>> Announcer: Live from Las Vegas, it's theCUBE covering NetApp Insight 2017. Brought to you by NetApps. >> Welcome back everyone, we are live in Las Vegas this is theCUBE, SiliconANGLE's flagship program where we go out to events and extract the signal from the noise. I'm John Furrier, my co-host Keith Townsend. We're here at NetApp Insight 2017 here at the Mandalay Bay with two great guests, a senior executive, senior NetApp folks, are going to share some insight on what's going on. We have Mark Bregman is the Senior Vice President and CTO thanks for coming on. John Woodall VP of Engineering at Integrated Archive Systems. The first partner of NetApp going back in the day. Welcome to theCUBE thanks for coming on. >> Thank you. >> Thank you. >> So we've seen that movie before, you know every cycle of innovation there's always opportunities. Interesting now we're in a cycle where you can see some new waves out there coming in. And we think we're surfing on some waves now, but the tsunami's coming. Everything from blockchain down to just cloud growth like crazy. You guys have done extremely well. You've seen them before, these transitions. People are busy right now, your customers are super busy. They've got app development going on, DevOps, they've got security unbuckling from IT becoming critical, data governance. What should they know about in this transition that they may miss or they should pay attention to. >> Well, I would say that the thing that is probably the most profound is we've gone through a couple of big transitions, as you mentioned, in the industry as a whole. 20, 30 years ago we would talk to customers and they'd start with infrastructure and they'd talk about servers and storage. 10, 15 years ago they start with applications and they'd talk about their ERP or whatever software. That would decide then the infrastructure. Today they're starting with data and companies are realizing that data is the thing that's going to transform their business. And then based on that data, what software am I going to use and then talk about infrastructure. So the conversation's kind of turned around completely from where it was 20 years ago. >> John, you've been a partner, I see the partner landscape certainly changing. You seeing resellers and VAR's and I think, does the word VAB even exist, value added business? They're actually building their own tech because there's opportunities to be a service provider. Almost like a telco, who would have thought? >> It's crazy, it's crazy. I think I think from our perspective as a longtime partner, we've been successful with NetApp through transitions. We were talking before about the resiliency of NetApp in going through transitions. They've done it again, the keynote today filled with a lot of, what I call, mic-drop moments of yet another level of innovation. But you're right things have flipped almost 180 degrees in the discussion that starting with data, starting with a business outcome, as part of the discussion. It's not about what can I sell, it's about in solving the problem, do I accelerate the pace of my business. Do I open up new ways to monetize in my business. Do I drive efficiencies in my business that translate to the bottom line. As a reseller and as a partner, we have to transition with that because the discussion changes, the skill sets change and it becomes much more of a services play on the front-end and to help through and then becomes managed services, as you know, and that. >> Mark I want to ask your a question. We were joking with the product marketing team on the cloud earlier that you know the slogan should be, I don't know NetApp could do that. It just keeps happening, oh, I didn't know they did that. While that's kind of a history NetApp, but I want to ask something specific. We see it's a success out there in the cloud, you look no further than Amazon Web Services. Now Microsoft's kind of catching up to the rear, Google's there's some other people are trying to kind of get in there. But Amazon's the winner when it comes to the number of announcements you see an event and I'm sure at Reinvent coming up is going to be a tsunami of their bigger announcements, more services so it's a plethora. And so that's an indicator of success. And also the new differentiator, at scale, as you got to keep iterating, you guys have a slew of announcements, so running engineering and being the CEO. What's going on at NetApp? What's the conversation like, you have all these roadmaps, is it just all this innovation, is it part of the plan and just give us some insight into how this all works. >> Well, I think for a long time, maybe for the first 20 years of the company, we were almost like a one product company. The innovations were all in that lane. They were all, you know, make this a better product, make ONTAP better and customers love that because they were growing with us. What's happened is it's kind of exploded in multiple dimensions. So we continue to innovate in our core. But at same time we're having to say, how can we use this capability in a completely different way, in the cloud? How can we help customers manage their data, no matter where it is, not just on our ONTAP systems. We made the acquisition of a little over a year ago, a year and a half ago, of SolidFire, to get into an area of a different approach to managing storage. And it's not sometimes people get it confused and they go that's how you got into flash. Frankly, we're already doing flash units and have flash in all of our product lines. The real reason we did that was to get into this more programmatic, scale out, API driven model of administration of storage. And we're having to do that in so many dimensions. so as we expand those dimensions, Of course we have to expand our innovation. We have to innovate at the given rate in each of threads. >> The old joke in Silicon Valley is you know get lucky once and you get rich. And it's hard, you know, the sophomore jinx whatever you want to call it, repeated successes is a sign of success and certainly as a partner you want to, you don't want to one trick pony at all. Now, I got to ask you, given the NetApp history of those successes, the data fabric is very good positioning I like that position because it's got a lot around it's super important, you think data is the new wave it's going to come bigger than cloud in terms of its impact. What from NetApp, for the customers that are watching and especially new customers, as you take new territory down with data, what is it about the NetApp portfolio, or the architecture the DNA that makes you guys relevant in this data fabric equation? Because you can't just get there overnight because of diseconomies of scale. What is it about NetApp that makes them super relevant? Couple things, one thing, what's the one thing? >> Well, I think I think it becomes back to I think you even said the term, DNA. It's what is it about NetApp, why are we one that's been around for 25 years and continue to make it through these transitions. And I think it's because, first of all, we don't rest on our laurels, we're not caught up in the innovator's dilemma of continuing to just refine what we already have. We'll do that, but we also recognize that there are emerging new customer needs. And our basic intellectual capital can be applied in different ways. So when I talk to our engineers, they don't talk about I build controllers that go into arrays that manage data. They realize that deeper down there's a kind of intellectual capital could go into a piece of software in the cloud. And there's a customer problem that we can go solve. So I think it's about being motivated by solving those customer data problems. >> So culture, some culture. >> It's culture. >> What are the products now, so you have a data, storage, storage stores data. So you don't need rocket science to figure out that you're storing data. >> I'll give you an example, there a lot of competitors in the flash storage business that have come into the market and basically gave up on us because we were late coming to that market. But we came in the market, we accelerated, we passed them, why is that? Partly, we built a good product at the flash storage layer. But more importantly we leveraged all of the storage management which we'd already built over 20 years. And so now we're suddenly out there with a very rock solid flash engine but it's supported by all the other capabilities which make it valuable to our customers. So it's not just, hey, here's a new tool, it's here's a new solution to your problem. And I think that's a big part of our DNA. And our technology side is we've been in data management for 20 years, we just never talked about it that way. >> So John, we had Dave Hitz on earlier, and he said that one of the keys to keeping away from the innovators dilemma has been that NetApp has leaned into the thing that will kill us. I tweeted that out, that's an awesome pull, that they've leaned into the things. As a partner though, that can be a bit scary. Technology is especially enterprise tech is a very stable thing. NetApp has been with ONTAP a very traditional partner even with fads and bringing those innovations to flash. How's that ride been for you guys over the past 25 years. >> It has been consistent, it has been a great partnership, and it continues to be a great partnership because as I look out and hone my portfolio of offerings and partnerships, NetApp stays very high in, that not just because we have a great run rate business, but because NetApp, in their innovation allows me to continue to solve problems with an existing partner, which makes us more efficient. Now, having said that we talked about you mentioned data fabric. That's a completely different discussion from a storage company. At first you think okay, I'm replicating data, I have a transport layer, that's fine. But what are you doing beyond that? I think you begin to see a new NetApp emerging as software defined. An organizing principle in my mind of the data fabric is it gives the customer freedom and flexibility that just buying storage doesn't give you. It gives them the flexibility to deploy in the cloud, next to the cloud, on-prem, as a virtual instance, as an AMI in the cloud, et cetera. So it allows the customer to place data and workloads where and when and how they want that makes sense for their business, not NetApp's business, or my business and so in that we're starting to see now with Anthony Lye's demo today of Cloud Orchestrator. >> Which, by the way, isn't shipping yet, but it's multi-cloud. >> Multi-cloud? >> It's multi-cloud instance. >> Yeah, that right there, and its applications, it's provisioning VM's, it's provisioning. >> If you guys get that to the market fast, it will be the first multi, True multi, orbiting call it real multi-cloud There's a lot of fake multi-cloud out there but that would be a real use case. >> And that's a completely different discussion so you know to kind of plagiarize, you can teach an old storage dog a new trick. So they transformed to meet the emerging needs of a new market, we are have to transform with them. So there's a bit of bumpiness that we're all going to experience as we learn that and do that. >> John, I just want to drill-down on that, I want to get also your both perspectives. What you're really teasing out with the Cloud Orchestrator demo in my mind, the impact of that demo significance is you guys as a storage company, now a data company, are enabling opportunities with the data. That's clearly what's happening, obviously, no debate there. But the impact is to developers. Now the developer dynamic is as these devops guys come in, there's new, there's re-skilling going on. So the biggest challenge of multi-cloud is each cloud has its own way to pipeline data or do things with data. So making that easy, I don't want to have to hire guys to program for each cloud. >> Mark: And they're hard to find. >> It's incredible, it's too hard. Abstracting that away is going to be a boon for the developer market. That's a new market, that's a different thing than NetApp. >> It's a very different market than we've been in before. >> So what are you doing? What's the plan, just continue to enable developers? >> Well, the comment you made earlier, about lean in to the thing that's going to kill you is exactly right, I wouldn't have said it quite like that but I'm not Dave Hitz. So we definitely, when we see a challenge we lean into it. And and that does two things, it's a little bit like, I don't know was it TaeKwonDo where you use the other competitors energy? >> I think it's judo. >> Think it's judo, use the other energy, the power the other opponent to win. And that's kind of what we're doing. I think when you do that it means we have to transform and our partners do, and you're a partner that's been with us long time, you've been through a lot of transitions. >> Yes we have. >> Well judo move is about leverage, and that's about having installed, you guys have that leverage with your customers. >> And the customers are moving as well, so we could try to keep them, hold them back. Or we can move with them and actually accelerate them to where they're going to our benefit, and to our partners benefit and I think that's what Dave was referring to. Well, Mark and John love to have you guys on, love to do a follow-up segment in Palo Alto, our offices are really across the yard from each other, certainly if you guys are in Sunnyvale This is a super important conversation. I'll give you guys the last word, impact to customers for NetApp with the new capabilities with data center innovation modernization, next gen data center, on-premise, true private cloud and power a horse in the cloud with data. All that working together in some cases end to end or in pieces whatever the customers is. What does it mean to the customer this new. >> I'll steal a line from our marketing teams and what it really means is it's going to enable customers to change the world with data. Transform their business, create new opportunities. >> It's a new wave in the economy. It's going to be disruptive and tumultuous for some. We have an opportunity to go into a customer and to help them find new ways, with their data, because the two key assets of company now is people and then data. So the people are there taking their data, allowing them to find new opportunities to go to market faster. NetApp's in a unique position. >> It reminds me of value creation, I mean a lot of stuff with blockchain you see the indicators, almost the Web1.0 again. You see in the new shift in architecture happening upside down it's almost reverse. >> The developer model's right. I mean you talk about Amazon, I think from 2008 until 2014 or 15 they introduced about three thousand new services on their platform. I don't see an average IT organization doing that. >> I think that rates gone up now. >> It's on an exponential growth there. >> I think we're starting to see the swim lanes, if you will, I'm calling them native clouds because they're so native. But they're also powering a new ecosystem and part of it, I wish we had more time to talk about the partner equation. There a lot of musical chairs going on in the partner ecosystem. You've been with NetApp from the beginning, congratulations. Congratulations on all the success on the platform and the product innovation. It's theCUBE bringing you the innovation and the data through our data fabric called theCUBE. We'll be back with more live coverage after this short break. >> Announcer: Coming off barrier breakers, status quo smashers, world.

>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle in 2000 >>nine. Hal Varian, Google's chief economist, said that statisticians would be the sexiest job in the coming decade. The modern big data movement >>really >>took off later in the following year. After the Second Hadoop World, which was hosted by Claudette Cloudera in New York City. Jeff Ham Abakar famously declared to me and John further in the Cube that the best minds of his generation, we're trying to figure out how to get people to click on ads. And he said that sucks. The industry was abuzz with the realization that data was the new competitive weapon. Hadoop was heralded as the new data management paradigm. Now, what actually transpired Over the next 10 years on Lee, a small handful of companies could really master the complexities of big data and attract the data science talent really necessary to realize massive returns as well. Back then, Cloud was in the early stages of its adoption. When you think about it at the beginning of the last decade and as the years passed, Maurin Mawr data got moved to the cloud and the number of data sources absolutely exploded. Experimentation accelerated, as did the pace of change. Complexity just overwhelmed big data infrastructures and data teams, leading to a continuous stream of incremental technical improvements designed to try and keep pace things like data Lakes, data hubs, new open source projects, new tools which piled on even Mawr complexity. And as we reported, we believe what's needed is a comm pleat bit flip and how we approach data architectures. Our next guest is Jean Marc de Connie, who is the director of emerging technologies That thought works. John Mark is a software engineer, architect, thought leader and adviser to some of the world's most prominent enterprises. She's, in my view, one of the foremost advocates for rethinking and changing the way we create and manage data architectures. Favoring a decentralized over monolithic structure and elevating domain knowledge is a primary criterion. And how we organize so called big data teams and platforms. Chamakh. Welcome to the Cube. It's a pleasure to have you on the program. >>Hi, David. This wonderful to be here. >>Well, okay, so >>you're >>pretty outspoken about the need for a paradigm shift in how we manage our data and our platforms that scale. Why do you feel we need such a radical change? What's your thoughts there? >>Well, I think if you just look back over the last decades you gave us, you know, a summary of what happened since 2000 and 10. But if even if we go before then what we have done over the last few decades is basically repeating and, as you mentioned, incrementally improving how we've managed data based on a certain assumptions around. As you mentioned, centralization data has to be in one place so we can get value from it. But if you look at the parallel movement off our industry in general since the birth of Internet, we are actually moving towards decentralization. If we think today, like if this move data side, if he said the only way Web would work the only way we get access to you know various applications on the Web pages is to centralize it. We would laugh at that idea, but for some reason we don't. We don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, you know, embrace the distribution of sources of data that they're not just within one part of organization. They're not just within even bounds of organization there beyond the bounds of organization. And then look back and say Okay, if that's the trend off our industry in general, Um, given the fabric of computation and data that we put in, you know globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we, you know, put a technology in place, um, to to look at it from a decentralized angle. >>Okay, so let's let's unpack that a little bit. I mean, you've spoken about and written that today's big architecture and you basically just mentioned that it's flawed, So I wanna bring up. I love your diagrams of a simple diagram, guys, if you could bring up ah, figure one. So on the left here we're adjusting data from the operational systems and other enterprise data sets and, of course, external data. We cleanse it, you know, you've gotta do the do the quality thing and then serve them up to the business. So So what's wrong with that picture that we just described and give granted? It's a simplified form. >>Yeah, quite a few things. So, yeah, I would flip the question may be back to you or the audience if we said that. You know, there are so many sources off the data on the Actually, the data comes from systems and from teams that are very diverse in terms off domains. Right? Domain. If if you just think about, I don't know retail, Uh, the the E Commerce versus Order Management versus customer This is a very diverse domains. The data comes from many different diverse domains. And then we expect to put them under the control off a centralized team, a centralized system. And I know that centralization. Probably if you zoom out, it's centralized. If you zoom in it z compartmentalized based on functions that we can talk about that and we assume that the centralized model will be served, you know, getting that data, making sense of it, cleansing and transforming it then to satisfy in need of very diverse set of consumers without really understanding the domains, because the teams responsible for it or not close to the source of the data. So there is a bit of it, um, cognitive gap and domain understanding Gap, um, you know, without really understanding of how the data is going to be used, I've talked to numerous. When we came to this, I came up with the idea. I talked to a lot of data teams globally just to see, you know, what are the pain points? How are they doing it? And one thing that was evident in all of those conversations that they actually didn't know after they built these pipelines and put the data in whether the data warehouse tables or like, they didn't know how the data was being used. But yet the responsible for making the data available for these diverse set of these cases, So s centralized system. A monolithic system often is a bottleneck. So what you find is, a lot of the teams are struggling with satisfying the needs of the consumers, the struggling with really understanding the data. The domain knowledge is lost there is a los off understanding and kind of in that in that transformation. Often, you know, we end up training machine learning models on data that is not really representative off the reality off the business. And then we put them to production and they don't work because the semantic and the same tax off the data gets lost within that translation. So we're struggling with finding people thio, you know, to manage a centralized system because there's still the technology is fairly, in my opinion, fairly low level and exposes the users of those technologies. I said, Let's say warehouse a lot off, you know, complexity. So in summary, I think it's a bottleneck is not gonna, you know, satisfy the pace of change, of pace, of innovation and the pace of, you know, availability of sources. Um, it's disconnected and fragmented, even though the centralizes disconnected and fragmented from where the data comes from and where the data gets used on is managed by, you know, a team off hyper specialized people that you know, they're struggling to understand the actual value of the data, the actual format of the data, so it's not gonna get us where our aspirations and ambitions need to be. >>Yes. So the big data platform is essentially I think you call it, uh, context agnostic. And so is data becomes, you know, more important, our lives. You've got all these new data sources, you know, injected into the system. Experimentation as we said it with the cloud becomes much, much easier. So one of the blockers that you've started, you just mentioned it is you've got these hyper specialized roles the data engineer, the quality engineer, data scientists and and the It's illusory. I mean, it's like an illusion. These guys air, they seemingly they're independent and in scale independently. But I think you've made the point that in fact, they can't that a change in the data source has an effect across the entire data lifecycle entire data pipeline. So maybe you could maybe you could add some color to why that's problematic for some of the organizations that you work with and maybe give some examples. >>Yeah, absolutely so in fact, that initially the hypothesis around that image came from a Siris of requests that we received from our both large scale and progressive clients and progressive in terms of their investment in data architectures. So this is where clients that they were there were larger scale. They had divers and reached out of domains. Some of them were big technology tech companies. Some of them were retail companies, big health care companies. So they had that diversity off the data and the number off. You know, the sources of the domains they had invested for quite a few years in, you know, generations. If they had multi generations of proprietary data warehouses on print that they were moving to cloud, they had moved to the barriers, you know, revisions of the Hadoop clusters and they were moving to the cloud. And they the challenges that they were facing were simply there were not like, if I want to just, like, you know, simplifying in one phrase, they were not getting value from the data that they were collecting. There were continuously struggling Thio shift the culture because there was so much friction between all of these three phases of both consumption of the data and transformation and making it available consumption from sources and then providing it and serving it to the consumer. So that whole process was full of friction. Everybody was unhappy. So its bottom line is that you're collecting all this data. There is delay. There is lack of trust in the data itself because the data is not representative of the reality has gone through a transformation. But people that didn't understand really what the data was got delayed on bond. So there is no trust. It's hard to get to the data. It's hard to create. Ultimately, it's hard to create value from the data, and people are working really hard and under a lot of pressure. But it's still, you know, struggling. So we often you know, our solutions like we are. You know, Technologies will often pointed to technology. So we go. Okay, This this version of you know, some some proprietary data warehouse we're using is not the right thing. We should go to the cloud, and that certainly will solve our problems. Right? Or warehouse wasn't a good one. Let's make a deal Lake version. So instead of you know, extracting and then transforming and loading into the little bits. And that transformation is that, you know, heavy process, because you fundamentally made an assumption using warehouses that if I transform this data into this multi dimensional, perfectly designed schema that then everybody can run whatever choir they want that's gonna solve. You know everybody's problem, but in reality it doesn't because you you are delayed and there is no universal model that serves everybody's need. Everybody that needs the divers data scientists necessarily don't don't like the perfectly modeled data. They're looking for both signals and the noise. So then, you know, we've We've just gone from, uh, et elles to let's say now to Lake, which is okay, let's move the transformation to the to the last mile. Let's just get load the data into, uh into the object stores into semi structured files and get the data. Scientists use it, but they're still struggling because the problems that we mentioned eso then with the solution. What is the solution? Well, next generation data platform, let's put it on the cloud, and we sell clients that actually had gone through, you know, a year or multiple years of migration to the cloud. But with it was great. 18 months I've seen, you know, nine months migrations of the warehouse versus two year migrations of the various data sources to the clubhouse. But ultimately, the result is the same on satisfy frustrated data users, data providers, um, you know, with lack of ability to innovate quickly on relevant data and have have have an experience that they deserve toe have have a delightful experience off discovering and exploring data that they trust. And all of that was still a missed so something something else more fundamentally needed to change than just the technology. >>So then the linchpin to your scenario is this notion of context and you you pointed out you made the other observation that look, we've made our operational systems context aware. But our data platforms are not on bond like CRM system sales guys very comfortable with what's in the CRM system. They own the data. So let's talk about the answer that you and your colleagues are proposing. You're essentially flipping the architecture whereby those domain knowledge workers, the builders, if you will, of data products or data services there now, first class citizens in the data flow and they're injecting by design domain knowledge into the system. So So I wanna put up another one of your charts. Guys, bring up the figure to their, um it talks about, you know, convergence. You showed data distributed domain, dream and architecture. Er this self serve platform design and this notion of product thinking. So maybe you could explain why this approach is is so desirable, in your view, >>sure. The motivation and inspiration for the approach came from studying what has happened over the last few decades in operational systems. We had a very similar problem prior to micro services with monolithic systems, monolithic systems where you know the bottleneck. Um, the changes we needed to make was always, you know, our fellow Noto, how the architecture was centralized and we found a nice nation. I'm not saying this is the perfect way of decoupling a monolith, but it's a way that currently where we are in our journey to become data driven, um is a nice place to be, um, which is distribution or decomposition off your system as well as organization. I think when we whenever we talk about systems, we've got to talk about people and teams that's responsible for managing those systems. So the decomposition off the systems and the teams on the data around domains because that's how today we are decoupling our business, right? We're decoupling our businesses around domains, and that's a that's a good thing and that What does that do really for us? What it does? Is it localizes change to the bounded context of fact business. It creates clear boundary and interfaces and contracts between the rest of the universe of the organization on that particular team, so removes the friction that often we have for both managing the change and both serving data or capability. So it's the first principle of data meshes. Let's decouple this world off analytical data the same to mirror the same way we have to couple their systems and teams and business why data is any different. And the moment you do that, So you, the moment you bring the ownership to people who understands the data best, then you get questions that well, how is that any different from silence that's connected databases that we have today and nobody can get to the data? So then the rest of the principles is really to address all of the challenges that comes with this first principle of decomposition around domain Context on the second principle is well, we have to expect a certain level off quality and accountability and responsibility for the teams that provide the data. So let's bring product thinking and treating data as a product to the data that these teams now, um share and let's put accountability around. And we need a new set of incentives and metrics for domain teams to share the data. We need to have a new set off kind of quality metrics that define what it means for the data to be a product. And we can go through that conversation perhaps later eso then the second principle is okay. The teams now that are responsible, the domain teams responsible for the analytical data need to provide that data with a certain level of quality and assurance. Let's call that a product and bring products thinking to that. And then the next question you get asked off by C. E. O s or city or the people who build the infrastructure and, you know, spend the money. They said, Well, it's actually quite complex to manage big data, and now we're We want everybody, every independent team to manage the full stack of, you know, storage and computation and pipelines and, you know, access, control and all of that. And that's well, we have solved that problem in operational world. And that requires really a new level of platform thinking toe provide infrastructure and tooling to the domain teams to now be able to manage and serve their big data. And that I think that requires reimagining the world of our tooling and technology. But for now, let's just assume that we need a new level of abstraction to hide away ton of complexity that unnecessarily people get exposed to and that that's the third principle of creating Selves of infrastructure, um, to allow autonomous teams to build their domains. But then the last pillar, the last you know, fundamental pillar is okay. Once you distributed problem into a smaller problems that you found yourself with another set of problems, which is how I'm gonna connect this data, how I'm gonna you know, that the insights happens and emerges from the interconnection of the data domains right? It does not necessarily locked into one domain. So the concerns around interoperability and standardization and getting value as a result of composition and interconnection of these domains requires a new approach to governance. And we have to think about governance very differently based on a Federated model and based on a computational model. Like once we have this powerful self serve platform, we can computational e automate a lot of governance decisions. Um, that security decisions and policy decisions that applies to you know, this fabric of mesh not just a single domain or not in a centralized. Also, really. As you mentioned that the most important component of the emissions distribution of ownership and distribution of architecture and data the rest of them is to solve all the problems that come with that. >>So very powerful guys. We actually have a picture of what Jamaat just described. Bring up, bring up figure three, if you would tell me it. Essentially, you're advocating for the pushing of the pipeline and all its various functions into the lines of business and abstracting that complexity of the underlying infrastructure, which you kind of show here in this figure, data infrastructure is a platform down below. And you know what I love about this Jama is it to me, it underscores the data is not the new oil because I could put oil in my car I can put in my house, but I can't put the same court in both places. But I think you call it polyglot data, which is really different forms, batch or whatever. But the same data data doesn't follow the laws of scarcity. I can use the same data for many, many uses, and that's what this sort of graphic shows. And then you brought in the really important, you know, sticking problem, which is that you know the governance which is now not a command and control. It's it's Federated governance. So maybe you could add some thoughts on that. >>Sure, absolutely. It's one of those I think I keep referring to data much as a paradigm shift. And it's not just to make it sound ground and, you know, like, kind of ground and exciting or in court. And it's really because I want to point out, we need to question every moment when we make a decision around how we're going to design security or governance or modeling off the data, we need to reflect and go back and say, um, I applying some of my cognitive biases around how I have worked for the last 40 years, I have seen it work. Or do I do I really need to question. And we do need to question the way we have applied governance. I think at the end of the day, the rule of the data governance and objective remains the same. I mean, we all want quality data accessible to a diverse set of users. And these users now have different personas, like David, Personal data, analyst data, scientists, data application, Um, you know, user, very diverse personal. So at the end of the day, we want quality data accessible to them, um, trustworthy in in an easy consumable way. Um, however, how we get there looks very different in as you mentioned that the governance model in the old world has been very commander control, very centralized. Um, you know, they were responsible for quality. They were responsible for certification off the data, you know, applying making sure the data complies. But also such regulations Make sure you know, data gets discovered and made available in the world of the data mesh. Really. The job of the data governance as a function becomes finding that equilibrium between what decisions need to be um, you know, made and enforced globally. And what decisions need to be made locally so that we can have an interoperable measure. If data sets that can move fast and can change fast like it's really about instead of hardest, you know, kind of putting the putting those systems in a straitjacket of being constant and don't change, embrace, change and continuous change of landscape because that's that's just the reality we can't escape. So the role of governance really the governance model called Federated and Computational. And by that I mean, um, every domain needs to have a representative in the governance team. So the role of the data or domain data product owner who really were understand the data that domain really well but also wears that hacks of a product owner. It is an important role that had has to have a representation in the governance. So it's a federation off domains coming together, plus the SMEs and people have, you know, subject matter. Experts who understands the regulations in that environmental understands the data security concerns, but instead off trying to enforce and do this as a central team. They make decisions as what need to be standardized, what need to be enforced. And let's push that into that computational E and in an automated fashion into the into the camp platform itself. For example, instead of trying to do that, you know, be part of the data quality pipeline and inject ourselves as people in that process, let's actually, as a group, define what constitutes quality, like, how do we measure quality? And then let's automate that and let Z codify that into the platform so that every native products will have a C I City pipeline on as part of that pipeline. Those quality metrics gets validated and every day to product needs to publish those SLOC or service level objectives. So you know, whatever we choose as a measure of quality, maybe it's the, you know, the integrity of the data, the delay in the data, the liveliness of it, whatever the are the decisions that you're making, let's codify that. So it's, um, it's really, um, the role of the governance. The objectives of the governance team tried to satisfies the same, but how they do it. It is very, very different. I wrote a new article recently trying to explain the logical architecture that would emerge from applying these principles. And I put a kind of light table to compare and contrast the roll off the You know how we do governance today versus how we will do it differently to just give people a flavor of what does it mean to embrace the centralization? And what does it mean to embrace change and continuous change? Eso hopefully that that that could be helpful. >>Yes, very so many questions I haven't but the point you make it to data quality. Sometimes I feel like quality is the end game. Where is the end game? Should be how fast you could go from idea to monetization with the data service. What happens again? You sort of address this, but what happens to the underlying infrastructure? I mean, spinning a PC to S and S three buckets and my pie torches and tensor flows. And where does that that lives in the business? And who's responsible for that? >>Yeah, that's I'm glad you're asking this question. Maybe because, um, I truly believe we need to re imagine that world. I think there are many pieces that we can use Aziz utilities on foundational pieces, but I but I can see for myself a 5 to 7 year roadmap of building this new tooling. I think, in terms of the ownership, the question around ownership, if that would remains with the platform team, but and perhaps the domain agnostic, technology focused team right that there are providing instead of products themselves. And but the products are the users off those products are data product developers, right? Data domain teams that now have really high expectations in terms of low friction in terms of lead time to create a new data product. Eso We need a new set off tooling, and I think with the language needs to shift from, You know, I need a storage buckets. So I need a storage account. So I need a cluster to run my, you know, spark jobs, too. Here's the declaration of my data products. This is where the data for it will come from. This is the data that I want to serve. These are the policies that I need toe apply in terms of perhaps encryption or access control. Um, go make it happen. Platform, go provision, Everything that I mean so that as a data product developer. All I can focus on is the data itself, representation of semantic and representation of the syntax. And make sure that data meets the quality that I have that I have to assure and it's available. The rest of provisioning of everything that sits underneath will have to get taken care of by the platform. And that's what I mean by requires a re imagination and in fact, Andi, there will be a data platform team, the data platform teams that we set up for our clients. In fact, themselves have a favorite of complexity. Internally, they divide into multiple teams multiple planes, eso there would be a plane, as in a group of capabilities that satisfied that data product developer experience, there would be a set of capabilities that deal with those need a greatly underlying utilities. I call it at this point, utilities, because to me that the level of abstraction of the platform is to go higher than where it is. So what we call platform today are a set of utilities will be continuing to using will be continuing to using object storage, will continue using relation of databases and so on so there will be a plane and a group of people responsible for that. There will be a group of people responsible for capabilities that you know enable the mesh level functionality, for example, be able to correlate and connects. And query data from multiple knows. That's a measure level capability to be able to discover and explore the measure data products as a measure of capability. So it would be set of teams as part of platforms with a strong again platform product thinking embedded and product ownership embedded into that. To satisfy the experience of this now business oriented domain data team teams s way have a lot of work to do. >>I could go on. Unfortunately, we're out of time. But I guess my first I want to tell people there's two pieces that you put out so far. One is, uh, how to move beyond a monolithic data lake to a distributed data mesh. You guys should read that in a data mesh principles and logical architectures kind of part two. I guess my last question in the very limited time we have is our organization is ready for this. >>E think the desire is there I've bean overwhelmed with number off large and medium and small and private and public governments and federal, you know, organizations that reached out to us globally. I mean, it's not This is this is a global movement and I'm humbled by the response of the industry. I think they're the desire is there. The pains are really people acknowledge that something needs to change. Here s so that's the first step. I think that awareness isa spreading organizations. They're more and more becoming aware. In fact, many technology providers are reach out to us asking what you know, what shall we do? Because our clients are asking us, You know, people are already asking We need the data vision. We need the tooling to support. It s oh, that awareness is there In terms of the first step of being ready, However, the ingredients of a successful transformation requires top down and bottom up support. So it requires, you know, support from Chief Data Analytics officers or above the most successful clients that we have with data. Make sure the ones that you know the CEOs have made a statement that, you know, we want to change the experience of every single customer using data and we're going to do, we're going to commit to this. So the investment and support, you know, exists from top to all layers. The engineers are excited that maybe perhaps the traditional data teams are open to change. So there are a lot of ingredients. Substance to transformation is to come together. Um, are we really ready for it? I think I think the pioneers, perhaps the innovators. If you think about that innovation, careful. My doctors, probably pioneers and innovators and leaders. Doctors are making making move towards it. And hopefully, as the technology becomes more available, organizations that are less or in, you know, engineering oriented, they don't have the capability in house today, but they can buy it. They would come next. Maybe those are not the ones who aren't quite ready for it because the technology is not readily available. Requires, you know, internal investment today. >>I think you're right on. I think the leaders are gonna lead in hard, and they're gonna show us the path over the next several years. And I think the the end of this decade is gonna be defined a lot differently than the beginning. Jammeh. Thanks so much for coming in. The Cuban. Participate in the >>program. Pleasure head. >>Alright, Keep it right. Everybody went back right after this short break.

>> Live, from Las Vegas, it's theCUBE. Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome back. This is theCUBE's coverage of VMworld 2018 here in Las Vegas. I'm Stu Miniman joined by my two guest hosts that have spent a bunch of time with us this week. John Mark Troyer and Justin Warren. Thank you, gentlemen for joining us for the wrap. >> Thanks for having us. >> Thanks for having us. >> We get to have a lot of fun. We get to hang out with community people, geek out on a lot of stuff. This is also a really good checkpoint for a lot of the IT industry. VMware, 800-pound gorilla in the data center. I put out one tweet that was like the 800-pound gorilla in the data center or the 800-pound gorilla in the cloud. The partnerships matured quite a bit, in my mind, for the last year. That was one of the big things that I've seen. RDS on-premises is definitely the thing that sticks out to me the most. John, let's start with you as to, checkpoint from last year. What impressed you? What are they making progress with? Let's start there. >> I think the RDS announcement was maybe even undersold here. We'll see in the coming months what actually happens and if everything works the way it's supposed to work. I think a lot of people who are putting chips down on various outcomes and scenarios in cloud world did not cover that one space in the roulette wheel. Cause that's actually pretty interesting. Stu, I kind of see this as a year of promises kept. Some promises that were made in years past are starting to come out. This multi-cloud world seems more real. VMware's relationships with various clouds and the hints that were thrown are there's more to come. It seems real. The cloud starting to come back on-prem. Both EBS on-prem and now Project Dimension with VMware being a service provider. I've talked to a number of vendors and you and I, Stu. Some are here on theCUBE. People starting to do more managed services from the cloud back into your data center. I see the multi-cloud world working and then this kind of blurring of on-prem and cloud even more. That's kind of what I'm seeing. >> Yeah, I've got to agree. It's that idea that cloud is a state of mind. It's not a location. >> We say it's an operating model at it's core, right? >> Right, yeah, and I think we're seeing a lot of those ideas come to fruition now that you can operate like a cloud on-site. It's how you run things, it's not where exactly you put it. With the multi-cloud world, like you said, we can have, some of it can be on-site, some of it can be in one cloud, another cloud, lots of different clouds. Some of it will be at the edge. We're seeing a lot of growth in edge computing, which is essentially just another way of doing on-site. Being able to use the same tools, and that, for me, is the idea around the RDS announcement. It's the same thing that you're used to in public cloud. Now I can do that on-site. We're seeing a real cross-pollination. You can take VMware and run that in cloud. You can take things from the cloud and now run it back on site. It's pretty exciting. >> This is awesome. We have an easy button. Customers just push a button. Any data, anywhere, moves all over the place. Laws of physics, throw them out. Come on, guys. I need some critical analysis here. The trope that I would have, always, when I became an analyst an eight years ago was like well, if it wasn't for management and security we would have this all sorted out. The multi-cloud world is made progress, but when I still look at it. RDS, super exciting. The thing that's most exciting about it? That's on-premises, it's doesn't have connection to Amazon, but I'm doing cool things with the exact same kind of bits there so I can do it here or there. Doesn't mean, necessarily here and there, or spread between there, because petabytes of data don't just float across the ether. We're still using things like the AWS Snowballs when we have to move a lot of data. Yes, it's matured, but when I look at the management of multi-cloud and how simple, there was a great comment from a company that's been around for a couple of decades on theCUBE and he said look, the new companies all say we're going to make this super easy. It's like well, because you don't have the trusted brand to set beside, simple would be nice but cloud isn't simple. Multi-cloud sure isn't simple. >> There was, probably, a surfeit of single panes of glass here at the show. Any app, any cloud, any whatever. Single pane of glass. We'll blueprint it, we'll manage it, we'll do it. That does seem like that probably isn't that real world. >> Multiple single panes of glass. >> Please, Justin, give me a touchpoint. When you talk to an administrator, how do they spell single pane of glass? >> Oh yes, P-A-I-N, yes, a single glass of pain. That's generally what it is. I think that the manageability and the operational side of things, that is where there's a lot more development required. Cloud is, yes it's a state of mind. It's a very different way of operating and a lot of the tools, particularly in the VMware community, a lot of what people are used to here is very much point and click. It's not really as automated as it would be in, say, developer land. I spend a lot of time with developers and a lot of what they're used to is all programmatic, it's driven from the API. We're seeing movement with things like PowerShell and VMware administrators are getting more comfortable with the idea of scripting and so on. But they're not programmers. They still need GUI tools. They still need things that are able to do point and click. Some things are better in that environment. I think we still have a long way to go with things around automation. The other thing that still has a long way to go, I think, is security. Security particularly around the networking of how you inter-connect with all of these things and do so securely at scale. There is a lot of invasion and work that's required to actually make that happen. >> Absolutely. John, do you have some comment there? >> I was going to say I think you're right. Especially on all those points. The community booth back here behind us this year had a VMware code section, which was jam-packed the whole time. For the first time. VMware's been trying to speak to developers for 10 years and not quite connecting. Now, these weren't developers back there, these were admins, and they're not going to ever be programmers, but they're going to start to learn more programmatic paradigms, automation, things like that. It was super popular this year. >> Luckily, we don't actually need programmers anymore, John, cause it's coding, which means you're really just coping, pasting, and modifying things and everything. Heck, I've even interviewed marketing people that are like oh, server-less, I can build with that stuff. Super easy. I don't think we need everybody to learn to even code, as it were. We bridged that gap. It's matured, it's become easier. They pulled over some of the, it was the EMC code team. It's half that team over there. They had some good gamification. >> Stu, I am an optimist and I think the glass is half full or 40% full at least. We've done some CUBE stuff, theCUBE's been all over the world here this spring, all through 2018. I've done a couple shows with you. The difference that I saw this year was that the use cases were real and the time to value was real. People are implementing cloud projects, multi-cloud projects, and they're getting to a good milestone within weeks or months. Admittedly, these are big, multi-national companies, so it's really at the top level where they have the army of people to do it, but sometimes these projects were very small and they were real. They weren't just marketing hokum up on stage. Of course, they're not the full enterprise in a couple of weeks, but that's the difference this year, I see, Stu. I'm 40% full. >> Absolutely, I'd say look. Energy level was up. Two years ago it kind of hit a nadir. It was doom and gloom. We were all over at the eye candy bar saluting the great run that VMware had and wondering who the next CEO was been. Now, energy level's back up. Investment in the ecosystem, oh my gosh. I don't think I've seen this many parties ever at a VMworld. We got to talk about something other than cloud so give me your non-cloud takeaways from the show. Areas that people should learn more about, things you saw in the ecosystem or from VMware or the community. >> I think that's one of the things I've noticed here at the show. Wandering around the show floor, unlike some of the other shows where it's we will have a storage show or we'll have a backup show. There's a lot more balance this year. There seems to be a good mix of some of everything. I think that it shows that in order to run a successful IT shop, you actually need to have a balance of, you need some backup, you need some data recovery, you need to have some software, you need some monitoring, you need to have security options. Go and have a look at all of the different vendors that are at a show like this to be able to make sure you have a portfolio approach to how you run things. >> Totally. I remember there were a couple of years, four or five years ago, it was like oh, it's VM storage world. >> Yeah. >> OK, yeah. John? >> There is a lot of storage here, but the storage is all connected to the cloud now. I think if you look at some of the big booths and some of the start-ups who have gotten funding recently. Large rounds. Cohesity, Datrium, Rubrik, folks like that, they're delivering on promises made in earlier years. Not particularly like oh wow, I never thought of, but this was the vision that we laid out and now we're delivering it this year. Big rounds of funding, big customer movement, connection to the cloud and solid, interesting DR as a service and data, as opposed to storage, ideas. I thought that was one of the more interesting aisles this year over there in the booths. >> To riff on what you said about developers and the bridge to the code idea, we see Puppet is here at the show, HashiCorp is here for the first time. >> Docker's there, of course. >> Docker's here. >> C & CF had a booth. >> Yep, C & CF had a booth. These are people that you wouldn't have expected to see at a VMware show in years past. >> One thing that struck me is companies with a mission for good. Pat Gelsinger kind of sets the bar. Talked about it in his keynote. Do better, do good, sets that example. He climbed Mt. Kilimanjaro for charity earlier this year. They had Malala up on stage with Sanjay Poonen. I did a couple of interviews here which were inspiring. Mission-driven companies and great to see the infrastructure in software companies being like hey, we're enabling and helping it. That was one to me. Takeaways from the community? Other things as we get to our wrap? >> I do wonder about that point. Just to add a little, slightly critical note on that. I think that there has been a bit of a tech lash, a bit of a backlash against tech companies. I wonder whether, I would like to see more from tech companies to show that this is real. That that social conscience is a real thing and it isn't just a bit of marketing that they've spray painted on to the front of the company. The fact that we had Malala here giving a keynote indicates that there is a commitment to it. I would want to see that carry through for the next couple of years, at least, to show that that sort of thing is real. And certainly, from the rest of the ecosystem, I expect that we're going to see a lot more. >> Diversity in the community, absolutely. I do realize we have three white guys of a certain age sitting here. We try to add diversity. I had my first European host on the program. Lisa's been on a lot this week. We're building out our bench, we're looking to add diversity. John, yeah, the community. >> Community, again, yeah, community was good this year. A lot of old faces have stayed around, which is really interesting but also people have left and come back. You saw people who have gone into the AWS and Microsoft ecosystems coming back in here. Again, some of those old faces. Also, new faces. Global diversity from the southern hemisphere and from other countries that you wouldn't expect are here today. That was super interesting. I do see a lot of energy, a lot of excitement about their careers going forward. I do see that tech needs to be, there was some symbolic do-good things here. But I mean, Justin is a little bit involved in your own home country about how the government has the power with technology to do good or bad. I think that may be an emerging thing that we see here now as you get a layer down of not only charity work but the impacts of technology. I bet we'll end up talking about that next year, Stu. >> Guys, we could start talking for a lot longer. The good news is I know how to get in touch with you. For our audience, by the way, you can hit us all up on Twitter, through various social channels. Jtroyer, jpwarren, I'm of course @stu. That's just S-T-U. Blue Cow is on Instagram. Follow the adventures of Blue Cow, showing where Justin's going all over the place. Thanks so much for joining us. Great coverage here. This community's where I get a lot of my guest hosts and still, it's like homecoming coming to this place. Thank you for watching theCUBE. (electronic tones)

>> Live, from Las Vegas, it's theCUBE. Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome back. This is theCUBE's coverage of VMworld 2018 here in Las Vegas. I'm Stu Miniman joined by my two guest hosts that have spent a bunch of time with us this week. John Mark Troyer and Justin Warren. Thank you, gentlemen for joining us for the wrap. >> Thanks for having us. >> Thanks for having us. >> We get to have a lot of fun. We get to hang out with community people, geek out on a lot of stuff. This is also a really good checkpoint for a lot of the IT industry. VMware, 800-pound gorilla in the data center. I put out one tweet that was like the 800-pound gorilla in the data center or the 800-pound gorilla in the cloud. The partnerships matured quite a bit, in my mind, for the last year. That was one of the big things that I've seen. RDS on-premises is definitely the thing that sticks out to me the most. John, let's start with you as to, checkpoint from last year. What impressed you? What are they making progress with? Let's start there. >> I think the RDS announcement was maybe even undersold here. We'll see in the coming months what actually happens and if everything works the way it's supposed to work. I think a lot of people who are putting chips down on various outcomes and scenarios in cloud world did not cover that one space in the roulette wheel. Cause that's actually pretty interesting. Stu, I kind of see this as a year of promises kept. Some promises that were made in years past are starting to come out. This multi-cloud world seems more real. VMware's relationships with various clouds and the hints that were thrown are there's more to come. It seems real. The cloud starting to come back on-prem. Both EBS on-prem and now Project Dimension with VMware being a service provider. I've talked to a number of vendors and you and I, Stu. Some are here on theCUBE. People starting to do more managed services from the cloud back into your data center. I see the multi-cloud world working and then this kind of blurring of on-prem and cloud even more. That's kind of what I'm seeing. >> Yeah, I've got to agree. It's that idea that cloud is a state of mind. It's not a location. >> We say it's an operating model at it's core, right? >> Right, yeah, and I think we're seeing a lot of those ideas come to fruition now that you can operate like a cloud on-site. It's how you run things, it's not where exactly you put it. With the multi-cloud world, like you said, we can have, some of it can be on-site, some of it can be in one cloud, another cloud, lots of different clouds. Some of it will be at the edge. We're seeing a lot of growth in edge computing, which is essentially just another way of doing on-site. Being able to use the same tools, and that, for me, is the idea around the RDS announcement. It's the same thing that you're used to in public cloud. Now I can do that on-site. We're seeing a real cross-pollination. You can take VMware and run that in cloud. You can take things from the cloud and now run it back on site. It's pretty exciting. >> This is awesome. We have an easy button. Customers just push a button. Any data, anywhere, moves all over the place. Laws of physics, throw them out. Come on, guys. I need some critical analysis here. The trope that I would have, always, when I became an analyst an eight years ago was like well, if it wasn't for management and security we would have this all sorted out. The multi-cloud world is made progress, but when I still look at it. RDS, super exciting. The thing that's most exciting about it? That's on-premises, it's doesn't have connection to Amazon, but I'm doing cool things with the exact same kind of bits there so I can do it here or there. Doesn't mean, necessarily here and there, or spread between there, because petabytes of data don't just float across the ether. We're still using things like the AWS Snowballs when we have to move a lot of data. Yes, it's matured, but when I look at the management of multi-cloud and how simple, there was a great comment from a company that's been around for a couple of decades on theCUBE and he said look, the new companies all say we're going to make this super easy. It's like well, because you don't have the trusted brand to set beside, simple would be nice but cloud isn't simple. Multi-cloud sure isn't simple. >> There was, probably, a surfeit of single panes of glass here at the show. Any app, any cloud, any whatever. Single pane of glass. We'll blueprint it, we'll manage it, we'll do it. That does seem like that probably isn't that real world. >> Multiple single panes of glass. >> Please, Justin, give me a touchpoint. When you talk to an administrator, how do they spell single pane of glass? >> Oh yes, P-A-I-N, yes, a single glass of pain. That's generally what it is. I think that the manageability and the operational side of things, that is where there's a lot more development required. Cloud is, yes it's a state of mind. It's a very different way of operating and a lot of the tools, particularly in the VMware community, a lot of what people are used to here is very much point and click. It's not really as automated as it would be in, say, developer land. I spend a lot of time with developers and a lot of what they're used to is all programmatic, it's driven from the API. We're seeing movement with things like PowerShell and VMware administrators are getting more comfortable with the idea of scripting and so on. But they're not programmers. They still need GUI tools. They still need things that are able to do point and click. Some things are better in that environment. I think we still have a long way to go with things around automation. The other thing that still has a long way to go, I think, is security. Security particularly around the networking of how you inter-connect with all of these things and do so securely at scale. There is a lot of invasion and work that's required to actually make that happen. >> Absolutely. John, do you have some comment there? >> I was going to say I think you're right. Especially on all those points. The community booth back here behind us this year had a VMware code section, which was jam-packed the whole time. For the first time. VMware's been trying to speak to developers for 10 years and not quite connecting. Now, these weren't developers back there, these were admins, and they're not going to ever be programmers, but they're going to start to learn more programmatic paradigms, automation, things like that. It was super popular this year. >> Luckily, we don't actually need programmers anymore, John, cause it's coding, which means you're really just coping, pasting, and modifying things and everything. Heck, I've even interviewed marketing people that are like oh, server-less, I can build with that stuff. Super easy. I don't think we need everybody to learn to even code, as it were. We bridged that gap. It's matured, it's become easier. They pulled over some of the, it was the EMC code team. It's half that team over there. They had some good gamification. >> Stu, I am an optimist and I think the glass is half full or 40% full at least. We've done some CUBE stuff, theCUBE's been all over the world here this spring, all through 2018. I've done a couple shows with you. The difference that I saw this year was that the use cases were real and the time to value was real. People are implementing cloud projects, multi-cloud projects, and they're getting to a good milestone within weeks or months. Admittedly, these are big, multi-national companies, so it's really at the top level where they have the army of people to do it, but sometimes these projects were very small and they were real. They weren't just marketing hokum up on stage. Of course, they're not the full enterprise in a couple of weeks, but that's the difference this year, I see, Stu. I'm 40% full. >> Absolutely, I'd say look. Energy level was up. Two years ago it kind of hit a nadir. It was doom and gloom. We were all over at the eye candy bar saluting the great run that VMware had and wondering who the next CEO was been. Now, energy level's back up. Investment in the ecosystem, oh my gosh. I don't think I've seen this many parties ever at a VMworld. We got to talk about something other than cloud so give me your non-cloud takeaways from the show. Areas that people should learn more about, things you saw in the ecosystem or from VMware or the community. >> I think that's one of the things I've noticed here at the show. Wandering around the show floor, unlike some of the other shows where it's we will have a storage show or we'll have a backup show. There's a lot more balance this year. There seems to be a good mix of some of everything. I think that it shows that in order to run a successful IT shop, you actually need to have a balance of, you need some backup, you need some data recovery, you need to have some software, you need some monitoring, you need to have security options. Go and have a look at all of the different vendors that are at a show like this to be able to make sure you have a portfolio approach to how you run things. >> Totally. I remember there were a couple of years, four or five years ago, it was like oh, it's VM storage world. >> Yeah. >> OK, yeah. John? >> There is a lot of storage here, but the storage is all connected to the cloud now. I think if you look at some of the big booths and some of the start-ups who have gotten funding recently. Large rounds. Cohesity, Datrium, Rubrik, folks like that, they're delivering on promises made in earlier years. Not particularly like oh wow, I never thought of, but this was the vision that we laid out and now we're delivering it this year. Big rounds of funding, big customer movement, connection to the cloud and solid, interesting DR as a service and data, as opposed to storage, ideas. I thought that was one of the more interesting aisles this year over there in the booths. >> To riff on what you said about developers and the bridge to the code idea, we see Puppet is here at the show, HashiCorp is here for the first time. >> Docker's there, of course. >> Docker's here. >> C & CF had a booth. >> Yep, C & CF had a booth. These are people that you wouldn't have expected to see at a VMware show in years past. >> One thing that struck me is companies with a mission for good. Pat Gelsinger kind of sets the bar. Talked about it in his keynote. Do better, do good, sets that example. He climbed Mt. Kilimanjaro for charity earlier this year. They had Malala up on stage with Sanjay Poonen. I did a couple of interviews here which were inspiring. Mission-driven companies and great to see the infrastructure in software companies being like hey, we're enabling and helping it. That was one to me. Takeaways from the community? Other things as we get to our wrap? >> I do wonder about that point. Just to add a little, slightly critical note on that. I think that there has been a bit of a tech lash, a bit of a backlash against tech companies. I wonder whether, I would like to see more from tech companies to show that this is real. That that social conscience is a real thing and it isn't just a bit of marketing that they've spray painted on to the front of the company. The fact that we had Malala here giving a keynote indicates that there is a commitment to it. I would want to see that carry through for the next couple of years, at least, to show that that sort of thing is real. And certainly, from the rest of the ecosystem, I expect that we're going to see a lot more. >> Diversity in the community, absolutely. I do realize we have three white guys of a certain age sitting here. We try to add diversity. I had my first European host on the program. Lisa's been on a lot this week. We're building out our bench, we're looking to add diversity. John, yeah, the community. >> Community, again, yeah, community was good this year. A lot of old faces have stayed around, which is really interesting but also people have left and come back. You saw people who have gone into the AWS and Microsoft ecosystems coming back in here. Again, some of those old faces. Also, new faces. Global diversity from the southern hemisphere and from other countries that you wouldn't expect are here today. That was super interesting. I do see a lot of energy, a lot of excitement about their careers going forward. I do see that tech needs to be, there was some symbolic do-good things here. But I mean, Justin is a little bit involved in your own home country about how the government has the power with technology to do good or bad. I think that may be an emerging thing that we see here now as you get a layer down of not only charity work but the impacts of technology. I bet we'll end up talking about that next year, Stu. >> Guys, we could start talking for a lot longer. The good news is I know how to get in touch with you. For our audience, by the way, you can hit us all up on Twitter, through various social channels. Jtroyer, jpwarren, I'm of course @stu. That's just S-T-U. Blue Cow is on Instagram. Follow the adventures of Blue Cow, showing where Justin's going all over the place. Thanks so much for joining us. Great coverage here. This community's where I get a lot of my guest hosts and still, it's like homecoming coming to this place. Thank you for watching theCUBE. (electronic tones)