(upbeat music) >> Welcome back to Supercloud22. This is an open community event, and it's dedicated to tracking the future of cloud in the 2020s. Supercloud is a term that we use to describe an architectural abstraction layer that hides the underlying complexities of the individual cloud primitives and APIs and creates a common experience for developers and users irrespective of where data is physically stored or on which cloud platform it lives. We're now going to explore the nuances of going to market in a world where data architectures span on premises across multiple clouds and are increasingly stretching out to the edge. Paula Hansen is the President and Chief Revenue Officer at Alteryx. And the reason we asked her to join us for Supercloud22 is because first of all, Alteryx is a company that is building a form of Supercloud in our view. If you have data in a bunch of different places and you need to pull in different data sets together, you might want to filter it or blend it, cleanse it, shape it, enrich it with other data, analyze it, report it out to your colleagues. Alteryx allows you to do that and automate that life cycle. And in our view is working to break down the data silos across clouds, hence Supercloud. Now, the other reason we invited Paula to the program is because she's a rockstar female in tech, and since day one at theCube, we've celebrated great women in tech, and in this case, a woman of data, Paula Hansen, welcome to the program. >> Thank you, Dave. I am absolutely thrilled to be here. >> Okay, we're going to focus on customers, their challenges and going to market in this cross cloud, multi-cloud, Supercloud world. First, Paula, what's changing in your view in the way that customers are innovating with data in the 2020s? >> Well, I think we've all learned very clearly over these last two years that the global pandemic has altered life and business as we know it. And now we're in an interesting time from a macroeconomic perspective as well. And so what we've seen is that every company in every industry has had to pivot and think about how they meet redefined customer expectations and an ever evolving competitive landscape. There really isn't an industry that wasn't reshaped in some way over the last couple of years. And we've been fortunate to work with companies in all industries that have adapted to this ever changing environment by leveraging Alteryx to help accelerate their digital transformations. Companies know that they need to unlock the full potential of their data to be able to move quickly to pivot and to respond to their customer's needs, as well as manage their businesses most efficiently. So I think nothing tells that story better than sharing a customer example with you, Dave. We love to share stories of our very innovative customers. And so the one that I'll share with you today in regards to this is Delta Airlines, who we're all very familiar with. And of course Delta's goal is to always keep their airplanes in the air flying passengers and getting people to their destinations efficiently. So they focus on the maintenance of their aircraft as a necessary part of running their business and they need to manage their maintenance stops and the maintenance of their aircraft very efficiently and effectively. So we work with them. They leverage our platform to automate all the processes for their aircraft maintenance centers. And so they've built out a fully automated reporting system on our platform leveraging tons of data. And this gives their service managers and their aircraft technicians foresight into what's happening with their scheduling and their maintenance processes. So this ensures that they've got the right technicians in the service center when the aircrafts land and that everything across that process is fully in place. And previously because of data silos and just complexity of data, this process would've taken them many many hours in each independent service center, and now leveraging Alteryx and the power of analytics and bringing all the data together. Those centers can do this process in just minutes and get their planes back in the air efficiently and delivering on their promises to their customers. So that's just one of many examples that we have in terms of the way the Alteryx analytics automation helps customers in this new age and helping to really unlock the power of their data. >> You know, Paul, that's an interesting example. Because in a previous life I worked with some airlines and people maybe don't realize this but, aircraft maintenance is the mission critical application for carriers. It's not the booking system. Because we've been there before, we show you there's a problem when you're booking or sometimes it's unfortunate, but people they get de booked. But the aircraft maintenance is the one that matters the most and that keeps planes in the air. So we hear all the time, you just mention it. About data silos and how problematic they are. So, specifically how are you seeing customers thinking about busting the data silos? >> Yeah, that's right, it's a big topic right now. Because companies realize that business processes that they run their business with, is very cross-functional in nature and requires data across every department in the enterprise. And you can't keep data locked in one department. So if you think of business processes like pay to procure or quote to cash, these are business processes that companies in every industry run their business. And that requires them to get data from multiple departments and bring all of that data together seamlessly to make the best business decisions that they can make. So what our platform does is, and is really well known for, is being very easy for users number one, and then number two, being really great at getting access to data quickly and easily from all those data silos, really, regardless of where it is. We talk about being everywhere. And when we say that we mean, whether it's on-prem, in your legacy applications and databases, or whether it's in the cloud with of course, all the multiple cloud platforms and modern cloud data warehouses. Regardless of where it is, we have the ability to bring that data together across hundreds of different data sources, bring it together to help drive insights and ultimately help our customers make better decisions, take action, and deliver on the business outcomes that they all are trying to drive within their respective industries. And what's- >> You know- >> Go ahead. >> Please carry on. >> Well, I was just going to say that what I do think has really sort of a tipping point in the last six months in particular is that executives themselves are really demanding of their organizations, this democratization of data. And the breaking down of the silos and empowering all of the employees across their enterprise regardless of how sophisticated they are with analytics to participate in the analytic opportunity. So we've seen some really cool things of late where executives, CEOs, chief financial officers, chief data officers are sponsoring events within their organizations to break down these silos and encourage their employees to come together on this democratization opportunity of democratization of data and analytics. And there's a shortage of data scientists on top of this. So there's no way that you're going to be able to hire enough data scientists to make sense of all this data running around your enterprise. So we believe with our platform we empower people regardless of their skillset. And so we see executives sponsoring these hackathons within their environments to bring together people to brainstorm and ideate on use cases, to share examples of how they leverage our platform and leverage the data within their organization to make better decisions. And it's really quite cool. Companies like Stanley Black & Decker, Ingersoll Rand, Inchcape PLC, these are all companies that the executive team has sponsored these hackathon events and seen really powerful things come out of it. As an example Ingersoll Rand sponsored their Alteryx hackathon with all of their data workers across various different functions where the data exists. And they focused on both top line revenue use cases as well as bottom line efficiency cases. And one of the outcomes was a use case that helped with their distribution center in north America and bringing all the data together across their various applications to reduce the amount of over ordering and under ordering of parts and more effectively manage their inventory within that distribution center. So, really cool to see this is now an executive level board level conversation. >> Very cool, a hackathon bringing people together for collaboration. A couple things that you said I want to comment on. Again, one of the reasons why we invited you guys to come on is, when you think about on-prem data and anybody who follows theCube and my breaking analysis program, knows we're big fans of Zhamak Dehghani's concept of data mesh. And data mesh is supposed to be inclusive. It doesn't matter if it's an S3 bucket, Oracle data base, or data warehouse, or data lake, that's just a note on the data mesh. And so it should be inclusive and Supercloud should include on-prem data to the extent that you can make that experience consistent. We have a lot of technical sessions here at Supercloud22, we're focusing now and go to market and the ecosystem. And we live in a world of multiple partners exploding ecosystems. And a lot of times it's co-opetition. So Paula, when you joined Alteryx you brought a proven go to market discipline to the company. Alignment with the customer, playbooks, best practice of sales, et cetera. And we've seen the results. It's a big reason why Mark Anderson and the board promoted you to president just after 10 months. Summarize how you approached the situation at Alteryx when you joined last spring. >> Yeah, I think first we were really intentional about what part of the market, what type of enterprises get the most benefit from the innovation that we deliver? And it's really clear that it's large enterprises. That the more complex a company is, most likely the more data they have and oftentimes the more decentralized that data is. And they're also really all trying to figure out how to remain competitive by leveraging that data. So, the first thing we did was be very intentional that we're focused on the enterprise and building out all of the capability required to be able to serve the enterprise. Of course, essential to all of that is having a platform capability because enterprises require that. So, with Suresh Vittal our Chief Product Officer, he's been fantastic in building out an end to end analytic platform that serves a wide range of analytic capabilities to a wide range of users. And then of course has this flexibility to operate both on-prem and in the cloud which is very important. Because we see this hybrid environment in this multicloud environment being something that is important to our customers. The second thing that I was really focused on was understanding how do you have those conversations with customers when they all are in maybe different types of backgrounds? So the way that you work with a business analyst in the office of finance or supply chain or sales and marketing, is different than the way that you serve a data scientist or a data engineer in IT. The way that you talk to a business owner who wants not to really understand the workflow level of data but wants to understand the insights of data, that's a different conversation. When you want to have a conversation of analytics for all or democratization of analytics at the executive level with the chief data officer or a CIO, that's a whole different conversation. And so we've built very specific sales plays to be able to have those conversations bring the relevant information to the relevant person so that we're really making sure that we explain the value proposition of the platform. Fully understand their world, their language and can work with them to deliver the value to them. And then the third thing that we did, was really heavily invest in our partnerships and you referenced this day. It's a a broad ecosystem out there. And we know that we have to integrate into that broad data ecosystem. and be a good partner to serve our customers. So, we've invested both in technology integration as well as go to market strategies with cloud data warehouse companies like Snowflake and Databricks, or RPA companies like UiPath and Blue Prism, as well as a wide range of other application and all of the cloud platforms because that's what our customers expect from us. So that's been a really important sort of third pillar of our strategy in making sure that from a go to market perspective, we understand where we fit in the ecosystem and how we collectively deliver on value to our joint customers. >> So that's super helpful. What I'm taking away from this is you didn't come to it with a generic playbook. Frank Lyman always talks about situation leadership. You assess the situation and applied that and a great example of partners is Snowflake and Databricks, these sort of opposites, but trying to solve similar problems. So you've got to be inclusive of all that. So we're trying to sort of squint through this Paula and say, okay, are there nuances and best practices beyond some of the the things that you just described that are unique to what we call Supercloud? Are there observations you can make with respect to what's different in this post isolation economy? Specifically in managing remote employees and of course remote partners, working with these complex ecosystems and the rise of this multi-cloud world, is it different or is it same wine new bottle? >> Well, I think it's both common from the on-prem or pre-cloud world, but there's also some differences as well. So what's common is that companies still expect innovation from us and still want us to be able to serve a wide range of skill sets. So our belief is that regardless of the skill set that you have, you can participate in the analytics opportunity for your company and unlocking the potential of your data. So we've been very focused since our inception to build out a platform that really serves this wide range of capabilities across the enterprise space. What's perhaps changed more or continues to evolve in this cloud world is just the flexibility that's required. You have to be everywhere. You have to be able to serve users wherever they are and be able to live in a multi-cloud or super cloud world. So when I think of cloud, I think it just unlocks a whole bigger opportunity for Alteryx and for companies that want to become analytic leaders. Because now you have users all over the globe, many of them looking for web-based analytic solutions. And of course these enterprises are all in various places on their journey to cloud and they want a partner and a platform that operates in all of those environments, which is what we do at Alteryx. So, I think it's an exciting time. I think that it's still very early in the analytic market and what companies are going to do to leverage their data to drive their transformation. And we're really excited to be a part of it. >> So last question is, I said up front we always like to celebrate women in tech. How'd you get into tech.? You've got a background, you've got somewhat of a technical background of being technical sales. And then of course rose up throughout your career and now have a leadership position. I called you a woman of data. How'd you get into it? Where'd you find the love of data? Give us the background and help us inspire some of the young women out there. >> Oh, well, but I'm super passionate about inspiring young women and thinking about the future next generation of women that can participate in technology and in data specifically. I grew up loving math and science. I went to school and got an electrical engineering degree but my passion around technology hasn't been just around technology for technology's sake, my passion around technology is what can it enable? What can it do? What are the outcomes that technology makes possible? And that's why data is so attractive because data makes amazing things possible. I shared some of those examples with you earlier but it not only can we have effect with data in businesses and enterprise, but governments globally now are realizing the ability for data to really have broad societal impact. And so I think that that speaks to women many times. Is that what does technology enable? What are the outcomes? What are the stories and examples that we can all share and be inspired by and feel good and and inspired to be a part of a broader opportunity that technology and data specifically enables? So that's what drives me. And those are the conversations that I have with the women that I speak with in all ages all the way down to K through 12 to inspire them to have a career in technology. >> Awesome, the more people in STEM the better, and the more women in our industry the better. Paula Hansen, thanks so much for coming in the program. Appreciate it. >> Thank you, Dave. >> Okay, keep it right there for more coverage from Supercloud 22, you're watching theCube. (upbeat music)

(upbeat music) >> Okay, welcome back everyone to theCUBE's coverage here at re:MARS. I'm John Furrier, host of theCUBE. It's the event where it's part of the "re:" series: re:MARS, re:Inforce, re:Invent. MARS stands for machine learning, automation, robotics, and space. And a lot of conversation is all about AI machine learning. This one's about AI and business transformation. We've got Stepan Pushkarev CTO, CEO, Co-Founder of Provectus. Welcome to theCUBE. And Russ Lamb, eCommerce Retail Data Engineering Lead at PepsiCo, customer story. Gentlemen, thanks for coming on theCUBE. >> Great to be here, John. >> Yeah, thanks for having us. >> I love the practical customer stories because it brings everything to life. This show is about the future, but it's got all the things we want, we love: machine learning, robotics, automation. If you're in DevOps, or you're in data engineering, this is the world of automation. So what's the relationship? You guys, you're a customer. Talk about the relationship between you guys. >> Sure, sure. Provectus as a whole is a professional services firm, premier, a AWS partner, specializing in machine learning, data, DevOps. PepsiCo is our customer, our marquee customer, lovely customer. So happy to jointly present at this re:Invent, sorry, re:MARS. Anyway, Russ... >> I made that mistake earlier, by the way, 'cause re:Invent's always on the tip of my tongue and re:MARS is just, I'm not used to it yet, but I'm getting there. Talk about what are you guys working together on? >> Well, I mean, we work with Provectus in a lot of ways. They really helped us get started within our e-commerce division with AWS, provided a lot of expertise in that regard and, you know, just hands-on experience. >> We were talking before we came on camera, you guys just had another talk and how it's all future and kind of get back to reality, Earth. >> Russ: Get back to Earth. >> If we're on earth still. We're not on Mars yet, or the moon. You know, AI's kind of got a future, but it does give a tell sign to what's coming, industrial change, full transformation, 'cause cloud does the back office. You got data centers. Now you've got cloud going to the edge with industrial spaces, the ultimate poster child of edge and automation safety. But at the end of the day, we're still in the real world. Now people got to run businesses. And I think, you know, having you here is interesting. So I have to ask you, you know, as you look at the technology, you got to see AI everywhere. And the theme here, to me, that I see is the inflection point driving all this future robotics change, that everyone's been waiting for by the way, but it's like been in movies and in novels, is the machine learning and AI as the tipping point. This is key. And now you're here integrating AI into your company. Tell us your story. >> Well, I think that every enterprise is going to need more machine learning, more, you know, AI or data science. And that's the journey that we're on right now. And we've come a long way in the past six years, particularly with our e-commerce division, it's a really data rich environment. So, you know, going from brick and mortar, you know, delivering to restaurants, vending machines and stuff, it's a whole different world when you're, people are ordering on Amazon every couple minutes, or seconds even, our products. But they, being able to track all that... >> Can you scope the problem statement and the opportunity? Because if I just kind of just, again, I'm not, you're in, it's your company, you're in the weeds, you're at the data, you're everything, But it just seems me, the world's now more integration, more different data sources. You've got suppliers, they have their different IT back ends. Some are in the cloud, some aren't in the cloud. This is, like, a hard problem when you want to bring data together. I mean, API certainly help, but can you scope the problem, and, like, what we're talking about here? >> Well, we've got so many different sources of data now, right? So we used to be relying on a couple of aggregators who would pull all this data for us and hand us an aggregated view of things. But now we're able to partner with different retailers and get detail, granular information about transactions, orders. And it's just changed the game, changed the landscape from just, like, getting a rough view, to seeing the nuts and bolts and, like, all the moving parts. >> Yeah, and you see in data engineering much more tied into like cloud scale. Then you got the data scientists, more the democratization application and enablement. So I got to ask, how did you guys connect? What was the problem statement? How did you guys, did you have smoke and fire? You came in solved the problem? Was it a growth thing? How did this, how did you guys connect as a customer with Provectus? >> Yeah, I can elaborate on that. So we were in the very beginning of that journey when there was, like, just a few people in this new startup, let's call it startup within PepsiCo. >> John: Yeah. >> Calling like a, it's not only e-commerce, it was a huge belief from the top management that it's going to bring tremendous value to the enterprise. So there was no single use case, "Hey, do this and you're going to get that." So it's a huge belief that e-commerce is the future. Some industry trends like from brand-centric to consumer-centric. So brand, product-centric. Amazon has the mission to build the most customer-centric customer company. And I believe that success, it gets a lot of enterprises are being influenced by that success. So I remember that time, PepsiCo had a huge belief. We started building just from scratch, figuring out what does the business need? What are the business use cases? We have not started with the IT. We have not started with this very complicated migrations, modernizations. >> John: So clean sheet of paper. >> Yeah. >> From scratch. >> From scratch. >> And so you got the green light. >> Yeah. >> And the leadership threw the holy water on that and said, "Hey, we'll do this."? >> That's exactly what happened. It was from the top down. The CEO kind of set aside the e-commerce vision as kind of being able to, in a rapidly evolving business place like e-commerce, it's a growing field. Not everybody's figured it out yet, but to be able to change quickly, right? The business needs to change quickly. The technology needs to change quickly. And that's what we're doing here. >> So this is interesting. A lot of companies don't have that, actually, luxury. I mean, it's still more fun because the tools are available now that all the hyper scales built on their own. I mean, back in the day, 10 years ago, they had to build it all, Facebook. You didn't know, I had people on here from Pinterest and other companies. They had to build all of that from scratch. Now cloud's here. So how did you guys do this? What was the playbook? Take us through the AI because it sounds like the AI is core, you know, belief principle of the whole entire system. What did you guys do? Take me through the journey there. >> Yeah. Beyond management decisions, strategic decisions that has been made as a separate startup, whatever- >> John: That's great. >> So some practical, tactical. So it may sound like a cliche, but it's a huge thing because I work with many enterprises and this, like, "center of excellence" that does a nice technology stuff and then looks for the budget on the different business units. It just doesn't go anywhere. It could take you forever to modernize. >> We call that the Game of Thrones environment. >> Yes. >> Yeah. Nothing ever gets done 'till it blows up at the end. >> Here, these guys, and I have to admit, I don't want to steal their thunder. I just want to emphasize it as an external person. These guys just made it so differently. >> John: Yeah. >> They even physically sat in a different office in a WeWork co-working and built that business from scratch. >> That's what Andy Jackson talked about two years ago. And if you look at some of the big successes on AWS, Capital One, all the big, Goldman Sachs. The leadership, real commitment, not like BS, like total commitment says, "Go." But enough rope to give you some room, right? >> Yeah. I think that's the thing is, there was always an IT presence, right, overseeing what we were doing within e-commerce, but we had a lot of freedoms to make design choices, technology choices, and really accelerate the business, focus on those use cases where we could make a big impact with a technology choice. >> Take me through the stages of the AI transformation. What are some of the use cases and specific tactics you guys executed on? >> Well, I think that the supply chain, which I think is a hot topic right now, but that was one use case where we're using, like, data real time, real time data to inform our sales projections and delivery logistics. But also our marketing return on investment, I feel like that was a really interesting, complex problem to solve using machine learning, Because there's so much data that we needed to process in terms of countries, territories, products, like where do you spend your limited marketing budget when you have so many choices, and, using machine learning, boil that all down to, you know, this is the optimal choice, right now. >> What were some of the challenges and how did you overcome them in the early days to get things set up, 'cause it takes a lot of energy to get it going, to get the models. What were some of the challenges and how did you overcome them? >> Well, I think some of it was expertise, right? Like having a partner like Provectus and Stepan really helped because they could guide us, Stepan could guide us, give his expertise and what he knows in terms of what he's seen to our budding and growing business. >> And what were the things that you guys saw that you contributed on? And was there anything new that you had to do together? >> Yeah, so yeah. First of all, just a very practical tip. Yes, start with the use cases. Clearly talk to the business and say, "Hey, these are the list of the use cases" and prioritize them. So not with IT, not with technology, not with the migration thing. Don't touch anything on legacy systems. Second, get data in. So you may have your legacy systems or some other third party systems that you work with. There's no AI without data. Get all the pipelines, get data. Quickly boat strap the data lake house. Put all the pipelines, all the governance in place. And yeah, literally took us three months to get up and running. And we started delivering first analytical reports. It's just to have something back to business and keep going. >> By the way, that's huge, speed. I mean, this is speed. You go back and had that baggage of IT and the old antiquated systems, you'd be dragging probably months. Right? >> It's years, years. Imagine you should migrate SAP to the cloud first. No, you don't do don't need to do that. >> Pipeline. >> Just get data. I need data. >> Stream that data. All right, where are we now? When did you guys start? I want to get just going to timeline my head 'cause I heard three months. Where are we now? You guys threw it. Now you have impact. You have, you have results. >> Yeah. I mean that for our marketing ROI engine, we've built it and it's developed within e-commerce, but we've started to spread it throughout the organization now. So it's not just about the digital and the e-commerce space. We're deploying it to, you know, regionally to other, to Europe, to Latin America, other divisions within PepsiCo. And it's just grown exponentially. >> So you have scale to it right now? >> Yeah. Well- >> How far are you in now? What, how many years, months, days? >> E-commerce, the division was created six years ago, which is, so we've had some time to develop this, our machine learning capabilities and this use case particular, but it's increasingly relevant and expansion is happening as we speak. >> What are you most proud of? You look back at the impact. What are you most proud of? >> I think the relationship we built with the people, you know, who use our technology, right. Just seeing the impact is what makes me proud. >> Can you give an example without revealing any confidential information? >> Yeah. Yeah. I mean, there was an example from my talk about, I was approached recently by our sales team. They were having difficulty with supply chain, monitoring our fill rate of our top brands with these retailers. And they come up to me, they have this problem. They're like, "How do we solve it?" So we work together to find a data source, just start getting that data in the hands of people who can use it within days. You know, not talking like a long time. Bring that data into our data warehouse, and then surface the data in a tool they can use, you know, within a matter of a week or two. >> I mean, the transformation is just incredible. In fact, we were talking on theCUBE earlier today around, you know, data warehouses in the cloud, data meshes of different pros and cons. And the theme that came out of that conversation was data's a product now. >> Yes. >> Yes. >> And what you're kind of describing is, just gimme the product or find it. >> Russ: Right. >> And bring it in with everything else. And there's some, you know, cleaning and stuff people do if they have issues with that. But, if not, it's just bring it in, right? It's a product. >> Well, especially with the data exchanges now. AWS has a data exchange and this, I think, is the future of data and what's possible with data because you don't have to start from, okay, I've got this Excel file somebody's been working with on their desktop. This is a, someone's taken that file, put it into a warehouse or a data model, and then they can share it with you. >> John: So are you happy with these guys? >> Absolutely, yeah. >> You're actually telling the story. What was the biggest impact that they did? Was it partnering? Was it writing code, bringing development in, counseling, all the above, managed services? What? >> I think the biggest impact was the idea, you know, like being able to bring ideas to the table and not just, you know, ask us what we want, right? Like I think Provectus is a true partner and was able to share that sort of expertise with us. >> You know, Andy Jackson, whenever I interview on theCUBE, he's now in charge of all Amazon. But when he was at (inaudible). He always had to use their learnings, get the learnings out. What was the learnings you look back now and say, Hey, those were tough times. We overcome them. We stopped, we started, we iterated, we kept moving forward. What was the big learning as you look back, some of the key success points, maybe some failures that you overcome. What was the big learnings that you could share with folks out there now that are in the same situation where they're saying, "Hey, I'd rather start from scratch and do a reset." >> Yeah. So with that in particular, yes, we started this like sort of startup within the enterprise, but now we've got to integrate, right? It's been six years and e-commerce is now sharing our data with the rest of the organization. How do we do that, right? There's an enterprise solution, and we've got this scrappy or, I mean, not scrappy anymore, but we've got our own, you know, way of doing. >> Kind of boot strap. I mean, you were kind of given charter. It's a start up within a big company, I mean- >> But our data platform now is robust, and it's one of the best I've seen. But how do we now get those systems to talk? And I think Provectus has came to us with, "Here, there's this idea called data mesh, where you can, you know, have these two independent platforms, but share the data in a centralized way. >> So you guys are obviously have a data mesh in place, big part of the architecture? >> So it is in progress, but we know the next step. So we know the next step. We know the next two steps, what we're going to do, what we need to do to make it really, to have that common method, data layer. between different data products within organization, different locations, different business units. So they can start talking to each other through the data and have specific escalates on the data. And yeah. >> It's smart because I think one of the things that people, I think, I'd love to get your reaction to this is that we've been telling the story for many, many years, you have horizontally scalable cloud and vertically specialized domain solutions, you need machine learning that's smart, but you need a lot of data to help it. And that's not, a new architecture, that's a data plane, it's control plane, but now everyone goes, "Okay, let's do silos." And they forget the scale side. And then they go, "Wait a minute." You know, "I'm not going to share it." And so you have this new debate of, and I want to own my own data. So the data layer becomes an interesting conversation. >> Yeah, yes. Meta data. >> Yeah. So what, how do you guys see that? Because this becomes a super important kind of decision point architecturally. >> I mean, my take is that there has to be some, there will always be domains, right? Everyone, like there's only so much that you can find commonality across, like in industry, for example. But there will always be a data owner. And, you know, kind of like what happened with rush to APIs, how that enabled microservices within applications and being sharing in a standardized way, I think something like that has to happen in the data space. So it's not a monolithic data warehouse, it's- >> You know, the other thing I want to ask you guys both, if you don't mind commenting while I got you here, 'cause you're both experts. >> We just did a showcase on data programmability. Kind of a radical idea, but like data as code, we called it. >> Oh yeah. >> And so if data's a product and you're acting on, you've got an architecture and system set up, you got to might code it's programmable. You need you're coding with data. Data becomes like a part of the development process. What do you guys think of when you hear data as code and data being programmable? >> Yeah, it's a interesting, so yeah, first of all, I think Russ can elaborate on that, Data engineering is also software engineering. Machine learning engineering is a software. At the end of the day, it's all product. So we can use different terms and buzz words for that but this is what we have at the end of the day. So having the data, well I will use another buzz word, but in terms of the headless architecture- >> Yes. >> When you have a nice SDK, nice API, but you can manipulate with the data as your programming object to build reach applications for your users, and give it, and share not as just a table in Redshift or a bunch of CSV files in S3 bucket, but share it as a programmable thing that you can work with. >> Data as code. >> Yeah. This is- >> Infrastructure code was a revolution for DevOps, but it's not AI Ops so it's something different. It's really it's data engineering. It's programming. >> Yeah. This is the way to deliver data to your consumers. So there are different ways you can show it on a dashboard. You can show it, you can expose it as an API, or you can give it as an object, programmable interface. >> So now you're set up with a data architecture that's extensible 'cause that's the goal. You don't want to foreclose. You must think about that must keep you up at night. What's going to foreclose that benefit? 'Cause there's more coming. Right? >> Absolutely. There's always more coming. And I think that's why it's important to have that robust data platform to work from. And yeah, as Stepan mentioned, I'm a big believer in data engineering as software engineering. It's not some like it's not completely separate. You have to follow the best practices software engineers practice. And, you know, really think about maintainability and scalability. >> You know, we were riffing about how cloud had the SRE managing all those servers. One person, data engineering has a many, a one to many relationships too. You got a lot going on. It's not managing a database. It's millions of data points and data opportunity. So gentlemen, thanks for coming on theCUBE. I really appreciate it. And thanks for telling the story of Pepsi. >> Of course, >> And great conversation. Congratulations on this great customer. And thanks for >> coming on theCUBE. >> Thanks, thank you. Thanks, Russ, would you like to wrap it up with the pantry shops story? >> Oh, yeah! I think it will just be a super relevant evidence of the agility and speed and some real world applicable >> Let's go. Close us out. >> So when, when the pandemic happened and there were lockdowns everywhere, people started buying things online. And we noticed this and got a challenge from our direct to consumer team saying, "Look, we need a storefront to be able to sell to our consumers, and we've got 30 days to do it." We need to be able to work fast. And so we built not just a website, but like everything that behind it, the logistics of supply chain aspects, the data platform. And we didn't just build one. We built two. We got pantry shop.com and snacks.com, within 30 days. >> Good domains! >> The domain broker was happy on that one. Well continue the story. >> Yeah, yeah. So I feel like that the agility that's required for that kind of thing and the like the planning to be able to scale from just, you know, an idea to something that people can use every day. And, and that's, I think.- >> And you know, that's a great point too, that shows if you're in the cloud, you're doing the work you're prepared for anything. The pandemic was the true test for who was ready because it was unforeseen force majeure. It was just like here it comes and the people who were in the cloud had that set up, could move quickly. The ones that couldn't. >> Exactly. >> We know what happened. >> And I would like to echo this. So they have built not just a website, they have built the whole business line within, and launched that successfully to production. That includes sales, marketing, supply chain, e-commerce, aside within 30 days. And that's just a role model that could be used by other enterprises. >> Yeah. And it was not possible without, first of all, right culture. And second, without cloud Amazon elasticity and all the tools that we have in place. >> Well, the right architecture allows for scale. That's the whole, I mean, you did everything right at the architecture that's scale. I mean, you're scaling. >> And we empower our engineers to make those choices, right. We're not, like, super bureaucratic where every decision has to be approved by the manager or the managers manager. The engineers have the power to just make good decisions, and that's how we move fast. >> That's exactly the future right there. And this is what it's all about. Reliability, scale agility, the ability to react and have applications roll out on top of it without long timeframes. Congratulations. Thanks for being on theCUBE. Appreciate it. All right. >> Thank you. >> Okay, you're watching theCUBE here at re:MARS 2020, I'm John Furrier. Stay tuned. We've got more coverage coming after this short break. (upbeat music)

(bright music) >> Welcome to this next session of AWS Storage Day. I'm your host, Dave Vellante of theCUBE. And right now we're going to explore how to simplify and evolve your data lake backup disaster recovery and analytics in the cloud. And we're joined by Kevin Miller who's the general manager of Amazon S3. Kevin, welcome. >> Thanks Dave. Great to see you again. >> Good to see you too. So listen, S3 started as like a small ripple in the pond and over the last 15 years, I mean, it's fundamentally changed the storage market. We used to think about storage as, you know, a box of disc drives that either store data in blocks or file formats and then object storage at the time it was, kind of used in archival storage, it needed specialized application interfaces, S3 changed all that. Why do you think that happened? >> Well, I think first and foremost, it's really just, the customers appreciated the value of S3 and being fully managed where, you know, we manage capacity. Capacity is always available for our customers to bring new data into S3 and really therefore to remove a lot of the constraints around building their applications and deploying new workloads and testing new workloads where they know that if something works great, it can scale up by a 100x or a 1000x. And if it doesn't work, they can remove the data and move on to the next application or next experiment they want to try. And so, you know, really, it's exciting to me. Really exciting when I see businesses across essentially every industry, every geography, you know, innovate and really use data in new and really interesting ways within their business to really drive actual business results. So it's not just about building data, having data to build a report and have a human look at a report, but actually really drive the day-to-day operations of their business. So that can include things like personalization or doing deeper analytics in industrial and manufacturing. A customer like Georgia-Pacific for example, I think is one of the great examples where they use a big data lake and collect a lot of sensor data, IoT sensor data off of their paper manufacturing machines. So they can run them at just the right speed to avoid tearing the paper as it's going through, which really just keeps their machines running more and therefore, you know, just reduce their downtime and costs associated with it. So you know, it's just that transformation again, across many industries, almost every industry that I can think of. That's really what's been exciting to see and continue to see. I think we're still in the really early days of what we're going to see as far as that innovation goes. >> Yeah, I got to agree. I mean, it's been pretty remarkable. Maybe you could talk about the pace of innovation for S3. I mean, if anything, it seems to be accelerating. How Kevin, does AWS, how has it thought about innovation over the past decade plus and where do you see it headed? >> Yeah, that's a great question Dave, really innovation is at our core as part of our core DNA. S3 launched more than 15 years ago, almost 16 years old. We're going to get a learner's permit for it next year. But, you know, as it's grown to exabytes of storage and trillions of objects, we've seen almost every use case you can imagine. I'm sure there's a new one coming that we haven't seen yet, but we've learned a lot from those use cases. And every year we just think about what can we do next to further simplify. And so you've seen that as we've launched over the last few years, things like S3 Intelligent Tiering, which was really the clouds first storage class to automatically optimize and reduce customer's costs for storage, for data that they were storing for a long time. And based on, you know, variable access patterns. We launched S3 Access Points to provide a simpler way to have different applications operating on shared data sets. And we launched earlier this year S3 Object Lambda, which really is, I think, cool technology. We're just starting to see how it can be applied to simplify serverless application development. Really the next wave, I think, of application development that doesn't need, not only is the storage fully managed, but the compute is fully managed as well. Really just simplify that whole end to end application development. >> Okay, so we heard this morning in the keynote, some exciting news. What can you tell us, Kevin? >> Yeah, so this morning we launched S3 Multi-Region Access Points and these are access points that give you a single global endpoint to access data sets that can span multiple S3 buckets in different AWS regions around the world. And so this allows you to build these multi-region applications and multi-region architectures with, you know, with the same approach that you use in a single region and then run these applications anywhere around the world. >> Okay. So if I interpret this correctly, it's a good fit for organizations with clients or operations around the globe. So for instance, gaming, news outlets, think of content delivery types of customers. Should we think about this as multi-region storage and why is that so important in your view? >> Absolutely. Yeah, that is multi-region storage. And what we're hearing is seeing as customers grow and we have multinational customers who have operations all around the world. And so as they've grown and their data needs grow around the world, they need to be using multiple AWS regions to store and access that data. Sometimes it's for low latency so that it can be closer to their end users or their customers, other times it's for regions where they just have a particular need to have data in a particular geography. But this is really a simple way of having one endpoint in front of data, across multiple buckets. So for applications it's quite easy, they just have that one end point and then the data, the requests are automatically routed to the nearest region. >> Now earlier this year, S3 turned 15. What makes S3 different, Kevin in your view? >> Yeah, it turned 15. It'll be 16 soon, you know, S3 really, I think part of the difference is it just operates at really an unprecedented scale with, you know, more than a hundred trillion objects and regularly peaking to tens of millions of requests per second. But it's really about the resiliency and availability and durability that are our responsibility and we focus every single day on protecting those characteristics for customers so that they don't have to. So that they can focus on building the businesses and applications that they need to really run their business and not worry about the details of running highly available storage. And so I think that's really one of the key differences with S3. >> You know, I first heard the term data lake, it was early last decade. I think it was around 2011, 2012 and obviously the phrase has stuck. How are S3 and data lakes simpatico, and how have data lakes on S3 changed or evolved over the years? >> Yeah. You know, the idea of data lakes, obviously, as you say, came around nine or 10 years ago, but I actually still think it's really early days for data lakes. And just from the standpoint of, you know, originally nine or 10 years ago, when we talked about data lakes, we were looking at maybe tens of terabytes, hundreds of terabytes, or a low number of petabytes and for a lot of data lakes, we're still seeing that that's the kind of scale that currently they're operating at, but I'm also seeing a class of data lakes where you're talking about tens or hundreds of petabytes or even more, and really just being used to drive critical aspects of customer's businesses. And so I really think S3, it's been a great place to run data lakes and continues to be. We've added a lot of capability over the last several years, you know, specifically for that data lake use case. And we're going to continue to do that and grow the feature set for data lakes, you know, over the next many years as well. But really, it goes back to the fundamentals of S3 providing that 11 9s of durability, the resiliency of having three independent data centers within regions. So the customers can use that storage knowing their data is protected. And again, just focus on the applications on top of that data lake and also run multiple applications, right? The idea of a data lake is you're not limited to one access pattern or one set of applications. If you want to try out a new machine learning application or something, do some advanced analytics, that's all possible while running the in-flight operational tools that you also have against that data. So it allows for that experimentation and for transforming businesses through new ideas. >> Yeah. I mean, to your point, if you go back to the early days of cloud, we were talking about storing, you know, gigabytes, maybe tens of terabytes that was big. Today, we're talking about hundreds and hundreds of terabytes, petabytes. And so you've got huge amount of information customers that are of that size and that scale, they have to optimize costs. Really that's top of mind, how are you helping customers save on storage costs? >> Absolutely. Dave, I mean, cost optimization is one of the key things we look at every single year to help customers reduce their costs for storage. And so that led to things like the introduction of S3 Intelligent Tiering, 10 years ago. And that's really the only cloud storage class that just delivers the automatic storage cost savings, as data access patterns change. And, you know, we deliver this without performance impact or any kind of operational overhead. It's really intended to be, you know, intelligent where customers put the data in. And then we optimize the storage cost. Or for example, last year we launched S3 Storage Lens, which is really the first and only service in the cloud that provides organization-wide visibility into where customers are storing their data, what the request rates are and so forth against their storage. So when you talk about these data lakes of hundreds of petabytes or even smaller, these tools are just really invaluable to help customers reduce their storage costs year after year. And actually, Dave I'm pleased, you know, today we're also announcing the launch of some improvements to S3 Intelligent Tiering, to actually further automate the cost savings. And what we're doing is we're actually removing the minimum storage duration. Previously, Intelligent Tiering had a 30 day minimum storage duration, and we're also eliminating our monitoring and automation charge for small objects. So previously there was that monitoring and automation charge applied to all objects independent of size. And now any object less than 120 kilobytes is not charged at that charge. So, and I think some pretty critical innovations on Intelligent Tiering that will help customers use that for an even wider set of data lake and other applications. >> That's three, it's ubiquitous. The innovation continues. You can learn more by attending the Storage Day S3 deep dive right after this interview. Thank you, Kevin Miller. Great to have you on the program. >> Yeah, Dave, thanks for having me. Great to see you. >> You're welcome, this is Dave Vellante and you're watching theCUBE's coverage of AWS Storage Day. Keep it right there. (bright music)

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cube. We're here with Omar assad is the vice president GM of H P S H C I and primary storage and data management business. And Sandeep Singh was the vice president of marketing for HP storage division. Welcome gents. Great to see you. >>Great to be here. Dave, >>It's a pleasure to be here today. >>Hey, so uh, last month you guys, you made a big announcement and and now you're, you know, shining the spotlight on that here at discover Cindy. Maybe you can give us a quick recap, what do we need to know? >>Yeah, Dave. We announced that we're expanding HB Green Lake by transforming HB storage to a cloud native software defined data services business. We unveiled a new vision for data that accelerates data, dream of transformation for our customers. Uh and it introduced a and we introduced the data services platform that consists of two game changing innovations are first announcement was Data services cloud console. It's a SAS based console that delivers the cut operational agility and it's designed to unify data operations through a suite of cloud data services. Our 2nd announcement is HPE. Electra. It's cloud native data infrastructure to power your data edge to cloud. And it's managed natively with data services cloud console to bring that cloud operational model to our customers wherever their data lives together with the data services platform. Hp Green Green Lake brings that cloud experience to our customers data across edge and on premises environment and lays the foundation for our customers to shift from managing storage to managing data. >>Well, I think it lays the foundation for the next decade. You know, when we entered this past decade, we we were Ricky bobby's terms like software led that that sort of morphed into. So the software defined data center containers with kubernetes, Let's zoom out for a minute. If we can homer maybe you could describe the problems that you're trying to address with this announcement. >>Thanks dave. It's always a pleasure talking to you on these topics. So in my role as general manager for primary storage, I speak with the hundreds of customers across the board and I consistently hear that data is at the heart of what our customers are doing and they're looking for a data driven transformative approach to their business. But as they engage on these things, there are two challenges that they consistently faced. The first one is that managing storage at scale Is rife with complexity. So while storage has gotten faster in the last 20 years, managing a single array or maybe two or three arrays has gotten simpler over time. But managing storage at scale when you deploy fleet. So storage as customers continue to gather, store and lifecycle that data. This process is extremely frustrating for customers. Still I. T. Administrators are firefighting, they're unable to innovate for their business because now data spans all the way from edge to corridor cloud. And then with the advent of public cloud there's another dimension of multi cloud that has been added to their data sprawl. And then secondly what what we what we consistently hear is that idea administrators need to shift from managing storage to managing data. What this basically means is that I. D. Has a desire to mobilize, protect and provision data seamlessly across its lifecycle and across the locations that it is stored at. Uh This ensures that I. D. Leaders uh and also people within the organization understand the context of the data that they store and they operate upon. Yet data management is an extremely big challenge and it is a web of fragmented data silos across processes across infrastructure all the way from test and dev to administration uh to production uh to back up to lifecycle data management. Uh And so up till now data management was tied up with storage management and this needs to change for our customers especially with the diversity of the application workloads as they're growing and as customers are expanding their footprint across a multi cloud environment >>just to add to almost uh response there. We recently conducted a survey that was actually done by E. S. She. Um and that was a survey of IT. decision makers. And it's interesting what it showcased, 93% of the respondents indicated that storage and data management complexity is impeding their digital transformation. 95% of the respondents indicated that solving storage and data management complexity is a top 10 business initiative for them and 94% want to bring the cloud experience on premises, >>you know, al china. And I think as you guys move to the sort of software world and container world affinity to developers homer, you talked about, you know, things like data protection and we talk about security being bolted on all the time. Now. It's designed in it's it's done at sort of the point of creation, not as an afterthought. And that's a big change that we see coming. Uh But let's talk about, you know, what also needs to change as customers make the move from this idea of managing storage to to managing data or maybe you can take that one. >>That's a that's a that's a very interesting problem. Right. What are the things that have to be true in order for us to move into this new data management model? So, dave one of the things that the public cloud got right is the cloud operational model uh which sets the standard for agility and a fast pace for our customers in a classic I. T. On prime model, if you ever wanted to stand up an application or if you were thinking about standing up a particular workload, uh you're going to file a series of I. T. Tickets and then you're at the mercy of whatever complex processes exist within organization and and depending on what the level of approvals are within a particular organization, standing up a workload can take days, weeks or even months in certain cases. So what cloud did was they brought that level of simplicity for someone that wanted to instead she ate an app. This means that the provisioning of underlying infrastructure that makes that workload possible needs to be reduced to minutes from days and weeks. But so what we are intending to do over here is to bring the best of both worlds together so that the cloud experience can be experienced everywhere with ease and simplicity and the customers don't need to change their operating model. So it's blending the two together. And that's what we are trying to usher in into this new era where we start to differentiate between data management and storage management as two independent things. >>Great, thank you for that. Omer sometimes I wonder if you could share with the audience, you know, the vision that you guys unveiled, What does it look like? How are you making it actually substantive and and real? >>Yeah. Dave. That's also great question. Um across the board it's time to reimagine data management. Everything that homer shared. Those challenges are leading to customers needing to break down the silos and complexity that plagues these distributed data environments. And our vision is to deliver a new data experience that helps customers unleash the power of data. We call this vision unified data jobs, Unified Data Ops integrates data centric policies to streamline data management, cloud native control to bring the cloud operational model to where customers data labs and a I driven insights to make the infrastructure invisible. It delivers a new data experience to simplify and bring that agility of cloud to data infrastructure. Streamline data management and help customers innovate faster than ever before. We're making the promise of Unified Data Ops Real by transforming Hve storage to a cloud native software defined data services business and introducing a data services platform that expands Hve Green Lake. >>I mean, you know, you talk about the complexity, I see, I look at it as you kind of almost embracing the complexity saying, look, it's gonna keep getting more complex as the cloud expands to the edge on prem Cross cloud, it gets more complex underneath. What you're doing is you're almost embracing that complexity and putting a layer over it and hiding that complexity from from the end customer that and so they can spend their time doing other things over. I wonder if you can maybe talk a little bit more about the data services console, Is it sort of another software layer to manage infrastructure? What exactly is it? >>It's a lot more than that, Dave and you're you're 100% right. It's basically we're attempting in this release to attack that complexity head on. So simply put data services. Cloud console is a SAS based console that delivers cloud operational model and cloud operational agility uh to our customers. It unifies data operations through a series of cloud data services that are delivered on top of this console to our customers in a continuous innovation stream. Uh And what we have done is going back to the point that I made earlier separating storage and data management and putting the strong suites of each of those together into the SAS delivered console for our customers. So what we have done is we have separated data and infrastructure management away from physical hardware to provide a comprehensive and a unified approach to managing data and infrastructure wherever it lives. From a customer's perspective, it could be at the edge, it could be in a coal. Oh, it could be in their data center or it could be a bunch of data services that are deployed within the public cloud. So now our customers with data services. Cloud console can manage the entire life cycle of their data from all the way from deployment, upgrading and optimizing it uh from a single console from anywhere in the world. Uh This console is designed to streamline data management with cloud data services that enable access to data. It allows for policy-based data protection, it allows for an organizational wide search on top of your storage assets. And we deliver basically a 360° visibility to all your data from a single console that the customer can experience from anywhere. So, so if you look at the journey the way we're deciding to deliver this. So the first, in its first incarnation, uh Data services, Cloud console gives you infrastructure and cloud data services to start to do data management along with that. But this is that foundation that we are placing in front of our customers, the SAS console, through which we get touch our customers on a daily basis. And now as our customers get access to the SAAS platform on the back end, we will continue to roll in additional services throughout the years on a true SAS based innovation base for our customers. And and these services can will be will be ranging all the way from data protection to multiple out data management, all the way to visibility all the way to understanding the context of your data as it's stored across your enterprise. And in addition to that, we're offering a consistent revised unified Api which allows for our customers to build automation against their storage infrastructure. Without ever worrying about that. As infrastructure changes, uh, the A. P I proof points are going to break for them. That is never going to happen because they are going to be programming to a single SAS based aPI interface from now on. >>Right. And that brings in this idea of infrastructure as code because you talk about as a service to talk about Green Lake and and my question is always okay. Tell me what's behind that. And if and if and if and if you're talking about boxes and and widgets, that's a it's a problem. And you're not, you're talking about services and A P. I. S and microservices and that's really the future model and infrastructure is code and ultimately data as code is really part of that. So, All right. So you guys, I know some of your branding folks, you guys give deep thought to this. So the second part of the announcement is the new product brands and deep maybe you can talk about that a little bit. >>Sure. Ultimately delivering the cloud operational model requires cognitive data infrastructure and that has been engineered to be natively managed from the cloud. And that's why we have also introduced H. P. E. Electra. Omar, Can you perhaps described HB electro even more. >>Absolutely. Thank you. Sandy. Uh, so with with HB Electoral we're launching a new brand of cloud native hardware infrastructure to power our customers data all the way from edge to the core to the cloud. The releases are smaller models for the edge then at the same time having models for the data center and then expanding those services into the public cloud as well. Right. All these hardware devices, Electoral hardware devices are cloud native and powered by our data services. Cloud Council, we're announcing two models with this launch H. P. E Electoral 9000. Uh, this is for our mission critical workloads. It has its history and bases in H P E. Primera. It comes with 100% availability guarantee. Uh It's the first of its type in the industry. It comes with standard support contract, no special verb is required. And then we're also launching HB Electoral 6000. Uh These are based in our history of uh nimble storage systems. Uh These these are for business critical applications, especially for that mid range of the storage market, optimizing price, performance and efficiency. Both of these systems are full envy any storage powered by our timeless capabilities with data in place upgrades. And then they both deliver a unified infrastructure and data management experience through the data services, cloud console. Uh And and and at the back end unified Ai Ops experience with H P. E. Info site is seamlessly blended in along with the offering for our >>customers. So this is what I was talking about before. It's sort of not your grandfather's storage business anymore. This is this is this is something that is part of that, that unified vision, that layer that I talked about, the A. P. I. Is the program ability. So you're you're reaching into new territory here. Maybe you can give us an example of how the customers experience what that looks like. >>Excellent. Love to Dave. So essentially what we're doing is we're changing the storage experience to a true cloud operational model for our customers. These recent announcements that we just went through along with, indeed they expand the cloud experience that our customers get with storage as a service with HP Green Lake. So a couple of examples to make this real. So the first of all is simplified deployment. Uh So I t no longer has to go through complex startup and deployment processes. Now all you need to do is these systems shipped and delivered to the customer's data center. Operational staff just need to rack and stack and then leave connect the power cable, connect the network cable. And the job is done. From that point onwards, data services console takes over where you can onboard these systems, you can provision these systems if you have a pre existing organization wide security as well as standard profile setup in data services console, we can automatically apply those on your behalf and bring these systems online. From a customer's perspective, they can be anywhere in the world to onboard these systems, they could be driving in a car, they could be sitting on a beach. Uh And and you know, these systems are automatically on boarded through this cloud operational model which is delivered through the SAAS application for our customers. Another big example. All that I'd like to shed light on is intent based provisioning. Uh So Dave typically provisioning a workload within a data center is an extremely spreadsheet driven trial and error kind of a task. Which system do I land it on? Uh Is my existing sl is going to be affected which systems that loaded which systems are loaded enough that I put this additional workload on it and the performance doesn't take. All of these decisions are trial and error on a constant basis with cloud Data services console along with the electron new systems that are constantly in a loop back information feeding uh Typical analytics to the console. All you need to do is to describe the type of the workload and the intent of the workload in terms of block size S. L. A. That you would like to experience at that point. Data services console consults with intra site at the back end. We run through thousands of data points that are constantly being given to us by your fleet and we come back with a few recommendations. You can accept the recommendation and at that time we go ahead and fully deploy this workload on your behalf or you can specify a particular system and then people try to enforce the S. L. A. On that system. So it completely eliminates the guesswork and the planning that you have to do in this regard. Uh And last but not the least. Uh You know, one of the most important things is, you know, upgrades has been a huge problem for our customers. Uh And typically oftentimes when you're not in this constant, you know, loop back communication with your customers. It often is a big challenge to identify which release or which bug fix or which update goes on to which particular machine, all of that has been completely taken away from our customers and fully automated. Uh We run thousands of signatures across are installed base. We identify which upgrades need to be curated for which machines in a fleet for a particular customer. And then if it applies to that customer we presented, and if the customer accepts it, we automatically go ahead and upgrade the system and and and last, but not the least from a global management perspective. Now, a customer has an independent data view of their data estate, independent from a storage estate and data services. Council can blend the two to give a consistent view or you can just look at the fleet view or the data view. >>It's kind of the holy Grail. I mean I've been in this business a long time and I think I. T. People have dreamt about you know this kind of capability for for a long long time. I wonder if we could sort of stay on the customers for a moment here and and talk about what's enabled. Now. Everybody's talking digital transformation. I joke about the joke. Not funny. The force marched to digital with Covid. Uh and we really wasn't planned for but the customers really want to drive now that digital transfer some of them are on the back burner and now they're moving to the front burner. What are the outcomes that are that are enabled here? Omar. >>Excellent. So so on on a typical basis for a traditional I. T. Customer this cloud operational model means that you know information technology staff can move a lot faster and they can be a lot more productive on the things that are directly relevant to their business. They can get up to 99% of the savings back to spend more time on strategic projects or best of all spend time with their families rather than managing and upgrading infrastructure and fleets of infrastructure. Right for line of business owners, the new experience means that their data infrastructure can be presented can be provision where the self service on demand type of capability. Uh They necessarily don't have to be in the data center to be able to make those decisions. Capacity management, performance management, all of that is died in and presented to them wherever they are easy to consume. SaS based models and especially for data innovators, whether it's D B A s, whether it's data analysts, they can start to consume infrastructure and ultimately data as a code to speed up their app development because again, the context that we're bringing forward is the context of data decoupling it from. Actually, storage management, storage management and data management are now two separate domains that can be presented through a single console to tie the end to end picture for a customer. But at the end of the day, what we have felt is that customers really, really want to rely and move forward with the data management and leave infrastructure management to machine oriented task, which we have completely automated on their behalf. >>So I'm sure you've heard you got the memo about, you know, H H p going all in on as a service. Uh it is clear that the companies all in. How does this announcement fit in to that overall mission? Cindy >>dave We believe the future is edge to cloud and our mission is to be the edge to cloud platform as a service company and as as HB transforms HP Green Lake is our unified cloud platform. Hp Green Link is how we deliver cloud services and agile cloud experiences to customers applications and data across the edge to cloud. With the storage announcement that we made recently, we announced that we're expanding HB Green Lake with as a service transformation of the HPV storage business to a cloud native software defined data services business. And this expands storage as a service, delivering full cloud experience to our customers data across edge and on prem environment across the board were committed to being a strategic partner for every one of our customers and helping them accelerate their digital transformation. >>Yeah, that's where the puck is going guys. Hey as always great conversation with with our friends from HP storage. Thanks so much for the collaboration and congratulations on the announcements and and I know you're not done yet. >>Thanks. Dave. Thanks. Dave. >>Thanks. Dave. It's a pleasure to be here. >>You're very welcome. And thank you for being with us for hp. You discovered 2021 you're watching the cube, the leader digital check coverage. Keep it right there, but right back. >>Yeah. Yeah.

>>Hello. I'm Professor Toru Suzuki Cherif cardiovascular medicine on associate dean of the College of Life Sciences at the University of Leicester in the United Kingdom, where I'm also director of the Lester Life Sciences accelerator. I'm also honorary consultant cardiologist within our university hospitals. It's part of the national health system NHS Trust. Today, I'd like to talk to you about our Lester Clinical Data Science Initiative. Now brief background on Lester. It's university in hospitals. Lester is in the center of England. The national health system is divided depending on the countries. The United Kingdom, which is comprised of, uh, England, Scotland to the north, whales to the west and Northern Ireland is another part in a different island. But national health system of England is what will be predominantly be discussed. Today has a history of about 70 years now, owing to the fact that we're basically in the center of England. Although this is only about one hour north of London, we have a catchment of about 100 miles, which takes us from the eastern coast of England, bordering with Birmingham to the west north just south of Liverpool, Manchester and just south to the tip of London. We have one of the busiest national health system trust in the United Kingdom, with a catchment about 100 miles and one million patients a year. Our main hospital, the General Hospital, which is actually called the Royal Infirmary, which can has an accident and emergency, which means Emergency Department is that has one of the busiest emergency departments in the nation. I work at Glen Field Hospital, which is one of the main cardiovascular hospitals of the United Kingdom and Europe. Academically, the Medical School of the University of Leicester is ranked 20th in the world on Lee, behind Cambridge, Oxford Imperial College and University College London. For the UK, this is very research. Waited, uh, ranking is Therefore we are very research focused universities as well for the cardiovascular research groups, with it mainly within Glenn Field Hospital, we are ranked as the 29th Independent research institution in the world which places us. A Suffield waited within our group. As you can see those their top ranked this is regardless of cardiology, include institutes like the Broad Institute and Whitehead Institute. Mitt Welcome Trust Sanger, Howard Hughes Medical Institute, Kemble, Cold Spring Harbor and as a hospital we rank within ah in this field in a relatively competitive manner as well. Therefore, we're very research focused. Hospital is well now to give you the unique selling points of Leicester. We're we're the largest and busiest national health system trust in the United Kingdom, but we also have a very large and stable as well as ethnically diverse population. The population ranges often into three generations, which allows us to do a lot of cohort based studies which allows us for the primary and secondary care cohorts, lot of which are well characterized and focused on genomics. In the past. We also have a biomedical research center focusing on chronic diseases, which is funded by the National Institutes of Health Research, which funds clinical research the hospitals of United Kingdom on we also have a very rich regional life science cluster, including med techs and small and medium sized enterprises. Now for this, the bottom line is that I am the director of the letter site left Sciences accelerator, >>which is tasked with industrial engagement in the local national sectors but not excluding the international sectors as well. Broadly, we have academics and clinicians with interest in health care, which includes science and engineering as well as non clinical researchers. And prior to the cove it outbreak, the government announced the £450 million investment into our university hospitals, which I hope will be going forward now to give you a brief background on where the scientific strategy the United Kingdom lies. Three industrial strategy was brought out a za part of the process which involved exiting the European Union, and part of that was the life science sector deal. And among this, as you will see, there were four grand challenges that were put in place a I and data economy, future of mobility, clean growth and aging society and as a medical research institute. A lot of the focus that we have been transitioning with within my group are projects are focused on using data and analytics using artificial intelligence, but also understanding how chronic diseases evolved as part of the aging society, and therefore we will be able to address these grand challenges for the country. Additionally, the national health system also has its long term plans, which we align to. One of those is digitally enabled care and that this hope you're going mainstream over the next 10 years. And to do this, what is envision will be The clinicians will be able to access and interact with patient records and care plants wherever they are with ready access to decision support and artificial intelligence, and that this will enable predictive techniques, which include linking with clinical genomic as well as other data supports, such as image ing a new medical breakthroughs. There has been what's called the Topol Review that discusses the future of health care in the United Kingdom and preparing the health care workforce for the delivery of the digital future, which clearly discusses in the end that we would be using automated image interpretation. Is using artificial intelligence predictive analytics using artificial intelligence as mentioned in the long term plans. That is part of that. We will also be engaging natural language processing speech recognition. I'm reading the genome amusing. Genomic announced this as well. We are in what is called the Midland's. As I mentioned previously, the Midland's comprised the East Midlands, where we are as Lester, other places such as Nottingham. We're here. The West Midland involves Birmingham, and here is ah collective. We are the Midlands. Here we comprise what is called the Midlands engine on the Midland's engine focuses on transport, accelerating innovation, trading with the world as well as the ultra connected region. And therefore our work will also involve connectivity moving forward. And it's part of that. It's part of our health care plans. We hope to also enable total digital connectivity moving forward and that will allow us to embrace digital data as well as collectivity. These three key words will ah Linkous our health care systems for the future. Now, to give you a vision for the future of medicine vision that there will be a very complex data set that we will need to work on, which will involve genomics Phanom ICS image ing which will called, uh oh mix analysis. But this is just meaning that is, uh complex data sets that we need to work on. This will integrate with our clinical data Platforms are bioinformatics, and we'll also get real time information of physiology through interfaces and wearables. Important for this is that we have computing, uh, processes that will now allow this kind of complex data analysis in real time using artificial intelligence and machine learning based applications to allow visualization Analytics, which could be out, put it through various user interfaces to the clinician and others. One of the characteristics of the United Kingdom is that the NHS is that we embrace data and captured data from when most citizens have been born from the cradle toe when they die to the grave. And it's important that we were able to link this data up to understand the journey of that patient. Over time. When they come to hospital, which is secondary care data, we will get disease data when they go to their primary care general practitioner, we will be able to get early check up data is Paula's follow monitoring monitoring, but also social care data. If this could be linked, allow us to understand how aging and deterioration as well as frailty, uh, encompasses thes patients. And to do this, we have many, many numerous data sets available, including clinical letters, blood tests, more advanced tests, which is genetics and imaging, which we can possibly, um, integrate into a patient journey which will allow us to understand the digital journey of that patient. I have called this the digital twin patient cohort to do a digital simulation of patient health journeys using data integration and analytics. This is a technique that has often been used in industrial manufacturing to understand the maintenance and service points for hardware and instruments. But we would be using this to stratify predict diseases. This'll would also be monitored and refined, using wearables and other types of complex data analysis to allow for, in the end, preemptive intervention to allow paradigm shifting. How we undertake medicine at this time, which is more reactive rather than proactive as infrastructure we are presently working on putting together what's it called the Data Safe haven or trusted research environment? One which with in the clinical environment, the university hospitals and curated and data manner, which allows us to enable data mining off the databases or, I should say, the trusted research environment within the clinical environment. Hopefully, we will then be able to anonymous that to allow ah used by academics and possibly also, uh, partnering industry to do further data mining and tool development, which we could then further field test again using our real world data base of patients that will be continually, uh, updating in our system. In the cardiovascular group, we have what's called the bricks cohort, which means biomedical research. Informatics Center for Cardiovascular Science, which was done, started long time even before I joined, uh, in 2010 which has today almost captured about 10,000 patients arm or who come through to Glenn Field Hospital for various treatments or and even those who have not on. We asked for their consent to their blood for genetics, but also for blood tests, uh, genomics testing, but also image ing as well as other consent. Hable medical information s so far there about 10,000 patients and we've been trying to extract and curate their data accordingly. Again, a za reminder of what the strengths of Leicester are. We have one of the largest and busiest trust with the very large, uh, patient cohort Ah, focused dr at the university, which allows for chronic diseases such as heart disease. I just mentioned our efforts on heart disease, uh which are about 10,000 patients ongoing right now. But we would wish thio include further chronic diseases such as diabetes, respiratory diseases, renal disease and further to understand the multi modality between these diseases so that we can understand how they >>interact as well. Finally, I like to talk about the lesser life science accelerator as well. This is a new project that was funded by >>the U started this January for three years. I'm the director for this and all the groups within the College of Life Sciences that are involved with healthcare but also clinical work are involved. And through this we hope to support innovative industrial partnerships and collaborations in the region, a swells nationally and further on into internationally as well. I realized that today is a talked to um, or business and commercial oriented audience. And we would welcome interest from your companies and partners to come to Leicester toe work with us on, uh, clinical health care data and to drive our agenda forward for this so that we can enable innovative research but also product development in partnership with you moving forward. Thank you for your time.

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Welcome back everyone to the cubes live coverage of Microsoft ignite. I'm your host, Rebecca Knight, along with my co host to minimun. We are doing joined by Donna Sarkar. She is the advocate lead Microsoft power platform at Microsoft. Thank you so much for coming on the show. Thank you very much for having me. Tai cube land. So tell us a little bit about power platform. It's something we're hearing some buzz about, but we still need the overview. What is it all about? All right, so for years, decades we in the tech industry, you have been on this mission where we say everyone in the world can benefit from learning to code, right? Uh, whether you're a farmer and accountant, a teacher, a lawyer, a doctor, some sort of code will help you do your job better and you'll be able to automate away boring tasks and make apps and websites to solve your business problems. >>Right? We've been saying this forever and soon we started to realize like, why are we asking everyone to learn to code when the end goal is to solve those business problems, right? So instead of learning to code, why not create a suite of low code or no code tools? So all of these people who we call citizen developers who may not be professional developers as in they didn't go to computer science school, they didn't do a coding boot camp. They don't live in visual studio all day. How can they use these low code tools to solve their specific business problems? So that's like the vision of power platform and they're, I would say six independent pillars of it. Um, the first one, the one that most people know is power BI, which is a dashboard to visualize data and you know, um, traction in your business and all of that. >>So that's the one that most of the fortune 500 are like quite familiar with. The second one that I think a lot of people have used, used to be called Microsoft flow. So this is a automation tool where you'd say, if I get an email, send me a text, you know, a kind of a, if this happens, then that happens. It's just a logical tool that connects lots and lots of services in our life together that has been renamed to power automate to focus more on the automation that many businesses have that we actually have not thought about for decades. How do we automate some of these processes that people have to do all the time? Third thing if I could. So of course one of the new announcements this week, power automate is the RPA piece. Yes. Come out there. So I guess it's a suite and this is a new offering as RPA. >>The robotic process automation is how we can, um, do UI automation, which is a huge pain in the neck. Like it's terrible because you say, Oh click box, wait three seconds, wait for this thing to happen. Sleep 10 sec. It is terrible. I've done UI automation, I hate it. UI automation. So much. So RPA, what it does for you is you perform the act actions and the code is generated and it replays. So that is this powerful tool for anyone who has to do any sort of repetitive scan form, scan, form, scan form, you know, sort of thing. So power automate. The third pillar is PowerApps, which I think everyone hears a lot about today, which is um, apps that are generated from whatever data source that you've got. Say you've got an Excel spreadsheet having, and I saw all of your guests are it all tracked in an Excel spreadsheet, right? >>Donna's coming now, Christina is coming next and there's Christina now and imagine you can see them in an app instead. And all of you have this app on your phone, you can say, Oh, what's on the docket for today, right? Donna's showing up at 11 Christina's at 1130 what are the questions we want to ask Donna? Click on the Donna tab, you get all the questions you want to talk to her about, et cetera. So PowerApps is a way to quickly generate an app from a data source without code. We have a whole bunch of templates depending on what you're trying to do. So maybe you're trying to make a gallery of photos or you're trying to make like an expense tool or like a gas mileage tool or whatever you're trying to do that every single business in the world has the same tools, slightly different. >>So the fourth thing is, um, a new announcement called power virtual assist, which is, um, think about it as simplified chatbots, right? Chatbots are everywhere. Uh, the way people think about making them is, Oh, I have to go get Azure cognitive services and learn it deeply and become a AI expert and learn to like speak natural language processing stuff. But in fact, you can build a chat bot in five minutes using power virtual assist, which was fantastic and really cool. And running through all of this is my favorite that I learned a lot about this week, which is called the AI builder. And AI builder is a tool really that brings intelligence to all of these things and makes you feel it kind of a badass. I'm like, Oh, I trained an AI model and deployed it and tested it on stage. That's crazy and cool. And I learned to do that in five minutes and believe you me, I'm not a data scientist. >>So it was a really, really cool set of tools that I personally, even as a pro developer, I'm very excited about. Well, I want to dig into the tools more than what they can do. But I first want to ask you a personal question because you're new to the role. You've been there two weeks. What made you, what was exciting to you about working with power platforms? So I've been at Microsoft for 14 years and I've always been in the windows division and I've always worked in a software engineering function. So always dealing with like C plus plus code comm code, how do we, what product code do we changes, do we make to windows the. And recently I've been realizing that my personal mission that anyone in the world should have my opportunities. It's, that's really important to me. Right? I grew up underserved society in Detroit, Michigan, right? >>I don't, I often feel like I don't deserve this life that I have and I fell into it because of luck and circumstance and I want other people to have these opportunities and not feel that same kind of impostor thing. So I always believe that tech is this, you know, this sword, this weapon that you can wield and it will as you make your way through the world and it creates so many opportunities, right? It, the opera and anyone in the world wants to hire a software engineer. Every company, right? Every company wants to hire devs. It doesn't matter if you're like government or like oil rigs, you want software developers. And I thought, what an amazing economic power and I want lots of people to have that. And lo and behold, I was offered the opportunity to head up a brand new advocacy team for the power platform, um, as part of the Azure advocates organization. >>And I said, Oh, that's amazing to be able to line up my personal passion with a mission in the company that doesn't come along very often. So I love my job. So it's interesting thought. I would love your viewpoint as someone that's been with Microsoft for 14 years, cause I know a lot of the advocacy people and many of them are ones that if you ask them if they would have joined Microsoft five years ago, I'm not sure. Sure. So you know, moving from windows to there. Tell us a little bit about culturally what's different about Microsoft today and you know, much more obviously than just windows. Yeah. Um, I would say that there's three things that are dramatically different. There's a lot of like things that people notice, but three things I think that are just, you can't even argue about it. One, we are definitely a learn it all mindset rather than a nodal where it's actually much better now to say, I do not know. >>Let's go find out, let's go do an experiment and then we'll have an answer. And that's much better than with great confidence saying something wrong. Right. Oh I know this will work for sure. I guarantee you. And then it not working because you're being a know it all rather than the learn it all. So that tolerance is off the charts. It's, it's expected. If you come in with a strong opinion with no sort of experimental data to back it up, that's no longer a good thing right now. People almost are suspicious. Like, really? Why do you, why do you think that? Have you checked it? Have you done the experiment? The second thing is, um, this co-creating with customers before, like you're asking about windows. I've worked on windows five versions and it always went a little like this, right? We as the developers would go and hide in Redmond, Washington for three and a half years and one day we would show up and say, here is your operating system. >>We'll see you in three years, have fun using it by, and then we go off and make another operating system. Right? We didn't stick around to figure out, is this operating system working for you? Are you being successful? What's you're trying to do? Are your customer successful? We just went ahead and made what we thought was next, right? Because we were convinced we knew better. But with windows 10 and every other product at Microsoft, now we actually cocreate with our customers, right? That feedback loop is part of the product cycle where we don't ship a product without having a feedback loop. So we shipped something. How are we getting feedback? What is the time baked in to actually take that feedback and make changes? So that's one thing. It's dramatically different. Um, it used to all be timed to code, product, time to fix bugs. >>That's it. Now it's code product, listen to customer feedback, fixed bugs from customers. That's it. So it dramatically shorten the amount of time it took to build an operating system because we don't need to make a three year long product. Instead we make like a six month long product. And when I ran the windows insider program, we were testing windows every week, right? Twice a week we're rolling out versions of windows to millions of people and getting their feedback in real time. And the third thing I'd say that's been a dramatic transformation is this inclusivity of not just different kinds of, you know, race in the city, but work styles, the kinds of businesses we do work with. Like we're a, we do Linux now, right? We do eggs. Um, our platform itself pulls from all sorts of data sources. We don't just say we only pull from Microsoft tech. >>Like if you have Excel, if you have access, if you have Azure, if you've sequel, we support you and everyone else go the heck away. No, we're, we're saying whatever data source you've got, we don't care. We'll build you a power app based on your data source. Bring your whole self to work, right? It's that bring your whole self to a work mindset that I think has permeated just across the company and a chosen our products. So you were talking about this feedback loop and I'm interested because these, these, the power platform was rolled out into 2018 we haven't seen any major revenue yet, but Microsoft sees a ton of promise here. So what was the customer feedback you were given in terms of these updates that you've just announced here at ignite and what were customers demanding, wanting, needing from these platforms, these, these, these tools? >>Well, there's been a few things. One, um, the uptake in power platform, especially power apps is the fastest growth of any business app in Microsoft history. Um, in the last like just two years we've reached 84% of the fortune 500 are running power. Now. That's kind of wild, right? When you think these are normally traditional companies who can be quite conservative, but they've got people, whether it's an it, it's a citizen dove or a PRODA, they're actually building power apps to supplement their business needs, right? So it's been just astronomical growth, which is fantastic. Um, and the feedback from this group is actually what dictates all of the changes we've been making. So one of the key things a lot of people said was we just adopted teams like last year, right? Our company adopted teams, we're all in on teams. All of our communication like realtime has done on teams, but power platform is not with teams. >>What's, what's the deal with that? Right? So the par platform dev team engineering team actually went and figured out how can you have a teams channel, how can you build a power plant, a power app, and then share that power app within your teams specifically. So say the three of us are working on a teams channel and I make a Oh, track your attendees app, the one we're talking about, I can share it within the teams itself and we can just see it from within the team's window. So it'll run within the teams window. Um, we can just deploy it to our phones as well. And with the same team's credentials as we're working, that applies to the app as well. So that's something that just rolled out this week as direct feedback from people who say we're, we want an on the latest and greatest. And that means teams. That's one means SharePoint online. That means our platform. That means all the things now. >>Yeah. So Donna, one of the things I love that you talked about is it doesn't take months to get started on this. So many announcements that you talked through all the six pillars and everything. For those people out there seeing what's new, give them some final tips as to how they should get started with, with the power platform family. >>I would say that um, one of the best things you can do is just get your hands on it, right? Stop reading about it. Stop looking at the announcements. Just get your hands on it. Because I was at first reading all these blog posts trying to understand CDs, power platform, AI builder, all this stuff. Stop. Just don't do it. The best thing to do is to go get on Microsoft learn. There's a start, a starter tutorial called canvas apps for power platform. Um, and go do the tutorial. All it does is it deploys an Excel spreadsheet to your personal machine or your personal one drive, whatever it is and using that, it's just carpet, right? It's like black carpet, white carpet and shows pictures of carpet and then you generate a power app. And it shows it in a gallery view on an app that you just see on your computer and then you deploy it to your phone. >>All it does is show you the power of an Excel spreadsheet converted into an app. So I've created a short URL for it just to make life easier for everyone. So it's AKA dot. Ms power up, super straight forward, super simple. And I talk about this tutorial all the time, not because I think it's the best tutorial that's ever existed, but for someone who has absolutely no idea and they're feeling intimidated to start, this is exactly the right thing to do because this tutorial, I am not kidding you both of you can do it in five minutes. Like on the next break. Once you're finished with me and Christina, I challenge you to do the tutorial. All right? Okay. Challenge accepted. One, one final thing. So you are known for this Ted talk that you gave Unimpossible syndrome earlier in this, in our conversation you said you fell into this like, Oh absolutely, you've gotten lucky, but yet you're a smart woman. >>Talk about imposter syndrome. And then and then give your best advice for the young people out there and an old people to frankly who are suffering. Imposter syndrome is a killer because it is a disease that is a global epidemic. It's not. Some people think it's a woman's problem, it's a people of color problem. No, it's not. It's an everyone problem. Every time I give this talk, the Ted audience was thousands of people. I would say about 70% men and when I asked how many of you feel these symptoms? Hands are up. 70% of people, and this was men too, who feel like I got here. You know the thoughts are usually I got here by accident. It was dumb luck. There's a mistake in the process. I slipped in under the radar any minute. Now someone's going to show up here and say, you don't belong here. >>Get out or someone's going to check my credentials or ask me like, how do you think you're as good as the people around you? Or why are you qualified to speak on this topic? Right? People are convinced this is going to happen. Like, almost everyone is convinced and it's wild. And I've realized the reason that happens is because we are not used to doing that thing yet. That's it. We don't imposter about the things we do every day. You don't imposter about being in camera on front of the camera in front of everyone because you do it all the time and you've gotten good reviews and obviously people come to talk to you. But if tomorrow I was to be like you and I are going to write office abs, you may say, ah, I don't think I'm qualified to do that. I don't know if you are or not. >>I'm just making stuff up at this point. Um, and you may say, I am not qualified to do that. And the reason you say that is because you've never done it before. Why would you be qualified to do that? It's like me trying to be qualified to ride a unicycle, right? Which I can't. So my advice to people who feels this, well I don't feel like I belong here, is break it down right into steps, debug this process and say, all right, there are parts of this process that I feel qualified to do and there's parts I do not feel qualified to do. What are they? So from my own example, I absolutely do not feel qualified to lead an advocacy team for power platform. Right. I said, I joined this team two weeks ago. I just learned about this product last year. How am I qualified to lead advocacy for this? >>So I had to break it down and I said, what? What am I feeling and posturing about? Is it leading advocacy? No, I did it for windows. I did it for hollow lens. I do know how to do that. Is it speaking in front of lots of people? Not really. I do that all the time. Is it writing content so others can learn? Not really. I do that all the time. Is it the product? Yes, it's the product. It's the, I don't feel like I know the ins and outs of the product that well. So if you were to ask me where exactly is the connector for, you know, Azure sequeled or PowerApps, I would just freeze. Like I do not know. I think it's in the Azure portal somewhere, somewhere. So I would feel that sense of imposter and like, Oh, I don't know. >>So I don't belong here. It's no, I just don't know the product that well. That's okay. I know advocacy well, so what I need to do now is identify things. I'm good at advocacy things. I'm not good at product, learn the product. That's it. It just becomes a really easy to do list or to learn list. Right. Learn it all mindset, not know it all. Mindset. I love it. Thank you so much. Thank you is a really terrific conversation. Wonderful. Thanks for having me. I'm Rebecca Knight for Stu Miniman. Stay tuned for more of the cubes live coverage of Microsoft ignite.

>> live from San Francisco, celebrating 10 years of high tech coverage. It's the Cube covering Veum World 2019. Brought to you by VM Wear and its ecosystem partners. >> Welcome back, everyone. Live cube coverage here in Mosconi, north of the Emerald 2019. I'm Javert David launch their 10th year covering the emerald. We here with this team Cube alumni Von Stuart, vice president technology at pier Storage. Great to see you guys another year, another privilege to sit >> down and have a little chat. >> Another. Another year that Vienna where doesn't die of something storage doesn't go away every year. Containers is going to kill the end where this is revealing. The EM wears resiliency as virtualization platform is just second to none has been, well, document. We've been talking about it because the operational efficiencies of what they've done has been great. You guys air kicking butt in storage on again, a sector that doesn't go away. You gotta put the data somewhere. Eso stores continues toe do Well, Congratulations. What's the big What's the big secret? Thanks. >> Well, we just shared our cue to >> financial results last week. 28% year on your growth. We are the by far the fastest growing storage company, and I think there's a lot of disruption for the legacy vendors. Right now. They're getting hit on all angles. Next. Gen. If vendors like us followed by the cloud as well this platforms like H. C, I think it's been it's been a tough sledding for similar legacy vendors. >> Talk about your relationship with the end, where and why that's been so important for pure because again, again, resiliency operations. At the end of the day, that's what the rubber hits the road, making developers happy, but operating it's a key. Yeah, if you look at >> so that's a really good question. If you look at our business, Veum, where is the number one platform deployed on top of pure storage platforms? And that's probably the case for most of the storage vendors because of their dominant position in the infrastructure. That means, as VM were evolves their product platforms right. Well, that's the pivotal acquisition Veum or Claude Foundation via McLaren AWS. And as that'll expand, you have to as a partner continued to jointly innovate, sometimes hand in hand. Sometimes, you know, on parallel paths to drive value into that that market for those customers or you're not gonna make it. And our investments of engineering wise are significant. We've had a large number of new capability that we've ruled out through the years that are specific to VM, where that are either integrations or enhancements to our platform. You know, we believe through external data points, we are the number one V balls vendor, which is, you know, which was something that being were launched about 78 years back. That kind of dip, but has risen back up. Um, and >> we were key, >> I think, um, design partner right now with the cloud platforms, the Via MacLeod Foundation as well as, ah, humor coordinative us. >> So, as you know, this is our 10th year VM world. You go back to 2010. There was what I used to call the storage cartel. And you weren't part of it, right? Had early access to the AP eyes you had. So obviously e m c was in there. Um, you were really the on lee sort of newbie to reach escape velocity. Your storage. Now there's basically two independent storage companies over a billion dollars. You guys a net up. Um, so >> when I was at both, >> you saw you saw >> the opportunity and okay, leaned in hard. Yeah, there >> was a time when he's >> paid off. But so why do you think, um, you were able to be one of the rare ones to achieve escape velocity when many people said that will never happen. You'll never see another $1,000,000,000 storage company. And then I'm interested in how you're achieving number one in Viv balls. In a world where it seems like, you know, the ecosystem is getting a little tighter between Dow Wand VM where? But how do you guys thrive in that dynamic? >> I think there's a challenge for all vendors in terms of market and try to get your message through right. If you if you one better does something well, the rest of the market tries too obvious. Get that. We've been fortunate enough that through our channel ecosystem, our system's integrator partners right to actually be able to demonstrate the technology that gain there enthusiasm to drive it into the market and then actually demonstrated to the customers. And so how does that show up? Uh, I think it's fair to say our platforms are more intelligent, they're more automated and they they operated a greater scale. Then then the competitors and you can look at this through one lens and say, Well, it's Veum or a P I says in that Make all the storage the same And it's like it does from a via more operational standpoint, but it doesn't mean how you deliver on that value Prop or what us. A platform deliver above and beyond is at parody, and that's really where we demonstrate a significant difference. Let me give you one example. We have a lot of customers. Ah, a lot customer growth in the last 12 months around Custer's who are deploying eight c i, along with all flash raise. Right? And David Floyd had reached out recently and said, Well, wouldn't one, you know, compete with the other? It's like, Yes, there's overlap. But what we're finding from customers is they're looking to say if my applications need to be more cost effective, easy to manage its scale, we actually want to put it on all flash rain, You say, How could that be? I'll give you one simply example. Do you know what it takes anywhere from 10 x 200 x, less time to upgrade your V and where infrastructure on a shared array. Then if it's on on hyper converged because you don't have to go through the evacuation and rehydration of all your data twice right? And so things like that, they're just really simple that you wouldn't pick up in like a marketing scheme. If you are a customer at scale, you go well. I can't afford 100 man hours. I can afford woman. And so it's It's simple things like that. It's rapid provisioning. It's not having Silas that are optimized for performance or availability or cost. It's about saying, you know your time to implement is one time life cycle on hardware. But it's probably something happens every quarter for the next three years, right? >> So this is your point about >> innovation in the innovative vendors. Your the modernization of storage is planning for these use cases where the old way didn't work. >> Yeah, yeah, you mentioned that you were 10 years now, and one of things that I've said over the last six or seven years being up yours, one of things I think is really interesting about pure is that our founder, John Call Grove, came out of the volume manager and file system space at Veritas, right? He was the founder for those products. He understood the intersection between managing a storage array and your application, and that goes through our ethos of our products, where I think a lot of storage platforms, a start up platforms come from George guys who worked on the Harbour side. And so they take a faster, you know, Piper faster from the media, and they make another box that behaves like the other box from an operational perspective. >> So he said, a C I a compliment or competitors. I'm still not sure which. Maybe it's both and then say, Same question for V. San. Yeah, how do you So, >> um, on air that we've put a lot of investment in and started one with via more around the middle of last year was putting V sand with pure storage flash race together, and what you see that materialized now is when you look at via MacLeod Foundation or via MacLeod in eight of us. The management domains must be visa, and that's so that you can have an instant out of the box controlled, um, management plane that Veum where you know, executes on and then you have workload domains and those could be on ah, hyper converge platform. Or they could be on third party storage. And when you put those on pure, then you again, all the advantages that we bring to bear as an infrastructure with all the same simplicity scale in lifecycle management that you get from from just, you know, the VM where std see manager. And so it works very well together. Now, look, I'm sure what I share with you here. They'll be some folks who are on the V sand team that they themselves are to be like, you know, B s. But that's the nature of our business. One >> of these I want to get your thoughts on this side. Vons. You've always >> been kind of on the cutting edge on all the conversations we've had. I gotta ask you about the container revolution, which not new doctor came out many many years ago. Jerry Chen when he funded those guys and we covered that extensively upset there was a small changed kubernetes is all the rage orchestrating the containers is a pivotal role in all the action happening here. It's big part of how things were with the app side. So the question is, how does continues impact the storage world? How do you see that being integrated in? There's talk of putting Cooper names on bare metal, so you start to see HC. I come back. Devices are important, she started. See hardware become important again with that? >> Well, I love you. Drop of pivotal there, right? First off, kudos to Vienna, where for the acquisition pill, little guys are exceptional. What they don't have is a lot of customers, but the customers they do have our large customers, right? So we've got a fair amount of pivotal on pure customers, and they are all at scale. So I think it's a great acquisition for VM, where by by far the most enterprise class form of containers today, >> and they've always kind of been the fold. Now they're officially in the fold. Yes, formalize it. >> And so now that the road map that was shared in terms of what via Moore looks to do to integrate containers into the Essex I platform itself right, it's managing V, EMS and containers next year. That's perfect in terms of not having customers have to pick or choose between which platform and where you're going to play something, allow them to say you can deploy on whichever format you want. It runs in the same ecosystem and management, and then that trickles down to the gun in your storage layer. So we do a lot of object storage within the container ecosystems. Today, a lot of high performance objects because you know the file sizes of instances or applications is much larger than you know, a document filed that you or I might create online. So there's a big need around performance in that space, along with again management at scale. It's >> interesting we sent about about Pivotal and I, By the way, I like the acquisition, too, because I think it was cheap. Any time you can pick up $4 billion asset for 800 million in cash, you know gets my attention. But Pivotal was struggling in the marketplace. The stock price never even came close to its I po. You know, it's spending patterns were down. Do you feel as though the integration will VM Where will supercharge Pivotal? >> I absolutely agree that I've had this view that the container ecosystem was really, um uh, segmented you had comes that built their products off a container. So save your twitter or your Facebook, right? The platform that your customers and interact interact with is all ran by containers. Then you have an enterprise. You have containers, which was more kind of classic applications. Right? And that would take time for the applications to be deployed. And so what did you see now for Mike stuff, right? See if you can run as a container. Right? Run is a container. As the enterprise app start to roll over, the enterprise will start to evolve from virtual machines, two containers. And so I think it's the timing's right. That's not to dismiss any of where people I think is built the brand right now, which is helping companies build next gen platforms. You know, after big sure that I don't name drop customers references to pull back there. Yeah, I think the time is right. >> I'm interested in how you guys can further capitalized on containers. And we've been playing around with this notion of of data assurance containers, Fring complexity. And so, you know, complexities oftentimes your friend, because you're all about simplifying complexity. But so how do you capitalize on this container trend in the next 3 to 5 years? So you've got storage >> needs for containers that either tend to be ephemeral or persistent. And I think when containers were virtually created, it was always this notion that would be ephemeral. And it's like, Yeah, but where's the data reside? Ultimately, there's been significant growth around data persistence, and we've driven that in terms of leveraging the flecks of all drivers that have been put into the community, driving that into our pure service orchestrator RPS O'Toole, which supports pivotal in kubernetes derivatives. Today again, we've got proven large scale installs on this. So it's it's, um, it's providing the same class of storage. Service is simplicity and elegance in your integrations that we have for Vienna, where we've been doing that across pivotal already. Pivotals. Interesting, right? They don't validate hardware, the only validate software. So they validate our P S O and having that same value prop for that that infrastructure, because they are scale, you never find a small scale containers ecosystem, and I keep referencing that point when you get to scale considerations around. What does it take to allow that environment to to remain online and holly performance are significant considerations and weak cell >> There. We'll talk about your event coming up. You guys have pierced accelerate September 17th and 18th Coming up Osti the VM where ecosystem that you're part of here. Big part of that. You guys have a lot of customers. I know you can reveal any news, but what's expected at this show? What can people who are interested in either attending or my peach in some of the notable things that might be happening >> lot orange? We know that >> one. Number two I know the cubes gonna be there >> for two days will be there for two days. >> So hopefully you guys will get a load of conversations with both our our team, product management, engineering, maybe some of leadership, but also customers. I think customers are always the best statement you can make about how your how you're doing and market. I think you will see from us a number of announcements that I am prohibited to share today, but some really big things that we're gonna introduce the market. So it should be excited for that. And some just a great showing of our partner. Our alliance ecosystem will be there. Obviously, VM will be there in force as well as red hat with the open >> again, there's gonna be a cloudy >> future for you. It's girls would be very analytical. It's going to be there elastics going to be there. So, you know, >> you guys like to do first of these shows. I mean, kind of I don't view it first with an all flesh array, but probably one of the first if not first the evergreen thing ticked off a lot of people like, Why didn't we think of that? You were first with sort of bundling envy. Any in the whole thing. The announcement you guys made with video. That was before anybody else. You know, your whole cloud play you like, you like to be first, So we expect another first next month. Hopefully we >> will deliver, and, uh, you're not gonna get me to leak anything. >> Thanks for the insight, Vice President. Reality Lions, that pier storage. David, let me stay with us for more coverage. Robin Madlock. CMO is coming on and, of course, tomorrow. Michael Dell, Pat Girl singer and more and more great guest senior vice presidents from VM wear from all different groups. We'll be asking the tough questions here in the Cube. Thanks for watching.

(lively classical music) >> Hello everyone, welcome to this special Cube conversation, we are here at the Power Panel Conversation. I'm John Furrier, in Palo Alto, California, theCUBE studies we have remote on the line here, talk about the cloud technology's impact on entrepreneurship and startups and overall ecosystem is Jim Long, who's the CEO of Didja, which is a startup around disrupting digital TV, also has been an investor and a serial entrepreneur, Sarbjeet Johal, who's the in-cloud influencer of strategy and investor out of Berkeley, California, The Batchery, and also Joseph Jacks, CUBE alumni, actually you guys are all CUBE alumni, so great to have you on. Joseph Jacks is the founder and general partner of OSS Capital, Open Source Software Capital, a new fund that's been raised specifically to commercialize and fund startups around open source software. Guys, we got a great panel here of experts, thanks for joining us, appreciate it. >> Go Bears! >> Nice to be here. >> So we have a distinguished panel, it's the Power Panel, we're on cloud technos, first I'd like to get you guys' reaction you know, you're to seeing a lot of negative news around what Facebook has become, essentially their own hyper-scale cloud with their application. They were called the digital, you know, renegades, or digital gangsters in the UK by the Parliament, which was built on open source software. Amazon's continuing to win, Azure's doing their thing, bundling Office 365, making it look like they've got more revenue with their catching up, Google, and then you got IBM and Oracle, and then you got an ecosystem that's impacted by this large scale, so I want to get your thoughts on first point here. Is there room for more clouds? There's a big buzzword around multiple clouds. Are we going to see specialty clouds? 'Causes Salesforce is a cloud, so is there room for more cloud? Jim, why don't you start? >> Well, I sure hope so. You know, the internet has unfortunately become sort of the internet of monopolies, and that doesn't do anyone any good. In fact, you bring up an interesting point, it'd be kind of interesting to see if Facebook created a social cloud for certain types of applications to use. I've no idea whether that makes any sense, but Amazon's clearly been the big gorilla now, and done an amazing job, we love using them, but we also love seeing, trying out different services that they have and then figuring out whether we want to develop them ourselves or use a specialty service, and I think that's going to be interesting, particularly in the AI area, stuff like that. So I sure hope more clouds are around for all of us to take advantage of. >> Joseph, I want you to weigh in here, 'cause you were close to the Kubernetes trend, in fact we were at a OpenStack event when you started Kismatic, which is the movement that became KubeCon Cloud Native, many many years ago, now you're investing in open source. The world's built on open source, there's got to be room for more clouds. Your thoughts on the opportunities? >> Yeah, thanks for having me on, John. I think we need a new kind of open collaborative cloud, and to date, we haven't really seen any of the existing major sort of large critical mass cloud providers participate in that type of model. Arguably, Google has probably participated and contributed the most in the open source ecosystem, contributing TensorFlow and Kubernetes and Go, lots of different open source projects, but they're ultimately focused on gravitating huge amounts of compute and storage cycles to their cloud platform. So I think one of the big missing links in the industry is, as we continue to see the rise of these large vertically integrated proprietary control planes for computing and storage and applications and services, I think as the open source community and the open source ecosystem continues to grow and explode, we'll need a third sort of provider, one that isn't based on monopoly or based on a traditional proprietary software business like Microsoft kind of transitioning their enterprise customers to services, sort of Amazon in the first camp vertically integrated many a buffet of all these different compute, storage, networking services, application, middleware. Microsoft focused on sort of building managed services of their software portfolio. I think we need a third model where we have sort of an open set of interfaces and an open standards based cloud provider that might be a pure software company, it might be a company that builds on the rails and the infrastructure that Amazon has laid down, spending tens of billions in cap ex, or it could be something based on a project like Kubernetes or built from the community ecosystem. So I think we need something like that just to sort of provide, speed the innovation, and disaggregate the services away from a monolithic kind of closed vendor like Amazon or Azure. >> I want to come back to that whole startup opportunity, but I want to get Sarbjeet in here, because we've been in the B2B area with just last week at IBM Think 2019. Obviously they're trying to get back into the cloud game, but this digital transformation that has been the cliche for almost a couple of years now, if not five or plus. Business has got to move to the cloud, so there's a whole new ball game of complete cultural shift. They need stability. So I want to talk more about this open cloud, which I love that conversation, but give me the blocking and tackling capabilities first, 'cause I got to get out of that old cap ex model, move to an operating model, transform my business, whether it's multi clouds. So Sarbjeet, what's your take on the cloud market for say, the enterprise? >> Yeah, I think for the enterprise... you're just sitting in that data center and moving those to cloud, it's a cumbersome task. For that to work, they actually don't need all the bells and whistles which Amazon has in the periphery, if you will. They need just core things like compute, network, and storage, and some other sort of services, maybe database, maybe data share and stuff like that, but they just want to move those applications as is to start with, with some replatforming and with some changes. Like, they won't make changes to first when they start moving those applications, but our minds are polluted by this thinking. When we see a Facebook being formed by a couple of people, or a company of six people sold for a billion dollars, it just messes up with our mind on the enterprise side, hey we can do that too, we can move that fast and so forth, but it's sort of tragic that we think that way. Well, having said that, and I think we have talked about this in the past. If you are doing anything in the way of systems innovation, if your building those at, even at the enterprise, I think cloud is the way to go. To your original question, if there's room for newer cloud players, I think there is, provided that we can detach the platforms from the environments they are sitting on. So the proprietariness has to kinda, it has to be lowered, the degree of proprietariness has to be lower. It can be through open source I think mainly, it can be from open technologies, they don't have to be open source, but portable. >> JJ was mentioning that, I think that's a big point. Jim Long, you're an entrepreneur, you've been a VC, you know all the VCs, been around for a while, you're also, you're an entrepreneur, you're a serial entrepreneur, starting out at Cal Berkeley back in the day. You know, small ideas can move fast, and you're building on Amazon, and you've got a media kind of thing going on, there's a cloud opportunity for you, 'cause you are cloud native, 'cause you're built in the cloud. How do you see it playing out? 'Cause you're scaling with Amazon. >> Well, so we obviously, as a new startup, don't have the issues the enterprise folks have, and I could really see the enterprise customers, what we used to call the Fortune 500, for example, getting together and insisting on at least a base set of APIs that Amazon and Microsoft et cetera adopt, and for a startup, it's really about moving fast with your own solution that solves a problem. So you don't necessarily care too much that you're tied into Amazon completely because you know that if you need to, you can make a change some day. But they do such a good job for us, and their costs, while they can certainly be lower, and we certainly would like more volume discounts, they're pretty darn amazing across the network, across the internet, we do try to price out other folks just for the heck of it, been doing that recently with CDNs, for example. But for us, we're actually creating a hybrid cloud, if you will, a purpose-built cloud to support local television stations, and we do think that's going to be, along with using Amazon, a unique cloud with our own APIs that we will hopefully have lots of different TV apps use our hybrid cloud for part of their application to service local TV. So it's kind of a interesting play for us, the B2B part of it, we're hoping to be pretty successful as well, and we hope to maybe have multiple cloud vendors in our mix, you know. Not that our users will know who's behind us, maybe Amazon, for something, Limelight for another, or whatever, for example. >> Well you got to be concerned about lock-in as you become in the cloud, that's something that everybody's worried about. JJ, I want to get back to you on the investment thesis, because you have a cutting edge business model around investing in open source software, and there's two schools of thought in the open source community, you know, free contribution's great, and let tha.t be organic, and then there's now commercialization. There's real value being created in open source. You had put together a chart with your team about the billions of dollars in exits from open source companies. So what are you investing in, what do you see as opportunities for entrepreneurs like Jim and others that are out there looking at scaling their business? How do you look at success, what's your advice, what do you see as leading indicators? >> I think I'll broadly answer your question with a model that we've been thinking a lot about. We're going to start writing publicly about it and probably eventually maybe publish a book or two on it, and it's around the sort of fundamental perspective of creating value and capturing value. So if you model a famous investor and entrepreneur in Silicon Valley who has commonly modeled these things using two different letter variables, X and Y, but I'll give you the sort of perspective of modeling value creation and value capture around open source, as compared to closed source or proprietary software. So if you look at value creation modeled as X, and value capture modeled as Y, where X and Y are two independent variables with a fully proprietary software company based approach, whether you're building a cloud service or a proprietary software product or whatever, just a software company, your value creation exponent is typically bounded by two things. Capital and fundraising into the entity creating the software, and the centralization of research and development, meaning engineering output for producing the software. And so those two things are tightly coupled to and bounded to the company. With commercial open source software, the exact opposite is true. So value creation is decoupled and independent from funding, and value creation is also decentralized in terms of the research and development aspect. So you have a sort of decentralized, community-based, crowd-sourced, or sort of internet, global phenomena of contributing to a code base that isn't necessarily owned or fully controlled by a single entity, and those two properties are sort of decoupled from funding and decentralized R and D, are fundamentally changing the value creation kind of exponent. Now let's look at the value capture variable. With proprietary software company, or proprietary technology company, you're primarily looking at two constituents capturing value, people who pay for accessing the service or the software, and people who create the software. And so those two constituents capture all the value, they capture, you know, the vendor selling the software captures maybe 10 or 20% of the value, and the rest of the value, I would would express it say as the customer is capturing the rest of the value. Most economists don't express value capture as capturable by an end user or a customer. I think that's a mistake. >> Jim, you're-- >> So now... >> Okay, Jim, your reaction to that, because there's an article went around this weekend from Motherboard. "The internet was built on free labor "of open source developers. "Is that sustainable?" So Jim, what's your reaction to JJ's comments about the interactions and the dynamic between value creation, value capture, free versus sustainable funding? >> Well if you can sort of mix both together, that's what I would like, I haven't really ever figured out how to make open source work in our business model, but I haven't really tried that hard. It's an intriguing concept for sure, particularly if we come up with APIs that are specific to say, local television or something like that, and maybe some special processes that do things that are of interest to the wider community. So it's something I do plan to look at because I do agree that if you, I mean we use open source, we use this thing called FFmpeg, and several other things, and we're really happy that there's people out there adding value to them, et cetera, and we have our own versions, et cetera, so we'd like to contribute to the community if we could figure out how. >> Sarbjeet, your reactions to JJ's thesis there? >> I think two things. I will comment on two different aspects. One is the lack of standards, and then open source becoming the standard, right. I think open source kind of projects take birth and life in its own, because we have lack of standard, 'cause these different vendors can't agree on standards. So remember we used to have service-oriented architecture, we have Microsoft pushing some standards from one side and IBM pushing from other, SOAP versus xCBL and XML, different sort of paradigms, right, but then REST API became the de facto standard, right, it just took over, I think what REST has done for software in last about 10 years or so, nothing has done that for us. >> well Kubernetes is right now looking pretty good. So if you look at JJ, Kubernetes, the movement you were really were pioneering on, it's having similar dynamic, I mean Kubernetes is becoming a forcing function for solidarity in the community of cloud native, as well as an actual interoperable orchestration layer for multiple clouds and other services. So JJ, your thoughts on how open source continues as some of these new technologies, like Kubernetes, continue to hit the scene. Is there any trajectory change in open source that you see, that you could share, I'd love to get your insights on what's next behind, you know, the rise of Kubernetes is happening, what's next? >> I think more abstractly from Kubernetes, we believe that if you just look at the rate of innovation as a primary factor for progress and forward change in the world, open source software has the highest rate of innovation of any technology creation phenomena, and as a consequence, we're seeing more standards emerge from the open source ecosystem, we're seeing more disruption happen from the open source ecosystem, we're seeing more new technology companies and new paradigms and shifts happen from the open source ecosystem, and kind of all progress across the largest, most difficult sort of compound, sensitive problems, influenced and kind of sourced from the open source ecosystem and the open source world overall. Whether it's chip design, machine learning or computing innovations or new types of architectures, or new types of developer paradigms, you know, biological breakthroughs, there's kind of things up and down the technology spectrum that have a lot to sort of thank open source for. We think that the future of technology and the future of software is really that open source is at the core, as opposed to the periphery or the edges, and so today, every software technology company, and cloud providers included, have closed proprietary cores, meaning that where the core is, the data path, the runtime, the core business logic of the company, today that core is proprietary software or closed source software, and yet what is also true, is at the edges, the wrappers, the sort of crust, the periphery of every technology company, we have lots of open source, we have client libraries and bindings and languages and integrations, configuration, UIs and so on, but the cores are proprietary. We think the following will happen over the next few decades. We think the future will gradually shift from closed proprietary cores to open cores, where instead of a proprietary core, an open core is where you have core open source software project, as the fundamental building block for the company. So for example, Hadoop caused the creation of MapR and Cloudera and Hortonworks, Spark caused the creation of Databricks, Kafka caused the creation of Confluent, Git caused the creation of GitHub and GitLab, and this type of commercial open source software model, where there's a core open source project as the kernel building block for the company, and then an extension of intellectual property or wrappers around that open source project, where you can derive value capture and charge for licensed product with the company, and impress customer, we think that model is where the future is headed, and this includes cloud providers, basically selling proprietary services that could be based on a mixture of open source projects, but perhaps not fundamentally on a core open source project. Now we think generally, like abstractly, with maybe somewhat of a reductionist explanation there, but that open core future is very likely, fundamentally because of the rate of innovation being the highest with the open source model in general. >> All right, that's great stuff. Jim, you're a historian of tech, you've lived it. Your thoughts on some of the emerging trends around cloud, because you're disrupting linear TV with Didja, in a new way using cloud technology. How do you see cloud evolving? >> Well, I think the long lines we discussed, certainly I think that's a really interesting model, and having the open source be the center of the universe, then figure out how to have maybe some proprietary stuff, if I can use that word, around it, that other people can take advantage of, but maybe you get the value capture and build a business on that, that makes a lot of sense, and could certainly fit in the TV industry if you will from where I sit... Bring services to businesses and consumers, so it's not like there's some reason it wouldn't work, you know, it's bound to, it's bound to figure out a way, and if you can get a whole mass of people around the world working on the core technology and if it is sort of unique to what mission of, or at least the marketplace you're going after, that could be pretty interesting, and that would be great to see a lot of different new mini-clouds, if you will, develop around that stuff would be pretty cool. >> Sarbjeet, I want you to talk about scale, because you also have experience working with Rackspace. Rackspace was early on, they were trying to build the cloud, and OpenStack came out of that, and guess what, the world was moving so fast, Amazon was a bullet train just flying down the tracks, and it just felt like Rackspace and their cloud, you know OpenStack, just couldn't keep up. So is scale an issue, and how do people compete against scale in your mind? >> I think scale is an issue, and software chops is an issue, so there's some patterns, right? So one pattern is that we tend to see that open source is now not very good at the application side. You will hardly see any applications being built as open source. And also on the extreme side, open source is pretty sort of lame if you will, at very core of the things, like OpenStack failed for that reason, right? But it's pretty good in the middle as Joseph said, right? So building pipes, building some platforms based on open source, so the hooks, integration, is pretty good there, actually. I think that pattern will continue. Hopefully it will go deeper into the core, which we want to see. The other pattern is I think the software chops, like one vendor has to lead the project for certain amount of time. If that project goes into sort of open, like anybody can grab it, lot of people contribute and sort of jump in very quickly, it tends to fail. That's what happened to, I think, OpenStack, and there were many other reasons behind that, but I think that was the main reason, and because we were smaller, and we didn't have that much software chops, I hate to say that, but then IBM could control like hundred parties a week, at the project >> They did, and look where they are. >> And so does HP, right? >> And look where they are. All right, so I'd love to have a Power Panel on open source, certainly JJ's been in the thick of it as well as other folks in the community. I want to just kind of end on lightweight question for you guys. What have you guys learned? Go down the line, start with Jim, Sarbjeet, and then JJ we'll finish with you. Share something that you've learned over the past three months that moved you or that people should know about in tech or cloud trends that's notable. What's something new that you've learned? >> In my case, it was really just spending some time in the last few months getting to know our end users a little bit better, consumers, and some of the impact that having free internet television has on their lives, and that's really motivating... (distorted speech) Something as simple as you might take for granted, but lower income people don't necessarily have a TV that works or a hotel room that has a TV that works, or heaven forbid they're homeless and all that, so it's really gratifying to me to see people sort of tuning back into their local media through television, just by offering it on their phone and laptops. >> And what are you going to do as a result of that? Take a different action, what's the next step for you, what's the action item? >> Well we're hoping, once our product gets filled out with the major networks, et cetera, that we actually provide a community attachment to it, so that we have over-the-air television channels is the main part of the app, and then a side part of the app could be any IP stream, from city council meetings to high schools, to colleges, to local community groups, local, even religious situations or festivals or whatever, and really try to tie that in. We'd really like to use local television as a way to strengthening all local media and local communities, that's the vision at least. >> It's a great mission you guys have at Didja, thanks for sharing that. Sarbjeet, what have learned over the past quarter, three months that was notable for you and the impact and something that changed you a little bit? >> What actually I have gravitated towards in last three to six months is the blockchain, actually. I was light on that, like what it can do for us, and is there really a thing behind it, and can we leverage it. I've seen more and more actually usage of that, and sort of full SCM, supply chain management and healthcare and some other sort of use cases if you will. I'm intrigued by it, and there's a lot of activity there. I think there's some legs behind it, so I'm excited about that. >> And are doing a blockchain project as a result, or are you still tire-kicking? >> No actually, I will play with it, I'm a practitioner, I play with it, I write code and play with it and see (Jim laughs) what does that level of effort it takes to do that, and as you know, I wrote the Alexa scale couple of weeks back, and play with AI and stuff like that. So I try to do that myself before I-- >> We're hoping blockchain helps even out the TV ad economy and gets rid of middle men and makes more trusting transactions between local businesses and stuff. At least I say that, I don't really know what I'm talking about. >> It sounds good though. You get yourself a new round of funding on that sound byte alone. JJ, what have you learned in the past couple months that's new to you and changed you or made you do something different? >> I've learned over the last few months, OSS Capital is a few months and change old, and so just kind of getting started on that, and it's really, I think potentially more than one decade, probably multi-decade kind of mostly consensus building effort. There's such a huge lack of consensus and agreement in the industry. It's a fascinatingly polarizing area, the sort of general topic of open source technology, economics, value creation, value capture. So my learnings over the past few months have just intensified in terms of the lack of consensus I've seen in the industry. So I'm trying to write a little bit more about observations there and sort of put thoughts out, and that's kind of been the biggest takeaway over the last few months for me. >> I'm sure you learned about all the lawyer conversations, setting up a fund, learnings there probably too right, (Jim laughs) I mean all the detail. All right, JJ, thanks so much, Sarbjeet, Jim, thanks for joining me on this Power Panel, cloud conversation impact, to entrepreneurship, open source. Jim Long, Sarbjeet Johal and Joseph Jacks, JJ, thanks for joining us, theCUBE Conversation here in Palo Alto, I'm John Furrier, thanks for watching. >> Thanks John. (lively classical music)

>> Narrator: Live from Nashville, Tennessee. It's the Cube. Covering Commvault GO 2018. Brought to you by Comvault. >> Welcome back to the Music City. This is the Cube at Commvault GO. I'm Stu Miniman with my Co-host Keith Townsend. Happy to welcome to the program one of the users of the show, actually, going to get to see her on stage at the keynote tomorrow. Ah, Michele Buschman who's the Vice President of Information Services at American Pacific Mortgage. Thanks so much for jointing us. >> Thanks for having me. >> Alright, ah, give us a little bit about your company and your roles of responsibility there. >> Sure, so, um, as you mentioned, I'm the Vice President of Information Services at American Pacific Mortgage. Um, I pretty much am responsible, you know, in the acting role or CIO, CTO, and CISO. So, I manage all technology for the company reporting to the COO. Um, our company is a top 15 independent mortgage bank. Um, we do about 10 billion dollars in mortgages a year, and have about a 25 hundred employee user base. >> Alright, so you've just got a couple of roles there, and luckily your in an industry, not much regulation to worry about, things aren't changing, things are kind of static. You just kind of put in a couple hours at the office and go, go take a nap, right? >> Ya, right (laughing). >> Um, why don't you tell us, what are some of those dynamics that are driving your up level business that are impacting, uh, the technology side. >> Oh, absolutely, so, um, you know, the mortgage industry is somewhat cyclical, and we are in that range where interest rates are going up, um, margin pressures are high. So, you know it's all about doing more with less and saving money. Um, in traditionally in the mortgage banking world, um, you know, IT resources, you're always a little bit short? Um, and so, that, you know, drives me to look for strategies that allow me to leverage my technical resources more for business value operations, than managing infrastructure, keeping lights on, um, which has really motivated us to move to the Cloud, and adopt platform type solutions similar to Commvault to be able to be more efficient with our few resources that we do have in our technology team. >> Alright, can you speak a little bit about Cloud. What is that driver, what does Cloud mean to your organization? And ah, yeah, what is the strategy as it sits today? >> Absolutely, so, um, we're kind of unique, I guess, to an extent in that, you know, when I walked into the organization four and a half years ago. The bulk of our critical business applications were already Sass hosted applications. Um, that grew out of the need because they had such a small technical team, um, you know, for the investments to manage the infrastructure to host applications is very high. So, um, luckily enough, I already had a head start, ah, in that the bulk of our critical business applications were CSS Sass hosted, so, um, what I've done since then is to look for those solutions that are more commodities. So, you know, why manage email on Prem when, you know, Microsoft can do a way better job than we could with the small staff we have. So, you know, it's slowly been, you know, taking each application, pulling it out, putting it into the Cloud, so that my team can be better leveraged to actually work on security initiatives, and um, business value, and transformation type of solutions. So, it is part of it is a, you know accessibility as well. Um, you know, we're in a changing environment where we want to be able to deliver our, um, employee workforce to be able to work anywhere, anytime, on any device, and in order to do that, we have to have solutions that are sitting out there, and accessible to them, um, and not always just sitting behind the firewall in the data center. >> So, let's talk a little bit about data management, data protection as it pertains to the business. What are some of the drivers, especially if you are in the Sass world that make you look at data protection suites as opposed to consuming native solutions within those services? >> Oh, absolutely. So, I very much have a strategy around platform services. Uh, when I walked into the organization, there's probably 30 different applications that were out in the environment, and none of them talked to each other. Um, when you're trying to manage, you know, bringing data across the organization to compile it and aggregate it to actually have something useful to the business. You have to have connected systems, but when you have a small team, it's very difficult to do that development working, connect all those systems, and manage them. So, what I like to look for is a platform solution, um, that will allow me to grow, um, as my budget allows, to add on the different modules that that platform solution, um, offers to me. So, you know, for example, you know, today's budget, I might have a certain limited amount that I can invest, but if I pick a solution that ultimately might give me 70, maybe 80 percent of the needs, um, then I'm only having to add in maybe a couple of other solutions and that cost to integrate and manage, and so overall it reduces the overall cost and complexity of the environment. >> So, you're in a mismatch of ten billion dollars a year in mortgages issued, yet, small IT staff, Sass solutions. When you think of Commvault 20 years, enterprise less solution, you don't think necessarily simple, easy to use, initially, so, why Commvault? >> Oh, absolutely, so, um, again within the first year I was there we went through a huge market share grab and so we grew 75 percent market share, and when I walked in the door, we needed to do investment in infrastructure. So, um, the original forecasts were totally blown out of the water, so the investment we made in small to midsize business type of solutions, we out grew before our contracts were due. So, when I went into this, um, we took about an 18 months, um, to take out time to find the right solution. Uh, we looked at about 6 different vendors, um, you know, we did a little bit of POC work, uh, we did references, um, and ah, basically at the end of the day I was looking for something that had a really good vision, um, that was platform driven, so I could continue to add additional products as budget allowed. Um, that had the ability to have more of a single pane of glass and very little man power to manage, um, and then, reliability was huge. Um, you know, we had some challenges with our previous solution of feeling comfortable that our backups would work in the event we had an incident. So, you know, when we looked at Commvault, um, you know, it may have been, um, you know, it's an enterprise solution which is what I wanted. I could scale without rip and replace. Um, great reputation, great vision, good, technology, you know, bones. Um, and so, you know, when I would go to the board for that, I said, you know, the investment may be a little bit more than a lower end solution, but it's going to give us the capability to grow with the business. >> You know Michele, it's interesting, if you dialed back and said you were looking at this five years ago, I wonder if the pricing strategy that Commvault had in place would fit what you're looking for. I'm sure you've seen as a customer, um, when I hear, you know, I kind of want to be able to reach that vision, but do it incrementally. Sounds like something you might get more from a startup? Maybe give us a little bit of insight what you've seen, how you look at this relationship, and what are some of those things that you are looking to add on in the future. >> Oh, absolutely, so, you know, absolutely, financials always come into place, right? You've got to be able to afford what you're putting into place. Um, you know, I will say that, um, their pricing model did change, you know, cause we had looked at that previously, and it was a pretty high price point to get in with the licensing under the perpetual licensing models. Um, so, with the change of how Commvault kind of moved with the times, more subscription style, made it a little more affordable for some of the smaller businesses to take advantage of. Um, and so, you know, that's how I kind of looked at it for, plus at the end of the day, if you're looking for a quality product around security, and recovery, and backup, it's worth the money to invest in something you feel comfortable that's going to meet that need. Um, and grow with you without, again, having you know, who wants to go through a migration every three years when your contracts up, right? Um, and then, as far as the other products, I'm looking, you know, at some of the new products that they've officially announced. It was really exciting to hear the CEO and COO talk today about the automation that they are building cause that plays absolutely into what we're trying to do in our organization. As we need stuff, you know, again, acception processing is what I always talk about. I only want to have to touch things when it's not working, and, you know, when there's some sort of exception. Um, and, so, I'm really excited about the way Commvault's headed down that path with the automation. Um, and then, also the data piece. Being able to really categorized the data, know if it's outdated or not. I mean, this is a very well known industry issue that we have, we are data hogs in the mortgage business. Um, and our users are as well. Uh, and so being able to identify the data that I have, I mean, you know, I walked into a situation where there's been no purge of data. You know, being able to really identify what is valuable date to not purge vs. the data we want to purge to reduce that footprint to reduce the risk for any kind of potential breech, or security incident. You know, the more you have out there, the more the chance you are going to get hit. >> So, you wear a bunch of hats that seem kind of in conflict especially, seeing that you report up to the COO. Security being the most interesting one. >> (Michele) Uh huh. >> How does your role as the CISO and your selection of the data protection suite, data management, impact your decision to go with a Commvault. >> Oh absolutely, that's huge as well, right? Um, you know, in our industry, we obviously are responsible for um, being custodians to a lot of personal information to consumers, so we have NPI, PI all over, and it's not even just with my critical business system vendor, you know, caus I rely on them heavily, they're much larger, they have, um, larger security teams, and larger budgets to typically protect our data. But, we also have that data internally into our own data warehouse. So, um, data protection is key. Um, so looking at products that will allow us to simplify that, have visibility into it, you know, that's another area I'm really looking forward to expanding my Commvalt use into as we start to actually, Um, you know, one of the other projects we're going to be working on potentially is moving our data warehouse to Microsoft Azure. So, um, you know, really having that, um, security plan figure out before the data is up in the cloud. >> Michele, I wonder what your experience has been with recovery. Is that something you test? Have you had to actually do a recovery? What is your experience been? >> Yeah, so, you know, knock on wood, I'm not sure if there's wood under here, but, you know, knock on wood. We haven't had a major incident, um, however, what we do, have done, now that we've actually deployed Commvault fully, um, is in, you know, it's too bad it's not a couple weeks from now because we're actually going to do a full DR exercise with our new backups now that are fully deployed with Commvault. >> So, you'll take a vacation the week after (laughing). >> So, we're going to actually test that out. That's one of the things that I task my team with is once my backups and everything was in place that we're going to, you know, do a tabletop exercise, but actually try to do a full recovery of some systems with the new backups to make sure we are all in good shape. Uh, but with that being said, I can already tell you just from a, um, you know, our old system to our new system, you know, with the features sets that we have available in Commvault compared to what we had in our other solution. The time to recover individual files is exponential. You know, our other solution, we had to recover an entire folder, not just individual files. And then, we're really excited also of being able to eventually being able to push out some self service file restoration capabilities that Commvalt allows us to do as well. >> So, as a natural consumer of, as a service, offering a mission critical businesses. How important is Commvalut role map to, as a service, for enterprise class solutions. >> Oh, I think that's great. I actually can't wait to see what they have to offer around that. Again, you know, um, I might be a unique use case, I don't know, because that's really how we manage our business from the IT side because of limited budget, limited resources is leveraging vendors. Um, so, I'm really excited to see how that evolves actually. Um, you know, from a service perspective. >> Okay, Michele, it's your second time coming to this event. For audiences that didn't come, what did you get out of it, what excites you the most coming to an event like this? >> I think there's two key things that I really enjoy going to conferences about. Um, one of course, is always the networking opportunities. I always, meet other people who have the same challenges that I do, and you know, they're looking at the same products, and being able to exchange ideas, um, and how you solve problems, and, you know talking to other people about real life issues, um, is so valuable. Uh, the other piece is always getting myself out of the office and getting more education. So, you know, really seeing what's evolving, what's changing, um, you know, what are the partners doing that work with Commvault, what's Commvault, you know, doing? Really, getting out of the office to have a chance to really get educated around that and what's really unique to about Commvalt GO to, is that a lot of it is customer based. Uh, you have customers up talking about their use cases and how they've implemented the product, so it's real life, ah, education, and not just, you know, um, a vendor up there talking about their product and selling it, right? >> Absolutely, we appreciate you sharing your story, Ah, with our audience here, and uh, congratulations on all the progress, ah, American Pacific Mortgage. And ah, boy, you know, tired of thinking of all the hats you've been wearing for those of us that wear a few hats, ah, we can definitely, ah, you know, appreciate that, alright. For Keith Townsend, I'm Stu Miniman, we'll be back with more programming here at Commvault GO. Thanks for watching The Cube. >> Michele: Thank you.

>> Announcer: Live, from San Francisco, it's theCUBE. Covering Red Hat Summit 2018. Brought to you by Red Hat. >> Hello everyone, welcome back, this is day three of theCUBE's exclusive coverage of Red Hat Summit 2018, live in San Francisco, California, at Moscone West. We're out in the open, in the middle of the floor here, I'm John Furrier, your co-host, with my co-host to speak, John Troyer, co-founder of TechReckoning, advisory and community development firm, our next guest is CUBE alumni Kim Stevenson, Senior Vice President, General Manager of the Data Center Group Solution segment at Lenovo, great to see you. >> Hey, how are you? >> Thanks for coming on, so Red Hat Summit, Lenovo, okay, how does that fit together for you guys, Data Center obviously is cloud now, and you got on-premise-- >> We're both in Raleigh (Kim laughs) >> You moved to Raleigh, news, what's the update? Where's that connection with an hybrid cloud is taking this world by storm? >> Yeah, so, we're a great partner with Red Hat, and we're very focused on enabling that hybrid enterprise through hybrid cloud. So one of the things that we've done, we do a lot of co-development, but one of the things is we've taken our systems management software, which is Xclarity, and we're the first to embed that into cloud forms, so that we can move assets, public assets to private assets, and vice versa, and that wouldn't be possible without working really closely with Red Hat, so-- >> Well Red Hat's been very strong at support, and you go to the RHL side, on the operating system side, very reliable, it's got years and years of experience, but it's always been kind of let's certify the hardware, and now that you have a hardware at the baseline moving up the stack, you have OpenShift, getting huge success, Kubernetes, now you've got multiple clouds, which has other hardware, security becomes a concern, we hear that, okay, security being on top of that's a really big deal. How does that change the game for you guys, how are you guys adjusting to that, because it requires everyone to do more work, but now you got automation playing a role, take us through that relationship between from the hardware all the way up to the stack. >> Yeah, and it is the weakest link issue, right, that every piece of the solution has to be secure in and its own right, and the solution has to be secure, right? So, we do a lot in the hardware environment through our supply chain, we have efficacy of every part and component that goes in, every piece of software loaded through manufacturing, one of the benefits of having your own manufacturing organization, so we know what give is a secure platform when there is ready to go. But then as you start to add the software, this is where things like containers become really important, and the ability to do monitoring of the environment, without having to stop the environment. And, so, we have a lot of investment going in OpenShift, and we've launched recently a DevOps practice, based on OpenShift, to actually accelerate the deployment of more and more containers, to again, figure out the security by design versus security after the fact. The problem with monitoring is it's after the fact. You want to design in, and you need to rethink the application structure in order to be able to do that. >> Talk about Lenovo's strategy and innovation around enterprise and emerging tech, because, consumerization of IT has been topic, we talk about going way back, many, many years, but actually, the role of consumer hardware products is becoming more and more enterprise, as IoT for instance, becomes a critical piece of the network, whether it's new wearables for humans, or a security camera on a network, the edge of the network is now the IoT device, but also the data center can be considered an edge, a big edge, right? So, you have now devices everywhere, that's not so much consumer-ish, it really has to be enterprise, and cloud enabled. What are you guys doing in the innovation area there? What are some of the things that Lenovo's doing to move the needle on really making a seamless IoT edge, secure, and functional? >> Yeah, so, one of the things, if you look back at the last ten years of IT, right, we've spent a lot of time as IT organizations consolidating data centers, and then, basically, getting rid of people in IT, right? The simplicity of an AWS, and Azure Stack, has actually driven down the number of operational people in IT. And now you're hitting this wave where, on-prem private clouds, are becoming more and more important. It could be the analytic workloads, it could be your blockchain workloads, but the workloads that you want to keep on-prem, and you're going, "Holy crap, I need a robust "operational organization to actually "make this come to life." So that was one of my predictions for this year, was operational simplicity rises in importance, and our response to that from a Lenovo solution is to build fully-integrated appliances. So we have fully-integrated private cloud appliances based on Azure Stack, based on Nutanix, based on VMware's vSAN, ready nodes, so that you pick either at the software layer only, or you can pick a fully-integrated appliance where it's integrated in the factory, that's what I call rack-and-roll, comes with white glove support, and you need far less operational people. And if you want to know, I mean, it's mimicking that simplicity that AWS offers, right? So it's really an application team that now can manage this entire operational environment. >> So is that targeted towards folks who are transitioning to cloud operations? One of the things about true private cloud is, they're essentially rebooting their organizations to be cloud operations, essentially. >> That's right, yeah. >> And so they want that plug-and-play, if you will, I use that old term, but, just out of the box, and then it becomes a resource on the network, is that what you-- >> Yeah, well everybody says, they say the hardware doesn't matter, well it matters (laughs), you know, because it what makes everything run. But what they mean by that is they don't want to mess with it, it needs to be a no-fuss, no-muss, it needs to be there like a utility, but not have to have the resource dedication that used to exist, where I needed storage admins, and database admins, and server admins. That level of monitoring and management has to be abstracted to the software layer, and you have to then be able to integrate your resource components to be able to do that, and look at it as a system, not as a component. And that's where we're headed with our strategy. >> Yeah, Kim, that's a great consumption model, right? An increasing part of the market, converged infrastructure, hybrid conversion infrastructure, like you say rack and, what'd you use? >> Rack-and-roll. >> Rack-and-roll, I like that. But the hardware does matter, right? A few years ago, if you'd listen to some people, we were going to be inside public clouds with some sort of undifferentiated pools of x86 servers out there, but it turns out the actual hardware, and the integration pieces, do matter. John mentioned IoT, AI, we've seen some examples of it here at the show, real world examples, and then for that, hardware really starts to matter. Can you talk a little bit about how Lenovo's looking to some of these emerging tech? >> At the beginning of the year, we formed an IoT division specifically to focus on IoT, and it really is bringing the edge to life, that's the mission of that particular organization. And so, we see sort of the remote office, branch office concept that has long since, I mean, it goes back to AS/400 days, right? You had branch office computing. But, reinventing itself in a modern way into these edge servers that can be rugged-ized, for, you know, we have edge servers in windmills, as an example, to manage and monitor a windmill farm, right? To optimize generation with wind shifts, those kinds of things, but it could be a closet, right, and it could-- >> It's not a data center. >> It's not a data center, is in a physical construct of a data center, is in the functionality provided, it is a data center, and so, we have from our PC group one of the things I'm pretty interested about is we have these things called stackables, so they're about five by eight inches of a PC, and then you can magnetically connect a battery to a magnetically projector to it through magnets, and you can get basically a stack of computing power. So, we've looked at that from our PC colleagues, and said, "Huh, that's the future of the edge, "but it needs to be ZEON class, "it needs to be enterprised as manageability,", and so it won't be five inches by eight inches when we're done, but, it will use some of that IP in the stackable nature, that will allow you, then I can put that stackable unit on the back of a television monitor for a smart display, I could put it back on a kiosk, or a vending machine, or, and all of the sudden, now I can get really different customer experience at the edge, and then I can parse data, maybe I don't need that data, to go back to the cloud, maybe I do need some of that, for, you know, machine-learning capabilities, I want to create big data sets back in the cloud, you can create that level of intelligence at the edge, and parse the data, to where you think the appropriate destination for that data is. >> How important is the IoT edge for you guys, and what should customers who are trying to merge cultures of OT, Operational Technology, with IT? 'Cause now you have IP devices. Which, it creates a security potential, but, there's now policy involved, you got to write software apps for it, you got unique use cases, talk about the importance of the IoT edge, for Lenovo, and what customers should be thinking about when they architect. >> So, my starting point is every piece of equipment becomes an IP-enabled device that will generate and collect data, you're going to have to figure out how to use that data, right? I said to our facilities leader, not too long ago, I said, I pointed at the table, at the conference table we were at, "What do you think this is?" And he's like, "Uh, it's table," and I'm like, "Hmm, no, to me, this is a smart table. "It could be IP-connected, and we could figure out, "is it the right value for this particular room," and you could just get into these crazy things, some will make sense, some won't make sense, but basically, I think every company is looking at how do they make their products and services smart by wrapping them with IT-enabled services. So that creates a new edge. We used to think of endpoints as PCs and phones, now there are cars, and you know, any form of transportation vehicle, they're windmills, they're semi-conductor equipment, you name it. And, that is sort of the new, that's where we are trying to attack, from the IoT perspective, what we're trying to help customers understand is, it's that data collection use case analysis that will enable them. One of my favorite examples is Ford has a prototype product, it's not a car, it's a baby crib. Now, why, right? So, through autonomous driving, they collect a bunch of data, everybody knows that when new parents have a cranky baby in the middle of the night, what do you do, you put 'em in the car, you take 'em for a ride, right? So this baby crib mimics the motion of a car, mimics the sound of an engine, and mimics the streetlights. There's no more taking your baby for a ride in the middle of the night, you put 'em in the bed, yeah, we've all done it! And this is why these endpoint devices collecting data to figure out these new products and services, and I just think, whether they ever bring that to market or not is not the point-- >> It's new experiences. >> It's a brilliant idea, and gives you a really good illustration of how creating these smart-enabled endpoints will allow you to generate new business opportunities. >> That's been a real theme here at the show, getting beyond the technology, right? Transformation is kind of a buzz word, but, I loved that they didn't put a huge amount of tech on stage, they really did talk to the people here, attendees, about, "Look, you've got to step up, "you've got to have new ideas, "you've got to affect the business." How are you, as you talk with both of your customers and inside Lenovo, addressing those kind of transformation and business ad sorts of deals? >> Yeah, look, I said today, and I really believe this, there's a new mandate for IT. The table stakes of keeping the business running, of course we have to keep the business running and running well, right? But really, every IT leader should be thinking about how do they redefine the customer experience for their organization, how they drive extreme productivity, through AI and blockchain and stuff, companies today are extraordinarily inefficient. We all live in a company, and we can tell you it's inefficient, right? But, you now have the ability to affordably drive out that inefficiency through this level of extreme productivity, and then everybody needs to be thinking about the future of the company, what are you in the business of, and how do you wrap those with new products and services, whether it's adjacent markets that you're going to create, or it's enhancements of your existing product, so you can reach new customers, new markets, and that's a far more interesting role for IT, but you can't give up the ship either, right? You cannot let operational performance decline while you're operating on the new mandate, which is why new operating models for IT, and the hyper-converged infrastructures, and in-- >> Containers have been a great help there too-- >> Containers, right, we just have to fundamentally re-architect, so that it's easy to actually drive change, flawless change, into the enterprise, and, the volume of change for our future is twice as great as what we've experienced in the past, and if you accept that as a premise, you'll rethink how you've done your architecture, and how you promote code into production, and how you manage that code going forward. >> We always love having you on theCUBE, 'cause you always do predictions, so I want to go back and get some predictions from you. What's your predictions next year, what do you see happening, you know, by the way, you have been right in a lot of your predictions, so, we have the tapes, we can go back and look at the videos. (laughs) Ah, I guess you were right on that one! What's your predictions this year, I mean obviously you've seen a lot going on, we are talking about, here on theCUBE, seeing what's going on with Kubernetes, change to OpenShift, that a new internet infrastructure's being recast, with compatibility modes, with containers, and Kubernetes for orchestration, cloud scale, you can come up with IoTs, a new infrastructure, and upgrade, is coming. So there's a lot of things happening. So what's your prediction, what's going to happen over the next year? >> Yeah, so I actually believe this is the first year that we have human capacity in IT organizations to reinvent the enterprise structure, which comes led with an enterprise architecture discussion. We've been moving more cloud to the cloud SaaS applications, you know, infrastructure as a service, and that is now absorbed enough into that you can stand back and look at it, so I do believe that, I call it data centers go micro, that the era of data center consolidation is over, that we will be more data centers, they just will be micro-data centers, because they will reflect the edge of every company, and those endpoint aggregation that you need to do to figure out what your data analysis is going to be. I also think that the operational simplicity that operating models are going to be redefined, as more and more private clouds get deployed, the structure of an IT organization has typically looked like this, you have four basic functions, you have IT engineering, IT operations, application development, and applications maintenance. That's typically the structure. I think you're going to see a collapsing of that. There actually is no reason for four independent functions, you need to organize by line of business, and the business outcome you're trying to drive, and, workers are going to need to be more versatile, in terms of being able to span, you're going to abstract a lot from the infrastructure, right, so you need to be able to manage at a higher level, therefore you can't organize in that discreet manner, and I think you'll start to see that come life-- >> John: Like horizontally scalable people. >> Sounds like horizontally scalable people, yeah. >> You've been a CIO at Intel, you have a lot of varieties of roles sittin' on some boards, you're now in an executive role at Lenovo, you're managing products, your responsibilities are building, shipping and business performance as well. How has your role changed? You've been there for about what, a year and a 1/2 or so? >> Yep, just about a year. >> Just about a year, what's the energy like, what are you bringing to the teams, what's your vision, what's your to do list within Lenovo to take it to the next level? >> Yeah, so when I started with Lenovo because I considered Lenovo the underdog, in the data center industry, which was going through phenomenal change, right? And so, the underdog has the best opportunity to capture hearts and minds and share when the industry's going through change, and so that's what attracted me. And it's been true. We organized, about this time last year, by customer segment, to serve the unique needs of our customers in terms of hyper-scaling customers, high performance compute and enterprise, both at the software-defined and traditional layer. And, in that one year, we've won six out of the ten top hyper-scalers in the world, from zero to six in a year, we consider that to be great, and we learn so much from their, they're doing a lot of customization, and they're two, three, four years ahead of what the general enterprise will consume, and so we're able to take that then and pull it back into our private cloud deployment strategy, into our enterprise management, software management, and strategy, because we see what they're doing, and use that as a virtual cycle of life, and we've got a lot of momentum in that area. And our employees are just excited about how much progress we've made in a year. And I would say if you pulled ten of 'em, nine out of ten would've said they wouldn't have believed we could make so much progress in one year. And that's a good feeling to have. Now, there's more work to do (laughs). >> Yeah, you have product leadership, you've got some great products, it's now just focus and getting on the right wave, right? I mean, 'cause the industry is changing! >> Kim: The industry is changing-- >> So you can move the needle big time. >> Yeah, and we've chosen from a software perspective, we've chosen a deep partnership model, with Red Hat as one of the partners, and so, if I look forward, and I would say, "Look, "we're going to have to go deeper and partner more broadly "across the ISV sphere to continue to bring "these tightly integrated appliances "in simple cloud deployment models to the market," and that's what you'll see us do next. >> Well it's exciting for you, and congratulation on that, and they're lucky to have you, and we know from when you were at Intel, you've seen the playbook, you know? (laughs) A lot of change going on, so great to see you, congratulations, we sure did love covering Lenovo, a lot of great action, thanks for your support, and thanks for coming on, sharing your insights here on theCUBE again, appreciate it. >> Thanks for having me. >> Kim Stevenson here outside theCUBE for Red Hat Summit 2018, live in San Francisco, I'm John Furrier with John Troyer, we'll be back with more, after this short break. (bright electronic music) (soothing music) >> Oftentimes the communities already know about a facility that's a problematic because, they smell it, they see it, but, again, they don't have the evidence to basically prove that whatever's happening with their health is related to that facility. (bright music) If you have a low-cost instrument that's easy to use, then all of the sudden, science becomes something that everyday people can do. (bright music) (somber electronic music) >> Hi I'm John Furrier, the co-founder of SiliconANGLE Media, and co-host of theCUBE. I've been in the tech business since I was 19, first programming on minicomputers in a large enterprise, and then worked at IBM and Hewlett Packard, a total of nine years in the enterprise, various jobs from programming, training, consulting, and ultimately, as an executive salesperson, and then started my first company in 1997. And moved to Silicon Valley in 1999, I've been here ever since. I've always loved technology, and I loved covering, you know, emerging technology. I was trained as a software developer, and loved business. And I loved the impact of software, and technology, to business. To me, creating technology that starts a company and creates value and jobs is probably one of the most rewarding things I've every been involved in. And, I bring that energy to theCUBE, because theCUBE is where all the ideas are, and where the experts are, where the people are, and I think what's most exciting about theCUBE is that we get to talk to people who are making things happen. Entrepreneurs, CEO of companies, venture capitalists, people who are really on a day-in and day-out basis, building great companies. And the technology business has just not a lot of real time, live TV coverage, and theCUBE is a nonlinear TV operation, we do everything that the TV guys on cable don't do. We do longer interviews, we ask tougher questions, we ask sometimes some light questions, we talk about the person, and what they feel about. It's not prompted, and scripted, it's a conversation, it's authentic. And for shows that have theCUBE coverage, it makes the show buzz, it creates excitement, and more importantly, it creates great content, and great digital assets, that can be shared instantaneously through the world. Over 31 million people have viewed theCUBE, and that is the result of great content, great conversations, and I'm so proud to be part of theCUBE, we're a great team. Hi, I'm John Furrier, thanks for watching theCUBE. (soothing music) >> Man: One of the community's goals.

>> Narrator: Live, from Las Vegas, it's theCUBE. Covering IBM Think, 2018. Brought to you by IBM >> Hello everyone, welcome back to theCUBE, we are here on the floor at IBM Think 2018 in theCUBE studios, live coverage from IBM Think. I'm John Furrier, the host of theCUBE, and we're here with Stefanie Chiras, who is the Vice President of Offering Management IBM Cognitive Systems, that's Power Systems, a variety of other great stuff, real technology performance happening with Power, it's been a good strategic bet for IBM. Stefanie, great to see you again, thanks for coming back on theCUBE. >> Absolutely, I love to be on, John, thank you for inviting me. >> When we we had a brief (mumbles) Bob Picciano, who's heading up Power and that group, one of the things we learned is there's a lot of stuff going on that's really going to be impacting the performance of things. Just take a minute to explain what you guys are offering in this area. Where does it fit into the IBM portfolio? What's the customer use cases? Where does that offering fit in? >> Yeah, absolutely. So I think here at Think it's been a great chance for us to see how we have really transformed. You know, we have been known in the market for AIX and IBMI. We continue to drive value in that space. We just GA'd on, yesterday, our new systems, based Power9 Processor chip for AIX and IBMI in Linux. So that remains a strong strategic push. Enterprise Linux. We transformed in 2014 to embrace Linux wholeheartedly, so we really are going after now the Linux base. SAP HANA has been an incredible workload where over a thousand customers run in SAP HANA. And boy we are going after this cognitive and AI space with our performance and our acceleration capabilities, particularly around GPUs, so things like unique differentiation in our NVLink is driving our capabilities with some great announcements here that we've had in the last couple of days. >> Jamie Thomas was on earlier, and she and I were talking about some of the things around really the software stack and the hardware kind of coming together. Can you just break that out? Because I know Power, we've been covering it, Doug Balog's been on many times. A lot of great growth right out of the gate. Ecosystem formed right around it. What else has happened? And separate out where the hardware innovation is and technology and what's software and how the ecosystem and people are adopting it. Can you just take us through that? >> Yeah, absolutely. And actually I think it's an interesting question because the ecosystem actually has happened on both sides of the fence, with both the hardware side and the software side, so OpenPOWER has grown dramatically on the hardware side. We just released our Power9 processor chip, so here is our new baby. This is the Power9. >> Hold it up. >> So this is our Power9 here, 8 billion transistors, 14 miles of wiring and 17 layers of metal, I mean it's a technology wonder. >> The props are getting so small we can't even show on the camera. (laughing) >> This is the Moore's Law piece that Jenny was talking about in her keynote. >> That's exactly it. But what we have really done strategically is changed what gets delivered from the CPU to more what gets delivered at a system level, and so our IO capabilities. First chip to market, delivering the first systems to market with PCIe Gen 4. So able to connect to other things much faster. We have NVLink 2.0, which provides nearly 10x the bandwidth to transport data between this chip and a GPU. So Jensen was onstage yesterday from NVIDIA. He held up his chip proudly as well. The capabilities that are coming out from being able to transport data between the power CPU and the GPU is unbelievable. >> Talk about the relationship with NVIDIA for a second, 'cause that's also, NVIDIA stocks up a lot of (mumbles) the bitcoin mining graphics card, but this is, again, one use case, NVIDIA's been doing very well, they're doing really well in IOT, self-driving cars, where data performance is critical. How do you guys play in that? What's the relationship with NVIDIA? >> Yeah, so it has been a great partnership with NVIDIA. When we launched in 2013, right at the end of 2013 we launched OpenPOWER, NVIDIA was one of the five founding members with us, Google, Mellanox, and Tyan. So they clearly wanted to change the game at the systems value level. We launched into that with we went and jointly bid with NVIDIA and Mellanox, we jointly bid for the Department of Energy when we co-named it Coral. But that came to culmination at the end of last year when we delivered the Summit and Sierra supercomputers to Oak Ridge and Lawrence Livermore. We did that with innovation from both us and NVIDIA, and that's what's driving things like this capability. And now we bring in software that exploits it. So that NVLink connection between the CPU and the GPU, we deliver software called PowerAI, we've optimized the frameworks to take advantage of that data transport between that CPU and GPU so it makes it consumable. With all of these things it's not just about the technology, it's about is it easy to consume at the software level? So great announcement yesterday with the capabilities to do logistic regression. Unbelievable, taking the ability to do advertising analytics, taking it from 70 minutes to 1 and 1/2. >> I mean we're going to geek out here. But let's go under the hood for a second. This is a really kind of a high end systems product, at the kind of performance levels. Where does that connect to the go to market? Who's the buyer of it? Is it OEMs? Is it integrators? Is it new hardware devices? How do I get involved and who's the target customer? And what kind of developers are you reaching? Can you just take us through that who's buying this product? >> So this is no longer relegated to the elite set. What we did, and I think this is amazing, when we delivered the Summit and Sierra, right? Huge cluster of these nodes. We took that same node, we pulled it into our product line as the AC922, and we delivered a 4 GPU air-cooled version to market. On December 22nd we GA'd, of last year. And we sold to over 40 independent clients by the end of 2017, so that's a short runway. And most of it, honestly, is all driven around AI. The AI adoption, and it's a cross enterprise. Our goal is really to make sure that the enterprises who are looking at AI now with their developer are ready to take it into production. We offer support for the frameworks on the system so they know that when they do development on this infrastructure, they can take it to production later. So it's very much driven toward taking AI to the enterprise, and it's all over. It's insurance, it's financial services sector. It's those kinds of enterprise that are using AI. >> So IO sensitive, right? So IOT not a target or maybe? >> So you know when we talk out to edge it's a little bit different, right? So the IOT today for us is driving a lot of data, that's coming in, and then you know at different levels-- >> There's not a lot of (mumbles) power needed at the edge. >> There is not, there is not. And it kind of scales in. We are seeing, I would say, kind of progression of that compute moving out closer. Whether or not it's on, it doesn't all come home necessarily anymore. >> Compute is being pushed to where the data is. >> Stefanie: Absolutely right. >> That's head room for you guys. Not a priority now because there's not an intense (mumbles) compute can solve that. >> Stefanie: That's right. >> All right, so where does the Cloud fit into it? You guys powering IBMs Cloud? >> So IBM Cloud has been a great announcement this year as well. So you've seen the focus here around AI and Cloud. So we announced that HANA will come on Power into the Cloud, specializing in large memory sets, so 24 terabyte memory sets. For clients that's huge to be able to exploit that-- >> Is IBM Cloud using Power or not? >> That will be in IBM Cloud. So go to IBM Cloud, be able to deploy an SAP certified HANA on Power deployment for large memory installs, which is great. We also announced PowerAI access, on Power9 technology in IBM Cloud. So we definitely are partnering both with IMB Cloud as well as with the analytics pieces. Data Science Experience available on Power. And I think it's very important, what you said earlier, John, about you want to bring the capabilities to where the data is. So things like a lot of clients are doing AI on prem where we can offer a solution. You can augment that with capabilities like Watson, right? Off prem. You can also do dev ops now with AI in the IBM Cloud. So it really becomes both a deployment model, but the client needs to be able to choose how they want to do it. >> And the data can come from multiple sources. There's always going to be latencies. So what about blockchain? I want to get to blockchain. Are you guys doing anything in the blockchain ecosystem? Obviously one complaint we've been hearing, obviously, is some of these cryptocurrency chains like Ethereum, has performance issues, they got projects coming out. A lot of open source in there. Is Power even puttin' their toe in the water with blockchain? >> We have put our toe in the water. Blockchain runs on Power. From an IBM portfolio perspective-- >> IBM blockchain runs on Power or blockchain, or other blockchains? >> Like Hyperledger. Like Hyperledger will run. So open source, blockchain will run on Power, but if you look at the IBM portfolio, the security capabilities in Z14 that that brings and pulling that into IBM Cloud, our focus is really to be able to deliver that level of security. So we lead with system Z in that space, and Z has been incredible with blockchain. >> Z is pretty expensive to purchase, though. >> But now you can purchase it in the Cloud through IBM Cloud, which is great. >> Awesome, this is the benefit of the Cloud. Sounds like soft layer is moving towards more of a Z mainframe, Power, backend? >> I think the IBM Cloud is broadening the capabilities that it has, because the workloads demand different things. Blockchain demands security. Now you can get that in the Cloud through Z. AI demands incredible compute strength with GPU acceleration, Power is great for that. And now a client doesn't have to choose. They can use the Cloud and get the best infrastructure for the workload they want, and IBM Cloud runs it. >> You guys have been busy. >> We've been busy. (laughing) >> Bob Picciano's been bunkered in. You guys have been crankin' out... love to do a deeper dive on this, Stefanie, and so we'd love to follow up with you guys, and we told Bob we would dig into that, too. Question I have for you now is, how do you talk about this group that you're building together? You know, the names are all internal IBM names, Power... Is it like a group? Do you guys call yourself like the modern infrastructure group? Is it like, what is it called, if you had to explain it to outside IBM, AIs easy, I know what AI team does. You're kind of doing AI. You're enabling AI. Are you a modern infrastructure? What is the pillar are you under? >> Yeah, so we sit under IBM systems, and we are definitely systems proud, right? Everything runs on infrastructure somewhere. And then within that three spaces you certainly have Z storage, and we empower, since we've set our sites on AI and cognitive workloads, internally we're called IBM Cognitive Systems. And I think that's really two things, both a focus on the workloads and differentiation we want to bring to clients, but also the fact that it's not just about the hardware, we're now doing software with things like PowerAI software, optimized for our hardware. There's magic that happens when the software and the hardware are co-optimized. >> Well if you look, I mean systems proud, I love that conversation because you look at the systems revolution that I grew up in, the computer science generation of the 80s, that was the open movement, BSD, pre-Linux, and then now everything about the Cloud and what's going on with AI and what I call the innovation sandwich with data in the middle and blockchain and AI as bread. >> Stefanie: Yep. >> You have all the perfect elements of automation, you know, Cloud. That's all going to be powered by a system. >> Absolutely. >> Especially operating systems skills are super imprtant. >> Super important. Super important. >> This is the foundational elements. >> Absolutely, and I think your point on open, that has really come in and changed how quickly this innovation is happening, but completely agree, right? And we'll see more fit for purpose types of things, as you mentioned. More fit for purpose. Where the infrastructure and the OS are driving huge value at a workload level, and that's what the client needs. >> You know, what dev ops proved with the Cloud movement was you can have programmable infrastructure. And what we're seeing with blockchain and decentralized web and AI, is that the real value, intellectual property, is going to be the business logic. That is going to be dealing with now a whole 'nother layer of programmability. It used to be the other way around. The technology determined >> That's right. >> the core decision, so the risk was technology purchase. Now that this risk is business model decision, how do you code your business? >> And it's very challenging for any business because the efficiency happens when those decisions get made jointly together. That's when real business efficiency. If you make one decision on one side of the line or the other side of the line only, you're losing efficiency that can be driven. >> And open is big because you have consensus algorithms, you got regulatory issues, the more data you're exposed to, and more horsepower that you have, this is the future, perfect storm. >> Perfect storm. >> Stefanie, thanks for coming on theCUBE, >> It's exciting. >> Great to see you. >> Oh my pleasure John, great to see you. >> You're awesome. Systems proud here in theCUBE, we're sharing all the systems data here at IBM Think. I'm John Furrier, more live coverage after this short break. All right.

(upbeat instrumental music) >> Narrator: Live from Las Vegas, it's the Cube. Covering AWS re:Invent 2017, presented by AWS, Intel, and our ecosystem of partners. >> Hey, welcome back everyone. This is the Cube, live here in Las Vegas for AWS re:Invent 2017. I'm John Furrier, the cohost of the cube. My cohost, Keith Townsend, here for our fifth year in a row, covering the thunderous growth of Amazon Web Services as they continue to not only nail the developers and the start ups, but continue to win the enterprise. Our next guest, Lew Cirne, who's the founder and CEO of publicly held New Relic, a very successful startup, one of the most admired places to work in the Bay area, and in tech. Lew, great to have you on the Cube, welcome. >> Hi. >> John: Hi, first time. >> I know, so great to be here. I can't believe it's the firs time. I've been such a fan for a long time. >> Now you're an alumni, the benefits. >> Here I am. >> All the benefits of being an alumni, all those season tickets to all of our games. I gotta, I want to just share something with the audience out there. You're the only public CEO that I know that's been on the Cube that writes software, has a GitHub account, and manages a publicly held company. So that's a unique thing and I want to just say it's awesome. >> It's a full plate, that's for sure, but I'm the luckiest guy in the world because I've always loved building software since my first computer I got in the Christmas of 82, what's that, 35 years ago now, and, and so, what an exciting time to be someone who's passionate about software and technology. Look what's going on in the cloud, and so I've been fortunate enough to start this company that's participating in this revolution in technology, so it's great. >> You guys are always in the cutting edge. I noticed, you guys get your hands dirty, you get in there, you're coding away, but you guys are very successful in a very important area right now, which is instrumentation of data. >> Lew: Absolutely. >> In applications, so I really want to get your, kind of your thoughts on the landscape. We were talking about on our intro analysis, that we're seeing a renaissance in software development, where with open source growing exponentially, a new software methodology's coming out, where there's just so much going on. Multiple databases within one app, IOT, so a new kind of thinking is evolving. What's your take on that? >> Well I think it's really important to understand why all of this is happening. So why are there 40,000 people here in Las Vegas for re:Invent? Why are people consuming the cloud at just a dizzying pace? It's not just for the sake of cloud computing, it's because there's this business imperative to compete on software, so if you look at where software was 15, 20 years ago, software was a tool to reduce costs and automate things in the back end. Now your software's your business. If you are a large global bank, your app has more to do with your customers' experience and satisfaction than the branch because nobody walks through a branch anymore, so now the best software developing bank is going to be the winner, so if you think about that's what's going on and that's why they're adopting new technologies to move faster, so where do we fit in? If you're going to compete on your software, and by competing you have to build the best stuff, the fastest as possible, so you have to get to market quickly, and that means you've got to change a lot. Anytime you're changing something rapidly, that introduces risk. New Relic de-risks all of that rapid movement by instrumentation, by measuring everything in the software. Those measurements help you move faster with confidence. >> And also I would say that you, not only does that create risks, but new software creates risks, so I'm doing server-less, I want to try the new service because it could A, add value, AKA Lamda or whatever, so a new, maybe time out is needed, so all kinds of new things or elements are going on inside the software stacks. >> Yes, and more complex than ever before, right, so you introduce things like Lambda server-less function computing, call it what you will, and you integrate it with, you know, microservice architecture, and so instead of one monolith, you might have hundreds, or even some of our customers have thousands of independent services, all supposed to be working in flawless concert in order to deliver a great customer experience. How on earth do you make sense of whether that's all working? Well it involves collecting an enormous amount of data about everything that's going on in real time, and then applying intelligence to that data using what we call at New Relic applied intelligence to tell our customers in real time, here's what's working well, and more importantly, here's what's going to be a problem if you don't take immediate action. And that's, you know, that's a hard problem to solve. We think we're the best at doing it. >> And that's critical too, because like you said, if it crashes, or there's some sort of breach hold that comes out there, all the stuff is at risk. >> And like, customers have just incredibly high expectations that only get higher and higher every day. Like, you know, one of our customers is Domino's and it's an amazing thing where you pre-order your pizza and you can see, second by second, how your order is doing, right? They put your pizza in the oven, then they took the pizza out of the oven, and I see that in phone, and that gives, that's that feedback that's valuable to me, right? So long as it's working, right? >> John: I'm hungry now. >> So we, we've ravished this word digital transformation all the time. >> Oh yeah, it's a little overused, but. >> It is a little overused. But melding that physical world with cold. I love it that you're a developer. First off, what's your favorite language? >> Oh geez, it really depends on the project. I'm really getting into, I love React right now on the front end. I'll still do Java when it needs some heavy lifting, Ruby for rapid prototyping. It really depends on the task at hand. >> So the value of reducing friction from a developer seeing a problem, needing to solve that problem, and getting the resources needed to solve a problem, AWS does a wonderful job of saying, you know what, developer, give me your credit card, we'll give you all the tools you need. Where is the first stumbling block because this is new capability, net new over the past few years? Where's the first set of stumbling blocks when developers reduce friction, get to that first level contact with the branch manager of the pizza store, where does it fall apart and New Relic comes in to help? >> Look, how many times have you ever had a developer or a tech or someone that works on my machine, right? >> Exactly, worked on my laptop. I don't know why it didn't deploy well in production, it worked perfectly fine on my laptop. >> I really, I started thinking about and solving this problem 20 years ago now. The notion of less instrument Java code because I was frustrated with the stuff that worked on my laptop. I couldn't understand why it didn't work when a customer used it, and everything prior to the customer using the software is nothing but sunk cost. There is no value in the software you're building until it runs in production. How well it runs in production is what determines the fate of the application. And that's where New Relic comes in, is we feel like alright, let me take you back to the ancient days of like turn of the century, 2000, nothing went to production without QA. Now nothing goes to production without instrumentation. >> Yeah, but now Agile's there, so the old days was a crab. You built a software product, but you didn't know if it was going to work until it went into production with QA. Now you're shipping stuff fast, so it's still. You've got that dev off mindset, but it's in QA. >> One of our customers, Airbnb, deploys more than a thousand times a day. And this is not a small, low load site. I mean like every deploy has to work, otherwise millions of people are impacted and it's the whole business, and it's a big business, so you're talking about a pace of innovation and change that cannot be managed with a traditional QA cycle. I've, of course testing's important, but instrumentation's more important than that. >> Lew, I want to ask you an important question because I asked Andy Jassie this last Monday when I had a one on one with him. A lot of people that are entering ecosystem for Amazon is new, that are new, or considerably, Amazon's the big, they're fearful, it's always going to be that way. He highlighted your company, New Relic, and said they're an amazing part, they do extremely well, even though they introduced Cloud Watch, which because some customers just wanted it, they have monitoring, but you guys are so much better. I said that, but if he implied it, obviously you're doing well. So the successful participation of the ecosystem is there. You can be successful in the Amazon ecosystem. >> Absolutely, it's a great partnership. >> So what's this formula for a new entry coming in or someone who's here that needs to find some white space? How do you read the tea leaves to know where not to play and where to play? >> You know, it just comes down to the fundamental good thought process you use when you're thinking about approaching your customer too. Don't think about what's in it for me, the Amazon partner. What's in it for Amazon? How do you make them more successful? And so when I imagine myself as Andy, who is like, what an incredible job he's done, but what Andy, what's top mind of Andy is how do I get more customers consuming more of Amazon faster, right? All of Amazon, all of Amazon's web services, and so we solve a problem for Andy and his team. We help our customers consume Amazon faster because we give them the confidence to consume more and move faster, and there's data to prove it. When Amazon asks their customers that aren't yet New Relic customers how much they're consuming and how fast, they get a slower rate of adoption than they do for the cohort that uses New Relic, and so it's in our mutual interest to go to market together because we help them consume more, and so I. >> John: Build a good product. >> Build a good product. >> John: Customer value. >> Think about how you help your partner be successful. Talk in that language, don't talk in language. >> Alright, so personal question. So you and I, pretend we're sitting here, having a beer, you're playing the guitar. >> A little light. >> I'm singing some tunes and Keith's our friend. He says I'm in trouble, I'm a CIO. I've got a transformation project. I don't know what to do. Which cloud do I use? How do I become data driven? Guys, help me out. Lew, what do you say? >> I say first of all, you have an instrumentation strategy. Everything, if you're a CIO in a large organization, you don't have one, two, three, or four projects. You have dozens, if not hundreds, sometimes thousands of applications and services that are all running, and you've got, I haven't met a CIO that doesn't say they've got too many monitoring tools. So you need an instrumentation strategy. Nothing should run in production without instrumentation. That's not just the service light stuff that runs on EC2, it's also every click that runs. You know, when Dunkin Donuts, which has been a longtime customer of ours, and they run in the Amazon Cloud, you know when you pre-order that doughnut, we track the tap, how long it takes from the phone all the way through the cloud services, all that's fully instrumented, so if you're a CIO, you say I can't be tactical with instrumentation. If I'm going to move fast and compete at my software, nothing should run in production without education. >> John: That's native. >> That's right. >> Foundational. >> Foundational. It's a core requirement to run in production if you're going to move at any level of speed, so establish that strategy, and then we think, we offer the best instrumentation, certainly the best value, the most ubiquitous, the easiest to use, the most comprehensive, and then we make the most sense of it, but you could pick another, you know you could pick another strategy. Some people do the heavy lifting of manually instrumenting all their code. We just don't think that's a good use of your developer time, so we automatically do that for you, but have a strategy and then execute to it. >> Awesome. Lew, congratulations on a blowout quarter. I won't even get you to comment on it, just say that you guys had a great quarter, stocks at an all time high, all because you guys are doing a great product. Congratulations and great to have you on the Cube. >> We're delighted to be here. I've honestly, I've been a longtime fan. It means a lot that you could have me on, and we really enjoy partnering with Amazon, and what a great show. >> Yeah, super successful ecosystem partner, one of the best, New Relic, based out of San Francisco, here with the founder and CEO, also musician, writes code, gets down and dirty, runs a publicly held company. He's Superman. Lew, thanks for coming on the Cube. More live data and action here on the Cube after this short break, stay with us. (upbeat instrumental music)

>> Announcer: Live from midtown Manhattan, it's theCUBE, covering BigData New York City 2017, brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Okay, welcome back everyone, we're live in New York City, this is theCUBE's coverage of BigData NYC, this is our own event for five years now we've been running it, been at Hadoop World since 2010, it's our eighth year covering the Hadoop World which has evolved into Strata Conference, Strata Hadoop, now called Strata Data, and of course it's bigger than just Strata, it's about big data in NYC, a lot of big players here inside theCUBE, thought leaders, entrepreneurs, and great guests. I'm John Furrier, the cohost this week with Jim Kobielus, who's the lead analyst on our BigData and our Wikibon team. Our next guest is Yaron Haviv, who's with iguazio, he's the founder and CTO, hot startup here at the show, making a lot of waves on their new platform. Welcome to theCUBE, good to see you again, congratulations. >> Yes, thanks, thanks very much. We're happy to be here again. >> You're known in the theCUBE community as the guy on Twitter who's always pinging me and Dave and team, saying, "Hey, you know, you guys got to "get that right." You really are one of the smartest guys on the network in our community, you're super-smart, your team has got great tech chops, and in the middle of all that is the hottest market which is cloud native, cloud native as it relates to the integration of how apps are being built, and essentially new ways of engineering around these solutions, not just repackaging old stuff, it's really about putting things in a true cloud environment, with an application development, with data at the center of it, you got a whole complex platform you've introduced. So really, really want to dig into this. So before we get into some of my pointed questions I know Jim's got a ton of questions, is give us an update on what's going on so you guys got some news here at the show, let's get to that first. >> So since the last time we spoke, we had tons of news. We're making revenues, we have customers, we've just recently GA'ed, we recently got significant investment from major investors, we raised about $33 million recently from companies like Verizon Ventures, Bosch, you know for IoT, Chicago Mercantile Exchange, which is Dow Jones and other properties, Dell EMC. So pretty broad. >> John: So customers, pretty much. >> Yeah, so that's the interesting thing. Usually you know investors are sort of strategic investors or partners or potential buyers, but here it's essentially our customers that it's so strategic to the business, we want to... >> Let's go with GA of the projects, just get into what's shipping, what's available, what's the general availability, what are you now offering? >> So iguazio is trying to, you know, you alluded to cloud native and all that. Usually when you go to events like Strata and BigData it's nothing to do with cloud native, a lot of hard labor, not really continuous development and integration, it's like continuous hard work, it's continuous hard work. And essentially what we did, we created a data platform which is extremely fast and integrated, you know has all the different forms of states, streaming and events and documents and tables and all that, into a very unique architecture, won't dive into that today. And on top of it we've integrated cloud services like Kubernetes and serverless functionality and others, so we can essentially create a hybrid cloud. So some of our customers they even deploy portions as an Opix-based settings in the cloud, and some portions in the edge or in the enterprise deployed the software, or even a prepackaged appliance. So we're the only ones that provide a full hybrid experience. >> John: Is this a SAS product? >> So it's a software stack, and it could be delivered in three different options. One, if you don't want to mess with the hardware, you can just rent it, and it's deployed in Equanix facility, we have very strong partnerships with them globally. If you want to have something on-prem, you can get a software reference architecture, you go and deploy it. If you're a telco or an IoT player that wants a manufacturing facility, we have a very small 2U box, four servers, four GPUs, all the analytics tech you could think of. You just put it in the factory instead of like two racks of Hadoop. >> So you're not general purpose, you're just whatever the customer wants to deploy the stack, their flexibility is on them. >> Yeah. Now it is an appliance >> You have a hosting solution? >> It is an appliance even when you deploy it on-prem, it's a bunch of Docker containers inside that you don't even touch them, you don't SSH to the machine. You have APIs and you have UIs, and just like the cloud experience when you go to Amazon, you don't open the Kimono, you know, you just use it. So our experience that's what we're telling customers. No root access problems, no security problems. It's a hardened system. Give us servers, we'll deploy it, and you go through consoles and UIs, >> You don't host anything for anyone? >> We host for some customers, including >> So you do whatever the customer was interested in doing? >> Yes. (laughs) >> So you're flexible, okay. >> We just want to make money. >> You're pretty good, sticking to the product. So on the GA, so here essentially the big data world you mentioned that there's data layers, like data piece. So I got to ask you the question, so pretend I'm an idiot for a second, right. >> Yaron: Okay. >> Okay, yeah. >> No, you're a smart guy. >> What problem are you solving. So we'll just go to the simple. I love what you're doing, I assume you guys are super-smart, which I can say you are, but what's the problem you're solving, what's in it for me? >> Okay, so there are two problems. One is the challenge everyone wants to transform. You know there is this digital transformation mantra. And it means essentially two things. One is, I want to automate my operation environment so I can cut costs and be more competitive. The other one is I want to improve my customer engagement. You know, I want to do mobile apps which are smarter, you know get more direct content to the user, get more targeted functionality, et cetera. These are the two key challenges for every business, any industry, okay? So they go and they deploy Hadoop and Hive and all that stuff, and it takes them two years to productize it. And then they get to the data science bit. And by the time they finished they understand that this Hadoop thing can only do one thing. It's queries, and reporting and BI, and data warehousing. How do you do actionable insights from that stuff, okay? 'Cause actionable insights means I get information from the mobile app, and then I translate it into some action. I have to enrich the vectors, the machine learning, all that details. And then I need to respond. Hadoop doesn't know how to do it. So the first generation is people that pulled a lot of stuff into data lake, and started querying it and generating reports. And the boss said >> Low cost data link basically, was what you say. >> Yes, and the boss said, "Okay, what are we going to do with this report? "Is it generating any revenue to the business?" No. The only revenue generation if you take this data >> You're fired, exactly. >> No, not all fired, but now >> John: Look at the budget >> Now they're starting to buy our stuff. So now the point is okay, how can I put all this data, and in the same time generate actions, and also deal with the production aspects of, I want to develop in a beta phase, I want to promote it into production. That's cloud native architectures, okay? Hadoop is not cloud, How do I take a Spark, Zeppelin, you know, a notebook and I turn it into production? There's no way to do that. >> By the way, depending on which cloud you go to, they have a different mechanism and elements for each cloud. >> Yeah, so the cloud providers do address that because they are selling the package, >> Expands all the clouds, yeah. >> Yeah, so cloud providers are starting to have their own offerings which are all proprietary around this is how you would, you know, forget about HDFS, we'll have S3, and we'll have Redshift for you, and we'll have Athena, and again you're starting to consume that into a service. Still doesn't address the continuous analytics challenge that people have. And if you're looking at what we've done with Grab, which is amazing, they started with using Amazon services, S3, Redshift, you know, Kinesis, all that stuff, and it took them about two hours to generate the insights. Now the problem is they want to do driver incentives in real time. So they want to incent the driver to go and make more rides or other things, so they have to analyze the event of the location of the driver, the event of the location of the customers, and just throwing messages back based on analytics. So that's real time analytics, and that's not something that you can do >> They got to build that from scratch right away. I mean they can't do that with the existing. >> No, and Uber invested tons of energy around that and they don't get the same functionality. Another unique feature that we talk about in our PR >> This is for the use case you're talking about, this is the Grab, which is the car >> Grab is the number one ride-sharing in Asia, which is bigger than Uber in Asia, and they're using our platform. By the way, even Uber doesn't really use Hadoop, they use MemSQL for that stuff, so it's not really using open source and all that. But the point is for example, with Uber, when you have a, when they monetize the rides, they do it just based on demand, okay. And with Grab, now what they do, because of the capability that we can intersect tons of data in real time, they can also look at the weather, was there a terror attack or something like that. They don't want to raise the price >> A lot of other data points, could be traffic >> They don't want to raise the price if there was a problem, you know, and all the customers get aggravated. This is actually intersecting data in real time, and no one today can do that in real time beyond what we can do. >> A lot of people have semantic problems with real time, they don't even know what they mean by real time. >> Yaron: Yes. >> The data could be a week old, but they can get it to them in real time. >> But every decision, if you think if you generalize round the problem, okay, and we have slides on that that I explain to customers. Every time I run analytics, I need to look at four types of data. The context, the event, okay, what happened, okay. The second type of data is the previous state. Like I have a car, was it up or down or what's the previous state of that element? The third element is the time aggregation, like, what happened in the last hour, the average temperature, the average, you know, ticker price for the stock, et cetera, okay? And the fourth thing is enriched data, like I have a car ID, but what's the make, what's the model, who's driving it right now. That's secondary data. So every time I run a machine learning task or any decision I have to collect all those four types of data into one vector, it's called feature vector, and take a decision on that. You take Kafka, it's only the event part, okay, you take MemSQL, it's only the state part, you take Hadoop it's only like historical stuff. How do you assemble and stitch a feature vector. >> Well you talked about complex machine learning pipeline, so clearly, you're talking about a hybrid >> It's a prediction. And actions based on just dumb things, like the car broke and I need to send a garage, I don't need machine learning for that. >> So within your environment then, do you enable the machine learning models to execute across the different data platforms, of which this hybrid environment is composed, and then do you aggregate the results of those models, runs into some larger model that drives the real time decision? >> In our solution, everything is a document, so even a picture is a document, a lot of things. So you can essentially throw in a picture, run tensor flow, embed more features into the document, and then query those features on another platform. So that's really what makes this continuous analytics extremely flexible, so that's what we give customers. The first thing is simplicity. They can now build applications, you know we have tier one now, automotive customer, CIO coming, meeting us. So you know when I have a project, one year, I need to have hired dozens of people, it's hugely complex, you know. Tell us what's the use case, and we'll build a prototype. >> John: All right, well I'm going to >> One week, we gave them a prototype, and he was amazed how in one week we created an application that analyzed all the streams from the data from the cars, did enrichment, did machine learning, and provided predictions. >> Well we're going to have to come in and test you on this, because I'm skeptical, but here's why. >> Everyone is. >> We'll get to that, I mean I'm probably not skeptical but I kind of am because the history is pretty clear. If you look at some of the big ideas out there, like OpenStack. I mean that thing just morphed into a beast. Hadoop was a cost of ownership nightmare as you mentioned early on. So people have been conceptually correct on what they were trying to do, but trying to get it done was always hard, and then it took a long time to kind of figure out the operational model. So how are you different, if I'm going to play the skeptic here? You know, I've heard this before. How are you different than say OpenStack or Hadoop Clusters, 'cause that was a nightmare, cost of ownership, I couldn't get the type of value I needed, lost my budget. Why aren't you the same? >> Okay, that's interesting. I don't know if you know but I ran a lot of development for OpenStack when I was in Matinox and Hadoop, so I patched a lot of those >> So do you agree with what I said? That that was a problem? >> They are extremely complex, yes. And I think one of the things that first OpenStack tried to bite on too much, and it's sort of a huge tent, everyone tries to push his agenda. OpenStack is still an infrastructure layer, okay. And also Hadoop is sort of a something in between an infrastructure and an application layer, but it was designed 10 years ago, where the problem that Hadoop tried to solve is how do you do web ranking, okay, on tons of batch data. And then the ecosystem evolved into real time, and streaming and machine learning. >> A data warehousing alternative or whatever. >> So it doesn't fit the original model of batch processing, 'cause if an event comes from the car or an IoT device, and you have to do something with it, you need a table with an index. You can't just go and build a huge Parquet file. >> You know, you're talking about complexity >> John: That's why he's different. >> Go ahead. >> So what we've done with our team, after knowing OpenStack and all those >> John: All the scar tissue. >> And all the scar tissues, and my role was also working with all the cloud service providers, so I know their internal architecture, and I worked on SAP HANA and Exodata and all those things, so we learned from the bad experiences, said let's forget about the lower layers, which is what OpenStack is trying to provide, provide you infrastructure as a service. Let's focus on the application, and build from the application all the way to the flash, and the CPU instruction set, and the adapters and the networking, okay. That's what's different. So what we provide is an application and service experience. We don't provide infrastructure. If you go buy VMware and Nutanix, all those offerings, you get infrastructure. Now you go and build with the dozen of dev ops guys all the stack above. You go to Amazon, you get services. Just they're not the most optimized in terms of the implementation because they also have dozens of independent projects that each one takes a VM and starts writing some >> But they're still a good service, but you got to put it together. >> Yeah right. But also the way they implement, because in order for them to scale is that they have a common layer, they found VMs, and then they're starting to build up applications so it's inefficient. And also a lot of it is built on 10-year-old baseline architecture. We've designed it for a very modern architecture, it's all parallel CPUs with 30 cores, you know, flash and NVMe. And so we've avoided a lot of the hardware challenges, and serialization, and just provide and abstraction layer pretty much like a cloud on top. >> Now in terms of abstraction layers in the cloud, they're efficient, and provide a simplification experience for developers. Serverless computing is up and coming, it's an important approach, of course we have the public clouds from AWS and Google and IBM and Microsoft. There are a growing range of serverless computing frameworks for prem-based deployment. I believe you are behind one. Can you talk about what you're doing at iguazio on serverless frameworks for on-prem or public? >> Yes, it's the first time I'm very active in CNC after Cloud Native Foundation. I'm one of the authors of the serverless white paper, which tries to normalize the definitions of all the vendors and come with a proposal for interoperable standard. So I spent a lot of energy on that, 'cause we don't want to lock customers to an API. What's unique, by the way, about our solution, we don't have a single proprietary API. We just emulate all the other guys' stuff. We have all the Amazon APIs for data services, like Kinesis, Dynamo, S3, et cetera. We have the open source APIs, like Kafka. So also on the serverless, my agenda is trying to promote that if I'm writing to Azure or AWS or iguazio, I don't need to change my app. I can use any developer tools. So that's my effort there. And we recently, a few weeks ago, we launched our open source project, which is a sort of second generation of something we had before called Nuclio. It's designed for real time >> John: How do you spell that? >> N-U-C-L-I-O. I even have the logo >> He's got a nice slick here. >> It's really fast because it's >> John: Nuclio, so that's open source that you guys just sponsor and it's all code out in the open? >> All the code is in the open, pretty cool, has a lot of innovative ideas on how to do stream processing and best, 'cause the original serverless functionality was designed around web hooks and HTTP, and even many of the open source projects are really designed around HTTP serving. >> I have a question. I'm doing research for Wikibon on the area of serverless, in fact we've recently published a report on serverless, and in terms of hybrid cloud environments, I'm not seeing yet any hybrid serverless clouds that involve public, you know, serverless like AWS Lambda, and private on-prem deployment of serverless. Do you have any customers who are doing that or interested in hybridizing serverless across public and private? >> Of course, and we have some patents I don't want to go into, but the general idea is, what we've done in Nuclio is also the decoupling of the data from the computation, which means that things can sort of be disjoined. You can run a function in Raspberry Pi, and the data will be in a different place, and those things can sort of move, okay. >> So the persistence has to happen outside the serverless environment, like in the application itself? >> Outside of the function, the function acts as the persistent layer through APIs, okay. And how this data persistence is materialized, that server separate thing. So you can actually write the same function that will run against Kafka or Kinesis or Private MQ, or HTTP without modifying the function, and ad hoc, through what we call function bindings, you define what's going to be the thing driving the data, or storing the data. So that can actually write the same function that does ETL drop from table one to table two. You don't need to put the table information in the function, which is not the thing that Lambda does. And it's about a hundred times faster than Lambda, we do 400,000 events per second in Nuclio. So if you write your serverless code in Nuclio, it's faster than writing it yourself, because of all those low-level optimizations. >> Yaron, thanks for coming on theCUBE. We want to do a deeper dive, love to have you out in Palo Alto next time you're in town. Let us know when you're in Silicon Valley for sure, we'll make sure we get you on camera for multiple sessions. >> And more information re:Invent. >> Go to re:Invent. We're looking forward to seeing you there. Love the continuous analytics message, I think continuous integration is going through a massive renaissance right now, you're starting to see new approaches, and I think things that you're doing is exactly along the lines of what the world wants, which is alternatives, innovation, and thanks for sharing on theCUBE. >> Great. >> That's very great. >> This is theCUBE coverage of the hot startups here at BigData NYC, live coverage from New York, after this short break. I'm John Furrier, Jim Kobielus, after this short break.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering VMworld 2017. Brought to you by VMware and its ecosystem partner. (bouncy upbeat music) >> Welcome back to SiliconANGLE Media's production of VMworld 2017. This is theCube. I am your host, Stu Miniman. Happy to be joined for this special segment. Calling it the independent wrap analysis multi-hybrid focus with Blue Cow. Blue Cow is here. First-time guests on the program and Blue Cow has brought a few of the friends. Friends of mine, people that I got to know through this phenomenal VMware community also guest host on the program here. Been a pleasure working with all three of you. John Troyer from Tech Reckoning Justin Warren from Pivot 9 and Keith Townsend, the CTO advisor. Gentlemen, thank you so much for coming here. Now, we're independent when we come to this and I don't think any of us are shy as to kind of sharing our opinions. I think all of us have had "I can't believe what you said on Twitter" at least once. In fact, I remember when John Troyer was working for VMware I did get a call every once in awhile. I've said, if I didn't get a call at least once a year from him saying, "Hey Stu, can you moderate that a little," I'm probably not doing my job. Let's get into it. The first thing I'd say is it's 2017. We blinked and like we're getting towards the end of it. Of course, there's the big party. There's still a whole bunch of sessions going for another day. Reactions on the show, high-level things. Keith, let's start down with you. >> First off, the energy of the show this year was, I have to say it was, I have to say it was up a notch. There was a lot of uncertainty around the acquisition and even Pat's future, whether or not he would be here for the VMworld this year, as the head of VMware he announced, I think it was kind of like with a little bit of pride, that he said "This is my 5th year as CEO of Vmware" and he bought the energy Monday and I think that energy has transferred throughout all of the VMware staff and throughout the show for the past few days. >> Just in that question, of course, and how many selfies has Blue Cow done at the show? >> Not as many as usual, unfortunately, because we've been very, very busy with briefings and meetings, so we haven't had as much selfie time as we've had, but we still make time to take a few photos around the show. And, yeah, I agree with Keith. The energy this year, and I think it had started with the example that Pat set at the first keynote. Which, it's just been lifted this year and I've been saying for, I've been hearing it from a lot of different people and I've been having it in conversations as well that this year, VMware stopped apologizing for existing and it's embraced itself, and I'm sure that having the stock price hit a nice high of a 107, I'm sure that helped with Pat and his idea of, "That makes you happy. Makes it a lot easier for you to keep your job." >> That's great, there was a comment actually The first time most of us remember. The week of Vmworld? The stock actually was going up. John, you know, you've got lots of experience with this community; your take. >> Certainly more energy than last year. I mean, let's look at the micro and the macro. There's always tactical stuff going on. Last year, Vster 6.5 had not been released. Dell acquisition and nobody was sure what was going on exactly. This year, the big VMware cloud on AWS announcement, I think, is an acknowledgement of maybe, that we can talk about. That, wait a minute. Once you get down to the nitty-gritty plumbing infrastructure layer, you still need to partner with somebody like VMware. I think the industry and the analysts, and the market, that's one of the things they like and then look at the macro trends on the economy. If you look at the Expo floor this year? Huge, lots of money being spent, lots of vendors here. There's something macro going on as well with the people here. >> Let's talk about two things I look at. Did VMware meet expectations? Was it what you expect? And, what are we going to be looking back at when we come here? John, I'll start with you, you hit on the big topic from my standpoint, looking at VMware and AWS. What will VMware look like in the future? Are they going to be a SAS provider? How does that transition from an infrastructure software company to a different fit for how they do cloud today versus the whole Vcloud era and everything before it? That was era not error even though, you know... >> Hey, they had a lot to do, of messaging and a lot of product-in announcements and a lot of introductions this week. I don't know, let's give them a B for that because there were a lot of them and they had a lot to do in a short space especially, like, through the lens of say the keynotes which is the lens a lot of people have. I think AWS, VMware Cloud on AWS is the big story. I don't know, I predict that in a year or two VMware will probably be the biggest VMware hoster service provider, right? I think a lot of workloads are going to shift into the AWS service through VMware and that will happen to excess capacity. It'll happens through a lot of different things. But, that's my prediction. >> I'm sorry, you say VMware will-- >> VMware will be the largest VMware hoster within a year or two. >> I feel like I'm watching the NFL Network. Bold predictions, here we have it. VMware has got 4500 partners, John. I've have Ajay Patella on a couple of times talking about his tiers of partners and everything like that. But let's let some of the guys weigh in. >> I'll extend on that, I kind of agree. I think that there's a lot of customers who will basically do a lift and shift and use cloud and I think having to choose between which of their children is the most beautiful and which one they love more has been has been really tearing them apart and I think that now they don't have to make that choice. I think they're going to be a lot easier for, particularly CIOs, to just say, "Yep, I'm doing some cloud." The announcement on Tuesday sort of felt a little flat for me because they were talking about Google container services which is running on Pivotal. Pivotal's sort of an unappreciated part of the whole portfolio, I think. There's a lot of companies some really interesting software development work there. But, as we mentioned, the development community? That's not this community. This is much more about infrastructure people. That kind of whole announcement and what they were talking about on Day 2? Just kind of went, it felt a little bit off for me. >> Yeah, I want to echo, I think a couple of statements that you've made. One, that VMware's seemed to embrace... Monday, they seem to embrace being VMware. You know what? We may pick on the concept of VMware VSphere being cloud. That VMware is very proud of calling their SDDC strategy which is an important strategy. It adds a lot of value to, not just legacy IT but current things that people are doing in their data center and they embraced being what they do well on Monday, and then we had cloud pizza on Tuesday which kind of broke that but I think I loved the message for VCF, VMware Cloud Foundation, this concept, this reference architecture, this validated design that I can run in my data center. I know that at a Rax pace, at a CNF such as... take your Switch, take your choice between Switch and CenturyLink, etc. I'm going to get that consistent openstack what should have been openstack filling across cloud providers, but John, I agree with you. AWS is AWS at the end of the day and it's a easy checkbox to say VMware Cloud on AWS? Really easy to do and it's easy to consume. I don't have to go and choose between Cloud providers. >> One of the things of this show is that there never enough hours in the day, even Vegas. I actually have to admit I got to bed at a reasonable hour every night. We still have one more night for me here so we'll see on that. Hallway conversations, parties, some of the really cool stuff on on the show floor we talked about a little. I'll start off with kind of, from a customer standpoint, Some customers I talked to; a number of them seemed to be, "I want to move faster. "I'm interested in trying new things "and price isn't necessarily number one on my list. "It's further down the list." Which reminds me: It's not quite there yet but I go to Amazon Reinvent and this will be the fifth year and we are doing the Cube at that show. That's the thing that really excites me. There's cool new things we're trying. I echo and agree with a lot of what you all said about Day 2. Most of the customers here aren't ready for PKS. Sure Pivotal has lots of customers that are using Vmware, but the average attendee's not there. Kind of a wild card, customer insights, cool parties, things there. John, do you want to start down on your end? >> Sure, my channel check and the most surprising thing that I saw this week were talking to SC's from VMware and saying that their customers were coming to them and asking "Help? I now have Kubernetes in the house. "What do I do with it?" That surprised me. I have been a Kubernetes and Container advocate but a skeptic as far as adoption and at least anecdotally the folks that I talk to, it sounds like actually it's now trickling its way and kind of to the mainstream to where the VMware accounts are going to be able to have to deal with it. Now I will say on the flip side, Stu, if you look out at the show floor there are no developer tools, dev ops tools, cloud tools, maybe some cloud tools. That side of, that AWS side of the house, the people that are there, those companies that are there who are not here. If you were a customer, if you were an IT person looking to, this year, finally, educate yourself on how to do that that wasn't here at this show. >> For me, it's been about migration. This is about we have a whole bunch of stuff running on VMware, it's already there and that was one of the reasons VMware was popular in the first place, was that you could take stuff you already doing and you can virtualize it and then you could increase the capacity utilization that you have and you could get some more efficiencies out of that and then people started to layer additional services on top of that and to do interesting an new things on that. It allowed them to do that because it kind of freed up some time. I think we're going to say that again as things start to move to the cloud people start to do them in different ways. the workloads will migrate. It's not just going to happen tomorrow and some of the things that we're seeing, one of the things that impressed me about the show was a company called Densify who had been around previously. They were called Server and they did a rebrand and repossession and nailed it and it's a very, very simple tool that actually sells about the business. It's not about a technology, they don't actually talk about how the thing works or what's going on underneath it. But it allows you to understand the effect of what's happening if you move from VMware here over to that cloud, this cloud or the other cloud and it shows you the pricing. I looked at that and just went I can walk into a CFO and I can sell them on the idea just showing them this. That kind of experience, I think, we're going to start seeing a lot more of that as people moved to the cloud. >> So Monday gave me a new catch phrase for VMworld. VMware moves at the speed of the CIO and, you know what? With hallway conversations I still talk to, John, I don't remember like one-third of the attendees of VMworld are all first-time attendees, I talked to a lot of first-time attendees and it's amazing because VMware has an enormous sales team and they are very aggressive getting to accounts and talking about the overall message. I had people coming up to me and saying "Man you know what, I just found out about this "vRealize Log Insight and it's amazing!" and I'm thinking, Wow, that doesn't get much much more traditional IT than log management with vRealize and you know VMware has preached that for the past 5 or 6 years at the show I think it just shows the Delta in the community from those looking to do the developer, dev ops and cloud-native integration. Us, as analysts, pushing VMware saying, "Hey, what's your digital transformation story? "It's something other than cloud pizza," to all the way, to the keeping the lights on with SAP and Oracle apps that will not change and haven't changed and probably won't change for the next 10 to 15 years. >> Yeah and actually it brings up an interesting point; I had a conversation with Pumela this morning and we were talking about how it used to be, come to the show and it's the virtualization show. Now, It's a pretty broad ecosystem and in some ways it's, I wouldn't say fragmented but I'm grasping for a better word because you walk through the show floor and Dentrify, interesting. We had one of their co-founders on as to that kind of cloud management, and how all those pieces, these big hairy issues that people are solving. We've got people working at analytics and data. You've got all the cloud pieces, security all over the place, networking, we've always had storage at the show. But I'd been a little jaded coming to VMworld. It's now my 8th year and I've kind of re-energized this year. I know that some people have stopped coming. There's a new influx coming in. Let's fast-forward to VMworld 2018. What are you hoping to see from this ecosystem? Any final things you'd want to say? "Hey, this is what we can do better?" Or, "This thing, Do it absolutely again especially!" We've got one more year in Vegas then I think we'll probably go back to San Francisco. You've all been to many of these. Where do we start? >> I'll take two. One, is I like'd to see more basketball players and rappers. We had a lot of them on. >> Did you hang with KD? >> I did not. I was busy. He called my people and I don't know if you want tee that one up, what that one is. >> You could mention that absolutely. >> Sure. I mean Rubrik was here winner of the Best of Show of VMworld. Also spent a lot of marketing dollars on Kevin Durant who was also an investor and also Henson Nischlak >> Did they make cards? I'm on a trading card. How hilarious is that? >> Keith: Trading cards were cool, I have one. >> Yeah. Absolutely. >> They came to play and and they bought it this year. Marketing dollar spent, I actually have a second predication which is that next year or the year after we'll be talking about, it seemed like VMware and Red Hat are throwing down against each other so I think next year we might be talking about the Dell technologies Red Hat wars in the cloud. >> Open source comes up but hadn't been discussed much except we did some Red Hat interviews here. Red Hat? Absolutely. Hybrid cloud environment, Microsoft, VMware, and Red Hat all players there. John's been thinking about this wrap for a while I know. >> Well I'm going to switch completely differently and into the future what I like to see just to shake it up a little bit. I don't think we should talking about AWS things around containers. I think there will be some of that conversation but what I want to see is that VMware starts hosting a function service. I want to see functions on VMware because I reckon that's where the industry is going to move to in the long time. >> Stu: Serverless, you're saying? >> Yeah, Serverless. >> Like I mentioned on Day two? >> I want to see a functions as a service on VMware on AWS. >> Oh, that will happen. >> There you go product management. That's what you can go build. >> You can tie it into Lambda right now, right? You'll have your... >> yeah but if you're tie it into Lambda that just plays right into AWS's hands. >> Give Chris Wolfe a call and Kit Colbert will make that happen. >> You know what? Full disclosure. I was part of judging for best of VMworld and Rubrik won Best of VMworld. I don't want to see more data protection. I don't want to see more secondary storage. I think one of the driving elements that part of that discussion, pulling back the onion a little bit was about redefining something in the data center that had been forgotten, that API level access Rubrik pushes API level access to the data center. This is something that I've asked from VMware forever which is to basically be the API to my data center. You may not ever, I may never get function as a service. I may never get PaaS, I may never get all these cool things from a developer perspective that I want from VMware but at the very minimum, you're the software defining data center. I want to have APIs into the data center and that data center is not just my physical Data Center but this whole VCF thing that's pushed whether it's in my data center, in Rackspace, or some other VCAMP partner or in AWS. My interface, If infrastructure is going to continue to be VMware's customer then you should enable me from an API perspective to manage my software-defining data center, believe it or not. >> Unfortunately, I love to chat with these gentlemen for hours at a time if I can. We're limited with the queue. We only give you a taste of what's happening at these shows if I've mentioned before, you need to come to these kind of events to talk to these quality people. We also mentioned a few of the sponsors on the show. Sponsorship helps us bring, not only the Cube to the event, but helps me bring high quality, independent analysis from gentlemen like this. Please check out all of our sponsors. Check out all of our content on theCUBE.net. These, all three of them, creating a lot of content. Go to their Twitter handle, @ctoadvisor, @jpwarren, and @jtroyer, I'm @stu. Thank you so much for joining us for our coverage of VMworld 2017. Reach out to all of us. Really, we'll get back to you. 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