(upbeat music) >> Narrator: From around the globe, it's theCUBE, with digital coverage of Postgres Vision 2021, brought to you by EDB. >> Well, good day, everybody. John Walls here on theCUBE, and continuing our CUBE conversation as part of Postgres Vision 2021, sponsored by EDB, with EDB Chief Technology Officer, Mr. Mark Linster. Mark, good morning to you. How are you doing today? >> I'm doing very fine, very good, sir. >> Excellent. Excellent. Glad you could join us. And we appreciate the time, chance, to look at what's going on in this world of data, which, as you know, continues to evolve quite rapidly. So let's just take that 30,000-foot perspective here to begin with here, and let's talk about data, and management, and what Postgres is doing in terms of accelerating all these innovative techniques, and solutions, and services that we're seeing these days. >> Yeah, so I think it's really... It's a fantastic confluence of factors that we've seen in Postgres, or are seeing in Postgres today, where Postgres has really, really matured over the last couple of years, where things like high availability, parallel processing, use of very high core counts, et cetera, have come together with the drive towards digital transformation, the enormous amounts of data that businesses are dealing with today, so, and then the third factor's really the embracing of open source, right? I mean, Linux has shown the way, and has shown that this is really, really possible. And now we're seeing Postgres as, I think, the next big open source innovation, after Linux, achieving the same type of transformation. So it's really, it's a maturing, it's an acceptance, and the big drive towards dealing with a lot more data as part of digital transformation. >> You know, part of that acceptance that you talk about is about kind of accepting the fact that you have a legacy system that maybe, if you're not going to completely overhaul, you still have to integrate, right? You've got to compliment and start this kind of migration. So in your perspective, or from your perspective, what kind of progress is Postgres allowing in the mindset of CTOs among your client base, or whatever, that their legacy systems can function in this new environment, that all is not lost, and while there is some, perhaps, catching up to do, or some patching you have to do here and there, that it's not as arduous, or not as complex, as might appear to be on the face. >> Well, I think there's, the maturing of Postgres that has really really opened this up, right? Where we're seeing that Postgres can handle these workloads, right? And at the same time, there's a growing number of success cases where companies across all industries, financial services, insurance, manufacturing, retail are using Postgres. So, so you're no longer, you're no longer the first leader who's taken a higher risk, right? Like, five or 10 years ago, Postgres knowledge was not readily available. So if you want Postgres, it was really hard to find somebody who could support you, right? Or find an employee that you could hire who would be the Postgres expert. That's no longer the case. There's plenty of books about Postgres. There's lots of conferences about Postgres. It's a big meetup topic. So, getting know how and getting acceptance amongst your team to use Postgres has become a lot easier, right? At the same time, over 90% of all enterprises today use open source in one way or the other. Which basically means they have open source policies. They have ways to bring open source into the development stream. So that makes it possible, right? Whereas before it was really hard, you had to have an individual who would be evangelized to go, get open source, et cetera, now open source is something that almost everybody is using. You know, from government to financing services, open sources use all over the place, right? So, so now you have something that really matured, right? There's a lot of references out there and then you have the policies that make it possible, right? You have the success stories and now all the pieces have come together to deal with this onslaught of data, right? And then maybe the last thing that that really plays a big role is the cloud. Postgres runs everywhere, right? I mean, it runs from an Arduino to Amazon. Everywhere. And so, which basically means if you want to drive agile business transformation, you call Postgres because you don't have to decide today where it's going to run. You're not locking into a vendor. You're not locking into a limited support system. You can run this thing anywhere. It'll run on your laptop. It'll run on every cloud in the world. You can have it managed, you can have it hosted. You can add have every flavor you want and there's lots of good Postgres support companies out there. So all of these factors together is really what makes us so interesting, right? >> Kubernetes and this marriage, this complimentary, you know relationship right now with Kubernetes, what has that done? You think in terms of providing additional services or at least providing perhaps a new approach or new philosophies, new concepts in terms of database management? >> Well, it's maybe the most the most surprising thing or surprising from the outside. Probably not from the inside, but you think that that Postgres this now 25 year old, database twenty-five year old open source project would be kind of like completely, you know, incompatible with Kubernetes, with containers. But what really happens is Postgres in containers today is the number one database, after Engine X. It is the number two software that is being deployed in containers. So it's really become the workhorse of the whole microservices transformation, right? A 25 year old software, well, it has a very small footprint. It has a lot of interesting features like GIS, document processing, now graph capabilities, common table expressions all those things that are really like cool for developers. And that's probably what leads it to be the number one database in containers. So it's absolutely compatible with Kubernetes. And the whole transformation towards microservices is is like, you know, there's nothing better out there. It runs everywhere and has the most innovative technologies in it. And that's what we're seeing. Also, you go to the annual stack overflow survey of developers, right? It's been consistently number one or number two most loved and most used database, right? So, so what's amazing is that it's this relatively old technology that is, you know, beating everybody else in this digital transformation and then the adoption by developers. >> Just like old dog new tricks, right? It's still winning, right? >> Yeah, yeah, and, and, you know, the elephant is the symbol and this elephant does dance. >> Still dancing that's right. You know, and this is kind of a loaded question but there are a lot of databases out there, a lot of options, obviously from your perspective, you know, Postgres is winning, right? And, and, and from the size of the marketplace it is certainly leading RA leader. In your opinion, you know, what, what is this confluence of factors that have influenced this, this market position if you will, of Postgres or market acceptance of Postgres? >> It's, I mean, it's the, it's a maturing of the core. As I said before, that the transaction rates et cetera, Postgres can handle, are growing every year and are growing dramatic, right? So that's one thing. And then you have it, that Postgres is really, I think, the most reliable and relational database out there as what is my opinion, I'm biased, I guess. And, and it's, it's super quality code but then you add to that the innovation drive. I mean, it was the first one out there with good JSONB support, right? And now it's brought in JSON Path as as part of the new SQL standard. So now you can address JSON data inside your database and the same way you do it inside your browser. And that's pretty cool for developers. Then you combine that with PostGIS, right, which is, I think the most advanced GIS system out there in database. Now, now you got relations, asset compliant, GIS and document. You may say what's so cool about that. Well, what's cool about it is I can do absolutely reliable asset compliant transactions. I can have a fantastic personalization engine through JSONB, and then all my applications need to know where is the transaction? Where is the next store? How far away I'm a form of the parking spot? Right? So now I got a really really nice recipe to put the applications of the future together. You add onto that movements toward supporting graph and supporting other capabilities inside the database. So now you got, you got capability, you've got reliability and you got fantastic innovation. I mean, there's nothing better out there. >> Let's hit the security angle here, 'cause you talked about the asset test, and certainly, you know, those, that criteria is being met. No question about that, whether it's isolation, durability, consistency, whatever, but, but security, I don't have to tell you what a growing concern this is. It's already paramount, but we're seeing every day write stories about, about intrusions and and invasions, if you will. So in terms of providing that layer of security that everybody's looking for right now, you know, this this ultra impenetrable force, if you will, what in your mind, what's Postgres allowing for, in that respect in terms of security, peace of mind, and maybe a little additional comfort that everybody in your space is looking for these? >> So, so look at, look at security with a database like, like multiple layers, right? There's not just, you don't do security only one place. It's like when you go into a bank branch, right? I mean, they do lock the door, they have a camera, there is a gate in front of the safe, there's a safe door. And inside the safe, there is still, again safety deposit boxes with individual locks. The same applies to Postgres, right? Where let's say we start at the heart of it where we can secure and protect tables and data. We're using access control lists and groups and usernames, et cetera. Right? So that's, that's at the heart of it. But then outside of that, we can encrypt the data when on disk or when it's in transit on disk. Most people use the Linux disc encryption systems but there's also good partners out there, like like more metric or others that we work with, that that provide security on disk. And then you go out from there and then you have the securing of the database itself again through the log-ins and the groups. You go out from there and now you have the securing of the hosts that the database is sitting on. Then you'll look at securing the data on the networks through SSL and certificates, et cetera. So that basically there's a multi-layer security model layer that positions Postgres extremely well. And then maybe the last thing is to say it certainly integrates very well with ELDAP, active directory, Kerberos, all the usual suspects that you would use to secure technology inside the enterprise or in an open network, like where people work from home, et cetera. >> You talked about the history about this 25 year old technology, you know, founded back at Cal Berkeley, you know, probably almost some 30 years ago and certainly has evolved. And, and as you have pointed out now as a very mature technology, what do you see though in terms of growth from here? Like, where does it go from here in the next 18 months, 24 months, what what do you think is that next barrier, that challenge that that you think the technology and this open source community wants to take on? >> Well, I think there's there's the continuous effort of making it faster, right? That always happens, right? Every database wants to be faster do more transactions per second, et cetera. And there's a lot of work that has been done there. I mean, just in the last couple of years, Postgres performance has increased by over 50%. Right? So, so transactions per second and that kind of scalability that is going to continue to be, to be a focus, right? And then the other one is leading the implementation of the SQL standards, right? So there'd be the most advanced database, the most innovative database, because, remember for many years now, Postgres has come up with a new release on an annual basis. Other database vendors are now catching up to that, but Postgres has done that for years. So innovation has always been at the heart of it. So we started with JSONB, Key value pair came even before that, PostGis has been around for a long time, graph extensions are going to be the next thing, ingestion of time series data is going to, is going to happen. So there's going to be an ongoing stream of innovations happening. But one thing that I can say is because Postgres is a pure open source project. There's not a hard roadmap, like where it's going to go but where it's going to go is always driven by what people want to have, right? There is no product management department. There's no, there's no great visionary that says, "Oh, this is where we're going to go." No, no. What's going to happen is what people want to have, right? If companies or contributors want to have a certain feature because they need it, well, that's how it's going to happen. And that's really been at the heart of this since Mike Stonebraker, who's an advisor to EDB today, invented it. And then, you know, the open source project got created. This has always been the movement to only focus on things that people actually want to have because if nobody wants to have it, we're just not going to build it because nobody wants it. Right? So when you asked me for the roadmap I believe it's going to be, you know, faster, obviously, always faster, right? Everybody wants faster. And then there's going to be innovation features like making the document stored even better, graph ingestion of large time series, et cetera. That's really what I believe is going to drive it forward. >> Wow. Yeah, the market has spoken and as you point out the market will continue to speak and, and drive that bus. So Mark, thank you for the time today. We certainly appreciate that. And wish EDB continued success at Postgres vision 2021. And thanks for the time. >> Thanks John, it was a pleasure. >> You bet. Mark Linster, joining us, the CTO at EDB. I'm John Walls, you've been watching theCUBE. (upbeat music)

>>From around the globe, it's the Cube with digital coverage of postgres Vision 2021 brought to you by >>enterprise DB. Hello everyone. This is Dave Volonte for the cube we're covering Postgres Vision 2021. The virtual cube edition. Welcome to our conversation with the Ceo Ed Boyajian is here is the Ceo of enterprise DB and we're gonna talk about what's happening in open source and database in the future of tech. Ed welcome. >>Hi Dave, Good to be here. >>Hey, several years ago, at a, at a Postgres Vision event, you put forth the premise that the industry was approaching a threshold moment, a digital transformation was the linchpin of that shift now. Ed Well you were correct and I have no doubt the audience agreed. Most people went back to their offices after that event and they returned to their hyper focus of their day to day jobs. Maybe a few accelerated their digital initiatives, but generally pre Covid, we moved in a pretty incremental pace and then the big bang hit. And if you were digital business, you are out of business. So that single event created the most rapid change that we've ever seen in the tech industry by far, nothing really compares. So the question is why is Postgres specifically and e d B generally the right fit for this new world? >>Yeah, I think, look, a couple of things are happening gave right along the bigger picture of digital transformation. We are seeing the database market in transformation and and I think the things that are driving that shift are the things that are resulting the success of Postgres and the success of B D B I think first and foremost we're seeing a dramatic re platform ng. And just like we saw in the world of Lennox where I was at red hat during that shift where people are moving from UNIX based systems to x 86 systems. We're seeing that similar re platform in happening. Whether that's from traditional infrastructures to cloud based infrastructures or container based infrastructures, it's a great opportunity for databases to be changed out. Postgres wins in that context because it's so easily deployed anywhere. I think the second thing that's changing is we're seeing a broad expansion of developers across the enterprise so they don't just live in I. T. Anymore. And I think as developers take on more power and control their defining the agenda and it's another place where Postgres shines, it's been a priority of the dBS to make postgres easier. Uh and that's coming to life. And I think the last Stack Overflow Developer Survey suggested that I think they survey 65 developers, the second most loved and the second most used database by developers, Postgres. And so I think there again Postgres shines in a moment of change. Uh and then I think the third is kind of obvious. It's always an elephant in the room, no pun intended. But it's this relentless nagging burden of the expenses of the incumbent proprietary databases and the need. And we especially saw this in Covid to start to change that more dramatically, change that economic equation here Again. PostGres shines. >>You know, I want to ask you, I'm gonna jump ahead to the future for a second because you're talking about the re platform NG and with your red hat chops, I kind of want to pick your brain on this because you're right, you saw it with red hat and you're kind of seeing it again when you think about open shift and where it's going my my question is related to replant forming around new types of workloads, new processing models at the edge. I mean you're seeing an explosion of processing power, GPU SNP us accelerators, dSPs and it appears that this is happening at a very low cost. I'm referring that you're saying Postgres can take advantage of that trend as well that that broader re platform ng trend to the edge, is that correct? >>It is. And I think you know this is, this has been one of the, I think the most interesting things with posters now I've been here almost 13 years. So if you put that in some perspective, I've watched Uh and participated in leading transformation in the category, you know, we've been squarely focused on postgres. So we've got 300 engineers who worry about making postgres better. And as you look across that landscape of time, not only as Postgres gotten more performant and more scalable, it's also proven to be the right database choice in the world of not just legacy migrations, but new application development. And I think that stack overflow developer survey is a good indicator of how developers feel about postgres. But you know, over that time frame I think if you went back to 2008 when I joined E D. B, post chris was considered a really good general purpose database. And today I think post chris is a great general purpose database. General purpose isn't sexy in the market broadly speaking, but Postgres capabilities across workloads in every area is really robust. Let me just spend a second on it. We look at our customer base is deploying in what we think of as systems of record, which are the traditional er, P type apps, uh you know where there's a single source of truth you might think of the RP apps there. We look at our customers deploying in systems of engagement. And those are apps that you might think of in the context of social media style apps or websites that are backed by a database in the third area Systems of analytics where you would typically think of data warehouse style applications interestingly. Postgres performs well and our customers report using us across that whole landscape of application areas. And I think that is one of postgres hidden superpowers. Is that ability to reach into each area of requirement on the workload side. >>And as always alluding to before that that itself is evolving as you now inject ai into the equation ai influencing and it's just a very exciting times ahead. There's no there's no database, You know, 20 years ago it was kind of boring. Now it's just exploding. I want to come back to that the notion of of post grass and maybe talk about other database models. Uh, I mean you mentioned that you've evolved from this, you know, system of record. You can take a system engagement on structured data etcetera. Jason. It's so how should we think about post grass in relation to other databases and specifically other business models of companies that provide database services? Why is Postgres attractive? Where is it winning? >>Yeah, I think a couple of places. So I mean first and foremost Postgres, you know, at his core, post chris is a sequel, relational databases in acid compliance, equal relational database. And that is inherently a strength of Postgres. But it's also a multi model database, which means we handle a lot of other, um, you know, database requirements, whether that's geospatial or or Jason, uh, for documents or time series, things like that. And so Postgres extensive bility is one of its inherent strengths and that's kind of been built in from the beginning of Postgres. So not surprisingly, people use postgres across the number of workloads because at the end of the day there's still value in having a database is able to do more. There are a lot of important specialty databases and I think they will remain important specialty databases, but Postgres thrives in its ability to cross cross over in that way. Um and I think that is, you know, one of the different key differentiators in how we've seen the market in the business development and that's the breadth of of workloads that Postgres succeeds in. But but our growth, if you kind of ventured it across vectors, we see growth happening, you know, in a few dimensions. First we see growth happening in new applications. About half of our customers that come to us today for new uh new postgres users are deploying us on new applications. The others are our second area migrating away from some existing legacy in companies often oracle. Not always. Um The third area of growth we see is in cloud, where Postgres is deployed very prolifically, both in the traditional cloud platforms, Uh like EC two, but then then again also uh in the database as a service environment. And then the fourth area growth we're seeing now is around uh container deployment, kubernetes deployment. >>Well, you may Oracle's prominent because it's just it's a big installed base and it's expensive and people, >>you >>know, they got a look at them. It's funny, I do a lot of TCO work and mostly, you know, usually TCO is about labor costs. When it comes to Oracle, it's about license costs and maintenance costs. And so to the extent that you can reduce that, at least for a portion of your state, you're gonna you're gonna drop right to the bottom line. But but but but I want to ask you about that kind of that spectrum that you think about the prevailing models for database you've got. On the one hand, You've got the right tool for the right job approach. It might be 10 or 12 data stores in the cloud. On the other hand, you've got, you know, kind of a converged approach. Oracle's going that direction clearly. Postgres with its open source innovation is going that direction. And it seems to me that at scale that's a more the latter is a more cost effective model. How do you think about that? >>Well, you know, I think at the end of the day, you kind of have to look at it. I mean, the business side of my brain looks at that as an addressable market question. Right? And you've heard me talk about three broad categories of workloads and you know, people define workloads in different bucket, but that's how we do it. But if you look at just a system of record in the system of engagement market, I think that's what would be traditionally viewed as the database market. Uh and there that's you know, let's just say for the sake of arguments of $45-$50 billion $18 billion dollar market. And you know, as we talk about that. So all in it's still between 60 and $70 billion market. And I think what happens there's so much heat and light poured on the valuation multiples of some of the specialty players. That the market gets confused, but the reality is our customers don't get confused. I mean if you look at those specialty players take that $48 billion market. I mean add up Mongo red is cockroach neo, all of those. I mean hugely valued companies. All unicorn companies. But combined to add up to a billion bucks don't get me wrong that's important revenue and meaningful in the workloads they support. But it's not. It doesn't define the full transformation of this category. Look at the systems of analysis again, another great great market example. I mean if you add up the consolidation of the Hadoop vendors add in there. Um Snowflake, you're still talking you know a billion five in revenue and an $18 billion market. So while those are all important technologies, the question is in this transformation move to the database market fully transform you. And my view is no it didn't were in the first maybe second inning of a $65 billion transformation. And I think this is where Postgres will ultimately shine. I think this is how Postgres wins because at the end of the day the nature of the workloads fits with postgres and the future tech that we're building in post schools will serve that broader set of needs I think more effectively >>well. And I love these tam expansion discussions because I think you're right on and I think it comes back to the data and we all talk about the data growth, the data explosion, we see the I. D. C. Numbers and you ain't seen nothing yet. And so data by its very nature is distributed. That's why I get so excited about these new platform models and and I want to tie it back to developers and open source because to me that is the linchpin of innovation um in the next decade it has been, I would even say for the last decade we've seen it, but it's gaining momentum, so, so in thinking about innovation and and specifically Postgres and an open source, you know, what can you share with us in terms of how we should think about your advantage, and again, what, where people are glomming leaning in to that advantage? >>Yeah, so, I mean, I think I think you bring up a really important topic for us as a company. Postgres we think is an incredibly powerful community, uh and when you step away from it again, I remember I told you I was at red hat before, now here at E D B, and there's a common thread that runs through those two experiences in both experiences. The companies are attached and prominent alongside a strong independent, open source community, and I think the notion of an independent community is really important to understand around postgres. There are hundreds and thousands of people contributing to Postgres now. E D B plays a big role in that. About approaching a third of the contributions. In the last release released, 13 of Postgres came from E D B. You might look at that and say gee, that sounds like a lot, but if you step away from it, you know, about 30% of those contributions, Most of the contributions come from a universe around D D. B. And that's inherently healthy for the community's ability to innovate and accelerate. And I think that while we play a strong role there, you can imagine that having and there are other great companies that are contributing to Postgres, I think having those companies participating and contributing gets the best, the best ideas to the front in innovation. So I think the inherent nature Postgres community makes it strong and healthy. And then contrast that to some of the other prominent high value open source companies, the companies and the communities are intimately intertwined. They're one and the same. They're actually not independent open source communities. And I think that therein lies one of the, one of the inherent weaknesses in those but postgres to rise because you know, we bring all those ideas from the DB, we bring a commercial contingent with us all the things we hope we emphasize and focus on in growth and postgres, whether that's in the areas of scalability, manageability, all hot topics, of course security, all of those areas. And then, you know, performance as always, all of those areas are informed to us by enterprise customers deploying post chris at scale. And I think that's the heart of what makes a successful independent project. >>Yeah. The combinatorial powers of of that ecosystem. Uh they their their multiplication, I've as opposed to the resources of one. I want to talk about postgres Vision 2021 sort of set up that a little bit. The theme this year is the future. Is you, what do you mean by that? >>So if you think about what we just said post the category is in transit database categories and transformation. And we know that many of our people are interested in. Postgres are early in their journey, their early in their experience. And so we want to focus this year's postcards vision on them that we understand as a company has been committed to postgres as long as we have and with the understanding we have the technology and best practices, we want to share that view those insights uh, with those who are coming to postgres, Some for the first time, some who are experienced >>Postgres. Vision 21 is june 22nd and 23rd. Go to enterprise db dot com and register the cube is going to be there. We hope you will be too. Ed, thanks for coming to the Cuban previewing the event. >>Thanks Dave. >>Thank you. We'll see you at Vision 21 >>mm mm.

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE conversation. >> Hey, welcome back, you're ready. Jeff Frick here with theCUBE. We are still getting through the year of 2020. It's still the year of COVID and there's no end in sight I think until we get to a vaccine. That said, we're really excited to have one of our favorite guests. We haven't had him on for a while. I haven't talked to him for a long time. He used to I think have the record for the most CUBE appearances of probably any CUBE alumni. We're excited to have him joining us from his house in Palo Alto. Bill Schmarzo, you know him as the Dean of Big Data, he's got more titles. He's the chief innovation officer at Hitachi Vantara. He's also, we used to call him the Dean of Big Data, kind of for fun. Well, Bill goes out and writes a bunch of books. And now he teaches at the University of San Francisco, School of Management as an executive fellow. He's an honorary professor at NUI Galway. I think he's just, he likes to go that side of the pond and a many time author now, go check him out. His author profile on Amazon, the "Big Data MBA," "The Art of Thinking Like A Data Scientist" and another Big Data, kind of a workbook. Bill, great to see you. >> Thanks, Jeff, you know, I miss my time on theCUBE. These conversations have always been great. We've always kind of poked around the edges of things. A lot of our conversations have always been I thought, very leading edge and the title Dean of Big Data is courtesy of theCUBE. You guys were the first ones to give me that name out of one of the very first Strata Conferences where you dubbed me the Dean of Big Data, because I taught a class there called the Big Data MBA and look what's happened since then. >> I love it. >> It's all on you guys. >> I love it, and we've outlasted Strata, Strata doesn't exist as a conference anymore. So, you know, part of that I think is because Big Data is now everywhere, right? It's not the standalone thing. But there's a topic, and I'm holding in my hands a paper that you worked on with a colleague, Dr. Sidaoui, talking about what is the value of data? What is the economic value of data? And this is a topic that's been thrown around quite a bit. I think you list a total of 28 reference sources in this document. So it's a well researched piece of material, but it's a really challenging problem. So before we kind of get into the details, you know, from your position, having done this for a long time, and I don't know what you're doing today, you used to travel every single week to go out and visit customers and actually do implementations and really help people think these through. When you think about the value, the economic value, how did you start to kind of frame that to make sense and make it kind of a manageable problem to attack? >> So, Jeff, the research project was eyeopening for me. And one of the advantages of being a professor is, you have access to all these very smart, very motivated, very free research sources. And one of the problems that I've wrestled with as long as I've been in this industry is, how do you figure out what is data worth? And so what I did is I took these research students and I stick them on this problem. I said, "I want you to do some research. Let me understand what is the value of data?" I've seen all these different papers and analysts and consulting firms talk about it, but nobody's really got this thing clicked. And so we launched this research project at USF, professor Mouwafac Sidaoui and I together, and we were bumping along the same old path that everyone else got, which was inched on, how do we get data on our balance sheet? That was always the motivation, because as a company we're worth so much more because our data is so valuable, and how do I get it on the balance sheet? So we're headed down that path and trying to figure out how do you get it on the balance sheet? And then one of my research students, she comes up to me and she says, "Professor Schmarzo," she goes, "Data is kind of an unusual asset." I said, "Well, what do you mean?" She goes, "Well, you think about data as an asset. It never depletes, it never wears out. And the same dataset can be used across an unlimited number of use cases at a marginal cost equal to zero." And when she said that, it's like, "Holy crap." The light bulb went off. It's like, "Wait a second. I've been thinking about this entirely wrong for the last 30 some years of my life in this space. I've had the wrong frame. I keep thinking about this as an act, as an accounting conversation. An accounting determines valuation based on what somebody is willing to pay for." So if you go back to Adam Smith, 1776, "Wealth of Nations," he talks about valuation techniques. And one of the valuation techniques he talks about is valuation and exchange. That is the value of an asset is what someone's willing to pay you for it. So the value of this bottle of water is what someone's willing to pay you for it. So everybody fixates on this asset, valuation in exchange methodology. That's how you put it on balance sheet. That's how you run depreciation schedules, that dictates everything. But Adam Smith also talked about in that book, another valuation methodology, which is valuation in use, which is an economics conversation, not an accounting conversation. And when I realized that my frame was wrong, yeah, I had the right book. I had Adam Smith, I had "Wealth of Nations." I had all that good stuff, but I hadn't read the whole book. I had missed this whole concept about the economic value, where value is determined by not how much someone's willing to pay you for it, but the value you can drive by using it. So, Jeff, when that person made that comment, the entire research project, and I got to tell you, my entire life did a total 180, right? Just total of 180 degree change of how I was thinking about data as an asset. >> Right, well, Bill, it's funny though, that's kind of captured, I always think of kind of finance versus accounting, right? And then you're right on accounting. And we learn a lot of things in accounting. Basically we learn more that we don't know, but it's really hard to put it in an accounting framework, because as you said, it's not like a regular asset. You can use it a lot of times, you can use it across lots of use cases, it doesn't degradate over time. In fact, it used to be a liability. 'cause you had to buy all this hardware and software to maintain it. But if you look at the finance side, if you look at the pure play internet companies like Google, like Facebook, like Amazon, and you look at their valuation, right? We used to have this thing, we still have this thing called Goodwill, which was kind of this capture between what the market established the value of the company to be. But wasn't reflected when you summed up all the assets on the balance sheet and you had this leftover thing, you could just plug in goodwill. And I would hypothesize that for these big giant tech companies, the market has baked in the value of the data, has kind of put in that present value on that for a long period of time over multiple projects. And we see it captured probably in goodwill, versus being kind of called out as an individual balance sheet item. >> So I don't think it's, I don't know accounting. I'm not an accountant, thank God, right? And I know that goodwill is one of those things if I remember from my MBA program is something that when you buy a company and you look at the value you paid versus what it was worth, it stuck into this category called goodwill, because no one knew how to figure it out. So the company at book value was a billion dollars, but you paid five billion for it. Well, you're not an idiot, so that four billion extra you paid must be in goodwill and they'd stick it in goodwill. And I think there's actually a way that goodwill gets depreciated as well. So it could be that, but I'm totally away from the accounting framework. I think that's distracting, trying to work within the gap rules is more of an inhibitor. And we talk about the Googles of the world and the Facebooks of the world and the Netflix of the world and the Amazons and companies that are great at monetizing data. Well, they're great at monetizing it because they're not selling it, they're using it. Google is using their data to dominate search, right? Netflix is using it to be the leader in on-demand videos. And it's how they use all the data, how they use the insights about their customers, their products, and their operations to really drive new sources of value. So to me, it's this, when you start thinking about from an economics perspective, for example, why is the same car that I buy and an Uber driver buys, why is that car more valuable to an Uber driver than it is to me? Well, the bottom line is, Uber drivers are going to use that car to generate value, right? That $40,000, that car they bought is worth a lot more, because they're going to use that to generate value. For me it sits in the driveway and the birds poop on it. So, right, so it's this value in use concept. And when organizations can make that, by the way, most organizations really struggle with this. They struggle with this value in use concept. They want to, when you talk to them about data monetization and say, "Well, I'm thinking about the chief data officer, try not to trying to sell data, knocking on doors, shaking their tin cup, saying, 'Buy my data.'" No, no one wants your data. Your data is more valuable for how you use it to drive your operations then it's a sell to somebody else. >> Right, right. Well, on of the other things that's really important from an economics concept is scarcity, right? And a whole lot of economics is driven around scarcity. And how do you price for scarcity so that the market evens out and the price matches up to the supply? What's interesting about the data concept is, there is no scarcity anymore. And you know, you've outlined and everyone has giant numbers going up into the right, in terms of the quantity of the data and how much data there is and is going to be. But what you point out very eloquently in this paper is the scarcity is around the resources to actually do the work on the data to get the value out of the data. And I think there's just this interesting step function between just raw data, which has really no value in and of itself, right? Until you start to apply some concepts to it, you start to analyze it. And most importantly, that you have some context by which you're doing all this analysis to then drive that value. And I thought it was really an interesting part of this paper, which is get beyond the arguing that we're kind of discussing here and get into some specifics where you can measure value around a specific business objective. And not only that, but then now the investment of the resources on top of the data to be able to extract the value to then drive your business process for it. So it's a really different way to think about scarcity, not on the data per se, but on the ability to do something with it. >> You're spot on, Jeff, because organizations don't fail because of a lack of use cases. They fail because they have too many. So how do you prioritize? Now that scarcity is not an issue on the data side, but it is this issue on the people resources side, you don't have unlimited data scientists, right? So how do you prioritize and focus on those opportunities that are most important? I'll tell you, that's not a data science conversation, that's a business conversation, right? And figuring out how you align organizations to identify and focus on those use cases that are most important. Like in the paper we go through several different use cases using Chipotle as an example. The reason why I picked Chipotle is because, well, I like Chipotle. So I could go there and I could write it off as research. But there's a, think about the number of use cases where a company like Chipotle or any other company can leverage your data to drive their key business initiatives and their key operational use cases. It's almost unbounded, which by the way, is a huge challenge. In fact, I think part of the problem we see with a lot of organizations is because they do such a poor job of prioritizing and focusing, they try to solve the entire problem with one big fell swoop, right? It's slightly the old ERP big bang projects. Well, I'm just going to spend $20 million to buy this analytic capability from company X and I'm going to install it and then magic is going to happen. And then magic is going to happen, right? And then magic is going to happen, right? And magic never happens. We get crickets instead, because the biggest challenge isn't around how do I leverage the data, it's about where do I start? What problems do I go after? And how do I make sure the organization is bought in to basically use case by use case, build out your data and analytics architecture and capabilities. >> Yeah, and you start backwards from really specific business objectives in the use cases that you outline here, right? I want to increase my average ticket by X. I want to increase my frequency of visits by X. I want to increase the amount of items per order from X to 1.2 X, or 1.3 X. So from there you get a nice kind of big revenue hit that you can plan around and then work backwards into the amount of effort that it takes and then you can come up, "Is this a good investment or not?" So it's a really different way to get back to the value of the data. And more importantly, the analytics and the work to actually call out the information. >> The technologies, the data and analytic technologies available to us. The very composable nature of these allow us to take this use case by use case approach. I can build out my data lake one use case at a time. I don't need to stuff 25 data sources into my data lake and hope there's someone more valuable. I can use the first use case to say, "Oh, I need these three data sources to solve that use case. I'm going to put those three data sources in the data lake. I'm going to go through the entire curation process of making sure the data has been transformed and cleansed and aligned and enriched and met of, all the other governance, all that kind of stuff this goes on. But I'm going to do that use case by use case, 'cause a use case can tell me which data sources are most important for that given situation. And I can build up my data lake and I can build up my analytics then one use case at a time. And there is a huge impact then, huge impact when I build out use case by use case. That does not happen. Let me throw something that's not really covered in the paper, but it is very much covered in my new book that I'm working on, which is, in knowledge-based industries, the economies of learning are more powerful than the economies of scale. Now think about that for a second. >> Say that again, say that again. >> Yeah, the economies of learning are more powerful than the economies of scale. And what that means is what I learned on the first use case that I build out, I can apply that learning to the second use case, to the third use case, to the fourth use case. So when I put my data into my data lake for my first use case, and the paper covers this, well, once it's in my data lake, the cost of reusing that data in a second, third and fourth use cases is basically, you know marginal cost is zero. So I get this ability to learn about what data sets are most important and to reapply that across the organization. So this learning concept, I learn use case by use case, I don't have to do a big economies of scale approach and start with 25 datasets of which only three or four might be useful. But I'm incurring the overhead for all those other non-important data sets because I didn't take the time to go through and figure out what are my most important use cases and what data do I need to support those use cases. >> I mean, should people even think of the data per se or should they really readjust their thinking around the application of the data? Because the data in and of itself means nothing, right? 55, is that fast or slow? Is that old or young? Well, it depends on a whole lot of things. Am I walking or am I in a brand new Corvette? So it just, it's funny to me that the data in and of itself really doesn't have any value and doesn't really provide any direction into a decision or a higher order, predictive analytics until you start to manipulate the data. So is it even the wrong discussion? Is data the right discussion? Or should we really be talking about the capabilities to do stuff within and really get people focused on that? >> So Jeff, there's so many points to hit on there. So the application of data is what's the value, and the queue of you guys used to be famous for saying, "Separating noise from the signal." >> Signal from the noise. Signal from a noise, right. Well, how do you know in your dataset what's signal and what's noise? Well, the use case will tell you. If you don't know the use case and you have no way of figuring out what's important. One of the things I use, I still rail against, and it happens still. Somebody will walk up my data science team and say, "Here's some data, tell me what's interesting in it." Well, how do you separate signal from noise if I don't know the use case? So I think you're spot on, Jeff. The way to think about this is, don't become data-driven, become value-driven and value is driven from the use case or the application or the use of the data to solve that particular use case. So organizations that get fixated on being data-driven, I hate the term data-driven. It's like as if there's some sort of frigging magic from having data. No, data has no value. It's how you use it to derive customer product and operational insights that drive value,. >> Right, so there's an interesting step function, and we talk about it all the time. You're out in the weeds, working with Chipotle lately, and increase their average ticket by 1.2 X. We talk more here, kind of conceptually. And one of the great kind of conceptual holy grails within a data-driven economy is kind of working up this step function. And you've talked about it here. It's from descriptive, to diagnostic, to predictive. And then the Holy grail prescriptive, we're way ahead of the curve. This comes into tons of stuff around unscheduled maintenance. And you know, there's a lot of specific applications, but do you think we spend too much time kind of shooting for the fourth order of greatness impact, instead of kind of focusing on the small wins? >> Well, you certainly have to build your way there. I don't think you can get to prescriptive without doing predictive, and you can't do predictive without doing descriptive and such. But let me throw a really one at you, Jeff, I think there's even one beyond prescriptive. One we're talking more and more about, autonomous, a ton of analytics, right? And one of the things that paper talked about that didn't click with me at the time was this idea of orphaned analytics. You and I kind of talked about this before the call here. And one thing we noticed in the research was that a lot of these very mature organizations who had advanced from the retrospective analytics of BI to the descriptive, to the predicted, to the prescriptive, they were building one off analytics to solve a problem and getting value from it, but never reusing this analytics over and over again. They were done one off and then they were thrown away and these organizations were so good at data science and analytics, that it was easier for them to just build from scratch than to try to dig around and try to find something that was never actually ever built to be reused. And so I have this whole idea of orphaned analytics, right? It didn't really occur to me. It didn't make any sense into me until I read this quote from Elon Musk, and Elon Musk made this statement. He says, " I believe that when you buy a Tesla, you're buying an asset that appreciates in value, not depreciates through usage." I was thinking, "Wait a second, what does that mean?" He didn't actually say it, "Through usage." He said, "He believes you're buying an asset that appreciates not depreciates in value." And of course the first response I had was, "Oh, it's like a 1964 and a half Mustang. It's rare, so everybody is going to want these things. So buy one, stick it in your garage. And 20 years later, you're bringing it out and it's worth more money." No, no, there's 600,000 of these things roaming around the streets, they're not rare. What he meant is that he is building an autonomous asset. That the more that it's used, the more valuable it's getting, the more reliable, the more efficient, the more predictive, the more safe this asset's getting. So there is this level beyond prescriptive where we can think about, "How do we leverage artificial intelligence, reinforcement, learning, deep learning, to build these assets that the more that they are used, the smarter they get." That's beyond prescriptive. That's an environment where these things are learning. In many cases, they're learning with minimal or no human intervention. That's the real aha moment. That's what I miss with orphaned analytics and why it's important to build analytics that can be reused over and over again. Because every time you use these analytics in a different use case, they get smarter, they get more valuable, they get more predictive. To me that's the aha moment that blew my mind. I realized I had missed that in the paper entirely. And it took me basically two years later to realize, dough, I missed the most important part of the paper. >> Right, well, it's an interesting take really on why the valuation I would argue is reflected in Tesla, which is a function of the data. And there's a phenomenal video if you've never seen it, where they have autonomous vehicle day, it might be a year or so old. And he's got his number one engineer from, I think the Microprocessor Group, The Computer Vision Group, as well as the autonomous driving group. And there's a couple of really great concepts I want to follow up on what you said. One is that they have this thing called The Fleet. To your point, there's hundreds of thousands of these things, if they haven't hit a million, that are calling home reporting home every day as to exactly how everyone took the Northbound 101 on-ramp off of University Avenue. How fast did they go? What line did they take? What G-forces did they take? And every one of those cars feeds into the system, so that when they do the autonomous update, not only are they using all their regular things that they would use to map out that 101 Northbound entry, but they've got all the data from all the cars that have been doing it. And you know, when that other car, the autonomous car couple years ago hit the pedestrian, I think in Phoenix, which is not good, sad, killed a person, dark tough situation. But you know, we are doing an autonomous vehicle show and the guy who made a really interesting point, right? That when something like that happens, typically if I was in a car wreck or you're in a car wreck, hopefully not, I learned the person that we hit learns and maybe a couple of witnesses learn, maybe the inspector. >> But nobody else learns. >> But nobody else learns. But now with the autonomy, every single person can learn from every single experience with every vehicle contributing data within that fleet. To your point, it's just an order of magnitude, different way to think about things. >> Think about a 1% improvement compounded 365 times, equals I think 38 X improvement. The power of 1% improvements over these 600,000 plus cars that are learning. By the way, even when the autonomous FSD, the full self-driving mode module isn't turned on, even when it's not turned on, it runs in shadow mode. So it's learning from the human drivers, the human overlords, it's constantly learning. And by the way, not only they're collecting all this data, I did a little research, I pulled out some of their job search ads and they've built a giant simulator, right? And they're there basically every night, simulating billions and billions of more driven miles because of the simulator. They are building, he's going to have a simulator, not only for driving, but think about all the data he's capturing as these cars are riding down the road. By the way, they don't use Lidar, they use video, right? So he's driving by malls. He knows how many cars are in the mall. He's driving down roads, he knows how old the cars are and which ones should be replaced. I mean, he has this, he's sitting on this incredible wealth of data. If anybody could simulate what's going on in the world and figure out how to get out of this COVID problem, it's probably Elon Musk and the data he's captured, be courtesy of all those cars. >> Yeah, yeah, it's really interesting, and we're seeing it now. There's a new autonomous drone out, the Skydio, and they just announced their commercial product. And again, it completely changes the way you think about how you use that tool, because you've just eliminated the complexity of driving. I don't want to drive that, I want to tell it what to do. And so you're saying, this whole application of air force and companies around things like measuring piles of coal and measuring these huge assets that are volume metric measured, that these things can go and map out and farming, et cetera, et cetera. So the autonomy piece, that's really insightful. I want to shift gears a little bit, Bill, and talk about, you had some theories in here about thinking of data as an asset, data as a currency, data as monetization. I mean, how should people think of it? 'Cause I don't think currency is very good. It's really not kind of an exchange of value that we're doing this kind of classic asset. I think the data as oil is horrible, right? To your point, it doesn't get burned up once and can't be used again. It can be used over and over and over. It's basically like feedstock for all kinds of stuff, but the feedstock never goes away. So again, or is it that even the right way to think about, do we really need to shift our conversation and get past the idea of data and get much more into the idea of information and actionable information and useful information that, oh, by the way, happens to be powered by data under the covers? >> Yeah, good question, Jeff. Data is an asset in the same way that a human is an asset. But just having humans in your company doesn't drive value, it's how you use those humans. And so it's really again the application of the data around the use cases. So I still think data is an asset, but I don't want to, I'm not fixated on, put it on my balance sheet. That nice talk about put it on a balance sheet, I immediately put the blinders on. It inhibits what I can do. I want to think about this as an asset that I can use to drive value, value to my customers. So I'm trying to learn more about my customer's tendencies and propensities and interests and passions, and try to learn the same thing about my car's behaviors and tendencies and my operations have tendencies. And so I do think data is an asset, but it's a latent asset in the sense that it has potential value, but it actually has no value per se, inputting it into a balance sheet. So I think it's an asset. I worry about the accounting concept medially hijacking what we can do with it. To me the value of data becomes and how it interacts with, maybe with other assets. So maybe data itself is not so much an asset as it's fuel for driving the value of assets. So, you know, it fuels my use cases. It fuels my ability to retain and get more out of my customers. It fuels ability to predict what my products are going to break down and even have products who self-monitor, self-diagnosis and self-heal. So, data is an asset, but it's only a latent asset in the sense that it sits there and it doesn't have any value until you actually put something to it and shock it into action. >> So let's shift gears a little bit and start talking about the data and talk about the human factors. 'Cause you said, one of the challenges is people trying to bite off more than they can chew. And we have the role of chief data officer now. And to your point, maybe that mucks things up more than it helps. But in all the customer cases that you've worked on, is there a consistent kind of pattern of behavior, personality, types of projects that enables some people to grab those resources to apply to their data to have successful projects, because to your point there's too much data and there's too many projects and you talk a lot about prioritization. But there's a lot of assumptions in the prioritization model that you can, that you know a whole lot of things, especially if you're comparing project A over in group A with project B, with group B and the two may not really know the economics across that. But from an individual person who sees the potential, what advice do you give them? What kind of characteristics do you see, either in the type of the project, the type of the boss, the type of the individual that really lends itself to a higher probability of a successful outcome? >> So first off you need to find somebody who has a vision for how they want to use the data, and not just collect it. But how they're going to try to change the fortunes of the organization. So it always takes a visionary, may not be the CEO, might be somebody who's a head of marketing or the head of logistics, or it could be a CIO, it could be a chief data officer as well. But you've got to find somebody who says, "We have this latent asset we could be doing more with, and we have a series of organizational problem challenges against which I could apply this asset. And I need to be the matchmaker that brings these together." Now the tool that I think is the most powerful tool in marrying the latent capabilities of data with all the revenue generating opportunities in the application side, because there's a countless number, the most important tool that I found doing that is design thinking. Now, the reason why I think design thinking is so important, because one of the things that design thinking does a great job is it gives everybody a voice in the process of identifying, validating, valuing, and prioritizing use cases you're going to go after. Let me say that again. The challenge organizations have is identifying, validating, valuing, and prioritizing the use cases they want to go after. Design thinking is a marvelous tool for driving organizational alignment around where we're going to start and what's going to be next and why we're going to start there and how we're going to bring everybody together. Big data and data science projects don't die because of technology failure. Most of them die because of passive aggressive behaviors in the organization that you didn't bring everybody into the process. Everybody's voice didn't get a chance to be heard. And that one person who's voice didn't get a chance to get heard, they're going to get you. They may own a certain piece of data. They may own something, but they're just waiting and lay, they're just laying there waiting for their chance to come up and snag it. So what you got to do is you got to proactively bring these people together. We call this, this is part of our value engineering process. We have a value engineering process around envisioning where we bring all these people together. We help them to understand how data in itself is a latent asset, but how it can be used from an economics perspective, drive all those value. We get them all fired up on how these can solve any one of these use cases. But you got to start with one, and you've got to embrace this idea that I can build out my data and analytic capabilities, one use case at a time. And the first use case I go after and solve, makes my second one easier, makes my third one easier, right? It has this ability that when you start going use case by use case two really magical things happen. Number one, your marginal cost flatten. That is because you're building out your data lake one use case at a time, and you're bringing all the important data lake, that data lake one use case at a time. At some point in time, you've got most of the important data you need, and the ability that you don't need to add another data source. You got what you need, so your marginal costs start to flatten. And by the way, if you build your analytics as composable, reusable, continuous learning analytic assets, not as orphaned analytics, pretty soon you have all the analytics you need as well. So your marginal cost flatten, but effect number two is that you've, because you've have the data and the analytics, I can accelerate time to value, and I can de-risked projects as I go use case by use case. And so then the biggest challenge becomes not in the data and the analytics, it's getting the all the business stakeholders to agree on, here's a roadmap we're going to go after. This one's first, and this one is going first because it helps to drive the value of the second and third one. And then this one drives this, and you create a whole roadmap of rippling through of how the data and analytics are driving this value to across all these use cases at a marginal cost approaching zero. >> So should we have chief design thinking officers instead of chief data officers that really actually move the data process along? I mean, I first heard about design thinking years ago, actually interviewing Dan Gordon from Gordon Biersch, and they were, he had just hired a couple of Stanford grads, I think is where they pioneered it, and they were doing some work about introducing, I think it was a a new apple-based alcoholic beverage, apple cider, and they talked a lot about it. And it's pretty interesting, but I mean, are you seeing design thinking proliferate into the organizations that you work with? Either formally as design thinking or as some derivation of it that pulls some of those attributes that you highlighted that are so key to success? >> So I think we're seeing the birth of this new role that's marrying capabilities of design thinking with the capabilities of data and analytics. And they're calling this dude or dudette the chief innovation officer. Surprise. >> Title for someone we know. >> And I got to tell a little story. So I have a very experienced design thinker on my team. All of our data science projects have a design thinker on them. Every one of our data science projects has a design thinker, because the nature of how you build and successfully execute a data science project, models almost exactly how design thinking works. I've written several papers on it, and it's a marvelous way. Design thinking and data science are different sides of the same coin. But my respect for data science or for design thinking took a major shot in the arm, major boost when my design thinking person on my team, whose name is John Morley introduced me to a senior data scientist at Google. And I was bottom coffee. I said, "No," this is back in, before I even joined Hitachi Vantara, and I said, "So tell me the secret to Google's data science success? You guys are marvelous, you're doing things that no one else was even contemplating, and what's your key to success?" And he giggles and laughs and he goes, "Design thinking." I go, "What the hell is that? Design thinking, I've never even heard of the stupid thing before." He goes, "I'd make a deal with you, Friday afternoon let's pop over to Stanford's B school and I'll teach you about design thinking." So I went with him on a Friday to the d.school, Design School over at Stanford and I was blown away, not just in how design thinking was used to ideate and bring and to explore. But I was blown away about how powerful that concept is when you marry it with data science. What is data science in its simplest sense? Data science is about identifying the variables and metrics that might be better predictors of performance. It's that might phrase that's the real key. And who are the people who have the best insights into what values or metrics or KPIs you might want to test? It ain't the data scientists, it's the subject matter experts on the business side. And when you use design thinking to bring this subject matter experts with the data scientists together, all kinds of magic stuff happens. It's unbelievable how well it works. And all of our projects leverage design thinking. Our whole value engineering process is built around marrying design thinking with data science, around this prioritization, around these concepts of, all ideas are worthy of consideration and all voices need to be heard. And the idea how you embrace ambiguity and diversity of perspectives to drive innovation, it's marvelous. But I feel like I'm a lone voice out in the wilderness, crying out, "Yeah, Tesla gets it, Google gets it, Apple gets it, Facebook gets it." But you know, most other organizations in the world, they don't think like that. They think design thinking is this Wufoo thing. Oh yeah, you're going to bring people together and sing Kumbaya. It's like, "No, I'm not singing Kumbaya. I'm picking their brains because they're going to help make their data science team much more effective and knowing what problems we're going to go after and how I'm going to measure success and progress. >> Maybe that's the next Dean for the next 10 years, the Dean of design thinking instead of data science, and who knew they're one and the same? Well, Bill, that's a super insightful, I mean, it's so, is validated and supported by the trends that we see all over the place, just in terms of democratization, right? Democratization of the tools, more people having access to data, more opinions, more perspective, more people that have the ability to manipulate the data and basically experiment, does drive better business outcomes. And it's so consistent. >> If I could add one thing, Jeff, I think that what's really powerful about design thinking is when I think about what's happening with artificial intelligence or AI, there's all these conversations about, "Oh, AI is going to wipe out all these jobs. Is going to take all these jobs away." And what we're actually finding is that if we think about machine learning, driven by AI and human empowerment, driven by design thinking, we're seeing the opportunity to exploit these economies of learning at the front lines where every customer engagement, every operational execution is an opportunity to gather not only more data, but to gather more learnings, to empower the humans at the front lines of the organization to constantly be seeking, to try different things, to explore and to learn from each of these engagements. I think it's, AI to me is incredibly powerful. And I think about it as a source of driving more learning, a continuous learning and continuously adapting an organization where it's not just the machines that are doing this, but it's the humans who've been empowered to do that. And my chapter nine in my new book, Jeff, is all about team empowerment, because nothing you do with AI is going to matter of squat if you don't have empowered teams who know how to take and leverage that continuous learning opportunity at the front lines of customer and operational engagement. >> Bill, I couldn't set a better, I think we'll leave it there. That's a great close, when is the next book coming out? >> So today I do my second to last final review. Then it goes back to the editor and he does a review and we start looking at formatting. So I think we're probably four to six weeks out. >> Okay, well, thank you so much, congratulations on all the success. I just love how the Dean is really the Dean now, teaching all over the world, sharing the knowledge and attacking some of these big problems. And like all great economics problems, often the answer is not economics at all. It's completely really twist the lens and don't think of it in that, all that construct. >> Exactly. >> All right, Bill. Thanks again and have a great week. >> Thanks, Jeff. >> All right. He's Bill Schmarzo, I'm Jeff Frick. You're watching theCUBE. Thanks for watching, we'll see you next time. (gentle music)

>> Live from Las Vegas. It's the Cube covering Adobe Summit twenty nineteen brought to you by X Ensure Interactive. >> Hey, welcome back, everyone. Day two of live coverage of the Cube here in Las Vegas for Adobe Summit twenty nineteen. I'm John Career with Jeff Brick, Our next guest needing Stallman, managing director of a Censure Interactive. Welcome to the Cube. Thanks for joining us. >> Thank you for having me. >> You can't miss your booth when you walk in. Got a nice set up there. You guys got a big prominent location to show. Tell us about Ascension Interactive. And what you guys doing the show? >> Oh, yeah. So thanks again for having us is a great a great summit. A great conference. It's one of our big kind of showcases for the year. We've got a couple of different experiences Were demo ing this year. We've got some really cool X are experiences that people are coming by the booth and putting device is on and it really interacting with and having fun with. We've got some interesting topics around Trends in content creation, headless content, train three D, etcetera. So some great topix around kind of Howard disrupting marketing and content with our clients today. >> Contest becomes so important now, Not only is it you have content development creatives. You have all kinds of applications now. Integrating was once kind of a cottage industry of creative doing cool stuff. Now that's kind of table stakes. It's a whole another level of cloud computing meets creative, so it's kind of an interesting growth curve right now, you're seeing a lot of adoption, a lot of the kind of tools from Tech in with the creative talk about that dynamic, because that's kind of the whole show here. It's all about not just marketing Cloud, and it's about creative experiences and now the new cool stuff out there and people try to figure out how to do it. I want that dynamic of creative tech coming together. >> Yeah, it's enemy from Accenture Interactive. That's really kind of where we've built our business around having that as a technology company that's really drawing a lot of specific talent to build out that creative tak kind of talent mindset. It's a different way of kind of operating and working and building those experiences, so we're kind of first and foremost and experience agency S O. We're all about building experiences for our clients, and it's a kind of ah maybe unique patch that we've we've carved out for ourselves. To say you have to consider technology is part of it and data and effectiveness and analytics. But then, actually, how do you build experiences that are really engage our customers and be really innovative? So certainly has its center at interactive. That's our That's our remit. And we're working out some really exciting work with clients in that area >> about the difference between center interactive and century proper. Because we've done a lot of enemies with center you guys, we're different talked about. The difference is that you guys have and what what's your mission? >> So it's enter. Active are first and foremost. We are an experience agencies. So again, those experiences could be everything from your typical kind of website experience. And how do you best in engage consumers at your site to commerce? Teo X are so we've got a Z mentioned it, several different applications of experiences and x r that we're demo ing here, and we're working on with our clients, um, a R V r as well as sale stools. So in the centre interactive, we take it, we take a creator first, like what is the experience. We really need to build, do the right type of research and then bring in the design, talent and the unique kind of optimization, talent and technology talent to be able to ensure that whatever we're building for a client is actually scaleable for more than just kind of that one exciting news case they've got. But how do you ensure that that's really going to be the right platform in experience? They can scale for other parts of the enterprise of the parts of the business, etcetera. We're proud of who we are >> seriously, because you guys are involved in a lot of things. You keep saying x r for extended reality, and I think it's interesting because some people think it's got to be one hundred percent immersive or not. But if you guys air pioneering, this is a lot of places to kind of extend reality. Blend the rial and the C g. I. And it kind of had this mixed combo experience. So where people using that what are some of the interesting opportunities beyond no trying on a dress from the computer with your with your avatar that you guys are working on >> right, So so definitely have our share of kind of cool consumer experiences and, you know, wanting interesting. That's things that's happening in the market is consumers. They're expecting as they start to engage with RVR, even like immersive commerce. And, um, you're online configurations for shopping and it kind of configuring your own products. They're expecting the same level of, like, hi and visualization that they're getting in the programs and media that they're consuming at home. So getting that right is that's That's a challenge for a lot of brands, and it's a challenge. And technologies, they're changing pretty rapidly to support that. So we've got an experience here were demo ing this week, which is is really on kind of that high end past, which is allowing your design your own your own bathroom experience with countertops, and it's so realistic that you can literally you feel like you could touch that. You could appreciate the textures. You can touch the experience. So it's it's really helping to kind of give customers give consumers back control, but they don't have to rely on a contractor and other types of design services. They really have many options. They can see what that looks like in their own space. I can do that from the convenience of my home, etcetera, and that's kind of one end around. And it's still consumer facing and how to brands create more amorous of shopping experience and make that pass to purchase easier, effective, faster like and, you know, close well. The other types of experiences that I think you're really, really powerful and really interesting is it's starting to use x r for training purposes. So we just want to go home. Oh, actually at Mobile World Congress for PR experience that we built to train foster care professionals on go on making incredibly complicated is around what to do with families and children and really trained them. So how do you take a very subjective experience and train people for the different scenarios to make the right judgment calls? And so that's an interesting kind of application of X r. We're also doing X are in the field of service service technician, so working on automotives and ensuring your using hand, our virtual technology to be able Tio I understand, is that the right party should be working on and what are the best practices around around, whether it's a home technician that's going out and trying to install our complex device or working at an automotive so >> so practical use cases. And then there's also the glamorous ones, like Game of Thrones. Talk about you guys. The relationship with game of thrones is a dynamic. Their share want the shows so that the Cube we Go game of thrones fan. So you guys were somewhat involved in that Such share. >> Yeah, so on. And it's very timely. Obviously, with the final season coming out of the fourteenth, and for like, super fans like myself, it's It's been an exciting year for us. So, um, Extension Interactive has done a very deliberate Siri's of acquisitions over the past ten years, and last year we acquired MCA Vision. So Maga Vision was renowned internationally for their CD I and special effects work on DH. No. One of the most exciting words they've received is an Emmy for outstanding visual effects for game of thrones. So So you got a lot of buzz at the time saying, What is extension interactive? What's what's the kind of thought process, their game of thrones, visual effects, and it really was all about this idea of, you know, again, consumers are expecting this level of visual and this level of experience in how they're interacting with you. So, Mac, a vision was a very we needed a way to be more innovative and how we're bringing the right talent and capabilities to building X. Our experiences, product configurations, etcetera and maka vision had unique capability around three visualisation CG I visual effects and really that again, that whole package of kind of art and technology to create these very high end visualization experiences. So So it's been a really exciting here for us. Um, and starting to now take that model and start to bring that Teo marketing teams that were working within the brands e commerce teams and starting to say, How do we create these type of >> bond? That >> it's It's a nice looking the MCA vision sight and and some of the you know, they have some of the cool movie stuff. But I was fascinated by the car stuff, right? They have these beautiful car shots for car commercials, and I'm curious after hearing about, you know, a be testing and you know all the things that you could do with your experience in the dental experience. Interactive are seeing that now with I got forty seven versions of that car commercial because now if I'm doing it with Mac Division, I don't have to shoot forty seven versions. I can manipulate the CG I car in a very different way because I know that you said super high gloss, super high glam. But it's programmable, so you can do stuff with it without having to call the team together and hope for a beautiful day in Carmel to go over the bridge. >> Exactly all those variables. So I mean brands right now, as they're trying to kind of create trying tio react and set up models to support hyper personalization programmatic content in it that is so challenging. It's so challenging because traditional >> means of >> going out and doing the shoot that you're talking about and doing. Even product shots and tons of photography like you have to create so many versions so expensive to be able to support all of your products. All the variations when you put global into the mix and you've got different labels and different languages etcetera. So, again, it's a It's a scale problem today. I think a lot of people think it's a technology problem, but it's actually it's actually that that's a solution. But it's definitely it's a human problem. And so in our practice, we focus on content creation models. And so this is why Macrovision acquisition so essential is we were disrupting the way continents created, whether it's for brands and their their commercial spots or it's their commerce content. Or or there social media content. By using this idea of taking a digital twin of, let's say, the Mercedes or the Mercedes car and being able to take engineering data and visualize a product digitally before it even exists before I mean literally, the prototype is not available. You know this amazing flexibility. Teo certainly configure that in many different ways, digitally. For these shoots, all you need is some some background in Madrid, etcetera, to be able to roll the car through, um, and Tamar and Magic. But you're able, Tio, you're now able Teo, represent that product, get your media created and put it into market to start generating buzz presales, et cetera. I mean, that's that's so powerful. You're getting ahead of product launch. >> How did how are the cost dynamics changing? Because before you said, it's expensive to do is shoot Yes, but now you can do multiple flavors within the computer is just radically different economics, because I'm sure when they come in and say, I want you guys to game of thrones I want that kind of production value like, yeah, that's really the expectancy. Yeah, To do it in software is a completely different kind of approach. >> I mean, I don't know how brands are not going to give it to this model because they cannot possibly they cannot. They're goingto exponential cross to be able Teo, keep pace with again, even just the variation of product, much less starting to now. Personalize that or be ableto dynamically. Render that so. The cost model today is is is exorbitant, and it's just growing. And so this because you're now able to configure things digitally and again used the right tools to be able tio represent different versions of product changed. The backgrounds, change, change, any of the factors that you need to be able to say this is a new piece of content that. I think it's better targeted at this segment. You want to test that out a little bit. I don't want to kind of double down on that and ending for all of that cost to go do this. You gives you a ton of flexibility, especially, and how you're bringing you no talent in wants to shoot it once and then and that enviable to swap. For example, I may change the bracelet on the talent to do five different ads out instead of >> risk management to a swells testing. Knowing what you're looking at, getsem visibility into what success looks like then, kind of figuring it out. One thing I want to ask you is that in the tech business, we've always been fascinated by Moore's law doubling the speed of the processors. That's Intel thing. But if you look at what you guys do with the game of thrones on the high end with CG, I see the C g I and all the cool stuff. The experiences that people have today become the expectations or the expectations become the new experiences. So you've seen an accelerated user experience. Visually, you got gaming, culture, gaming environments. I mean fortnight wasn't around two years ago. Right? Half the world pretty much plays the game or you got game of thrones. So he's now will soon become table stakes, these kinds of experience. So I got to see where you guys are going with that. How does that change how you guys operate because you gotta look at the expectations of the users consumer. That might be the new experience. How to figure out that dynamic is challenging. How do you guys do that? What's the What's the guiding philosophy around that? That trend? >> Yes. So we have, um we're maniacal about ensuring that the experience for designing is really well thought through with the right research in the right input from us. We're on the right contact. So while it may sound like a great idea and it may sound like something you need, like, how do we make sure we're doing the right thing? Right? Diligence, Tio to build the red experience and represent the product in the right way. And then we also a maniacal on the back end of testing and after optimizing that so being very realistic about is it effective is a driving is driving. Whatever the K p I is, even if it's just innovation, is it driving the KP eyes, uh, that you need and then adjusting? Because nothing could be stagnant? He's >> super exciting area. I mean, there's so much opportunity and change going on. Awesome final questions about the relationship with the job You guys are here. Adobes got a whole growth strategy in front, and that looks really strongly gotta cloud technology platform. Now they're integrating data across multiple their modules in their suites. How does that impact you guys? What's your relationship with Adobe? Yes, >> so we are. We are very big partner of Adobe. We've had a accolades throughout the years of being partner of the year. So we have a large practice dedicated Teo helping clients really look at how to implement the stack howto build content and campaign delivery models on top of that. So it's, um, both the technology and an implement implementation focus, but quite frankly, and I think what's unique is a is a process and kind of how do you operational as that focus? Like I said, you know, everyone's talking about atomic comic, the atomic content these days and certainly, I mean the adobe stack. Absolutely. Khun support that And really power personalized dynamic content for you is a brand but operational operational izing. That is a totally different story. So we're really working with the Adobe team closely on with our customers. Tio kind of build the model on top of the stack and say, How do you need to change your organization to really, really get the value out of out of these tools and really deliver the experiences that are going to be differentiated? >> We've heard that all along all week here and other events we go to is that it's not the tech problem. It's these new capabilities being operationalized older cultures as a people process problem. >> Yeah, it seems >> to be the big, big story. >> It's a it's it's. And I would say it's an ongoing challenge for the brands we work within, and they're constantly getting additional. Um, uh, market demands to be able to kind of continue changing their model. Like I said, programmatic particularly and hyper personalization is is really putting that into practice is is >> great practice Navy. Thanks for coming on. Sharing your insights here on the I do appreciate it. Thank you very much >> for having me >> live coverage here in Dopey Summit twenty nineteen in Las Vegas. To keep coverage day to continue. Stay with us for more after this short break.

>> Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their Ecosystem partners. >> Oh welcome back, to theCUBE. Continuing coverage here from AWS re:Invent, as we start to wind down our coverage here on the second day. We'll be here tomorrow as well, live on theCUBE, bringing you interviews from Hall D at the Sands Expo. Along with Justin Warren, I'm John Walls, and we're joined by Jonathan Ballon, who's the Vice President of the internet of things at Intel. Jonathan, thank you for being with us today. Good to see you, >> Thanks for having me guys. >> All right, interesting announcement today, and last year it was all about DeepLens. This year it's about DeepRacer. Tell us about that. >> What we're really trying to do is make AI accessible to developers and democratize various AI tools. Last year it was about computer vision. The DeepLens camera was a way for developers to very inexpensively get a hold of a camera, the first camera that was a deep-learning enabled, cloud connected camera, so that they could start experimenting and see what they could do with that type of device. This year we took the camera and we put it in a car, and we thought what could they do if we add mobility to the equation, and specifically, wanted to introduce a relatively obscure form of AI called reinforcement learning. Historically this has been an area of AI that hasn't really been accessible to most developers, because they haven't had the compute resources at their disposal, or the scale to do it. And so now, what we've done is we've built a car, and a set of tools that help the car run. >> And it's a little miniature car, right? I mean it's a scale. >> It's 1/118th scale, it's an RC car. It's four-wheel drive, four-wheel steering. It's got GPS, it's got two batteries. One that runs the car itself, one that runs the compute platform and the camera. It's got expansion capabilities. We've got plans for next year of how we can turbo-charge the car. >> I love it. >> Right now it's baby steps, so to speak, and basically giving the developer the chance to write a reinforcement learning model, an algorithm that helps them to determine what is the optimum way that this car can move around a track, but you're not telling the car what the optimum way is, you're letting the car figure it out on their own. And that's really the key to reinforcement learning is you don't need a large dataset to begin with, it's pre-trained. You're actually letting, in this case, a device figure it out for themselves, and this becomes very powerful as a tool, when you think about it being applied to various industries, or various use-cases, where we don't know the answer today, but we can allow vast amounts of computing resources to run a reinforcement model over and over, perhaps millions of times, until they find the optimum solution. >> So how do you, I mean that's a lot of input right? That's a lot, that's a crazy number of variables. So, how do you do that? So, how do you, like in this case, provide a car with all the multiple variables that will come into play. How fast it goes, and which direction it goes, and all that, and on different axes and all those things, to make these own determinations, and how will that then translate to a real specific case in the workplace? >> Well, I mean the obvious parallel is of course autonomous driving. AWS had Formula One on stage today during Andy Jassy's keynote, that's also an Intel customer, and what Formula One does is they have the fastest cars in the world, and they have over 120 sensors on that car that are bringing in over a million pieces of data per second. Being able to process that vast amount of data that quickly, which includes a variety of data, like it's not just, it's also audio data, it's visual data, and being able to use that to inform decisions in close to real time, requires very powerful compute resources, and those resources exist both in the cloud as well as close to the source of the data itself at the edge, in the physical environment. >> So, tell us a bit about the software that's involved here, 'cause people think of Intel, you know that some people don't know about the software heritage that Intel has. It's not just about, the Intel inside isn't just the hardware chips that's there, there's a lot of software that goes into this. So, what's the Intel angle here on the software that powers this kind of distributed learning. >> Absolutely, software is a very important part of any AI architecture, and for us we've a tremendous amount of investment. It's almost perhaps, equal investment in software as we do in hardware. In the case of what we announced today with DeepRacer and AWS, there's some toolkits that allow developers to better harness the compute resources on the car itself. Two things specifically, one is we have a tool called, RL Coach or Reinforcement Learning Coach, that is integrated into SageMaker, AWS' machine learning toolkit, that allows them to access better performance in the cloud of that data that's coming into the, off their model and into their cloud. And then we also have a toolkit called OpenVINO. It's not about drinking wine. >> Oh darn. >> Alright. >> Open means it's an opensource contribution that we made to the industry. Vino, V-I-N-O is Visual Inference and Neural Network Optimization, and this is a powerful tool, because so much of AI is about harnessing compute resources efficiently, and as more and more of the data that we bring into our compute environments is actually taking place in the physical world, it's really important to be able to do that in a cost-effective and power-efficient way. OpenVINO allows developers to actually isolate individual cores or an integrated GPU on a CPU without knowing anything about hardware architecture, and it allows them then to apply different applications, or different algorithms, or inference workloads very efficiently onto that compute architecture, but it's abstracted away from any knowledge of that. So, it's really designed for an application developer, who maybe is working with a data scientist that's built a neural network in a framework like TensorFlow, or Onyx, or Pytorch, any tool that they're already comfortable with, abstract away from the silicon and optimize their model onto this hardware platform, so it performs at orders of magnitude better performance then what you would get from a more traditional GPU approach. >> Yeah, and that kind of decision making about understanding chip architectures to be able to optimize how that works, that's some deep magic really. The amount of understanding that you would need to have to do that as a human is enormous, but as a developer, I don't know anything about chip architectures, so it sounds like the, and it's a thing that we've been hearing over the last couple of days, is these tools allow developers to have essentially superpowers, so you become an augmented intelligence yourself. Rather than just giving everything to an artificial intelligence, these tools actually augment the human intelligence and allow you to do things that you wouldn't otherwise be able to do. >> And that's I think the key to getting mass market adoption of some of these AI implementations. So, for the last four or five years since ImageNet solved the image recognition problem, and now we have greater accuracy from computer models then we do from our own human eyes, really AI was limited to academia, or large IT tech companies, or proof-of-concepts. It didn't really scale into these production environments, but what we've seen over the couple of years is really a democratization of AI by companies like AWS and Intel that are making tools available to developers, so they don't need to know how to code in Python to optimize a compute module, or they don't need to, in many cases, understand the fundamental underlying architectures. They can focus on whatever business problem they're tryin' to solve, or whatever AI use-case it is that they're working on. >> I know you talked about DeepLens last year, and now we've got DeepRacer this year, and you've got the contest going on throughout this coming year with DeepRacer, and we're going to have a big race at the AWS re:Invent 2019. So what's next? I mean, or what are you thinking about conceptually to, I guess build on what you've already started there? >> Well, I can't reveal what next years, >> Well that I understand >> Project will be. >> But generally speaking. >> But what I can tell you, what I can tell you is what's available today in these DeepRacer cars is a level playing field. Everyone's getting the same car and they have essentially the same tool sets, but I've got a couple of pro-tips for your viewers if they want to win some of these AWS Summits that are going to be around the world in 2019. Two pro-tips, one is they can leverage the OpenVINO toolkit to get much higher inference performance from what's already on that car. So, I encourage them to work with OpenVINO. It's integrated into SageMaker, so that they have easy access to it if they're an AWS developer, but also we're going to allow an expansion of, almost an accelerator of the car itself, by being able to plug in an Intel Neural Compute Stick. We just released the second version of this stick. It's a USB form factor. It's got a Movidius Myriad X Vision processing unit inside. This years version is eight times more powerful than last years version, and when they plug it into the car, all of that inference workload, all of those images, and information that's coming off those sensors will be put onto the VPU, allowing all the CPU, and GPU resources to be used for other activities. It's going to allow that car to go at turbo speed. >> To really cook. >> Yeah. (laughing) >> Alright, so now you know, you have no excuse, right? I mean Jonathan has shared the secret sauce, although I still think when you said OpenVINO you got Justin really excited. >> It is vino time. >> It is five o'clock actually. >> Alright, thank you for being with us. >> Thanks for having me guys. >> And good luck with DeepRacer for the coming year. >> Thank you. >> It looks like a really, really fun project. We're back with more, here at AWS re:Invent on theCUBE, live in Las Vegas. (rhythmic digital music)

>> From Tavern on the Green in Central Park, New York it's theCUBE. Covering Veritas Vision Solution Day, brought to you by Veritas. >> Welcome back to New York City everybody. We're here in the heart of Central Park at Tavern On the Green, a beautiful facility. I'm surrounded by Yankee fans so I'm like a fish out of water. But that's okay, it's a great time of the year. We love it, we're still in it up in Boston so we're happy. Dave Vellante here, you're watching theCUBE, the leader in live tech coverage. Nathan Hall is here, he's the field CTO at Pure Storage. Nathan, good to see you. >> Good to see you too. >> Thanks for coming on. >> Thanks. >> So you guys made some announcements today with Veritas, what's that all about? >> It's pretty exciting and Veritas, being the market leader in data protection software. Now our customers are able to take Veritas's net backup software and use it to drive the policy engine of Snapshots for our FlashArrays. They're also able to take Veritas and back up our data hub, which is our new strategy with FlashBlade to really unify all of data analytics onto a single platform. So Veritas really is the solution net back up that's able to back up all the workloads and Pure is the solution that's able to run all the workloads. >> So what if I could follow-up on that, maybe push you a little bit? A lot of these announcements that you see, we call them Barney deals, I love you, you love me, we go to market together and everything's wonderful. Are we talking about deeper integration than that or is just kind of press release? >> Absolutely deeper integration. So you'll see not just how-to guides, white papers, et cetera, but there's actual engineering-level integration that's happening here. We're available as an advanced disk target within that back up, we've integrated into CloudPoint as well. We certify all of our hardware platforms with Veritas. So this is deep, deep engineering-level integration. >> Yeah, we're excited about Pure, we followed you guys since the early days. You know we saw Scott Dietzen, what he built, very impressive modern architecture, you won't be a legacy for 20, 25 years so you've got a lot going for you. Presumably it's easier to integrate with such a modern architecture, but now at the same time you got to integrate with Veritas, it's been around for about 25 years. We heard a lot about how they're investing in API-based architectures, and microservices, and containers and the like, so what is that like in terms of integrating with a 25-year-old company? >> Well I think, from Pure's perspective we are API first, we're RESTfull APIs first. We've done a ton of integrations across multiple platforms whether it's Kubernetes, Docker, VMware, et cetera, so we have a lot of experience in terms of how to integrate with various flavors of other infrastructure. I think Veritas has done a lot of work as well in terms of maturing their API to really be this kind of cloud-first type of API, this RESTful API, that made our cross-integration much easier. >> You guys like being first, there were a number of firsts, you guys were kind of the first, or one of the first with flash for block. You were kind of the first for file. You guys have hit AI pretty hard, everybody's now doing that. You guys announced the first partnership with NVIDIA, everybody's now doing that. (laughs) You guys announced giving away NVME as part of the Stack for no upcharge, everybody's now doing that. So, you like to be first. Culturally, you've worked at some other companies, what's behind that? >> Well culturally, this is best company I've worked at in terms of culture, period, and really it all starts with the culture of the company. I think that's why we're first in so many places and it's not just first in terms of first to market. It's really about first in terms of customer feedback. If you look at the Gartner Magic Quadrant we're up, we've been at leaders quadrant for five years in a row. But this year, we're indisputably the leader. Furthest to the right on the X-axis, furthest north on the Y-axis and that's all driven by just a customer-obsessed culture. We've got a Net Promoter Score of 86.6 which is stratospheric. It's something that puts us in the top 1% of all business-to-business companies, not just tech companies. So, it's really that culture about customer obsession that drives us to be first. Both to market, in a lot of cases, but also just first in terms of customer perception of our technology. >> You guys were a first at really escape velocity, the billion dollar unicorn status, and now you're kind of having that fly-wheel effect where you're able to throw off different innovations in different areas. Can you talk more about the data hub and the relevance to what you're doing with Veritas and data protection? Let's unpack that a little bit. >> Sure, sure, the data hub, we had a great keynote this morning with Jyothi the VP of Marketing for Veritas and he had an interesting customer tidbit. He had some sort of unnamed government agency customer that actually gets penalized when they're unable to retrieve data fast enough. That's not something that many of our customers have, but they do get penalized in terms of opportunity costs. The reason why is 'cause customers just have their data siloed into all these different split-up locations and that prevents them from being able to get insight out of that data. If you look at AI luminaries like Andrew Ng or even people like Dominique Brezinski at Apple, they all agree that you have to, in order to be successful with your data strategy, you have to unify these data silos. And that's what the data hub does. For the first time we're able to unify everything from data warehousing, to data lakes, to streaming analytics, to AI and now even backup all onto a single platform with multidimensional performance. That's FlashBlade and that is our data hub, we think it's revolutionary and we're challenging the rest of the storage industry to follow suit. Let's make less silos, let's unify the data into a data hub so that our customers can get real actionable information out of their data. >> I was on a crowd chat the other day, you guys put out an open letter to the storage community, an open challenge, so that was kind of both a little controversial but also some fun. That's a very important point you're making about sort of putting data at the core. I make an observation, it's not so much true about Facebook anymore 'cause after the whole fake news thing their market value dropped. But if you look at the top five companies in terms of market value, include Facebook in there, they and Berkshire keep doing this, but let's assume for a second that Facebook's up there. Apple, Google, Facebook, Microsoft, and Amazon, top five in terms of US market value. Of course markets ebb and they flow, but it's no coincidence that those are data companies. They all have a lot of hard assets at those companies. They've got data at their core so it's interesting to hear you talk about data hub because one of the challenges that we see for traditional companies, call them incumbents, is they have data in stovepipes. For them to compete they've got to put it in the digital world, they've got to put data at their core. It's not just for start-ups and people doing Greenfield, it's for folks that are established and don't want to get disrupted. Long-winded question, how do they get, let's think of traditional company, an incumbent company, how do they get from point A to point B with the data hub? >> I think Andrew Ng has a great talked-point on this. He basically talks about your data strategy and you need to think about, as a company, how do you acquire data and then how do you unify into a single data hub? It's not just around putting it on a single platform, such as FlashBlade. A valuable byproduct of that is if you have all the stove-piped data, though you probably in terms of your data scientist trying to get access to it, now have to, they have 10 different stovepipes you've got 10 different VPs that you have to go talk to in order to get access to that data. So it really starts with stopping the bleeding and starting to have a data strategy around how do we acquire and how do we make certain or storing data in the same place and have a single unified data hub in order to maximize the value we are able to get out of that data. >> You know when I talked to, I'll throw my two cents in, I talk to a lot of chief data officers. To me, the ones that are most insightful talk about their five imperatives. First of all, is they got to understand how data contributes to monetization. Whether it's saving money or making money, it's not necessarily selling your data. I think a lot of people make that mistake, oh I'm going to monetize my data, I mean I'm going to sell my data, no, it's all about how it contributes to value. The second is, what about data sources? And then how do I get access to data sources? There's a lot implied there in terms of governance and security and who has access to that. And in the same time, how do I scale up my business so that I get the right people who can act on that data? Then how do I form relationships with a line of business so that I can maximize that monetization? Those are, I think, sensible steps that aren't trivial. They require a lot of thought and a lot of cultural change and I would imagine that's what a lot of your customers are going through right now. >> I think they are and I think as IT practitioners out there, I think that we have a duty to get closer to our business and be able to kind of educate them around these data strategies. To give them the same level of insight that you're talking about, you see in some chief data officers. But if I looked out at the, there's a recent study on the Fortune 50, the CXOs, and these aren't even CIOs, they're actually, we think as IT practitioners that the cloud is the most disruptive thing that we see, but the CEOs and the CFOs are actually five times more likely to talk about AI and data as being more disruptive to their business. But most of them have no data strategy, most of them don't know how AI works. It's up to us as IT practitioners to educate the business. To say here's what's possible, here's what we have to do in order to maximize the value out of data, so that you can get a business advantage out of this. It's incumbent on us as IT leaders. >> So Nathan, I think again, that's really insightful because let's face it, if you're moving at the speed of the CIO, which is what many companies want to do, because that's the so called, fat middle and that's where the money is. But you're behind, I mean we're moving into a new era, the cloud era, no pun intended, is here, it's solid but we're entering that data of machine intelligence and we built the foundation with the dupe even, there's a lot of data now what do we do with it? We see, and I wonder if you could comment on this, is the innovation engine of the future changing it? It use to be Moore's Law, we marched to the cadence of Moore's Law for years. Now it's data applying machine intelligence and then, of course, using the cloud for scale and attracting start-ups and innovation. That's fine because we want to program infrastructure, we don't want to deploy infrastructure. If you think about Pure, you got data for sure. You're going hard after machine intelligence. And cloud, if I understand your cloud play, you sell to cloud providers whether they're on-prem or in the public cloud but what do you think about those? That innovation sandwich that I just described and how do you guys play? >> Well, cloud is where we get over 30% of our revenue so we're actually selling to the cloud, cloud service providers, et cetera. For example, one of the biggest cloud service providers out there that I think today's announcement helps them out a lot from a policy perspective actually used FlashBlade to reduce their SLAs, to reduce their restore time from, I think, it was 30 hours down to 38 minutes. They were paying money before to their customers. What we see in our cloud strategy is one of empowering cloud providers, but also we think that cloud is increasingly, at the infrastructure layer, going to be commoditized and it's going to be about how do we enable multicloud? So how do we enable customers to get around data gravity problems? I've got this big, weighty database that I want to see if I can move it up to the cloud but that takes me forever. So how do we help customers be able to move to one cloud or even exit a cloud to another or back to on-prem? We think there's a lot of value in applying our, for example deduplication technology, et cetera, to helping customers with those data gravity problems, to making a more open world in terms of sharing data to and from the cloud. >> Great, well we looked at Pure and Veritas getting together, do some hard core engineering, going to market, solving some real problems. Thanks Nathan for hanging out, this iconic beautiful Tavern on the Green in the heart of New York City. Appreciate you coming on theCUBE. >> Thanks Dave. >> All right, keep it right there everybody, Dave Vallante. We'll be right back right after this short break. You're watching theCUBE from Veritas Solutions Day, #VeritasVision, be right back. (digital music)

For Las Vegas, it's the cube covering vm world 2018, brought to you by vm ware and its ecosystem partners. Ladies and gentlemen, Vm ware would like to thank it's global diamond sponsors and it's platinum sponsors for vm world 2018 with over 125,000 members globally. The vm ware User Group connects via vmware customers, partners and employees to vm ware, information resources, knowledge sharing, and networking. To learn more, visit the [inaudible] booth in the solutions exchange or the hemoglobin gene vm village become a part of the community today. This presentation includes forward looking statements that are subject to risks and uncertainties. Actual results may differ materially as a result of various risk factors including those described in the 10 k's 10 q's and k's vm ware. Files with the SEC. Ladies and Gentlemen, please welcome Pat Gelsinger. Welcome to vm world. Good morning. Let's try that again. Good morning and I'll just say it is great to be here with you today. I'm excited about the sixth year of being CEO. When it was on this stage six years ago were Paul Maritz handed me the clicker and that's the last he was seen. We have 20,000 plus here on site in Vegas and uh, you know, on behalf of everyone at Vm ware, you know, we're just thrilled that you would be with us and it's a joy and a thrill to be able to lead such a community. We have a lot to share with you today and we really think about it as a community. You know, it's my 23,000 plus employees, the souls that I'm responsible for, but it's our partners, the thousands and we kicked off our partner day yesterday, but most importantly, the vm ware community is centered on you. You know, we're very aware of this event would be nothing without you and our community and the role that we play at vm wares to build these cool breakthrough innovations that enable you to do incredible things. You're the ones who take our stuff and do amazing things. You altogether. We have truly changed the world over the last two decades and it is two decades. You know, it's our anniversary in 1998, the five people that started a vm ware, right. You know, it was, it was exactly 20 years ago and we're just thrilled and I was thinking about this over the weekend and it struck me, you know, anniversary, that's like old people, you know, we're here, we're having our birthday and it's a party, right? We can't have a drink yet, but next year. Yeah. We're 20 years old. Right. We can do that now. And I'll just say the culture of this community is something that truly is amazing and in my 38 years, 38 years in tech, that sort of sounds like I'm getting old or something, but the passion, the loyalty, almost a cult like behavior that we see in this team of people to us is simply thrilling. And you know, we put together a little video to sort of summarize the 20 years and some of that history and some of the unique and quirky aspects of our culture. Let's watch that now. We knew we had something unique and then we demonstrated that what was unique was also some reasons that we love vm ware, you know, like the community out there. So great. The technology I love it. Ware is solid and much needed. Literally. I do love Vmr. It's awesome. Super Awesome. Pardon? There's always someone that wants to listen and learn from us and we've learned so much from them as well. And we reached out to vm ware to help us start building. What's that future world look like? Since we're doing really cutting edge stuff, there's really no better people to call and Bmr has been known for continuous innovation. There's no better way to learn how to do new things in it than being with a company that's at the forefront of technology. What do you think? Don't you love that commitment? Hey Ashley, you know, but in the prep sessions for this, I thought, boy, what can I do to take my commitment to the next level? And uh, so, uh, you know, coming in a couple days early, I went to down the street to bad ass tattoo. So it's time for all of us to take our commitment up level and sometimes what happens in Vegas, you take home. Thank you. Vm Ware has had this unique role in the industry over these 20 years, you know, and for that we've seen just incredible things that have happened over this period of time and it's truly extraordinary what we've accomplished together. And you know, as we think back, you know, what vm ware has uniquely been able to do is I'll say bridge across know and we've seen time and again that we see these areas of innovation emerging and rapidly move forward. But then as they become utilized by our customers, they create this natural tension of what business wants us flexibility to use across these silos of innovation. And from the start of our history, we have collectively had this uncanny ability to bridge across these cycles of innovation. You know, an act one was clearly the server generation. You know, it may seem a little bit, uh, ancient memory now, but you remember you used to walk into your data center and it looked like the loove the museum of it passed right? You know, and you had your old p series and your z series in your sparks and your pas and your x86 cluster and Yo, it had to decide, well, which architecture or am I going to deploy and run this on? And we bridged across and that was the magic of Esx. You don't want to just changed the industry when that occurred. And I sort of called the early days of Esx and vsphere. It was like the intelligence test. If you weren't using it, you fail because Yup. Servers, 10 servers become one months, become minutes. I still have people today who come up to me and they reflect on their first experience of vsphere or be motion and it was like a holy moment in their life and in their careers. Amazing and act to the Byo d, You know, can we bridge across these devices and users wanted to be able to come in and say, I have my device and I'm productive on it. I don't want to be forced to use the corporate standard. And maybe more than anything was the power of the iphone that was introduced, the two, seven, and suddenly every employee said this is exciting and compelling. I want to use it so I can be more productive when I'm here. Bye. Jody was the rage and again it was a tough challenge and once again vm ware helped to bridge across the surmountable challenge. And clearly our workspace one community today is clearly bridging across these silos and not just about managing devices but truly enabling employee engagement and productivity. Maybe act three was the network and you know, we think about the network, you know, for 30 years we were bound to this physical view of what the network would be an in that network. We are bound to specific protocols. We had to wait months for network upgrades and firewall rules. Once every two weeks we'd upgrade them. If you had a new application that needed a firewall rule, sorry, you know, come back next month we'll put, you know, deep frustration among developers and ceos. Everyone was ready to break the chains. And that's exactly what we did. An NSX and Nice Sierra. The day we acquired it, Cisco stock drops and the industry realizes the networking has changed in a fundamental way. It will never be the same again. Maybe act for was this idea of cloud migration. And if we were here three years ago, it was student body, right to the public cloud. Everything is going there. And I remember I was meeting with a cio of federal cio and he comes up to me and he says, I tried for the last two years to replatform my 200 applications I got to done, you know, and all of a sudden that was this. How do I do cloud migration and the effective and powerful way. Once again, we bridged across, we brought these two worlds together and eliminated this, uh, you know, this gap between private and public cloud. And we'll talk a lot more about that today. You know, maybe our next act is what we'll call the multicloud era. You know, because today in a recent survey by Deloitte said that the average business today is using eight public clouds and expected to become 10 plus public clouds. And you know, as you're managing different tools, different teams, different architectures, those solution, how do you, again bridge across, and this is what we will do in the multicloud era, we will help our community to bridge across and take advantage of these powerful cycles of innovation that are going on, but be able to use them across a consistent infrastructure and operational environment. And we'll have a lot more to talk about on this topic today. You know, and maybe the last item to bridge across maybe the most important, you know, people who are profit. You know, too often we think about this as an either or question. And as a business leader, I'm are worried about the people or the And Milton Friedman probably set us up for this issue decades ago when he said, planet, right? the sole purpose of a business is to make profits. You want to create a multi-decade dilemma, right? For business leaders, could I have both people and profits? Could I do well and do good? And particularly for technology, I think we don't have a choice to think about these separately. We are permeating every aspect of business. And Society, we have the responsibility to do both and have all the things that vm ware has accomplished. I think this might be the one that I'm most proud of over, you know, w we have demonstrated by vsphere and the hypervisor alone that we have saved over 540 million tons of co two emissions. That is what you have done. Can you believe that? Five hundred 40 million tons is enough to have 68 percent of all households for a year. Wow. Thank you for what you have done. Thank you. Or another translation of that. Is that safe enough to drive a trillion miles and the average car or you could go to and from Jupiter just in case that was in your itinerary a thousand times. Right? He was just incredible. What we have done and as a result of that, and I'll say we were thrilled to accept this recognition on behalf of you and what you have done. You know, vm were recognized as number 17 in the fortune. Change the world list last week. And we really view it as accepting this honor on behalf of what you have done with our products and technology tech as a force for good. We believe that fundamentally that is our opportunity, if not our obligation, you know, fundamentally tech is neutral, you know, we together must shape it for good. You know, the printing press by Gutenberg in 1440, right? It was used to create mass education and learning materials also can be used for extremist propaganda. The technology itself is neutral. Our ecosystem has a critical role to play in shaping technology as a force for good. You know, and as we think about that tomorrow, we'll have a opportunity to have a very special guest and I really encourage you to be here, be on time tomorrow morning on the stage and you know, Sanjay's a session, we'll have Malala, Nobel Peace Prize winner and fourth will be a bit of extra security as you come in and you understand that. And I just encourage you not to be late because we see this tech being a force for good in everything that we do at vm ware. And I hope you'll enjoy, I'm quite looking forward to the session tomorrow. Now as we think about the future. I like to put it in this context, the superpowers of tech know and you know, 38 years in the industry, you know, I am so excited because I think everything that we've done over the last four decades is creating a foundation that allows us to do more and go faster together. We're unlocking game, changing opportunities that have not been available to any people in the history of humanity. And we have these opportunities now and I, and I think about these four cloud, you have unimaginable scale. You'll literally with your Amex card, you can go rent, you know, 10,000 cores for $100 per hour. Or if you have Michael's am ex card, we can rent a million cores for $10,000 an hour. Thanks Michael. But we also know that we're in many ways just getting started and we have tremendous issues to bridge across and compatible clouds, mobile unprecedented scale. Literally, your application can reach half the humans on the planet today. But we also know that five percent, the lowest five percent of humanity or the other half of humanity, they're still in the lower income brackets, less than five percent penetrated. And we know that we have customer examples that are using mobile phones to raise impoverished farmers in Africa, out of poverty just by having a smart phone with proper crop, the information field and whether a guidance that one tool alone lifting them out of poverty. Ai knows, you know, I really love the topic of ai in 1986. I'm the chief architect of the 80 46. Some of you remember what that was. Yeah, I, you know, you're, you're my folk, right? Right. And for those of you who don't, it was a real important chip at the time. And my marketing manager comes running into my office and he says, Pat, pat, we must make the 46 a great ai chip. This is 1986. What happened? Nothing an AI is today, a 30 year overnight success because the algorithms, the data have gotten so much bigger that we can produce results, that we can bring intelligence to everything. And we're seeing dramatic breakthroughs in areas like healthcare, radiology, you know, new drugs, diagnosis tools, and designer treatments. We're just scratching the surface, but ai has so many gaps, yet we don't even in many cases know why it works. Right? And we'll call that explainable ai and edge and Iot. We're connecting the physical and the digital worlds was never before possible. We're bridging technology into every dimension of human progress. And today we're largely hooking up things, right? We have so much to do yet to make them intelligent. Network secured, automated, the patch, bringing world class it to Iot, but it's not just that these are super powers. We really see that each and each one of them is a super power in and have their own right, but they're making each other more powerful as well. Cloud enables mobile conductivity. Mobile creates more data, more data makes the AI better. Ai Enables more edge use cases and more edge requires more cloud to store the data and do the computing right? They're reinforcing each other. And with that, we know that we are speeding up and these superpowers are reshaping every aspect of society from healthcare to education, the transportation, financial institutions. This is how it all comes together. Now, just a simple example, how many of you have ever worn a hardhat? Yeah, Yo. Pretty boring thing. And it has one purpose, right? You know, keep things from smacking me in the here's the modern hardhat. It's a complete heads up display with ar head. Well, vr capabilities that give the worker safety or workers or factory workers or supply people the ability to see through walls to understand what's going on inside of the equipment. I always wondered when I was a kid to have x Ray Vision, you know, some of my thoughts weren't good about why I wanted it, but you know, I wanted to. Well now you can have it, you know, but imagine in this environment, the complex application that sits behind it. You know, you're accessing maybe 50 year old building plants, right? You're accessing HVAC systems, but modern ar and vr capabilities and new containerized displays. You'll think about that application. You know, John Gage famously said the network is the computer pat today says the application is now a network and pretty typically a complicated one, you know, and this is the vm ware vision is to make that kind of environment realizable in every aspect of our business and community and we simply have been on this journey, any device, any application, any cloud with intrinsic security. And this vision has been consistent for those of you who have been joining us for a number of years. You've seen this picture, but it's been slowly evolving as we've worked in piece by piece to refine and extend this vision, you know, and for it, we're going to walk through and use this as the compass for our discussion today as we walk through our conversation. And you know, we're going to start by a focus on any cloud. And as we think about this cloud topic, you know, we see it as a multicloud world hybrid cloud, public cloud, but increasingly seeing edge and telco becoming clouds in and have their own right. And we're not gonna spend time on it today, but this area of Telco to the is an enormous opportunity for us in our community. You know, data centers and cloud today are over 80 percent virtualized. The Telco network is less than 10 percent virtualized. Wow. An industry that's almost as big as our industry entirely unvirtualized, although the technologies we've created here can be applied over here and Telco and we have an enormous buildout coming with five g and environments emerging. What an opportunity for us, a virgin market right next to us and we're getting some early mega winds in this area using the technologies that you have helped us cure rate than the So we're quite excited about this topic area as well. market. So let's look at this full view of the multicloud. Any cloud journey. And we see that businesses are on a multicloud journey, you know, and today we see this fundamentally in these two paths, a hybrid cloud and a public cloud. And these paths are complimentary and coexisting, but today, each is being driven by unique requirements and unique teams. Largely the hybrid cloud is being driven by it. And operations, the public cloud being driven more by developers and line of business requirements and as some multicloud environment. So how do we deliver upon that and for that, let's start by digging in on the hybrid cloud aspect of this and as we think about the hybrid cloud, we've been talking about this subject for a number of years and I want to give a very specific and crisp definition. You're the hybrid cloud is the public cloud and the private cloud cooperating with consistent infrastructure and consistent operations simply put seamless path to and from the cloud that my workloads don't care if it's here or there. I'm able to run them in a agile, scalable, flexible, efficient manner across those two environments, whether it's my data center or someone else's, I can bring them together to make that work is the magic of the Vm ware Cloud Foundation. The vm ware Cloud Foundation brings together computer vsphere and the core of why we are here, but combines with that networking storage delivered through a layer of management and automation. The rule of the cloud is ruthlessly automate everything. We laid out this vision of the software defined data center seven years ago and we've been steadfastly working on this vision and vm ware. Cloud Foundation provides this consistent infrastructure and operations with integrated lifecycle management automation. Patching the m ware cloud foundation is the simplest path to the hybrid cloud and the fastest way to get vm ware cloud foundation is hyperconverged infrastructure, you know, and with this we've combined integrated then validated hardware and as a building block inside of this we have validated hardware, the v Sand ready environments. We have integrated appliances and cloud delivered infrastructure, three ways that we deliver that integrate integrated hyperconverged infrastructure solution. And we have by far the broadest ecosystem of partners to do it. A broad set of the sand ready nodes from essentially everybody in the industry. Secondly, we have integrated appliances, the extract of vxrail that we have co engineered with our partners at Dell technology and today in fact Dell is releasing the power edge servers, a major step in blade servers that again are going to be powering vxrail and vxrack systems and we deliver hyperconverged infrastructure through a broader set of Vm ware cloud partners as well. At the heart of the hyperconverged infrastructure is v San and simply put, you know, be San has been the engine that's just been moving rapidly to take over the entire integration of compute and storage and expand to more and more areas. We have incredible momentum over 15,000 customers for v San Today and for those of you who joined us, we say thank you for what you have done with this product today. Really amazing you with 50 percent of the global 2000 using it know vm ware. V San Vxrail are clearly becoming the standard for how hyperconverge is done in the industry. Our cloud partner programs over 500 cloud partners are using ulv sand in their solution, you know, and finally the largest in Hci software revenue. Simply put the sand is the software defined storage technology of choice for the industry and we're seeing that customers are putting this to work in amazing ways. Vm Ware and Dell technologies believe in tech as a force for good and that it can have a major impact on the quality of life for every human on the planet and particularly for the most underdeveloped parts of the world. Those that live on less than $2 per day. In fact that this moment 5 billion people worldwide do not have access to modern affordable surgery. Mercy ships is working hard to change the global surgery crisis with greater than 400 volunteers. Mercy ships operates the largest NGO hospital ship delivering free medical care to the poorest of the poor in Africa. Let's see from them now. When the ship shows up to port, literally people line up for days to receive state of the art life, sane changing life saving surgeries, tumor site limbs, disease blindness, birth defects, but not only that, the personnel are educating and training the local healthcare providers with new skills and infrastructure so they can care for their own. After the ship has left, mercy ships runs on Vm ware, a dell technology with VX rail, Dell Isilon data protection. We are the it platform for mercy ships. Mercy ships is now building their next generation ship called global mercy, which were more than double. It's lifesaving capacity. It's the largest charity hospital ever. It will go live in 20 slash 20 serving Africa and I personally plan on being there for its launch. It is truly amazing what they are doing with our technology. Thanks. So we see this picture of the hybrid cloud. We've talked about how we do that for the private cloud. So let's look over at the public cloud and let's dig into this a little bit more deeply. You know, we're taking this incredible power of the Vm ware Cloud Foundation and making it available for the leading cloud providers in the world and with that, the partnership that we announced almost two years ago with Amazon and on the stage last year, we announced their first generation of products, no better example of the hybrid cloud. And for that it's my pleasure to bring to stage my friend, my partner, the CEO of aws. Please welcome Andy Jassy. Thank you andy. You know, you honor us with your presence, you know, and it really is a pleasure to be able to come in front of this audience and talk about what our teams have accomplished together over the last, uh, year. Yo, can you give us some perspective on that, Andy and what customers are doing with it? Well, first of all, thanks for having me. I really appreciate it. It's great to be here with all of you. Uh, you know, the offering that we have together customers because it allows them to use the same software they've been using to again, where cloud and aws is very appealing to manage their infrastructure for years to be able to deploy it an aws and we see a lot of customer momentum and a lot of customers using it. You see it in every imaginable vertical business segment in transportation. You see it with stagecoach and media and entertainment. You see it with discovery communications in education, Mit and Caltech and consulting and accenture and cognizant and dxc you see in every imaginable vertical business segment and the number of customers using the offering is doubling every quarter. So people were really excited about it and I think that probably the number one use case we see so far, although there are a lot of them, is customers who are looking to migrate on premises applications to the cloud. And a good example of that is mit. We're there right now in the process of migrating. In fact, they just did migrate 3000 vms from their data centers to Vm ware cloud native us. And this would have taken years before to do in the past, but they did it in just three months. It was really spectacular and they're just a fun company to work with and the team there. But we're also seeing other use cases as well. And you're probably the second most common example is we'll say on demand capabilities for things like disaster recovery. We have great examples of customers you that one in particular, his brakes, right? Urban in those. The brings security trucks and they all armored trucks coming by and they had a critical need to retire a secondary data center that they were using, you know, for Dr. so we quickly built to Dr Protection Environment for $600. Bdms know they migrated their mission critical workloads and Wallah stable and consistent Dr and now they're eliminating that site and looking for other migrations as well. The rate of 10 to 15 percent. It was just a great deal. One of the things I believe Andy, he'll customers should never spend capital, uh, Dr ever again with this kind of capability in place. That is just that game changing, you know, and you know, obviously we've been working on expanding our reach, you know, we promised to make the service available a year ago with the global footprint of Amazon and now we've delivered on that promise and in fact today or yesterday if you're an ozzie right down under, we announced in Sydney, uh, as well. And uh, now we're in US Europe and in APJ. Yeah. It's really, I mean it's very exciting. Of course Australia is one of the most virtualized places in the world and, and it's pretty remarkable how fast European customers have started using the offering to and just the quarter that's been out there and probably have the many requests customers has had. And you've had a, probably the number one request has been that we make the offering available in all the regions. The aws has regions and I can tell you by the end of 2019 will largely be there including with golf clubs and golf clap. You guys have been, that's been huge for you guys. Yeah. It's a government only region that we have that a lot of federal government workloads live in and we are pretty close together having the offering a fedramp authority to operate, which is a big deal on a game changer for governments because then there'll be able to use the familiar tools they use and vm ware not just to run their workloads on premises but also in the cloud as well with the data privacy requirements, security requirements they need. So it's a real game changer for government too. Yeah. And this you can see by the picture here basically before the end of next year, everywhere that you are and have an availability zone. We're going to be there running on data. Yup. Yeah. Let's get with it. Okay. We're a team go faster. Okay. You'll and you know, it's not just making it available, but this pace of innovation and you know, you guys have really taught us a few things in this respect and since we went live in the Oregon region, you know, we've been on a quarterly cadence of major releases and two was really about mission critical at scale and we added our second region. We added our hybrid cloud extension with m three. We moved the global rollout and we launched in Europe with m four. We really add a lot of these mission critical governance aspects started to attack all of the industry certifications and today we're announcing and five right. And uh, you know, with that, uh, I think we have this little cool thing you know, two of the most important priorities for that we're doing with ebs and storage. Yeah, we'll take, customers, our cost and performance. And so we have a couple of things to talk about today that we're bringing to you that I think hit both of those on a storage side. We've combined the elasticity of Amazon Elastic Block store or ebs with ware is Va v San and we've provided now a storage option that you'll be able to use that as much. It's very high capacity and much more cost effective and you'll start to see this initially on the Vm ware cloud. Native us are five instances which are compute instances, their memory optimized and so this will change the cost equation. You'll be able to use ebs by default and it'll be much more cost effective for storage or memory intensive workloads. Um, it's something that you guys have asked for. It's been very frequently requested it, it hits preview today. And then the other thing is that we've worked really hard together to integrate vm ware's Nsx along with aws direct neck to have a private even higher performance conductivity between on premises and the cloud. So very, very exciting new capabilities to show deep integration between the companies. Yeah. You know, in that aspect of the deep integration. So it's really been the thing that we committed to, you know, we have large engineering teams that are working literally every day. Right on bringing together and how do we fuse these platforms together at a deep and intimate way so that we can deliver new services just like elastic drs and the c and ebs really powerful, uh, capabilities and that pace of innovation continue. So next maybe. Um, maybe six. I don't know. We'll see. All right. You know, but we're continuing this toward pace of innovation, you know, completing all of the capabilities of Nsx. You'll full integration for all of the direct connect to capabilities. Really expanding that. You're only improving licensed capabilities on the platform. We'll be adding pks on top of for expanded developer a capabilities. So just. Oh, thank you. I, I think that was formerly known as Right, and y'all were continuing this pace of storage Chad. So anyway. innovation going forward, but I think we also have a few other things to talk about today. Andy. Yeah, I think we have some news that hopefully people here will be pretty excited about. We know we have a pretty big database business and aws and it's. It's both on the relational and on the nonrelational side and the business is billions of dollars in revenue for us and on the relational side. We have a service called Amazon relational database service or Amazon rds that we have hundreds of thousands of customers using because it makes it much easier for them to set up, operate and scale their databases and so many companies now are operating in hybrid mode and will be for a while and a lot of those customers have asked us, can you give us the ease of manageability of those databases but on premises. And so we talked about it and we thought about and we work with our partners at Vm ware and I'm excited to announce today, right now Amazon rds on Vm ware and so that will bring all the capabilities of Amazon rds to vm ware's customers for their on premises environments. And so what you'll be able to do is you'll be able to provision databases. You'll be able to scale the compute or the memory or the storage for those database instances. You'll be able to patch the operating system or database engines. You'll be able to create, read replicas to scale your database reads and you can deploy this rep because either on premises or an aws, you'll be able to deploy and high high availability configuration by replicating the data to different vm ware clusters. You'll be able to create online backups that either live on premises or an aws and then you'll be able to take all those databases and if you eventually want to move them to aws, you'll be able to do so rather easily. You have a pretty smooth path. This is going to be available in a few months. It will be available on Oracle sql server, sql postgresql and Maria DB. I think it's very exciting for our customers and I think it's also a good example of where we're continuing to deepen the partnership and listen to what customers want and then innovate on their behalf. Absolutely. Thank you andy. It is thrilling to see this and as we said, when we began the partnership, it was a deep integration of our offerings and our go to market, but also building this bi-directional hybrid highway to give customers the capabilities where they wanted cloud on premise, on premise to the cloud. It really is a unique partnership that we've built, the momentum we're feeling to our customer base and the cool innovations that we're doing. Andy, thank you so much for you Jordan Young, rural 20th. You guys appreciate it. Yeah, we really have just seen incredible momentum and as you might have heard from our earnings call that we just finished this. We finished the last quarter. We just really saw customer momentum here. Accelerating. Really exciting to see how customers are starting to really do the hybrid cloud at scale and with this we're just seeing that this vm ware cloud foundation available on Amazon available on premise. Very powerful, but it's not just the partnership with Amazon. We are thrilled to see the momentum of our Vm ware cloud provider program and this idea of the vm ware cloud providers has continued to gain momentum in the industry and go over five years. Right. This program has now accumulated more than 4,200 cloud partners in over 120 countries around the globe. It gives you choice, your local provider specialty offerings, some of your local trusted partners that you would have in giving you the greatest flexibility to choose from and cloud providers that meet your unique business requirements. And we launched last year a program called Vm ware cloud verified and this was saying you're the most complete embodiment of the Vm ware Cloud Foundation offering by our cloud partners in this program and this logo you know, allows you to that this provider has achieved the highest standard for cloud infrastructure and that you can scale and deliver your hybrid cloud and partnering with them. It know a particular. We've been thrilled to see the momentum that we've had with IBM as a huge partner and our business with them has grown extraordinarily rapidly and triple digits, but not just the customer count, which is now over 1700, but also in the depth of customers moving large portions of the workload. And as you see by the picture, we're very proud of the scope of our partnerships in a global basis. The highest standard of hybrid cloud for you, the Vm ware cloud verified partners. Now when we come back to this picture, you know we, you know, we're, we're growing in our definition of what the hybrid cloud means and through Vm Ware Cloud Foundation, we've been able to unify the private and the public cloud together as never before, but we're also seeing that many of you are interested in how do I extend that infrastructure further and farther and will simply call that the edge right? And how do we move data closer to where? How do we move data center resources and capacity closer to where the data's being generated at the operations need to be performed? Simply the edge and we'll dig into that a little bit more, but as we do that, what are the things that we offer today with what we just talked about with Amazon and our VCP p partners is that they can consume as a service this full vm ware Cloud Foundation, but today we're only offering that in the public cloud until project dimension of project dimension allows us to extend delivered as a service, private, public, and to the edge. Today we're announcing the tech preview, a project dimension Vm ware cloud foundation in a hyperconverged appliance. We're partnered deeply with Dell EMC, Lenovo for the first partners to bring this to the marketplace, built on that same proven infrastructure, a hybrid cloud control plane, so literally just like we're managing the Vm ware cloud today, we're able to do that for your on premise. You're small or remote office or your edge infrastructure through that exact same as a service management and control plane, a complete vm ware operated end to end environment. This is project dimension. Taking the vcf stack, the full vm ware cloud foundation stack, making an available in the cloud to the edge and on premise as well, a powerful solution operated by BM ware. This project dimension and project dimension allows us to have a fundamental building block in our approach to making customers even more agile, flexible, scalable, and a key component of our strategy as well. So let's click into that edge a little bit more and we think about the edge in the following layers, the compute edge, how do we get the data and operations and applications closer to where they need to be. If you remember last year I talked about this pendulum swinging of centralization and decentralization edge is a decentralization force. We're also excited that we're moving the edge of the devices as well and we're doing that in two ways. One with workspace, one for human optimized devices and the second is project pulse or Vm ware pulse. And today we're announcing pulse two point zero where you can consume it now as a service as well as with integrated security. And we've now scaled pulse to support 500 million devices. Isn't that incredible, right? I mean this is getting a scale. Billions and billions and finally networking is a key component. You all that. We're stretching the networking platform, right? And evolving how that edge operates in a more cloud and that's a service white and this is where Nsx St with Velo cloud is such a key component of delivering the edge of network services as well. Taken together the device side, the compute edge and rethinking and evolving the networking layer together is the vm ware edge strategy summary. We see businesses are on this multicloud journey, right? How do we then do that for their private of public coming together, the hybrid cloud, but they're also on a journey for how they work and operate it across the public cloud and the public cloud we have this torrid innovation, you'll want Andy's here, challenges. You know, he's announcing 1500 new services or were extraordinary innovation and you'll same for azure or Google Ibm cloud, but it also creates the same complexity as we said. Businesses are using multiple public clouds and how do I operate them? How do I make them work? You know, how do I keep track of my accounts and users that creates a set of cloud operations problems as well in the complexity of doing that. How do you make it work? Right? And your for that. We'll just see that there's this idea cloud cost compliance, analytics as these common themes that of, you know, keep coming up and we're seeing in our customers that are new role is emerging. The cloud operations role. You're the person who's figuring out how to make these multicloud environments work and keep track of who's using what and which data is landing where today I'm thrilled to tell you that the, um, where is acquiring the leader in this space? Cloudhealth technologies. Thank you. Cloudhealth technologies supports today, Amazon, azure and Google. They have some 3,500 customers, some of the largest and most respected brands in the, as a service industry. And Sasa business today rapidly span expanding feature sets. We will take cloudhealth and we're going to make it a fundamental platform and branded offering from the um, where we will add many of the other vm ware components into this platform, such as our wavefront analytics, our cloud, choreo compliance, and many of the other vm ware products will become part of the cloudhealth suite of services. We will be enabling that through our enterprise channels as well as through our MSP and BCPP partners as well know. Simply put, we will make cloudhealth the cloud operations platform of choice for the industry. I'm thrilled today to have Joe Consella, the CTO and founder. Joe, please stand up. Thank you joe to your team of a couple hundred, you know, mostly in Boston. Welcome to the Vm ware family, the Vm ware community. It is a thrill to have you part of our team. Thank you joe. Thank you. We're also announcing today, and you can think of this, much like we had v realize operations and v realize automation, the compliment to the cloudhealth operations, vm ware, cloud automation, and some of you might've heard of this in the past, this project tango. Well, today we're announcing the initial availability of Vm ware, cloud automation, assemble, manage complex applications, automate their provisioning and cloud services, and manage them through a brokerage the initial availability of cloud automation services, service. Your today, the acquisition of cloudhealth as a platform, the aware of the most complete set of multicloud management tools in the industry, and we're going to do so much more so we've seen this picture of this multicloud journey that our customers are on and you know, we're working hard to say we are going to bridge across these worlds of innovation, the multicloud world. We're doing many other things. You're gonna hear a lot at the show today about this year. We're also giving the tech preview of the Vm ware cloud marketplace for our partners and customers. Also today, Dell technologies is announcing their cloud marketplace to provide a self service, a portfolio of a Dell emc technologies. We're fundamentally in a unique position to accelerate your multicloud journey. So we've built out this any cloud piece, but right in the middle of that any cloud is the network. And when we think about the network, we're just so excited about what we have done and what we're seeing in the industry. So let's click into this a little bit further. We've gotten a lot done over the last five years. Networking. Look at these numbers. 80 million switch ports have been shipped. We are now 10 x larger than number two and software defined networking. We have over 7,500 customers running on Nsx and maybe the stat that I'm most proud of is 82 percent of the fortune 100 has now adopted nsx. You have made nsx these standard and software defined networking. Thank you very much. Thank you. When we think about this journey that we're on, we started. You're saying, Hey, we've got to break the chains inside of the data center as we said. And then Nsx became the software defined networking platform. We started to do it through our cloud provider partners. Ibm made a huge commitment to partner with us and deliver this to their customers. We then said, boy, we're going to make a fundamental to all of our cloud services including aws. We built this bridge called the hybrid cloud extension. We said we're going to build it natively into what we're doing with Telcos, with Azure and Amazon as a service. We acquired the St Wagon, right, and a Velo cloud at the hottest product of Vm ware's portfolio today. The opportunity to fundamentally transform branch and wide area networking and we're extending it to the edge. You're literally, the world has become this complex network. We have seen the world go from the old defined by rigid boundaries, simply put in a distributed world. Hardware cannot possibly work. We're empowering customers to secure their applications and the data regardless of where they sit and when we think of the virtual cloud network, we say it's these three fundamental things, a cloud centric networking fabric with intrinsic security and all of it delivered in software. The world is moving from data centers to centers of data and they need to be connected and Nsx is the way that we will do that. So you'll be aware of is well known for this idea of talking but also showing. So no vm world keynote is okay without great demonstrations of it because you shouldn't believe me only what we can actually show and to do that know I'm going to have our CTL come onstage and CTL y'all. I used to be a cto and the CTO is the certified smart guy. He's also known as the chief talking officer and today he's my demo partner. Please walk, um, Vm ware, cto ray to the stage. Right morning pat. How you doing? Oh, it's great ray, and thanks so much for joining us. Know I promised that we're going to show off some pretty cool stuff here. We've covered a lot already, but are you up to the task? We're going to try and run through a lot of demos. We're going to do it fast and you're going to have to keep me on time to ask an awkward question. Slow me down. Okay. That's my fault if you run along. Okay, I got it. I got it. Let's jump right in here. So I'm a CTO. I get to meet lots of customers that. A few weeks ago I met a cio of a large distribution company and she described her it infrastructure as consisting of a number of data centers troll to us, which he also spoke of a large number of warehouses globally, and each of these had local hyperconverged compute and storage, primarily running surveillance and warehouse management applications, and she pulls me four questions. The first question she asked me, she says, how do I migrate one of these data centers to Vm ware cloud on aws? I want to get out of one of these data centers. Okay. Sounds like something andy and I were just talking exactly, exactly what you just spoke to a few moments ago. She also wanted to simplify the management of the infrastructure in the warehouse as themselves. Okay. He's age and smaller data centers that you've had out there. Her application at the warehouses that needed to run locally, butter developers wanted to develop using cloud infrastructure. Cloud API is a little bit late. The rds we spoken with her in. Her final question was looking to the future, make all this complicated management go away. I want to be able to focus on my application, so that's what my business is about. So give me some new ways of how to automate all of this infrastructure from the edge to the cloud. Sounds pretty clear. Can we do it? Yes we can. So we're going to dive right in right now into one of these demos. And the first demo we're going to look at it is vm ware cloud on aws. This is the best solution for accelerating this public cloud journey. So can we start the demo please? So what you were looking at here is one of those data centers and you should be familiar with this product. It's a familiar vsphere client. You see it's got a bunch of virtual machines running in there. These are the virtual machines that we now want to be able to migrate and move the VMC on aws. So we're going to go through that migration right now. And to do that we use a product that you've seen already atx, however it's the x has been, has got some new cool features since the last time we download it. Probably on this stage here last year, I wanted those in particular is how do we do bulk migration and there's a new cool thing, right? Whole thing we want to move the data center en mass and his concept here is cloud motion with vsphere replication. What this does is it replicates the underlying storage of the virtual machines using vsphere replication. So if and when you want to now do the final migration, it actually becomes a vmotion. So this is what you see going on right here. The replication is in place. Now when you want to touch you move those virtual machines. What you'll do is a vmotion and the key thing to think about here is this is an actual vmotion. Those the ends as room as they're moving a hustler, migrating remained life just as you would in a v motion across one particular infrastructure. Did you feel complete application or data center migration with no dying town? It's a Standard v motion kind of appearance. Wow. That is really impressive. That's correct. Wow. You. So one of the other things we want to talk about here is as we are moving these virtual machines from the on prem infrastructure to the VMC on aws infrastructure, unfortunately when we set up the cloud on VMC and aws, we only set up for hosts, uh, that might not be, that'd be enough because she is going to move the whole infrastructure of that this was something you guys, you and Andy referred to briefly data center. Now, earlier, this concept of elastic drs. what elastic drs does, it allows the VMC on aws to react to the workloads as they're being created and pulled in onto that infrastructure and automatically pull in new hosts into the VMC infrastructure along the way. So what you're seeing here is essentially the MC growing the infrastructure to meet the needs of the workloads themselves. Very cool. So overseeing that elastic drs. we also see the ebs capabilities as well. Again, you guys spoke about this too. This is the ability to be able to take the huge amount of stories that Amazon have, an ebs and then front that by visa you get the same experience of v Sign, but you get this enormous amount of storage capabilities behind it. Wow. That's incredible. That's incredible. I'm excited about this. This is going to enable customers to migrate faster and larger than ever before. Correct. Now she had a series of little questions. Okay. The second question was around what about all those data centers and those age applications that I did not move, and this is where we introduce the project which you've heard of already tonight called project dementia. What this does, it gives you the simplicity of Vm ware cloud, but bringing that out to the age, you know what's basically going on here, vmc on aws is a service which manages your infrastructure in aws. We know stretch that service out into your infrastructure, in your data center and at the age, allowing us to be able to manage that infrastructure in the same way. Once again, let's dive down into a demo and take a look at what this looks like. So what you've got here is a familiar series of services available to you, one of them, which is project dimension. When you enter project dimension, you first get a view of all of the different infrastructure that you have available to you, your data centers, your edge locations. You can then dive deeply into one of these to get a closer look at what's going on here. We're diving into one of these The problem is there's a networking problem going on in this warehouse. warehouses and we see it as a problem here. How do we know? We know because vm ware is running this as a managed service. We are directly managing or sorry, monitoring your infrastructure or we discover there's something going wrong here. We automatically create the ASR, so somebody is dealing with this. You have visibility to what's going on, but the vm ware managed service is already chasing the problem for you. Oh, very good. So now we're seeing this dispersed infrastructure with project dementia, but what's running on it so well before we get with running out, you've got another problem and the problem is of course, if you're managing a lot of infrastructure like this, you need to keep it up to date. And so once again, this is where the vm ware managed service kicks in. We manage that infrastructure in terms of patching it and updating it for you. And as an example, when we released a security patch, here's one for the recent l, one terminal fault, the Vmr managed service is already on that and making sure that your on prem and edge infrastructure is up to date. Very good. Now, what's running? Okay. So what's running, uh, so we mentioned this case of this software running at the edge infrastructure itself, and these are workloads which are running locally in those age, uh, those edge locations. This is a surveillance application. You can see it here at the bottom it says warehouse safety monitor. So this is an application which gathers images and then stores those images He said my sql database on top there, now this is where we leverage the somewhere and it puts them in a database. technology you just learned about when Andy and pat spoke about disability to take rds and run that on your on prem infrastructure. The block of virtual machines in the moment are the rds components from Amazon running in your infrastructure or in your edge location, and this gives you the ability to allow your developers to be able to leverage and operate against those Apis, but now the actual database, the infrastructure is running on prem and you might be doing just for performance reasons because of latency, you might be doing it simply because this data center is not always connected to the cloud. When you take a look into under the hood and see what's going on here, what you actually see this is vsphere, a modified version of vsphere. You see this new concept of my custom availability zone. That is the availability zone running on your infrastructure which supports or ds. What's more interesting is you flip back to the Amazon portal. This is typically what your developers are going to do. Once again, you see an availability zone in your Amazon portal. This is the availability zone running on your equipment in your data center. So we've truly taken that already as infrastructure and moved it to the edge so the developer sees what they're comfortable with and the infrastructure sees what they're comfortable with bridging those two worlds. Fabulous. Right. So the final question of course that we got here was what's next? How do I begin to look to the future and say I am going to, I want to be able to see all of my infrastructure just handled in an automated fashion. And so when you think about that, one of the questions there is how do we leverage new technologies such as ai and ml to do that? So what you've got here is, sorry we've got a little bit later. What you've got here is how do I blend ai in a male and the power of what's in the data center itself. Okay. And we could do that. We're bringing you the AI and ml, right? And fusing them together as never before to truly change how the data center operates. Correct. And it is this introduction is this merging of these things together, which is extremely powerful in my mind. This is a little bit like a self driving vehicle, so thinking about a car driving down the street is self driving vehicle, it is consuming information from all of the environment around it, other vehicles, what's happening, everything from the wetter, but it also has a lot of built in knowledge which is built up to to self learning and training along the way in the kids collecting lots of that data for decades. Exactly. And we've got all that from all the infrastructure that we have. We can now bring that to bear. So what we're focusing on here is a project called project magna and project. Magna leverage is all of this infrastructure. What it does here is it helps connect the dots across huge datasets and again a deep insight across the stack, all the way from the application hardware, the infrastructure to the public cloud, and even the age and what it does, it leverages hundreds of control points to optimize your infrastructure on Kpis of cost performance, even user specified policies. This is the use of machine language in order to fundamentally transform. I'm sorry, machine learning. I'm going back to some. Very early was here, right? This is the use of machine learning and ai, which will automatically transform. How do you actually automate these data centers? The goal is true automation of your infrastructure, so you get to focus on the applications which really served needs of your business. Yeah, and you know, maybe you could think about that as in the past we would have described the software defined data center, but in the future we're calling it the self driving data center. Here we are taking that same acronym and redefining it, right? Because the self driving data center, the steep infusion of ai and machine learning into the management and automation into the storage, into the networking, into vsphere, redefining the self driving data center and with that we believe fundamentally is to be an enormous advance and how they can take advantage of new capabilities from bm ware. Correct. And you're already seeing some of this in pieces of projects such as some of the stuff we do in wavefront and so already this is how do we take this to a new level and that's what project magnet will do. So let's summarize what we've seen in a few demos here as we work in true each of these very quickly going through these demos. First of all, you saw the n word cloud on aws. How do I migrate an entire data center to the cloud with no downtime? Check, we saw project dementia, get the simplicity of Vm ware cloud in the data center and manage it at the age as a managed service check. Amazon rds and Vm ware. Cool Demo, seamlessly deploy a cloud service to an on premises environment. In this case already. Yes, we got that one coming in are in m five. And then finally project magna. What happens when you're looking to the future? How do we leverage ai and ml to self optimize to virtual infrastructure? Well, how did ray do as our demo guy? Thank you. Thanks. Thanks. Right. Thank you. So coming back to this picture, our gps for the day, we've covered any cloud, let's click into now any application, and as we think about any application, we really view it as this breadth of the traditional cloud native and Sas Coobernetti is quickly maybe spectacularly becoming seen as the consensus way that containers will be managed and automate as the framework for how modern APP teams are looking at their next generation environment, quickly emerging as a key to how enterprises build and deploy their applications today. And containers are efficient, lightweight, portable. They have lots of values for developers, but they need to also be run and operate and have many infrastructure challenges as well. Managing automation while patch lifecycle updates, efficient move of new application services, know can be accelerated with containers. We also have these infrastructure problems and you know, one thing we want to make clear is that the best way to run a container environment is on a virtual machine. You know, in fact, every leader in public cloud runs their containers and virtual machines. Google the creator and arguably the world leader in containers. They runs them all in containers. Both their internal it and what they run as well as G K, e for external users as well. They just announced gke on premise on vm ware for their container environments. Google and all major clouds run their containers and vms and simply put it's the best way to run containers. And we have solved through what we have done collectively the infrastructure problems and as we saw earlier, cool new container apps are also typically some ugly combination of cool new and legacy and existing environments as well. How do we bridge those two worlds? And today as people are rapidly moving forward with containers and Coobernetti's, we're seeing a certain set of problems emerge. And Dan cone, right, the director of CNCF, the Coobernetti, uh, the cloud native computing foundation, the body for Coobernetti's collaboration and that, the group that sort of stewards the standardization of this capability and he points out these four challenges. How do you secure them? How do you network and you know, how do you monitor and what do you do for the storage underneath them? Simply put, vm ware is out to be, is working to be is on our way to be the dial tone for Coobernetti's. Now, some of you who were in your twenties might not know what that means, so we know over to a gray hair or come and see me afterward. We'll explain what dial tone means to you or maybe stated differently. Enterprise grade standard for Cooper netties and for that we are working together with our partners at Google as well as pivotal to deliver Vm ware, pks, Cooper netties as an enterprise capability. It builds on Bosh. The lifecycle engine that's foundational to the pivotal have offerings today, uh, builds on and is committed to stay current with the latest Coobernetti's releases. It builds on Nsx, the SDN container, networking and additional contributions that were making like harbor the Vm ware open source contribution for the container registry. It packages those together makes them available on a hybrid cloud as well as public cloud environments with pks operators can efficiently deploy, run, upgrade their coopernetties environments on SDDC or on all public clouds. While developers have the freedom to embrace and run their applications rapidly and efficiently, simply put, pks, the standard for Coobernetti's in the enterprise and underneath that Nsx you'll is emerging as the standard for software defined networking. But when we think about and we saw that quote on the challenges of Kubernetes today, we see that networking is one of the huge challenge is underneath that and in a containerized world, things are changing even more rapidly. My network environment is moving more quickly. NSX provides the environment's easily automate networking and security for rapid deployment of containerized environments that fully supports the MRP chaos, fully supports pivotal's application service, and we're also committed to fully support all of the major kubernetes distribution such as red hat, heptio and docker as well Nsx, the only platform on the planet that can address the complexity and scale of container deployments taken together Vm Ware, pks, the production grade computer for the enterprise available on hybrid cloud, available on major public clouds. Now, let's not just talk about it again. Let's see it in action and please walk up to the stage. When di Carter with Ray, the senior director of cloud native marketing for Vm ware. Thank you. Hi everybody. So we're going to talk about pks because more and more new applications are built using kubernetes and using containers with vm ware pts. We get to simplify the deploying and the operation of Kubernetes at scale. When the. You're the experts on all of this, right? So can you take as true the scenario of how pks or vm ware pts can really help a developer operating the Kubernedes environment, developed great applications, but also from an administrator point of view, I can really handle things like networking, security and those configurations. Sounds great. I love to dive into the demo here. Okay. Our Demo is. Yeah, more pks running coubernetties vsphere. Now pks has a lot of cool functions built in, one of which is Nsx. And today what I'm going to show you is how NSX will automatically bring up network objects as quick Coobernetti's name spaces are spun up. So we're going to start with the fees per client, which has been extended to Ron pks, deployed cooper clusters. We're going to go into pks instance one, and we see that there are five clusters running. We're going to select one other clusters, call application production, and we see that it is running nsx. Now a cluster typically has multiple users and users are assigned namespaces, and these namespaces are essentially a way to provide isolation and dedicated resources to the users in that cluster. So we're going to check how many namespaces are running in this cluster and more brought up the Kubernetes Ui. We're going to click on namespace and we see that this cluster currently has four namespaces running wire. We're going to do next is bringing up a new name space and show that Nsx will automatically bring up the network objects required for that name space. So to do that, we're going to upload a Yammel file and your developer may actually use Ku Kata command to do this as well. We're going to check the namespace and there it is. We have a new name space called pks rocks. Yeah. Okay. Now why is that guy now? It's great. We have a new name space and now we want to make sure it has the network elements assigned to us, so we're going to go to the NSX manager and hit refresh and there it is. PKS rocks has a logical robber and a logical switch automatically assigned to it and it's up and running. So I want to interrupt here because you made this look so easy, right? I'm not sure people realize the power of what happened here. The developer, winton using Kubernetes, is api infrastructure to familiar with added a new namespace and behind the scenes pks and tardy took care of the networking. It combination of Nsx, a combination of what we do at pks to truly automate this function. Absolutely. So this means that if you are on the infrastructure operation, you don't need to worry about your developer springing up namespaces because Nsx will take care of bringing the networking up and then bringing them back down when the namespace is not used. So rate, but that's not it. Now, I was in operations before and I know how hard it is for enterprises to roll out a new product without visibility. Right, so pks took care of those dates, you operational needs as well, so while it's running your clusters, it's also exporting Meta data so that your developers and operators can use wavefront to gain deep visibility into the health of the cluster as well as resources consumed by the cluster. So here you see the wavefront Ui and it's showing you the number of nodes running, active parts, inactive pause, et cetera. You can also dive deeper into the analytics and take a look at information site, Georgia namespace, so you see pks rocks there and you see the number of active nodes running as well as the CPU utilization and memory consumption of that nice space. So now pks rocks is ready to run containerized applications and microservices. So you just get us a very highlight of a demo here to see a little bit what pks pks says, where can we learn more? So we'd love to show you more. Please come by the booth and we have more cool functions running on pks and we'd love to have you come by. Excellent. Thank you, Lindy. Thank you. Yeah, so when we look at these types of workloads now running on vsphere containers, Kubernedes, we also see a new type of workload beginning to appear and these are workloads which are basically machine learning and ai and in many cases they leverage a new type of infrastructure, hardware accelerators, typically gps. What we're going to talk about here is how in video and Vm ware have worked together to give you flexibility to run sophisticated Vdi workloads, but also to leverage those same gpu for deep learning inference workloads also on vsphere. So let's dive right into a demo here. Again, what you're seeing here is again, you're looking at here, you're looking at your standard view realized operations product, and you see we've got two sets of applications here, a Vdi desktop workload and machine learning, and the graph is showing what's happening with the Vdi desktops. These are office workers leveraging these desktops everyday, so of course the infrastructure is super busy during the daytime when they're in the office, but the green area shows this is not been used very heavily outside of those times. So let's take a look. What happens to the machine learning application in this case, this organization leverages those available gpu to run the machine learning operations outside the normal working hours. Let's take a little bit of a deeper dive into what the application it is before we see what we can do from an infrastructure and configuration point of view. So this machine learning application processes a vast number of images and it clarify or sorry, it categorizes these images and as it's doing so, it is moving forward and putting each of these in a database and you can see it's operating here relatively fast and it's leveraging some gps to do that. So typical image processing type of machine learning problem. Now let's take a dive in and look at the infrastructure which is making this happen. First of all, we're going to look only at the Vdi employee Dvt, a Vdi infrastructure here. So I've got a bunch of these applications running Vdi applications. What I want to do is I want to move these so that I can make this image processing out a application run a lot faster. Now normally you wouldn't do this, but pot insisted that we do this demo at 10:30 in the morning when the office workers are in there, so we're going to move older Vdi workloads over to the other cluster and that's what you're seeing is going on right now. So as they move over to this other cluster, what we are now doing is freeing up all of the infrastructure. The GPU that Vdi workload was using here. We see them moving across and now you've freed up that infrastructure. So now we want to take a look at this application itself, the machine learning application and see how we can make use of that. Now freed up infrastructure we've got here is the application is running using one gpu in a vsphere cluster, but I've got three more gpu is available now because I've moved the Vdi workloads. We simply modify the application, let it know that these are available and you suddenly see an increase in the processing capabilities because of what we've done here in terms of making the flexibility of accessing those gps. So what you see here is the same gps that youth for Vdi, which you probably have in your infrastructure today, can also be used to run sophisticated machine learning and ai type of applications on your vsphere infrastructure. So let's summarize what we've seen in the various demos here in this section. First of all, we saw how the MRPS simplifies the deployment and operating operation of Kubernetes at scale. What we've also seen is that leveraging the Nvidia Gpu, we can now run the most demanding workloads on vsphere. When we think about all of these applications and these new types of workloads that people are running. I want to take one second to speak to another workload that we're seeing beginning to appear in the data center. And this is of course blockchain. We're seeing an increasing number of organizations evaluating blockchains for smart contract and digital consensus solutions. So this tech, this technology is really becoming or potentially becoming a critical role in how businesses will interact each other, how they will work together. We'd project concord, which is an open source project that we're releasing today. You get the choice, performance and scale of verifiable trust, which you can then bring to bear and run in the enterprise, but this is not just another blockchain implementation. We have focused very squarely on making sure that this is good for enterprises. It focuses on performance, it focuses on scalability. We have seen examples where running consensus algorithms have taken over 80 days on some of the most common and widely used infrastructure in blockchain and we project conquered. You can do that in two and a half hours. So I encourage you to check out this project on get hub today. You'll also see lots of activity around the whole conference. Speaking about this. Now we're going to dive into another section which is the anti device section. And for that I need to welcome pat back up there. Thank you pat. Thanks right. So diving into any device piece of the puzzle, you and as we think about the superpowers that we have, maybe there are no more area that they are more visible than in the any device aspect of our picture. You know, and as we think about this, the superpowers, you know, think about mobility, right? You know, and how it's enabling new things like desktop as a service in the mobile area, these breadth of smartphones and devices, ai and machine learning allow us to manage them, secure them and this expanding envelope of devices in the edge that need to be connected and wearables and three d printers and so on. We've also seen increasing research that says engaged employees are at the center of business success. Engaged employees are the critical ingredient for digital transformation. And frankly this is how I run vm ware, right? You know, I have my device and my work, all my applications, every one of my 23,000 employees is running on our transformed workspace one environment. Research shows that companies that, that give employees ready anytime access are nearly three x more likely to be leaders in digital transformation. That employees spend 20 percent of their time today on manual processes that can be automated. The way team collaboration and speed of division decisions increases by 16 percent with engaged employees with modern devices. Simply put this as a critical aspect to enabling your business, but you remember this picture from the silos that we started with and each of these environments has their own tribal communities of management, security automation associated with them, and the complexity associated with these is mind boggling and we start to think about these. Remember the I'm a pc and I'm a Mac. Well now you have. I'm an Ios. I'm a droid and other bdi and I'm now a connected printer and I'm a connected watch. You remember citrix manager and good is now bad and sccm a failed model and vpns and Xanax. The chaos is now over at the center of that is vm ware, workspace one, get it out of the business of managing devices, automate them from the cloud, but still have the mentor price. Secure cloud based analytics that brings new capabilities to this critical topic. You'll focus your energy on creating employee and customer experiences. You know, new capabilities to allow like our airlift, the new capability to help customers migrate from their sccm environment to a modern management, expanding the use of workspace intelligence. Last year we announced the chromebook and a partnership with HP and today I'm happy to announce the next step in our partnerships with Dell. And uh, today we're announcing that Dell provisioning for Vm ware, workspace one as part of Dell's ready to work solutions Dallas, taking the next leap and bringing workspace one into the core of their client to offerings. And the way you can think about this as Literally a dell drop ship, lap pops showing up to new employee. day one, productivity. You give them their credential and everything else is delivered by workspace one, your image, your software, everything patched and upgraded, transforming your business, right beginning at that device experience that you give to your customer. And again, we don't want to talk about it. We want to show you how this works. Please walk to the stage with re renew the head of our desktop products marketing. Thank you. So we just heard from pat about how workspace one integrated with Dell laptops is really set up to manage windows devices. What we're broadly focused on here is how do we get a truly modern management system for these devices, but one that has an intelligence behind it to make sure that we're kept with a good understanding of how to keep these devices always up to date and secure. Can we start the demo please? So what we're seeing here is to be the the front screen that you see of workspace one and you see you've got multiple devices a little bit like that demo that patch assured. I've got Ios, android, and of course I've got windows renewal. Can you please take us through how workspace one really changes the ability of somebody an it administrator to update and manage windows into our environment? Absolutely. With windows 10, Microsoft has finally joined the modern management body and we are really excited about that. Now. The good news about modern management is the frequency of ostp updates and how quickly they come out because you can address all those security issues that are hitting our radar on a daily basis, but the bad news about modern management is the frequency of those updates because all of us in it admins, we have to test each and every one of our applications would that latest version because we don't want to roll out that update in case of causes any problems with workspace one, we saw that we simply automate and provide you with the APP compatibility information right out of the box so you can now automate that update process. Let's take a quick look. Let's drill down here further into the windows devices. What we'll see is that only a small percentage of those devices are on that latest version of operating system. Now, that's not a good thing because it might have an important security fix. Let's scroll down further and see what the issue is. We find that it's related to app compatibility. In fact, 38 percent of our devices are blocked from being upgraded and the issue is app compatibility. Now we were able to find that not by asking the admins to test each and every one of those, but we combined windows analytics data with APP intelligent out of the box and be provided that information right here inside of the console. Let's dig down further and see what those devices and apps look like. So knew this is the part that I find most interesting. If I am a system administrator at this point I'm looking at workspace one is giving me a key piece of information. It says if you proceed with this update, it's going to fail 84, 85 percent at a time. So that's an important piece of information here, but not alone. Is it telling me that? It is telling me roughly speaking why it thinks it's going to fail. We've got a number of apps which are not ready to work with this new version, particularly the Mondo card sales lead tracker APP. So what we need to do is get engineering to tackle the problems with this app and make sure that it's updated. So let's get fixing it in order to fix it. What we'll do is create an automation and we can do this right out of the box in this automation will open up a Jira ticket right from within the console to inform the engineers about the problem, not just that we can also flag and send a notification to that engineering manager so that it's top of mine and they can get working on this fixed right away. Let's go ahead and save that automation right here, ray UC. There's the automation that we just So what's happening here is essentially this update is now scheduled meeting. saved. We can go and update oldest windows devices, but workspace one is holding the process of proceeding with that update, waiting for the engineers to update the APP, which is going to cause the problem. That's going to take them some time, right? So the engineers have been working on this, they have a fixed and let's go back and see what's happened to our devices. So going back into the ios updates, what we'll find is now we've unblocked those devices from being upgraded. The 38 percent has drastically dropped down. It can rest in peace that all of the devices are compliant and on that latest version of operating system. And again, this is just a snapshot of the power of workspace one to learn more and see more. I invite you all to join our EOC showcase keynote later this evening. Okay. So we've spoken about the presence of these new devices that it needs to be able to manage and operate across everything that they do. But what we're also seeing is the emergence of a whole new class of computing device. And these are devices which are we commonly speak to have been at the age or embedded devices or Iot. And in many cases these will be in factories. They'll be in your automobiles, there'll be in the building, controlling, controlling, uh, the building itself, air conditioning, etc. Are quite often in some form of industrial environment. There's something like this where you've got A wind farm under embedded in each of these turbines. This is a new class of computing which needs to be managed, secured, or we think virtualization can do a pretty good job of that in new virtualization frontier, right at the edge for iot and iot gateways, and that's gonna. That's gonna, open up a whole new realm of innovation in that space. Let's dive down and taking the demo. This spaces. Well, let's do that. What we're seeing here is a wind turbine farm, a very different than a data center than what we're used to and all the compute infrastructure is being managed by v center and we see to edge gateway hose and they're running a very mission critical safety watchdog vm right on there. Now the safety watchdog vm is an fte mode because it's collecting a lot of the important sensor data and running the mission critical operations for the turbine, so fte mode or full tolerance mode, that's a pretty sophisticated virtualization feature allowing to applications to essentially run in lockstep. So if there's a failure, wouldn't that gets to take over immediately? So this no sophisticated virtualization feature can be brought out all the way to the edge. Exactly. So just like in the data center, we want to perform an update, so as we performed that update, the first thing we'll do is we'll suspend ft on that safety watchdog. Next, we'll put two. Oh, five into maintenance mode. Once that's done, we'll see the power of emotion that we're all familiar with. We'll start to see all the virtual machines vmotion over to the second backup host. Again, all the maintenance, all the update without skipping a heartbeat without taking down any daily operations. So what we're seeing here is the basic power of virtualization being brought out to the age v motion maintenance mode, et cetera. Great. What's the big deal? We've been doing that for years. What's the, you know, come on. What's the big deal? So what you're on the edge. So when you get to the age pack, you're dealing with a whole new class of infrastructure. You're dealing with embedded systems and new types of cpu hours and process. This whole demo has been done on an arm 64. Virtualization brought to arm 64 for embedded devices. So we're doing this on arm on the edge, correct. Specifically focused for embedded for age oems. Okay. Now that's good. Okay. Thank you ray. Actually, we've got a summary here. Pat, just a second before you disappear. A lot to rattle off what we've just seen, right? We've seen workspace one cross platform management. What we've also seen, of course esx for arm to bring the power of vfx to edge on 64, but are in platforms will go no. Okay. Okay. Thank you. Thanks. Now we've seen a look at a customer who is taking advantage of everything that we just saw and again, a story of a customer that is just changing lives in a fundamental way. Let's see. Make a wish. So when a family gets the news that a child is sick and it's a critical illness, it could be a life threatening illness. The whole family has turned upside down. Imagine somebody comes to you and they say, what's the one thing you want that's in your heart? You tell us and then we make that happen. So I was just calling to give you the good news that we're going to be able to grant jackson a wish make, which is the largest wish granting organizations in the United States. English was featured in the cbs 60 minutes episode. Interestingly, it got a lot of hits, but uh, unfortunately for the it team, the whole website crashed make a wish is going through a program right now where we're centralizing technology and putting certain security standards in place at our chapters. So what you're seeing here, we're configuring certain cloud services to make sure that they always are able to deliver on the mission whether they have a local problem or not is we continue to grow the partnership and work with vm ware. It's enabling us to become more efficient in our processes and allows us to grant more wishes. It was a little girl. She had a two year old brother. She just wanted a puppy and she was forthright and I want to name the puppy in my name so my brother would always have me to list them off a five year old. It's something we can't change their medical outcome, but we can change their spiritual outcome and we can transform their lives. Thank you. Working together with you truly making wishes come true. The last topic I want to touch on today, and maybe the most important to me personally is security. You got to fundamentally, when we think about this topic of security, I'll say it's broken today and you know, we would just say that the industry got it wrong that we're trying to bolt on or chasing bad, and when we think about our security spend, we're spending more and we're losing more, right? Every day we're investing more in this aspect of our infrastructure and we're falling more behind. We believe that we have to have much less security products and much more security. You know, fundamentally, you know, if you think about the problem, we build infrastructure, right? Generic infrastructure, we then deploy applications, all kinds of applications, and we're seeing all sorts of threats launched that as daily tens of millions. You're simple virus scanner, right? Is having tens of millions of rules running and changing many times a day. We simply believe the security model needs to change. We need to move from bolted on and chasing bad to an environment that has intrinsic security and is built to ensure good. This idea of built in security. We are taking every one of the core vm ware products and we are building security directly into it. We believe with this, we can eliminate much of the complexity. Many of the sensors and agents and boxes. Instead, they'll directly leverage the mechanisms in the infrastructure and we're using that infrastructure to lock it down to behave as we intended it to ensure good, right on the user side with workspace one on the network side with nsx and microsegmentation and storage with native encryption and on the compute with app defense, we are building in security. We're not chasing threats or adding on, but radically reducing the attack surface. When we look at our applications in the data center, you see this collection of machines running inside of it, right? You know, typically running on vsphere and those machines are increasingly connected. Through nsx and last year we introduced the breakthrough security solution called app defense and app defense. Leverages the unique insight we get into the application so that we can understand the application and map it into the infrastructure and then you can lock down, you could take that understanding, that manifest of its behavior and then lock those vms to that intended behavior and we do that without the operational and performance burden of agents and other rear looking use of attack detection. We're shrinking the attack surface, not chasing the latest attack vector, you know, and this idea of bolt on versus chasing bad. You sort of see it right in the network. Machines have lots of conductivity, lots of applications running and something bad happens. It basically has unfettered access to move horizontally through the data center and most of our security is north, south. MosT of the attacks are eastwest. We introduced this idea of microsegmentation five years ago, and by it we're enabling organizations to secure some networks and separate sensitive applications and services as never before. This idea isn't new, that just was never practical before nsx, but we're not standing still. Our teams are innovating to leap beyond 12. What's next beyond microsegmentation, and we see this in three simple words, learn, imagine a system that can look into the applications and understand their behavior and how they should operate. we're using machine learning and ai instead of chasing were to be able to ensure good where that that system can then locked down its behavior so the system consistently operates that way, but finally we know we have a world of increasing dynamic applications and as we move to more containerize the microservices, we know this world is changing, so we need to adapt. We need to have more automation to adapt to the current behavior. Today I'm very excited to have two major announcements that are delivering on this vision. The first of those vsphere platinum, our flagship vm ware vsphere product now has app defense built right in platinum will enable virtualization teams. Yeah, go ahead. Yeah, let's use it. Platinum will enable virtualization teams you to give an enormous contribution to the security profile of your enterprise. You could see whatever vm is for its purpose, its behavior until the system. That's what it's allowed to do. Dramatically reducing the attack surface without impact. On operations or performance, the capability is so powerful, so profound. We want you to be able to leverage it everywhere, and that's why we're building it directly into vsphere, vsphere platinum. I call it the burger and fries. You know, nobody leaves the restaurant without the fries who would possibly run a vm in the future without turning security on. That's how we want this to work going forward. Vsphere platinum and as powerful as microsegmentation has been as an idea. We're taking the next step with what we call adaptive microsegmentation. We are fusing Together app defense and vsphere with nsx to allow us to align the policies of the application through vsphere and the network. We can then lock down the network and the compute and enable this automation of the microsegment formation taken together adaptive microsegmentation. But again, we don't want to just tell you about it. We want to show you. Please welcome to the stage vj dante, who heads our machine learning team for app dispense. Vj a very good vj. Thanks for joining us. So, you know, I talked about this idea right, of being able to learn, lock and adapt. Uh, can you show it to us? Great. Yeah. Thank you. With vc a platinum, what we have done is we have put in everything you need to learn, lock and adapt, right with the infrastructure. The next time you bring up your wifi at line, you'll actually see a difference right in there. Let's go with that demo. There you go. And when you look at our defense there, what you see is that all your guests, virtual machines and all your host, hundreds of them and thousands of virtual machines enabling for that difference. It's in there. And what that does is immediately gets you visibility into the processes running on those virtual machines and the risk for the first time. Think about it for the first time. You're looking at the infrastructure through the lens of an application. Here, for example, the ecommerce application, you can see the components that make up that application, how they interact with each other, the specific process, a specific ip address on a specific board. That's what you get, but so we're learning the behavior. Yes. Yeah, that's very good. But how do you make sure you only learn good behavior? Exactly. How do we make sure that it's not bad? We actually verify me insured. It's all good. We ensured that everybody these reputation is verified. We ensured that the haven is verified. Let's go to svc host, for example. This process can exhibit hundreds of behaviors across numerous. Realize what we do here is we actually verify that failure saw us. It's actually a machine learning models that had been trained on millions of instances of good, bad at you said, and then automatically verify that for okay, so we said, you. We learned simply, learn now, lock. How does that work? Well, once you learned the application, locking it is as simple as clicking on that verify and protect button and then you can lock both the compute and network and it's done. So we've pushed those policies into nsx and microsegmentation has been established actually locked down the compute. What is the operating system is exactly. Let's first look at compute, protected the processes and the behaviors are locked down to exactly what is allowed for that application. And we have bacon policies and program your firewall. This is nsx being configured automatically for you, laurie, with one single click. Very good. So we said learn lock. Now, how does this adapt thing work? Well, a bad change is the only constant, but modern applications applications change on a continuous basis. What we do is actually pretty simple. We look at every change as it comes in determinant is good or bad. If it's good, we say allow it, update the policies. That's bad. We denied. Let's look at an example as asco dxc. It's exhibiting a behavior that they've not seen getting the learning period. Okay? So this machine has never behave this This hasn't been that way. But. way. But again, our machine learning models had seen thousands of instances of this process. They know this is normal. It talks on three 89 all the time. So what it's done to the few things, it's lowered the criticality of the alarm. Okay, so false positive. Exactly. The bane of security operations, false positives, and it has gone and updated. Jane does locks on compute and network to allow for that behavior. Applications continues to work on this project. Okay, so we can learn and adapt and action right through the compute and the network. What about the client? Well, we do with workplace one, intelligence protect and manage end user endpoint, but what's one intelligence? Nsx and actually work together to protect your entire data center infrastructure, but don't believe me. You can watch it for yourself tomorrow tom cornu keynote. You want to be there, at 1:00 PM, be there or be nowhere. I love you. Thank you veejay. Great job. Thank you so much. So the idea of intrinsic security and ensuring good, we believe fundamentally changing how security will be delivered in the enterprise in the future and changing the entire security industry. We've covered a lot today. I'm thrilled as I stand on stage to stand before this community that truly has been at the center of changing the world of technology over the last couple of decades. In it. We've talked about this idea of the super powers of technology and as they accelerate the huge demand for what you do, you know in the same way we together created this idea of the virtual infrastructure admin. You'll think about all the jobs that we are spawning in the discussion that we had today, the new skills, the new opportunities for each one of us in this room today, quantum program, machine learning engineer, iot and edge expert. We're on the cusp of so many new capabilities and we need you and your skills to do that. The skills that you possess, the abilities that you have to work across these silos of technology and enabled tomorrow. I'll tell you, I am now 38 years in the industry and I've never been more excited because together we have the opportunity to build on the things that collective we have done over the last four decades and truly have a positive global impact. These are hard problems, but I believe together we can successfully extend the lifespan of every human being. I believe together we can eradicate chronic diseases that have plagued mankind for centuries. I believe we can lift the remaining 10 percent of humanity out of extreme poverty. I believe that we can reschedule every worker in the age of the superpowers. I believe that we can give modern ever education to every child on the planet, even in the of slums. I believe that together we could reverse the impact of climate change. I believe that together we have the opportunity to make these a reality. I believe this possibility is only possible together with you. I asked you have a please have a wonderful vm world. Thanks for listening. Happy 20th birthday. Have a great topic.