in terms of progression order of operations if you will it's the low-hanging fruit what are people working on now and what are what are some of the aspirational goals around when you start thinking about multi cloud and automation yep so I wanted to get back to answer that question I want to answer your question you know what led us there and why aviatrix you know in working some large internal IT projects and and looking at how we were going to integrate those solutions you know we like to build everything with recipes where Network is probably playing catch-up in the DevOps world but with a DevOps mindset looking to speed to deploy support all those things so when you start building your recipes you take a little of this a little of that and you mix it all together well when you look around you say wow look there's this big bag of a VHS let me plop that in that solves a big part of my problems that I have to speed to integrate speed to deploy and the operational views that I need to run this so that was 11 years about reference architectures yeah absolutely so you know they came with a full slate of reference architectures already the out there and ready to go that fit our needs so it's very very easy for us to integrate those into our recipes what do you guys think about all the multi vendor interoperability conversations that have been going on choice has been a big part of multi cloud in terms of you know customers want choice didn't you know they'll put a workload in the cloud that works but this notion of choice and interoperability is become a big conversation it is and I think our approach and that's why we talk to customers is let's let's speed and be risk of that decision making process and how do we do that because the interoperability is key you're not just putting it's not just a single vendor we're talking you know many many vendors I mean think about the average number of cloud applications a customer uses a business and enterprise business today you know it's it's above 30 it's it's skyrocketing and so what we do and we look at it from an Billy approaches how do things interoperate we test it out we validate it we build a reference architecture it says these are the critical design elements now let's build one with aviatrix and show how this works with aviatrix and I think the the important part there though is the automation piece that we add to it invisibility so I think the visibility is what's what I see lacking across the industry today and the cloud needed that's been a big topic yep okay in terms of aviatrix that you guys see them coming in there one of the ones that are emerging and the new brands emerging with multi cloud you still got the old guard incumbents with huge footprints how our customers dealing with that that kind of component in dealing with both of them yeah I mean where we have customers that are ingrained with a particular vendor and you know we have partnerships with many vendors so our objective is to provide the solution that meets that client and you they all want multi vendor they all want interoperability correct all right so I got to ask you guys a question while we were defining de to operations what does that mean I mean you guys are looking at the big business and technical components of architecture what does de two operations mean what's the definition of that yeah so I think from our perspective my experience we you know de to operations whether it's it's not just the you know the orchestration piece and setting up and let it a lot of automate and have some you know change control you're looking at this from a data perspective how do I support this ongoing and make it easy to make changes as we evolve that the the cloud is very dynamic the the nature of how that fast is expanding the number of features is astonishing trying to keep up to date with a number of just networking capabilities and services that are added so I think day to operation starts with a fundable understanding of you know building out supporting a customer's environments and making it the automation piece easy from from you know a distance I think yeah and you know taking that to the next level of being able to enable customers to have catalog items that they can pick and choose hey I need this network connectivity from this cloud location back to this on pram and being able to have that automated and provisioned just simply by ordering it for the folks watching out there guys take a minute to explain as you guys are in the trenches doing a lot of good work what are some of the engagement that you guys get into how does that progress what is that what's what happens there they call you up and say hey I need multi-cloud or you're already in there I mean take us through why how someone can engage to use a global si to come in and make this thing happen what's looks like typical engagement look like yeah so from our perspective we typically have a series of workshops in a methodology that we kind of go along the journey number one we have a foundational approach and I don't mean foundation meaning the network foundation that's a very critical element we got a factor in security we got a factor in automation so we think about foundation we do a workshop that starts with education a lot of times we'll go in and we'll just educate the customer what does VPC sharing you know what is a private link and Azure how does that impact your business you know customers I want to share services out in an ecosystem with other customers and partners well there's many ways to accomplish that so our goal is to you know understand those requirements and then build that strategy with them thoughts George oh yeah I mean I'm one of the guys that's down in the weeds making things happen so I'm not the guy on the front line interfacing with the customers every day but we have a similar approach you know we have a consulting practice that will go out and and apply their practices to see what those and when do you parachute in yeah when I then is I'm on the back end working with our offering development leads for the networking so we understand or seeing what customers are asking for and we're on the back end developing the solutions that integrate with our own offerings as well as enable other customers to just deploy quickly to meet their connectivity needs it so the patterns are similar great final question for you guys I want to ask you to paint a picture of what success looks like and you know for name customers you don't forget in reveal of kind of who they are but what does success look like in multi-cloud as you as you paint a picture for the folks here and watching on the live stream it's if someone says hey I want to be multi-cloud I got to have my operations agile I want full DevOps I want programmability security built in from day zero what does success look like yeah I think success looks like this so when you're building out a network the network is a harder thing to change than some other aspects of cloud so what we think is even if you're thinking about that second cloud which we have most of our customers are on to public clouds today they might be dabbling in that is you build that network foundation an architecture that takes in consideration where you're going and so once we start building that reference architecture out that shows this is how to sit from a multi-cloud perspective not a single cloud and let's not forget our branches let's not forget our data centers let's not forget how all this connects together because that's how we define multi-cloud it's not just in the cloud it's on Prem and it's off Prem and so collectively I think the key is also is that we provide them an hld you got to start with in a high-level design that can be tweaked as you go through the journey but you got to give a solid structural foundation and that networking which we think most customers think as not not the network engineers but as an afterthought we want to make that the most critical element before you start the journey Jorge from your seed had a success look for you so you know it starts out on these journeys often start out people not even thinking about what is gonna happen what what their network needs are when they start their migration journey to the cloud so I want this success to me looks like them being able to end up not worrying about what's happening in the network when they move to the cloud good guys great insight thanks for coming on share and pen I've got a round of applause the global system integrators [Applause] [Music] okay welcome back from the live feed I'm shuffle with the cube Steve Eleni CEO of aviatrix my co-host our next panel is the aviatrix certified engineers also known as aces this is the folks that are certified their engineering they're building these new solutions please welcome Toby Foster min from Attica Stacy linear from Terra data and Jennifer Reid with Victor Davis to the stage I was just gonna I was just gonna rip you guys and say where's your jackets and Jen's got the jacket on okay good love the aviatrix aces pile of gear there above the clouds soaring to new heights that's right so guys aviatrix aces love the name I think it's great certified this is all about getting things engineered so there's a level of certification I want to get into that but first take us through the day in the life of an ace and just to point out Stacey's a squad leader so he's like a squadron leader Roger and leader yeah squadron leader so he's got a bunch of aces underneath him but share your perspective day-in-the-life Jeff we'll start with you sure so I have actually a whole team that works for me both in the in the North America both in the US and in Mexico and so I'm eagerly working to get them certified as well so I can become a squad leader myself but it's important because one of the the critical gaps that we've found is people having the networking background because they're you graduate from college and you have a lot of computer science background you can program you've got Python but networking in packets they just don't get and so just taking them through all the processes that it's really necessary to understand when you're troubleshooting is really critical mm-hmm and because you're gonna get an issue where you need to figure out where exactly is that happening on the network you know is my my issue just in the V PCs and on the instant side is a security group or is it going on print and this is something actually embedded within Amazon itself I mean I should troubleshot an issue for about six months going back and forth with Amazon and it was the vgw VPN because they were auto-scaling on two sides and we ended up having to pull out the Cisco's and put in aviatrix so I could just say okay it's fixed and actually actually helped the application teams get to that and get it solved yeah but I'm taking a lot of junior people and getting them through that certification process so they can understand and see the network the way I see the network I mean look I've been doing this such for 25 years but I got out when I went in the Marine Corps that's what I did and coming out the network is still the network but people don't get the same training they get they got in the 90s it's just so easy just write some software and they work takes care of itself yes I'll be will get I'll come back to that I want to come back to that that problem solved with Amazon but Toby I think the only thing I have to add to that is that it's always the network fault as long as I've been in network have always been the network's fault and I'm even to this day you know it's still the network's fault and part of being a network guy is that you need to prove when it is and when it's not your fault and that means you need to know a little bit about a hundred different things to make that and now you got a full stack DevOps you gotta know a lot more times another hundred and these times are changing yeah they say you're a squadron leader I get that right what is what does a squadron leader first can you describe what it is I think probably just leading all the network components of it but not they from my perspective when to think about what you asked them was it's about no issues and no escalation soft my day is a good that's a good day yes it's a good day Jennifer you mentioned the Amazon thing this brings up a good point you know when you have these new waves come in you have a lot of new things newly use cases a lot of the finger-pointing it's that guy's problem that girl's problem so what is how do you solve that and how do you get the young guns up to speed is there training is that this is where the certification comes in well is where the certification is really going to come in I know when we we got together at reinvent one of the the questions that that we had with Stephen the team was what what should our certification look like you know she would just be teaching about what aviatrix troubleshooting brings to bear but what should that be like and I think Toby and I were like no no no that's going a little too high we need to get really low because the the better someone can get at actually understanding what actually happening in the network and and where to actually troubleshoot the problem how to step back each of those processes because without that it's just a big black box and they don't know you know because everything is abstracted in Amazon Internet and Azure and Google is substracted and they have these virtual gateways they have VPNs that you just don't have the logs on it's you just don't know and so then what tools can you put in front of them of where they can look because there are full logs well as long as we turned on the flow logs when they built it you know and there's like each one of those little things that well if they had decided to do that when they built it it's there but if you can come in later to really supplement that with training to actual troubleshoot and do a packet capture here as it's going through then teaching them how to read that even yeah Toby we were talking before we came on up on stage about your career you've been networking all your time and then you know you're now entering a lot of younger people how is that going because the people who come in fresh they don't have all the old war stories they don't know you talk about you know that's dimmer fault I walk in bare feet in the snow when I was your age I mean it's so easy now right they say what's your take on how you train the young P so I've noticed two things one is that they are up to speed a lot faster in generalities of networking they can tell you what a network is in high school level now where I didn't learn that too midway through my career and they're learning it faster but they don't necessarily understand why it's that way or you know everybody thinks that it's always slash 24 for a subnet and they don't understand why you can break it down smaller why it's really necessary so the the ramp up speed is much faster for these guys that are coming in but they don't understand why and they need some of that background knowledge to see where it's coming from and why is it important and old guys that's where we thrive Jennifer you mentioned you you got in from the Marines health spa when you got into networking how what was it like then and compared it now almost like we heard earlier static versus dynamic don't be static cuz then you just set the network you got a perimeter yeah no there was no such thing ya know so back in the day I mean I mean we had banyan vines for email and you know we had token ring and I had to set up token ring networks and figure out why that didn't work because how many of things were actually sharing it but then actually just cutting fiber and running fiber cables and dropping them over you know shelters to plug them in and oh crap they swung it too hard and shattered it now I gotta be great polished this thing and actually shoot like to see if it works I mean that was the network crimped five cat5 cables to run an Ethernet you know and then from that just said network switches dumb switches like those were the most common ones you had then actually configuring routers and you know logging into a Cisco router and actually knowing how to configure that and it was funny because I had gone all the way up and was a software product manager for a while so I've gone all the way up the stack and then two and a half three years ago I came across to to work with entity group that it became Victor Davis but we went to help one of our customers Davis and it was like okay so we need to fix the network okay I haven't done this in 20 years but all right let's get to it you know because it really fundamentally does not change it's still the network I mean I've had people tell me well you know when we go to containers we will not have to worry about the network and I'm like yeah you don't I do and then with this were the program abilities it really interesting so I think this brings up the certification what are some of the new things that people should be aware of that come in with the aviatrix ace certification what are some of the highlights can you guys share some of the some of the highlights around the certifications I think some of the importance is that it's it doesn't need to be vendor specific for network generality or basic networking knowledge and instead of learning how Cisco does something or how Palo Alto does something we need to understand how and why it works as a basic model and then understand how each vendor has gone about that problem and solved it in a general that's true in multi cloud as well you can't learn how cloud networking works without understanding how a double u.s. senator and GCP are all slightly the same but slightly different and some things work and some things don't I think that's probably the number one take I think having a certification across clouds is really valuable cuz we heard the global si help the business issues what does it mean to do that is it code is that networking is it configuration is that aviatrix what is the I mean op C aviatrix is the ASA certification but what is it about the multi cloud that makes it multi networking and multi vendor easy answer is yes so you got to be a generalist getting your hands and all you have to be right it takes experience because it's every every cloud vendor has their own certification whether that's hops and advanced networking and advanced security or whatever it might be yeah they can take the test but they have no idea how to figure out what's wrong with that system and the same thing with any certification but it's really getting your hands in there and actually having to troubleshoot the problems you know actually work the problem you know and calm down it's going to be okay I mean because I don't know how many calls I've been on or even had aviatrix join me on it's like okay so everyone calm down let's figure out what's happening it's like we've looked at that screen three times looking at it again it's not gonna solve that problem right but at the same time you know remaining calm but knowing that it really is I'm getting a packet from here to go over here it's not working so what could be the problem you know and actually stepping them through with those scenarios but that's like you only get that by having to do it you know and seeing it and going through it and then I have a question so we you know I just see it we started this program maybe months ago we're seeing a huge amount of interest I mean we're oversubscribed on all the training sessions we've got people flying from around the country even with coronavirus flying to go to Seattle to go to these events were oversubscribed good is that watching leader would put there yeah is that something that you see in your organization's are you recommending that to people do you see I mean I'm just I guess I'm surprised I'm not surprised but I'm really surprised by the demand if you would of this multi cloud network certification because it really isn't anything like that is that something you guys can comment on or do you see the same things in your organization's I say from my side because we operate in the multi cloud environment so it really helps and it's beneficial for us yeah I think I would add that uh networking guys have always needed to use certifications to prove that they know what they know right it's not good enough to say yeah I know IP addresses or I know how a network works and a couple little check marks or a little letters buying helps give you validity um so even in our team we can say hey you know we're using these certifications to know that you know enough of the basics and enough of the understandings that you have the tools necessary right so I guess my final question for you guys is why an eighth certification is relevant and then second part is share what the livestream folks who aren't yet a certified or might want to jump in to be AVH or certified engineers why is it important so why is it relevant and why shouldn't someone want to be an ace-certified I'm uses the right engineer I think my views a little different I think certification comes from proving that you have the knowledge not proving that you get a certification to get no I mean they're backwards so when you've got the training and the understanding and the you use that to prove and you can like grow your certification list with it versus studying for a test to get a certification and have no understanding of ok so that who is the right person that look at this is saying I'm qualified is it a network engineer is it a DevOps person what's your view you know is it a certain you know I think cloud is really the answer it's the as we talked like the edge is getting eroded so is the network definitions eating eroded we're getting more and more of some network some DevOps some security lots and lots of security because network is so involved in so many of them that's just the next progression there I would say I expand that to more automation engineers because we have those now probably extended as well well I think that the training classes themselves are helpful especially the entry-level ones for people who may be quote-unquote cloud architects but I've never done anything and networking for them to understand why we need those things to really work whether or not they go through to eventually get a certification is something different but I really think fundamentally understanding how these things work it makes them a better architect makes them better application developer but even more so as you deploy more of your applications into the cloud really getting an understanding even from our people who have tradition down on Prem networking they can understand how that's going to work in the cloud - well I know we've got just under 30 seconds left I want to get one more question than just one more for the folks watching that are maybe younger that don't have that networking training from your experiences each of you can answer why is it should they know about networking what's the benefit what's in it for them motivate them share some insights and why they should go a little bit deeper in networking Stacey we'll start with you we'll go down I'd say it's probably fundamental right if you don't deliver solutions networking use the very top I would say if you fundamental of an operating system running on a machine how those machines talk together as a fundamental change is something that starts from the base and work your way up right well I think it's a challenge because you you've come from top down now you're gonna start looking from bottom up and you want those different systems to cross communicate and say you built something and you're overlapping IP space not that that doesn't happen but how can I actually make that still operate without having to reappear e-platform it's like those challenges like those younger developers or sis engineers can really start to get their hands around and understand those complexities and bring that forward in their career they got to know the how the pipes are working and because know what's going some plumbing that's right and the works a how to code it that's right awesome thank you guys for great insights ace certified engineers also known as aces give a round of applause thank you okay all right that concludes my portion thank you Steve thanks for have Don thank you very much that was fantastic everybody round of applause for John Currier yeah so great event great event I'm not going to take long we've got we've got lunch outside for that for the people here just a couple of things just call to action right so we saw the Aces you know for those of you out on the stream here become a certified right it's great for your career it's great for knowledge is is fantastic it's not just an aviatrix thing it's gonna teach you about cloud networking multi-cloud networking with a little bit of aviatrix exactly what the Cisco CCIE program was for IP network that type of the thing that's number one second thing is is is is learn right so so there's a there's a link up there for the four to join the community again like I started this this is a community this is the kickoff to this community and it's a movement so go to what a v8 community bh6 comm starting a community at multi cloud so you know get get trained learn I'd say the next thing is we're doing over a hundred seminars in across the United States and also starting into Europe soon will come out and will actually spend a couple hours and talk about architecture and talk about those beginning things for those of you on the you know on the livestream in here as well you know we're coming to a city near you go to one of those events it's a great way to network with other people that are in the industry as well as to start to learn and get on that multi-cloud journey and then I'd say the last thing is you know we haven't talked a lot about what aviatrix does here and that's intentional we want you you know leaving with wanting to know more and schedule get with us in schedule a multi our architecture workshop session so we we sit out with customers and we talk about where they're at in that journey and more importantly where they're going in that in-state architecture from networking compute storage everything and everything you heard today every panel kept talking about architecture talking about operations those are the types of things that we saw we help you cook define that canonical architecture that system architecture that's yours so for so many of our customers they have three by five plotted lucid charts architecture drawings and it's the customer name slash aviatrix arc network architecture and they put it on their whiteboard that's what what we and that's the most valuable thing they get from us so this becomes their twenty-year network architecture drawing that they don't do anything without talking to us and look at that architecture that's what we do in these multi hour workshop sessions with customers and that's super super powerful so if you're interested definitely call us and let's schedule that with our team so anyway I just want to thank everybody on the livestream thank everybody here hopefully it was it was very useful I think it was and joined the movement and for those of you here join us for lunch and thank you very much [Applause] [Music]

(electronic music) >> From Santa Clara, California in the heart of Silicon Valley, its theCUBE. Covering Altitude 2020, brought to you by Aviatrix. (electronic music) >> Female pilot: Good morning, ladies and gentlemen, this is your captain speaking, we will soon be taking off on our way to altitude. (upbeat music) Please keep your seat belts fastened and remain in your seat. We will be experiencing turbulence, until we are above the clouds. (thunder blasting) (electronic music) (seatbelt alert sounds) Ladies and gentlemen, we are now cruising at altitude. Sit back and enjoy the ride. (electronic music) >> Female pilot: Altitude is a community of thought leaders and pioneers, cloud architects and enlightened network engineers, who have individually and are now collectively, leading their own IT teams and the industry. On a path to lift cloud networking above the clouds. Empowering enterprise IT to architect, design and control their own cloud network, regardless of the turbulent clouds beneath them. It's time to gain altitude. Ladies and gentlemen, Steve Mullaney, president and CEO of Aviatrix. The leader of multi-cloud networking. (electronic music) (audience clapping) >> Steve: All right. (audience clapping) Good morning everybody, here in Santa Clara as well as to the millions of people watching the livestream worldwide. Welcome to Altitude 2020, all right. So, we've got a fantastic event, today, I'm really excited about the speakers that we have today and the experts that we have and really excited to get started. So, one of the things I wanted to share was this is not a one-time event. This is not a one-time thing that we're going to do. Sorry for the Aviation analogy, but, you know, Sherry Wei, aviatrix means female pilot so everything we do has an aviation theme. This is a take-off, for a movement. This isn't an event, this is a take-off of a movement. A multi-cloud networking movement and community that we're inviting all of you to become part of. And why we're doing that, is we want to enable enterprises to rise above the clouds, so to speak and build their network architecture, regardless of which public cloud they're using. Whether it's one or more of these public clouds. So the good news, for today, there's lots of good news but this is one good news, is we don't have any PowerPoint presentations, no marketing speak. We know that marketing people have their own language. We're not using any of that, and no sales pitches, right? So instead, what are we doing? We're going to have expert panels, we've got Simon Richard, of Gartner here. We've got ten different network architects, cloud architects, real practitioners that are going to share their best practices and their real world experiences on their journey to the multi-cloud. So, before we start, everybody know what today is? In the U.S., it's Super Tuesday. I'm not going to get political, but Super Tuesday there was a bigger, Super Tuesday that happened 18 months ago. And Aviatrix employees know what I'm talking about. Eighteen months ago, on a Tuesday, every enterprise said, "I'm going to go to the cloud". And so what that was, was the Cambrian explosion, for cloud, for the enterprise. So, Frank Cabri, you know what a Cambrian explosion is. He had to look it up on Google. 500 million years ago, what happened, there was an explosion of life where it went from very simple single-cell organisms to very complex, multi-cell organisms. Guess what happened 18 months ago, on a Tuesday, I don't really know why, but every enterprise, like I said, all woke up that day and said, "Now I'm really going to go to cloud" and that Cambrian explosion of cloud meant that I'm moving from a very simple, single cloud, single-use case, simple environment, to a very complex, multi-cloud, complex use case environment. And what we're here today, is we're going to go undress that and how do you handle those, those complexities? And, when you look at what's happening, with customers right now, this is a business transformation, right? People like to talk about transitions, this is a transformation and it's actually not just a technology transformation, it's a business transformation. It started from the CEO and the Boards of enterprise customers where they said, "I have an existential threat to the survival of my company." If you look at every industry, who they're worried about is not the other 30-year-old enterprise. What they're worried about is the three year old enterprise that's leveraging cloud, that's leveraging AI, and that's where they fear that they're going to actually wiped out, right? And so, because of this existential threat, this is CEO led, this is Board led, this is not technology led, it is mandated in the organizations. We are going to digitally transform our enterprise, because of this existential threat and the movement to cloud is going to enable us to go do that. And so, IT is now put back in charge. If you think back just a few years ago, in cloud, it was led by DevOps, it was led by the applications and it was, like I said, before the Cambrian explosion, it was very simple. Now, with this Cambrian explosion, an enterprise is getting very serious and mission critical. They care about visibility, they care about control, they care about compliance, conformance, everything, governance. IT is in charge and that's why we're here today to discuss that. So, what we're going to do today, is much of things but we're going to validate this journey with customers. >> Steve: Did they see the same thing? We're going to validate the requirements for multi-cloud because, honestly, I've never met an enterprise that is not going to be multicloud. Many are one cloud today but they all say, " I need to architect my network for multiple clouds", because that's just what, the network is there to support the applications and the applications will run in whatever cloud it runs best in and you have to be prepared for that. The second thing is, is architecture. Again, with IT in charge, you, architecture matters. Whether its your career, whether its how you build your house, it doesn't matter. Horrible architecture, your life is horrible forever. Good architecture, your life is pretty good. So, we're going to talk about architecture and how the most fundamental and critical part of that architecture and that basic infrastructure is the network. If you don't get that right, nothing works, right? Way more important than compute. Way more important than storage. Network is the foundational element of your infrastructure. Then we're going to talk about day two operations. What does that mean? Well day one is one day of your life, where you wire things up they do and beyond. I tell everyone in networking and IT -- it's every day of your life. And if you don't get that right, your life is bad forever. And so things like operations, visibility, security, things like that, how do I get my operations team to be able to handle this in an automated way because it's not just about configuring it in the cloud, it's actually about how do I operationalize it? And that's a huge benefit that we bring as Aviatrix. And then the last thing we're going to talk and it's the last panel we have, I always sayyou can't forget about the humans, right? So all this technology, all these things that we're doing, it's always enabled by the humans. At the end of the day, if the humans fight it, it won't get deployed. And we have a massive skills gap, in cloud and we also have a massive skills shortage. You have everyone in the world trying to hire cloud network architects, right? There's just not enough of them going around. So, at Aviatrix, we said as leaders do, "We're going to help address that issue and try to create more people." We created a program, what we call the ACE Program, again, aviation theme, it stands for Aviatrix Certified Engineer. Very similar to what Cisco did with CCIEs where Cisco taught you about IP networking, a little bit of Cisco, we're doing the same thing, we're going to teach network architects about multicloud networking and architecture and yeah, you'll get a little bit of Aviatrix training in there, but this is the missing element for people's careers and also within their organizations. So we're going to go talk about that. So, great, great event, great show. We're going to try to keep it moving. I next want to introduce, my host, he is the best in the business, you guys have probably seen him multiple, many times, he is the co-CEO and co founder of theCUBE, John Furrier. (audience clapping) (electronic music) >> John: Okay, awesome, great speech there, awesome. >> Yeah. >> I totally agree with everything you said about the explosion happening and I'm excited, here at the heart of silicon valley to have this event. It's a special digital event with theCUBE and Aviatrix, where we're live-streaming to, millions of people, as you said, maybe not a million. >> Maybe not a million. (laughs) Really to take this program to the world and this is really special for me, because multi-cloud is the hottest wave in cloud. And cloud-native networking is fast becoming the key engine, of the innovations, so we got an hour and a half of action-packed programming. We have a customer panel. Two customer panels. Before that Gartner's going to come out, talk about the industry. We have global system integrators, that will talk about, how their advising and building these networks and cloud native networking. And then finally the ACE's, the Aviatrix Certified Engineers, are going to talk more about their certifications and the expertise needed. So, let's jump right in, let's ask, Simon Richard to come on stage, from Gartner. We'll kick it all off. (electronic music) (clapping) >> John: Hi, can I help you. Okay, so kicking things off, getting started. Gartner, the industry experts on cloud. Really kind of more, cue your background. Talk about your background before you got to Gartner? >> Simon: Before being at Gartner, I was a chief network architect, of a Fortune 500 company, that with thousands of sites over the world and I've been doing everything in IT from a C programmer, in the 90, to a security architect, to a network engineer, to finally becoming a network analyst. >> So you rode the wave. Now you're covering the marketplace with hybrid cloud and now moving quickly to multi-cloud, is really what everyone is talking about. >> Yes. >> Cloud-native's been discussed, but the networking piece is super important. How do you see that evolving? >> Well, the way we see Enterprise adapting, cloud. The first thing you do about networking, the initial phases they either go in a very ad hoc way. Is usually led by none IT, like a shadow IT, or application people, sometime a DevOps team and it just goes as, it's completely unplanned. They create VPC's left and right with different account and they create mesh to manage them and they have Direct Connect or Express Route to any of them. So that's the first approach and on the other side. again within our first approach you see what I call, the lift and shift. Where we see like enterprise IT trying to, basically replicate what they have in a data center, in the Cloud. So they spend a lot of time planning, doing Direct Connect, putting Cisco routers and F5 and Citrix and any checkpoint, Palo Alto device, that in a sense are removing that to the cloud. >> I got to ask you, the aha moment is going to come up a lot, in one our panels, is where people realize, that it's a multi-cloud world. I mean, they either inherit clouds, certainly they're using public cloud and on-premises is now more relevant than ever. When's that aha moment? That you're seeing, where people go, "Well I got to get my act together and get on this cloud." >> Well the first, right, even before multi-cloud. So there is two approach's. The first one, like the adult way doesn't scare. At some point IT has to save them, 'cause they don't think about the tools, they don't think about operation, they have a bunch of VPC and multiple cloud. The other way, if you do the lift and shift way, they cannot take any advantages of the cloud. They lose elasticity, auto-scaling, pay by the drink. All these agility features. So they both realize, okay, neither of these ways are good, so I have to optimize that. So I have to have a mix of what I call, the cloud native services, within each cloud. So they start adapting, like all the AWS Construct, Azure Construct or Google Construct and that's what I call the optimal phase. But even that they realize, after that, they are all very different, all these approaches different, the cloud are different. Identities is constantly, difficult to manage across clouds. I mean, for example, anybody who access' accounts, there's subscription, in Azure and GCP, their projects. It's a real mess, so they realized, well I don't really like constantly use the cloud product and every cloud, that doesn't work. So I have, I'm going multi-cloud, I like to abstract all of that. I still want to manage the cloud from an EPI point of view, I don't necessarily want to bring my incumbent data center products, but I have to do that and in a more EPI driven cloud environment. >> So, the not scaling piece that you where mentioning, that's because there's too many different clouds? >> Yes. >> That's the least they are, so what are they doing? What are they, building different development teams? Is it software? What's the solution? >> Well, the solution is to start architecting the cloud. That's the third phase. I called that the multi-cloud architect phase, where they have to think about abstraction that works across cloud. Fact, even across one cloud it might not scale as well, If you start having like ten thousand security agreement, anybody who has that doesn't scale. You have to manage that. If you have multiple VPC, it doesn't scale. You need a third-party, identity provider. In variously scales within one cloud, if you go multiple cloud, it gets worse and worse. >> Steve, weigh in here. What's your thoughts? >> I thought we said this wasn't going to be a sales pitch for Aviatrix. (laughter) You just said exactly what we do, so anyway, that's a joke. What do you see in terms of where people are, in that multi-cloud? So, like lot of people, you know, everyone I talk to, started at one cloud, right, but then they look and then say okay but I'm now going to move to Azure and I'm going to move to... (trails off) Do you see a similar thing? >> Well, yes. They are moving but there's not a lot of application, that uses three cloud at once, they move one app in Azure, one app in AWS and one app in Google. That's what we see so far. >> Okay, yeah, one of the mistakes that people think, is they think multi-cloud. No one is ever going to go multi-cloud, for arbitrage. They're not going to go and say, well, today I might go into Azure, 'cause I get a better rate on my instance. Do you agree? That's never going to happen. What I've seen with enterprise, is I'm going to put the workload in the app, the app decides where it runs best. That may be Azure, maybe Google and for different reasons and they're going to stick there and they're not going to move. >> Let me ask you guys-- >> But the infrastructure, has to be able to support, from a networking team. >> Yes. >> Be able to do that. Do you agree with that? >> Yes, I agree. And one thing is also very important, is connecting to the cloud, is kind of the easiest thing. So, the wide area network part of the cloud, connectivity to the cloud is kind of simple. >> Steve: I agree. >> IP's like VPN, Direct Connect, Express Route. That's the simple part, what's difficult and even the provisioning part is easy. You can use Terraform and create VPC's and Vnet's across your three cloud provider. >> Steve: Right. >> What's difficult is that they choose the operation. So we'll define day two operation. What does that actually mean? >> Its just the day to day operations, after you know, the natural, lets add an app, lets add a server, lets troubleshoot a problem. >> Something changes, now what do you do? >> So what's the big concerns? I want to just get back to the cloud native networking, because everyone kind of knows what cloud native apps are. That's been the hot trend. What is cloud native networking? How do you guys, define that? Because that seems to be the hardest part of the multi-cloud wave that's coming, is cloud native networking. >> Well there's no, you know, official Gartner definition but I can create one on the spot. >> John: Do it. (laughter) >> I just want to leverage the Cloud Construct and the cloud EPI. I don't want to have to install, like a... (trails off) For example, the first version was, let's put a virtual router that doesn't even understand the cloud environment. >> Right. If I have if I have to install a virtual machine, it has to be cloud aware. It has to understand the security group, if it's a router. It has to be programmable, to the cloud API. And understand the cloud environment. >> And one thing I hear a lot from either CSO's, CIO's or CXO's in general, is this idea of, I'm definitely not going API. So, its been an API economy. So API is key on that point, but then they say. Okay, I need to essentially have the right relationship with my suppliers, aka you called it above the clouds. So the question is... What do I do from an architectural standpoint? Do I just hire more developers and have different teams, because you mentioned that's a scale point. How do you solve this problem of, okay, I got AWS, I got GCP, or Azure, or whatever. Do I just have different teams or do I just expose EPI's? Where is that optimization? Where's the focus? >> Well, I think what you need, from a network point of view is a way, a control plane across the three clouds. And be able to use the API's of the cloud, to build networks but also to troubleshoot them and do day to day operation. So you need a view across the three clouds, that takes care of routing, connectivity. >> Steve: Performance. >> John: That's the Aviatrix plugin, right there. >> Steve: Yeah. So, how do you see, so again, your Gartner, you see the industry. You've been a network architect. How do you see this this playing out? What are the legacy incumbent client server, On Prem networking people, going to do? >> Well they need to.. >> Versus people like a Aviatrix? How do you see that playing out? >> Well obviously, all the incumbents, like Arista, Cisco, Juniper, NSX. >> Steve: Right. >> They want to basically do the lift and shift part, they want to bring, and you know, VMware want to bring in NSX on the cloud, they call that "NSX everywhere" and Cisco want to bring in ACI to the cloud, they call that "ACI Anywhere". So, everyone's.. (trails off) And then there's CloudVision from Arista, and Contrail is in the cloud. So, they just want to bring the management plane, in the cloud, but it's still based, most of them, is still based on putting a VM in them and controlling them. You extend your management console to the cloud, that's not truly cloud native. >> Right. >> Cloud native you almost have to build it from scratch. >> We like to call that cloud naive. >> Cloud naive, yeah. >> So close, one letter, right? >> Yes. >> That was a big.. (slurs) Reinvent, take the T out of Cloud Native. It's Cloud Naive. (laughter) >> That went super viral, you guys got T-shirts now. I know you're loving that. >> Steve: Yeah. >> But that really, ultimately, is kind of a double-edged sword. You can be naive on the architecture side and ruleing that. And also suppliers or can be naive. So how would you define who's naive and who's not? >> Well, in fact, their evolving as well, so for example, in Cisco, it's a little bit more native than other ones, because there really is, "ACI in the cloud", you can't really figure API's out of the cloud. NSX is going that way and so is Arista, but they're incumbent, they have their own tools, its difficult for them. They're moving slowly, so it's much easier to start from scratch. Even you, like, you know, a network company that started a few years ago. There's only really two, Aviatrix was the first one, they've been there for at least three or four years. >> Steve: Yeah. >> And there's other one's, like Akira, for example that just started. Now they're doing more connectivity, but they want to create an overlay network, across the cloud and start doing policies and things. Abstracting all the clouds within one platform. >> So, I got to ask you. I interviewed an executive at VMware, Sanjay Poonen, he said to me at RSA last week. Oh, there'll only be two networking vendors left, Cisco and VMware. (laughter) >> What's you're response to that? Obviously when you have these waves, these new brands that emerge, like Aviatrix and others. I think there'll be a lot of startups coming out of the woodwork. How do you respond to that comment? >> Well there's still a data center, there's still, like a lot, of action on campus and there's the wan. But from the cloud provisioning and cloud networking in general, I mean, they're behind I think. You know, you don't even need them to start with, you can, if you're small enough, you can just keep.. If you have AWS, you can use the AWS construct, they have to insert themselves, I mean, they're running behind. From my point of view. >> They are, certainly incumbents. I love the term Andy Jess uses at Amazon web services. He uses "Old guard, new guard", to talk about the industry. What does the new guard have to do? The new brands that are emerging. Is it be more DevOp's oriented? Is it NetSec ops? Is it NetOps? Is it programmability? These are some of the key discussions we've been having. What's your view, on how you see this programmability? >> The most important part is, they have to make the network simple for the Dev teams. You cannot make a phone call and get a Vline in two weeks anymore. So if you move to the cloud, you have to make that cloud construct as simple enough, so that for example, a Dev team could say, "Okay, I'm going to create this VPC, but this VPC automatically associates your account, you cannot go out on the internet. You have to go to the transit VPC, so there's lot of action in terms of, the IAM part and you have to put the control around them to. So to make it as simple as possible. >> You guys, both. You're the CEO of Aviatrix, but also you've got a lot of experience, going back to networking, going back to the, I call it the OSI days. For us old folks know what that means, but, you guys know what this means. I want to ask you the question. As you look at the future of networking, you hear a couple objections. "Oh, the cloud guys, they got networking, we're all set with them. How do you respond to the fact that networking's changing and the cloud guys have their own networking. What's some of the paying points that's going on premises of these enterprises? So are they good with the clouds? What needs... What are the key things that's going on in networking, that makes it more than just the cloud networking? What's your take on it? >> Well as I said earlier. Once you could easily provision in the cloud, you can easily connect to the cloud, its when you start troubleshooting applications in the cloud and try to scale. So that's where the problem occurred. >> Okay, what's your take on it. >> And you'll hear from the customers, that we have on stage and I think what happens is all the clouds by definition, designed to the 80-20 rule which means they'll design 80% of the basic functionality. And then lead to 20% extra functionality, that of course every Enterprise needs, to leave that to ISV's, like Aviatrix. Because why? Because they have to make money, they have a service and they can't have huge instances, for functionality that not everybody needs. So they have to design to the common and that, they all do it, right? They have to and then the extra, the problem is, that Cambrian explosion, that I talked about with enterprises. That's what they need. They're the ones who need that extra 20%. So that's what I see, there's always going to be that extra functionality. In an automated and simple way, that you talked about, but yet powerful. With the up with the visibility and control, that they expect of On Prem. That kind of combination, that Yin and the Yang, that people like us are providing. >> Simon I want to ask you? We're going to ask some of the cloud architect, customer panels, that same question. There's pioneer's doing some work here and there's also the laggards who come in behind their early adopters. What's going to be the tipping point? What are some of these conversations, that the cloud architects are having out there? Or what's the signs, that they need to be on this, multi-cloud or cloud native networking trend? What are some of the signal's that are going on in the environment? What are some of the thresholds? Are things that are going on, that they can pay attention to? >> Well, once they have the application on multiple cloud and they have to get wake up at two in the morning, to troubleshoot them. They'll know it's important. (laughter) So, I think that's when the rubber will hit the road. But, as I said, it's easier to prove, at any case. Okay, it's AWS, it's easy, user transit gateway, put a few VPC's and you're done. And you create some presents like Equinox and do a Direct Connect and Express Route with Azure. That looks simple, its the operations, that's when they'll realize. Okay, now I need to understand! How cloud networking works? I also need a tool, that gives me visibility and control. But not only that, I need to understand the basic underneath it as well. >> What are some of the day in the life scenarios. you envision happening with multi-cloud, because you think about what's happening. It kind of has that same vibe of interoperability, choice, multi-vendor, 'cause they're multi-cloud. Essentially multi-vendor. These are kind of old paradigms, that we've lived through with client server and internet working. What are some of the scenarios of success, that might be possible? Will be possible, with multi-cloud and cloud native networking. >> Well, I think, once you have good enough visibility, to satisfy your customers, not only, like to, keep the service running and application running. But to be able to provision fast enough, I think that's what you want to achieve. >> Simon, final question. Advice for folks watching on the Livestream, if they're sitting there as a cloud architect or CXO. What's your advice to them right now, in this market, 'cause obviously, public cloud check, hybrid cloud, they're working on that. That gets on premises done, now multi-cloud's right behind it. What's your advice? >> The first thing they should do, is really try to understand cloud networking. For each of their cloud providers and then understand the limitations. And, is what the cloud service provider offers enough? Or you need to look to a third party, but you don't look at a third party to start with. Especially an incumbent one, so it's tempting to say "I have a bunch of F5 experts", nothing against F5. I'm going to bring my F5 in the Cloud, when you can use an ELB, that automatically understand eases and auto scaling and so on. And you understand that's much simpler, but sometimes you need your F5, because you have requirements. You have like iRules and that kind of stuff, that you've used for years. 'cause you cannot do it. Okay, I have requirement and that's not met, I'm going to use Legacy Star and then you have to start thinking, okay, what about visibility control, above the true cloud. But before you do that you have to understand the limitations of the existing cloud providers. First, try to be as native as possible, until things don't work, after that you can start thinking of the cloud. >> Great insight, Simon. Thank you. >> That's great. >> With Gartner, thank you for sharing. (electronic music) >> Welcome back to ALTITUDE 2020. For the folks in the live stream, I'm John Furrier, Steve Mullaney, CEO of Aviatrix. For our first of two customer panels with cloud network architects, we've got Bobby Willoughby, AEGON Luis Castillo from National Instruments and David Shinnick with FactSet. Guys, welcome to the stage for this digital event. Come on up. (audience clapping) (upbeat music) Hey good to see you, thank you. Customer panel, this is my favorite part. We get to hear the real scoop, we get the Gardener giving us the industry overview. Certainly, multi-cloud is very relevant, and cloud-native networking is a hot trend with the live stream out there in the digital events. So guys, let's get into it. The journey is, you guys are pioneering this journey of multi-cloud and cloud-native networking and are soon going to be a lot more coming. So I want to get into the journey. What's it been like? Is it real? You've got a lot of scar tissue? What are some of the learnings? >> Absolutely. Multi-cloud is whether or not we accept it, as network engineers is a reality. Like Steve said, about two years ago, companies really decided to just bite the bullet and move there. Whether or not we accept that fact, we need to not create a consistent architecture across multiple clouds. And that is challenging without orchestration layers as you start managing different tool sets and different languages across different clouds. So it's really important to start thinking about that. >> Guys on the other panelists here, there's different phases of this journey. Some come at it from a networking perspective, some come in from a problem troubleshooting, what's your experiences? >> From a networking perspective, it's been incredibly exciting, it's kind of once in a generational opportunity to look at how you're building out your network. You can start to embrace things like infrastructure as code that maybe your peers on the systems teams have been doing for years, but it just never really worked on-prem. So it's really exciting to look at all the opportunities that we have and all of the interesting challenges that come up that you get to tackle. >> And effects that you guys are mostly AWS, right? >> Yeah. Right now though, we are looking at multiple clouds. We have production workloads running in multiple clouds today but a lot of the initial work has been with Amazon. >> And you've seen it from a networking perspective, that's where you guys are coming at it from? >> Yup. >> Awesome. How about you? >> We evolve more from a customer requirement perspective. Started out primarily as AWS, but as the customer needed more resources from Azure like HPC, Azure AD, things like that, even recently, Google analytics, our journey has evolved into more of a multi-cloud environment. >> Steve, weigh in on the architecture because this is going to be a big conversation, and I wanted you to lead this section. >> I think you guys agree the journey, it seems like the journey started a couple of years ago. Got real serious, the need for multi-cloud, whether you're there today. Of course, it's going to be there in the future. So that's really important. I think the next thing is just architecture. I'd love to hear what you, had some comments about architecture matters, it all starts, every enterprise I talked to. Maybe talk about architecture and the importance of architects, maybe Bobby. >> From architecture perspective, we started our journey five years ago. >> Wow, okay. >> And we're just now starting our fourth evolution over network architect. And we call it networking security net sec, versus just as network. And that fourth-generation architecture should be based primarily upon the Palo Alto Networks and Aviatrix. Aviatrix to new orchestration piece of it. But that journey came because of the need for simplicity, the need for a multi-cloud orchestration without us having to go and do reprogramming efforts across every cloud as it comes along. >> I guess the other question I also had around architecture is also... Luis maybe just talk about it. I know we've talked a little bit about scripting, and some of your thoughts on that. >> Absolutely. So for us, we started creating the network constructs with cloud formation, and we've stuck with that for the most part. What's interesting about that is today, on-premise, we have a lot of automation around how we provision networks, but cloud formation has become a little bit like the new manual for us. We're now having issues with having to automate that component and making it consistent with our on-premise architecture and making it consistent with Azure architecture and Google cloud. So, it's really interesting to see companies now bring that layer of abstraction that SD-WAN brought to the wound side, now it's going up into the cloud networking architecture. >> Great. So on the fourth generation, you mentioned you're on the fourth-gen architecture. What have you learned? Is there any lessons, scratch issue, what to avoid, what worked? What was the path that you touched? >> It's probably the biggest lesson there is that when you think you finally figured it out, you haven't. Amazon will change something, Azure change something. Transit Gateway is a game-changer. And listening to the business requirements is probably the biggest thing we need to do upfront. But I think from a simplicity perspective, like I said, we don't want to do things four times. We want to do things one time, we want be able to write to an API which Aviatrix has and have them do the orchestration for us. So that we don't have to do it four times. >> How important is architecture in the progression? Is it do you guys get thrown in the deep end, to solve these problems, are you guys zooming out and looking at it? How are you guys looking at the architecture? >> You can't get off the ground if you don't have the network there. So all of those, we've gone through similar evolutions, we're on our fourth or fifth evolution. I think about what we started off with Amazon without Direct Connect Gateway, without Transit Gateway, without a lot of the things that are available today, kind of the 80, 20 that Steve was talking about. Just because it wasn't there doesn't mean we didn't need it. So we needed to figure out a way to do it, we couldn't say, "Oh, you need to come back to the network team in a year, and maybe Amazon will have a solution for it." We need to do it now and evolve later and maybe optimize or change the way you're doing things in the future. But don't sit around and wait, you can't. >> I'd love to have you guys each individually answer this question for the live streams that comes up a lot. A lot of cloud architects out in the community, what should they be thinking about the folks that are coming into this proactively and, or realizing the business benefits are there? What advice would you guys give them on architecture? What should be they'd be thinking about, and what are some guiding principles you could share? >> So I would start with looking at an architecture model that can spread and give consistency to the different cloud vendors that you will absolutely have to support. Cloud vendors tend to want to pull you into using their native tool set, and that's good if only it was realistic to talk about only one cloud. But because it doesn't, it's super important to talk about, and have a conversation with the business and with your technology teams about a consistent model. >> And how do I do my day one work so that I'm not spending 80% of my time troubleshooting or managing my network? Because if I'm doing that, then I'm missing out on ways that I can make improvements or embrace new technologies. So it's really important early on to figure out, how do I make this as low maintenance as possible so that I can focus on the things that the team really should be focusing on? >> Bobby, your advice there, architecture. >> I don't know what else I can add to that. Simplicity of operations is key. >> So the holistic view of day two operations you mentioned, let's can jump in day one as you're getting stuff set up, day two is your life after. This is kind of of what you're getting at, David. So what does that look like? What are you envisioning as you look at that 20-mile stair, out post multi-cloud world? What are some of the things that you want in the day two operations? >> Infrastructure as code is really important to us. So how do we design it so that we can start fit start making network changes and fitting them into a release pipeline and start looking at it like that, rather than somebody logging into a router CLI and troubleshooting things in an ad hoc nature? So, moving more towards a dev-ops model. >> You guys, anything to add on that day two? >> Yeah, I would love to add something. In terms of day two operations you can either sort of ignore the day two operations for a little while, where you get your feet wet, or you can start approaching it from the beginning. The fact is that the cloud-native tools don't have a lot of maturity in that space and when you run into an issue, you're going to end up having a bad day, going through millions and millions of logs just to try to understand what's going on. That's something that the industry just now is beginning to realize it's such a big gap. >> I think that's key because for us, we're moving to more of an event-driven or operations. In the past, monitoring got the job done. It's impossible to monitor something that is not there when the event happens. So the event-driven application and then detection is important. >> Gardner is all about the cloud-native wave coming into networking. That's going to be a serious thing. I want to get your guys' perspective, I know you have each different views of how you come into the journey and how you're executing. And I always say the beauty's in the eye of the beholder and that applies to how the network's laid out. So, Bobby, you guys do a lot of high-performance encryption, both on AWS and Azure. That's a unique thing for you. How are you seeing that impact with multi-cloud? >> That's a new requirement for us too, where we have an increment to encrypt. And then if you ever get the question, should I encrypt, should I not encrypt? The answer is always yes. You should encrypt when you can encrypt. For our perspective, we need to migrate a bunch of data from our data centers. We have some huge data centers, and getting that data to the cloud is a timely expense in some cases. So we have been mandated, we have to encrypt everything, leave in the data center. So we're looking at using the Aviatrix insane mode appliances to be able to encrypt 10, 20 gigabits of data as it moves to the cloud itself. >> David, you're using Terraform, you've got FireNet, you've got a lot of complexity in your network. What do you guys look at the future for your environment? >> So many exciting that we're working on now as FireNet. So for our security team that obviously have a lot of knowledge base around Palo Alto, and with our commitments to our clients, it's not very easy to shift your security model to a specific cloud vendor. So there's a lot of SOC 2 compliance and things like that were being able to take some of what you've worked on for years on-prem and put it in the cloud and have the same type of assurance that things are going to work and be secure in the same way that they are on-prem, helps make that journey into the cloud a lot easier. >> And Louis, you guys got scripting, you got a lot of things going on. What's your unique angle on this? >> Absolutely. So for disclosure, I'm not an Aviatrix customer yet. (laughs) >> It's okay, we want to hear the truth, so that's good. Tell us, what are you thinking about? What's on your mind? >> When you talk about implementing a tool like this, it's really just really important to talk about automation focus on value. When you talk about things like encryption and things like so you're encrypting tunnels and encrypting the path, and those things should be second nature really. When you look at building those back-ends and managing them with your team, it becomes really painful. So tools like Aviatrix that add a lot automation it's out of sight, out of mind. You can focus on the value, and you don't have to focus on this. >> So I got to ask you guys. I see Aviatrix was here, they're supplier to this sector, but you guys are customers. Everyone's pitching your stuff, people knock on you, "Buy my stuff." How do you guys have that conversation with the suppliers, like the cloud vendors and other folks? What's it like? We're API all the way? You've got to support this? What are some of your requirements? How do you talk to and evaluate people that walk in and want to knock on your door and pitch you something? What's the conversation like? >> It's definitely API driven. We definitely look at the API structure that the vendors provide before we select anything. That is always first of mine and also, what problem are we really trying to solve? Usually, people try to sell or try to give us something that isn't really valuable, like implementing a Cisco solution on the cloud doesn't really add a lot of value, that's where we go. >> David, what's your conversation like with suppliers? Do you have a certain new way to do things? As it becomes more agile, essentially networking, and getting more dynamic, what are some of the conversations with either in commits or new vendors that you're having? What do you require? >> Ease of use is definitely high up there. We've had some vendors come in and say, "Hey, when you go to set this up, "we're going to want to send somebody on-site." And they're going to sit with you for a day to configure it. And that's a red flag. Well, wait a minute, do we really, if one of my really talented engineers can't figure it out on his own, what's going on there and why is that? Having some ease of use and the team being comfortable with it and understanding it is really important. >> Bobby, how about you? Old days was, do a bake-off and the winner takes all. Is it like that anymore? What's evolving? Bake-off last year for but still win. But that's different now because now when you get the product, you can install the product in AWS and Azure, have it up running in a matter of minutes. So the key is that can you be operational within hours or days instead of weeks? But do we also have the flexibility to customize it, to meet your needs? Because you don't want to be put into a box with the other customers when you have needs that are past their needs. >> I can almost see the challenge that you guys are living, where you've got the cloud immediate value, depending how you can roll up any solutions, but then you might have other needs. So you've got to be careful not to buy into stuff that's not shipping. So you're trying to be proactive and at the same time, deal with what you got. How do you guys see that evolving? Because multi-cloud to me is definitely relevant, but it's not yet clear how to implement across. How do you guys look at this baked versus future solutions coming? How do you balance that? >> Again, so right now, we're taking the ad hoc approach and experimenting what the different concepts of cloud are and really leveraging the native constructs of each cloud. But there's a breaking point for sure. You don't get to scale this like someone said, and you have to focus on being able to deliver, developers their sandbox or their play area for the things that they're trying to build quickly. And the only way to do that is with some consistent orchestration layer that allows you to-- >> So you expect a lot more stuff to becoming pretty quickly in that area. >> I do expect things to start maturing quite quickly this year. >> And you guys see similar trend, new stuff coming fast? >> Yeah. Probably the biggest challenge we've got now is being able to segment within the network, being able to provide segmentation between production, non-production workloads, even businesses, because we support many businesses worldwide and isolation between those is a key criteria there. So the ability to identify and quickly isolate those workloads is key. So the CIOs that are watching are saying, "Hey, take that hill, do multi-cloud." And then you have the bottoms up organization, "Pause, you're like off a little bit, it's not how it works." What is the reality in terms of implementing as fast as possible? Because the business benefits are clear, but it's not always clear on the technology how to move that fast. What are some of the barriers, what are the blockers, what are the enablers? >> I think the reality is that you may not think you're multi-cloud, but your business is. So I think the biggest barrier there is understanding what the requirements are and how best to meet those requirements in a secure manner. Because you need to make sure that things are working from a latency perspective that things work the way they did and get out of the mind shift that it was a tier-three application and the data center, it doesn't have to be a tier-three application in the cloud. So, lift and shift is not the way to go. >> Scale is a big part of what I see is the competitive advantage by these clouds and used to be proprietary network stacks in the old days, and then open systems came, that was a good thing. But as cloud has become bigger, there's an inherent lock-in there with the scale. How do you guys keep the choice open? How are you guys thinking about interoperability? What are some of the conversations that you guys are having around those key concepts? >> When we look at from a networking perspective, it's really key for you to just enable all the class to be able to communicate between them. Developers will find a way to use the cloud that best suits their business needs. And like you said, it's whether you're in denial or not, of the multi-cloud fact that your company is in already that's it becomes really important for you to move quickly. >> Yeah. And a lot of it also hinges on how well is the provider embracing what that specific cloud is doing? So, are they swimming with Amazon or Azure and just helping facilitate things, and they're doing the heavy lifting API work for you? Or are they swimming upstream and they're trying to hack it all together in messy way? And so that helps you stay out of the lock-in because there, if they're using Amazon native tools to help you get where you need to be, it's not like Amazon is going to release something in the future that completely makes you have designed yourself into a corner. So the closer, more than cloud-native they are, the more, the easier it is to deploy. >> Which also need to be aligned in such a way that you can take advantage of those cloud-native technologies. Will it make sense? TGW is a gamechanger in terms of cost and performance. So to completely ignore that, would be wrong. But if you needed to have encryption, TGW is not encrypted, so you need to have some type of Gateway to do the VPN encryption. So, the Aviatrix tool will give you the beauty of both worlds. You can use TGW or the Gateway. Real quick on the last minute we have, I want to just get a quick feedback from you guys. I hear a lot of people say to me, "Hey, pick the best cloud for the workload you got, then figure out multicloud behind the scenes." Do you guys agree with that? Do I go more to one cloud across the whole company or this workload works great on AWS, that workload works great on this. From a cloud standpoint, do you agree with that premise, and then when is multi-cloud stitching altogether? >> From an application perspective, it can be per workload, but it can also be an economical decision, certain enterprise contracts will pull you in one direction to add value, but the network problem is still the same. >> It doesn't go away. >> You don't want to be trying to fit a square into a round hall. If it works better on that cloud provider, then it's our job to make sure that service is there and people can use it. >> I agree, you just need to stay ahead of the game, make sure that the network infrastructure is there, security is available and is multi-cloud capable. >> At the end of the day, you guys are just validating that it's the networking game now. Cloud storage, compute check, networking is where the action is. Awesome. Thanks for your insights guys, appreciate you coming on the panel. Appreciate it, thanks. (upbeat music) >> John: Our next customer panel, got great another set of cloud network architects, Justin Smith with Zuora, Justin Brodley with EllieMae and Amit Utreja with Coupa. Welcome to stage. (audience applauds) (upbeat music) >> All right, thank you. >> How are ya? >> Thank you. Thank You. >> Hey Amit. How are ya? >> Did he say it right? >> Yeah. >> Okay he's got all the cliff notes from the last session, welcome back. Rinse and repeat. We're going to go into the hood a little bit. And I think they nailed what we've been reporting, we've been having this conversation around, networking is where the action is because that's at the end of the day you got to move packet from A to B and you got workloads exchanging data. So it's really killer. So let's get started. Amit, what are you seeing as the journey of multicloud as you go under the hood and say, "Okay, I got to implement this. "I have to engineer the network, "make it enabling, make it programmable, "make it interoperable across clouds." That almost sounds impossible to me. What's your take? >> Yeah, it seems impossible but if you are running an organization which is running infrastructure as a code it is easily doable. Like you can use tools out there that's available today, you can use third party products that can do a better job. But put your architecture first, don't wait. Architecture may not be perfect, put the best architecture that's available today and be agile, to iterate and make improvements over the time. >> We get to Justin's over here, so I have to be careful when I point a question to Justin, they both have the answer. Okay, journeys, what's the journey been like? Is there phases, We heard that from Gardner, people come into multicloud and cloud native networking from different perspectives? What's your take on the journey, Justin? >> Yeah, from our perspective, we started out very much focused on one cloud and as we've started doing acquisitions, we started doing new products to the market, the need for multicloud becomes very apparent, very quickly for us. And so having an architecture that we can plug and play into and be able to add and change things as it changes is super important for what we're doing in the space. >> Justin, your journey. >> Yes. For us, we were very ad hoc oriented and the idea is that we were reinventing all the time, trying to move into these new things and coming up with great new ideas. And so rather than it being some iterative approach with our deployments that became a number of different deployments. And so we shifted that toward and the network has been a real enabler of this. There's one network and it touches whatever cloud we want it to touch, and it touches the data centers that we need it to touch, and it touches the customers that we needed to touch. Our job is to make sure that the services that are available in one of those locations are available in all of the locations. So the idea is not that we need to come up with this new solution every time, it's that we're just iterating on what we've already decided to do. >> Before we get the architecture section, I want to ask you guys a question? I'm a big fan of let the app developers have infrastructure as code, so check. But having the right cloud run that workload, I'm a big fan of that, if it works great. But we just heard from the other panel, you can't change the network. So I want to get your thoughts, what is cloud native networking? And is that the engine really, that's the enabler for this multicloud trend? What's you guys take? We'll start with Amit, what do you think about that? >> Yeah, so you're going to have workloads running in different clouds and the workloads would have affinity to one cloud or other. But how you expose that it's a matter of how you are going to build your networks. How you're going to run security. How you're going to do egress, ingress out of it so -- >> You said networking is the big problem to solve. >> Yes. >> What's the solution? What's the key pain points and problem statement? >> The key pain point for most companies is how do you take your traditionally on premise network and then blow it out to the cloud in a way that makes sense. You have IP conflicts, you have IP space, you have public IPs on premise as well as in the cloud. And how do you kind of make sense of all of that? And I think that's where tools like Aviatrix make a lot of sense in that space. >> From our side, it's really simple. It's a latency, it's bandwidth and availability. These don't change whether we're talking about cloud or data center, or even corporate IT networking. So our job when these all of these things are simplified into like, S3, for instance and our developers want to use those. We have to be able to deliver that and for a particular group or another group that wants to use just just GCP resources. We have to support these requirements and these wants, as opposed to saying, "Hey, that's not a good idea." No, our job is to enable them not to disable them. >> Do you guys think infrastructure is code? Which I love that, I think that's the future in this. We even saw that with DevOps. But as you start getting the networking, is it getting down to the network portion where its network as code? Because storage and compute working really well, we're seeing all Kubernetes on service mesh trend. Network has code, reality is it there? Is it still got work to do? >> It's absolutely there, you mentioned net DevOps and it's very real. In Coupa we build our networks through terraform and not only just terraform, build an API so that we can consistently build VNets and VPC all across in the same way. >> So you guys are doing it? >> Yup. And even security groups. And then on top and Aviatrix comes in, we can peer the networks bridge all the different regions through code. >> Same with you guys. >> Yeah. >> What do you think about this? >> Everything we deploy is done with automation and then we also run things like Lambda on top to make changes in real time, we don't make manual changes on our network. In the data center, funny enough, it's still manual but the cloud has enabled us to move into this automation mindset. And all my guys, that's what they focus on is bringing, now what they're doing in the cloud into the data center, which is kind of opposite of what it should be or what it used to be. >> It's full DevOps then? >> Yes. >> For us, it was similar on-prem is still somewhat very manual, although we're moving more and more to ninja and terraform type concepts. But everything in the production environment is code, confirmation terraform code and now coming into the data center same (mumbles). >> So I just wanted to jump in Justin Smith, one of the comment that you made, because it's something that we always talk about a lot is that the center of gravity of architecture used to be an on-prem and now it's shifted in the cloud. And once you have your strategic architecture, what do you do? You push that everywhere. So what you used to see at the beginning of cloud was pushing the architecture on-prem into cloud. Now, I want to pick up on what you said, do you others agree that the center of gravity is here, I'm now pushing what I do in the cloud back into on-prem? And then so first that and then also in the journey, where are you at from zero to 100 of actually in the journey to cloud? Are you 50% there, are you 10%? Are you evacuating data centers next year? Where are you guys at? >> Yeah, so there's there's two types of gravity that you typically are dealing with, with the migration. First is data, gravity and your data set, and where that data lives. And then the second is the network platform that wraps all that together. In our case, the data gravity solely mostly on-prem but our network is now extending out to the app tier, it's going to be in cloud. Eventually, that data, gravity will also move to cloud as we start getting more sophisticated but in our journey, we're about halfway there. About halfway through the process, we're taking a handle of lift and shift and -- >> Steve: And when did that start? >> We started about three years ago. >> Okay, okay. >> Well for Coupa it's a very different story. It started from a garage and 100% on the cloud. So it's a business plan management platform, software as a service run 100% on the cloud. >> That was was like 10 years ago, right? >> Yes. >> Yeah. >> You guys are riding the wave of the architecture. Justin I want to ask you, Zuora, you guys mentioned DevOps. Obviously, we saw the huge observability wave, which essentially network management for the cloud, in my opinion. It's more dynamic, but this is about visibility. We heard from the last panel you don't know what's being turned on or turned off from a services standpoint, at any given time. How is all this playing out when you start getting into the DevOps down (mumbles)? >> This is the big challenge for all of us is visibility. When you talk transport within a cloud, very interestingly we we have moved from having a backbone that we bought, that we own, that would be data center connectivity. Zuora's a subscription billing company, so we want to support the subscription mindset. So rather than going and buying circuits and having to wait three months to install and then coming up with some way to get things connected and resiliency and redundancy. My backbone is in the cloud. I use the cloud providers interconnections between regions to transport data across and so if you do that with their native solutions, you do lose visibility. There are areas in that that you don't get, which is why controllers and having some type of management plane is a requirement for us to do what we're supposed to do and provide consistency while doing it. >> Great conversation. I loved what you said earlier latency, bandwidth, I think availability were your top three things. Guys SLA, just do ping times between clouds it's like, you don't know what you're getting for round trip time. This becomes a huge kind of risk management, black hole, whatever you want to call it, blind spot. How are you guys looking at the interconnect between clouds? Because I can see that working from ground to cloud on per cloud but when you start dealing with multiclouds workloads, SLAs will be all over the map, won't they just inherently. How do you guys view that? >> Yeah, I think we talked about workload and we know that the workloads are going to be different in different clouds, but they're going to be calling each other. So it's very important to have that visibility, that you can see how data is flowing at what latency and what availability is there and our authority needs to operate on that. >> So use the software dashboard, look at the times and look at the latency -- >> In the old days, Strongswan Openswan you try to figure it out, in the new days you have to figure out. >> Justin, what's your answer to that because you're in the middle of it? >> Yeah, I think the key thing there is that we have to plan for that failure, we have to plan for that latency in our applications. If certain things are tracking in your SLI, certain things are planning for and you loosely coupled these services in a much more microservices approach. So you actually can handle that kind of failure or that type of unknown latency and unfortunately, the cloud has made us much better at handling exceptions in a much better way. >> You guys are all great examples of cloud native from day one. When did you have the tipping point moment or the epiphany of saying a multiclouds real, I can't ignore it, I got to factor that into all my design principles and everything you're doing? Was there a moment or was it from day one? >> There are two reasons, one was the business. So in business, there were some affinity to not be in one cloud or to be in one cloud and that drove from the business side. So as a cloud architect our responsibility was to support that business. Another is the technology, some things are really running better in, like if you're running Dotnet workload or your going to run machine learning or AI so that you would have that preference of one cloud over other. >> Guys, any thoughts on that? >> That was the bill that we got from AWS. That's what drives a lot of these conversations is the financial viability of what you're building on top of. This failure domain idea which is fairly interesting. How do I solve our guarantee against a failure domain? You have methodologies with back end direct connects or interconnect with GCP. All of these ideas are something that you have to take into account but that transport layer should not matter to whoever we're building this for. Our job is to deliver the frames and the packets, what that flows across, how you get there? We want to make that seamless. And so whether it's a public internet API call or it's a back end connectivity through direct connect, it doesn't matter. It just has to meet a contract that you've signed with your application, folks. >> Yeah, that's the availability piece. >> Justin, your thoughts on that, any comment on that? >> So actually multiclouds become something much more recent in the last six to eight months, I'd say. We always kind of had a very much an attitude of like moving to Amazon from our private cloud is hard enough, why complicate it further? But the realities of the business and as we start seeing, improvements in Google and Azure and different technology spaces, the need for multicloud becomes much more important. As well as our acquisition strategies are matured, we're seeing that companies that used to be on premise that we typically acquire are now very much already on a cloud. And if they're on a cloud, I need to plug them into our ecosystem. And so that's really changed our multicloud story in a big way. >> I'd love to get your thoughts on the clouds versus the clouds, because you compare them Amazon's got more features, they're rich with features. Obviously, the bills are high to people using them. But Google's got a great network, Google's networks pretty damn good And then you got Azure. What's the difference between the clouds? Where do they fall? Where do they peak in certain areas better than others? What are the characteristics, which makes one cloud better? Do they have a unique feature that makes Azure better than Google and vice versa? What do you guys think about the different clouds? >> Yeah, to my experience, I think the approach is different in many places. Google has a different approach very DevOps friendly and you can run your workloads with your network can span regions. But our application ready to accept that. Amazon is evolving. I remember 10 years back Amazon's network was a flat network, we would be launching servers in 10.0.0/8, right. And then the VPCs came out. >> We'll have to translate that to English for the live feed. Not good. So the VPCs concept came out, multi account came out, so they are evolving. Azure had a late start but because they have a late start, they saw the pattern and they have some mature setup on the network. >> They've got around the same price too. >> I think they're all trying to say they're equal in their own ways. I think they all have very specific design philosophies that allow them to be successful in different ways and you have to kind of keep that in mind as you architect your own solution. For example, Amazon has a very regional affinity, they don't like to go cross region in their architecture. Whereas Google is very much it's a global network, we're going to think about as a global solution. I think Google also has advantage that it's third to market and so has seen what Azure did wrong, it seeing what AWS did wrong and it's made those improvements and I think that's one of their big advantage. >> They got great scale too. Justin thoughts on the cloud. >> So yeah, Amazon built from the system up and Google built from the network down. So their ideas and approaches are from a global versus original, I agree with you completely that is the big number one thing. But the if you look at it from the outset, interestingly, the inability or the ability for Amazon to limit layer to broadcasting and what that really means from a VPC perspective, changed all the routing protocols you can use. All the things that we had built inside of a data center to provide resiliency and make things seamless to users, all of that disappeared. And so because we had to accept that at the VPC level, now we have to accept that at the WAN level. Google's done a better job of being able to overcome those things and provide those traditional network facilities to us. >> Just a great panel, we could go all day here, it's awesome. So I heard, we will get to the cloud native naive questions. So kind of think about what's naive and what's cloud, I'll ask that next but I got to ask you I had a conversation with a friend he's like, "WAN is the new LAN?" So if you think about what the LAN was at a data center, WAN is the new LAN, cause you keep talking about the cloud impact? So that means ST-WAN, the old ST-WAN kind of changing. There's a new LAN. How do you guys look at that? Because if you think about it, what LANs were for inside a premises was all about networking, high speed. But now when you take the WAN and make it, essentially a LAN, do you agree with that? And how do you view this trend? Is it good or bad or is it ugly? What you guys take on this? >> Yeah, I think it's a thing that you have to work with your application architects. So if you are managing networks and if you're a server engineer, you need to work with them to expose the unreliability that it would bring in. So the application has to handle a lot of the difference in the latencies and the reliability has to be worked through the application there. >> LAN, WAN, same concept is that BS? Can you give some insight? >> I think we've been talking about for a long time the erosion of the edge. And so is this just a continuation of that journey we've been on for last several years. As we get more and more cloud native and we talked about API's, the ability to lock my data in place and not be able to access it really goes away. And so I think this is just continuation. I think it has challenges. We start talking about WAN scale versus LAN scale, the tooling doesn't work the same, the scale of that tooling is much larger. and the need to automation is much, much higher in a WAN than it wasn't a LAN. That's why you're seeing so much infrastructure as code. >> Yeah. So for me, I'll go back again to this, it's bandwidth and its latency that define those two LAN versus WAN. But the other thing that's comes up more and more with cloud deployments is whereas our security boundary and where can I extend this secure aware appliance or set of rules to protect what's inside of it. So for us, we're able to deliver VRFs or route forwarding tables for different segments wherever we're at in the world. And so they're trusted to talk to each other but if they're going to go to someplace that's outside of their network, then they have to cross the security boundary, where we enforce policy very heavily. So for me, there's it's not just LAN, WAN it's how does environment get to environment more importantly. >> That's a great point in security, we haven't talked it yet but that's got to be baked in from the beginning, this architecture. Thoughts on security, how you guys are dealing with it? >> Yeah, start from the base, have app to app security built in. Have TLS, have encryption on the data at transit, data at rest. But as you bring the application to the cloud and they're going to go multicloud, talking to over the internet, in some places, well have app to app security. >> Our principles day, security is day zero every day. And so we always build it into our design, build into our architecture, into our applications. It's encrypt everything, it's TLS everywhere. It's make sure that that data is secure at all times. >> Yeah, one of the cool trends at RSA, just as a side note was the data in use encryption piece, which is homomorphic stuff was interesting. Alright guys, final question. We heard on the earlier panel was also trending at re:Invent, we think the T out of cloud native, it spells cloud naive. They have shirts now, Aviatrix kind of got this trend going. What does that mean to be naive? To your peers out there watching the live stream and also the suppliers that are trying to supply you guys with technology and services, what's naive look like and what's native look like? When is someone naive about implementing all this stuff? >> So for me, because we are in 100% cloud, for us its main thing is ready for the change. And you will find new building blocks coming in and the network design will evolve and change. So don't be naive and think that it's static, evolve with the change. >> I think the biggest naivety that people have is that well, I've been doing it this way for 20 years, I've been successful, it's going to be successful in cloud. The reality is that's not the case. You got to think some of the stuff a little bit differently and you need to think about it early enough, so that you can become cloud native and really enable your business on cloud. >> Yeah for me it's being open minded. Our industry, the network industry as a whole, has been very much I'm smarter than everybody else and we're going to tell everybody how it's going to be done. And we fell into a lull when it came to producing infrastructure and so embracing this idea that we can deploy a new solution or a new environment in minutes as opposed to hours, or weeks or months in some cases, is really important in and so >> - >> It's naive being closed minded, native being open minded. >> Exactly. For me that was a transformative kind of where I was looking to solve problems in a cloud way as opposed to looking to solve problems in this traditional old school way. >> All right, I know we're at a time but I got to asked one more question, so you guys so good. Give me a quick answer. What's the BS language when you, the BS meter goes off when people talk to you about solutions? What's the kind of jargon that you hear, that's the BS meter going off? What are people talking about that in your opinion you here you go, "That's total BS?" What triggers you? >> So that I have two lines out of movies if I say them without actually thinking them. It's like 1.21 gigawatts are you out of your mind from Back to the Future right? Somebody's giving you all these wiz bang things. And then Martin Maul and Michael Keaton in Mr Mom when he goes to 220, 221, whatever it takes. >> Yeah. >> Those two right there, if those go off in my mind where somebody's talking to me, I know they're full of baloney. >> So a lot of speeds and feeds, a lot of speeds and feeds a lot of -- >> Just data. Instead of talking about what you're actually doing and solutioning for. You're talking about, "Well, it does this this this." Okay to 220, 221. (laughter) >> Justin, what's your take? >> Anytime I start seeing the cloud vendors start benchmarking against each other. Your workload is your workload, you need to benchmark yourself. Don't listen to the marketing on that, that's just awful. >> Amit, what triggers you in the BS meter? >> I think if somebody explains to you are not simple, they cannot explain you in simplicity, then it's all bull shit. >> (laughs) That's a good one. Alright guys, thanks for the great insight, great panel. How about a round of applause to practitioners. (audience applauds) (upbeat music) >> John: Okay, welcome back to Altitude 2020 for the digital event for the live feed. Welcome back, I'm John Furrier with theCUBE with Steve Mullaney, CEO Aviatrix. For the next panel from Global System Integrated, the folks who are building and working with folks on their journey to multicloud and cloud-native networking. We've got a great panel, George Buckman with DXC and Derrick Monahan with WWT, welcome to the stage. (Audience applauds) >> Hey >> Thank you >> Groovy spot >> All right (upbeat music) >> Okay, you guys are the ones out there advising, building, and getting down and dirty with multicloud and cloud-native networking, we just heard from the customer panel. You can see the diversity of where people come in to the journey of cloud, it kind of depends upon where you are, but the trends are all clear, cloud-native networking, DevOps, up and down the stack, this has been the main engine. What's your guys' take of this journey to multicloud? What do you guys think? >> Yeah, it's critical, I mean we're seeing all of our enterprise customers enter into this, they've been through the migrations of the easy stuff, ya know? Now they're trying to optimize and get more improvements, so now the tough stuff's coming on, right? They need their data processing near where their data is. So that's driving them to a multicloud environment. >> Yeah, we've heard some of the Edge stuff, I mean, you guys are-- >> Exactly. >> You've seen this movie before, but now it's a whole new ballgame, what's your take? Yeah, so, I'll give you a hint, our practice is not called the cloud practice, it's the multicloud practice, and so if that gives you a hint of how we approach things. It's very consultative. And so when we look at what the trends are, like a year ago. About a year ago we were having conversations with customers, "Let's build a data center in the cloud. Let's put some VPCs, let's throw some firewalls, let's put some DNS and other infrastructure out there and let's hope it works." This isn't a science project. What we're starting to see is customers are starting to have more of a vision, we're helping with that consultative nature, but it's totally based on the business. And you've got to start understanding how lines of business are using the apps and then we evolve into the next journey which is a foundational approach to-- >> What are some of the problems some of your customers are solving when they come to you? What are the top things that are on their mind, obviously the ease of use, agility, all that stuff, what specifically are they digging into? >> Yeah, so complexity, I think when you look at a multicloud approach, in my view is, network requirements are complex. You know, I think they are, but I think the approach can be, "Let's simplify that." So one thing that we try to do, and this is how we talk to customers is, just like you simplify in Aviatrix, simplifies the automation orchestration of cloud networking, we're trying to simplify the design, the plan, and implementation of the infrastructure across multiple workloads, across multiple platforms. And so the way we do it, is we sit down, we look at not just use cases, not just the questions we commonly anticipate, we actually build out, based on the business and function requirements, we build out a strategy and then create a set of documents, and guess what? We actually build it in a lab, and that lab that we platform rebuilt, proves out this reference architectural actually works. >> Absolutely, we implement similar concepts. I mean, they're proven practices, they work, right? >> But George, you mentioned that the hard part's now upon us, are you referring to networking, what specifically were you getting at there when you said, "The easy part's done, now the hard part?" >> So for the enterprises themselves, migrating their more critical apps or more difficult apps into the environments, ya know, we've just scratched the surface, I believe, on what enterprises are doing to move into the cloud, to optimize their environments, to take advantage of the scale and speed to deployment and to be able to better enable their businesses. So they're just now really starting to-- >> So do you guys see what I talked about? I mean, in terms of that Cambrian explosion, I mean, you're both monster system integrators with top fortune enterprise customers, you know, really rely on you for guidance and consulting and so forth, and deploy their networks. Is that something that you've seen? I mean, does that resonate? Did you notice a year and a half ago all of a sudden the importance of cloud for enterprise shoot up? >> Yeah, I mean, we're seeing it now. >> Okay. >> In our internal environment as well, ya know, we're a huge company ourselves, customer zero, our internal IT, so, we're experiencing that internally and every one of our other customers as well. >> So I have another question and I don't know the answer to this, and a lawyer never asks a question that you don't know the answer to, but I'm going to ask it anyway. DXC and WWT, massive system integrators, why Aviatrix? >> Great question, Steve, so I think the way we approach things, I think we have a similar vision, a similar strategy, how you approach things, how we approach things, at World Wide Technology. Number one, we want a simplify the complexity. And so that's your number one priority. Let's take the networking, let's simplify it, and I think part of the other point I'm making is we see this automation piece as not just an after thought anymore. If you look at what customers care about, visibility and automation is probably at the top three, maybe the third on the list, and I think that's where we see the value. I think the partnership that we're building and what I get excited about is not just putting yours and our lab and showing customers how it works, it's co-developing a solution with you. Figuring out, "Hey, how can we make this better?" >> Right >> Visibility is a huge thing, just in security alone, network everything's around visibility. What automation do you see happening, in terms of progression, order of operations, if you will? What's the low hanging fruit? What are people working on now? What are some of the aspirational goals around when you start thinking about multicloud and automation? >> So I wanted to get back to his question. >> Answer that question. >> I wanted to answer your question, you know, what led us there and why Aviatrix. You know, in working some large internal IT projects, and looking at how we were going to integrate those solutions, you know, we like to build everything with recipes. Network is probably playing catch-up in the DevOps world but with a DevOps mindset, looking to speed to deploy, support, all those things, so when you start building your recipe, you take a little of this, a little of that, and you mix it all together, well, when you look around, you say, "Wow, look, there's this big bag of Aviatrix. "Let me plop that in. That solves a big part "of my problems that I had, the speed to integrate, "the speed to deploy, and the operational views "that I need to run this." So that was what led me to-- >> John: So how about reference architectures? >> Yeah, absolutely, so, you know, they came with a full slate of reference architectures already out there and ready to go that fit our needs, so it was very easy for us to integrate those into our recipes. >> What do you guys think about all the multi-vendor inter-operability conversations that have been going on? Choice has been a big part of multicloud in terms of, you know, customers want choice, they'll put a workload in the cloud if it works, but this notion of choice and interoperability has become a big conversation. >> It is, and I think that our approach, and that's the way we talk to customers is, "Let's speed and de-risk that decision making process, "and how do we do that?" Because interoperability is key. You're not just putting, it's not just a single vendor, we're talking, you know, many many vendors, I mean think about the average number of cloud applications a customer uses, a business, an enterprise business today, you know, it's above 30, it's skyrocketing and so what we do, and we look at it from an interoperability approach is, "How do things inter-operate?" We test it out, we validate it, we build a reference architecture that says, "These are the critical design elements, "now let's build one with Aviatrix "and show how this works with Aviatrix." And I think the important part there, though, is the automation piece that we add to it and visibility. So I think the visibility is what I see lacking across industry today. >> In cloud-native that's been a big topic. >> Yep >> Okay, in terms of Aviatrix, as you guys see them coming in, they're one of the ones that are emerging and the new brands emerging with multicloud, you've still got the old guard encumbered with huge footprints. How are customers dealing with that kind of component in dealing with both of them? >> Yeah, I mean, we have customers that are ingrained with a particular vendor and you know, we have partnerships with many vendors. So our objective is to provide the solution that meets that client. >> John: And they all want multi-vendor, they all want interoperability. >> Correct. >> All right, so I got to ask you guys a question while we were defining Day-2 operations. What does that mean? You guys are looking at the big business and technical components of architecture, what does Day-2 operations mean, what's the definition of that? >> Yeah, so I think from our perspective, with my experience, we, you know, Day-2 operations, whether it's not just the orchestration piece in setting up and let it automate and have some, you know, change control, you're looking at this from a Day-2 perspective, "How do I support this ongoing "and make it easy to make changes as we evolve?" The cloud is very dynamic. The nature of how fast it's expanding, the number features is astonishing. Trying to keep up to date with the number of just networking capabilities and services that are added. So I think Day-2 operations starts with a fundamental understanding of building out supporting a customer's environments, and making the automation piece easy from a distance, I think. >> Yeah and, you know, taking that to the next level of being able to enable customers to have catalog items that they can pick and choose, "Hey I need this network connectivity "from this cloud location back to this on-prem." And being able to have that automated and provisioned just simply by ordering it. >> For the folks watching out there, guys, take a minute to explain as you guys are in the trenches doing a lot of good work. What are some of the engagements that you guys get into? How does that progress? What happens there, they call you up and say, "Hey I need some multicloud," or you're already in there? I mean, take us through how someone can engage to use a global SI, they come in and make this thing happen, what's the typical engagement look like? >> Derrick: Yeah, so from our perspective, we typically have a series of workshops in the methodology that we kind of go along the journey. Number one, we have a foundational approach. And I don't mean foundation meaning the network foundation, that's a very critical element, we got to factor in security and we got to factor in automation. So when you think about foundation, we do a workshop that starts with education. A lot of times we'll go in and we'll just educate the customer, what is VPC sharing? You know, what is a private link in Azure? How does that impact your business? We have customers that want to share services out in an ecosystem with other customers and partners. Well there's many ways to accomplish that. Our goal is to understand those requirements and then build that strategy with them. >> Thoughts George, on-- >> Yeah, I mean, I'm one of the guys that's down in the weeds making things happen, so I'm not the guy on the front line interfacing with the customers every day. But we have a similar approach. We have a consulting practice that will go out and apply their practices to see what those-- >> And when do you parachute in? >> Yeah, when I parachute in is, I'm on the back end working with our offering development leads for networking, so we understand and are seeing what customers are asking for and we're on the back end developing the solutions that integrate with our own offerings as well as enable other customers to just deploy quickly to meet their connectivity needs. So the patterns are similar. >> Right, final question for you guys, I want to ask you to paint a picture of what success looks like. You don't have to name customers, you don't have to get in and reveal who they are, but what does success look like in multicloud as you paint a picture for the folks here and watching on the live stream, if someone says, "Hey I want to be multicloud, I got to to have my operations Agile, I want full DevOps, I want programmability and security built in from Day-zero." What does success look like? >> Yeah, I think success looks like this, so when you're building out a network, the network is a harder thing to change than some other aspects of cloud. So what we think is, even if you're thinking about that second cloud, which we have most of our customers are on two public clouds today, they might be dabbling in it. As you build that network foundation, that architecture, that takes in to consideration where you're going, and so once we start building that reference architecture out that shows, this is how to approach it from a multicloud perspective, not a single cloud, and let's not forget our branches, let's not forget our data centers, let's not forget how all this connects together because that's how we define multicloud, it's not just in the cloud, it's on-prem and it's off-prem. And so collectively, I think the key is also is that we provide them an HLD. You got to start with a high level design that can be tweaked as you go through the journey but you got to give it a solid structural foundation, and that networking which we think, most customers think as not the network engineers, but as an after thought. We want to make that the most critical element before you start the journey. >> George, from your seat, how does success look for you? >> So, you know it starts out on these journeys, often start out people not even thinking about what is going to happen, what their network needs are when they start their migration journey to the cloud. So I want, success to me looks like them being able to end up not worrying about what's happening in the network when they move to the cloud. >> Steve: Good point. >> Guys, great insight, thanks for coming on and sharing. How about a round of applause for the global system integrators? (Audience applauds) (Upbeat music) >> The next panel is the AVH certified engineers, also known as ACEs. This is the folks that are certified, they're engineering, they're building these new solutions. Please welcome Toby Foss from Informatica, Stacey Lanier from Teradata, and Jennifer Reed with Viqtor Davis to the stage. (upbeat music) (audience cheering) (panelists exchanging pleasantries) >> You got to show up. Where's your jacket Toby? (laughing) You get it done. I was just going to rib you guys and say, where's your jackets, and Jen's got the jacket on. Okay, good. >> Love the Aviatrix, ACEs Pilot gear there above the Clouds. Going to new heights. >> That's right. >> So guys Aviatrix aces, I love the name, think it's great, certified. This is all about getting things engineered. So there's a level of certification, I want to get into that. But first take us through the day in the life of an ACE, and just to point out, Stacy is a squad leader. So he's, he's like a-- >> Squadron Leader. >> Squadron Leader. >> Yeah. >> Squadron Leader, so he's got a bunch of ACEs underneath him, but share your perspective a day in the Life. Jennifer, we'll start with you. >> Sure, so I have actually a whole team that works for me both in the North America, both in the US and in Mexico. So I'm eagerly working to get them certified as well, so I can become a squad leader myself. But it's important because one of the critical gaps that we've found is people having the networking background because you graduate from college, and you have a lot of computer science background, you can program you've got Python, but networking in packets they just don't get. So, just taking them through all the processes that it's really necessary to understand when you're troubleshooting is really critical. Because you're going to get an issue where you need to figure out where exactly is that happening on the network, Is my issue just in the VPCs? Is it on the instance side is a security group, or is it going on prem? This is something actually embedded within Amazon itself? I mean, I troubleshot an issue for about six months going back and forth with Amazon, and it was the VGW VPN. Because they were auto scaling on two sides, and we ended up having to pull out the Cisco's, and put in Aviatrix so I could just say, " okay, it's fixed," and actually helped the application teams get to that and get it solved. But I'm taking a lot of junior people and getting them through that certification process, so they can understand and see the network, the way I see the network. I mean, look, I've been doing this for 25 years when I got out. When I went in the Marine Corps, that's what I did, and coming out, the network is still the network. But people don't get the same training they got in the 90s. >> Was just so easy, just write some software, and they were, takes care of itself. I know, it's pixie dust.  >> I'll come back to that, I want to come back to that, the problem solved with Amazon, but Toby. >> I think the only thing I have to add to that is that it's always the network's fault. As long as I've been in networking, it's always been the network's fault. I'm even to this day, it's still the network's fault, and part of being a network guy is that you need to prove when it is and when it's not your fault. That means you need to know a little bit about 100 different things, to make that work. >> Now you got a full stack DevOps, you got to know a lot more times another hundred. >> Toby: And the times are changing, yeah. >> This year the Squadron Leader and get that right. What is the Squadron Leader firstly? Describe what it is. >> I think is probably just leading on the network components of it. But I think, from my perspective, when to think about what you asked them was, it's about no issues and no escalations. So of my day is like that, I'm happy to be a squadron leader. >> That is a good outcome, that's a good day. >> Yeah, sure, it is. >> Is there good days? You said you had a good day with Amazon? Jennifer, you mentioned the Amazon, and this brings up a good point, when you have these new waves come in, you have a lot of new things, new use cases. A lot of the finger pointing it's that guy's problem , that girl's problems, so how do you solve that, and how do you get the Young Guns up to speed? Is there training, is it this where the certification comes in? >> This is where the certifications really going to come in. I know when we got together at Reinvent, one of the questions that we had with Steve and the team was, what should our certification look like? Should we just be teaching about what AVH troubleshooting brings to bear, but what should that be like? I think Toby and I were like, No, no, no, no. That's going a little too high, we need to get really low because the better someone can get at actually understanding what's actually happening in the network, and where to actually troubleshoot the problem, how to step back each of those processes. Because without that, it's just a big black box, and they don't know. Because everything is abstracted, in Amazon and in Azure and in Google, is abstracted, and they have these virtual gateways, they have VPNs, that you just don't have the logs on, is you just don't know. So then what tools can you put in front of them of where they can look? Because there are full logs. Well, as long as they turned on the flow logs when they built it, and there's like, each one of those little things that well, if they'd had decided to do that, when they built it, it's there. But if you can come in later to really supplement that with training to actual troubleshoot, and do a packet capture here, as it's going through, then teaching them how to read that even. >> Yeah, Toby, we were talking before we came on up on stage about your career, you've been networking all your time, and then, you're now mentoring a lot of younger people. How is that going? Because the people who come in fresh they don't have all the old war stories, like they don't talk about it, There's never for, I walk in bare feet in the snow when I was your age, I mean, it's so easy now, right, they say. What's your take on how you train the young People. >> So I've noticed two things. One is that they are up to speed a lot faster in generalities of networking. They can tell you what a network is in high school level now, where I didn't learn that til midway through my career, and they're learning it faster, but they don't necessarily understand why it's that way here. Everybody thinks that it's always slash 24 for a subnet, and they don't understand why you can break it down smaller, why it's really necessary. So the ramp up speed is much faster for these guys that are coming in. But they don't understand why and they need some of that background knowledge to see where it's coming from, and why is it important, and that's old guys, that's where we thrive. >> Jennifer, you mentioned you got in from the Marines, it helps, but when you got into networking, what was it like then and compare it now? Because most like we heard earlier static versus dynamic Don't be static is like that. You just set the network, you got a perimeter. >> Yeah, no, there was no such thing. So back in the day, I mean, we had Banyan vines for email, and we had token ring, and I had to set up token ring networks and figure out why that didn't work. Because how many of things were actually sharing it. But then actually just cutting fiber and running fiber cables and dropping them over shelters to plug them in and all crap, they swung it too hard and shattered it and now I got to figure eight Polish this thing and actually should like to see if it works. I mean, that was the network , current cat five cables to run an Ethernet, and then from that I just said, network switches, dumb switches, like those were the most common ones you had. Then actually configuring routers and logging into a Cisco router and actually knowing how to configure that. It was funny because I had gone all the way up, I was the software product manager for a while. So I've gone all the way up the stack, and then two and a half, three years ago, I came across to work with Entity group that became Viqtor Davis. But we went to help one of our customers Avis, and it was like, okay, so we need to fix the network. Okay, I haven't done this in 20 years, but all right, let's get to it. Because it really fundamentally does not change. It's still the network. I mean, I've had people tell me, Well, when we go to containers, we will not have to worry about the network. And I'm like, yeah, you don't I do. >> And that's within programmability is a really interesting, so I think this brings up the certification. What are some of the new things that people should be aware of that come in with the Aviatrix A certification? What are some of the highlights? Can you guys share some of the highlights around the certifications? >> I think some of the importance is that it doesn't need to be vendor specific for network generality or basic networking knowledge, and instead of learning how Cisco does something, or how Palo Alto does something, We need to understand how and why it works as a basic model, and then understand how each vendor has gone about that problem and solved it in a general. That's true in multicloud as well. You can't learn how Cloud networking works without understanding how AWS and Azure and GCP are all slightly the same but slightly different, and some things work and some things don't. I think that's probably the number one take. >> I think having a certification across Clouds is really valuable because we heard the global s eyes as you have a business issues. What does it mean to do that? Is it code, is it networking? Is it configurations of the Aviatrix? what is, he says,the certification but, what is it about the multiCloud that makes it multi networking and multi vendor? >> The easy answer is yes, >> Yes is all of us. >> All of us. So you got to be in general what's good your hands and all You have to be. Right, it takes experience. Because every Cloud vendor has their own certification. Whether that's SOPs and advanced networking and event security, or whatever it might be, yeah, they can take the test, but they have no idea how to figure out what's wrong with that system. The same thing with any certification, but it's really getting your hands in there, and actually having to troubleshoot the problems, actually work the problem, and calm down. It's going to be okay. I mean, because I don't know how many calls I've been on or even had aviators join me on. It's like, okay, so everyone calm down, let's figure out what's happening. It's like, we've looked at that screen three times, looking at it again is not going to solve that problem, right. But at the same time, remaining calm but knowing that it really is, I'm getting a packet from here to go over here, it's not working, so what could be the problem? Actually stepping them through those scenarios, but that's like, you only get that by having to do it, and seeing it, and going through it, and then you get it. >> I have a question, so, I just see it. We started this program maybe six months ago, we're seeing a huge amount of interest. I mean, we're oversubscribed on all the training sessions. We've got people flying from around the country, even with Coronavirus, flying to go to Seattle to go to these events where we're subscribed, is that-- >> A good emerging leader would put there. >> Yeah. So, is that something that you see in your organizations? Are you recommending that to people? Do you see, I mean, I'm just, I guess I'm surprised or not surprised. But I'm really surprised by the demand if you would, of this MultiCloud network certification because there really isn't anything like that. Is that something you guys can comment on? Or do you see the same things in your organization? >> I see from my side, because we operate in a multiCloud environments that really helps and some beneficial for us. >> Yeah, true. I think I would add that networking guys have always needed to use certifications to prove that they know what they know. >> Right. >> It's not good enough to say, Yeah, I know IP addresses or I know how a network works. A couple little check marks or a little letters body writing helps give you validity. So even in our team, we can say, Hey, we're using these certifications to know that you know enough of the basics and enough of the understandings, that you have the tools necessary, right. >> I guess my final question for you guys is, why an ACE certification is relevant, and then second part is share with the live stream folks who aren't yet ACE certified or might want to jump in to be aviatrix certified engineers. Why is it important, so why is it relevant and why should someone want to be a certified aviatrix certified engineer? >> I think my views a little different. I think certification comes from proving that you have the knowledge, not proving that you get a certification to get an army there backwards. So when you've got the training and the understanding and you use that to prove and you can, like, grow your certification list with it, versus studying for a test to get a certification and have no understanding of it. >> Okay, so that who is the right person that look at this and say, I'm qualified, is it a network engineer, is it a DevOps person? What's your view, a little certain. >> I think Cloud is really the answer. It's the, as we talked like the edges getting eroded, so is the network definition getting eroded? We're getting more and more of some network, some DevOps, some security, lots and lots of security, because network is so involved in so many of them. That's just the next progression. >> Do you want to add something there? >> I would say expand that to more automation engineers, because we have those now, so I probably extend it beyond this one. >> Jennifer you want to? >> Well, I think the training classes themselves are helpful, especially the entry level ones for people who may be "Cloud architects" but have never done anything in networking for them to understand why we need those things to really work, whether or not they go through to eventually get a certification is something different. But I really think fundamentally understanding how these things work, it makes them a better architect, makes them better application developer. But even more so as you deploy more of your applications into the Cloud, really getting an understanding, even from people who have traditionally done Onprem networking, they can understand how that's going to work in Cloud. >> Well, I know we've got just under 30 seconds left. I want to get one more question then just one more, for the folks watching that are maybe younger than, that don't have that networking training. From your experiences each of you can answer why should they know about networking, what's the benefit? What's in it for them? Motivate them, share some insights of why they should go a little bit deeper in networking. Stacy, we'll start with you, we'll go then. >> I'll say it's probably fundamental, right? If you want to deliver solutions, networking is the very top. >> I would say if you, fundamental of an operating system running on a machine, how those machines start together is a fundamental changes, something that start from the base and work your way up. >> Jennifer? >> Right, well, I think it's a challenge. Because you've come from top down, now you're going to start looking from bottom up, and you want those different systems to cross-communicate, and say you've built something, and you're overlapping IP space, note that that doesn't happen. But how can I actually make that still operate without having to re IP re platform. Just like those challenges, like those younger developers or assistant engineers can really start to get their hands around and understand those complexities and bring that forward in their career. >> They get to know then how the pipes are working, and they're got to know it--it's the plumbing. >> That's right, >> They got to know how it works, and how to code it. >> That's right. >> Awesome, thank you guys for great insights, ACE Certified Engineers, also known as ACEs, give them a round of applause. (audience clapping) (upbeat music) >> Thank you, okay. All right, that concludes my portion. Thank you, Steve Thanks for having me. >> John, thank you very much, that was fantastic. Everybody round of applause for John Furrier. (audience applauding) Yeah, so great event, great event. I'm not going to take long, we got lunch outside for the people here, just a couple of things. Just to call the action, right? So we saw the ACEs, for those of you out of the stream here, become a certified, right, it's great for your career, it's great for not knowledge, is fantastic. It's not just an aviator's thing, it's going to teach you about Cloud networking, MultiCloud networking, with a little bit of aviatrix, exactly like the Cisco CCIE program was for IP network, that type of the thing, that's number one. Second thing is learning, right? So there's a link up there to join the community. Again like I started this, this is a community, this is the kickoff to this community, and it's a movement. So go to community.avh.com, starting a community of multiCloud. So get get trained, learn. I'd say the next thing is we're doing over 100 seminars across the United States and also starting into Europe soon, we will come out and we'll actually spend a couple hours and talk about architecture, and talk about those beginning things. For those of you on the livestream in here as well, we're coming to a city near you, go to one of those events, it's a great way to network with other people that are in the industry, as well as to start alone and get on that MultiCloud journey. Then I'd say the last thing is, we haven't talked a lot about what Aviatrix does here, and that's intentional. We want you leaving with wanting to know more, and schedule, get with us and schedule a multi hour architecture workshop session. So we sit down with customers, and we talk about where they're at in that journey, and more importantly, where they're going, and define that end state architecture from networking, computer, storage, everything. Everything you've heard today, everybody panel kept talking about architecture, talking about operations. Those are the types of things that we solve, we help you define that canonical architecture, that system architecture, that's yours. So many of our customers, they have three by five, plotted lucid charts, architecture drawings, and it's the customer name slash Aviatrix, network architecture, and they put it on their whiteboard. That's the most valuable thing they get from us. So this becomes their 20 year network architecture drawing that they don't do anything without talking to us and look at that architecture. That's what we do in these multi hour workshop sessions with customers, and that's super, super powerful. So if you're interested, definitely call us, and let's schedule that with our team. So anyway, I just want to thank everybody on the livestream. Thank everybody here. Hopefully it was it was very useful. I think it was, and Join the movement, and for those of you here, join us for lunch, and thank you very much. (audience applauding) (upbeat music)

ladies and gentlemen this is your captain speaking we will soon be taking off on our way to altitude please keep your seatbelts fastened and remain in your seats we will be experiencing turbulence until we are above the clouds ladies and gentlemen we are now cruising at altitude sit back and enjoy the ride [Music] altitude is a community of thought leaders and pioneers cloud architects and enlightened network engineers who have individually and are now collectively leading their own IT teams and the industry on a path to lift cloud networking above the clouds empowering Enterprise IT to architect design and control their own cloud network regardless of the turbulent clouds beneath them it's time to gain altitude ladies and gentlemen Steve Mulaney president and CEO of aviatrix the leader of multi cloud networking [Music] [Applause] all right good morning everybody here in Santa Clara as well as to the what millions of people watching the livestream worldwide welcome to altitude 2020 all right so we've got a fantastic event today really excited about the speakers that we have today and the experts that we have and really excited to get started so one of the things I wanted to just share was this is not a one-time event it's not a one-time thing that we're gonna do sorry for the aviation analogy but you know sherry way aviatrix means female pilot so everything we do as an aviation theme this is a take-off for a movement this isn't an event this is a take-off of a movement a multi-cloud networking movement and community that we're inviting all of you to become part of and-and-and why we're doing that is we want to enable enterprises to rise above the clouds so to speak and build their network architecture regardless of which public cloud they're using whether it's one or more of these public clouds so the good news for today there's lots of good news but this is one good news is we don't have any powerpoint presentations no marketing speak we know that marketing people have their own language we're not using any of that in those sales pitches right so instead what are we doing we're going to have expert panels we've got Simone Rashard Gartner here we've got 10 different network architects cloud architects real practitioners they're going to share their best practices and there are real-world experiences on their journey to the multi cloud so before we start and everybody know what today is in the u.s. it's Super Tuesday I'm not gonna get political but Super Tuesday there was a bigger Super Tuesday that happened 18 months ago and maybe eight six employees know what I'm talking about 18 months ago on a Tuesday every enterprise said I'm gonna go to the cloud and so what that was was the Cambrian explosion for cloud for the price so Frank kibrit you know what a Cambrian explosion is he had to look it up on Google 500 million years ago what happened there was an explosion of life where it went from very simple single-cell organisms to very complex multi-celled organisms guess what happened 18 months ago on a Tuesday I don't really know why but every enterprise like I said all woke up that day and said now I'm really gonna go to cloud and that Cambrian explosion of cloud went meant that I'm moving from very simple single cloud single use case simple environment to a very complex multi cloud complex use case environment and what we're here today is we're gonna go and dress that and how do you handle those those those complexities and when you look at what's happening with customers right now this is a business transformation right people like to talk about transitions this is a transformation and it's actually not just the technology transformation it's a business transformation it started from the CEO and the boards of enterprise customers where they said I have an existential threat to the survival of my company if you look at every industry who they're worried about is not the other 30 year old enterprise what they're worried about is the three year old enterprise that's leveraging cloud that's leveraging AI and that's where they fear that they're going to actually get wiped out right and so because of this existential threat this is CEO lead this is board led this is not technology led it is mandated in the organization's we are going to digitally transform our enterprise because of this existential threat and the movement to cloud is going to enable us to go do that and so IT is now put back in charge if you think back just a few years ago in cloud it was led by DevOps it was led by the applications and it was like I said before their Cambrian explosion is very simple now with this Cambrian explosion and enterprises getting very serious and mission critical they care about visibility they care about control they care about compliance conformance everything governance IT is in charge and and and that's why we're here today to discuss that so what we're going to do today is much of things but we're gonna validate this journey with customers do they see the same thing we're gonna validate the requirements for multi-cloud because honestly I've never met an enterprise that is not going to be multi-cloud many are one cloud today but they all say I need to architect my network for multiple clouds because that's just what the network is there to support the applications and the applications will run and whatever cloud it runs best in and you have to be prepared for that the second thing is is is architecture again with the IT in charge you architecture matters whether it's your career whether it's how you build your house it doesn't matter horrible architecture your life is horrible forever good architecture your life is pretty good so we're gonna talk about architecture and how the most fundamental and critical part of that architecture and that basic infrastructure is the network if you don't get that right nothing works right way more important and compute way more important than storm dense storage network is the foundational element of your infrastructure then we're going to talk about day 2 operations what does that mean well day 1 is one day of your life that's who you wire things up they do and beyond I tell everyone in networking and IT it's every day of your life and if you don't get that right your life is bad forever and so things like operations visibility security things like that how do I get my operations team to be able to handle this in an automated way because it's not just about configuring it in the cloud it's actually about how do I operationalize it and that's a huge benefit that we bring as aviatrix and then the last thing we're going to talk and it's the last panel we have I always say you can't forget about the humans right so all this technology all these things that we're doing it's always enabled by the humans at the end of the day if the humans fight it it won't get deployed and we have a massive skills gap in cloud and we also have a massive skill shortage you have everyone in the world trying to hire cloud network architects right there's just not enough of them going around so at aviatrix as leaders knew we're gonna help address that issue and try to create more people we created a program and we call the ACE program again an aviation theme it stands for aviatrix certified engineer very similar to what Cisco did with CC IES where Cisco taught you about IP networking a little bit of Cisco we're doing the same thing we're gonna teach network architects about multi-cloud networking and architecture and yeah you'll get a little bit of aviatrix training in there but this is the missing element for people's careers and also within their organization so we're gonna we're gonna go talk about that so great great event great show when try to keep it moving I'd next want to introduce my my host he's the best in the business you guys have probably seen him multiple million times he's the co CEO and co-founder of Tube John Fourier okay awesome great great speech they're awesome I totally agree with everything you said about the explosion happening and I'm excited here at the heart of Silicon Valley to have this event it's a special digital event with the cube and aviatrix where we live streaming to millions of people as you said maybe not a million maybe not really take this program to the world this is a little special for me because multi-cloud is the hottest wave and cloud and cloud native networking is fast becoming the key engine of the innovation so we got an hour and a half of action-packed programming we have a customer panel two customer panels before that Gartner is going to come on talk about the industry we have a global system integrators we talk about how they're advising and building these networks and cloud native networking and then finally the Aces the aviatrix certified engineer is gonna talk more about their certifications and the expertise needed so let's jump right in and let's ask someone rashard to come on stage from Gartner we'll check it all up [Applause] [Music] okay so kicking things off certain started gartner the industry experts on cloud really kind of more to your background talk about your background before you got the gardener yeah before because gardener was a chief network architect of a fortune five companies with thousands of sites over the world and I've been doing everything and IT from a C programmer in the 90 to a security architect to a network engineer to finally becoming a network analyst so you rode the wave now you're covering at the marketplace with hybrid cloud and now moving quickly to multi cloud is really I was talking about cloud natives been discussed but the networking piece is super important how do you see that evolving well the way we see Enterprise adapt in cloud first thing you do about networking the initial phases they either go in a very ad hoc way is usually led by non non IT like a shadow whitey or application people or some kind of DevOps team and it's it just goes as it's completely unplanned decreed VP sees left and right with a different account and they create mesh to manage them and their direct connect or Express route to any of them so that's what that's a first approach and on the other side again it within our first approach you see what I call the lift and shift way we see like Enterprise IT trying to basically replicate what they have in a data center in the cloud so they spend a lot of time planning doing Direct Connect putting Cisco routers and f5 and Citrix and any checkpoint Palo Alto divides the data that are sent removing that to that cloud and I ask you the aha moments gonna come up a lot of our panels is where people realize that it's a multi cloud world I mean they either inherit clouds certainly they're using public cloud and on-premises is now more relevant than ever when's that aha moment that you're seeing where people go well I got to get my act together and get on this well the first but even before multi-cloud so these two approach the first one like the adduct way doesn't scale at some point idea has to save them because they don't think about the two they don't think about operations they have a bunch of VPC and multiple clouds the other way that if you do the left and shift wake they cannot take any advantages of the cloud they lose elasticity auto-scaling pay by the drink these feature of agility features so they both realize okay neither of these ways are good so I have to optimize that so I have to have a mix of what I call the cloud native services within each cloud so they start adapting like other AWS constructor is your construct or Google construct then that's I would I call the up optimal phase but even that they they realize after that they are very different all these approaches different the cloud are different identities is completely difficult to manage across clouds I mean for example AWS has accounts there's subscription and in adarand GCP their projects it's a real mess so they realize well I can't really like concentrate used the cloud the cloud product and every cloud that doesn't work so I have I'm doing multi cloud I like to abstract all of that I still wanna manage the cloud from an API to interview I don't necessarily want to bring my incumbent data center products but I have to do that in a more API driven cloud they're not they're not scaling piece and you were mentioning that's because there's too many different clouds yes that's the piece there so what are they doing whether they really building different development teams as its software what's the solution well this the solution is to start architecting the cloud that's the third phase I call that the multi cloud architect phase where they have to think about abstraction that works across cloud fact even across one cloud it might not scale as well if you start having like 10,000 security group in AWS that doesn't scale you have to manage that if you have multiple VPC it doesn't scale you need a third party identity provider so it barely scales within one cloud if you go multiple cloud it gets worse and worse see way in here what's your thoughts I thought we said this wasn't gonna be a sales pitch for aviatrix you just said exactly what we do so anyway I'm just a joke what do you see in terms of where people are in that multi cloud a lot of people you know everyone I talked to started in one cloud right but then they look and they say okay but I'm now gonna move to adjourn I'm gonna move do you see a similar thing well yes they are moving but they're not there's not a lot of application that use a tree cloud at once they move one app in deserve one app in individuals one get happened Google that's what we see so far okay yeah I mean one of the mistakes that people think is they think multi-cloud no one is ever gonna go multi-cloud for arbitrage they're not gonna go and say well today I might go into Azure because I got a better rate of my instance that's never do you agree with that's never going to happen what I've seen with enterprise is I'm gonna put the workload in the app the app decides where it runs best that may be a sure maybe Google and for different reasons and they're gonna stick there and they're not gonna move let me ask you infrastructure has to be able to support from a networking team be able to do that do you agree with that yes I agree and one thing is also very important is connecting to that cloud is kind of the easiest thing so though while I run Network part of the cloud connectivity to the cloud is kind of simple I agree IPSec VP and I reckon Express that's a simple part what's difficult and even a provisioning part is easy you can use terraform and create v pieces and v nets across which we cloud provider right what's difficult is the day-to-day operations so it's what to find a to operations what is that what does that actually mean this is the day-to-day operations after it you know the natural let's add an app let's add a server let's troubleshoot a problem so what so your life something changes how would he do so what's the big concerns I want to just get back to this cloud native networking because everyone kind of knows with cloud native apps are that's been a hot trend what is cloud native networking how do you how do you guys define that because that seems to be the oddest part of the multi-cloud wave that's coming as cloud native networking well there's no you know official garner definition but I can create one on another spot it's do it I just want to leverage the cloud construct and a cloud epi I don't want to have to install like like for example the first version was let's put a virtual router that doesn't even understand and then the cloud environment right if I have if I have to install a virtual machine it has to be cloud aware it has to understand the security group if it's a router it has to be programmable to the cloud API and and understand the cloud environment you know one things I hear a lot from either see Saussure CIOs or CXOs in general is this idea of I'm definitely on going API so it's been an API economy so API is key on that point but then they say okay I need to essentially have the right relationship with my suppliers aka clouds you call it above the clouds so the question is what do i do from an architecture standpoint do I just hire more developers and have different teams because you mentioned that's a scale point how do you solve this this problem of okay I got AWS I got GCP or Azure or whatever do I just have different teams or just expose api's where is that optimization where's the focus well I take what you need from an android point of view is a way a control plane across the three clouds and be able to use the api of the cloud to build networks but also to troubleshoot them and do they to operation so you need a view across a three cloud that takes care of routing connectivity that's you know that's the aviatrix plug of you right there so so how do you see so again your Gartner you you you you see the industry you've been a network architect how do you see this this plane out what are the what are the legacy incumbent client-server on-prem networking people gonna do well these versus people like aviatrix well how do you see that plane out well obviously all the incumbent like Arista cisco juniper NSX right they want to basically do the lift and ship or they want to bring and you know VM I want to bring in a section that cloud they call that NSX everywhere and cisco monks bring you star in the cloud recall that each guy anywhere right so everyone what and and then there's cloud vision for my red star and contrail is in the cloud so they just want to bring the management plain in the cloud but it's still based most of them it's still based on putting a VM them in controlling them right you you extend your management console to the cloud that's not truly cloud native right cloud native you almost have to build it from scratch we like to call that cloud naive clown that close one letter yeah so that was a big con surgeon i reinvent take the tea out of cloud native its cloud naive i went super viral you guys got t-shirts now i know you love it but yeah but that really ultimately is kind of a double-edged sword you got to be you can be naive on the on the architecture side and rolling out but also suppliers are can be naive so how would you define who's naive and who's not well in fact they're evolving as well so for example in cisco you it's a little bit more native than other ones because they're really ACI in the cloud you call you you really like configure api so the cloud and nsx is going that way and so is Arista but they're incumbent they have their own tools it's difficult for them they're moving slowly so it's much easier to start from scratch Avenue like and you know and network happiness started a few years ago there's only really two aviatrix was the first one they've been there for at least three or four years and there's other ones like Al Kyra for example that just started now that doing more connectivity but they want to create an overlay network across the cloud and start doing policies and trying abstracting all the clouds within one platform so I gotta ask you I interviewed an executive at VMware Sanjay Pune and he said to me at RSA last week oh the only b2 networking vendors left Cisco and VMware what's your respect what's your response to that obviously I mean when you have these waves as new brands that emerge like AV X and others though I think there'll be a lot of startups coming out of the woodwork how do you respond to that comment well there's still a data center there's still like a lot of action on campus and there's the one but from the cloud provisioning and clown networking in general I mean they're behind I think you know in fact you don't even need them to start to it you can if you're small enough you can just keep if you're in AWS you can user it with us construct they have to insert themselves I mean they're running behind they're all certainly incumbents I love the term Andy Jesse's that Amazon Web Services uses old guard new guard to talk about the industry what does the new guard have to do the new and new brands that emerge in is it be more DevOps oriented neck Nets a cops is that net ops is the programmability these are some of the key discussions we've been having what's your view on how you see this program their most important part is they have to make the network's simple for the dev teams and from you cannot have that you cannot make a phone call and get it via line in two weeks anymore so if you move to that cloud you have to make the cloud construct as simple enough so that for example a dev team could say okay I'm going to create this VP see but this VP see automatically being your associate to your account you cannot go out on the internet you have to go to the transit VP C so there's a lot of action in terms of the I am part and you have to put the control around them too so to make it as simple as possible you guys both I mean you're the COC aviatrix but also you guys a lot of experience going back to networking going back to I call the OSI mace which for us old folks know that means but you guys know this means I want to ask you the question as you look at the future of networking here a couple of objectives oh the cloud guys they got networking we're all set with them how do you respond to the fact that networking is changing and the cloud guys have their own networking what some of the pain points that's going on premises and these enterprises so are they good with the clouds what needs what are the key things that's going on in networking that makes it more than just the cloud networking what's your take on well I as I said earlier that once you you could easily provision in the cloud you can easily connect to that cloud is when you start troubleshooting application in the cloud and try to scale so this that's where the problem occurs see what you're taking on it and you'll hear from the from the customers that that we have on stage and I think what happens is all the cloud the clouds by definition designed to the 80/20 rule which means they'll design 80% of the basic functionality and they'll lead the 20% extra functionality that of course every enterprise needs they'll leave that to ISVs like aviatrix because why because they have to make money they have a service and they can't have huge instances for functionality that not everybody needs so they have to design to the common and that's they all do it right they have to and then the extra the problem is that can be an explosion that I talked about with enterprises that's holy that's what they need that they're the ones who need that extra 20% so that's that's what I see is is there's always gonna be that extra functionality the in in an automated and simple way that you talked about but yet powerful with up with the visibility and control that they expect of on prep that that's that kind of combination that yin and the yang that people like us are providing some I want to ask you were gonna ask some of the cloud architect customer panels it's the same question this pioneers doing some work here and there's also the laggards who come in behind the early adopters what's gonna be the tipping point what are some of those conversations that the cloud architects are having out there or what's the signs that they need to be on this multi cloud or cloud native networking trend what are some the signals that are going on in their environment what are some of the threshold or things that are going on that there can pay attention to well well once they have application and multiple cloud and they have they get wake up at 2:00 in the morning to troubleshoot them they don't know it's important so I think that's the that's where the robber will hit the road but as I said it's easier to prove it it's okay it's 80s it's easy user transit gateway put a few V pcs and you're done and use create some presents like equinox and do Direct Connect and Express route with Azure that looks simple is the operations that's when they'll realize okay now I need to understand our car networking works I also need a tool that give me visibility and control not button tell me that I need to understand the basic underneath it as well what are some of the day in the life scenarios that you envision happening with multi cloud because you think about what's happening it kind of has that same vibe of interoperability choice multi-vendor because you have multi clouds essentially multi vendor these are kind of old paradigms that we've lived through the client-server and internet working wave what are some of those scenarios of success and that might be possible it would be possible with multi cloud and cloud native networking well I think once you have good enough visibility to satisfy your customers you know not only like to keep the service running an application running but to be able to provision fast enough I think that's what you want to achieve small final question advice for folks watching on the live stream if they're sitting there as a cloud architect or a CXO what's your advice to them right now in this market because honestly public check hybrid cloud they're working on that that gets on-premise is done now multi-class right behind it what's your advice the first thing they should do is really try to understand cloud networking for each of their cloud providers and then understand the limitation and is what their cloud service provider offers enough or you need to look to a third party but you don't look at a third party to start to it especially an incumbent one so it's tempting to say on and I have a bunch of f5 experts nothing against f5 I'm going to bring my five in the cloud when you can use a needle be that automatically understand ease ease and auto-scaling and so on and you understand that's much simpler but sometimes you need you have five because you have requirements you have like AI rules and that kind of stuff that you use for years you cannot do it's okay I have requirement and that net I'm going to use legacy stuff and then you have to start thinking okay what about visibility control about the tree cloud but before you do that you have to understand the limitation of the existing cloud providers so first try to be as native as possible until things don't work after that you can start taking multi-cloud great insight somewhat thank you for coming someone in charge with Gardner thanks for sharing thank you appreciate it [Applause] informatica is known as the leading enterprise cloud data management company we are known for being the top in our industry in at least five different products over the last few years especially we've been transforming into a cloud model which allows us to work better with the trends of our customers in order to see agile and effective in a business you need to make sure that your products and your offerings are just as relevant in all these different clouds than what you're used to and what you're comfortable with one of the most difficult challenges we've always had is that because we're a data company we're talking about data that a customer owns some of that data may be in the cloud some of that data may be on Prem some of them data may be actually in their data center in another region or even another country and having that data connect back to our systems that are located in the cloud has always been a challenge when we first started our engagement with aviatrix we only had one plan that was Amazon it wasn't till later that a jerk came up and all of a sudden we found hey the solution we already had in place for aviatrix already working in Amazon and now works in Missouri as well before we knew it GCP came up but it really wasn't a big deal for us because we already had the same solution in Amazon and integer now just working in GCP by having a multi cloud approach we have access to all three of them but more commonly it's not just one it's actually integrations between multiple we have some data and ensure that we want to integrate with Amazon we have some data in GCP that we want to bring over to a data Lake assure one of the nice things about aviatrix is that it gives a very simple interface that my staff can understand and use and manage literally hundreds of VPNs around the world and while talking to and working with our customers who are literally around the world now that we've been using aviatrix for a couple years we're actually finding that even problems that we didn't realize we had were actually solved even before we came across the problem and it just worked cloud companies as a whole are based on reputation we need to be able to protect our reputation and part of that reputation is being able to protect our customers and being able to protect more importantly our customers data aviatrix has been helpful for us in that we only have one system that can manage this whole huge system in a simple easy direct model aviatrix is directly responsible for helping us secure and manage our customers not only across the world but across multiple clouds users don't have to be VPN or networking experts in order to be able to use the system all the members on my team can manage it all the members regardless of their experience can do different levels of it one of the unexpected two advantages of aviatrix is that I don't have to sell it to my management the fact that we're not in the news at three o'clock in the morning or that we don't have to get calls in the middle of the night no news is good news especially in networking things that used to take weeks to build are done in hours I think the most important thing about a matrix is it provides me consistency aviatrix gives me a consistent model that I can use across multiple regions multiple clouds multiple customers okay welcome back to altitude 2020 for the folks on the livestream I'm John for Steve Mulaney with CEO of aviatrix for our first of two customer panels on cloud with cloud network architects we got Bobby Willoughby they gone Luis Castillo of National Instruments and David should Nick with fact set guys welcome to the stage for this digital event come on up [Music] hey good to see you thank you okay okay customer panelist is my favorite part we get to hear the real scoop we got the gardener giving us the industry overview certainly multi clouds very relevant and cloud native networking is the hot trend with the live stream out there and the digital event so guys let's get into it the journey is you guys are pioneering this journey of multi cloud and cloud native networking and it's soon gonna be a lot more coming so I want to get into the journey what's it been like is it real you got a lot of scar tissue and what are some of the learnings yeah absolutely so multi cloud is whether or not we we accepted as a network engineers is a is a reality like Steve said about two years ago companies really decided to to just to just bite the bullet and and and move there whether or not whether or not we we accept that fact we need to now create a consistent architecture across across multiple clouds and that that is challenging without orchestration layers as you start managing different different tool sets in different languages across different clouds so that's it's really important that to start thinking about that guys on the other panelists here there's different phases of this journey some come at it from a networking perspective some come in from a problem troubleshooting what's what's your experiences yeah so from a networking perspective it's been incredibly exciting it's kind of a once-in-a-generation 'el opportunity to look at how you're building out your network you can start to embrace things like infrastructure as code that maybe your peers on the systems teams have been doing for years but it just never really worked on pram so it's really it's really exciting to look at all the opportunities that we have and then all the interesting challenges that come up that you that you get to tackle an effect said you guys are mostly AWS right yep right now though we are looking at multiple clouds we have production workloads running in multiple clouds today but a lot of the initial work has been with Amazon and you've seen it from a networking perspective that's where you guys are coming at it from yep yeah we evolved more from a customer requirement perspective started out primarily as AWS but as the customer needed more resources to measure like HPC you know as your ad things like that even recently Google at Google Analytics our journey has evolved into mortal multi-cloud environment Steve weigh in on the architecture because this has been the big conversation I want you to lead this second yeah so I mean I think you guys agree the journey you know it seems like the journey started a couple years ago got real serious the need for multi-cloud whether you're there today of course it's gonna be there in the future so that's really important I think the next thing is just architecture I'd love to hear what you you know had some comments about architecture matters it all starts I mean every Enterprise that I talk to maybe talk about architecture and the importance of architecture maybe Bobby it's a particular perspective we sorted a journey five years ago Wow okay and we're just now starting our fourth evolution of our network architect and we'll call it networking security net sec yep adverse adjusters network and that fourth generation or architectures be based primarily upon Palo Alto Networks an aviatrix a matrix doing the orchestration piece of it but that journey came because of the need for simplicity okay I need for multi-cloud orchestration without us having to go and do reprogramming efforts across every cloud as it comes along right I guess the other question I also had around architectures also Louis maybe just talk about I know we've talked a little bit about you know scripting right and some of your thoughts on that yeah absolutely so so for us we started we started creating the network constructs with cloud formation and we've we've stuck with that for the most part what's interesting about that is today on premise we have a lot of a lot of automation around around how we provision networks but cloud formation has become a little bit like the new manual for us so we're now having issues with having to to automate that component and making it consistent with our on-premise architecture making it consistent with Azure architecture and Google cloud so it's really interesting to see to see companies now bring that layer of abstraction that SD when brought to the to the wine side now it's going up into into the into the cloud networking architecture so on the fourth generation of you mentioned you're in the fourth gen architecture what do you guys what have you learned is there any lessons scar tissue what to avoid what worked what was some of the there was a path that's probably the biggest list and there is when you think you finally figured it out you have it right Amazon will change something as you change something you know transit gateways a game changer so in listening to the business requirements is probably the biggest thing we need to do up front but I think from a simplicity perspective like I said we don't want to do things four times we want to do things one time we won't be able to write to an API which aviatrix has and have them do the orchestration for us so that we don't have to do it four times how important is architecture in the progression is it you guys get thrown in the deep end to solve these problems or you guys zooming out and looking at it it's a I mean how are you guys looking at the architecture I mean you can't get off the ground if you don't have the network there so all of those there we've gone through similar evolutions we're on our fourth or fifth evolution I think about what we started off with Amazon without a direct connect gate without a transit Gateway without a lot of the things that are available today kind of the 80/20 that Steve was talking about just because it wasn't there doesn't mean we didn't need it so we needed to figure out a way to do it we couldn't say oh you need to come back to the network team in a year and maybe Amazon will have a solution for it right you need to do it now and in evolve later and maybe optimize or change the way you're doing things in the future but don't sit around and wait you can I'd love to have you guys each individually answer this question for the live stream because it comes up a lot a lot of cloud architects out in the community what should they be thinking about the folks that are coming into this proactively and/or realizing the business benefits are there what advice would you guys give them an architecture what should be they be thinking about and what are some guiding principles you could share so I would start with looking at an architecture model that that can that can spread and and give consistency they're different to different cloud vendors that you will absolutely have to support cloud vendors tend to want to pull you into using their native toolset and that's good if only it was realistic to talk about only one cloud but because it doesn't it's it's it's super important to talk about and have a conversation with the business and with your technology teams about a consistent model so that's the David yeah talking as earlier about day two operations so how do I design how do I do my day one work so that I'm not you know spending eighty percent of my time troubleshooting or managing my network because I'm doing that then I'm missing out on ways that I can make improvements or embrace new technologies so it's really important early on to figure out how do I make this as low maintenance as possible so that I can focus on the things that the team really should be focusing on Bobby your advice the architect I don't know what else I can do that simplicity of operations is key alright so the holistic view of day to operation you mentioned let's can jump in day one is your your your getting stuff set up day two is your life after all right this is kinda what you're getting at David so what does that look like what are you envisioning as you look at that 20 mile stair out post multi-cloud world what are some of the things that you want in a day to operations yeah infrastructure is code is really important to us so how do we how do we design it so that we can fit start making network changes and fitting them into like a release pipeline and start looking at it like that rather than somebody logging into a router CLI and troubleshooting things on in an ad hoc nature so moving more towards the DevOps model is anything on that day - yeah I would love to add something so in terms of day 2 operations you can you can either sort of ignore the day 2 operations for a little while where you get well you get your feet wet or you can start approaching it from the beginning the fact is that the the cloud native tools don't have a lot of maturity in that space and when you run into an issue you're gonna end up having a bad day going through millions and millions of logs just to try to understand what's going on so that's something that that the industry just now is beginning to realize it's it's such a such a big gap I think that's key because for us we're moving to more of an event-driven or operations in the past monitoring got the job done it's impossible to modern monitor something there's nothing there when the event happens all right so the event-driven application and then detect is important yeah I think garden was all about the cloud native wave coming into networking that's gonna be a serious thing I want to get you guys perspectives I know you have different views of how you come into the journey and how you're executing and I always say the beauties in the eye of the beholder and that kind of applies how the networks laid out so Bobby you guys do a lot of high-performance encryption both on AWS and Azure that's kind of a unique thing for you how are you seeing that impact with multi cloud yeah and that's a new requirement for us to where we we have an intern crypt and they they ever get the question should I encryption and I'll encrypt the answer is always yes you should encrypt when you can encrypt for our perspective we we need to migrate a bunch of data from our data centers we have some huge data centers and then getting that data to the cloud is the timely experiencing some cases so we have been mandated that we have to encrypt everything leaving the data center so we're looking at using the aviatrix insane mode appliances to be able to encrypt you know 10 20 gigabits of data as it moves to the cloud itself David you're using terraform you got fire Ned you've got a lot of complexity in your network what do you guys look at the future for yours environment yeah so something exciting that or yeah now is fire net so for our security team they obviously have a lot of a lot of knowledge base around Palo Alto and with our commitments to our clients you know it's it's it's not very easy to shift your security model to a specific cloud vendor right so there's a lot of stuck to compliance of things like that where being able to take some of what you've you know you've worked on for years on Bram and put it in the cloud and have the same type of assurance that things are gonna work and be secure in the same way that they are on prem helps make that journey into the cloud a lot easier and Louis you guys got scripting and get a lot of things going on what's your what's your unique angle on this yeah no absolutely so full disclosure I'm not a not not an aviatrix customer yet it's ok we want to hear the truth that's good Ellis what are you thinking about what's on your mind no really when you when you talk about implementing the tool like this it's really just really important to talk about automation and focus on on value so when you talk about things like and things like so yeah encrypting tunnels and encrypting the paths and those things are it should it should should be second nature really when you when you look at building those backends and managing them with your team it becomes really painful so tools like aviatrix that that add a lot of automation it's out of out of sight out of mind you can focus on the value and you don't have to focus on so I gotta ask you guys I see AV traces here they're they're a supplier to the sector but you guys are customers everyone's pitching you stuff people are not gonna buy my stuff how do you guys have that conversation with the suppliers like the cloud vendors and other folks what's the what's it like where API all the way you got to support this what are some of the what are some of your requirements how do you talk to and evaluate people that walk in and want to knock on your door and pitch you something what's the conversation like um it's definitely it's definitely API driven we we definitely look at the at that the API structure of the vendors provide before we select anything that that is always first in mind and also what a problem are we really trying to solve usually people try to sell or try to give us something that isn't really valuable like implementing a solution on the on the on the cloud isn't really it doesn't really add a lot of value that's where we go David what's your conversation like with suppliers you have a certain new way to do things as as becomes more agile and essentially the networking become more dynamic what are some of the conversation is with the either incumbents or new new vendors that you're having what it what do you require yeah so ease of use is definitely definitely high up there we've had some vendors come in and say you know hey you know when you go to set this up we're gonna want to send somebody on site and they're gonna sit with you for your day to configure it and that's kind of a red flag what wait a minute you know do we really if one of my really talented engineers can't figure it out on his own what's going on there and why is that so you know having having some ease-of-use and the team being comfortable with it and understanding it is really important Bobby how about you I mean the old days was do a bake-off and you know the winner takes all I mean is it like that anymore what's the Volvic bake-off last year first you win so but that's different now because now when you you get the product you can install the product in AWS energy or have it up and running a matter of minutes and so the key is is they can you be operational you know within hours or days instead of weeks but but do we also have the flexibility to customize it to meet your needs could you want to be you won't be put into a box with the other customers we have needs that surpass their cut their needs yeah I almost see the challenge that you guys are living where you've got the cloud immediate value to make an roll-up any solutions but then you have might have other needs so you've got to be careful not to buy into stuff that's not shipping so you're trying to be proactive at the same time deal with what you got I mean how do you guys see that evolving because multi-cloud to me is definitely relevant but it's not yet clear how to implement across how do you guys look at this baked versus you know future solutions coming how do you balance that so again so right now we we're we're taking the the ad hoc approach and and experimenting with the different concepts of cloud and really leveraging the the native constructs of each cloud but but there's a there's a breaking point for sure you don't you don't get to scale this I like like Simone said and you have to focus on being able to deliver a developer they're their sandbox or their play area for the for the things that they're trying to build quickly and the only way to do that is with the with with some sort of consistent orchestration layer that allows you to so you've got a lot more stuff to be coming pretty quickly IDEs area I do expect things to start to start maturing quite quite quickly this year and you guys see similar trend new stuff coming fast yeah part of the biggest challenge we've got now is being able to segment within the network being able to provide segmentation between production on production workloads even businesses because we support many businesses worldwide and and isolation between those is a key criteria there so the ability to identify and quickly isolate those workloads is key so the CIOs that are watching or that are saying hey take that he'll do multi cloud and then you know the bottoms up organization think pause you're kind of like off a little bit it's not how it works I mean what is the reality in terms of implementing you know and as fast as possible because the business benefits are clear but it's not always clear in the technology how to move that fast yeah what are some of the barriers one of the blockers what are the enabler I think the reality is is that you may not think you're multi-cloud but your business is right so I think the biggest barriers there is understanding what the requirements are and how best to meet those requirements in a secure manner because you need to make sure that things are working from a latency perspective that things work the way they did and get out of the mind shift that you know it was a cheery application in the data center it doesn't have to be a Tier three application in the cloud so lift and shift is is not the way to go scale is a big part of what I see is the competitive advantage to allow these clouds and used to be proprietary network stacks in the old days and then open systems came that was a good thing but as clouds become bigger there's kind of an inherent lock in there with the scale how do you guys keep the choice open how're you guys thinking about interoperability what are some of the conversations and you guys are having around those key concepts well when we look at when we look at the moment from a networking perspective it it's really key for you to just enable enable all the all the clouds to be to be able to communicate between them developers will will find a way to use the cloud that best suits their their business team and and like like you said it's whether whether you're in denial or not of the multi cloud fact that your company is in already that's it becomes really important for you to move quickly yeah and a lot of it also hinges on how well is the provider embracing what that specific cloud is doing so are they are they swimming with Amazon or sure and just helping facilitate things they're doing the you know the heavy lifting API work for you or they swimming upstream and they're trying to hack it all together in a messy way and so that helps you you know stay out of the lock-in because they're you know if they're doing if they're using Amazon native tools to help you get where you need to be it's not like Amazon's gonna release something in the future that completely you know makes you have designed yourself into a corner so the closer they're more cloud native they are the more the easier it is to to deploy but you also need to be aligned in such a way that you can take advantage of those cloud native technologies will it make sense tgw is a game-changer in terms of cost and performance right so to completely ignore that would be wrong but you know if you needed to have encryption you know teach Adobe's not encrypted so you need to have some type of a gateway to do the VPN encryption you know so the aviatrix tool give you the beauty of both worlds you can use tgw with a gateway Wow real quick in the last minute we have I want to just get a quick feedback from you guys I hear a lot of people say to me hey the I picked the best cloud for the workload you got and then figure out multi cloud behind the scenes so that seems to be do you guys agree with that I mean is it do I go Mull one cloud across the whole company or this workload works great on AWS that work was great on this from a cloud standpoint do you agree with that premise and then wit is multi clouds did you mall together yeah from from an application perspective it it can be per workload but it can also be an economical decision certain enterprise contracts will will pull you in one direction that add value but the the network problem is still the same doesn't go away yeah yeah I mean you don't want to be trying to fit a square into a round hall right so if it works better on that cloud provider then it's our job to make sure that that service is there and people can use it agree you just need to stay ahead of the game make sure that the network infrastructure is there secure is available and is multi cloud capable yeah I'm at the end of the day you guys just validating that it's the networking game now how cloud storage compute check networking is where the action is awesome thanks for your insights guys appreciate you coming on the panel appreciate thanks thank you [Applause] [Music] [Applause] okay welcome back on the live feed I'm John fritz T Blaney my co-host with aviatrix I'm with the cube for the special digital event our next customer panel got great another set of cloud network architects Justin Smith was aura Justin broadly with Ellie Mae and Amit Oh tree job with Cooper welcome to stage [Applause] all right thank you thank you oK you've got all the cliff notes from the last session welcome rinse and repeat yeah yeah we're going to go under the hood a little bit I think they nailed the what we've been reporting and we've been having this conversation around networking is where the action is because that's the end of the day you got a move a pack from A to B and you get workloads exchanging data so it's really killer so let's get started Amit what are you seeing as the journey of multi cloud as you go under the hood and say okay I got to implement this I have to engineer the network make it enabling make it programmable make it interoperable across clouds I mean that's like I mean almost sounds impossible to me what's your take yeah I mean it's it seems impossible but if you are running an organization which is running infrastructure as a cordon all right it is easily doable like you can use tools out there that's available today you can use third-party products that can do a better job but but put your architecture first don't wait architecture may not be perfect put the best architecture that's available today and be agile to ET rate and make improvements over the time we got to Justin's over here so I have to be careful when I point a question adjusting they both have to answer okay journeys what's the journey been like I mean is there phases we heard that from Gardner people come into multi cloud and cloud native networking from different perspectives what's your take on the journey Justin yeah I mean from Mars like - we started out very much focused on one cloud and as we started doing errands we started doing new products the market the need for multi cloud comes very apparent very quickly for us and so you know having an architecture that we can plug in play into and be able to add and change things as it changes is super important for what we're doing in the space just in your journey yes for us we were very ad hoc oriented and the idea is that we were reinventing all the time trying to move into these new things and coming up with great new ideas and so rather than it being some iterative approach with our deployments that became a number of different deployments and so we shifted that tour and the network has been a real enabler of this is that it there's one network and it touches whatever cloud we want it to touch and it touches the data centers that we need it to touch and it touches the customers that we need it to touch our job is to make sure that the services that are of and one of those locations are available in all of the locations so the idea is not that we need to come up with this new solution every time it's that we're just iterating on what we've already decided to do before we get the architecture section I want to ask you guys a question I'm a big fan of you know let the app developers have infrastructure as code so check but having the right cloud run that workload I'm a big fan of that if it works great but we just heard from the other panel you can't change the network so I want to get your thoughts what is cloud native networking and is that the engine really that's the enabler for this multi cloud trend but you guys taken we'll start with Amit what do you think about that yeah so you are gonna have workloads running in different clouds and the workloads would have affinity to one cloud over other but how you expose that it's matter of how you are going to build your networks how we are going to run security how we are going to do egress ingress out of it so it's the big problem how do you split says what's the solution what's the end the key pain points and problem statement I mean the key pain point for most companies is how do you take your traditional on-premise network and then blow that out to the cloud in a way that makes sense you know IP conflicts you have IP space you pub public eye peas and premise as well as in the cloud and how do you kind of make them a sense of all of that and I think that's where tools like aviatrix make a lot of sense in that space from our site it's it's really simple it's latency and bandwidth and availability these don't change whether we're talking about cloud or data center or even corporate IT networking so our job when when these all of these things are simplified into like s3 for instance and our developers want to use those we have to be able to deliver that and for a particular group or another group that wants to use just just GCP resources these aren't we have to support these requirements and these wants as opposed to saying hey that's not a good idea now our job is to enable them not to disable them do you think you guys think infrastructure as code which I love that I think it's that's the future it is we saw that with DevOps but I just start getting the networking is it getting down to the network portion where it's network as code because storage and compute working really well is seeing all kubernetes on ServiceMaster and network is code reality is it there is it still got work to do it's absolutely there I mean you mentioned net DevOps and it's it's very real I mean in Cooper we build our networks through terraform and on not only just out of fun build an API so that we can consistently build V nets and VPC all across in the same way we get to do it yeah and even security groups and then on top and aviatrix comes in we can peer the networks bridge bridge all the different regions through code same with you guys but yeah about this everything we deploy is done with automation and then we also run things like lambda on top to make changes in real time we don't make manual changes on our network in the data center funny enough it's still manual but the cloud has enabled us to move into this automation mindset and and all my guys that's what they focus on is bringing what now what they're doing in the cloud into the data center which is kind of opposite of what it should be that's full or what it used to be it's full DevOps then yes yeah I mean for us it was similar on premise still somewhat very manual although we're moving more Norton ninja and terraform concepts but everything in the production environment is colored confirmation terraform code and now coming into the datacenter same I just wanted to jump in on a Justin Smith one of the comment that you made because it's something that we always talk about a lot is that the center of gravity of architecture used to be an on-prem and now it's shifted in the cloud and once you have your strategic architecture what you--what do you do you push that everywhere so what you used to see at the beginning of cloud was pushing the architecture on prem into cloud now i want to pick up on what you said to you others agree that the center of architect of gravity is here i'm now pushing what i do in the cloud back into on Prem and wait and then so first that and then also in the journey where are you at from zero to a hundred of actually in the journey to cloud do you 50% there are you 10% yes I mean are you evacuating data centers next year I mean were you guys at yeah so there's there's two types of gravity that you typically are dealing with no migration first is data gravity and your data set and where that data lives and then the second is the network platform that interrupts all that together right in our case the data gravity sold mostly on Prem but our network is now extend out to the app tier that's going to be in cloud right eventually that data gravity will also move to cloud as we start getting more sophisticated but you know in our journey we're about halfway there about halfway through the process we're taking a handle of you know lift and shift and when did that start and we started about three years ago okay okay go by it's a very different story it started from a garage and one hundred percent on the clock it's a business spend management platform as a software-as-a-service one hundred percent on the cloud it was like ten years ago right yes yeah you guys are riding the wave love that architecture Justin I want to ask you Sora you guys mentioned DevOps I mean obviously we saw the huge observability wave which is essentially network management for the cloud in my opinion right yeah it's more dynamic but this is about visibility we heard from the last panel you don't know what's being turned on or turned off from a services standpoint at any given time how is all this playing out when you start getting into the DevOps down well this layer this is the big challenge for all of us as visibility when you talk transport within a cloud you know we very interestingly we have moved from having a backbone that we bought that we owned that would be data center connectivity we now I work for soar as a subscription billing company so we want to support the subscription mindset so rather than going and buying circuits and having to wait three months to install and then coming up with some way to get things connected and resiliency and redundancy I my backbone is in the cloud I use the cloud providers interconnections between regions to transport data across and and so if you do that with their native solutions you you do lose visibility there there are areas in that that you don't get which is why controlling you know controllers and having some type of management plane is a requirement for us to do what we're supposed to do and provide consistency while doing it a great conversation I loved when you said earlier latency bandwidth availability with your sim pop3 things guys SLA I mean you just do ping times are between clouds it's like you don't know what you're getting for round-trip times this becomes a huge kind of risk management black hole whatever you want to call blind spot how are you guys looking at the interconnects between clouds because you know I can see that working from you know ground to cloud I'm per cloud but when you start doing with multi clouds workloads I mean s LA's will be all over the map won't they just inherently but how do you guys view that yeah I think we talked about workload and we know that the workloads are going to be different in different clouds but they are going to be calling each other so it's very important to have that visibility that you can see how data is flowing at what latency and whatever ability is our is there and our authority needs to operate on that so it's so you use the software dashboard look at the times and look at the latency in the old days strong so on open so on you try to figure it out and then your days you have to figure out just what she reinsert that because you're in the middle of it yeah I mean I think the the key thing there is that we have to plan for that failure we have to plan for that latency in our applications that start thinking start tracking in your SLI something you start planning for and you loosely couple these services and a much more micro services approach so you actually can handle that kind of failure or that type of unknown latency and unfortunately the cloud has made us much better at handling exceptions a much better way you guys are all great examples of cloud native from day one and you guys had when did you have the tipping point moment or the Epiphany of saying a multi clouds real I can't ignore it I got to factor it into all my design design principles and and everything you're doing what's it was there a moment was it was it from day one no there were two reasons one was the business so in business there was some affinity to not be in one cloud or to be in one cloud and that drove from the business side so as a cloud architect our responsibility was to support that business and other is the technology some things are really running better in like if you are running dot Network load or you are going to run machine learning or AI so that you have you would have that reference of one cloud over other so it was the bill that we got from AWS I mean that's that's what drives a lot of these conversations is the financial viability of what you're building on top of it which is so we this failure domain idea which is which is fairly interesting is how do I solve or guarantee against a failure domain you have methodologies with you know back-end direct connects or interconnect with GCP all of these ideas are something that you have to take into account but that transport layer should not matter to whoever we're building this for our job is to deliver the frames in the packets what that flows across how you get there we want to make that seamless and so whether it's a public internet API call or it's a back-end connectivity through Direct Connect it doesn't matter it just has to meet a contract that you signed with your application folks yeah that's the availability piece just in your thoughts on anything any common uh so actually a multi clouds become something much more recent in the last six to eight months I'd say we always kind of had a very much an attitude of like moving to Amazon from our private cloud is hard enough why complicate it further but the realities of the business and as we start seeing you know improvements in Google and Asia and different technology spaces the need for multi cloud becomes much more important as well as our acquisition strategies I matured we're seeing that companies that used to be on premise that we typically acquire are now very much already on a cloud and if they're on a cloud I need to plug them into our ecosystem and so that's really change our multi cloud story in a big way I'd love to get your thoughts on the clouds versus the clouds because you know you compare them Amazon's got more features they're rich with features I see the bills are how could people using them but Google's got a great network Google's networks pretty damn good and then you got a sure what's the difference between the clouds who with they've evolved something whether they peak in certain areas better than others what what are the characteristics which makes one cloud better do they have a unique feature that makes as you're better than Google and vice versa what do you guys think about the different clouds yeah to my experience I think there is approaches different in many places Google has a different approach very DevOps friendly and you can run your workload like the your network and spend regions time I mean but our application ready to accept that MS one is evolving I mean I remember 10 years back Amazon's Network was a flat network we will be launching servers and 10.0.0.0 so the VP sees concept came out multi-account came out so they are evolving as you are at a late start but because they have a late start they saw the pattern and they they have some mature set up on the yeah I think they're all trying to say they're equal in their own ways I think they all have very specific design philosophies that allow them to be successful in different ways and you have to kind of keep that in mind as you architectural solution for example amazon has a very much a very regional affinity they don't like to go cross region in their architecture whereas Google is very much it's a global network we're gonna think about as a global solution I think Google also has advantages its third to market and so has seen what Asia did wrong it seemed with AWS did wrong and it's made those improvements and I think that's one of their big advantage at great scale to Justin thoughts on the cloud so yeah Amazon built from the system up and Google built from the network down so their ideas and approaches are from a global versus or regional I agree with you completely that that is the big number one thing but the if you look at it from the outset interestingly the inability or the ability for Amazon to limit layer 2 broadcasting and and what that really means from a VPC perspective changed all the routing protocols you can use all the things that we have built inside of a data center to provide resiliency and and and make things seamless to users all of that disappeared and so because we had to accept that at the VPC level now we have to accept it at the LAN level Google's done a better job of being able to overcome those things and provide those traditional Network facilities to us just great panel can go all day here's awesome so I heard we could we'll get to the cloud native naive questions so kind of think about what's not even what's cloud is that next but I got to ask you had a conversation with a friend he's like Wayne is the new land so if you think about what the land was at a datacenter when is the new link you could talking about the cloud impact so that means st when the old st way is kind of changing into the new land how do you guys look at that because if you think about it what lands were for inside a premises was all about networking high-speed but now when you take the win and make it essentially a land do you agree with that and how do you view this trend and is it good or bad or is it ugly and what's what you guys take on this yeah I think it's a it's a thing that you have to work with your application architect so if you are managing networks and if you are a sorry engineer you need to work with them to expose the unreliability that would bring in so the application has to hand a lot of this the difference in the latencies and and the reliability has to be worked through the application there Lanois same concept is that BS I think we've been talking about for a long time the erosion of the edge and so is this is just a continuation of that journey we've been on for the last several years as we get more and more cloud native and we start about API is the ability to lock my data in place and not be able to access it really goes away and so I think this is just continuation that thing I think it has challenges we start talking about weighing scale versus land scale the tooling doesn't work the same the scale of that tooling is much larger and the need to automation is much much higher in a way and than it was in a land that's where is what you're seeing so much infrastructure as code yeah yes so for me I'll go back again to this its bandwidth and its latency right that bet define those two land versus win but the other thing that's comes up more and more with cloud deployments is where is our security boundary and where can I extend this secure aware appliance or set of rules to to protect what's inside of it so for us we're able to deliver vr af-s or route forwarding tables for different segments wherever we're at in the world and so they're they're trusted to talk to each other but if they're gonna go to someplace that's outside of their their network then they have to cross a security boundary and where we enforce policy very heavily so for me there's it's not just land when it's it's how does environment get to environment more importantly that's a great point and security we haven't talked to yet but that's got to be baked in from the beginning this architecture thoughts on security are you guys are dealing with it yeah start from the base have apt to have security built in have TLS have encryption on the data I transit data at rest but as you bring the application to the cloud and they are going to go multi-cloud talking to over the Internet in some places well have apt web security I mean I mean our principles day Security's day zero every day and so we we always build it into our design build into our architecture into our applications it's encrypt everything it's TLS everywhere it's make sure that that data is secured at all times yeah one of the cool trends at RSA just as a side note was the data in use encryption piece which is a homomorphic stuff is interesting all right guys final question you know we heard on the earlier panel was also trending at reinvent we take the tea out of cloud native it spells cloud naive okay they got shirts now aviatrix kind of got this trend going what does that mean to be naive so if you're to your peers out there watching a live stream and also the suppliers that are trying to supply you guys with technology and services what's naive look like and what's native look like when is someone naive about implementing all this stuff so for me it's because we are in hundred-percent cloud for us it's main thing is ready for the change and you will you will find new building blocks coming in and the network design will evolve and change so don't be naive and think that it's static you wall with the change I think the big naivety that people have is that well I've been doing it this way for 20 years and been successful it's going to be successful in cloud the reality is that's not the case you have to think some of the stuff a little bit differently and you need to think about it early enough so that you can become cloud native and really enable your business on cloud yeah for me it's it's being open minded right the the our industry the network industry as a whole has been very much I am smarter than everybody else and we're gonna tell everybody how it's going to be done and we had we fell into a lull when it came to producing infrastructure and and and so embracing this idea that we can deploy a new solution or a new environment in minutes as opposed to hours or weeks or four months in some cases is really important and and so you know it's are you being closed-minded native being open minded exactly and and it took a for me it was that was a transformative kind of where I was looking to solve problems in a cloud way as opposed to looking to solve problems in this traditional old-school way all right I know we're out of time but I ask one more question so you guys so good it could be a quick answer what's the BS language when you the BS meter goes off when people talk to you about solutions what's the kind of jargon that you hear that's the BS meter going off what are people talking about that in your opinion you here you go that's total BS but what triggers use it so that I have two lines out of movies that are really I can if I say them without actually thinking them it's like 1.21 jigowatts are you out of your mind from Back to the Future right somebody's getting a bang and then and then Martin Mull and and Michael Keaton and mr. mom when he goes to 22 21 whatever it takes yeah those two right there if those go off in my mind somebody's talking to me I know they're full of baloney so a lot of speech would be a lot of speeds and feeds a lot of data did it instead of talking about what you're actually doing and solutioning for you're talking about well I does this this this and any time I start seeing the cloud vendor start benchmarking against each other it's your workload is your workload you need to benchmark yourself don't don't listen to the marketing on that that's that's all what triggers you and the bsp I think if somebody explains you and not simple they cannot explain you in simplicity then that's good all right guys thanks for the great insight great time how about a round of applause DX easy solutions integrating company than we service customers from all industry verticals and we're helping them to move to the digital world so as a solutions integrator we interface with many many customers that have many different types of needs and they're on their IT journey to modernize their applications into the cloud so we encounter many different scenarios many different reasons for those migrations all of them seeking to optimize their IT solutions to better enable their business we have our CPS organization it's cloud platform services we support AWS does your Google Alibaba corkle will help move those workloads to wherever it's most appropriate no one buys the house for the plumbing equally no one buys the solution for the networking but if the plumbing doesn't work no one likes the house and if this network doesn't work no one likes a solution so network is ubiquitous it is a key component of every solution we do the network connectivity is the lifeblood of any architecture without network connectivity nothing works properly planning and building a scalable robust network that's gonna be able to adapt with the application needs critical when encountering some network design and talking about speed the deployment aviatrix came up in discussion and we then further pursued an area DHT products have incorporated aviatrix is part of a new offering that we are in the process of developing that really enhances our ability to provide cloud connectivity for the Lyons cloud connectivity is a new line of networking services so we're getting into as our clients moving the hybrid cloud networking it is much different than our traditional based services and aviatrix provides a key component in that service before we found aviatrix we were using just native peering connections but there wasn't a way to visualize all those peering connections and with multiple accounts multiple contacts for security with a VA Church were able to visualize those different peering connections of security groups it helped a lot especially in areas of early deployment scenarios were quickly able to then take those deployment scenarios and turn them into scripts that we can then deploy repeatedly their solutions were designed to work with the cloud native capabilities first and where those cloud native capabilities fall short they then have solution sets that augment those capabilities I was pleasantly surprised number one with the aviatrix team as a whole and their level of engagement with us you know we weren't only buying the product we were buying a team that came on board to help us implement and solution that was really good to work together to learn both what aviatrix had to offer as well as enhancements that we had to bring that aviatrix was able to put into their product and meet our needs even better aviatrix was a joy to find because they really provided us the technology that we needed in order to provide multi cloud connectivity that really added to the functionality that you can't get from the basically providing services we're taking our customers on a journey to simplify and optimize their IT maybe Atrix certainly has made my job much easier okay welcome back to altitude 2020 for the digital event for the live feed welcome back I'm John Ford with the cube with Steve Mulaney CEO aviatrix for the next panel from global system integrators the folks who are building and working with folks on their journey to multi cloud and cloud native networking we've got a great panel George Buckman with dxc and Derek Monahan with wwt welcome to the stage [Applause] [Music] okay you guys are the ones out there advising building and getting down and dirty with multi cloud and cloud native network and we just heard from the customer panel you can see the diversity of where people come in to the journey of cloud it kind of depends upon where you are but the trends are all clear cloud native networking DevOps up and down the stack this has been the main engine what's your guys take of the disk Jerry to multi cloud what do you guys seeing yeah it's it's critical I mean we're seeing all of our enterprise customers enter into this they've been through the migrations of the easy stuff you know now they're trying to optimize and get more improvement so now the tough stuffs coming on right and you know they need their data processing near where their data is so that's driving them to a multi cloud environment okay we heard some of the edge stuff I mean you guys are exactly you've seen this movie before but now it's a whole new ballgame what's your take yeah so I'll give you a hint so our practice it's not called the cloud practice it's the multi cloud practice and so if that gives you a hint of how we approach things it's very consultative and so when we look at what the trends are let's look a little year ago about a year ago we're having conversations with customers let's build a data center in the cloud let's put some VP C's let's throw some firewalls with some DNS and other infrastructure out there and let's hope it works this isn't a science project so what we're trying to see is customers are starting to have more of a vision and we're helping with that consultative nature but it's totally based on the business and you got to start understanding how the lines of business are using the and then we evolved into the next journey which is a foundational approach to what are some of the problem statement customers are solving when they come to you what are the top things that are on their my house or the ease of use of Julie all that stuff but what specifically they digging into yeah so complexity I think when you look at a multi cloud approach in my view is network requirements are complex you know I think they are but I think the approach can be let's simplify that so one thing that we try to do this is how we talk to customers is let's just like you simplify an aviatrix simplifies the automation orchestration of cloud networking we're trying to simplify the design the planning implementation of infrastructure across multiple workloads across multiple platforms and so the way we do it is we sit down we look at not just use cases and not just the questions in common we tis anticipate we actually build out based on the business and function requirements we build out a strategy and then create a set of documents and guess what we actually build in the lab and that lab that we platform we built proves out this reference architecture actually works absolutely we implement similar concepts I mean we they're proven practices they work great so well George you mentioned that the hard part's now upon us are you referring to networking what is specifically were you getting at Terrance's the easy parts done now so for the enterprises themselves migrating their more critical apps or more difficult apps into the environments you know they've just we've just scratched the surface I believe on what enterprises are doing to move into the cloud to optimize their environments to take advantage of the scale and speed to deployment and to be able to better enable their businesses so they're just now really starting the - so do you get you guys see what I talked about them in terms of their Cambrian explosion I mean you're both monster system integrators with you know top fortune enterprise customers you know really rely on you for for guidance and consulting and so forth and boy they're networks is that something that you you've seen I mean does that resonate did you notice a year and a half ago and all of a sudden the importance of cloud for enterprise shoot up yeah I mean we're seeing it not okay in our internal environment as you know we're a huge company or as customers so we're experiencing that internal okay and every one of our other customers so I have another question oh but I don't know the answer to this and the lawyer never asks a question that you don't know the answer to but I'm gonna ask it anyway DX c + w WT massive system integrators why aviatrix yep so great question Steve so I think the way we approach things I think we have a similar vision a similar strategy how you approach things how we approach things that world by technology number one we want to simplify the complexity and so that's your number one priorities let's take the networking let's simplify it and I think part of the other point I'm making is we have we see this automation piece as not just an afterthought anymore if you look at what customers care about visibility and automation is probably the top three maybe the third on the list and I think that's where we see the value and I think the partnership that we're building and what I would I get excited about is not just putting yours in our lab and showing customers how it works is Co developing a solution with you figuring out hey how can we make this better right visibility's a huge thing jump in security alone network everything's around visibility what automation do you see happening in terms of progression order of operations if you will it's a low-hanging fruit what are people working on now what are what are some of the aspirational goals around when you start thinking about multi cloud and automation yep so I wanted to get back to answer that question I want to answer your question you know what led us there and why aviatrix you know in working some large internal IT projects and and looking at how we were gonna integrate those solutions you know we like to build everything with recipes where network is probably playing catch-up in the DevOps world but with a DevOps mindset looking to speed to deploy support all those things so when you start building your recipes you take a little of this a little of that and you mix it all together well when you look around you say wow look there's this big bag of a VHS let me plop that in that solves a big part of my problems that I have to speed to integrate speed to deploy and the operational views that I need to run this so that was 11 years about reference architectures yeah absolutely so you know they came with a full slate of reference textures already the out there and ready to go that fit our needs so it's very very easy for us to integrate those into our recipes what do you guys think about all the multi vendor interoperability conversations that have been going on choice has been a big part of multi-cloud in terms of you know customers want choice they didn't you know they'll put a workload in the cloud that works but this notion of choice and interoperability is become a big conversation it is and I think our approach and that's why we talk to customers is let's let's speed and be risk of that decision making process and how do we do that because the interoperability is key you're not just putting it's not just a single vendor we're talking you know many many vendors I mean think about the average number of cloud application as a customer uses a business and enterprise business today you know it's it's above 30 it's it's skyrocketing and so what we do and we look at it from an interoperability approach is how do things interoperate we test it out we validate it we build a reference architecture it says these are the critical design elements now let's build one with aviatrix and show how this works with aviatrix and I think the the important part there though is the automation piece that we add to it in visibility so I think the visibility is what's what I see lacking across the industry today and the cloud needed that's been a big topic okay in terms of aviatrix as you guys see them coming in they're one of the ones that are emerging and the new brands emerging but multi-cloud you still got the old guard incumbents with huge footprints how our customers dealing with that that kind of component and dealing with both of them yeah I mean where we have customers that are ingrained with a particular vendor and you know we have partnerships with many vendors so our objective is to provide the solution that meets that client and you they all want multi vendor they all want interoperability correct all right so I got to ask you guys a question while we were defining day two operations what does that mean I mean you guys are looking at the big business and technical components of architecture what does day to Operations mean what's the definition of that yeah so I think from our perspective my experience we you know day to operations whether it's it's not just the you know the orchestration piece and setting up and let it a lot of automate and have some you know change control you're looking at this from a data perspective how do I support this ongoing and make it easy to make changes as we evolve the the the cloud is very dynamic the the nature of how the fast is expanding the number of features is astonish trying to keep up to date with a number of just networking capabilities and services that are added so I think day to operation starts with a fundable understanding of you know building out supporting a customer's environments and making it the automation piece easy from from you know a distance I think yeah and you know taking that to the next level of being able to enable customers to have catalog items that they can pick and choose hey I need this network connectivity from this cloud location back to this on pram and being able to have that automated and provisioned just simply by ordering it for the folks watching out there guys take a minute to explain as you guys are in the trenches doing a lot of good work what are some of the engagement that you guys get into how does that progress what is that what's what happens do they call you up and say hey I need some multi-cloud or you're already in there I mean take us through why how someone can engage to use a global si to come in and make this thing happen what's looks like typical engagement look like yeah so from our perspective we typically have a series of workshops in a methodology that we kind of go along the journey number one we have a foundational approach and I don't mean foundation meaning the network foundation that's a very critical element we got a factor in security we've got a factor in automation so we think about foundation we do a workshop that starts with education a lot of times we'll go in and we'll just educate the customer what is VP she's sharing you know what is a private Lincoln or how does that impact your business we have customers I want to share services out in an ecosystem with other customers and partners well there's many ways to accomplish that so our goal is to you know understand those requirements and then build that strategy with them thoughts Georgia yeah I mean I'm one of the guys that's down in the weeds making things happen so I'm not the guy on the front line interfacing with the customers every day but we have a similar approach you know we have a consulting practice that will go out and and apply their practices to see what those and when do you parachute in yeah and when I then is I'm on the back end working with our offering development leads for the networking so we understand or seeing what customers are asking for and we're on the back end developing the solutions that integrate with our own offerings as well as enable other customers to just deploy quickly to beep their connectivity needs it so the patterns are similar right final question for you guys I want to ask you to paint a picture of what success looks like and you know the name customers didn't forget in reveal kind of who they are but what does success look like in multi-cloud as you paint a picture for the folks here and watching on the live stream it's someone says hey I want to be multi-cloud I got to have my operations agile I want full DevOps I want programmability security built in from day zero what does success look like yeah I think success looks like this so when you're building out a network the network is a harder thing to change than some other aspects of cloud so what we think is even if you're thinking about that second cloud which we have most of our customers are on to public clouds today they might be dabbling in that as you build that network foundation that architecture that takes in consideration where you're going and so once we start building that reference architecture out that shows this is how to sit from a multi cloud perspective not a single cloud and let's not forget our branches let's not forget our data centers let's not forget how all this connects together because that's how we define multi-cloud it's not just in the cloud it's on Prem and it's off from and so collectively I think the key is also is that we provide them an hld you got to start with a high level design that can be tweaked as you go through the journey but you got to give a solid structural foundation and that that networking which we think most customers think as not not the network engineers but as an afterthought we want to make that the most critical element before you start the journey Jorge from your seed how do you success look for you so you know it starts out on these journeys often start out people not even thinking about what is gonna happen what what their network needs are when they start their migration journey to the cloud so I want this success to me looks like them being able to end up not worrying about what's happening in the network when they move to the cloud good point guys great insight thanks for coming on share and pen I've got a round of applause the global system integrators Hey [Applause] [Music] okay welcome back from the live feed I'm chef for with the cube Steve Eleni CEO of aviatrix my co-host our next panel is the aviatrix certified engineers also known as aces this is the folks that are certified their engineering they're building these new solutions please welcome Toby Foster min from Attica Stacy linear from Teradata and Jennifer Reid with Victor Davis to the stage I was just gonna I was just gonna rip you guys see where's your jackets and Jen's got the jacket on okay good love the aviatrix aces pile of gear they're above the clouds towards a new heights that's right so guys aviatrix aces love the name I think it's great certified this is all about getting things engineered so there's a level of certification I want to get into that but first take us through the day in the life of an ace and just to point out Stacey's a squad leader so he's like a Squadron Leader Roger and leader yeah Squadron Leader so he's got a bunch of aces underneath him but share your perspective day-in-the-life Jennifer will start with you sure so I have actually a whole team that works for me both in the in the North America both in the US and in Mexico and so I'm eagerly working to get them certified as well so I can become a squad leader myself but it's important because one of the the critical gaps that we've found is people having the networking background because they're you graduate from college and you have a lot of computer science background you can program you've got Python but now working in packets they just don't get and so just taking them through all the processes that it's really necessary to understand when you're troubleshooting is really critical mm-hmm and because you're gonna get an issue where you need to figure out where exactly is that happening on the network you know is my my issue just in the VP C's and on the instance side is a security group or is it going on print and this is something actually embedded within Amazon itself I mean I should troubleshot an issue for about six months going back and forth with Amazon and it was the vgw VPN because they were auto-scaling on two sides and we ended up having to pull out the Cisco's and put in aviatrix so I could just say okay it's fixed and I actually actually helped the application teams get to that and get it solved yeah but I'm taking a lot of junior people and getting them through that certification process so they can understand and see the network the way I see the network I mean look I've been doing this for 25 years when I got out when I went in the Marine Corps that's what I did and coming out the network is still the network but people don't get the same training they get they got in the 90s it's just so easy just write some software they work takes care of itself yes he'll be we'll come back to that I want to come back to that problem solve with Amazon but Toby I think the only thing I have to add to that is that it's always the network fault as long as I've been in network have always been the network's fault sure and I'm even to this day you know it's still the network's fault and part of being a network guy is that you need to prove when it is and when it's not your fault and that means you need to know a little bit about a hundred different things to make that and now you've got a full stack DevOps you got to know a lot more times another hundred and these times are changing they see your squadron leader I get that right what is what is a squadron leader first can you describe what it is I think it probably just leading all the network components of it but are they from my perspective when to think about what you asked them was it's about no issues and no escalation soft my day is like that's a good outcome that's a good day it's a good day Jennifer you mentioned the Amazon thing this brings up a good point you know when you have these new waves come in you have a lot of new things newly use cases a lot of the finger-pointing it's that guys problem that girls problem so what is how do you solve that and how do you get the young guns up to speed is there training is that this is where the certification comes in those where the certification is really going to come in I know when we we got together at reinvent one of the the questions that that we had with Stephen the team was what what should our certification look like you know she would just be teaching about what aviatrix troubleshooting brings to bear but what should that be like and I think Toby and I were like no no no that's going a little too high we need to get really low because the the better someone can get at actually understanding what actually happening in the network and and where to actually troubleshoot the problem how to step back each of those processes because without that it's just a big black box and they don't know you know because everything is abstracted in Amazon Internet and Azure and Google is substracted and they have these virtual gateways they have VPNs that you just don't have the logs on it's you just don't know and so then what tools can you put in front of them of where they can look because there are full logs well as long as they turned on the flow logs when they built it you know and there's like each one of those little things that well if they'd had decided to do that when they built it it's there but if you can come in later to really supplement that with training to actual troubleshoot and do a packet capture here as it's going through then teaching them how to read that even yeah Toby we were talking before he came on up on stage about your career you've been networking all your time and then you know you're now mentoring a lot of younger people how is that going because the people who come in fresh they don't have all the old war stories they don't know you talk about you know that's dimmer fault I walk in Mayr feet in the snow when I was your age I mean it's so easy now right they say what's your take on how you train the young P so I've noticed two things one is that they are up to speed a lot faster in generalities of networking they can tell you what a network is in high school level now where I didn't learn that too midway through my career and they're learning it faster but they don't necessarily understand why it's that way or you know everybody thinks that it's always slash 24 for a subnet and they don't understand why you can break it down smaller why it's really necessary so the the ramp up speed is much faster for these guys that are coming in but they don't understand why and they need some of that background knowledge to see where it's coming from and why is it important and that's old guys that's where we thrive Jennifer you mentioned you you got in from the Marines health spa when you got into networking how what was it like then and compare it now most like we've heard earlier static versus dynamic don't be static cuz back then you just said the network you got a perimeter yeah no there was no such thing ya know so back in the day I mean I mean we had banyan vines for email and you know we had token ring and I had to set up token ring networks and figure out why that didn't work because how many of things were actually sharing it but then actually just cutting fiber and running fiber cables and dropping them over you know shelters to plug them in and oh crap they swung it too hard and shattered it now I gotta be great polished this thing and actually shoot like to see if it works I mean that was the network current five cat 5 cables to run an Ethernet you know and then from that just said network switches dumb switches like those were the most common ones you had then actually configuring routers and you know logging into a Cisco router and actually knowing how to configure that and it was funny because I had gone all the way up and was a software product manager for a while so I've gone all the way up the stack and then two and a half three years ago I came across to to work with entity group that became Victor Davis but we went to help one of our customers Avis and it was like okay so we need to fix the network okay I haven't done this in 20 years but all right let's get to it you know because it really fundamentally does not change it's still the network I mean I've had people tell me well you know when we go to containers we will not have to worry about the network and I'm like yeah you don't I do and then with this within the program abilities it really interesting so I think this brings up the certification what are some of the new things that people should be aware of that come in with the aviatrix ace certification what are some of the highlights can you guys share some of the some of the highlights around the certifications I think some of the importance is that it's it doesn't need to be vendor specific for network generality or basic networking knowledge and instead of learning how Cisco does something or how Palo Alto does something we need to understand how and why it works as a basic model and then understand how each vendor has gone about that problem and solved it in a general that's true in multi cloud as well you can't learn how cloud networking works without understanding how AWS integer and GCP are all slightly the same but slightly different and some things work and some things don't I think that's probably the number one take I think having a certification across clouds is really valuable because we heard the global si you help the business issues what does it mean to do that is it code is that networking is it configuration is that aviatrix what is the amine oxy aviatrix is a certification but what is it about the multi cloud that makes it multi networking and multi vendor and easy answer is yes so you got to be a general let's go to your hands and all you have to be it takes experience because it's every every cloud vendor has their own certification whether that's hops and [Music] advanced networking and advanced security or whatever it might be yeah they can take the test but they have no idea how to figure out what's wrong with that system and the same thing with any certification but it's really getting your hands in there and actually having to troubleshoot the problems you know actually work the problem you know and calm down it's going to be okay I mean because I don't know how many calls I've been on or even had aviatrix join me on it's like okay so everyone calm down let's figure out what's happening it's like we've looked at that screen three times looking at it again it's not going to solve that problem right but at the same time you know remaining calm but knowing that it really is I'm getting a packet from here to go over here it's not working so what could be the problem you know and actually stepping them through those scenarios but that's like you only get that by having to do it you know and seeing it and going through it and then I have a question so we you know I just see it we started this program maybe six months ago we're seeing a huge amount of interest I mean we're oversubscribed on all the training sessions we've got people flying from around the country even with coronavirus flying to go to Seattle to go to these events were oversubscribed a good is that watching leader would put there yeah something that you see in your organizations are you recommending that to people do you see I mean I'm just I would guess I'm surprised I'm not surprised but I'm really surprised by the demand if you would of this multi-cloud network certification because it really isn't anything like that is that something you guys can comment on or do you see the same things in your organization's I say from my side because we operate in the multi cloud environment so it really helps an official for us I think I would add that networking guys have always needed to use certifications to prove that they know what they know it's not good enough to say yeah I know IP addresses or I know how a network works and a couple little check marks or a little letters buying helps give you validity so even in our team we can say hey you know we're using these certifications to know that you know enough of the basics enough of the understandings that you have the tools necessary right so okay I guess my final question for you guys is why an eighth certification is relevant and then second part is share what the livestream folks who aren't yet a certified or might want to jump in to be AVH or certified engineers why is it important so why is it relevant and why shouldn't someone want to be an ace-certified I'm used to right engineer I think my views a little different I think certification comes from proving that you have the knowledge not proving that you get a certification to get no I mean they're backwards so when you've got the training and the understanding and the you use that to prove and you can like grow your certification list with it versus studying for a test to get a certification and have no understanding it okay so that who is the right person that look at this is saying I'm qualified is it a network engineer is it a DevOps person what's your view you know is it a certain you know I think cloud is really the answer it's the as we talked like the edge is getting eroded so is the network definition getting eroded we're getting more and more of some network some DevOps some security lots and lots of security because network is so involved in so many of them that's just the next progression I don't say I expend that to more automation engineers because we have those nails probably well I think that the training classes themselves are helpful especially the entry-level ones for people who may be quote-unquote cloud architects but I've never done anything and networking for them to understand why we need those things to really work whether or not they go through to eventually get a certification is something different but I really think fundamentally understanding how these things work it makes them a better architect makes some better application developer but even more so as you deploy more of your applications into the cloud really getting an understanding even from our people who've tradition down on prime networking they can understand how that's going to work in the cloud too well I know we got just under 30 seconds left but I want to get one more question than just one more for the folks watching that are you may be younger that don't have that networking training from your experiences each of you can answer why is it should they know about networking what's the benefit what's in it for them motivate them share some insights and why they should go a little bit deeper in networking Stacey we'll start with you we'll go down let's say it's probably fundamental right if you want to deliver solutions no we're going use the very top I would say if you fundamental of an operating system running on a machine how those machines talk together as a fundamental change is something that starts from the base and work your way up right well I think it's a challenge because you've come from top-down now you're gonna start looking from bottom up and you want those different systems to cross communicate and say you've built something and you're overlapping IP space not that that doesn't happen but how can I actually make that still operate without having to reappear e-platform it's like those challenges like those younger developers or sis engineers can really start to get their hands around and understand those complexities and bring that forward in their career they got to know the how the pipes are working you guys know what's going some plumbing that's right and they gotta know how it works I had a code it it's right awesome thank you guys for great insights ace certain ABS your certified engineers also known as aces give a round of applause thank you okay all right that concludes my portion thank you Steve thanks for have Don thank you very much that was fantastic everybody round of applause for John for you yeah so great event great event I'm not gonna take long we got we've got lunch outside for that for the people here just a couple of things just call to action right so we saw the aces you know for those of you out on the stream here become a certified right it's great for your career it's great for not knowledge is is fantastic it's not just an aviatrix thing it's gonna teach you about cloud networking multi-cloud networking with a little bit of aviatrix exactly what the Cisco CCIE program was for IP network that type of the thing that's number one second thing is is is is learn right so so there's a there's a link up there for the four to join the community again like I started this this is a community this is the kickoff to this community and it's a movement so go to what a v8 community aviatrix comm starting a community a multi cloud so you know get get trained learn I'd say the next thing is we're doing over a hundred seminars in across the United States and also starting into Europe soon will come out and will actually spend a couple hours and talk about architecture and talk about those beginning things for those of you on the you know on the livestream in here as well you know we're coming to a city near you go to one of those events it's a great way to network with other people that are in the industry as well as to start to learn and get on that multi-cloud journey and then I'd say the last thing is you know we haven't talked a lot about what aviatrix does here and that's intentional we want you you know leaving with wanting to know more and schedule get with us in schedule a multi our architecture workshop session so we we sit out with customers and we talk about where they're at in that journey and more importantly where they're going and define that end state architecture from networking compute storage everything and everything you heard today every panel kept talking about architecture talking about operations those are the types of things that we solve we help you define that canonical architecture that system architecture that's yours so for so many of our customers they have three by five plotted lucid charts architecture drawings and it's the customer name slash aviatrix arc network architecture and they put it on their whiteboard that's what what we and that's the most valuable thing they get from us so this becomes their twenty-year network architecture drawing that they don't do anything without talking to us and look at that architecture that's what we do in these multi hour workshop sessions with customers and that's super super powerful so if you're interested definitely call us and let's schedule that with our team so anyway I just want to thank everybody on the livestream thank everybody here hopefully it was it was very useful I think it was and joined the movement and for those of you here join us for lunch and thank you very much [Applause] [Music] you

[Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] [Music] you you you you [Music] [Music] [Music] [Music] ladies and gentlemen please take your seats good morning ladies and gentlemen this is your captain speaking we will soon be taking off on our way to altitude please keep your seatbelts fastened and remain in your seats we will be experiencing turbulence until we are above the clouds ladies and gentlemen we are now cruising at altitude sit back and enjoy the ride [Music] altitude is a community of thought leaders and pioneers cloud architects and enlightened network engineers who have individually and are now collectively leading their own IT teams and the industry on a path to lift cloud networking above the clouds empowering Enterprise IT to architect design and control their own cloud network regardless of the turbulent clouds beneath them it's time to gain altitude ladies and gentlemen Steve Mulaney president and CEO of aviatrix the leader of multi cloud networking [Music] [Applause] all right good morning everybody here in Santa Clara as well as to the what millions of people watching the livestream worldwide welcome to altitude 2020 alright so we've got a fantastic event today I'm really excited about the speakers that we have today and the experts that we have and really excited to get started so one of the things I wanted to just share was this is not a one-time event it's not a one-time thing that we're gonna do sorry for the aviation analogy but you know sherry way aviatrix means female pilot so everything we do as an aviation theme this is a take-off for a movement this isn't an event this is a takeoff of a movement a multi-cloud networking movement and community that we're inviting all of you to become part of and-and-and why we're doing that is we want to enable enterprises to rise above the clouds so to speak and build their network architecture regardless of which public cloud they're using whether it's one or more of these public clouds so the good news for today there's lots of good news but this is one good news is we don't have any PowerPoint presentations no marketing speak we know that marketing people have their own language we're not using any of that in those sales pitches right so instead what are we doing we're going to have expert panels we've got some owners chart of Gartner here we've got 10 different network architects cloud architects real practitioners they're going to share their best practices and there are real-world experiences on their journey to the multi cloud so before we start and everybody know what today is in the US it's Super Tuesday I'm not gonna get political but Super Tuesday there was a bigger Super Tuesday that happened 18 months ago and maybe eight six employees know what I'm talking about 18 months ago on a Tuesday every Enterprise said I'm gonna go to the cloud and so what that was was the Cambrian explosion for cloud for the price so Franco Bree you know what a Cambrian explosion is he had to look it up on Google 500 million years ago what happened there was an explosion of life where it went from very simple single-cell organisms to very complex multi-celled organisms guess what happened 18 months ago on a Tuesday I don't really know why but every enterprise like I said all woke up that day and said now I'm really gonna go to cloud and that Cambrian explosion of cloud went meant that I'm moving from very simple single cloud single use case simple environment to a very complex multi cloud complex use case environment and what we're here today is we're gonna go and dress that and how do you handle those those those complexities and when you look at what's happening with customers right now this is a business transformation right people like to talk about transitions this is a transformation and it's actually not just the technology transformation it's a business transformation it started from the CEO and the boards of enterprise customers where they said I have an existential threat to the survival of my company if you look at every industry who they're worried about is not the other 30 year old enterprise what they're worried about is the three year old enterprise that's leveraging cloud that's leveraging AI and that's where they fear that they're going to actually get wiped out right and so because of this existential threat this is CEO lead this is board led this is not technology led it is mandated in the organization's we are going to digitally transform our enterprise because of this existential threat and the movement to cloud is going to enable us to go do that and so IT is now put back in charge if you think back just a few years ago in cloud it was led by DevOps it was led by the applications and it was like I said before their Cambrian explosion is very simple now with this Cambrian explosion and enterprises getting very serious and mission-critical they care about visibility they care about control that about compliance conformance everything governance IT is in charge and and and that's why we're here today to discuss that so what we're going to do today is much of things but we're gonna validate this journey with customers did they see the same thing we're going to validate the requirements for multi-cloud because honestly I've never met an enterprise that is not going to be multi-cloud many are one cloud today but they all say I need to architect my network for multiple clouds because that's just what the network is there to support the applications and the applications will run and whatever cloud it runs best in and you have to be prepared for that the second thing is is is architecture again with the IT in charge you architecture matters whether it's your career whether it's how you build your house it doesn't matter horrible architecture your life is horrible forever good architecture your life is pretty good so we're going to talk about architecture and how the most fundamental and critical part of that architecture and that basic infrastructure is the network if you don't get that right nothing works right way more important and compute way more important than storm dense storage network is the foundational element of your infrastructure then we're going to talk about day two operations what does that mean well day 1 is one day of your life who you wire things up they do and beyond I tell everyone in networking and IT it's every day of your life and if you don't get that right your life is bad forever and so things like operations visibility security things like that how do I get my operations team to be able to handle this in an automated way because it's not just about configuring it in the cloud it's actually about how do i operationalize it and that's a huge benefit that we bring as aviatrix and then the last thing we're going to talk and it's the last panel we have I always say you can't forget about the humans right so all this technology all these things that we're doing it's always enabled by the humans at the end of the day if the humans fight it it won't get deployed and we have a massive skills gap in cloud and we also have a massive skill shortage you have everyone in the world trying to hire cloud network architects right there's just not enough of them going around so at aviatrix we as leaders ooh we're gonna help address that issue and try to create more people we created a program and we call the ACE program again an aviation theme it stands for aviatrix certified engineer very similar to what Cisco did with CCI es what Cisco taught you about IP networking a little bit of Cisco we're doing the same thing we're gonna teach network architects about multi-cloud networking and architecture and yeah you'll get a little bit of aviatrix training in there but this is the missing element for people's careers and also within their organization so we're gonna we're gonna go talk about that so great great event great show when to try to keep it moving I'd next want to introduce my my host he's the best in the business you guys have probably seen him multiple million times he's the co CEO and co-founder of joob John Ferrier [Applause] okay awesome great great speech they're awesome I totally agree with everything you said about the explosion happening and I'm excited here at the heart of Silicon Valley to have this event it's a special digital event with the cube and aviatrix where we live streaming to millions of people as you said maybe not a million maybe not really take this program to the world this is a little special for me because multi-cloud is the hottest wave and cloud and cloud native networking is fast becoming the key engine of the innovation so we got an hour and a half of action-packed programming we have a customer panel to customer panels before that Gartner is going to come out and talk about the industry we have a global system integrators they talk about how they're advising and building these networks and cloud native networking and then finally the Aces the aviatrix certified engineer is gonna talk more about their certifications and the expertise needed so let's jump right in and let's ask some own rashard to come on stage from Gartner we'll kick it all up [Applause] [Music] okay so kicking things off certain started gardener the industry experts on cloud really kind of more to your background talk about your background before you got the gardener yeah before because gardener was a chief network architect of a fortune five companies with thousands of sites over the world and I've been doing everything and IT from a C programmer the ninety-two a security architect to a network engineer to finally becoming a network analyst so you rode the wave now you're covering in the marketplace with hybrid cloud and now moving quickly to multi cloud is really was talking about cloud natives been discussed but the networking piece is super important how do you see that evolving well the way we see Enterprise adapt in cloud first thing you do about networking the initial phases they either go in a very ad hoc way is usually led by non non IT like a shadow IT or application people are sometime a DevOps team and it's it just goes as it's completely unplanned decreed VP sees left and right as with different account and they create mesh to manage them and they have direct connect or Express route to any of them so that's what that's a first approach and on the other side again it within our first approach you see what I call the lift and shift way we see like Enterprise IT trying to basically replicate what they have in a data center in the cloud so they spend a lot of time planning doing Direct Connect putting Cisco routers and f5 and Citrix and any checkpoint Palo Alto divides that the atoms that are sent removing that to that cloud they ask you the aha moments gonna come up a lot of our panels is where people realize that it's a multi cloud world I mean they either inherit clouds certainly they're using public cloud and on-premises is now more relevant than ever when's that aha moment that you're seeing where people go well I got to get my act together and get on this well the first but even before multi-cloud so these two approach the first one like the ad hoc way doesn't scale at some point idea has to save them because they don't think about the - they don't think about operations we have a bunch of VPC and multiple clouds the other way that if you do the left and shift week they cannot take any advantages of the cloud they lose elasticity auto-scaling pay by the drink these feature of agility features so they both realize okay neither of these words are good so I have to optimize that so I have to have a mix of what I call the cloud native services within each cloud so they start adapting like other AWS constructor is your construct or Google construct and that's what I call the optimal phase but even that they realize after that they are very different all these approaches different the cloud are different identities is completely difficult to manage across clouds I mean for example AWS as accounts there's subscription and in as ER and GCP their projects it's a real mess so they realize well I can't really like concentrate used the cloud the cloud product and every cloud that doesn't work so I have I'm doing multi cloud I like to abstract all of that still wanna manage the cloud from an epi xx view I don't necessarily want to bring my incumbent data center products but I have to do that in a more API driven cloud they're not they're not scaling piece and you were mentioning that's because there's too many different clouds yes that's the piece there so what are they doing whether they read they building different development teams as its software what's the solution well this the solution is to start architecting the cloud that's the third phase I call that the multi cloud architect phase where they have to think about abstraction that works across cloud fact even across one cloud it might not scale as well if you start having like 10,000 security group in AWS that doesn't scale you have to manage that if you have multiple VPC it doesn't scale you need a third-party identity provider so it barely scales within one cloud if you go multiple cloud it gets worse and worse see way in here what's your thoughts I thought we said this wasn't gonna be a sales pitch for aviatrix you just said exactly what we do so anyway up just a joke what do you see in terms of where people are in that multi cloud like a lot of people you know everyone I talked to started in one cloud right but then they look and they say okay but I'm now gonna move to adjourn I'm gonna move do you see a similar thing well yes they are moving but they're not there's not a lot of application that use a tree cloud at once they move one app in Azure one app in individuals one get app in Google that's what we see so far okay yeah I mean one of the mistakes that people think is they think multi-cloud no one is ever gonna go multi-cloud for arbitrage they're not gonna go and say well today I might go into Azure because I got a better rate of my instance that's never do you agree with that's never gonna happen what I've seen with enterprise is I'm gonna put the work load and the app the app decides where it runs best that may be a sure maybe Google and for different reasons and they're gonna stick there and they're not gonna move let me ask you infrastructure has to be able to support from a networking King be able to do that do you agree with that yes I agree and one thing is also very important is connecting to that cloud is kind of the easiest thing so though while I run network part of the cloud connectivity to the cloud is kind of simple you know I agree IPSec VPN and I reckon Express route that's a simple part what's difficult and even a provisioning part is easy you can use terraform and create v pieces and v nets across which we cloud providers right what's difficult is the day-to-day operations so it's what to find a to operations what is that what does that actually mean it's just the day-to-day operations after you know the natural let's add an app that's not a server let's troubleshoot a problem so what ending so your life if something changes now what do you do so what's the big concerns I want to just get back to this cloud native networking because everyone kind of knows with cloud native apps are that's the hot trend what is cloud native networking how do you how do you guys define that because that seems to be the oddest part of the multi cloud wave that's coming as cloud native networking well there's no you know official gardener definition but I can create one on another spot is do it I just want to leverage the cloud construct and a cloud epi I don't want to have to install like like for example the first version was let's put a virtual router that doesn't understand and then the cloud environment right if I have if I have to install a virtual machine it has to be cloud aware it has to understand the security group if it's a router it has to be programmable to the cloud API and and understand the cloud environment you know one things I hear a lot from either see Saussure CIOs or CXOs in general is this idea of I'm definitely on going API so it's been an API economy so API is key on that point but then they say okay I need to essentially have the right relationship with my suppliers aka clouds you call it above the clouds so the question is what do i do from an architecture standpoint do I just hire more developers and have different teams because you mentioned that's a scale point how do you solve this this problem of okay I got AWS I got GCP or Azure or whatever do I just have different teams or just expose API guys where is that optimization where's the focus well I think what you need from an android point of view is a way a control plane across the three clouds and be able to use the api of that cloud to build networks but also to troubleshoot them and do they to operation so you need a view across a three cloud that takes care of routing connectivity that's you know that's the aviatrix plug of view right there so so how do you see so again your Gartner you you you you see the industry you've been a network architect how do you see this this plan out what are the what are the legacy incumbent client-server on-prem networking people gonna do well these versus people like aviatrix well how do you see that playing out well obviously all the incumbent like Arista cisco juniper NSX right they want to basically do the lift and chip are they want to bring and you know VM I want to bring in a section that cloud they call that NSX everywhere and cisco wants bring you star in the cloud they call that each guy anywhere right so everyone what and and then there's cloud vision for my red star and Khan trailers in a cloud so they just want to bring the management plain in the cloud but it's still based most of them it's still based on putting a VM them in controlling them right you you extend your management console to the cloud that's not really cloud native right cloud native you almost have to build it from scratch we like to call that cloud naive well not so close one letter yeah so that was a big culture to reinvent take the tea out of cloud native it's cloud naive that went super viral you guys got t-shirts now I know you love yeah but yeah but that really ultimately is kind of a double-edged sword you got to be you can be naive on the on the architecture side and rolling up but also suppliers are can be naive so how would you define who's naive and who's not well in fact they're evolving as well so for example in Cisco you it's a little bit more native than other ones because they're really scr in the cloud you can't you you really like configure API so the cloud and NSX is going that way and so is Arista but they're incumbent they have their own tools is difficult for them they're moving slowly so it's much easier to start from scratch Avenue like and you know a network happiness started a few years ago there's only really two aviatrix was the first one they've been there for at least three or four years and there's other ones like Al Kyra for example that just started now that doing more connectivity but they want to create an overlay network across the cloud and start doing policies and trying abstracting all the clouds within one platform so I gotta ask you I interviewed an executive at VMware Sanjay Pune and he said to me at RSA last week I was only be two networking vendors left Cisco and VMware what's your respect what's your response to that obviously I mean when you have these waves as new brands that emerge like aviation others though I think there'll be a lot of startups coming out of the woodwork how do you respond to that comment well there's still a data center there's still like a lot of action on campus and there's the one but from the cloud provisioning and clown networking in general I mean they're behind I think you know in fact you don't even need them to start to it you can if you're small enough you can just keep if you're in a table us you can use it with us construct they have to insert themselves I mean they're running behind they're all certainly incumbents I love the term Andy Jesse's that Amazon Web Services uses old guard new guard to talk about the industry what does the new guard have to do the new and new brands that emerge in is it be more DevOps oriented neck net sec Ops is that net ops is the programmability these are some of the key discussions we've been having what's your view on how you see this ability their most important part is they have to make the network's simple for the dev teams and from you cannot have that you cannot make a phone call and get it V line in two weeks anymore so if you move to that cloud you have to make the cloud construct as simple enough so that for example a dev team could say okay I'm going to create this V PC but this V PC automatically being your associate your account you cannot go out on the internet you have to go to the transit VPC so there's a lot of action in terms of the I am part and you have to put the control around them too so to make it as simple as possible you guys both I mean you're the COC aviatrix but also you guys a lot of experience going back to networking going back to I call the OSI days which for us old folks know what that means but you guys know this means I want to ask you the question as you look at the future of networking here a couple of objections oh the cloud guys they got networking we're all set with them how do you respond to the fact that networking is changing and the cloud guys have their own networking what some of the pain points that's going on premises and these enterprises so are they good with the clouds what needs what are the key things that's going on in networking that makes it more than just the cloud networking what's your take on well as I said earlier that once you you could easily provision in the cloud you can easily connect to the cloud is when you start troubleshooting application in the cloud and try to scale so this that's what the problem occurs see what you're taking on it and you'll hear from the from the customers that that we have on stage and I think what happens is all the cloud the clouds by definition designed to the 80/20 rule which means they'll design 80% of the basic functionality and they'll lead to 20% extra functionality that of course every Enterprise needs they'll leave that to ISVs like aviatrix because why because they have to make money they have a service and they can't have huge instances for functionality that not everybody needs so they have to design to the common and that's they all do it right they have to and then the extra the problem is that can be an explosion that I talked about with enterprises that's holy that's what they need that they're the ones who need that extra 20% so that's that's what I see is is there's always going to be that extra functionality that in an automated and simple way that you talked about but yet powerful with up with the visible in control that they expect of on prep that that's that kind of combination that yin and the yang that people like us are providing some I want to ask you were gonna ask some of the cloud architect customer panels it's the same question this pioneers doing some work here and there's also the laggers who come in behind the early adopters what's gonna be the tipping point what are some of those conversations that the cloud architects are having out there or what's the signs that they need to be on this multi cloud or cloud native networking trend what are some of the signals that are going on their environment what are some of the thresholds or things that are going on that there can pay attention to well one once they have application and multiple cloud and they have they get wake up at 2:00 in the morning to troubleshoot them they don't know it's important so I think that's the that's where the robbery will hit the road but as I said it's easier to prove it it's okay it's a TBS it's easy use a transit gateway put a few V PCs and you're done and you create some presents like equinox and do Direct Connect and Express route with Azure that looks simple as the operations that's when they'll realize okay now I need to understand our car networking works I also need a tool that give me visibility and control not but I'm telling you that I need to understand a basic underneath it as well what are some of the day in the life scenarios that you envision happening with multi cloud because you think about what's happening it kind of has that same vibe of interoperability choice multi vendor because you have multi clouds essentially multi vendor these are kind of old paradigms that we've lived through the client-server an internet working wave what are some of those scenarios of success and that might be possible it would be possible with multi cloud and cloud native networking well I think once you have good enough visibility to satisfy your customers you know you not only like to keep the service running an application running but to be able to provision fast enough I think that's what you want to achieve small final question advice for folks watching on the live stream if they're sitting there as a cloud architect or a CXO what's your advice to them right now in this because honestly public cloud check hybrid cloud they're working on that that kids on premise is done now multi class right behind it what's your advice the first thing they should do is really try to understand cloud networking for each of their cloud providers and then understand the limitation and is what there's cloud service provider offers enough or you need to look to a third party but you don't look at a third party to start with especially an incumbent one so it's tempting to say I have a bunch of f5 experts nothing against f5 I'm going to bring my five in a cloud when you can use a needle be that automatically understand is ease and auto scaling and so on and you understand that's much simpler but sometimes you need you have five because you have requirements you have like AI rules and that kind of stuff that you use for years you cannot do it's okay I have requirement and that met I'm going to use legacy stuff and then you have to start taking okay what about visibility control about the three cloud but before you do that you have to understand the limitation of the existing cloud providers so first try to be as native as possible until things don't work after that you can start taking multi-cloud great insight somewhat thank you for coming summit in charge with Gardner thanks for sharing thank you appreciate it thanks [Applause] informatica is known as the leading enterprise cloud data management company we are known for being the top in our industry in at least five different products over the last few years especially we've been transforming into a cloud model which allows us to work better with the trends of our customers in order to see agile and effective in a business you need to make sure that your products and your offerings are just as relevant in all these different clouds than what you're used to and what you're comfortable with one of the most difficult challenges we've always had is that because we're a data company we're talking about data that a customer owns some of that data may be in the cloud some of that data may be on Prem some of that data may be actually in their data center in another region or even another country and having that data connect back to our systems that are located in the cloud has always been a challenge when we first started our engagement myth aviatrix we only had one plan that was Amazon it wasn't till later that a jerk came up and all of a sudden we found hey the solution we already had in place for her aviatrix already working in Amazon and now works in Missouri as well before we knew what GCP came up but it really wasn't a big deal for us because we already had the same solution in Amazon and integer now just working in GCP by having a multi cloud approach we have access to all three of them but more commonly it's not just one it's actually integrations between multiple we have some data and ensure that we want to integrate with Amazon we have some data in GCP that we want to bring over to a data Lake measure one of the nice things about aviatrix is that it gives a very simple interface that my staff can understand and use and manage literally hundreds of VPNs around the world and while talking to and working with our customers who are literally around the world now that we've been using aviatrix for a couple years we're actually finding that even problems that we didn't realize we had were actually solved even before we came across the problem and it just worked cloud companies as a whole are based on reputation we need to be able to protect our reputation and part of that reputation is being able to protect our customers and being able to protect more importantly our customers data aviatrix has been helpful for us in that we only have one system that can manage this whole huge system in a simple easy direct model aviatrix is directly responsible for helping us secure and manage our customers not only across the world but across multiple clouds users don't have to be VPN or networking experts in order to be able to use the system all the members on my team can manage it all the members regardless of their experience can do different levels of it one of the unexpected two advantages of aviatrix is that I don't have to sell it to my management the fact that we're not in the news at three o'clock in the morning or that we don't have to get calls in the middle of the night no news is good news especially in networking things that used to take weeks to build or done in hours I think the most important thing about a matrix is it provides me consistency aviatrix gives me a consistent model that I can use across multiple regions multiple clouds multiple customers okay welcome back to altitude 2020 for the folks on the livestream I'm John for Steve Mulaney with CEO of aviatrix for our first of two customer panels on cloud with cloud network architects we got Bobby Willoughby they gone Luis Castillo of National Instruments David should Nick with fact set guys welcome to the stage for this digital event come on up [Applause] [Music] hey good to see you thank you okay okay customer pal this is my favorite part we get to hear the real scoop against a gardener given this the industry overview certainly multi clouds very relevant and cloud native networking is the hot trend with a live stream out there and the digital event so guys let's get into it the journey is you guys are pioneering this journey of multi cloud and cloud native networking and the soon gonna be a lot more coming so I want to get into the journey what's it been like is it real you got a lot of scar tissue and what are some of the learnings yeah absolutely so multi cloud is whether or not we we accepted as a network engineers is a reality like Steve said about two years ago companies really decided to to just to just bite the bullet and and and move there whether or not whether or not we we accept that fact we need to now create a consistent architecture across across multiple clouds and that that is challenging without orchestration layers as you start managing different different tool sets and different languages across different clouds so that's it's really important that to start thinking about that guys on the other panelists here there's different phases of this journey some come at it from a networking perspective some come in from a problem troubleshooting what's what's your experiences yeah so from a networking perspective it's been incredibly exciting it's kind of a once-in-a-generation --all opportunity to look at how you're building out your network you can start to embrace things like infrastructure as code that maybe your peers on the systems teams have been doing for years but it just never really worked on bram so it's really it's really exciting to look at all the opportunities that we have and then all the interesting challenges that come up that you that you get to tackle an effect said you guys are mostly AWS right yep right now though we're we are looking at multiple clouds we have production workloads running in multiple clouds today but a lot of the initial work has been with Amazon and you've seen it from a networking perspective that's where you guys are coming at it from yep yeah we evolved more from a customer requirement perspective started out primarily as AWS but as the customer needed more resources to measure like HPC you know as your ad things like that even recently Google at Google Analytics our journey has evolved into more of a multi cloud environment Steve weigh in on the architecture because this has been the big conversation I want you to lead this second yeah so I mean I think you guys agree the journey you know it seems like the journey started a couple years ago got real serious the need for multi cloud whether you're there today of course it's gonna be there in the future so that's really important I think the next thing is just architecture I'd love to hear what you had some comments about architecture matters it all starts I mean every Enterprise I talk to maybe talk about architecture and the importance of architecture maybe Bobby it's a particular perspective we sorted a journey five years ago Wow okay and we're just now starting our fourth evolution of our network architect and we'll call it networking security net sec yep versus Justice Network and that fourth generation architectures be based primarily upon Palo Alto Networks an aviatrix I have a trick to in the orchestration piece of it but that journey came because of the need for simplicity ok the need for a multi cloud orchestration without us having to go and do reprogramming efforts across every cloud as it comes along right I guess the other question I also had around architectures also Louis maybe just talk about I know we've talked a little bit about you know scripting right and some of your thoughts on that yeah absolutely so so for us we started we started creating the network constructs with cloud formation and we've we've stuck with that for for the most part what's interesting about that is today on premise we have a lot of a lot of automation around around around how we provision networks but cloud formation has become a little bit like the new manual for us so we're now having issues with having the to automate that component and making it consistent with our on premise architecture making it consistent with Azure architecture and Google cloud so it's really interesting to see to see companies now bring that layer of abstraction that sty and brought to the do the web side now it's going up into into the into the cloud networking architecture so on the fourth generation of you mentioned you're in the fourth gen architecture what do you guys what have you learned is there any lessons scar tissue what to avoid what worked what was the middle it was a path that's probably the biggest lesson there is that when you think you finally figured it out you have it right Amazon will change something as you change something you know transit gateways a game changer so in listening to the business requirements is probably the biggest thing we need to do up front but I think from a simplicity perspective we like I said we don't want to do things four times we want to do things one time we won't be able to write to an API which aviatrix has and have them do the orchestration for us so that we don't have to do it four times how important is architecture in the progression is it you guys get thrown in the deep end to solve these problems or you guys zooming out and looking at it it's a I mean how are you guys looking at the architecture I mean you can't get off the ground if you don't have the network there so all of those now we've gone through similar evolutions we're on our fourth or fifth evolution I think about what we started off with Amazon without a direct connect gateway about a trans a gateway without a lot of the things that are available today kind of the 80/20 that Steve was talking about just because it wasn't there doesn't mean we didn't need it so we needed to figure out a way to do it we couldn't say oh you need to come back to the network team in a year and maybe Amazon will have a solution for it right you need to do it now and it evolved later and maybe optimized for change the way you're doing things in the future but don't sit around and wait you can't I'd love to have you guys each individually answer this question for the live stream because it comes up a lot a lot of cloud architects out in the community what should they be thinking about the folks that are coming into this proactively and/or realizing the business benefits are there what advice would you guys give them an architecture what should be they be thinking about and what are some guiding principles you could share so I would start with looking at an architecture model that that can that can spread and and give consistency they're different to different cloud vendors that you will absolutely have to support cloud vendors tend to want to pull you into using their native toolset and that's good if only it was realistic to talk about only one cloud but because it doesn't it's it's it's super important to talk about and have a conversation with the business and with your technology teams about a consistent model so that's David yeah talking as we prepare about a day to operations so how do I design how do I do my day one work so that I'm not you know spending eighty percent of my time troubleshooting or managing my network because I'm doing that then I'm missing out on ways that I can make improvements or embrace new technologies so it's really important early on to figure out how do I make this as low maintenance as possible so that I can focus on the things that the team really should be focusing on Bobby your advice to the architect I don't know what else I can do that simplicity of operations is key right all right so the holistic view of j2 operation you mentioned let's could jump in day one is you're you're you're getting stuff set up day two is your life after all right this is kind of what you're getting at David so what does that look like what are you envisioning as you look at that 20 miles their outpost multi-cloud world what are some of the things then you want in a day to operations yeah infrastructure is code is really important to us so how do we how do we design it so that we can fit start making network changes and fitting them into like a release pipeline and start looking at it like that rather than somebody logging into a router seoi and troubleshooting things on in an ad hoc nature so moving more towards a DevOps model there's anything on that day - yeah I would love to add something so in terms of date to operations you can you can either sort of ignore the day - operations for a little while where you get well well you get your feet wet or you can start approaching it from the beginning the fact is that the the cloud native tools don't have a lot of maturity in that space and when you run into an issue you're gonna end up having a bad day going through millions and millions of logs just to try to understand what's going on so that's something that that the industry just now is beginning to to realize it's it's such as such a big gap I think that's key because for us we're moving to more of an event-driven operations in the past monitoring got the job done it's impossible to modern monitor something that it's nothing there when the event happens all right so the event-driven application and then detection is important yeah I think Gardner was all about the cloud native wave coming into networking that's gonna be a serious thing I want to get you guys perspectives I know you have different views of how you come into the journey and how you're executing and I always say the beauties in the eye of the beholder and that kind of applies how the network's laid out so Bobby you guys do a lot of high-performance encryption both on AWS and Azure that's kind of a unique thing for you how are you seeing that impact with multi cloud yeah and that's a new requirement for us to where we we have an equipment to encrypt and they they never get the question should i encryption and I'll encrypt the answer is always yes you should encrypt when you can encrypt for our perspective we we need to migrate a bunch of data from our data centers we have some huge data centers and then getting that data to the cloud is the timely experiencing some cases so we have been mandated that we have to encrypt everything leaving the data center so we're looking at using the aviatrix insane mode appliances to be able to encrypt you know 10 20 gigabits of data as it moves to the cloud itself David you're using terraform you got fire Ned you got a lot of complexity in your network what do you guys look at the future for your environment yeah so something exciting that or yeah now is fire net so for our security team they obviously have a lot of a lot of knowledge base around Palo Alto and with our commitments to our clients you know it's it's it's not very easy to shift your security model to a specific cloud vendor right so there's a lot of stuck to compliance or things like that where being able to take some of what you've you know you've worked on for years on Bram and put it in the cloud and have the same type of assurance that things are gonna work and be secure in the same way that they are on prem helps make that journey into the cloud a lot easier and Louis you guys got scripting you got a lot of things going on what's your what's your unique angle on this yeah no absolutely so full disclosure I'm not a not not an aviatrix customer yet it's ok wanna hear the truth that's good Ellis what are you thinking about what's on your mind no really when you when you talk about implementing the tool like this it's really just really important to talk about automation and focus on on value so when you talk about things like encryption and things like so yeah encrypting tunnels and encrypting the paths and those things are it should it should should be second nature really when you when you look at building those backends and managing them with your team it becomes really painful so tools like aviatrix that that add a lot of automation it's out of out of sight out of mind you can focus on the value and you don't have to focus on so I gotta ask you guys I'll see aviatrix is here they're their supplier to the sector but you guys are customers everyone's pitching you stuff these people are not gonna here to buy my stuff how do you guys have that conversation with the suppliers like the cloud vendors and other folks what's the what's it like we're API all the way you got to support this what are some of the what are some of your requirements how do you talk to and evaluate people that walk in and want to knock on your door and pitch you something what's the conversation like it's definitely it's definitely API driven we we definitely look at the at the PAP i structure of the vendors provide before we select anything that that is always first of mine and also what a problem are we really trying to solve usually people try to sell or try to give us something that isn't really valuable like implementing a solution on the on the on the cloud isn't really it doesn't really add a lot of value that's where we go David what's your conversation like with suppliers you have a certain new way to do things as as becomes more agile and essentially the networking and more dynamic what are some of the conversation is with the either incumbents or new new vendors that you're having what do what do you require yeah so ease of use is definitely definitely high up there we've had some vendors come in and say you know hey you know when you go to set this up we're gonna want to send somebody on-site and they're gonna sit with you for a day to configure it and that's kind of a red flag what wait a minute you know do we really if one of my really talented engineers can't figure it out on his own what's going on there and why is that so you know having having some ease-of-use and the team being comfortable with it and understanding it is really important probably how about you I mean the old days was do a bake-off and you know the winner takes all I mean is it like that anymore what's involving take off last year first you win so but that's different now because now you and you when you get the product you can install the product in AWS energy or have it up and running a matter of minutes and so key is is that it can you be operational you know within hours or days instead of weeks right but do we also have the flexibility to customize it to meet your needs could you want to be you want to be put into a box with the other customers we have needs that surpassed or cut their needs yeah I almost see the challenge of you guys are living where you've got the cloud immediate value depending on roll-up any solutions but then you have might have other needs so you've got to be careful not to buy into stuff that's not shipping so you're trying to be proactive at the same time deal with what you got I mean how do you guys see that evolving because multi-cloud to me is definitely relevant but it's not yet clear how to implement across how do you guys look at this baked versus you know future solutions coming how do you balance that so again so right now we we're we're taking the the ad hoc approach and and experimenting with the different concepts of cloud and really leveraging the the native constructs of each cloud but but there's it there's a breaking point for sure you don't you don't get to scale this I like like Seamon said and you have to focus on being able to deliver a developer they're their sandbox or their play area for the for the things that they're trying to build quickly and the only way to do that is with the with with some sort of consistent orchestration layer that allows you to so you've spent a lot more stuff to be coming pretty quickly IDEs area I do expect things to start to start maturing quite quite quickly this year and you guys see similar trend new stuff coming fast yeah you know part of the biggest challenge we've got now is being able to segment within the network being able to provide segmentation between production on production workloads even businesses because we support many businesses worldwide and and isolation between those is a key criteria there so the ability to identify and quickly isolate those workloads is key so the CIOs that are watching or that are saying hey take that he'll do multi cloud and then you know the bottoms up organization take pause you're kind of like off it's not how it works I mean what is the reality in terms of implementing you know in as fast as possible because the business benefits are clear but it's not always clear in the technology how to move that fast yeah what are some of the barriers what are the blockers what are the enablers I think the reality is is that you may not think your multi-cloud but your business is right so I think the biggest barriers there is understanding what the requirements are and how best to meet those requirements Inc and then secure manner because you need to make sure that things are working from a latency perspective that things work the way they did and get out of the mind shift that you know it was a cheery application in the data center it doesn't have to be a Tier three application in the cloud so lift and shift is is not the way to go scale is a big part of what I see is the competitive advantage to lot of these clouds and they used to be proprietary network stacks in the old days and then open systems came that was a good thing but as clouds become bigger there's kind of an inherent lock in there with the scale how do you guys keep the choice open how're you guys thinking about interoperability what are some of the conversations and you guys are having around those key concepts well when we look at when we look at the problem from a networking perspective it it's really key for you to just enable enable all the all the clouds to be to be able to communicate between them developers will will find a way to use the cloud that best suits their their business need and and like like you said it's whether whether you're in denial or not of the multi cloud fact that then your company is in already that's it becomes really important for you to move quickly yeah and a lot of it also hinges on how well is the provider embracing what that specific cloud is doing so are they are they swimming with Amazon or Azure and just helping facilitate things they're doing the you know the heavy lifting API work for you or are they swimming upstream and they're trying to hack it all together in a messy way and so that helps you you know stay out of the lock-in because they're you know if they're doing if they're using Amazon native tools to help you get where you need to be it's not like Amazon's gonna release something in the future that completely you know you have designed yourself into a corner so the closer they're more than cloud native they are the more the easier it is to to deploy but you also need to be aligned in such a way that you can take advantage of those cloud native technologies will they make sense tgw is a game changer in terms of cost and performance right so to completely ignore that would be wrong but you know if you needed to have encryption you know teach Adobe's not encrypted so you need to have some type of a gateway to do the VPN encryption you know so the aviatrix tool gives you the beauty of both worlds you can use tgw or the Gateway Wow real quick in the last minute we have I want to just get a quick feedback from you guys I hear a lot of people say to me hey the I picked the best cloud for the workload you got and then figure out multi cloud behind the scenes so that seems to be do you guys agree with that I mean is it do I go mole to one cloud across the whole company or this workload works great on AWS that work was great on this from a cloud standpoint you agree with that premise and then witness multi-cloud stitch them all together yeah from from an application perspective it it can be per workload but it can also be an economical decision certain enterprise contracts will will pull you in one direction to add value but the the network problem is still the same go away yeah yeah I mean you don't want to be trying to fit a square into a round Hall right so if it works better on that cloud provider then it's our job to make sure that that service is there and people can use it agree you just need to stay ahead of the game make sure that the then they're working for structure is there secure is available and is multi cloud capable yeah I'm at the end the day you guys just validating that it's the networking game now cloud storage compute check networking is where the action is awesome thanks for your insights guys appreciate you coming on the panel appreciate Thanks thank you [Applause] [Music] [Applause] okay welcome back on the live feed I'm John for its Dee Mulaney my co-host with aviatrix I'm with the cube for the special digital event our next customer panel got great another set of cloud network architects Justin Smith was aura Justin broadly with Ellie Mae and Amit Oh tree job with Koopa Pokemon stage [Applause] all right thank you thank you oK you've got all the cliff notes from the last session welcome rinse and repeat yeah yeah we're going to go under the hood a little bit I think I think they nailed the what we've been reporting and we've been having this conversation around networking is where the action is because that's the end of the day you got a move attack from A to B and you get work gloves exchanging data so it's really killer so let's get started Amit what are you seeing as the journey of multi cloud as you go under the hood and say okay I got to implement this I have to engineer the network make it enabling make it programmable make it interoperable across clouds I mean that's like I mean almost sounds impossible to me what's your taking yeah I mean it it seems impossible but if you are running an organization which is running infrastructure as a cordon all right it is easily doable like you can use tools out there that's available today you can use third-party products that can do a better job but but put your architecture first don't wait architecture may not be perfect put the best architecture that's available today and be agile to iterate and make improvements over the time we got to Justin's over here so I have to be careful when I point a question adjusting they both have to answer but okay journeys what's the journey been like I mean is there phases we heard that from Gardner people come into multi cloud and cloud native networking from different perspectives what's your take on the journey Justin yeah I mean from Mars like to we started out very much focused on one cloud and as we started doing Atkins we started doing new products the market the need for multi cloud comes very apparent very quickly for us and so you know having an architecture that we can plug in play into and be able to add and change things as it changes is super important for what we're doing in the space just in your journey yes for us we were very ad hoc oriented and the idea is that we were reinventing all the time trying to move into these new things and coming up with great new ideas and so rather than it being some iterative approach with our deployments that became a number of different deployments and so we shifted that tour and the network has been a real enabler of this is that it there's one network and it touches whatever cloud we want it to touch and it touches the data centers that we need it to touch and it touches the customers that we need it to touch our job is to make sure that the services that are available and one of those locations are available in all of the locations so the idea is not that we need to come up with this new solution every time it's that we're just iterating on what we've already decided to do before we get the architecture section I want to ask you guys a question I'm a big fan of you know let the app developers have infrastructure as code so check but having the right cloud run that workload I'm a big fan of that if it works great but we just heard from the other panel you can't change the network so I want to get your thoughts what is cloud native networking and is that the engine really got the enabler for this multi cloud trend but you guys taken we'll start with a mint what do you think about that yeah so you are gonna have workloads running in different clouds and the workloads would have affinity to one cloud over other but how you expose that it's matter of how you are going to build your networks how we are going to run security how we are going to do egress ingress out of it so it means the big problem how do you split says what's the solution what's the end the key pain points and problem statement I mean the key pain point for most companies is how do you take your traditional on-premise network and then blow that out to the cloud in a way that makes sense you know IP conflicts you have IP space you pub public eye peas and premise as well as in the cloud and how do you kind of make a sense of all of that and I think that's where tools like aviatrix make a lot of sense in that space from our site it's it's really simple it's a latency and bandwidth and availability these don't change whether we're talking about cloud or data center or even corporate IT networking so our job when when these all of these things are simplified into like s3 for instance and our developers want to use those we have to be able to deliver that and for a particular group or another group that wants to use just just GCP resources these aren't we have to support these requirements and these wants as opposed to saying hey that's not a good idea our job is to enable them not to disable them do you think I do you guys think infrastructure has code which I love that I think that's the future it is we saw that with DevOps but I just start getting the networking is it getting down to the network portion where it's network is code because stores and compute working really well is seeing all kubernetes and service master and network is code reality is that there is got work to do it's absolutely there I mean you mentioned net DevOps and it's it's very real I mean in Cooper we build our networks through terraform and on not only just out of fun build an API so that we can consistently build V nets and VPC all across in the same way three guys do it yeah and even security groups and then on top an aviatrix comes in we can peer the networks bridge bridge all the different regions through code same with you guys but yeah think about this everything we deploy is done with automation and then we also run things like lambda on top to make changes in real time we don't make manual changes on our network in the data center funny enough it's still manual but the cloud has enabled us to move into this automation mindset and and all my guys that's what they focus on is is bringing what now what they're doing in the cloud into the data center which is kind of opposite of what it should be that's full or what it used to be it's full DevOps then yes yeah I mean for us was similar on premise still somewhat very manual although we're moving more Norton ninja and terraform concepts but everything in the production environment is colored confirmation terraform code and now coming into the datacenter same I just wanted to jump in on a Justin Smith one of the comment that you made cuz it's something that we always talk about a lot is that the center of gravity of architecture used to be an on-prem and now it's shifted in the cloud and once you have your strategic architecture what you--what do you do you push that everywhere so what you used to see at the beginning of cloud was pushing the architecture on prem into cloud now i want to pick up on what you said to you others agree that the center of architect of gravity is here i'm now pushing what i do in the cloud back into on-prem and what and then so first that and then also in the journey where are you at from 0 to 100 of actually in the journey to cloud do you 50% there are you 10% are you vacuum datacenters next year I mean were you guys at yeah so there's there's two types of gravity that you typically are dealing with with no migration first is data gravity and your data set and where that data lives and then the second is the network platform that interrupts all that together in our case the data gravity sold mostly on Prem but our network is now extend out to the app tier that's gonna be in cloud right eventually that data gravity will also move to cloud as we start getting more sophisticated but you know in our journey we're about halfway there about halfway through the process we're taking a handle of lift and shift and when did that start and we started about three years ago okay okay cool bye it's a very different story it started from a garage and 100% on the clock it's a business spend management platform as a software as a service 100% on the cloud it was like 10 years ago right yes yeah you guys are riding the wave love that architecture Justin I want to ask you is or you guys mentioned DevOps I mean honestly we saw the huge observability wave which is essentially network management for the cloud in my opinion right yeah it's more dynamic but this is about visibility we heard from the last panel you don't know what's being turned on or turned off from a services standpoint at any given time how is all this playing out when you start getting into the DevOps down well this this is the big challenge for all of us as visibility when you talk transport within a cloud you know we very interesting we have moved from having a backbone that we bought that we owned that would be data center connectivity we now I work for as or as a subscription billing company so we want to support the subscription mindset so rather than going and buying circuits and having to wait three months to install and then coming up with some way to get things connected and resiliency and redundancy I my backbone is in the cloud I use the cloud providers interconnections between regions to transport data across and and so if you do that with their native solutions you you do lose visibility there there are areas in that that you don't get which is why controlling you know controllers and having some type of management plane is a requirement for us to do what we're supposed to do and provide consistency while doing it a great conversation I loved when you said earlier latency bandwidth I think availability with your sim pop3 things guys SLA I mean you just do ping times between clouds it's like you don't know what you're getting for round-trip times this becomes a huge kind of risk management black hole whatever you want to call blind spot how are you guys looking at the interconnects between clouds because you know I can see that working from you know ground to cloud I'm per cloud but when you start doing with multi clouds workloads SLA is will be all of the map won't they just inherently but how do you guys view that yeah I think we talked about workload and we know that the workloads are going to be different in different clouds but they are going to be calling each other so it's very important to have that visibility that you can see how data is flowing at what latency and what our ability is hour is there and our authority needs to operate on that so it's solely use the software dashboard look at the times and look at the latency in the old day is strong so on open so on you try to figure it out and then your day is you have to figure out just what's your answer to that because you're in the middle of it yeah I mean I think the key thing there is that we have to plan for that failure we have to plan for that latency in our applications that's starting start tracking your SLI something you start planning for and you loosely couple these services and a much more micro services approach so you actually can handle that kind of failure or that type of unknown latency and unfortunately the cloud has made us much better at handling exceptions a much better way you guys are all great examples of cloud native from day one and you guys had when did you have the tipping point moment or the Epiphany of saying a multi clouds real I can't ignore it I got to factor it into all my design design principles and and everything you're doing what's it was there a moment over that was it from day one now there are two divisions one was the business so in business there was some affinity to not be in one cloud or to be in one cloud and that drove from the business side so as a cloud architect our responsibility was to support that business and other is the technology some things are really running better in like if you are running dot network load or you are going to run machine learning or AI so that you have you would have that reference of one cloud over other so it was the bill that we got from AWS I mean that's that's what drives a lot of these conversations is the financial viability of what you're building on top of it which is so we this failure domain idea which is which is fairly interesting how do I solve our guarantee against a failure domain you have methodologies with you know back-end direct connects or interconnect with GCP all of these ideas are something that you have to take into account but that transport layer should not matter to whoever we're building this for our job is to deliver the frames in the packets what that flows across how you get there we want to make that seamless and so whether it's a public Internet API call or it's a back-end connectivity through Direct Connect it doesn't matter it just has to meet a contract that you signed with your application folks yeah that's the availability piece just on your thoughts on that I think any comment on that so actually multi clouds become something much more recent in the last six to eight months I'd say we always kind of had a very much an attitude of like moving to Amazon from our private cloud is hard enough why complicate it further but the realities of the business and as we start seeing you know improvements in Google and Asia and different technology spaces the need for multi cloud becomes much more important as well as our acquisition strategies I matured we're seeing that companies that used to be on premise that we typically acquire are now very much already on a cloud and if they're on a cloud I need to plug them into our ecosystem and so that's really change our multi cloud story in a big way I'd love to get your thoughts on the clouds versus the clouds because you know you compare them Amazon's got more features they're rich with features I see the bills are hiking people using them but Google's got a great network he googles networks pretty damn good and then you got Asher what's the difference between the clouds who where they evolve something where they peak in certain areas better than others what what are the characteristics which makes one cloud better do they have a unique feature that makes as you're better than Google and vice versa what do you guys think about the different clouds yeah to my experience I think there is the approach is different in many places Google has a different approach very DevOps friendly and you can run your workload like the your network can span regions time I mean but our application ready to accept that MS one is evolving I mean I remember 10 years back Amazon's Network was a flat network we will be launching servers and 10.0.0.0 so so the VP sees concept came out multi-account came out so they are evolving as you are at a late start but because they have a late start they saw the pattern and they they have some mature set up on the I mean I think they're all trying to say they're equal in their own ways I think they all have very specific design philosophies that allow them to be successful in different ways and you have to kind of keep that in mind as you architect your own solution for example Amazon has a very much a very regional affinity they don't like to go cross region in their architecture whereas Google is very much it's a global network we're gonna think about as a global solution I think Google also has a banjo it's third to market and so it has seen what a sure did wrong it's seen what AWS did wrong and it's made those improvements and I think that's one of their big advantage at great scale to Justin thoughts on the cloud so yeah Amazon built from the system up and Google built from the network down so their ideas and approaches are from a global versus or regional I agree with you completely that that is the big number one thing but the if you look at it from the outset interestingly the the inability or the ability for Amazon to limit layer two broadcasting and and what that really means from a VPC perspective changed all the routing protocols you can use all the things that we have built inside of a data center to provide resiliency and and and make things seamless to users all of that disappeared and so because we had to accept that at the VPC level now we have to accept it at the LAN level Google's done a better job of being able to overcome those things and provide those traditional network facilities to us just great panel can go all day here's awesome so I heard we could we'll get to the cloud native naive questions so kind of think about what's not even what's cloud is that next but I got to ask you had a conversation with a friend he's like Wayne is the new land so if you think about what the land was at a datacenter when is the new link you get talking about the cloud impact so that means st when the old st winds kind of changing into the new land how do you guys look at that because if you think about it what lands were for inside a premises was all about networking high speed but now when you take a win and make the essentially a land do you agree with that and how do you view this trend and is it good or bad or is it ugly and what's what you guys take on this yeah i think it's a it's a thing that you have to work with your application architect so if you are managing networks and if you're a sorry engineer you need to work with them to expose the unreliability that would bring in so the application has to hand a lot of this the difference in the latencies and and the reliability has to be worked through the application there land when same concept as that BS I think we've been talking about for a long time the erosion of the edge and so is this is just a continuation of that journey we've been on for the last several years as we get more and more cloud native and we start about API is the ability to lock my data in place and not be able to access it really goes away and so I think this is just continuation that thing I think it has challenges we start talking about weighing scale versus land scale the tooling doesn't work the same the scale of that tooling is much larger and the need to automation is much much higher in a way and than it was in a land that's what you're seeing so much infrastructure as code yeah yeah so for me I'll go back again to this its bandwidth and its latency right that that define those two land versus when but the other thing that comes up more and more with cloud deployments is where is our security boundary and where can I extend this secure aware appliance or set of rules to protect what's inside of it so for us we're able to deliver VRS or route forwarding tables for different segments wherever we're at in the world and so they're they're trusted to talk to each other but if they're gonna go to someplace that's outside of their their network then they have to cross a security boundary and where we enforce policy very heavily so for me there's it's not just land when it's it's how does environment get to environment more importantly that's a great point and security we haven't talked to yet but that's got to be baked in from the beginning that's architecture thoughts on security are you guys are dealing with it yeah start from the base have app to app security built-in have TLS have encryption on the data a transit data at rest but as you bring the application to the cloud and they are going to go multi-cloud talking to over the Internet in some places well have apt web security I mean I mean our principals day security is day zero every day and so we we always build it into our design we want our architecture into our applications its encrypt everything its TLS everywhere it's make sure that that data is secured at all times yeah one of the cool trends at RSA just as a side note was the data in use encryption piece which is a homomorphic stuff was interesting all right guys final question you know we heard on the earlier panel was also trending at reinvent we take the tea out of cloud native it spells cloud naive okay they got shirts now aviatrix kind of got this trend going what does that mean to be naive so if you're to your peers out there watching a live stream and also the suppliers that are trying to supply you guys with technology and services what's naive look like and what's native look like when is someone naive about implementing all this stuff so for me it's because we are in hundred-percent cloud for us it's main thing is ready for the change and you will you will find new building blocks coming in and the network design will evolve and change so don't be naive insane that it's static you wall with the change I think the big naivety that people have is that well I've been doing it this way for 20 years and been successful it's going to be successful in cloud the reality is that's not the case you have to think some of the stuff a little bit differently and you need to think about it early enough so that you can become cloud native and really enable your business on cloud yeah for me it's it's being open minded right the the our industry the network industry as a whole has been very much I am smarter than everybody else and we're gonna tell everybody how it's going to be done and we had we fell into a lull when it came to producing infrastructure and and and so embracing this idea that we can deploy a new solution or a new environment in minutes as opposed to hours or weeks or four months in some cases is really important and and so you know it's not me being closed-minded native being open minded exactly and and it took a for me it was that was a transformative kind of where I was looking to solve problems in a cloud way as opposed to looking to solve problems in this traditional old-school way all right I know we're out of time but I ask one more question so you guys so good it could be a quick answer what's the BS language when you the BS meter goes off when people talk to you about solutions what's the kind of jargon that you hear that's the BS meter going off what are people talking about that in your opinion you here you go that's total B yes but what triggers use it so that I have two lines out of movies that are really I can if I say them without actually thinking them it's like 1.21 jigowatts are you out of your mind from Back to the Future right somebody's giving you all these and then and then Martin Mull and and Michael Keaton and mr. mom when he goes to 22 21 whatever it takes yeah those two right there if those go off in my mind somebody's talking to me I know they're full of baloney so a lot of speech would be a lot of speeds and feeds a lot of data did it instead of talking about what you're actually doing and solutioning for you're talking about well I does this this this and any time I start seeing the cloud vendor start benchmarking against each other it's your workload is your workload you need a benchmark yourself don't don't listen to the marketing on that that's that's all what triggers you and the bsp I think if somebody explains you and not simple they cannot explain you in simplicity then that's good all right guys thanks for the great insight great pen how about a round of applause DX easy solutions integrating company that we service customers from all industry verticals and we're helping them to move to the digital world so as a solutions integrator we interface with many many customers that have many different types of needs and they're on their IT journey to modernize their applications into the cloud so we encounter many different scenarios many different reasons for those migrations all of them seeking to optimize their IT solutions to better enable their business we have our CPS organization it's cloud platform services we support AWS does your Google Alibaba porco will help move those workloads to wherever it's most appropriate no one buys the house for the plumbing equally no one buys the solution for the networking but if the plumbing doesn't work no one likes the house and if this network doesn't work no one likes a solution so network is ubiquitous it is a key component of every solution we do the network connectivity is the lifeblood of any architecture without network connectivity nothing works properly planning and building a scalable robust network that's gonna be able to adapt with the application needs its critical when encountering some network design and talking about speed the deployment aviatrix came up in discussion and we then further pursued an area DHT products that incorporated aviatrix is part of a new offering that we are in the process of developing that really enhances our ability to provide cloud connectivity for the lance cloud connectivity there's a new line of networking services that we're getting into as our clients moving the hybrid cloud networking it is much different than our traditional based services an aviatrix provides a key component in that service before we found aviatrix we were using just native peering connections but there wasn't a way to visualize all those peering connections and with multiple accounts multiple contacts for security with a v8 church we were able to visualize those different peering connections of security groups it helped a lot especially in areas of early deployment scenarios were quickly able to then take those deployment scenarios and turn them into scripts that we can then deploy repeatedly their solutions were designed for work with the cloud native capabilities first and where those cloud native capabilities fall short they then have solution sets that augment those capabilities I was pleasantly surprised number one with the aviatrix team as a whole in their level of engagement with us you know we weren't only buying the product we were buying a team that came on board to help us implement and solution that was really good to work together to learn both what aviatrix had to offer as well as enhancements that we had to bring that aviatrix was able to put into their product and meet our needs even better aviatrix was a joy to find because they really provided us the technology that we needed in order to provide multi cloud connectivity that really added to the functionality that you can't get from the basically providing services we're taking our customers on a journey to simplify and optimize their IT infrastructure baby Atrix certainly has made my job much easier okay welcome back to altitude 2020 for the digital event for the live feed welcome back I'm John fray with the cube with Steve Mulaney CEO aviatrix for the next panel from global system integrators the folks who are building and working with folks on their journey to multi cloud and cloud native networking we've got a great panel George Buckman with dxc and Derek Monahan with wwt welcome to the stage [Applause] [Music] okay you guys are the ones out there advising building and getting down and dirty with multi cloud and cloud native network and we start from the customer panel you can see the diversity of where people come into the journey of cloud it kind of depends upon where you are but the trends are all clear cloud native networking DevOps up and down the stack this has been the main engine what's your guys take of the disk Jerry to multi cloud what do you guys seeing yep yeah it's it's critical I mean we're seeing all of our enterprise customers enter into this they've been through the migrations of the easy stuff you know now they're trying to optimize and get more improvement so now the tough stuffs coming on right and you know they need their data processing near where their data is so that's driving them to a multi cloud environment okay we heard some of the edge stuff I mean you guys are you've seen this movie before but now it's a whole new ballgame what's your take yeah so I'll give you a hint so our practice it's not called the cloud practice it's the multi cloud practice and so if that gives you a hint of how we approach things it's very consultative and so when we look at what the trends are let's look a little year ago about a year ago we were having conversations with customers let's build a data center in the cloud let's put some VP C's let's throw some firewalls with some DNS and other infrastructure out there and let's hope it works this isn't a science project so what we're trying we're starting to see is customers are starting to have more of a vision and we're helping with that consultative nature but it's totally based on the business and you got to start understanding how the lines of business are using the apps and then we evolved into that next journey which is a foundational approach to what are some of the problem statements customers are solving when they come to you what are the top things that are on their my house or the ease of use of Julie all that stuff but what specifically they did digging into yeah some complexity I think when you look at a multi cloud approach in my view is network requirements are complex you know I think they are but I think the approach can be let's simplify that so one thing that we try to do this is how we talk to customers is let's just like you simplify an aviatrix simplifies the automation orchestration of cloud networking we're trying to simplify the design the planning implementation of infrastructure across multiple workloads across multiple platforms and so the way we do it is we sit down we look at not just use cases and not just the questions in common we anticipate we actually build out based on the business and function requirements we build out a strategy and then create a set of documents and guess what we actually build in the lab and that lab that we platform we built proves out this reference architecture actually works absolutely we implement similar concepts I mean we they're proven practices they work great so well George you mentioned that the hard parts now upon us are you referring to networking what is specifically were you getting at Tara says the easy parts done that so for the enterprises themselves migrating their more critical apps or more difficult apps into the environments you know they've just we've just scratched the surface I believe on what enterprises that are doing to move into the cloud to optimize their environments to take advantage of the scale and speed to deployment and to be able to better enable their businesses so they're just now really starting the >> so do you get you guys see what I talked about them in terms of their Cambrian explosion I mean you're both monster system integrators with you know top fortune enterprise customers you know really rely on you for for guidance and consulting and so forth and boy they're networks is that something that you you've seen I mean - does that resonate did you notice a year and a half ago and all of a sudden the importance of cloud for enterprise shoot up yeah I mean we're seeing it okay in our internal environment as you know we're a huge company or as customers are in 30 so we're experiencing that internal okay and every one of our other customers so I I have another question oh but I don't know the answer to this and the lawyer never asks a question that you don't know the answer to but I'm gonna ask it anyway DX c @ w WT massive system integrators why aviatrix yep so great question Steve so I think the way we approach things I think we have a similar vision a similar strategy how you approach things how we approach things that world by technology number one we want to simplify the complexity and so that's your number one priorities let's take the networking but simplify it and I think part of the other point I'm making is we have we see this automation piece as not just an afterthought anymore if you look at what customers care about visibility and automation is probably the at the top three maybe the third on the list and I think that's where we see the value and I think the partnership that we're building and what I what I get excited about is not just putting yours in our lab and showing customers how it works is Co developing a solution with you figuring out hey how can we make this better Bank visibily is a huge thing jump in security alone network everything's around visibility what automation you see happening in terms of progression order of operations if you will it's the low-hanging fruit what are people working on now and what are what are some of the aspirational goals around when you start thinking about multi cloud an automation yep so I wanted to get back to answer that question I want to answer your question you know what led us there and why aviatrix you know in working some large internal IT projects and and looking at how we were going to integrate those solutions you know we like to build everything with recipes where network is probably playing catch-up in the DevOps world but with a DevOps mindset looking to speed to deploy support all those things so when you start building your recipes you take a little of this a little of that and you mix it all together well when you look around you say wow look there's this big bag of athe let me plop that in that solves a big part of my problems that I have to speed to integrate speed to deploy and the operational views that I need to run this so that was 11 years about reference architectures yeah absolutely so you know they came with a full slate of reference architectures already the out there and ready to go that fit our needs so it's very very easy for us to integrate those into our recipes what do you guys think about all the multi vendor interoperability conversations that have been going on choice has been a big part of multi cloud in terms of you know customers want choice didn't you know they'll put a workload in the cloud that works but this notion of choice and interoperability is become a big conversation it is and I think our approach and that's why we talk to customers is let's let's speed and D risk of that decision making process and how do we do that because the interoperability is key you're not just putting it's not just a single vendor we're talking you know many many vendors I mean think about the average number of cloud application as a customer uses a business and enterprise business today you know it's it's above 30 it's it's skyrocketing and so what we do and we look at it from an Billee approach is how do things interoperate we test it out we validate it we build a reference architecture says these are the critical design elements now let's build one with aviatrix and show how this works with aviatrix and I think the the important part there though is the automation piece that we add to it invisibility so I think the visibility is what's what I see lack in cross industry today and the cloud needed that's been a big topic okay in terms of aviatrix as you guys see them coming in there one of the ones that are emerging and the new brands emerging with multi cloud you still got the old guard incumbent with huge footprints how our customers dealing with that that kind of component and dealing with both of them yeah I mean where we have customers that are ingrained with a particular vendor and you know we have partnerships with many vendors so our objective is to provide the solution that meets that client and you they all want multi vendor they all want interoperability correct all right so I got to ask you guys a question what we were defining day to operations what does that mean I mean you guys are looking at the big business and technical components of architecture what does day to Operations mean what's the definition of that yeah so I think from our perspective my experience we you know day to operations whether it's it's not just the you know the orchestration piece and setting up and let it a lot of automate and have some you know change control you're looking at this from a data perspective how do I support this ongoing and make it easy to make changes as we evolve that the the cloud is very dynamic the the nature of how the fast is expanding the number of features is astonishing trying to keep up to date with a number of just networking capabilities and services that are added so I think day to operation starts with a fundable understanding of you know building out supporting a customer's environments and making it the automation piece easy from from you know a distance I think yeah and you know taking that to the next level of being able to enable customers to have catalog items that they can pick and choose hey I need this network connectivity from this cloud location back to this on pram and being able to have that automated and provisioned just simply by ordering it for the folks watching out there guys take a minute to explain as you guys are in the trenches doing a lot of good work what are some of the engagement that you guys get into how does that progress what is the what's what happens there they call you up and say hey I need multi-cloud or you're already in there I mean take us through why how someone can engage to use a global si to come in and make this thing happen what's typical engagement look like yeah so from our perspective we typically have a series of workshops in a methodology that we kind of go along the journey number one we have a foundational approach and I don't mean foundation meaning the network foundation that's a very critical element we got a factor in security we've got to factor in automation so we think about foundation we do a workshop that starts with education a lot of times we'll go in and we'll just educate the customer what does VPC sharing you know what is a private link and asher how does that impact your business you know customers I want to share services out in an ecosystem with other customers and partners well there's many ways to accomplish that so our goal is to you know understand those requirements and then build that strategy with them thoughts Georgia yeah I mean I'm one of the guys that's down in the weeds making things happen so I'm not the guy on the front line interfacing with the customers every day but we have a similar approach you know we have a consulting practice that will go out and and apply their practices to see what those and when do you parachute in yeah and when I've been is I'm on the back end working with our offering development leads for the networking so we understand or seeing what customers are asking for and we're on the back end developing the solutions that integrate with our own offerings as well as enable other customers to just deploy quickly to meet their connectivity needs it so the patterns are similar right final question for you guys I want to ask you to paint a picture of what success looks like and you know the name customers didn't again reveal kind of who they are but what does success look like in multi-cloud as you as you paint a picture for the folks here and watching on the live stream it's someone says hey I want to be multi-cloud I got to have my operations agile I want full DevOps I want programmability security built in from day zero what does success look like yeah I think success looks like this so when you're building out a network the network is a harder thing to change than some other aspects of cloud so what we think is even if you're thinking about that second cloud which we have most of our customers are on to public clouds today they might be dabbling in is you build that network foundation at architecture that takes in consideration where you're going and so once we start building that reference architecture out that shows this is how to sit from a multi-cloud perspective not a single cloud and let's not forget our branches let's not forget our data centers let's not forget how all this connects together because that's how we define multi-cloud it's not just in the cloud it's on Prem and it's off Prem and so collectively I think the key is also is that we provide them an hld you got to start with a high level design that can be tweaked as you go through the journey but you got to give a solid structural foundation and that networking which we think most customers think as not not the network engineers but as an afterthought we want to make that the most critical element before you start the journey Jorge from your seed how do you success look for you so you know it starts out on these journeys often start out people not even thinking about what is gonna happen with what their network needs are when they start their migration journey to the cloud so I want this success to me looks like them being able to end up not worrying about what's happening in the network when they move to the cloud good guys great insight thanks for coming on share and pen I've got a round of applause the global system integrators [Applause] [Music] okay welcome back from the live feed I'm chef for with the q Steve Valenti CEO of aviatrix my co-host our next panel is the aviatrix certified engineer is also known as aces this is the folks that are certified their engineering they're building these new solutions please welcome Toby Foss from informatica Stacy linear from Teradata and Jennifer Reed with Victor Davis to the stage I was just gonna I was just gonna rip you guys see where's your jackets and Jen's got the jacket on okay good love the aviatrix aces pile of gear they're above the clouds story to new heights that's right so guys aviatrix aces love the name I think it's great certified this is all about getting things engineered so there's a level of certification I want to get into that but first take us through the day in the life of an ace and just to point out Stacey's a squad leader so he's like it Squadron Leader Roger and leader yeah Squadron Leader he's got a bunch of aces underneath him but share your perspective day-in-the-life Jennifer we'll start with you sure so I have actually a whole team that works for me both in the in the North America both in the US and in Mexico and so I'm really working to get them certified as well so I can become a squad leader myself but it's important because one of the the critical gaps that we've found is people having the networking background because they're you graduate from college and you have a lot of computer science background you can program you've got Python but networking in packets they just don't get and so just taking them through all the processes that it's really necessary to understand when you're troubleshooting is really critical mm-hm and because you're gonna get an issue where you need to figure out where exactly is that happening on the network you know is my my issue just in the V PC is and on the instant side is a security group or is it going on print and is this something actually embedded within Amazon itself I mean I should troubleshot an issue for about six months going back and forth with Amazon and it was the vgw VPN because they were auto-scaling on two sides and we ended up having to pull out the Cisco's and put in aviatrix so I could just say okay it's fixed and actually actually helped the application teams get to that and get it solved yeah but I'm taking a lot of junior people and getting them through that certification process so they can understand and see the network the way I see the network I mean look I've been doing this for 25 years when I got out when I went in the Marine Corps that's what I did and coming out the network is still the network but people don't get the same training they get they got in the 90s it's just so easy just write some software they work takes care of itself yes he'll be will good I'll come back to that I want to come back to that problem solve with Amazon but Toby I think the only thing I have to add to that is that it's always the network fault as long as I've been in never I've always been the network's fault and I'm even to this day you know it's still the network's fault and part of being a network guy is that you need to prove when it is and when it's not your fault and that means you need to know a little bit about a hundred different things to make that and now you've got a full stack DevOps you got to know a lot more times another 100 and these times are changing yeah they say you're Squadron Leader I get that right what is what is the squadron leader first can you describe what it is I think probably just leading all the network components of it but not they from my perspective when to think about what you ask them was it's about no issues and the escalation soft my day is a good outcome that's a good day it's a good day again every mission the Amazon this brings up a good point you know when you have these new waves come in you have a lot of new things new we use cases a lot of the finger-pointing it's that guys problem that girls problem so what how do you solve that and how do you get the young guns up to speed is there training is that this is where the certification comes in was where the certification is really going to come in I know when we we got together at reinvent one of the the questions that that we had with Steve and the team was what what should our certification look like you know she would just be teaching about what aviatrix troubleshooting brings to bear like what should that be like and I think Toby and I were like no no no that's going a little too high we need to get really low because the the better someone can get at actually understanding what actually happening in the network and and where to actually troubleshoot the problem how to step back each of those processes because without that it's just a big black box and they don't know you know because everything is abstracted in Amazon Internet and Azure and Google is substracted and they have these virtual gateways they have VPNs that you just don't have the logs on it's you just don't know and so then what tools can you put in front of them of where they can look because there are four logs well as long as they turned on the flow logs when they built it you know and there's like each one of those little things that well if they'd had decided to do that when they built it it's there but if you can come in later to really supplement that with training to actual troubleshoot and do a packet capture here as it's going through then teaching them how to read that even yeah Toby we were talking before he came on up on stage about your career you've been networking all your time and then you know you're now mentoring a lot of younger people how is that going because the people who come in fresh they don't have all the old war stories they don't know you talk about yeah that's never fault I walk in Mayr feet in the snow when I was your age I mean it's so easy now right they say what's your take on how you train the young piece so I've noticed two things one is that they are up to speed a lot faster in generalities of networking they can tell you what a network is in high school level now where I didn't learn that too midway through my career and they're learning it faster but they don't necessarily understand why it's that way here you know everybody thinks that it's always slash 24 for a subnet and they don't understand why you can break it down smaller why it's really necessary so the the ramp up speed is much faster for these guys that are coming in but they don't understand why and they need some of that background knowledge to see where it's coming from and why is it important and old guys that's where we thrive Jennifer you mentioned you got in from the Marines health spa when you got into networking how what was it like then and compare it now most like we've heard earlier static versus dynamic don't be static because back then you just said the network you got a perimeter yeah I know there was no such thing yeah no so back in the day I mean I mean we had banyan vines for email and you know we had token ring and I had to set up token ring networks and figure out why that didn't work because how many of things were actually sharing it but then actually just cutting fiber and running fiber cables and dropping them over you know shelters to plug them in and oh crap they swung it too hard and shattered it and how I gotta be great polished this thing and actually shoot like to see if it works I mean that was the network current five cat 5 cables to run an Ethernet you know and then from that just said network switches dumb switches like those were the most common ones you had then actually configuring routers and you know logging into a Cisco router and actually knowing how to configure that and it was funny because I had gone all the way up and was a software product manager for a while so I've gone all the way up the stack and then two and a half three years ago I came across to to work with entity group that became Victor Davis but we went to help one of our customers Avis and it was like okay so we need to fix the network okay I haven't done this in 20 years but all right let's get to it you know because it really fundamentally does not change it's still the network I mean I've had people tell me well you know when we go to containers we will not have to worry about the network and I'm like yeah you don't I do and then with this with and programmability is it really interesting so I think this brings up the certification what are some of the new things that people should be aware of that come in with the aviatrix ace certification what are some of the highlights can you guys share some of the some of the highlights around the certifications I think some of the importance is that it's it doesn't need to be vendor specific for network generality or basic networking knowledge and instead of learning how Cisco does something or how Palo Alto does something we need to understand how and why it works as a basic model and then understand how each vendor has gone about that problem and solved it in a general that's true in multi cloud as well you can't learn how cloud networking works without understanding how AWS integer and GCP are all slightly the same but slightly different and some things work and some things don't I think that's probably the number one take I think having a certification across clouds is really valuable because we heard the global s eyes cover the business issues what does it mean to do that is it code is that networking is the configuration is that aviatrix what is the I mean obviate races the ACE certifications but what is it about the multi cloud that makes it multi networking and multi vendor easy answer is yes so you got to be a general let's go to your hands and all you have to be it takes experience because it's every every cloud vendor has their own certification whether that is ops and [Music] advanced networking and advanced security or whatever it might be yeah they can take the test but they have no idea how to figure out what's wrong with that system and the same thing with any certification but it's really getting your hands in there and actually having to troubleshoot the problems you know actually work the problem you know and calm down it's going to be okay I mean because I don't know how many calls I've been on or even had aviatrix join me on it's like okay so everyone calm down let's figure out what's happening it's like we've looked at that screen three times looking at it again it's not gonna solve that problem right but at the same time you know remaining calm but knowing that it really is I'm getting a packet from here to go over here it's not working so what could be the problem you know and actually stepping them through those scenarios but that's like you only get that by having to do it you know and seeing it and going through it and then I have a question so we you know I just see it we started this program maybe six ago we're seeing a huge amount of interest I mean we're oversubscribed on all the training sessions we've got people flying from around the country even with coronavirus flying to go to Seattle to go to these events were oversubscribed good is that watching leader would put there yeah is that something that you see in your organization's are you recommending that to people do you see I mean I'm just I guess I'm surprised I'm not surprised but I'm really surprised by the demand if you would of this multi-cloud network certification because it really isn't anything like that is that something you guys can comment on or do you see the same things in your organization's I see from my side because we operate in the multi cloud environment so it really helps and it's beneficial for us yeah I think I would add that uh networking guys have always needed to use certifications to prove that they know what they know right it's not good enough to say yeah I know IP addresses or I know how a network works and a couple little check marks or a little letters by your name helps give you validity um so even in our team we can say hey you know we're using these certifications to know that you know enough of the basics and enough of the understandings that you have the tools necessary right so I guess my final question for you guys is why an eighth certification is relevant and then second part is share with the livestream folks who aren't yet a certified or might want to jump in to be AVH or certified engineers why is it important so why is it relevant and why should someone want to be an ace-certified I'm used to write engineer I think my view is a little different I think certification comes from proving that you have the knowledge not proving that you get a certification to get know I mean they're backwards so when you've got the training in the understanding and the you use that to prove and you can like grow your certification list with it versus studying for a test to get a certification and have no understanding of ok so that who is the right person that look at this is saying I'm qualified is it a network engineer is it a DevOps person what's your view you know is it a certain you know I think cloud is really the answer it's the as we talked like the edge is getting eroded so is the network initially eating eroded we're getting more and more of some network some DevOps some security lots and lots of security because network is so involved in so many of them that it's just the next progression I would say I expand that to more automation engineers because we have those nails probably extended as well well I think that the training classes themselves are helpful especially the entry-level ones for people who may be quote-unquote cloud architects but have never done anything and networking for them to understand why we need those things to really work whether or not they go through to eventually get a certification is something different but I really think fundamentally understanding how these things work it makes them a better architect makes some better application developer but even more so as you deploy more of your applications into the cloud really getting an understanding even from our people who have tradition down on Prem networking they can understand how that's going to work in the cloud - well I know we've got just under 30 seconds left but I want to get one more question and just one more for the folks watching that are you maybe younger that don't have that networking training from your experiences each of you can answer why is it should they know about networking what's the benefit what's in it for them motivate them share some insights and why they should go a little bit deeper in networking Stacy we'll start with you we'll go down let's say it's probably fundamental right if you want to deliver solutions networking use the very top I would say if you fundamental of an operating system running on a machine how those machines talk together as a fundamental change is something that starts from the base and work your way up right well I think it's a challenge because you you've come from top-down now you're gonna start looking from bottom-up and you want those different systems to cross communicate and say you built something and you're overlapping IP space not that that doesn't happen but how can I actually make that still operate without having to reappear e-platform it's like those challenges like those younger developers or sis engineers can really start to get their hands around and understand those complexities and bring that forward in their career they got to know the pilot pipes are working and some plumbing that's right works at how to code it that's right awesome thank you guys for great insights ace certain babies you're certified engineers also known as aces give a round of applause thank you okay all right that concludes my portion thank you Steve thanks for have Don thank you very much that was fantastic everybody round of applause for John for you yeah so great event great event I'm not going to take long we've got we've got lunch outside for that for the people here just a couple of things just call to action right so we saw the Aces you know for those of you out on the stream here become a certified right it's great for your career it's great for not knowledge is is fantastic it's not just an aviatrix thing it's gonna teach you about cloud networking multi-cloud networking with a little bit of aviatrix exactly what the cisco CCIE program was for IP network that type of the thing that's number one second thing is is is is learn right so so there's a there's a link up there for the four to join the community again like I started this this is a community this is the kickoff to this community and it's a movement so go to what a v8 community a bh6 comm was starting a community at multi cloud so you know get get trained learn I'd say the next thing is we're doing over a hundred seminars in across the United States and also starting into Europe soon will come out and will actually spend a couple hours and talk about architecture and talk about those beginning things for those of you on the you know on the livestream in here as well you know we're coming to a city near you go to one of those events it's a great way to network with other people that are in the industry as well as start to learn and get on that multi-cloud journey and then I'd say the last thing is you know we haven't talked a lot about what aviatrix does here and that's intentional we want you you know leaving with wanting to know more and schedule get with us in schedule a multi our architecture workshop session so we we sit out with customers and we talk about where they're at in that journey and more important where they're going and to find that end state architecture from networking compute storage everything and everything you heard today every panel kept talking about architecture talking about operations those are the types of things that we saw we help you cook define that canonical architecture that system architecture that's yours so for so many of our customers they have three by five plotted lucid charts architecture drawings and it's the customer name slash aviatrix arc network architecture and they put it on their whiteboard that's what what we and that's the most valuable thing they get from us so this becomes their 20-year network architecture drawing that they don't do anything without talking to us and look at that architecture that's what we do in these multi hour workshop sessions with customers and that's super super powerful so if you're interested definitely call us and let's schedule that with our team so anyway I just want to thank everybody on the livestream thank everybody here hopefully it was it was very useful I think it was and joined the movement and for those of you here join us for lunch and thank you very much [Applause] [Music] [Applause] [Music] you

>> Live from San Francisco it's theCUBE. Covering IBM Think 2019, brought to you by IBM. (electronic beat music) >> Welcome back to theCUBE. We are live at IBM Think 2019 in soggy San Francisco. I'm Lisa Martin, with Dave Vellante. Dave, I hope you brought a big umbrella today. >> Well luckily the Marriott lent me one, so-- >> I got one from my hotel, too. And what a perfect day to day have the hybrid, multi-cloud open upon us, shower San Francisco with rain, and talk about weather with an IBM expert. Mark Gildersleeve, welcome to the Cube. You are Vice President, Head of Business Solutions, and Watson Media, The Weather Company. >> Thank you for having me. >> Our pleasure, so, we think IBM, this is the second annual IBM Think. There's about what, 30,000 people here, 2,000 plus business and technical sessions. There is a lot, a broad spectrum, no pun intended, of topics to cover, but excited to talk with you today about what IBM is doing in the agriculture industry. Let's talk about it from the growers perspective first, and we'll cover some other, other outlets. But, what are some of the challenges that growers are facing in 2019? >> So, first of all, if you think about it, this is a really sporty industry for growers to be in. They've got to worry about things that they can't have any control over: the weather, pest and disease, government regulation, trade, commodity pricing, there's a lot that they can't control. To make matters worse, they have very slim margins, okay, and they had to learn all these various aspects of technology to try to become better. And so, they're almost drowning in data, trying to figure out what do I do about it to get more yield, to get more profitability, to get better quality? There's a lot of challenges that they're wrestling with today. (people chattering) >> Well this is a huge problem, because the, the amount of farmable land isn't growing. It's essentially flat. >> It's flat. >> Maybe it's even shrinking. >> It's flat. >> They're talking with a multi-decade, 20, 30-year time frame. Population growth, we're talking about another two, two and a half billion people over the next three decades. So, something's got to give. What does the data say? >> So you're exactly correct, the estimates of population growth are 2.3 billion between now and 2050. That's 30% population growth. With zero incremental air-able lands, so, huge yeah. So we have to get yields, at least 30% higher. Okay, so if you think about that problem we're not going to get that yield increase status quo. We're not going to get that yield increase without having a much more data and an AI driven approach to agriculture, and that's exactly what we're doing. Our solution right now has 14 different AI and analytic capabilities inserted into it. Just to try to help growers, for one, make sense of their data and make better decisions to try and get their yield up, their profit up, their quality up. >> And is there enough in your estimation markers, is there enough head room actually to accommodate that population growth, given the constraints? >> Absolutely, taking a simple example of being a corn grower in the U.S. The average corn grower gets 175 bushels per acre, but the 70th percentile gets like 250, okay? So, if we got in, in the example of corn, every person that's at the 50th percentile, up to the 70th percentile, which is extremely doable. You can, you are, by definition, increasing the yield 30% in that case. So, it's doable, and we can see examples of growers doing it today. But what you have to understand is that 70% of the differences in performance between growers are just their farming practices. So, we have to get a handle on what farming practices drive better yield. We have to get those people at 50% to 70%. The people at 30% up to 50. We just have to get them about 20 points better in the benchmarking, and we will actually solve this problem from a U.S. perspective, then we have to do different things for other parts of the world. >> Now there's a multi-variable problem here as well though, because you got consumer patterns changing, people want, you know, more sustainable. You go into the grocery store now, you see all grass-fed, or free-range, and, so that takes up more land. Do consumer, how do consumer preferences, and the shifting consumer preferences factor in? >> It's the biggest change I think that's happened in this industry in the last 20 years. If you look at 20 years ago, 30 years ago, the tech chains were being driven kind of more from the ag-input side, and that's kind of the people that are selling to the growers. Now, we have the food companies hearing from consumers that they want sustainable, they want better quality, they want more nutrition, they want to understand how to have less chemicals going into their food. Okay, now we have the buyers of the growers, pushing on those growers to say you need to give me a better product. This change of consumers, and this ripple through the food eco-system is the big change. And the food companies are at the center of this revolution. And it's actually really interesting, and I think it actually will knit together this whole ag-eco-system, so that you now have to worry about the ag input people, the growers, the food companies, and the retailers, the bankers and the insurers, all kind of understanding, and coming together to figure out how to get better product to the consumers, and also, by the way, increase the yield so they can solve the food production problem. >> So, where do you start? Are you talking, what's the lowest hanging fruit? Is it going to the large-scale growers that have more resources, potentially resources that understand technology enough to start at that source? What about the smaller scale farmer growers? >> So, I think that, we have IBM clients that are interested in solving every aspect of the kind of size of foreign problem. So, I met with one organization from Africa today. In Africa, it's all a small farmer problem, right? And, and the vast bulk of growers in the world are small farmers, okay? But when we're looking at kind of solving the problem overall, we want to start with the food companies, and the people in finance. Because, right now, food companies, when they're trying to deal with their growers, they're trying to manage these growers with spreadsheets. Even though these are very sophisticated companies, very sophisticated. We need to help those food companies better understand what's going on the field. What chemicals that are going onto the land? When was the crop planted? When is it going to be harvested? When can I expect it in my storage facility? And they really want to understand, what are the farmers doing that are giving them the best quality crop? And how can they learn from the data, to get best practices for all the rest of their growers? If we start with the food companies, and have them work with their growers and the agronomists, that's going to be the best way to introduce change into this sector, I believe. >> And they're kind of the the pivot point between the consumer, they understand the consumer demand, they can feed that back to the farmers. Of course, they're ultimate goal is to make a profit. But look at it, if you give the people what they want, there's going to be a way to make money here. It's just, it's not going to be the same way that they've made money for the past 50 years. >> Exact, exactly right. But you know, take an example, in my house, we buy organic milk, okay? We're paying a premium for organic milk. We're willing to pay a premium. >> Happy to do so, yup. >> Happy to do it. We feel like it tastes better. We feel good about also the quality of it. So, I think in many cases, food companies are willing to pay a premium to growers to deliver a very specific crop to them. And so, this issue of food companies having more growers under contract, and working with those growers to deliver a better product, is of high interest to virtually every food company, every beer company that we've talked to. Every retailer that's worrying about the supermarket shelves. They're all worried about trying to get better product to the shelf, 'cause that's what the consumers are asking for. There is money, in this system, if you get the quality up. So that's really what we're focusing on with the food companies. >> People happy to pay for that and this eco-system is actually quite interesting. You talk a bit about, you talked about the banks. They're, even health care is part of the eco-system. >> It's the other constituent. >> They've said that people start making better food choices. It could ripple through to health effects. So, maybe you're paying more, as a consumer, for an individual product, but you could be living longer, having better health, maybe having lower health care costs. >> One analogy that I think you might find interesting, is that, just as all of us have an electronic medical record, that has all the images that would have been taken of our body, like an MRI, or our health history, our hospitalizations, what surgeries we've had. We're now, as IBM, bringing the electronic field record, which is an exact analogy to the electronic medical record, but it's about the field. What's been grown there? What have been the yields? What are the chemicals? When was the crop planted? What kind of tillage practices are being used? And we're trying to, essentially build that database of the electronic field record as the cornerstone for all the analytics for the AI that we're building, and running against, to help figure out benchmarks for all the corn growers in U.S.A., or the potato growers in the Netherlands. And beyond the benchmarks, best practices, so that we can say, what are the people that are 70th percentile doing, that the people that are 30th percentile aren't doing? We can bring all those people up. It's very cool. >> So we're talking about IBM, the computer company, right? So, what's the big picture of IBM's role? Obviously, there's a data angle. But what's the IBM story here? The holistic story. >> So, first pillar is data. Every piece of data coming off of a combine or a sprayer, so the equipment data, the machine data. All the environmental data, remotely-sensed data, soil-sensed data, stuff that's going on to the field, as well as the farm practices. So, there's a whole data story that, who better than IBM to handle massive amounts of data? Secondly, AI and analytics, right? So, we've got 13 or 14 different analytics and AI products embedded in our decision platform. All intending to give that grower a better first guess, a better recommendation of, here's what the data tells us about your field. It's still up to the grower and the agronomist to make the final call, but we can give them a much better guess than they have just based on their own personal fields experience. Then lastly, it's decisions that we can help that grower make. So, an example would be: we can help a banker understand exactly what crop is being grown on a piece of land without having the banker have to send somebody out and look at it. So, they can understand compliance-wise, Was a loan that I wrote being used in the purpose that was intended? But there are many enterprise examples of that. So it's data, AI, decisions. And that's then connected across the eco-system. It's a great IBM story 'cause we've been in business, we've been serving the USDA for 91 years. We've been in agriculture a long time. Lots of people in IBM don't know it, but we've been at this a long time. >> And if we look at the growers for a second, this is really kind of where it all starts, right? I understand this triangulation, and the constituents that are involved from the food companies, to the retailers, to the bankers. But, if we look at the growers, what are some of the benefits? Do you have a favorite success story where, whether it's a large-scale grower or something smaller, where their, maybe their loan terms are better? Or they have lower costs? Or they're actually making a better impact on the environment? What's your favorite grower impact story? >> There are lots actually, but let's pick a few. The first is, we have a lot of aspects of crop protection, where we can use satellite imagery to figure out where a crop is under stress. Where, what part of the field is under stress. Help them go out and scout that field. Take a picture with their smart phone and have Watson tell you what the disease is that's infecting that crop. And, essentially, be able to take faster action. When you're faster with crop protection, you are saving a lot of your crop. You get better yield, that's money in the bank. So crop protection is one. A second example is, with best practices, showing some of these growers what the 70th percentile growers are doing, that the 50th percentile guys are not doing. You can say, here are the four things that these 70th percentile guys are doing. You should try those four things. Or you might want to try two of them this year, two of them next year. But best practice is a huge impact. The last impact is, we help people with yield. So, we can now say okay, this is the projected yield that you're going to have at the end of the season. Here's what you can sell at the middle of the season. Here's what you're going to be able to sell at the end of the season. And we help them with market timing. Trading profitability can be easily 20, 30 bucks of incremental profit per acre. So, there's kind of a financial angle, there's a best practices angle, and there's a protecting your field angle, as the three examples I give you. >> Well, and that's huge from the standpoint of the debt loads that farmers face around the world. Over a trillion dollars in debt, in just, you know, a few countries. What does the future hold from that standpoint? What are the implications of that debt load? Obviously there's an imperative to improve yields and improve profitability, but your thoughts? >> So, first of all, you're correct that debt is a really enormous issue. So, for example, there's an article in the Wall Street Journal last week. Bankruptcies are at the highest level in the U.S. since the crash of 2008. So, this debt load, and the debt service is a really large problem. Here's how I'd like to try to focus it. Many growers have been taught to worry about better yield. When we should have been focusing more on better profit per acre. There are two ways you can get out that profit per acre. One is, you can do things with new chance fertilization, seed type, plant date, that can drive your yield better. But the other aspect is, there are parts of your land that are going to be lower productivity potential. Your smartest move is to put less inputs on those portions of the land and double down on the inputs on the highest productivity areas of the land. Because most farmers don't understand that there's 25% of their land, where they're actually losing money, and they'd be better to actually not be planting. But instead the idea is, plant at a lower population rate, put less input costs in, and then you can even make that area of less productive land profitable. If we improve the profitability of these growers, they can afford the debt service, and that's kind of the way to do it. The other aspect is that, everybody that's doing contract growing for a given food company is getting a premium on their crop. Oftentimes, 10%, or even 15% premium. That 10%, or 15%, solves the problem of the debt service for almost every grower, in the U.S. that's doing zero crops. >> That focus on profitability versus pure yield per acre. That's potentially involves a a different crop? And a shifting strategy? >> Usually it's a different farming practice. So, it's applying variable rate technology. It's essentially understanding how to treat each aspect of your field differently so that you're not treating it homogeneously. But you're actually saying, I'm going to do this practice, and with this level of input costs down over here, in this section of the land. And do a different practice over here. Because, every piece of land has low productivity areas, high productivity areas, and areas that are either high or low, depending on the weather. Understanding how the land varies is a huge data insight that we give growers with our data insights using AI. >> And that can drop right to the bottom line, obviously. >> It's all bottom line, baby. >> Last question before we have to wrap, this is, I feel like we're scratching just the surface here, of such an interesting topic of, and the massive global implications of IBM and agriculture can have on all of us. Where can people go on the IBM website for example, to learn more about this? >> You can go to the, well, so at the Think, there are a number of sections actually that we have right now. Talks that we're giving later on Friday morning. All related to the Watson Decision Platform for Agriculture. And there's material at the Think exhibit stuff that you can go to. We're also exhibiting in the Watson Media and Weather section downstairs. We'd ask everybody to come there. >> Excellent, well Mark, thanks so much for joining Dave and me on the program today, really interesting conversation. >> Great story. >> Thank you for having me. >> Our pleasure. We want to thank you for watching the Cube, I'm Lisa Martin, with Dave Vellante. Live, from IBM Think 2019. Stick around, we'll be right back shortly with our next guest. (electronic music beat)

>> Live from Times Square in New York City, it's theCUBE, covering IBM's Change the Game, Winning with AI, brought to you by IBM. >> Hi everybody, welcome back to theCUBE's special presentation. We're here at the Western Hotel and the theater district covering IBM's announcements. They've got an analyst meeting today, partner event. They've got a big event tonight. IBM.com/winwithAI, go to that website, if you're in town register. You can watch the webcast online. You'll see this very cool play of Vince Lombardy, one of his famous plays. It's kind of a power sweep right which is a great way to talk about sort of winning and with X's and O's. So anyway, Daniel Hernandez is here the vice president of IBM analytics, long time Cube along. It's great to see you again, thanks for coming on. >> My pleasure Dave. >> So we've talked a number of times. We talked earlier this year. Give us the update on momentum in your business. You guys are doing really well, we see this in the quadrants and the waves, but your perspective. >> Data science and AI, so when we last talked we were just introducing something called IBM Club Private for data. The basic idea is anybody that wants to do data science, data engineering or building apps with data anywhere, we're going to give them a single integrated platform to get that done. It's going to be the most efficient, best way to do those jobs to be done. We introduced it, it's been a resounding success. Been rolling that out with clients, that's been a whole lot of fun. >> So we talked a little bit with Rob Thomas about some of the news that you guys have, but this is really your wheelhouse so I'm going to drill down into each of these. Let's say we had Rob Beerden on yesterday on our program and he talked a lot about the IBM Red Hat and Hortonworks relationship. Certainly they talked about it on their earnings call and there seems to be clear momentum in the marketplace. But give us your perspective on that announcement. What exactly is it all about? I mean it started kind of back in the ODPI days and it's really evolved into something that now customers are taking advantage of. >> You go back to June last year, we entered into a relationship with Hortonworks where the basic primacy, was customers care about data and any data driven initiative was going to require data science. We had to do a better job bringing these eco systems, one focused on kind of Hadoop, the other one on classic enterprise analytical and operational data together. We did that last year. The other element of that was we're going to bring our data science and machine learning tools and run times to where the data is including Hadoop. That's been a resounding success. The next step up is how do we proliferate that single integrated stack everywhere including private Cloud or preferred Clouds like Open Shift. So there was two elements of the announcement. We did the hybrid Cloud architecture initiative which is taking the Hadoop data stack and bringing it to containers and Kubernetes. That's a big deal for people that want to run the infrastructure with Cloud characteristics. And the other was we're going to bring that whole stack onto Open Shift. So on IBM's side, with IBM Cloud Private for data we are driving certification of that entire stack on OpenShift so any customer that's betting on OpenShift as their Cloud infrastructure can benefit from that and the single integrated data stack. It's a pretty big deal. >> So OpenShift is really interesting because OpenShift was kind of quiet for awhile. It was quiest if you will. And then containers come on the scene and OpenShift has just exploded. What are your perspectives on that and what's IBM's angle on OpenShift? >> Containers of Kubernetes basically allow you to get Cloud characteristics everywhere. It used to be locked in to kind of the public Cloud or SCP providers that were offering as a service whether PAS OR IAS and Docker and Kubernetes are making the same underline technology that enabled elasticity, pay as you go models available anywhere including your own data center. So I think it explains why OpenShift, why IBM Cloud Private, why IBM Club Private for data just got on there. >> I mean the Core OS move by Red Hat was genius. They picked that up for the song in our view anyway and it's really helped explode that. And in this world, everybody's talking about Kubernetes. I mean we're here at a big data conference all week. It used to be Hadoop world. Everybody's talking about containers, Kubernetes and Multi cloud. Those are kind of the hot trends. I presume you've seen the same thing. >> 100 percent. There's not a single client that I know, and I spend the majority of my time with clients that are running their workloads in a single stack. And so what do you do? If data is an imperative for you, you better run your data analytic stack wherever you need to and that means Multi cloud by definition. So you've got a choice. You can say, I can port that workload to every distinct programming model and data stack or you can have a data stack everywhere including Multi clouds and Open Shift in this case. >> So thinking about the three companies, so Hortonworks obviously had duped distro specialists, open source, brings that end to end sort of data management from you know Edge, or Clouds on Prim. Red Hat doing a lot of the sort of hardcore infrastructure layer. IBM bringing in the analytics and really empowering people to get insights out of data. Is that the right way to think about that triangle? >> 100 percent and you know with the Hortonworks and IBM data stacks, we've got our common services, particularly you're on open meta data which means wherever your data is, you're going to know about it and you're going to be able to control it. Privacy, security, data discovery reasons, that's a pretty big deal. >> Yeah and as the Cloud, well obviously the Cloud whether it's on Prim or in the public Cloud expands now to the Edge, you've also got this concept of data virtualization. We've talked about this in the past. You guys have made some announcements there. But let's put a double click on that a little bit. What's it all about? >> Data virtualization been going on for a long time. It's basic intent is to help you access data through whatever tools, no matter where the data is. Traditional approaches of data virtualization are pretty limiting. So they work relatively well when you've got small data sets but when you've got highly fragmented data, which is the case in virtually every enterprise that exists a lot of the undermined technology for data virtualization breaks down. Data coming through a single headnote. Ultimately that becomes the critical issue. So you can't take advantage of data virtualization technologies largely because of that when you've got wide scale deployments. We've been incubating technology under this project codename query plex, it was a code name that we used internally and that we were working with Beta clients on and testing it out, validating it technically and it was pretty clear that this is a game changing method for data virtualization that allows you to drive the benefits of accessing your data wherever it is, pushing down queries where the data is and getting benefits of that through highly fragmented data landscape. And so what we've done is take that extremely innovated next generation data virtualization technology include it in our data platform called IBM Club Private for Data, and made it a critical feature inside of that. >> I like that term, query plex, it reminds me of the global sisplex. I go back to the days when actually viewing sort of distributed global systems was very, very challenging and IBM sort of solved that problem. Okay, so what's the secret sauce though of query plex and data virtualization? How does it all work? What's the tech behind it? >> So technically, instead of data coming and getting funneled through one node. If you ever think of your data as kind of a graph of computational data nodes. What query plex does is take advantage of that computational mesh to do queries and analytics. So instead of bringing all the data and funneling it through one of the nodes, and depending on the computational horsepower of that node and all the data being able to get to it, this just federates it out. It distributes out that workload so it's some magic behind the scenes but relatively simple technique. Low computing aggregate, it's probably going to be higher than whatever you can put into that single node. >> And how do customers access these services? How long does it take? >> It would look like a standard query interface to them. So this is all magic behind the scenes. >> Okay and they get this capability as part of what? IBM's >> IBM's Club Private for Data. It's going to be a feature, so this project query plex, is introduced as next generation data virtualization technology which just becomes a part of IBM Club Private for Data. >> Okay and then the other announcement that we talked to Rob, I'd like to understand a little bit more behind it. Actually before we get there, can we talk about the business impact of query plex and data virtualization? Thinking about it, it dramatically simplifies the processes that I have to go through to get data. But more importantly, it helps me get a handle on my data so I can apply machine intelligence. It seems like the innovation sandwich if you will. Data plus AI and then Cloud models for scale and simplicity and that's what's going to drive innovation. So talk about the business impact that people are excited about with regard to query plex. >> Better economics, so in order for you to access your data, you don't have to do ETO in this particular case. So data at rest getting consumed because of this online technology. Two performance, so because of the way this works you're actually going to get faster response times. Three, you're going to be able to query more data simply because this technology allows you to access all your data in a fragmented way without having to consolidate it. >> Okay, so it eliminates steps, right, and gets you time to value and gives you a bigger corporate of data that you can the analyze and drive inside. >> 100 percent. >> Okay, let's talk about stack overflow. You know, Rob took us through a little bit about what that's, what's going on there but why stack overflow, you're targeting developers? Talk to me more about that. >> So stack overflow, 50 million active developers each month on that community. You're a developer and you want to know something, you have to go to stack overflow. You think about data science and AI as disciplines. The idea that that is only dermained to AI and data scientists is very limiting idea. In order for you to actually apply artificial intelligence for whatever your use case is instead of a business it's going to require multiple individuals working together to get that particular outcome done including developers. So instead of having a distinct community for AI that's focused on AI machine developers, why not bring the artificial intelligence community to where the developers already are, which is stack overflow. So, if you go to AI.stackexchange.com, it's going to be the place for you to go to get all your answers to any question around artificial intelligence and of course IBM is going to be there in the community helping out. >> So it's AI.stackexchange.com. You know, it's interesting Daniel that, I mean to talk about digital transformation talking about data. John Furrier said something awhile back about the dots. This is like five or six years ago. He said data is the new development kit and now you guys are essentially targeting developers around AI, obviously a data centric. People trying to put data at the core of the organization. You see that that's a winning strategy. What do you think about that? >> 100 percent, I mean we're the data company instead of IBM, so you're probably asking the wrong guy if you think >> You're biased. (laughing) >> Yeah possibly, but I'm acknowledged. The data over opinions. >> Alright, tell us about tonight what we can expect? I was referencing the Vince Lombardy play here. You know, what's behind that? What are we going to see tonight? >> We were joking a little bit about the old school power eye formation, but that obviously works for your, you're a New England fan aren't you? >> I am actually, if you saw the games this weekend Pat's were in the power eye for quite a bit of the game which I know upset a lot of people. But it works. >> Yeah, maybe we should of used it as a Dallas Cowboy team. But anyways, it's going to be an amazing night. So we're going to have a bunch of clients talking about what they're doing with AI. And so if you're interested in learning what's happening in the industry, kind of perfect event to get it. We're going to do some expert analysis. It will be a little bit of fun breaking down what those customers did to be successful and maybe some tips and tricks that will help you along your way. >> Great, it's right up the street on the west side highway, probably about a mile from the Javis Center people that are at Strata. We've been running programs all week. One of the themes that we talked about, we had an event Tuesday night. We had a bunch of people coming in. There was people from financial services, we had folks from New York State, the city of New York. It was a great meet up and we had a whole conversation got going and one of the things that we talked about and I'd love to get your thoughts and kind of know where you're headed here, but big data to do all that talk and people ask, is that, now at AI, the conversation has moved to AI, is it same wine, new bottle, or is there something substantive here? The consensus was, there's substantive innovation going on. Your thoughts about where that innovation is coming from and what the potential is for clients? >> So if you're going to implement AI for let's say customer care for instance, you're going to be three wrongs griefs. You need data, you need algorithms, you need compute. With a lot of different structure to relate down to capture data wasn't captured until the traditional data systems anchored by Hadoop and big data movement. We landed, we created a data and computational grid for that data today. With all the advancements going on in algorithms particularly in Open Source, you now have, you can build a neuro networks, you can do Cisco machine learning in any language that you want. And bringing those together are exactly the combination that you need to implement any AI system. You already have data and computational grids here. You've got algorithms bringing them together solving some problem that matters to a customer is like the natural next step. >> And despite the skills gap, the skill gaps that we talked about, you're seeing a lot of knowledge transfer from a lot of expertise getting out there into the wild when you follow people like Kirk Born on Twitter you'll see that he'll post like the 20 different models for deep learning and people are starting to share that information. And then that skills gap is closing. Maybe not as fast as some people like but it seems like the industry is paying attention to this and really driving hard to work toward it 'cause it's real. >> Yeah I agree. You're going to have Seth Dulpren, I think it's Niagara, one of our clients. What I like about them is the, in general there's two skill issues. There's one, where does data science and AI help us solve problems that matter in business? That's really a, trying to build a treasure map of potential problems you can solve with a stack. And Seth and Niagara are going to give you a really good basis for the kinds of problems that we can solve. I don't think there's enough of that going on. There's a lot of commentary communication actually work underway in the technical skill problem. You know, how do I actually build these models to do. But there's not enough in how do I, now that I solved that problem, how do we marry it to problems that matter? So the skills gap, you know, we're doing our part with our data science lead team which Seth opens which is telling a customer, pick a hard problem, give us some data, give us some domain experts. We're going to be in the AI and ML experts and we're going to see what happens. So the skill problem is very serious but I don't think it's most people are not having the right conversations about it necessarily. They understand intuitively there's a tech problem but that tech not linked to a business problem matters nothing. >> Yeah it's not insurmountable, I'm glad you mentioned that. We're going to be talking to Niagara Bottling and how they use the data science elite team as an accelerant, to kind of close that gap. And I'm really interested in the knowledge transfer that occurred and of course the one thing about IBM and companies like IBM is you get not only technical skills but you get deep industry expertise as well. Daniel, always great to see you. Love talking about the offerings and going deep. So good luck tonight. We'll see you there and thanks so much for coming on theCUBE. >> My pleasure. >> Alright, keep it right there everybody. This is Dave Vellanti. We'll be back right after this short break. You're watching theCUBE. (upbeat music)

>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE! Now, here's your host, Dave Vellante. >> Hi, everybody, welcome to this special CUBE Conversation. You know, big data workloads have evolved, and the infrastructure that runs big data workloads is also evolving. Big data, AI, other emerging workloads need infrastructure that can keep up. Welcome to this special CUBE Conversation with Patrick Osborne, who's the vice president and GM of big data and secondary storage at Hewlett Packard Enterprise, @patrick_osborne. Great to see you again, thanks for coming on. >> Great, love to be back here. >> As I said up front, big data's changing. It's evolving, and the infrastructure has to also evolve. What are you seeing, Patrick, and what's HPE seeing in terms of the market forces right now driving big data and analytics? >> Well, some of the things that we see in the data center, there is a continuous move to move from bare metal to virtualized. Everyone's on that train. To containerization of existing apps, your apps of record, business, mission-critical apps. But really, what a lot of folks are doing right now is adding additional services to those applications, those data sets, so, new ways to interact, new apps. A lot of those are being developed with a lot of techniques that revolve around big data and analytics. We're definitely seeing the pressure to modernize what you have on-prem today, but you know, you can't sit there and be static. You gotta provide new services around what you're doing for your customers. A lot of those are coming in the form of this Mode 2 type of application development. >> One of the things that we're seeing, everybody talks about digital transformation. It's the hot buzzword of the day. To us, digital means data first. Presumably, you're seeing that. Are organizations organizing around their data, and what does that mean for infrastructure? >> Yeah, absolutely. We see a lot of folks employing not only technology to do that. They're doing organizational techniques, so, peak teams. You know, bringing together a lot of different functions. Also, too, organizing around the data has become very different right now, that you've got data out on the edge, right? It's coming into the core. A lot of folks are moving some of their edge to the cloud, or even their core to the cloud. You gotta make a lot of decisions and be able to organize around a pretty complex set of places, physical and virtual, where your data's gonna lie. >> There's a lot of talk, too, about the data pipeline. The data pipeline used to be, you had an enterprise data warehouse, and the pipeline was, you'd go through a few people that would build some cubes and then they'd hand off a bunch of reports. The data pipeline, it's getting much more complex. You've got the edge coming in, you've got, you know, core. You've got the cloud, which can be on-prem or public cloud. Talk about the evolution of the data pipeline and what that means for infrastructure and big data workloads. >> For a lot of our customers, and we've got a pretty interesting business here at HPE. We do a lot with the Intelligent Edge, so, our Edgeline servers in Aruba, where a a lot of the data is sitting outside of the traditional data center. Then we have what's going on in the core, which, for a lot of customers, they are moving from either traditional EDW, right, or even Hadoop 1.0 if they started that transformation five to seven years ago, to, a lot of things are happening now in real time, or a combination thereof. The data types are pretty dynamic. Some of that is always getting processed out on the edge. Results are getting sent back to the core. We're also seeing a lot of folks move to real-time data analytics, or some people call it fast data. That sits in your core data center, so utilizing things like Kafka and Spark. A lot of the techniques for persistent storage are brand new. What it boils down to is, it's an opportunity, but it's also very complex for our customers. >> What about some of the technical trends behind what's going on with big data? I mean, you've got sprawl, with both data sprawl, you've got workload sprawl. You got developers that are dealing with a lot of complex tooling. What are you guys seeing there, in terms of the big mega-trends? >> We have, as you know, HPE has quite a few customers in the mid-range in enterprise segments. We have some customers that are very tech-forward. A lot of those customers are moving from this, you know, Hadoop 1.0, Hadoop 2.0 system to a set of essentially mixed workloads that are very multi-tenant. We see customers that have, essentially, a mix of batch-oriented workloads. Now they're introducing these streaming type of workloads to folks who are bringing in things like TensorFlow and GPGPUs, and they're trying to apply some of the techniques of AI and ML into those clusters. What we're seeing right now is that that is causing a lot of complexity, not only in the way you do your apps, but the number of applications and the number of tenants who use that data. It's getting used all day long for various different, so now what we're seeing is it's grown up. It started as an opportunity, a science project, the POC. Now it's business-critical. Becoming, now, it's very mission-critical for a lot of the services that drives. >> Am I correct that those diverse workloads used to require a bespoke set of infrastructure that was very siloed? I'm inferring that technology today will allow you to bring those workloads together on a single platform. Is that correct? >> A couple of things that we offer, and we've been helping customers to get off the complexity train, but provide them flexibility and elasticity is, a lot of the workloads that we did in the past were either very vertically-focused and integrated. One app server, networking, storage, to, you know, the beginning of the analytics phase was really around symmetrical clusters and scaling them out. Now we've got a very rich and diverse set of components and infrastructure that can essentially allow a customer to make a data lake that's very scalable. Compute, storage-oriented nodes, GPU-oriented nodes, so it's very flexible and helps us, helps the customers take complexity out of their environment. >> In thinking about, when you talk to customers, what are they struggling with, specifically as it relates to infrastructure? Again, we talked about tooling. I mean, Hadoop is well-known for the complexity of the tooling. But specifically from an infrastructure standpoint, what are the big complaints that you hear? >> A couple things that we hear is that my budget's flat for the next year or couple years, right? We talked earlier in the conversation about, I have to modernize, virtualize, containerizing my existing apps, that means I have to introduce new services as well with a very different type of DevOps, you know, mode of operations. That's all with the existing staff, right? That's the number one issue that we hear from the customers. Anything that we can do to help increase the velocity of deployment through automation. We hear now, frankly, the battle is for whether I'm gonna run these type of workloads on-prem versus off-prem. We have a set of technology as well as services, enabling services with Pointnext. You remember the acquisition we made around cloud technology partners to right-place where those workloads are gonna go and become like a broker in that conversation and assist customers to make that transition and then, ultimately, give them an elastic platform that's gonna scale for the diverse set of workloads that's well-known, sized, easy to deploy. >> As you get all this data, and the data's, you know, Hadoop, it sorta blew up the data model. Said, "Okay, we'll leave the data where it is, "we'll bring the compute there." You had a lot of skunk works projects growing. What about governance, security, compliance? As you have data sprawl, how are customers handling that challenge? Is it a challenge? >> Yeah, it certainly is a challenge. I mean, we've gone through it just recently with, you know, GDPR is implemented. You gotta think about how that's gonna fit into your workflow, and certainly security. The big thing that we see, certainly, is around if the data's residing outside of your traditional data center, that's a big issue. For us, when we have Edgeline servers, certainly a lot of things are coming in over wireless, there's a big buildout in advent of 5G coming out. That certainly is an area that customers are very concerned about in terms of who has their data, who has access to it, how can you tag it, how can you make sure it's secure. That's a big part of what we're trying to provide here at HPE. >> What specifically is HPE doing to address these problems? Products, services, partnerships, maybe you could talk about that a little bit. Maybe even start with, you know, what's your philosophy on infrastructure for big data and AI workloads? >> I mean, for us, we've over the last two years have really concentrated on essentially two areas. We have the Intelligent Edge, which is, certainly, it's been enabled by fantastic growth with our Aruba products in the networks in space and our Edgeline systems, so, being able to take that type of compute and get it as far out to the edge as possible. The other piece of it is around making hybrid IT simple, right? In that area, we wanna provide a very flexible, yet easy-to-deploy set of infrastructure for big data and AI workloads. We have this concept of the Elastic Platform for Analytics. It helps customers deploy that for a whole myriad of requirements. Very compute-oriented, storage-oriented, GPUs, cold and warm data lakes, for that matter. And the third area, what we've really focused on is the ecosystem that we bring to our customers as a portfolio company is evolving rapidly. As you know, in this big data and analytics workload space, the software development portion of it is super dynamic. If we can bring a vetted, well-known ecosystem to our customers as part of a solution with advisory services, that's definitely one of the key pieces that our customers love to come to HP for. >> What about partnerships around things like containers and simplifying the developer experience? >> I mean, we've been pretty public about some of our efforts in this area around OneSphere, and some of these, the models around, certainly, advisory services in this area with some recent acquisitions. For us, it's all about automation, and then we wanna be able to provide that experience to the customers, whether they want to develop those apps and deploy on-prem. You know, we love that. I think you guys tag it as true private cloud. But we know that the reality is, most people are embracing very quickly a hybrid cloud model. Given the ability to take those apps, develop them, put them on-prem, run them off-prem is pretty key for OneSphere. >> I remember Antonio Neri, when you guys announced Apollo, and you had the astronaut there. Antonio was just a lowly GM and VP at the time, and now he's, of course, CEO. Who knows what's in the future? But Apollo, generally at the time, it was like, okay, this is a high-performance computing system. We've talked about those worlds, HPC and big data coming together. Where does a system like Apollo fit in this world of big data workloads? >> Yeah, so we have a very wide product line for Apollo that helps, you know, some of them are very tailored to specific workloads. If you take a look at the way that people are deploying these infrastructures now, multi-tenant with many different workloads. We allow for some compute-focused systems, like the Apollo 2000. We have very balanced systems, the Apollo 4200, that allow a very good mix of CPU, memory, and now customers are certainly moving to flash and storage-class memory for these type of workloads. And then, Apollo 6500 were some of the newer systems that we have. Big memory footprint, NVIDIA GPUs allowing you to do very high calculations rates for AI and ML workloads. We take that and we aggregate that together. We've made some recent acquisitions, like Plexxi, for example. A big part of this is around simplification of the networking experience. You can probably see into the future of automation of the networking level, automation of the compute and storage level, and then having a very large and scalable data lake for customers' data repositories. Object, file, HTFS, some pretty interesting trends in that space. >> Yeah, I'm actually really super excited about the Plexxi acquisition. I think it's because flash, it used to be the bottleneck was the spinning disk, flash pushes the bottleneck largely to the network. Plexxi gonna allow you guys to scale, and I think actually leapfrog some of the other hyperconverged players that are out there. So, super excited to see what you guys do with that acquisition. It sounds like your focus is on optimizing the design for I/O. I'm sure flash fits in there as well. >> And that's a huge accelerator for, even when you take a look at our storage business, right? So, 3PAR, Nimble, All-Flash, certainly moving to NVMe and storage-class memory for acceleration of other types of big data databases. Even though we're talking about Hadoop today, right now, certainly SAP HANA, scale-out databases, Oracle, SQL, all these things play a part in the customer's infrastructure. >> Okay, so you were talking before about, a little bit about GPUs. What is this HPE Elastic Platform for big data analytics? What's that all about? >> I mean, we have a lot of the sizing and scalability falls on the shoulders of our customers in this space, especially in some of these new areas. What we've done is, we have, it's a product/a concept, and what we do is we have this, it's called the Elastic Platform for Analytics. It allows, with all those different components that I rattled off, all great systems in of their own, but when it comes to very complex multi-tenant workloads, what we do is try to take the mystery out of that for our customers, to be able to deploy that cookie-cutter module. We're even gonna get to a place pretty soon where we're able to offer that as a consumption-based service so you don't have to choose for an elastic type of acquisition experience between on-prem and off-prem. We're gonna provide that as well. It's not only a set of products. It's reference architectures. We do a lot of sizing with our partners. The Hortonworks, CloudEra's, MapR's, and a lot of the things that are out in the open source world. It's pretty good. >> We've been covering big data, as you know, for a long, long time. The early days of big data was like, "Oh, this is great, "we're just gonna put white boxes out there "and off the shelf storage!" Well, that changed as big data got, workloads became more enterprise, mainstream, they needed to be enterprise-ready. But my question to you is, okay, I hear you. You got products, you got services, you got perspectives, a philosophy. Obviously, you wanna sell some stuff. What has HPE done internally with regard to big data? How have you transformed your own business? >> For us, we wanna provide a really rich experience, not just products. To do that, you need to provide a set of services and automation, and what we've done is, with products and solutions like InfoSight, we've been able to, we call it AI for the Data Center, or certainly, the tagline of predictive analytics is something that Nimble's brought to the table for a long time. To provide that level of services, InfoSight, predictive analytics, AI for the Data Center, we're running our own big data infrastructure. It started a number of years ago even on our 3PAR platforms and other products, where we had scale-up databases. We moved and transitioned to batch-oriented Hadoop. Now we're fully embedded with real-time streaming analytics that come in every day, all day long, from our customers and telemetry. We're using AI and ML techniques to not only improve on what we've done that's certainly automating for the support experience, and making it easy to manage the platforms, but now introducing things like learning, automation engines, the recommendation engines for various things for our customers to take, essentially, the hands-on approach of managing the products and automate it and put into the products. So, for us, we've gone through a multi-phase, multi-year transition that's brought in things like Kafka and Spark and Elasticsearch. We're using all these techniques in our system to provide new services for our customers as well. >> Okay, great. You're practitioners, you got some street cred. >> Absolutely. >> Can I come back on InfoSight for a minute? It came through an acquisition of Nimble. It seems to us that you're a little bit ahead, and maybe you say a lot a bit ahead of the competition with regard to that capability. How do you see it? Where do you see InfoSight being applied across the portfolio, and how much of a lead do you think you have on competitors? >> I'm paranoid, so I don't think we ever have a good enough lead, right? You always gotta stay grinding on that front. But we think we have a really good product. You know, it speaks for itself. A lot of the customers love it. We've applied it to 3PAR, for example, so we came out with some, we have VMVision for a 3PAR that's based on InfoSight. We've got some things in the works for other product lines that are imminent pretty soon. You can think about what we've done for Nimble and 3PAR, we can apply similar type of logic to Elastic Platform for Analytics, like running at that type of cluster scale to automate a number of items that are pretty pedantic for the customers to manage. There's a lot of work going on within HPE to scale that as a service that we provide with most of our products. >> Okay, so where can I get more information on your big data offerings and what you guys are doing in that space? >> Yeah, so, we have, you can always go to hp.com/bigdata. We've got some really great information out there. We're in our run-up to our big end user event that we do every June in Las Vegas. It's HPE Discover. We have about 15,000 of our customers and trusted partners there, and we'll be doing a number of talks. I'm doing some work there with a British telecom. We'll give some great talks. Those'll be available online virtually, so you'll hear about not only what we're doing with our own InfoSight and big data services, but how other customers like BTE and 21st Century Fox and other folks are applying some of these techniques and making a big difference for their business as well. >> That's June 19th to the 21st. It's at the Sands Convention Center in between the Palazzo and the Venetian, so it's a good conference. Definitely check that out live if you can, or if not, you can all watch online. Excellent, Patrick, thanks so much for coming on and sharing with us this big data evolution. We'll be watching. >> Yeah, absolutely. >> And thank you for watcihing, everybody. We'll see you next time. This is Dave Vellante for theCUBE. (fast techno music)

(techno music) >> (announcer) From Berlin, Germany it's theCUBE covering DataWorks Summit Europe 2018. Brought to you by Hortonworks. >> Well hello, welcome to theCUBE. We're here on day two of DataWorks Summit 2018 in Berlin, Germany. I'm James Kobielus. I'm lead analyst for Big Data Analytics in the Wikibon team of SiliconANGLE Media. And who we have here today, we have Alan Gates whose one of the founders of Hortonworks and Hortonworks of course is the host of DataWorks Summit and he's going to be, well, hello Alan. Welcome to theCUBE. >> Hello, thank you. >> Yeah, so Alan, so you and I go way back. Essentially, what we'd like you to do first of all is just explain a little bit of the genesis of Hortonworks. Where it came from, your role as a founder from the beginning, how that's evolved over time but really how the company has evolved specifically with the folks on the community, the Hadoop community, the Open Source community. You have a deepening open source stack with you build upon with Atlas and Ranger and so forth. Gives us a sense for all of that Alan. >> Sure. So as I think it's well-known, we started as the team at Yahoo that really was driving a lot of the development of Hadoop. We were one of the major players in the Hadoop community. Worked on that for, I was in that team for four years. I think the team itself was going for about five. And it became clear that there was an opportunity to build a business around this. Some others had already started to do so. We wanted to participate in that. We worked with Yahoo to spin out Hortonworks and actually they were a great partner in that. Helped us get than spun out. And the leadership team of the Hadoop team at Yahoo became the founders of Hortonworks and brought along a number of the other engineering, a bunch of the other engineers to help get started. And really at the beginning, we were. It was Hadoop, Pig, Hive, you know, a few of the very, Hbase, the kind of, the beginning projects. So pretty small toolkit. And we were, our early customers were very engineering heavy people, or companies who knew how to take those tools and build something directly on those tools right? >> Well, you started off with the Hadoop community as a whole started off with a focus on the data engineers of the world >> Yes. >> And I think it's shifted, and confirm for me, over time that you focus increasing with your solutions on the data scientists who are doing the development of the applications, and the data stewards from what I can see at this show. >> I think it's really just a part of the adoption curve right? When you're early on that curve, you have people who are very into the technology, understand how it works, and want to dive in there. So those tend to be, as you said, the data engineering types in this space. As that curve grows out, you get, it comes wider and wider. There's still plenty of data engineers that are our customers, that are working with us but as you said, the data analysts, the BI people, data scientists, data stewards, all those people are now starting to adopt it as well. And they need different tools than the data engineers do. They don't want to sit down and write Java code or you know, some of the data scientists might want to work in Python in a notebook like Zeppelin or Jupyter but some, may want to use SQL or even Tablo or something on top of SQL to do the presentation. Of course, data stewards want tools more like Atlas to help manage all their stuff. So that does drive us to one, put more things into the toolkit so you see the addition of projects like Apache Atlas and Ranger for security and all that. Another area of growth, I would say is also the kind of data that we're focused on. So early on, we were focused on data at rest. You know, we're going to store all this stuff in HDFS and as the kind of data scene has evolved, there's a lot more focus now on a couple things. One is data, what we call data-in-motion for our HDF product where you've got in a stream manager like Kafka or something like that >> (James) Right >> So there's processing that kind of data. But now we also see a lot of data in various places. It's not just oh, okay I have a Hadoop cluster on premise at my company. I might have some here, some on premise somewhere else and I might have it in several clouds as well. >> K, your focus has shifted like the industry in general towards streaming data in multi-clouds where your, it's more stateful interactions and so forth? I think you've made investments in Apache NiFi so >> (Alan) yes. >> Give us a sense for your NiFi versus Kafka and so forth inside of your product strategy or your >> Sure. So NiFi is really focused on that data at the edge, right? So you're bringing data in from sensors, connected cars, airplane engines, all those sorts of things that are out there generating data and you need, you need to figure out what parts of the data to move upstream, what parts not to. What processing can I do here so that I don't have to move upstream? When I have a error event or a warning event, can I turn up the amount of data I'm sending in, right? Say this airplane engine is suddenly heating up maybe a little more than it's supposed to. Maybe I should ship more of the logs upstream when the plane lands and connects that I would if, otherwise. That's the kind o' thing that Apache NiFi focuses on. I'm not saying it runs in all those places by my point is, it's that kind o' edge processing. Kafka is still going to be running in a data center somewhere. It's still a pretty heavy weight technology in terms of memory and disk space and all that so it's not going to be run on some sensor somewhere. But it is that data-in-motion right? I've got millions of events streaming through a set of Kafka topics watching all that sensor data that's coming in from NiFi and reacting to it, maybe putting some of it in the data warehouse for later analysis, all those sorts of things. So that's kind o' the differentiation there between Kafka and NiFi. >> Right, right, right. So, going forward, do you see more of your customers working internet of things projects, is that, we don't often, at least in the industry of popular mind, associate Hortonworks with edge computing and so forth. Is that? >> I think that we will have more and more customers in that space. I mean, our goal is to help our customers with their data wherever it is. >> (James) Yeah. >> When it's on the edge, when it's in the data center, when it's moving in between, when it's in the cloud. All those places, that's where we want to help our customers store and process their data. Right? So, I wouldn't want to say that we're going to focus on just the edge or the internet of things but that certainly has to be part of our strategy 'cause it's has to be part of what our customers are doing. >> When I think about the Hortonworks community, now we have to broaden our understanding because you have a tight partnership with IBM which obviously is well-established, huge and global. Give us a sense for as you guys have teamed more closely with IBM, how your community has changed or broadened or shifted in its focus or has it? >> I don't know that it's shifted the focus. I mean IBM was already part of the Hadoop community. They were already contributing. Obviously, they've contributed very heavily on projects like Spark and some of those. They continue some of that contribution. So I wouldn't say that it's shifted it, it's just we are working more closely together as we both contribute to those communities, working more closely together to present solutions to our mutual customer base. But I wouldn't say it's really shifted the focus for us. >> Right, right. Now at this show, we're in Europe right now, but it doesn't matter that we're in Europe. GDPR is coming down fast and furious now. Data Steward Studio, we had the demonstration today, it was announced yesterday. And it looks like a really good tool for the main, the requirements for compliance which is discover and inventory your data which is really set up a consent portal, what I like to refer to. So the data subject can then go and make a request to have my data forgotten and so forth. Give us a sense going forward, for how or if Hortonworks, IBM, and others in your community are going to work towards greater standardization in the functional capabilities of the tools and platforms for enabling GDPR compliance. 'Cause it seems to me that you're going to need, the industry's going to need to have some reference architecture for these kind o' capabilities so that going forward, either your ecosystem of partners can build add on tools in some common, like the framework that was laid out today looks like a good basis. Is there anything that you're doing in terms of pushing towards more Open Source standardization in that area? >> Yes, there is. So actually one of my responsibilities is the technical management of our relationship with ODPI which >> (James) yes. >> Mandy Chessell referenced yesterday in her keynote and that is where we're working with IBM, with ING, with other companies to build exactly those standards. Right? Because we do want to build it around Apache Atlas. We feel like that's a good tool for the basis of that but we know one, that some people are going to want to bring their own tools to it. They're not necessarily going to want to use that one platform so we want to do it in an open way that they can still plug in their metadata repositories and communicate with others and we want to build the standards on top of that of how do you properly implement these features that GDPR requires like right to be forgotten, like you know, what are the protocols around PIII data? How do you prevent a breach? How do you respond to a breach? >> Will that all be under the umbrella of ODPI, that initiative of the partnership or will it be a separate group or? >> Well, so certainly Apache Atlas is part of Apache and remains so. What ODPI is really focused up is that next layer up of how do we engage, not the programmers 'cause programmers can gage really well at the Apache level but the next level up. We want to engage the data professionals, the people whose job it is, the compliance officers. The people who don't sit and write code and frankly if you connect them to the engineers, there's just going to be an impedance mismatch in that conversation. >> You got policy wonks and you got tech wonks so. They understand each other at the wonk level. >> That's a good way to put it. And so that's where ODPI is really coming is that group of compliance people that speak a completely different language. But we still need to get them all talking to each other as you said, so that there's specifications around. How do we do this? And what is compliance? >> Well Alan, thank you very much. We're at the end of our time for this segment. This has been great. It's been great to catch up with you and Hortonworks has been evolving very rapidly and it seems to me that, going forward, I think you're well-positioned now for the new GDPR age to take your overall solution portfolio, your partnerships, and your capabilities to the next level and really in terms of in an Open Source framework. In many ways though, you're not entirely 100% like nobody is, purely Open Source. You're still very much focused on open frameworks for building fairly scalable, very scalable solutions for enterprise deployment. Well, this has been Jim Kobielus with Alan Gates of Hortonworks here at theCUBE on theCUBE at DataWorks Summit 2018 in Berlin. We'll be back fairly quickly with another guest and thank you very much for watching our segment. (techno music)

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.

>> Announcer: Live, from Midtown Manhattan, it's theCUBE. Covering Big Data, New York City, 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay welcome back, everyone. Live in Manhattan, New York City, in Hell's Kitchen, this is theCUBE's special event, our annual CUBE-Wikibon Research Big Data event in Manhattan. Alongside Strata, Hadoop; formerly Hadoop World, now called Strata Data, as the world continues. This is our annual event; it's our fifth year here, sixth overall, wanted to kind of move from uptown. I'm John Furrier, the co-host of theCUBE, with Peter Burris, Head of Research at SiliconANGLE and GM of Wikibon Research. Our next guest is Tim Smith, who's the SVP of technical operations at AppNexus; technical operations for large scale is an understatement. But before we get going; Tim, just talk about what AppNexus as a company, what you guys do, what's the core business? >> Sure, AppNexus is the second largest digital advertising marketplace after google. We're an internet technology company that harnessed, we harness data and machine learning to power the companies that comprise the open internet. We began by building a powerful technology platform, in which we embedded core capabilities, tools and features. With me so far? >> Yeah, we got it. >> Okay, on top of that platform, we built a core suite of cloud-based enterprise products that enable the buying and selling of digital advertising, and a scale-transparent and low-cost marketplace where other companies can transact; either using our enterprise products, or those offered by other companies. If you want to hear a little about the daily peaks, peak feeds and speeds, it is Strata, we should probably talk about that. We do about 11.8 billion impressions transacted on a daily basis. Each of those is a real-time auction conducted in a fraction of a second, well under half a second. We see about 225 billion impressions per day, and we handle about 5 million queries per second at peak load. We produce about 150 terabytes of data each day, and we move about 400 gigabits into and out of the internet at peak, all those numbers are daily peaks. Makes sense? >> Yep. >> Okay, so by way of comparison, which might be useful for people, I believe the NYSE currently does roughly 2 million trades per day. So if we round that up to 3 million trades a day and assume the NYSE were to conduct that volume every single day of the year; 7 days a week, 365 days a year, that'd be about a billion trades a year. Similarly, I believe Visa did about 28-and-a-half billion transactions in their fiscal third quarter. I'll round that up to 30 billion, and average it out to about 333 million transactions per day and annualize it to about 4 billion transactions per year. Little bit of math, but as I mentioned, AppNexus does an excess of 10 billion transactions per day. And so it seems reasonable to say that AppNexus does roughly 10 times the transaction volume in one day, than the NYSE does in a year. And similarly, it seems reasonable to say that AppNexus daily does more than two times the transaction volume that Visa does in a year. Obviously, these are all just very rough numbers based on publicly available information about the NYSE and Visa, and both the NYSE and Visa do far, far more volume than AppNexus when measured in terms of dollars. So given our volumes, it's imperative that AppNexus does each transaction with the maximum efficiency and lowest reasonable possible cost, and that is one of the most challenging aspects of my job. >> So thanks for spending the time to give the overview. There's a lot of data; I mean 10 billion a day is massive volume. I mean the internet, and you see the scale, is insane. We're in a new era right now of web-scale. We've seen it in Facebook, and it's enormous. It's only going to get bigger, right? So on the online ad tech, you guys are essentially doing like a Google model, that's not everything but Google, which is still huge numbers. Then you include Microsoft and everybody else. Really heavy lifting, IT-like situation. What's the environment like? And just talk about, you know, what's it like for you guys. Because you got a lot of opp's, I mean terms of dev opp's. You can't break anything, because that 10 billion transaction or near, it's a significant impact. So you have to have everything buttoned-up super tight, yet you got to innovate and grow with the future growth. What's the IT environment like? >> It's interesting. We have about 8,000 servers spread across about seven data centers on three continents, and we run, as you mentioned, around the clock. There's no closing bell; downtime is not acceptable. So when you look at our environment, you're talking about four major categories of server complexes. We have real-time processing, which is the actual ad serving. We have a data pipeline, which is what we call our big data environment. We also have client-facing environment and an infrastructure environment. So we use a lot of different tools and applications, but I think the most relevant ones to this discussion are Hadoop and its friends HDFS, and Hive and Spark. And then we use the Vertica Analytics Platform. And together Hadoop and its friends, and Vertica comprise our entire data pipeline. They're both very disk-intensive. They're cluster based applications, and it's a lot of challenge to keep them up and running. >> So what are some of those challenges? Just explain a little bit, because you also have a lot of opportunity. I mean, it's money flowing through the air, basically; digital air, if you will. I mean, they got a lot of stuff happening. Take us through the challenges. >> You know, our biggest apps are all clustered. And all of our clusters are built with commodity servers, just like a lot of other environments. The big data app clusters traditionally have had internal disks, while almost all of our other servers are very light on disk. One of the biggest challenges is, since the server is the fundamental building block of a cluster, then regardless of whether you need more compute or more storage, you always have to add more servers to get it. That really limits flexibility and creates a lot of inefficiencies, and I really, really am obsessive about reducing and eliminating inefficiencies. So, with me so far? >> Yep. >> Great. The inefficiencies result from two major factors. First, not all workloads require the same ratio of compute to storage. Some workloads are more compute-intensive, and others are really less dependent on storage, while other workloads require a lot more storage. So we have to use standard server configurations and as a result, we wind up with underutilized compute and storage. This is undesirable, it's inefficient, yet given our scale, we have to use standardized configurations. So that's the first big challenge. The second is the compute to disk ratio. It's generally fixed when you buy the servers. Yes, we can certainly add more disks in the field, but that's a labor intensive, and it's complicated from a logistics and an asset management standpoint, and you're fundamentally limited by the number of disk slots in the server. So now you're right back into the trap of more storage requires more servers, regardless of whether you need more compute or not. And then you compound the inefficiencies. >> Couldn't you just move the resources from, unused resources, from one cluster to the other? >> I've been asked that a lot; and no, it's just not that simple. Each application cluster becomes a silo due to its configuration of storage and compute. This means you just can't move servers from clusters because the clusters are optimized for the workloads, and the fact that you can't move resources from one cluster to another, it's more inefficiencies. And then they're compounded over time since workloads change, and the ideal ratio of compute-to-storage changes. And the end result is unused resources trapped in silos and configurations that are no longer optimized for your workload. And there's only really one solution that we've been able to find. And to paraphrase an orator far, far more talented than I am, namely Ronald Reagan, we need to open this gate, tear down these silos. The silos just have to go away. They fundamentally limit flexibility and efficiency. >> What were some of the other issues caused by using servers with internal drives? >> You have more maintenance, you've got to deal with the logistics. But the biggest problem is service and storage have significantly different life cycles. Servers typically have a three year life cycle before they're obsolete. Storage typically is four to six years. You can sometimes stretch that a little further with the storage. Inside the servers that are replaced every 3 years, we end up replacing storage before the end of its effective lifetime; that's inefficient. Further, since the storage is inside the servers, we have to do massive data migrations when we replace servers. Migrations, they're time consuming, they're logistically difficult, and they're high risk. >> So how did DriveScale help you guys? Because you guys certainly have a challenging environment, you laid out the the story, and we appreciate that. How did DriveScale help you with the challenges? >> Well, what we really wanted to do was disaggregate storage from servers, and DriveScale enables us to do that. Disaggregating resources is a new term in the industry, but I think lot of people are focusing on it. I can explain it if you think that would make sense. >> What do you mean by disaggregating resources? Can you explain that, and how it works? >> Sure, so instead of buying servers with internal drives, we now buy diskless servers with JBODs. And DriveScale lets us easily compose servers with whatever amount of disk storage we need, from the server resource pool and the disk resource pool; and they're separate pools. This means we have the right balance of compute and storage for each workload, and we can easily adjust it over time. And all of this is done via software, so it's easy to do with a GUI or in our case, at our scale, scripting. And it's done on demand, and it's much more efficient. >> How does it help you with the underutilized resource challenge you mentioned earlier? >> Well, since we can add and remove resources from each cluster, we can manage exactly how much compute power and storage is deployed for each workload. Since this is all done via software, it can be done quickly and easily. We don't have to send a technician into a data center to physically swap drives, add drives, move drives. It's all done via software and it's very, very efficient. >> Can you move resources between silos? >> Well, yes and no. First off, our goal is no more silos. That said, we still have clusters, and once we completely migrate to DriveScale, all of our compute and storage resources will be consolidated into just a few common pools. And disk storage will no longer differentiate pools; thus, we have fewer pools. For more, we have fewer pools and can use the resources in each pool for more workloads. And when our needs change and they always do, we can reallocate resources as needed. >> What of the life cycle management challenge? How you guys address that? >> Well that's addressed with DriveScale. The compute and the storage are now disaggregated or separated into diskless servers and JBODs, so we can upgrade one without touching the other. We want to upgrade servers to take advantage of new processors or new memory architectures, we just replace the servers, re-combine the disks with the new servers, and we're back up and operating. It saves the cost of buying new disks when we don't need to, and it also simplifies logistics and reduces risk, as we no longer have to run the old plant and the new plant concurrently, and do a complicated data migration. >> What about this qualifying server and storage vendors? Do you still do that? Or how's that impact -- >> We actually don't have to do it. We're still using the same server vendor. We've used Dell for many, many years, we continue to use them. We are using them for storage and there was no real work, we just had to add DriveScale into the mix. >> What's it like working with DriveScale? >> They're really wonderful to work with. They have a really seasoned team. They were at Sun Microsystems and Cisco, they built some of the really foundational products that changed the internet, that the internet was built on. They're really talented, they really bright, and they're really focused on customer success. >> Great story, thanks for sharing that. My final question for you is, you guys have a very big, awesome environment, you've got a lot of scale there. It's great for a startup to get into an environment like this, because one, they could get access to the data, work with a good team like you have. What's it like working with a startup? >> You know it's always challenging at first; too many things to do. >> They got talented guys. Most of the startups, those early day startups, they got all their A players out there. >> They have their A players, and we've been very pleased working with them. We're dealing with the top talent, some of the top talent in the industry, that created the industry. They have a proven track record. We really don't have any concerns, we know they're committed to our success and they have a great team, and great investors. >> A final, final question. For your friends out there are watching, and other practitioners who are trying to run things at scale with a cloud. What's your advice to them? You've been operating at scale, and a lot of, billions of transactions, I mean huge; it's only going to get bigger. Put your IT friendly advice hat on. What's the mindset of operators out there, technical op's, as dev op's comes in seeing a lot of that. What do people need to be thinking about to run at scale? >> There's no magic silver bullet. There's no magic answers. The public cloud is very helpful in a lot of ways, but you really have to think hard about your economics, you have to think about your scale. You just have to be sure that you're going into each decision knowing that you've looked at the costs and the benefits, the performance, the risks, and you don't expect there to be simple answers. >> Yeah, there's no magic beans as they say. You've got to make it work for the business. >> No magic beans, I wish there were. >> Tim, thanks so much for the story. Appreciate the commentaries. Live coverage at Big Data NYC, it's theCUBE. Be back with more after this short break. (upbeat techno music)