>> Live from Las Vegas, it's theCUBE! Covering Adobe Summit, 2019. Brought to you by Adobe. Welcome back everyone to the Cube's coverage, here in Las Vegas for Adobe Summit 2019. I'm John Furrier with Jeff Frick, our next guest is Ronell Hugh, head of product strategy and marketing for Adobe and Adobe Cloud Experience, which was announced available today, welcome to theCUBE, thanks for joining us. >> Hey, thank you John, thanks for having us. >> So the Experience Cloud Platform, is game changer for Adobe. >> Yes. Could you describe what is it? Like, where'd it come from, how'd it all start? >> Yeah I can definitely do that. So, the Experience Platform, Adobe Experience Platform, the genesis of it came from, data is such an important part, I think you've had lots of people on here talking about data and what it can do. And really it's like, when you have data that is dispersed across an enterprise, how do you actually, what do you do with that, right? A lot of customers are out there, and I, terminology I came across the other day was data swamps, you know, data lakes, data warehouse, we're all aware of those ideas. But how do you take that data and actually do something meaningful? The idea came from, we have siloed repositories for our data, sitting across all of our solutions, how do we bring that together and rationalize and standardize that data, so that it's more useful for a customer, so they actually can do something that's truly meaningful with it? And that's really around driving these real time personalized experiences with customers, right? And so I think that's where it started. And as we've evolved that, what you heard today is kind of what you're seeing about how do we then take that to the next level? How do you apply machine learning? How do you provide a data model that standardizes the taxonomy across the ecosystem? How do you then leverage that and how do you have it being open? To now, you give customers, developers an opportunity to start to develop new applications that advances what they're trying to do in their environment. >> What I think, what I found super impressive was, you guys really cracked the code on what I call cloud scale architecture, >> Yeah. >> While not, missing out on the opportunities to innovate at the user level. You have the creativity, the applications, and then the data almost is like this DevOps kind of mindset where it's like the data's being available in a diverse way for the use cases that matter at the right time, so. That's a hard nut to crack. >> Yeah it is a hard nut to crack, I think. But at the core, again, it's like, it's the data that's important. Once you have that centralized, you've created some rules around that, you're governing it so that you can now leverage, depending on what you're trying to use it for, it's really then down to the use cases. To your point, like, what are the specific use cases a customer has, that they're trying to solve? There could be industry ones that we could apply them to, we've identified a few of those that we think are important for customers, some of those around the real-time customer data platform and how Experience Platform from along with Audience Manager helps to solve that use case for a customer. But there's others around, how do you enable customers, from a development standpoint? Applications, they're really trying to figure out, hey, I need an open system, but I can start to develop something rich and new, right? And drive advancements in their organizations. And so there's a lot that we've had, there's kind of four that we've identified from a use case standpoint. But that's not limited to those four. Every customer is going to apply either one or all of those in a unique way within their environment. >> When you say four, you mean clouds, like analytical cloud, ad cloud-- >> No, no, I mean, so the use cases that we've identified. >> Oh okay. >> So we have, real-time customer data platform, we have one around, application, customer experience application development, customer journey intelligence is all around how do you take and leverage AI ML tools, to help enrich data? And then we have one around how you take and deliver across multiple applications. What's the channel execution looks like, now that you have data standardized in one place? What does that mean for your channels that you're now trying to execute across your ecosystem? >> Well you guys did the product development on this and the product marketing and all the stuff that goes in to building a platform, you got to go out an talk to customers, right? So what was the, when you guys talked to customers, what was their initial feedback to you guys? And when you 'em the platform now, where are they, I mean, what's the reaction? Can you share some either anecdotal or, specific? >> Yeah, anecdotally, I mean we started talking about a platform and the idea and a vision of a platform, I think, three or four years ago. Last year we then laid the groundwork around, there's three areas to this, a profile, the data side too and a content side, what you're seeing now is a data piece of this, like, how does data then really drive a lot of the interactions there? And as we've progressed, the reception has been great. Customers are like, we understand this. And it's really around the notion of real-time. Real-time is really built on the knowledge that, hey, you're taking data, you're not just doing batch any more. I know batch is predominantly what customers like to use. But real-time means getting data in, that's current. That therefore you can then action upon. Which really is the relevant data that you need. And I think that started to resonate really well. >> How do they define real-time? 'Cause it could depend based upon the application. If you're a doctor you need real-time now. >> If you're an investor, >> Yeah, you need it now! >> You need it now! If you're a BI application on a query, it could be a little slower. I mean real-time is a relative term, can you just unpack the customer's expectation of real-time? >> Yeah I mean, you look across multiple verticals, right? So, depending which vertical you're in, to your point, it could vary, right? But if you're a brand that's delivering consumer experiences, real-time is like, are you interacting with them with the right data to help inform that interaction with that customer, right? And that is real-time. So it varies by industry of course, right? Hospitality, you think of that, when you walk into a hotel, getting a notification that your room is ready. Me recently coming here on a plane trip, having to check my luggage, notified that the bag was check in, and also now that it's being delivered now for me to pick up. Those are all, that's real-time, right? And it varies, I think, by industry. And I think that's where it starts to get really exciting, is like how do you apply it? What does it mean for real-time for each company that's starting to apply Experience Platform to their infrastructure? >> That's my favorite definition of that, real-time is in time to do something about it. (all laughing) Which depending on what the situation is, could be a short period of time or a longer period of time. But Ronall I'm curious, 'cause we've always had the transactional data and real-time's always been a focus on the transactional data, but on the behavioral data to then pull back in to transactional activity, that's a little bit more recent. Especially with so many sources of data that are coming in and changing all the time. How are people dealing with that data flow challenge and as you said, aggregating it and coalescing it into a single platform that now you can take action on it? >> Yeah, I mean the behavioral data's a core to Adobe it's definitely a part of our bread and butter. And I think it's combining it with all the other data sources that will make it even more richer for our customers, right? You think about a customer, if the real Holy Grail, in a way, of our Experience Platform is that real-time customer profile. There're so many different data points that help to build that. When you isolate it just behavioral, that's great. We know the interactions that a customer is having with the brand, but there's other parts that, transactional, POS, social, that helps to build out the view of that customer. And then, think of then at that point, for a customer, any of our customers are using this today, some that were heard today as part of our keynote. How they're then taking that to the next level of how they then build experiences for their customers. It's because it's a culmination of all of that, right? I think behavioral is a huge part of it. Because it's not static data or stagnant data, it's kind of like that data that we have that's been gathered over the last several years of a customer, and how they're currently interacting with a brand. But then it's, again, bringing it all together. Harnessing that, and then building that real-time customer profile, it really is a powerful piece of the platform. >> You know when I looked at the slide on the keynote, it was clear that this'll have a lot of data chops within Adobe. Because you had the data pipelining piece after data input sources, and then the other side of the chart was the piece around the applications, ISVs, ecosystem, and then you had your real-time profile, which I get is the centerpiece. But before that you had something that was around semantic data pipelining, >> Semantic data pipelining yeah. >> Data pipelining and semantics. >> Yeah. >> What is that piece? Is that really where the transformations are happening? Is that the input into the, you're smiling, wow. >> Yeah this is great, I love talking about this. >> You're nerding out. Okay. >> So, pipeline and semantics is all around, so pipeline is the thought process around, we have connectors that we built, right? That's really where the data comes in. When we see at the beginning of the diagram is the bit that said streaming, it's the connectors that allow that streaming to happen but it also gives customers the option of saying, now you can batch it, right? You can batch it, which is what you've been doing, but streaming is really what we're pushing. 80% of customers still think that batching is the only way to manage their data right? And then really it's more about, hey, if you want to action in real-time, where is that data currently at? So that's what we say that happens with the data in the pipeline part of it. Additionally you have things like Adobe Experience Platform Launch and Auditor, Launch is all around data collection as well. But it's also about deployment of tags. When you deploy a tag you're also connecting information that can feed back into the system as well, and then the last piece of that is we have a feature of Platform that's called Auditor, and really it's about auditing your environment to make sure that it's being implemented correctly, right? Semantics is all about governance and control of the data. Standardizing the data, so we have something we call Experience Data Model, they talked a little bit about that, or ExDM, Experience Data Model is all around, it's an open source initiative to help standardize taxonomy of your data. I grew up in Germany, first language is German, and when I moved to the US if I were to walk into a room and started speaking German, no one would've understood me, right? It would've been stares and everything. But if I had switched my language, luckily I speak English too, so I was able to share and speak English, it's the same with data. You can't have it labeled differently for it to communicate. And that's what really happens in semantics and the data pipeline piece we did. >> And it's important too, I want to unpack it a little bit >> It's great to know. >> because semantics also feeds into contextual awareness. And one of the things we've observed doing these CUBE interviews with a lot of experts is, we've heard diverged data and flow, creates more visibility into potential blind spots. Just in data science parlance. Talk about that streaming piece, I think that's something that I see, the people who get data right, will stream as much as they could to get some flow going, to get data sources coming in, to have more diverse data. Talk about that dynamic of diverse data. >> Diverse data, I mean, a part of that diagram you saw, on the left of that when Anjul was speaking, was around data sources, data inputs, right? And so we talked about behavioral, transactional, third party, POS, and it's the variety of data, and that coming in consistently that helps you create that picture of a customer. So you need a variety of data. I think just having our data gives you, again, like we talked about before, the behavioral components of that, but consistently bringing in multiple pieces of data helps to take that further. Now one thing you talked about was AI, and I want to take you there just a little bit 'cause that piece of then how you can manipulate the data, and enrich with new insights, is key. Again, lots more data, standardized, controlled, now being governed in the right way to meet different regulations and policies that are out there. And then now adding AI models to that, ML models to that, to take your organization further. I think that's where we see the power of that data, and having lots of data. Open and extensible is one of the key things that we've been talking about with the platform. >> And clean data feeds clean machine learning. >> Yeah. >> Dirty data gives dirty machine learning. >> Yeah, dirty insights, right? (both laughing) And we always want it to be clean, right? But that's so important, we sit here and think about it, customers want that. They're desiring to have that so they can innovate within their infrastructure and their organizations to take their businesses further. >> And that's where we see the machine, that's why data's so core for you guys in this piece. Alright, so what is the customer environment like? Are they all tuned in to what you just said? I can see some progress in the big companies and maybe, cloud native folks getting, jazzed up on that but, are the big companies tuning in to this? In your mind, where are they on the progress bar? >> Yeah, so John and Jeff, the big companies that we have talked to, are typically further along, that are cloud native, they're more pushing the boundaries of innovation and when we looked at this by industry, you tend to see more of the typical companies by industry that are kind of leaning into this. You know, hospitality, automotive, you have entertainment, media, you also have retail, you know. There's been a lot of interest from those from healthcare and financial services as well because they see the implications of what it means to them in terms of managing their data and executing that data to drive more engagement with their customers. >> They get an edge too, if they can nail the customer experience with data, they'll have a competitive advantage, I mean, if I had to choose between a hotel that was going to take care of me on my app, versus one that doesn't, I think I'm going to go with the one with the app every time. >> Definitely. >> If the price is, all things being equal. >> A key part to that though, and Shantanu I think, and Anjul, multiple people mentioned today, was that customer journey, right? Depending on where you are, data plays a key role in all aspects of that customer journey. And how do you activate it then in each part of the customer journey? To drive those experiences in real-time. So I think it's a key part to how we see it working. And I think that the AI and ML, it explodes even further, to your point, that cleanliness of the data then just makes that more potent in terms of what it can deliver. >> Well one of the things that you guys have is Adobe products, your customers have other things besides Adobe. So one of the things Anjul said in her keynote was open data open APIs. So how do you bring that other stuff in, when, first party data is getting harder and harder to get with all the stuff we're seeing online these days with privacy and regulations? First party data's great, if you can get it. >> Yeah. >> So how is this all impacting, outside the Adobe realm from a customer standpoint because they want to have a platform that can be easily tied together? How do you guys look at that changing landscape? It's changing pretty radically. >> It's high priority for our customers, right? They've always had a challenge with isolated vendors, right? And how do you then bring that data together? One of the things that we'd readily notice when I talked to customers is that, this excites them. The opportunity that they have now, to have a platform, regardless of which whether it's first party or third party, to bring that together, is something that they deem as necessary for their organizations to be successful, right? And so now it's all about, we've built now the tools to help them do that. We actually have third party connectors, right? So you can bring in data or we have ETL partners that we can work with to bring that data through that source-- >> And developers can develop on it, right? >> And developers can develop on it. >> Is there a developer program for the Experience Platform yet, or is that still ongoing? >> There is, a big component of what we're doing is the developer betas for this so now developers can go to adobe.com, adobe.io actually, and find a lot of the APIs that are there, available for them, and documentation to help them build an application on top of Platform. >> So they can do that today? >> They can do that today. >> Awesome. >> They can go check that out today, and that, but you're pointing out something that's really important. A platform that is open and extensible, now makes itself available to customers who have, large developer teams. Many CTOs have an organization engineers area, chomping at the bit to build new applications for their organizations. They also have big data science teams too, that are, wanting this take. Data science teams have always been about massaging data, they've been managing it, that gets old for them. They don't want to do that, they want to build something that's unique, innovative and actually inspire their organizations. >> High quality data, real-time and relevant, fast and cool, that's what it's all about. >> Yeah. >> And you guys got a platform, so final question for you. To get a platform right, we've observed, you got to enable success. You've got to be an enabling technology. What's the big secret sauce for this platform? >> The secret sauce. I think it comes down to something that may seem simple. But I think there's a couple pieces that are a secret sauce to it, the ultimate secret sauce that is powered by those other areas, is that real-time customer profile. And that's only the secret sauce because of, what we do from out data connector standpoint of bringing in data in real-time, and standardizing that with the right taxonomy to then inform that real-time customer profile. It's the power of what the platform can do. And then after that, how you use query to develop more data inputs from that, or how you then deliver that, through decisioning or other triggers that you might have available, that's really the secret sauce of what we have within the platform. >> Awesome, Ronall, thanks for coming on. >> Thank you. >> Appreciate the insights we'll follow up, love the streaming, love the real-time profiling, love the data. Adobe's Experience Platform, hitting the market. It's theCUBE, live coverage, day one of two days, of wall to wall coverage. We'll be right back after this short break. (electronic music)

(intro music) >> Good evening. Welcome back to theCUBE's coverage of day one of Snowflake Summit 22 live from Caesar's Forum in Las Vegas. Lisa Martin, here with Dave Vellante. Dave, we have had an action-packed day one. A lot of news coming out this morning. We've talked to Snowflake folks. We've talked to partners, we've talked to customers. A lot going on today. >> It's our light day. Tomorrow it even gets more intense. >> I know. I'm a little scared. (Dave Vellante laughing) We've got another partner of Snowflakes onboard with us here. Please welcome, let me get this, Sudhir Chaturvedi, President and Executive Board Member at LTI. How did I do? >> Yeah, very well, actually. (laughing) >> Dave Vellante: Outstanding. >> Welcome to the program. Tell us a little bit about you and then talk to the audience about LTI and what you're doing with Snowflake. >> Sure. So, LTI is a global technology consulting and services firm. We had (indistinct) out of India. We're part of a large conglomerate, which is over 80 years old. Our founders were two Danish engineers who came to India and were essentially stuck when World War II broke out, and they created a company that's lasted 80 years. So we are very proud of our heritage. We come from an engineering background and frankly what we do with Snowflake is really bring that engineering DNA to Snowflake. So we are, we've been a partner of Snowflake. We are an elite partner of Snowflake, and we work with them across all regions in the world, actually. 50 plus customers today. So, we have great partnership for today. >> And I have a note here. It says you're the GSI Delivery Platform Partner of the Year. Congratulations. What does that entail? What are the requirements to get that award? >> Yeah, I know we are very proud that we are the Delivery Platform Partner of the Year this year. We were the Innovation Partner of the Year, last year. So it shows the journey from innovation to execution in showing delivery. I think what it entails is that we've been recognized for leadership and excellence in executing Snowflake programs at scale, the migration programs and the implementation programs that we've done for customers across the globe. >> Take us back, how did you first find Snowflake? When did you decide to lean in as a company? >> Yeah, it's a great question actually. You know, in fact, so we went public as a company in 2016 and at that time, how do I put it politely? People weren't expecting that much of us. They thought we'll be one amongst many other companies. And we decided that we will vector the company on data, digital, and cloud, and we'll make bets on partners that are perhaps unknown at that time. So in late 2017, early 2018, we started partnering with Snowflake. And since then I must, you know, hand it to Snowflake. We have an phenomenal partnership with them. I just met Frank this morning. Chris Degnan is their Chief Revenue Officer, Colleen Kapase. All of these people have been tremendous in terms of how they work together with us across the world to bring what essentially is phenomenal technology to our clients. >> What was the allure back then? It was, you know, cloud data warehouse, simplified data warehouse, the technically splitting storage from compute, you know, infinite, blah, blah, blah. Was that the allure and saying or did you have a broader vision? >> No, I think what happened was clients were struggling with data because data and applications in our world were sort of very tightly intertwined and they weren't really leveraging data for making realtime decisions. So the moment we saw the promise of Snowflake that you can create true data on cloud, which on sort of all data on cloud, you know what Frank was talking about this morning, and it's available in real time and you can do a lot of things on it. We said, this is technology of the future. It truly is because it separated storage and compute. It did many things that were not possible before. So I think the thing is when you see promising technology as a GSI, you always wonder, should we wait for it to be proven before we jump in? >> Dave Vellante: Right. >> Or should we jump in right up front and help them prove the model? And we decided to take the first approach where we jumped in right up front. >> Dave Vellante: You bet. >> And I think that's helped us earlier. >> Jumped in head first, pandemic hits, they go public. >> Yes. >> Lots of stuff going on. Talk to us about how you're leveraging the power this flywheel that Snowflake has created that I think is just getting bigger and faster. >> Sudhir: Absolutely. >> How are you leveraging the power of the technology to really deliver business outcomes for clients? >> No, that's a great question. And the thing with our initial focus was to get people onto data on cloud and with Snowflake, but now it's really around driving business outcomes from there. So we have a suite called Fosfor which is a data to decisions product suite, which is Snowflake ready. We've also launched PolarSled too which is based on business outcomes. So what we've done is we've done is we've actually created about 155 NorthStars. So various industry sectors, what business outcome do you want to achieve? We call that a NorthStar. And then we say, how do you achieve it with Snowflake? You know, so what we are doing is we're saying let's achieve the business outcome that's going to drive more consumption, but essentially, you know, we live in a difficult world, a increasingly difficult world. So we want to help people take better database decisions. >> Well, what are some of the more interesting ways in which your clients are using Snowflake? >> Yeah, I think when I look at, for example, we have a client in the financial services sector who was struggling with, you know, they're one of the largest asset management and fund management companies in the world. They're a household name, everybody knows them. And they probably have an EFT or some sort of 401k with them. And what they were struggling with was to say, how do I actually get various sources of data together in a way that I can make better asset, you know, better fund management decisions because otherwise it was left to a lot of very traditional equity research reporting and fund managers taking their expertise. Here, the data from multiple sources being available, running some AIML routines on it, we're able to show them patterns in various asset classes, on options, on investments that they hadn't seen before. And now that they've jumped headlong into it, 15 of their units across the world are using it now. So I think the power of once you see data in action that it's sort of, it's almost like the superpower that smart people get. It's like, yeah, like you suddenly arm them with so much more than they had previously. And then they get so much better at what they're doing. And ultimately consumers like us benefit from that. So, you know, that's really where we want to go. >> What's LTIs like best sweet spot where, you go into a client and you know, wow, this is a perfect fit for what we do? >> Yeah. So I think I would say banking and insurance is 47% of our business. We really understand that business extremely well. The other aspect of that is because we come from a manufacturing heritage. We've had that as well. And media is something we've done more recently. So, you know we've got a media cloud along with Snowflake. So I would say these are the sectors that we are, so we've been very domain focused as a client, as a company. You know, domain first, technology, we'll work with whatever technology the domain needs but that's really been helpful to us all. And this is where that whole point of NorthStar and Fosfor comes back in, which is, today, I think without the data on cloud you would've never achieved the kind of outcomes that we are able to achieve with our clients today. >> How did you feel about the recent sales pivot that Snowflake has made in terms of retail, but also healthcare and life sciences? Talk to me about that and is that enabling your joint customers to really leverage? >> Yeah, no, I think it's very exciting. We are working with clients on that. They like the new model. They're looking forward to, I think what clients are now doing is they're putting data perhaps ahead of even in these times where people are looking at, you know, we are seeing seven or eight very difficult macroeconomic trends. People are wondering, clients are wondering, what's this going to mean for their business in the future? So they're looking at spends and saying, what do I prioritize? But what I find is that that data spend only goes up, you know? So, our own data practice has sort of grown fourfold in the last six years, you know? So it's been just an exponential growth for us. And essentially Snowflake is our largest bet in that space even over every other technology that's out there. So I think clients, when they see that combination of how Snowflake is changing and what we can bring to them, I think the model works well for them. >> You know, ecosystem is one of the areas that we always pay attention to. You can see, just look around,. I mean, you compare 2019 to where we are today. What's the importance of ecosystem to LTI and how do you see it evolving? >> That's a great question. So, you know, it's like, I think in About a Boy, you know, Hugh Grant says that no man is an island. You know, and I think the same thing applies for companies. Any company, no matter what size they are, if they think that they can do everything themselves and I think they're not going to be successful in the long run. We believe that the ecosystem of partnerships is what drives all the best outcomes for our clients and our clients expect that today. They want (indistinct) partners to work together. And the thing with an ecosystem is, you know no one person can dominate an ecosystem, you know? The customer has to be at the center of the ecosystem and then everybody in the ecosystem is actually saying how best do I service the customer? So I think if you have that kind of customer centricity and you understand that ecosystems, you know, on your own you'll never be as good as an ecosystem. I think you nailed it, but it requires, a partnering ethos and that's what we really like about Snowflake. Such a strong partnering ethos. I still, I keep telling people if I text or message Chris or Colleen, I'll get a response in within 15, 20 minutes. You know, that's invaluable when you're trying to do great things for your joint clients, you know, so. >> Sounds like there's a lot of synergies there around the customer obsession, customer centricity. >> Absolutely. I think responsiveness in today's world is key. You know, I think the first people to respond, even if it's to say, you know what, I hear you I'm going to get back to you. I think, you know, people love that about you. It's easy to say customer centric. It's difficult to actually practice it in real life. And we believe that, for us, responsiveness is the key. We'll respond no matter what time of day or night. And the other thing is we'll respond even with our partners, right? We are not going to respond on our own and then bring everybody else along. Even things like, I don't know this but I can refer you to a partner who can help you do this. That's also a response. >> That responsiveness is so critical, especially in this day and age where I think one of the things that was in short supply during COVID and one of the many things is patience and tolerance. >> Correct. >> Right? On us as consumers and our business lives. So being able to respond even just to say we're checking, don't know yet, that builds trust between organizations with customers. >> Well, yeah, absolutely. In fact, you know, even the first year of the pandemic we grew nine and a half percent, year and year. >> In India, we were the fastest growing company that year. And if anybody asked me why did you grow nine and half percent when the industry grew at -1%, you know, in that financial. I think it was the speed at which we responded between February and June to client requests. We responded even before, I know I was in calls till 12:30 in the night working with clients to say, okay how do we fix this? How do we change this? How do we stop doing something? How do we cut costs, whatever they needed. And what we did in the first three months actually helped us our first four months when the first wave of the pandemic really hit. Actually clients were like these guys were on our side when times are tough. Let's sort of bet on them. And the data business actually grew. And I keep saying this, you know, whenever a big macro trend hits when there's more uncertainty, people look to the data because your judgment and experience is no longer applicable. Nobody in the world had any experience or judgment that could be applied in COVID times, right? So you need to now look at the data and say, okay, is the data telling me something that I would never come to know based on my own experience? And I think, you know, this is what I call the real database decisions is no company in the world will say we don't do it. But I think today's world, we are seeing real time data decisions being taken. We see it in the supply chain all the time. We see it in how banks are processing interest rate rises, et cetera. It's the speed at which they're acting would not be possible without a data first kind of approach they've taken. >> Right. And it has to be real time these days. >> It has to be. >> Every organization. That's no longer a nice to have. >> No, you know, and data is getting out of date also so quickly. I mean, in today's world, with the war in Ukraine I think the first thing we realized was that almost every parameter on commodity, whether it was oil or steel or shipping or whatever, it changed so rapidly that the only way to predict, many of our clients were not able to to tell their customers when they would be able to deliver products and service or products, especially manufacturing clients because they just didn't know when they would get their materials and go get their parts, et cetera. And we used data to say, okay, let's at least establish a base on which, because clients get disappointed, more customers get disappointed when you don't meet a delivery date. So we wanted to say, let's make it more predictable, even in unpredictable times. So we were able to manage expectations. We were able to do that better. Without the data there was no way it would've happened. There was just no way. And frankly, for us, Snowflake is the reason. For us it's our biggest bet in the data space. And that's how most of the work that we are doing in supply chain, in fact, I'm just headed to a manufacturing event that our team has organized, which is with Snowflake on data on cloud for manufacturing clients. So we've been slightly behind the curve compared to some of the others, but now seeing the promise and saying, hey let's go for this. >> There's a tremendous amount of potential. We're only scratching the surface. We thank you so much >> Sudhir: Thank you. >> For joining David me on the program, talking about LTI, the power of what you're doing together with Snowflake. We'll let you get to that manufacturing event. I'm sure that they are looking forward to talking to you. >> Yeah, no. Thank you so much. It was lovely to speak to you. Thank you so much. >> Likewise. My pleasure. For our guest and Dave Vellante, this is Lisa Martin signing off from the show floor of Snowflake Summit 22. Day one coverage is complete. Dave and I look forward to seeing you bright and early tomorrow for a jam packed day two. Thanks so much for watching. Take good care. (outro music)

>>Hi, everyone. Welcome to the cubes presentation of the AWS startup showcase the theme. This episode is data as code, and this is season two, episode two of the ongoing series covering exciting startups from the ecosystem in cloud and the future of data analytics. I'm your host, John furry. You're getting great featured panel here with AWS heroes, Lynn blankets, the CEO of Lindbergh Lega consulting, Peter Hanson's, founder of cloud Cedar and Alex debris, principal of debris advisory. Great to see all of you here and, uh, remotely and look forward to see you in person at the next re-invent or other event. >>Thanks for having us. >>So Lynn, you're doing a lot of work in healthcare, Peter you're in the middle of all the action as data as code Alex. You're in deep on the databases. We've got a good round up of, of topics here ranging from healthcare to getting under the hood on databases. So as we'll start with you, what are you working on right now? What trends do you see in the database space? >>Yeah, sure. So I do, uh, I do a lot of consulting work working with different people and, you know, often with, with dynamo DB or, or just general serverless technology type stuff. Um, if you want to talk about trends that I'm seeing right now, I would say trends you're seeing as a lot, just more serverless native databases or cloud native databases where you're seeing these cool databases come out that really take advantage of, uh, this new cloud environment, right? Where you have scalability, you have plasticity of the clouds. So you're not having, you know, instant space environments anymore. You're paying for capacity, you're paying for throughput. You're able to scale up and down. You're not managing individual instances. So a lot of cool stuff that we're seeing, you know, um, with this new generation of, of infrastructure and in particular database is taking advantage of this, this new cloud world >>And really lot deep into the database side in terms of like cloud native impact, diversity of database types, when to use certain databases that also a big deal. >>Yeah, absolutely. I like, I totally agree. I love seeing the different types of databases and, you know, AWS has this whole, uh, purpose-built database strategy. And I think that, that makes a lot of sense. Um, you know, I want to go too far with it. I would, I would more think about purpose-built categories and things like that, you know, specialize in an OLTB database within your, within your organization, whether that's dynamo DB or document DB or relational database Aurora or something like that. But then also choose some sort of analytics database, you know, if it's drew it or Redshift or Athena, and then, you know, if you have some specialized needs, you want to show some real time stuff to your users, check out rock site. If you want to, uh, you know, do some graph analytics, fraud detection, checkout tiger graph, a lot of cool stuff that we're seeing from the startup showcase here. >>Looking forward to unpacking that Lynn you've been in love now, a healthcare action with cloud ops, the pandemic pushes hard core on everybody. What are you working on? >>Yeah, it's all COVID data all the time. Uh, before the pandemic, I was supporting research groups for cancer genomics, which I still do, but, um, what's, uh, impactful is the explosive data volumes. You know, when you there's big data and there's genomic data, you know, I've worked with clients that have broken data centers, broken public cloud provider data centers because of the daily volume they're putting in. So there's this volume aspect. And then there's a collaboration, particularly around COVID research because of pandemic. And so you have this explosive volume, you have this, um, need for, uh, computational complexity. And that means cloud the challenge is it, you know, put the pedal to the metal. So you've got all these bioinformatics researchers that are used to single machine. Suddenly they have to deal with distributed compute. So it's a wild time to be in this space. >>What was the big change that you've seen with the, uh, the pandemic and in genomic cloud genomic specifically what's the big change has happened. >>The amount of data that is being put into the public cloud, um, previously people would have their data on their local, uh, capacity, and then they would publish their paper and the data may or may not become available for, uh, reproducing the research, uh, to accelerate for drug discovery and even variant identification. The data sets are being pushed to public cloud repositories, which is a whole new set of concerns. You have not only dealing with the volume and cost, but security, you know, there's federated security is non-trivial and not well understood by this domain. So there's so much work available here. >>Awesome. Peter, you're doing a lot with the data as a platform kind of view and platform engineering data as code is, is something that's being kicked around. What are you working on and how does platform engineering change as data becomes so much more prevalent in its value proposition? >>Yeah. So I'm the founder of cloud Cedar and, um, we sort of built this company out, this consultancy all around the challenges that a lot of companies have got with getting their data sorted, getting it organized, getting it ready for other use cases, such as analytics and machine learning, um, AI workloads and the like. So typically a platform engineering team will look after the organization of a company infrastructure, making sure that it's coherent across the company and a data platform, engineering teams doing something similar in that sense where they're, they're looking at making sure that, uh, data teams have a solid foundation to build upon, uh, that everything's quite predictable and what that enables is a faster velocity and the ability to use data as code as a way of specifying and onboarding data, building that, translating it, transforming it out into its specific domains and then on to data products. >>I have to ask you while you're here. Um, there's a big trend around data meshes right now. You're hearing, we've had a lot of stuff on the cube. Um, what are practical that people are using data mesh, first of all, is it relevant and how are people looking at this data mesh conversation? >>I think it becomes more and more relevant, uh, the bigger the organization that you're dealing with. So, you know, often times in the enterprise, you've got, uh, projects with timelines of five to 10 years often outlasting technology life cycles. The technology that you're building on is probably irrelevant by the time that you complete it. And what we're seeing is that data engineering teams and data teams more broadly, this organizational bottleneck and data mesh is all about, uh, breaking down that, um, bottleneck and decentralizing the work, shifting that work back onto, uh, development teams who oftentimes have got more of the context and a centralized data engineering team. And we're seeing a lot of, uh, Philocity increases as a result of that. >>It's interesting. There's so many different aspects of how data is changing the world. Lynn talks about the volume with the cloud and genomics. We're hearing data engineering at a platform level. You're talking about slicing and dicing and real-time information. You mentioned rock set, Alex. So I'd like to ask each of you to answer this next question, which is how has the team dynamics changed with data engineering because every single company's impacted. So if you're researchers, Lynn, you're pumping more data into the cloud, that's got a little bit of data engineering to it. Do they even understand that is that impacting them? So how has data changed the responsibilities or roles in this new emerging area of data engineering or whatever you want to call it? Lynn, we'll start with you. What do you, what do you see this impact? >>Well, you know, I mean, dev ops becomes data ops and ML ops and, uh, you know, this is a whole emergent area of work and it starts with an understanding of container technologies, which, you know, in different verticals like FinTech, that's a given, right, but in bioinformatics building an appropriately optimized Docker container is something I'm still working with customers now on because they have the concept of a Docker container is just a virtual machine, which obviously it isn't, or shouldn't be. So, um, you have, again, as I mentioned previously, this humongous skill gap, um, concepts like D, which are prevalent in ad tech FinTech, that's not available yet for most of my customers. So those are the things that I'm building. So the whole ops space is, um, this a wide open area. And really it's a question of practicality. Um, you know, I have, uh, a lot of experience with data lakes and, you know, containerizing and using the data lake platform. But a lot of my customers are going to move to like an interim pass based solutions. If they're using spark, for example, they might use to use a managed spark solution as an interim, um, step up to the cloud before they build their own containers. Because the amount of knowledge to do that effectively is non-trivial >>Peter, you mentioned data, you mentioned data lakes, onboarding data into lake house architectures, for instance, something that you're familiar with. Um, this is not obvious to some verticals obvious to others. What do you see this data engineering impact from a personnel standpoint? And then ultimately how things get built, >>You know, are you directing that to me, >>Peter? >>Yeah. So I think, um, first and foremost, you know, the workload that data engineering teams are dealing with is ever increasing. Usually there's a 10 X ratio of, um, software engineers to data engineers within a business and usually double the amount of analysts to data engineers again. And so they're, they're fighting it ever increasing backload. And, uh, so they're fighting an ever increasing backlog of, of, uh, tasks to do and tickets to, to, to churn through. And so what we're seeing is that data engineering teams are becoming data platform engineering teams where they're building capability instead of constantly hamster wheels spinning if you will. And so with that in mind, with onboarding data into, uh, a Lakehouse architecture or a data lake where data engineering teams, uh, uh, getting wins is developing a very good baseline of structure where they're getting the categorization, the data tagging, whether this data is of a particular domain, does it contain some, um, PII data, for instance, uh, and, and, and, and then the security aspects, and also, you know, the mechanisms on which to do the data transformations, >>Alex, on the database side, those are known personas in an enterprise, a them, the database team, but now the scale is so big. Um, and there's so much going on in databases. How does the data engineering impact organizations from your standpoint? >>Yeah, absolutely. I think definitely, you know, gone are the days where you have a single relational database that is serving operational queries for your users, and you can also serve analytics queries, you know, for your internal teams. It's, it's now split up into those purpose-built databases, like we've said. Uh, but now you've got two different teams managing it and they're, they're designing their data model for different things. You know? So L LLTP might have a more de-normalized model, something that works for very fast operations and it's optimized for that, but now you need to suck that data out and get it elsewhere so that your, your PM or your business analyst, or whoever can crunch through some of that. And, you know, now it needs to be in a more normalized format. How do you sort of bridge that gap? That's a tough one. I think you need to, you know, build empathy on each side of, of what each side is doing and, and build the tools to say, Hey, this is going to help you, uh, you know, LLTP team, if we know what, what users are actually doing, and, and if you can get us into the right format there, so that then I can, you know, we can analyze it, um, on the backend. >>So I think, I think building empathy across those teams is helpful. >>When I left to come back to, you mentioned a health and informatics is coming back. Um, but it's interesting, you know, I look at a database world and you look at the solutions that are out there. A lot of companies that build data solutions don't have a data problem. They've never, they're not swimming in a lot of data, but then you look at like the field that you're working in right now with the genomics and health and, and quantum, they're always, they're dealing with data all the time. So you have people who deal with a lot of data all the time are breaking through New Zealand. People who are don't have that experience are now becoming data full, right? So people are now either it's a first time problem, or they've always been swimming in a ton of data. So it's more of what's the new playbook. And then, wow, I've never had to deal with a lot of data before. What's your take? >>It's interesting. Cause they know, uh, bioinformatics hires, um, uh, grad students. So grad students, you know, use their, our scripts with their file on their laptop. And so, um, to get those folks to understand distributed container-based computing is like I said, a not non-trivial problem. What's been really interesting with the money pouring in to COVID research is when I first started, some of the workflows would take, you know, literally 500 hours and that was just okay. And coming out of FinTech, I was, uh, I could, I was blown away like FinTech is like, could that please take a millisecond rather than a second? Right. And so what has now happened, which makes it, you know, like I said, even more fun to work in this domain is, uh, the research dollars have really gone up because of the pandemic. And so there are, there are, there's this blending of people like me with more of a big data background coming into bioinformatics and working side by side. >>So it's this interesting sort of translation because you have the whole taxonomy of bioinformatics with genomics and sequencers and all the weird file types that you get. And then you have the whole taxonomy of dev ops data ops, you know, containers and Kubernetes and all that. And trying to get that into pipelines that can actually, you know, be efficient, given the constraints. Of course, we, on the tech side, we always want to make it super optimized. I had a customer that we got it down from 500 hours to minutes, but they wanted to stay with the past solution because it was easier for them to go from 500 hours to five hours was good enough, but you know, the techies want to get it down to five minutes. >>This is, this is, we've seen this movie before dev ops, um, edge and op operations, you know, IOT, world scenes, the convergence of cultures. Now you have data and then old, old school operations kind of coming up. So this kind of supports the thesis. That data as code is the next infrastructure as code. What do you guys, what's the reaction there for you guys? What do you think about that? What does data's code mean? If infrastructure's code was cloud and dev ops, what is data as code? What does that mean? >>I could take it if you like. I think, um, data teams, organizations, um, have been long been this bottleneck within the organization and there's like this dark matter of untapped energy and potential waiting to be unleashed a data with the advent of open source projects like DBT, um, have been slowly sort of embracing software development, lifecycle practices. And this is really sort of seeing a, a big steep increase in, um, in their velocity. And, and this is only going to increase and improve as we're seeing data teams, um, embrace starter as code. I think it's, uh, the future is bright for data. So I'm very excited. >>Lynn Peter reaction. I mean, agility data is code is developer concept CICB pipeline. You mentioned it new operational workflows coming into traditional operations reaction. >>Yeah. I mean, I think Peter's right on there. I'd say, you know, some of those tools we're seeing come in from, from software, like, like DBT, basically giving you that infrastructure as code, but applied to that data realm. Also there have been a few, like get for data type things, pack a derm, I believe is one and a few other ones where you bring that in and you also see a lot of immutability concepts flowing into the data realm. So I think just seeing some of those software engineering concepts come over to the data world has, has been pretty interesting >>What we'll literally just versioning datasets and the identification of what's in a data set. What's not in a data set. Some of this is around ethical AI as well, um, is a whole, uh, area that has come out of research groups. Um, mostly AI research groups, but is being applied to medical data and needs to be obviously, um, so this, this, this, um, metadata and versioning around data sets is really, I think, a very of the moment area. >>Yeah, I think we, we, you guys are bringing up a really good kind of direction that's happening in data. And that is something that you're seeing on the software side, open source and now dev ops. And now going to data is that the supply chain challenges of we've been talking about it here on the cube and this, this, um, this episode is, you know, we've seen Ukraine war, but some open source, you know, malware hitting datasets is data secure. What is that going to look like? So you starting to get into this what's the supply chain, is it verified data sets if data sets have to be managed a whole nother level of data supply chain comes up, what do you guys think about that? >>I'll jump in. Oh, sorry. I'll jump in again. I think that, you know, there's, there's, um, some, some of the compliance requirements, um, around financial data are going to be applied to other types of data, probably health data. So immutability reproducibility, um, that is, uh, legally required. Um, also some of the privacy requirements that originated in Europe with GDPR are going to be replicated as more and more, um, types of data. And again, I'm always going to speak for health, but there's other types as well coming out of personal devices and that kind of stuff. So I think, you know, this idea of data as code is it's, it goes down to versioning and controlling and, um, that's, uh, that's sort of a real succinct way to say it that we didn't used to think about that. We just put it in our, you know, relational database and we were good to go, but, um, versioning and controlling in the global ecosystem is kind of, uh, where I'm focusing my efforts. >>It brings up a good question. If databases, if data is going to be part of the development process has to be addressable, which means horizontally scalable. That means it has to be accessible and open. How do you make that work and not foreclose it with a lot of restrictions? >>I think the use of data catalogs and appropriate tagging and categorization, you know, I think, you know, everyone's heard of the term data swamp, and I think that just came about because that everyone saw like, oh, wow, S3, you know, infinite storage. We just, you know, throw whatever in there for as long as we want. And I think at times, you know, the proliferation of S3 buckets, um, and the like, you know, we've just seen, uh, perhaps security, not maintained as well as it could have been. And I think that's kind of where data platform engineering teams have really sort of, uh, come into the, for, you know, creating a governance set of buckets like formation on top. But I think that's kind of where we need to see a lot more work with appropriate tags and also the automatic publishing of metadata into data catalogs so that, um, folks can easily search and address particular data sets and also control the access. You know, for instance, you've got some PII data, perhaps really only your marketing folks should be looking at email addresses and the like not perhaps your finance folks. So I think, you know, there's, there's a lot to be leveraged there in formation and other solutions, >>Alex, let's back up and talk about what's in it for the customer, right. Let's zoom back and saying reality is I just got to get my data to make sure it's secure always on and not going to be hackable. And I just got to get my data available on river performance. So then, then I got to start thinking about, okay, how do I intersect it? So what should teams be thinking about right now as I look up all their data options or databases across their enterprise? >>Yeah, it's, it's a, it's a good question. I just, you know, I think Peter made some good points there and you can think of history as sort of ebbing and flowing between centralization and decentralization a lot of times. And you know, when storage was expensive, data was going to be sort of centralized and Maine maintained, sort of a, you know, by the, uh, the people that are in charge of it. But then when, when S3 comes along, it really decreases storage. Now we can do a lot more experiments on it. We can store a lot more of our data, keep it around and do different things on it. You know, now we've got regulations again, we were, we gotta, we gotta be more realistic about, about keeping that data secure and make sure we're, we're doing the right things with it. So it's, we're gonna probably go through a period of, of centralization as we work out some of this tooling around, you know, tagging and, and ethical AI that, that both Peter. And when we're talking about here and maybe get us into that, that next wearable world of de-centralization again. But I, I think that ebb and flow is going to be natural in response to, you know, the problems of the, the other extreme, >>Where are we in the market right now from progress standpoint, because data lakes don't want to be data swamps. You seeing lake formation as a data architecture, as an example, where are we with customers? What are they doing right now? Where would you put them in the progress bar of, of evolution towards the Nirvana of having this data sovereignty? And this data is code environment. Are they just now in the data lake store, everything real-time and historical? >>Well, I can jump in there. Um, SQL on files is the, is the driver. And so we know when Amazon got Athena, um, that really drove a lot of the customers to really realistically look at data lake technologies, but data warehouses are not going away. And the integration between the two is not seamless. No, we, we are partners with AWS, but we don't work for them. So we can tell you the truth here. Um, there's, there's work to it, but it really, for my customers, it really upped the ante around data lake, uh, because Athena and technologies like that, the serverless, um, SQL queries or the familiar quarry, um, uh, libraries really drove a movement away from either OLTB or OLAP, more expensive, more cumbersome structures, >>But they still need that. Oh, LTP, like if they have high latency issues, they want to be low latency. Can they have the best of both worlds? That's the question. >>I mean, I w I would say we're getting, you know, we're getting closer. We're always going to be, uh, you know, that technology is going to be moving forward, and then we'll just move the goalpost again, in terms of, of what we're asking from it. But I think, you know, the technology that's getting out there, you can get, get really well. And then, you know, just what I work in the dynamo DB world. So you can get really great low latency. So, you know, single digit millisecond LLTP response times on that. I think some of the analytics stuff has been a problem with that. And there, there are different solutions out there to where you can export dynamo to S3, and then you can be doing SQL on your FA your files with Athena Lakeland's talking about, or now you see, you know, rock set of partner here that that'll just ingest your dynamo, DB data, you know, make all those changes. So if you're doing a lot of, uh, changes to your data and dynamo is going to reflect in Roxanna, and then you can do analytics queries, you can do complex filters, different things like that. So, you know, I, I think we continue to push the envelope and then we moved the goalpost again. But, um, you know, I think we're in a, a lot better place than we were a few years ago, for sure. >>Where do you guys see this going relative to the next level? If data as code becomes that next agile, um, software defined environment with open source? Well, all of these new tools with serverless things happening with data lakes are built in with nice architectures with data warehouses, where does it go next? What happens next? If this becomes an agile environment, what's the impact? >>Well, I don't want to be so dominant, but I have, I feel strongly, so I'm going to jump in here. So, so I, um, I feel like, you know, now for my, my, my most computationally intensive workloads, I'm using GPS, I'm bursting to GPU for TensorFlow neural networks. So I've been doing quite a bit of exploration around Amazon bracket for QPS and it's early. Um, and it's specialty. It's not, you know, for everybody. And the learning curve again is pretty daunting, but, um, there are some use cases out there. I mean, I got ahold of a paper where some people did some, um, it was a Q CNN, um, quantum convolutional neural network for lung cancer images, um, from COVID patients and the, the, uh, the QP Hugh, um, algorithm pipeline performed more accurately and faster. So I think, um, bursting to quantum is something to pay attention to. >>Awesome. Peter, what's your take on what's next? >>Well, I think there's still, um, that, that was absolutely fascinating from Lynn, but I think also there's, there's, uh, you know, some more sort of low-level, uh, low-hanging fruit available in, in the data stack. I think there's a lot of, there's still a lot of challenges around the transformation there, getting our data from sort of raw landed data into business domains, and that sort of talks to a lot of what data mesh is all about. I think if we can somehow make that a little more frictionless, because that that's really where the like labor intensive work is. That's, that's kinda dominating, uh, data engineering teams and where we're sort of trying to push that, that workload back onto, um, you know, software engineering teams. >>Alice will give you the final word. What's the impact. What's the next step? What's it look like in the future? >>Yeah, for sure. I mean, I've never had the, uh, breaking a data center problem that wind's had, or the bursting the quantum problem, for sure. But, you know, if you're in that, you know, the pool I swim and of terabytes of data and below and things like that, I think it's a good time. It just like we saw, you know, like we were talking about dev ops and, and pushing, uh, you know, allowing software engineers to handle more of, of the operation stuff. I think the same thing with data can happen where, you know, software engineering teams can handle not just their code, not just, you know, deploying and operating it, but also thinking about their data around the code. And that doesn't mean you won't have people assist you within your organization. You won't have some specialists in there, but I think pushing more stuff, even onto the individual development teams where they have ownership of that. And they're thinking about it through all this different life cycle. I mean, I'm pretty bullish on that. And I think that's an exciting development >>Was that shift, what left with left is security. What does that mean to >>Shipped so much stuff left, but now, you know, the things that were at the end are back at the end again, but, uh, you know, at least we think we can think about that stuff early in the process, which is good, >>Great conversation, very provocative, very realistic and great impact on the future data as code is real, the developers I do believe will have a great operational role and the data stack concept and impacting things like quantum, it's all kind of lining up nicely. Um, and it's a great opportunity to be in this field from a science and policy standpoint. Um, data engineering is legit. It's going to continue to grow and thanks for unpacking that here on the queue. Appreciate it. Okay. Great panel D AWS heroes. They work with AWS and the ecosystem independently out there. They're in the trenches doing the front lines, cracking the code here with data as code season two, episode two of the ongoing series of the 80, but startups I'm John for your host. Thanks for watching.

>>live from Copenhagen, Denmark. It's the Q covering Nutanix dot next 2019. Brought to you by Nutanix. Okay, Welcome back, everyone. To the Bella Centre in Copenhagen, Denmark. We are kicking off day two of the cubes live coverage of dot Next Nutanix the Nutanix show dot Next I'm your host, Rebecca night sitting alongside stew. Minutemen, of course, Do. The word of the day is delight. And in Copenhagen, Denmark, which is a year after your voted the most happy, the happiest country, the country that coined the term Hugh Ge, which means a sense of well being. What do you think delight It means in the context of this show in particular. >>Yeah, Rebecca. Right yesterday I thought I only knew one word. Ivan tackle. It was, Thank you, of course, but Hugh GE is actually one I I'd read about cause it's interesting. The study of happiness. They actually have an institute here in Denmark on talk about it. As you said, the people are some of the happiest. You say, Wow, it's, you know, often cold and rainy and things like that. But they do look into the study of delight, and it's it's something that I find pretty fascinating. I read a book by Tony Shea, who's the founder and CEO of Zappos talked about. You know, we all talk about where you want to go in career and what you want to do. But you know, how do we actually understand happiness and bringing it to the Tannic Show? Definitely. There is a certain joy from the community here. We've had a lot of talk with some of the practitioners as well as some of Nutanix employees, they want to say customer focused. They wantto, you know, build these experiences as the CEO Dheeraj Pandey said. And therefore, it's not about that that product, because so much in technology it's that new, shiny thing that we understand. Oh, it's never a silver bullet, and there's always the repercussions. And how do I have to reorganize? Things change so fast and technology. But if I could have experienced with the example get used all the time, is you know what would transform when we move to you know, the smartphone revolutionized by the iPhone or so many other things that just pull together, that that simplicity that gets baked in the design, something we've talked about both, You know, in Denmark as well as from the Nutanix discussion s o. So pulling those pieces together kind of a left brain right brain all pulling together. It has been interesting. And yeah, it gives kind of a highlight as to why Copenhagen was a nice place. Definitely. We've enjoyed, you know, being here at the show. >>Absolutely. And I think you're you're you're you're right on or we'll be talking a lot about designed today because delight is one of those again. It's something ineffable quality. You don't know you're being delighted because you're just being delighted. It's just nice at the ease of use. And in Monica Kumar, who we had on the show yesterday, of course, was talking about all all of the elements that go into that, taking 10 clicks and making enemies e swipe, eliminating downtime just a kn easy, intuitive use, which is which is absolutely what goes into delighting customers. We're gonna have a teacher. I'm a Chandran on the show today, talking Maura about designed to, uh, tell me about the energy of the show. We're gonna get into Nutanix a bit more today too. But just what do you think about the energy? Ah, what what you're feeling. >>So there are certain shows that we go to where we know that you have the true believers at the show. Splunk sw dot com is one where they all love the geeky T shirts that they get and people enjoy their service. Now, another one. A lot of the software companies it transformed the way they think. And then then they work. S O. You know, Dave wanted for years would tell me about that community community I know. Well, the VM world community. This reminds me of earlier days in VM World VM wear, you know, is dominant in their space. But, >>you know, >>they're shows. Not exactly. You know, a There are parties and their friends that we get together and one of the best communities in the industry. But, you know, it's a much, much bigger company. When you're 60,000 people and things like that, there's not as much of the kind of smaller, you know, touch and feel. You know, we heard from Monica yesterday. She talked about right when she joined the company. You know, somebody she knew would reached out about an issue that need to be worked out and just seamless, all swarming to solve that issue. Something, you know, I've done it. Some companies I've worked out where you know what teams pulling for. You know, the customer comes first and you get things done. So the customers here definitely are highly engaged, very excited because the experience of using the solution has made their lives easier and transfer help them transform their business. You know, that goal of I t helping toe not only support but be a driver of the business is exciting. >>So So exactly. And this is what we're gonna be talking about today to new tenants. They have this passionate customer base which they will need as they are a maturing company. So not now They're 10. They're hitting their their tween age years. So talk a little bit about what you're seeing about Nutanix trajectory and what it needs to do to to hit those next steps. >>S o. You know, the discussion for the last two years has been the move from removing hardware for something that they sold, which was always it was the software that was important and changes really passed along the hardware to this move to subscription, and along with that, it isn't just the same core a OS Nutanix software and some of the pieces that go with it. But really, they're expanding beyond infrastructure software to some of the application software. So yesterday we had Nikola, who's the CEO of Frame Frame, is desktop as a service S O. That was the type of software that sat on top of Nutanix or on top of the cloud expanding in that market. We're going have Bala on today to talk about ERA its database database absolutely an application that's that on Nutanix. But now they're building some of these applications. It's interesting. Almost 10 years ago, VM where tried to get into the application space they bought an email company they bought a social company on. Really, that didn't pan out well for them. Amazon does not sell many of their. They sell some of their own application, but most of them are an open source solution that is then delivered as opposed to the building applications. On top of a building applications is that the realm of Oracle on Microsoft and IBM have these, so it positions Nutanix in it in a little bit of different space. And how much are they going to have the customers that bought the platform that will build the service's leverage? The service is on top of them versus how many customers will come to them because of that application. Say, Oh, well, you know, database is one of those challenging things. If I could just have a nice, simple solution and maybe that's in the cloud. Or maybe it is on, you know, Nutanix environment in their data center on their server of choice. You know there are some Pastor Newtown is going forward to a much broader tam, but it's much broader competition, too, and you know their sales force and there's go to market their there's partners we're gonna spend a little time talking about, like the systems integrators today s Oh, it is a big, vast sea out there in the I T World. Nutanix has carved out a nice position where they are today, but, you know, opening up a number of areas of adjacent seas that they're going. So as they ride the software wave that they're pushing, it's an interesting one to set them up for the next 10 years. >>Absolutely. So what do you see are the biggest headwinds facing Nutanix right now. But as we've said, they have a passionate customer base. They've on the main stage. This morning we heard about their high net promoter score. We heard about there. They're amazing customer retention s o much repeat business. What do you think, though, Is is sort of the main What should be keeping dear Ege Pandey up at night. >>So one of the biggest challenges is you know, your 5000 person company. How do you keep growing at that pace? How can I hire we heard in Europe? It is a you know what it is a challenging market to hire. You are no longer that small startup that I'm going to get some AIPO bang for Buck. Now I'm a public company, you know, and you know, their stock incentives and things you can do. But Nutanix has a number of areas that they think they have exciting ways for people to be a part of some of these next waves that they're pushing. But that that is a big challenge. There is really cooperative in out there. We've spent much time talking about the ecosystem. They have a decent ecosystem, but their position in the cloud world Is there a player amongst many, many Betty, you know, hundreds, if not thousands, of companies out there When if you go to Amazon, reinvent you confined the Nutanix booth. But it's not one of the big players there you go to the Microsoft show, go to the Google shows. They are a small piece of that. And when we asked peerages, How do you position yourself and how do you, you know, get awareness in this environment? So when they had to down quarters, it was definitely marketing and sales, where the areas that they said they could not hire fast enough so they are going to need to invest more and they still aren't profitable. So we're almost three years past the I po. If you look at the transition to software, their revenues have been relatively flat. Their margins have been going up. But the market will not reward them if they can't keep the growth going. And, you know, start getting closer to that full profitability. >>Exactly, exactly. Well, these are all gonna be topics that we're going to dig deeper into today. We've got a great lineup of gas. And then, of course, the final keynote speaker. One of your faves. >>Yeah, Well, Kit Harington. Rebecca, What did you think of Carolina? >>She was fantastic. And I think what was really exciting about the interviewee, er was name Is Hae a friend of yours? Uh was It was how he was really drawing these analogies to Nutanix journey. It's similar to that of a professional athlete, and that is someone who who's getting knocked down and has to get back up against someone who's hit winning a few things, winning some business here, but she still needs >>She made a great point where said right. You know, the day after she was named number one, her father was like, Well, you need to get lower. You need to do this. And she's like, Wait, I'm number one. But you have to keep working or everyone will come after you. And so Nutanix is in a strong position, but absolutely they know that they need to keep working and training and improving listening to their customers to move forward. >>Absolutely, absolutely. So so. I think she had a lot of lessons for for Newtown Road, for the Nutanix community to so stew. I'm excited. For Day two, We're gonna have a lot of great custom, bloody great customers and Nutanix people on the show today to >>looking forward to it. And they had a fun party last night. They had the DJs were bumping. They had nice international food, some art and some interesting people dressed up as >>hedges and food >>and things walking around. So it was a little bit weird, but a lot of fun. >>And they're the happiest country in the world. What can we say? I'm Rebecca Knight. First Amendment, stay tuned for more of the cubes. Live coverage of Nutanix dot next.

>> From our studios in the heart of Silicon Valley. HOLLOWAY ALTO, California It is a cube conversation >> high on Peter Birds and welcome to another cube conversation from our beautiful Palo Alto studios. One of the things that makes a cube so exciting as we get great guest from great companies coming on here and talking about some of their new products that they're trying to get in the marketplace of customers Khun Doom or with their technology. And we've got that today. Eric Herzog, cmon VP of worldwide storage channels that IBM storage. He's here to talk about some new things that IBM is doing that especially relevant to high performance, closer, more down market, branch oriented kinds of applications. Eric, welcome to the Cube. >> Thank you, Peter. Really appreciate. Very excited to be with Cuba's Always. >> All right, So what? Start Give us the quick business update and IBM, And let's talk about how that inform some of the new announcement. You >> sure? So two thousand eighteen was a great year for IBM storage. Lots of new introductions and portfolio continue with our multi cloudiness. Everything we've doing now for seven years, all about my multi cloud hybrid private, multiple public cloud providers would continue that mantra. You always something very interesting from a storage array system level perspective brought out extensive portfolio around Envy Me the newest high performance protocol, both inside of a storage array and connecting a storage rate into a network fabric for storage. >> Now let's talk about that. Envy me because envy Me has been associate ID a little bit more higher and stuff. Some of the new things you're doing are bringing envy me and related classes of technology flash to a new class of workload. New class of Hugh's case. Tell us about it. >> Absolutely so what we're doing is bringing out the >> brand new >> refresh store wise portfolio. We start with R V seven thousand, which has envy me both inside the array and support for envy him Over Fibre channel. We have our fifty one hundred just below that, also supporting Envy me in the storage system. We're bringing out a new version of our fifty thirty called the fifty thirty at the very entry space are fifty tenny. These solutions all deliver dramatic performance gains but incredible price discounts as well. For example, the fifty ten e is not only twice as fast as the older fifty ten, but it happens to be up to twenty five percent less expensive. More for the money. That's the key watchword in the store. Wai's family. >> So tell us a little bit more about the fifty Tenney. What kind of use you love talking about applications, workload? Use cases? What kinds of applications were close use cases Are we talking about? >> So we've done a couple things. So first of all, we're leading with all flash across the portfolio. Yes, we still sell hybrids and hard drive a ways, and we'LL still do that in the fifty Tenney, for example. So if you're using hard drive, raise backup in archive work loads. Of course. Now, when using all flash arrays in a smaller shop, it could be your primary storage. Herzog's Barn Grill. That might be the great way to go when you're thinking more of the broader enterprises. It's great for edge. So branches of a bank, all of the outlets of a retail location and even a core data center. Not every workload is even not every data set is even so. Certain things need more expensive arrays and other ways you can go with an entry product. Still deliver the availability, the reliability of the performance you need, but you don't need to spend the most amount of money and stories gives you. That breath gives you the right price point the right software, and it even gives you six nines of availability, which is only thirty one seconds of downtime in a full year on an entry product. That's incredible. >> Well, I would think that the fifty thirty he would be especially relevant for some of those scale at work loves. Tell us about that. >> So in the fifty thirty, we can scale out into two note cluster up to thirty two petabytes, but we start small. You could get it at twelve. Same thing two. Ex Performance. Up to thirty percent less money and all of the store West family comes with our award winning Spectrum Virtualized software, which delivers enterprise class data services. Such a snapshot replication data rest, encryption, tearing, migration, et cetera, et cetera, not only for IBM store wise portfolio, but actually could work with over four hundred fifty raise, most of which are not ours. Great value for the money. Great software and bring better performance at a lower price. The fifty thirty and the whole portfolio includes our spectrum virtually software family. >> Now that's important because as we think about that, the relationship between these and other IBM or other products in the portfolio and multi cloud I know there's some work that's being done there tell us a bit about some of the some of the new updates that you've made. How that spectrum family is becoming even more relevant in the multi club so >> well, when you look at the whole family, everything in the spectrum family has heavy clarification in a multi cloud environment. Let's take spectrum protect not new from an announcement perspective of what we're doing and what we're launching on what we're doing from a new perspective. But it's been ableto backup to the cloud for years. In fact, over three hundred fifty cloud providers use spectrum protect as the engine further back. Oppa's a service portfolio Spectrum virtualized Computer Club. But we also have spectrum virtualized for public cloud that allows you to do staff shot replication only for IBM arrays, but for competitive a raise out to a public loud and even supports a rhe air gapping with a snapshot so you don't have to worry about ransomware malware, that's all. With Spectrum Virtualized family are spectrum sale product can automatically tear to the cloud IBM clad object storage could go from on premise toe off premise. So the big thing we've done with all of our portfolio, the software and then the arrays that sit on it when the case of spectrum protect backup is make sure we can work with any and almost every single cloud in the industry. Whether it's a big cloud like IBM Cloud, Amazon or Microsoft or a small cloud provider, you may want to use a local cloud provider depending on where you're located, not use one of the big club fighters. We work with that cloud provider to, But you made >> some made some special for spectrum virtual eyes. I mean spectrum virtualized. You're adding a new brother to the portfolio >> so that spectrum virtualized Republic Cloud. We first brought it out on IBM Cloud only. It now supports a ws. We know customers multi cloud most end users and you guys have written about it extensively at Weeki Bond in the Cube and silicon angle. That and users will not use one public loud. They will have four, five, six different public clouds. So spectrum virtualized republic loud delivers to onsite arrays. All the capability spectrum virtualized for public cloud sits in a V m wear virtualized in stand station out of the public cloud provider. Giving all those enterprise class functionalities and allowing us to move data back and forth to IBM. Cloud allows to move data back and forth to an Amazon cloud not only first store wise but also for again over four hundred fifty Raise that aren't ours using the spectrum virtualized software. So that's a great edition. We had it for IBM Cloud now for Amazon. As Republican Stanley first brought it out last year. It will also be extended to more clouds in the future as well. >> So store rise gonna refresh nooooo spectrum virtualized for public cloud Also getting, you know, adding to the portfolio great stuff. How do you anticipate that customers are gonna respond? >> Well, we've already had a great response for those customers we talked to under a non disclosure agreement. Now we're public with this new portfolio. What's not to like? You get extensive software capably spectrum virtualized with our fifty one hundred store wise and are seven thousand stories. Now get thie Envy Me technology, which is white hot performance technology in the storage injury, except at a much lower price point that when our competitors are brought out. So he brought Andrea me high end technology into the entry price point space, which is great. And we also have a nice portfolio that gives you certain products. Accuse the court data center other pranks that you would use the edge like banking and all the locations or in retail. So you're not going to put the most expensive practice. But you have a great six nines of availability, extensive software, twice the performance, and I said up to twenty five percent or thirty percent less, depending on which of our products than the older product. Bigger, faster, better, cheaper. >> So, Eric, let me be one of first congratulate you thie IBM storage journey since you and Ed Assualt have shown up at IBM or come backto idea in some cases has it's been a great thing to watch. You really refreshed portfolio made some great strides and we're getting great feedback from customers about the effort. So congratulations. >> Great. Thank you. And the new store lives is the latest in that and look for more just like we did in two thousand eighteen. Refresh across the plug. There's more coming in the second half here in other elements of our portfolio. >> Great sea IBM back and relevant in storage World Eric Herds on CMO VP of worldwide store channels, IBM Storage Thanks once again for being on the Cube. >> Thank you, Peter on. >> I'm Peter Burroughs. Thanks for listening until next time. Thanks for participating in this cube conversation.

>> Voiceover: Live from San Francisco, it's The Cube covering DevNet Create 2017 brought to you by Cisco. >> Welcome back everyone. Live in San Francisco, this is exclusive Cube coverage of DevNet Create, Cisco's inaugural event where they're going out into the devops world into the community ingratiating and donating a million dollars for hardware, really taking their DevNet developer program to the next level, really creating an open developer devops ethos. Coverage two days. I'm John Furrier with my co-host, Peter Burris, head of wikibon.com research, also head of research SiliconANGLE Media. Our next guest is Abby Kearns, Executive director of Cloud Foundry. Welcome back to The Cube. Good to see you. >> Always a pleasure. >> I'm excited to chat with you for multiple reasons. One, you've got a hot product but at Dell EMC world more than ever you start to see the emergence of Cloud Foundry coalescing, not consolidating, coalescing the stakeholders. >> Abby: Yeah. >> And so you start to see multi-cloud starting to develop as the swim lane or a path, certainly hybrid cloud is hot. Cloud Foundry is kind of interesting right now. So, congratulations. Give us the update. What's going on? Obviously, you've got a spring in your step. What's happening? >> Well, not to be biased, but I feel like Cloud Foundry's always been interesting. >> John: Well, from a growth standpoint, now more than ever. >> Yeah, we started talking about multi-cloud a year ago. So, it's really interesting to see it really taking form in the industry where people are like, "Yes." People don't want to be locked into a single cloud. Yes, they want to have choice. And yes, they want to be able to take their workloads and move them anywhere and public cloud, right now, has gotten such amazing traction. And they're coming up with interesting things. You know, GCP is really coming into it's own and Azure's really starting to take shape. I think there's a lot of potential for a lot of features and services to really be available. >> The thing I like talking to you about is ... Talking with you is because you're in an area that is misunderstood early on. You've been beating on this drum, we've talked about this before. Andy, Jessie and I had similar conversations about this, but Amazon, how they were misunderstood in the beginning. People were dismissing it. And so there's always a tipping point. The Cube's the same way. "What do you guys do?" And we keep on ... And then people figure it out. That's kind of when the rest of the world, mainstream starts to get it and in particular, these are the model. What was the tipping point for you because I know that you had this same vision. What's the tipping point now? Why are we now is it happening? Because of the pressure? Is it because now the tools are coming to the table? What's the forcing function that's taking Cloud Foundry from this alternative approach to a viable, scalable opportunity? >> Well, I think it's always been viable. I think where we are, though, is we're seeing users starting to get traction on digital transformation. And I know digital transformation, everyone's like, "God, not that term again. We're so tired of it." But, it's true. It's more of these enterprise organizations are, "I'm now a software company," or, "I'm now competing against Airbnb or Tesla." You know, the landscape is changing and so as they realize they become software companies and they need to develop software, they're investing more in developers and development and they're like, "Oh, well, how do I do that quickly? How do I really focus on that?" Because turns out really investing in a lot of other ancillary aspects isn't core to my business. It's not changing who I am. And so investing in technology, in software in particular, allows you to differentiate your business. And so a platform like Cloud Foundry really abstracts the way an infrastructure automates that as much as possible, so the developers have the freedom to create. And that's really what's going to differentiate businesses that are becoming software companies. >> So, as you think about the developer, break it down where you think it's going to be in about five years. Because we're here at the developer conference and most of these people are folks with network expertise or folks with traditional software development expertise coming into the world where we're going to build distributed applications. Very, very important stuff. But as you think about the characteristics or how the demographics of what the developer is, how much is it going to be the professional hard-core developer, how much of it is going to be citizen development? Where do you think all this goes in five years as we start to see how all this new software gets created to serve all the business needs that are on the horizon of a digital world? >> Well, my opinion is that eventually everyone is going to be a developer of some type, whether it's taking advantage of business logic or operationalizing outcomes from machine learning or automotive AI, just taking advantage of that. But in five years, I think, where we are today, the technology is definitely growing faster than user's capability to adopt it all. So, there is a growing gap there. >> And use cases are emerging as well. So, another dimension to that complexity is new devices are connected. >> Exactly, so I think there's going to be an exponential over the next couple of years of growth in terms of the technology, what it enables, why it enables, and how the users are adopting it. Because I think we all theorize about what users could do and will do, but at the end of the day, if these large enterprise organizations start actually putting the focus and the force behind development, imagine what they can come up with. You know, look at what GE's doing with Predix, or SAP is doing with their cloud platform and think about the investment around those applications and the ability to influence where we go. You know, seven years ago we wouldn't have predicted the iPhone would be the tool that it is today. Or the iPad or the way that we actually make use of these as platforms because of the applications. The applications have really driven the innovation around that and I think we'll start seeing that the applications and the use cases really driving the innovation leaps. >> Talk about the challenges and opportunities that digital transformation has for business that are trying to get there and there's obviously different business profiles, startup, fast growing, public company, I mean, Ford. There's a customer of yours I know, I don't want to get into the whole Mark Fields thing. There's challenges at different levels of the organizations. So, to implement devops, at the end of the day, Ford's trying to get better cars, not necessarily a better cloud. Cloud enables them to do things. So, companies have to look at this and have a journey. What is the part that you see that companies are doing well from a journey standpoint and how are they laying out that digital transformation with Cloud Foundry? >> Well, I think more than a journey, they have to have a clear vision, a clear idea where they want to go. Because at the end of the day, technology shouldn't be the goal. Technology should be the enabler to achieve that goal. And ensuring that companies can maintain that clear vision, and really lead from the top with that vision, because, at the end of the day, we talk about digital transformation. Technology is a topic I talk about a lot because, obviously, Cloud Foundry's focusing on the technology piece, but the cultural shift, what it enables is really what's both critical, but also the most difficult. These organizations are trying to transform and become software companies, are also fundamentally changing their business model, their organization, and the way they leverage technology and that's a huge shift for many of these organizations. >> Actually businesses, we were talking before the camera how companies should look at that process because you have to kind of invest and it's not just the old days, you buy a general purpose software stack. Then the suppliers took care of it, say Oracle, whoever. Hey, they supply it, they turnkey, there's some TCO, total cost of ownership involved. I get that. But now, with developers, you're talking about training, you're talking about devops, you're talking about real investment. >> Restructuring, hiring, retention. It changes fundamentally the way you think about everything. How do you hire developers? How do you hire cloud native developers? How do you retain talent? How do you restructure teams? When we talk about two-pizza teams or cross-functional alignment, what that's really saying is, "Hey, I need you to rethink your entire org structure and the way that you incentivize people and motivate people." >> John: And fund it. >> And funding is like, you know, gone are the days of give me your five year plan and we'll do your capex and OPEX allocations. But it needs to be more iterative because you're encouraging agile. You're saying fell fast or iterate more. You're really saying I want you to take ideas and iterate on them, get them out the door, and then maybe that doesn't work. Maybe we try again. But the idea is to continue to iterate and innovate on that. >> Abby, what trends are you seeing in terms of pattern recognition as you go out and evangelize and support your customers with Cloud Foundry? Beauty is in the eye of the beholder depending on how you implement your cloud, IBM and others, the customers. What's the pattern that's consistent across the Cloud Foundry ecosystem that's happening right now, that's maybe different from a few years ago that's emerging? >> Well, to me, the Cloud Foundry users are key. I spend a lot of time talking to them because, for me, it's interesting. We can theorize about the technology and where it should go, but at the end of the day, how you're using it and what you're doing with it is the most important, one might say. >> John: And what are they doing? What are some examples? >> They are really starting to get traction. I mean, Comcast is a great example. The amount of traction they've gained. They have over 1000 developers working on Cloud Foundry right now. Over 10,000 applications running on it. They're doing 180 million transactions per day. That is huge. And, for them, it's not just the amount of investment they've got in it, but it's also how it's transforming the way they work. How much more productive they are and how getting better ideas out to the hands of customers. It's changing the way that they think about customers. Improving the way that they connect to their customers and that's the fundamental shift. >> Have you observed any, because we've, again, been funding the present creation of these events, especially inaugural events like DevNet Create for Cisco, which is to put their toes in the water, but they're committed to it. CubeCon, we saw that emerge. We saw Cloud Native emerge back in the 2008 timeframe with The Cube. Open Stack, obviously, has trajectory. Are you seeing a community expansion? Certainly there's expansion of the community in general. But we're seeing our Cube alumni fans here. I saw Patrick Riley earlier. I saw Lisa Marie. There's not one community any more. There's a series of new communities. OpenStack is one, you got Cloud Native Foundation, or Compute ... CNCF, you've got Cloud Foundry. There seems to be kind of like a flowing set of people in the community. What's happening in the community layers. I mean, it's all good. Does it mean anything? >> Yeah, it means open source is amazing. Because, at the end of the day, that's what's amazing about open source. We can do work with other projects in other communities. We have a great relationship with OpenStack. We have a great relationship with our sister CNCF. In fact the open service broker API project that we announced last year was a way to really take the best of great technology and make it available across other platforms and communities. Because at the end of the day, when we're talking about open source, when we're talking about bringing together diverse perspectives, diverse people to innovate more. So, collaborative R&D is where open source can really drive real value. >> It's an expansion of the community of open source. By the way, I will note that we cover, Hugh, Peter we talked about open source that have gone public. Cloud Air, MuleSoft, the list goes on and on. There's multiple new IPOs. Since RedHat and Hortonworks started that wave, so real companies. >> Real companies doing real things on open source. >> Let me push on this open source concept really quickly because it's very clear that it's been a successful model. But open source has been most successful where the marketplace has a very clear convention of what is being open source. For example, we knew what a UNIX operating system was. LINUX is an open source option. Came very clear. When you think about big data and Hadoop, the use cases of big data, the use cases associated with very complex analytics, not as clear. So, we get a lot of open source stuff that's being created that kind of marginally improves things. How is the open source world through companies like Cloud Air that can provide some leadership going to evolve to get more focus on use cases and how we're going to apply this through open source innovation, as opposed to just creating software that is defined in terms of other open source software around it? What are your thoughts on that? >> Well, I think, going back to the point about diverse participation, that's where the real innovation's happening. So, the innovation isn't really happening at a single company or a single individual. It's happening when you bring together a bunch of individuals and a bunch of different organizations with a bunch of different perspectives. Because that's where you really start to see value. Because you're thinking outside of the box that you know. When you start thinking outside of your known use case, your known customer base and start bringing in other perspectives, that's where you're really able to push the envelope a little bit more and a little bit faster and also build and accelerated ecosystem around that quickly of people that want to participate and commit to driving that and continue to drive that innovation. >> That is recruiting opportunity for the companies. I mean, we were just talking about Cisco being closer to networking side. This is an opportunity to have a foray into innovation, but also recruiting, getting some new blood in. >> What we found in our research that developers actually list that as one of their driving factors on whether or not they're going to join a company. What is their level of participation in an open source project because they want to be able to be part of something bigger. They want to be able to contribute and be able to influence where that technology is going and that is power. >> You're starting to see on GitHub on about pages companies on the executive masthead. Check out my GitHub, see what my code ... Again, this is the badge of honor like in the gaming world where you see how many merit badges you got or guns you've acquired, depending which game you do. But in a way, this is now really the resumes, not the static LinkedIn and it's like what code have you done, what communities are you in. It almost really is a testament. >> I think it's exciting because it's saying that we not only care about technology, but we care about where it's going and that's real exciting both from an open source standpoint, but also as a developer and as a business leader. That should be exciting because you're now able to influence the technology. >> Okay, final question for you Abby. What does this event mean to you? Obviously Cisco is a new event, inaugural event, very cool, very humble, very well one by Suzy and the team, but they have a DevNet Create Cisco Developer Program. Networking guys, we know there. What does this mean, in your opinion, in terms of Cisco's statement to the industry? >> I think any program that really wants to bring developers together and give them an opportunity to collaborate, and develop more, I think it's amazing. That's something that we strive for at Cloud Foundry as well in our event coming up in a couple of weeks, which I think you'll be at. >> John: We'll be there, yep. >> It's also we're trying to mimic something similar, giving an opportunity for developers to come together, share ideas, share knowledge and contribute and work together on common projects. >> Final, final question since you brought up the event. Give us a quick preview of what to expect at the Cloud Foundry Summit in San Francisco. >> Yes, so in a couple of weeks we will host Cloud Foundry Summit North America. There's some announcements that you should pay attention to. >> John: Come on, tell us! >> Some really exciting announcements. >> Put the dots out there, we'll connect them. >> Some new new members that we're excited about joining as well as some new technology announcements. But more than that, it's our first time. We've really been rejiggering the structure of the event and we like to think of ourselves of an agile foundation. And we wanted to encourage more developers to be there, so, we're offering developer language track, so with Node and Cloud Native Java and SAP's got a track. But more than that we're also going to be announcing general availability of the Cloud Foundry Certified Developer. So, we're going to offer training on site and certification on site for the first time. So, the idea is to make this a place for developers to come and share ideas and network, but also learn more about not just Cloud Foundry, but cloud native best practices. >> So, a confab with all the bells and whistles, plus now the learning tracks to make it kind of a hands-on event. Abby Kearns, executive director of Cloud Foundry here at Cisco's inaugural DevNet Create events, Cube's coverage. I'm John Furrier with Peter Burris. Stay with us and check out Cloud Foundry Summit in a few weeks. I'm John Furrier with Peter Burris. We'll be right back. (techno music)

hey welcome back everybody Jeff Rick here or the cube conversation and the SiliconANGLE cubes Palo Alto studio a little bit of a break and the crazy conference season so here to kind of fix the gear and take things up and sit down and in the context of a conversation outside of a show to really get the update and we're really excited to be joined here by two guests who are announcing a pretty exciting deal that's happening today is who you shoot a CTO of Hitachi Data scissors welcome again to you and jack mazzoni vice president storage networking at brocade welcome thank you so let's just jump right into it tell everybody what happened today and why this is big news yeah sure I'm gonna start it and so what we're announcing today is broke aids developed its its next-gen called gen-6 fibre channel switches and it's a whole portfolio and we're very excited that hitachi who resells the OEM are our product to to their customer base is launching on the state as well so we're very excited about that and it's big news right and so you'll be able to buy this product today from hitachi for all the great customers that we have out there today and that's the big announcement excellent and why is this important to your customers well this is just the next evolution in fibre channel I mean 32 gigabit per second don't you know we were just on 16 now not long ago and so it's going to open up a lot of bandwidth open up you know more workload being processed provide new opportunities for new applications as well so it's funny a lot a lot of talk on you know already it in the end of Moore's law we're going to be able to squeak out more compute power outage micro processors and stuff but it sounds like you guys are squeezing out a lot more performance on the network yeah I know absolutely and one thing that you know Hugh mentioned earlier which I thought was great is you know when you get performance like this in the network and you just get performance in general enables consolidation enables efficiencies right and when flash is able to go and allow you to do let's say the same or more amount of workloads with less course that's a good thing right and and the networks then got to be able to handle that and it's that kind of efficiencies that when we can jointly bring to our customers that allows them to then spend the time and think about how they transform their IT operations right into this digital transformation era into into enabling IT to be the strategic foundation to go drive the enterprise right and I know sometimes it's hard to to make that connection all the way from Genesis fibre channel to that that's how that connection goes so so it's it's been a proven winner to drive performance it saves money it saves it enables innovation and I think the commitment that brocade and Hitachi have had to to quality to the highest levels of reliability and customer service over the years has really been a cornerstone of our success it's been a great partnership I know our CEO likes to say we partner better than anybody in the industry and that's absolutely true and Hitachi has just been one of those fantastic partners for us for over a decade now so let's unpack that a little bit why is partnership so important and not only just specifically between the two companies here but you know we go to a ton of shows and every show now even if it's a specific vendor like the pentaho show is a whole ecosystem right nobody can do it alone anymore and there's a really kind of renewed focus around the ecosystem and and everyone kind of coming together at the end of the day provide solutions to customers that are going to solve problems so it's a very important piece of it yeah and I think you've a great example that is if it really is a requirement if you think about private cloud infrastructures and converge infrastructures you're bringing so many elements together to deliver a total solution and Hitachi UCP is a great example where you have you know great technologies from hitachi in there we've been able to participate some of our fibre channel as well as our IP storage switches we were able to participate with that and so really I think if you want to participate in a cloud type of architecture whether it's public private hybrid you're going to have to partner you're going to have to particles you may not have all the technologies you may not have all the specialties and customers could require that on at some some levels that's kind of my take on it yes I mean you know we could have tried to develop our own fibre channel switches but you know that would have taken a lot more effort and time and distraction from what our core competencies are you know I mean brocade has a conference season networking both IP and fibre channel networking so it doesn't make any sense for us to try to do that which is better to partner with that right so and the future is going to be all about partnering and and more toward open source to right and the other thing that we find over and over again is really the changing expectations of the way software performs and we hear it all the time you know that why doesn't the software at my work perform like the software on my phone and why isn't it faster and why isn't it more integrated with other sources of information so the demand for better faster stronger applications is only going to increase right nobody wants less data though he wants less performance buddy wats less latency and especially in kind of an API world where all these applications are now not just siloed stacks of applications but they're pulling data from all sorts of places the speed and latency really becomes critical yeah I know I absolutely right and that's why I think this announcement and the construct of the you know the all-flash data center and all the advancements happening with flash is so important it's that linkage and then what the applications can do once they take advantage that you know I always tell people it's like remember the first time your laptop went to a all flash disk remember that experience like via the old spinning disk you're booting up well go to windows right and then you with all flash it was like that emotional experience or how great it was right you take that level at an enterprise level right where you have thousands and thousands of thousands of disks running thousands of applications and now you bring in flash and then around the corner you ring in nvme it's amazing to think about what's going to be coming down the future right and we're very excited about our position it really being it that the the central point of if you will where all this information flow has to go through the network and you know whether it's fibre channel whether it's IP you know we're going to keep to our core values which is you know the highest levels of qualities resiliency bringing in the analytics and partner partner with the top quality companies in the world such as itachi and what was interesting about this release is you added a lot more than a tease a lot more manageability lot more reporting a lot more visibility you know one of the big themes obviously in big data is to move from you know reactive to predictive too prescriptive right and so to have the management layer to have kind of the extra amount of information that you can take advantage of because you've got excess capacity and the pipes if you will and better connectivity to the infrastructure enables a whole different layer of management is which is if you've talked about you and prior interviews you people have to manage a lot more right they're not managing individual boxes anymore now whole different scale man need to be able to automate that those management tools helps us to automate that the infrastructure management also the security part is very important you know the security that brocade brings them into their right into the switch itself right and the security is an interesting point right because that's again a consistent theme everywhere we go it's the old moat just doesn't work anymore the mode and the castle walls now you really have to have security baked in all over the place and the data layer the networking layer all over the place it was the interesting thing is if you think about fiber channel all right let's just offer five channels of technology it is fundamentally right more secure than Ethernet oh we love you know really a great IP portfolio and everything but if you think about Ethernet or excuse me fibre channel when you plug in it it's off by default well first it's a separate network all together right so that's that's one layer secure but it's an off by default meaning that just get you plug in doesn't mean you have access to anything you know you got to go through one man here go there's only going to go through some other stuff but some people say its complexity but but you're at least now actively saying how are the communication is going to happen thin within the this network or either that's really the opposite right because the benefit ethering you plug it in and hey everybody's connected right that's what you want but but when it comes to enterprise let's say storage applications that needs a really but is that the behavior you want that anything that just plugs into it all of a sudden now can connect and and that's one thing that gets kind of lost sometimes than the discussions and the monitor data centers and here I'm really glad that you brought it up and you dropped out of to Jeff it's it's we realize that we're adding more things into it right we're adding more capabilities for in-flight encryption you mentioned forward error correction so the other capabilities were built in it so we take security very seriously and and inherently I think that's another reason that the viability of fibre channel has remained for as long as it has been yeah and it just own it one more time you know kind of what are some of the specific benefits that came out of you two working together for this launch how are you really kind of taking advantage of each other's strengths to really provide a better solution today that people can go out and get well one of the things is they offer backward compelled compatibility we're with two generations right right and that enables us we have a lot of legacy things that we've got to bring forward they don't just rip everything out and put in all these stuff turn the data center off for the weekend is my bonus so you know it gives us that easy transition migration into these higher higher technology levels big one yeah a big one yeah and I think when when the in the porn part two is when we deliver our systems to itachi they test it with their latest and greatest storage they do this full you know systems total solution test so when a customer that brings it into the environment it's it's been fully tested completely NM by brocade and hitachi and then to Hugh's point it's it also then works its backward compatible with everything in the environment nothing's going to you know that nothing will ever break but you know so much time and effort is put into making sure everything runs to seamless as possible because again you have to think about the environments that we're in all right those from mission-critical big environments they got to solve some serious problems they're not up for science projects they're not for risk right yes they have to advance the technology but it's got it done be done in a way that a mitigator essence done a responsible way and that's where I think when you bring their storage and our network together as well as their servers right we have our technology part of their server solutions as well you get some very compelling solutions all right well congratulations to both of you and also to the team's I'm sure there was a lot of work that went up into this day and it's always a relief to get here so thanks for stopping by and sharing the story thank you absolutely right with you and Jack I'm chef Rick you're watching the Q's the cube conversation from Palo Alto thanks for watching we'll see you next time