(upbeat music) >> We are back, approaching the finish line here at Supercomputing 22, our last interview of the day, our last interview of the show. And I have to say Dave Nicholson, my co-host, My name is Paul Gillin. I've been attending trade shows for 40 years Dave, I've never been to one like this. The type of people who are here, the type of problems they're solving, what they talk about, the trade shows are typically, they're so speeds and feeds. They're so financial, they're so ROI, they all sound the same after a while. This is truly a different event. Do you get that sense? >> A hundred percent. Now, I've been attending trade shows for 10 years since I was 19, in other words, so I don't have necessarily your depth. No, but seriously, Paul, totally, completely, completely different than any other conference. First of all, there's the absolute allure of looking at the latest and greatest, coolest stuff. I mean, when you have NASA lecturing on things when you have Lawrence Livermore Labs that we're going to be talking to here in a second it's a completely different story. You have all of the academics you have students who are in competition and also interviewing with organizations. It's phenomenal. I've had chills a lot this week. >> And I guess our last two guests sort of represent that cross section. Armando Acosta, director of HPC Solutions, High Performance Solutions at Dell. And Matt Leininger, who is the HPC Strategist at Lawrence Livermore National Laboratory. Now, there is perhaps, I don't know you can correct me on this, but perhaps no institution in the world that uses more computing cycles than Lawrence Livermore National Laboratory and is always on the leading edge of what's going on in Supercomputing. And so we want to talk to both of you about that. Thank you. Thank you for joining us today. >> Sure, glad to be here. >> For having us. >> Let's start with you, Armando. Well, let's talk about the juxtaposition of the two of you. I would not have thought of LLNL as being a Dell reference account in the past. Tell us about the background of your relationship and what you're providing to the laboratory. >> Yeah, so we're really excited to be working with Lawrence Livermore, working with Matt. But actually this process started about two years ago. So we started looking at essentially what was coming down the pipeline. You know, what were the customer requirements. What did we need in order to make Matt successful. And so the beauty of this project is that we've been talking about this for two years, and now it's finally coming to fruition. And now we're actually delivering systems and delivering racks of systems. But what I really appreciate is Matt coming to us, us working together for two years and really trying to understand what are the requirements, what's the schedule, what do we need to hit in order to make them successful >> At Lawrence Livermore, what drives your computing requirements I guess? You're working on some very, very big problems but a lot of very complex problems. How do you decide what you need to procure to address them? >> Well, that's a difficult challenge. I mean, our mission is a national security mission dealing with making sure that we do our part to provide the high performance computing capabilities to the US Department of Energy's National Nuclear Security Administration. We do that through the Advanced Simulation computing program. Its goal is to provide that computing power to make sure that the US nuclear rep of the stockpile is safe, secure, and effective. So how we go about doing that? There's a lot of work involved. We have multiple platform lines that we accomplish that goal with. One of them is the advanced technology systems. Those are the ones you've heard about a lot, they're pushing towards exit scale, the GPU technologies incorporated into those. We also have a second line, a platform line, called the Commodity Technology Systems. That's where right now we're partnering with Dell on the latest generation of those. Those systems are a little more conservative, they're right now CPU only driven but they're also intended to be the everyday work horses. So those are the first systems our users get on. It's very easy for them to get their applications up and running. They're the first things they use usually on a day to day basis. They run a lot of small to medium size jobs that you need to do to figure out how to most effectively use what workloads you need to move to the even larger systems to accomplish our mission goals. >> The workhorses. >> Yeah. >> What have you seen here these last few days of the show, what excites you? What are the most interesting things you've seen? >> There's all kinds of things that are interesting. Probably most interesting ones I can't talk about in public, unfortunately, 'cause of NDA agreements, of course. But it's always exciting to be here at Supercomputing. It's always exciting to see the products that we've been working with industry and co-designing with them on for, you know, several years before the public actually sees them. That's always an exciting part of the conference as well specifically with CTS-2, it's exciting. As was mentioned before, I've been working with Dell for nearly two years on this, but the systems first started being delivered this past August. And so we're just taking the initial deliveries of those. We've deployed, you know, roughly about 1600 nodes now but that'll ramp up to over 6,000 nodes over the next three or four months. >> So how does this work intersect with Sandia and Los Alamos? Explain to us the relationship there. >> Right, so those three laboratories are the laboratories under the National Nuclear Security Administration. We partner together on CTS. So the architectures, as you were asking, how do we define these things, it's the labs coming together. Those three laboratories we define what we need for that architecture. We have a joint procurement that is run out of Livermore but then the systems are deployed at all three laboratories. And then they serve the programs that I mentioned for each laboratory as well. >> I've worked in this space for a very long time you know I've worked with agencies where the closest I got to anything they were actually doing was the sort of guest suite outside the secure area. And sometimes there are challenges when you're communicating, it's like you have a partner like Dell who has all of these things to offer, all of these ideas. You have requirements, but maybe you can't share 100% of what you need to do. How do you navigate that? Who makes the decision about what can be revealed in these conversations? You talk about NDA in terms of what's been shared with you, you may be limited in terms of what you can share with vendors. Does that cause inefficiency? >> To some degree. I mean, we do a good job within the NSA of understanding what our applications need and then mapping that to technical requirements that we can talk about with vendors. We also have kind of in between that we've done this for many years. A recent example is of course with the exit scale computing program and some things it's doing creating proxy apps or mini apps that are smaller versions of some of the things that we are important to us. Some application areas are important to us, hydrodynamics, material science, things like that. And so we can collaborate with vendors on those proxy apps to co-design systems and tweak the architectures. In fact, we've done a little bit that with CTS-2, not as much in CTS as maybe in the ATS platforms but that kind of general idea of how we collaborate through these proxy applications is something we've used across platforms. >> Now is Dell one of your co-design partners? >> In CTS-2 absolutely, yep. >> And how, what aspects of CTS-2 are you working on with Dell? >> Well, the architecture itself was the first, you know thing we worked with them on, we had a procurement come out, you know they bid an architecture on that. We had worked with them, you know but previously on our requirements, understanding what our requirements are. But that architecture today is based on the fourth generation Intel Xeon that you've heard a lot about at the conference. We are one of the first customers to get those systems in. All the systems are interconnected together with the Cornell Network's Omni-Path Network that we've used before and are very excited about as well. And we build up from there. The systems get integrated in by the operations teams at the laboratory. They get integrated into our production computing environment. Dell is really responsible, you know for designing these systems and delivering to the laboratories. The laboratories then work with Dell. We have a software stack that we provide on top of that called TOSS, for Tri-Lab Operating System. It's based on Redhead Enterprise Linux. But the goal there is that it allows us, a common user environment, a common simulation environment across not only CTS-2, but maybe older systems we have and even the larger systems that we'll be deploying as well. So from a user perspective they see a common user interface, a common environment across all the different platforms that they use at Livermore and the other laboratories. >> And Armando, what does Dell get out of the co-design arrangement with the lab? >> Well, we get to make sure that they're successful. But the other big thing that we want to do, is typically when you think about Dell and HPC, a lot of people don't make that connection together. And so what we're trying to do is make sure that, you know they know that, hey, whether you're a work group customer at the smallest end or a super computer customer at the highest end, Dell wants to make sure that we have the right setup portfolio to match any needs across this. But what we were really excited about this, this is kind of our, you know big CTS-2 first thing we've done together. And so, you know, hopefully this has been successful. We've made Matt happy and we look forward to the future what we can do with bigger and bigger things. >> So will the labs be okay with Dell coming up with a marketing campaign that said something like, "We can't confirm that alien technology is being reverse engineered." >> Yeah, that would fly. >> I mean that would be right, right? And I have to ask you the question directly and the way you can answer it is by smiling like you're thinking, what a stupid question. Are you reverse engineering alien technology at the labs? >> Yeah, you'd have to suck the PR office. >> Okay, okay. (all laughing) >> Good answer. >> No, but it is fascinating because to a degree it's like you could say, yeah, we're working together but if you really want to dig into it, it's like, "Well I kind of can't tell you exactly how some of this stuff is." Do you consider anything that you do from a technology perspective, not what you're doing with it, but the actual stack, do you try to design proprietary things into the stack or do you say, "No, no, no, we're going to go with standards and then what we do with it is proprietary and secret."? >> Yeah, it's more the latter. >> Is the latter? Yeah, yeah, yeah. So you're not going to try to reverse engineer the industry? >> No, no. We want the solutions that we develop to enhance the industry to be able to apply to a broader market so that we can, you know, gain from the volume of that market, the lower cost that they would enable, right? If we go off and develop more and more customized solutions that can be extraordinarily expensive. And so we we're really looking to leverage the wider market, but do what we can to influence that, to develop key technologies that we and others need that can enable us in the high forms computing space. >> We were talking with Satish Iyer from Dell earlier about validated designs, Dell's reference designs for for pharma and for manufacturing, in HPC are you seeing that HPC, Armando, and is coming together traditionally and more of an academic research discipline beginning to come together with commercial applications? And are these two markets beginning to blend? >> Yeah, I mean so here's what's happening, is you have this convergence of HPC, AI and data analytics. And so when you have that combination of those three workloads they're applicable across many vertical markets, right? Whether it's financial services, whether it's life science, government and research. But what's interesting, and Matt won't brag about, but a lot of stuff that happens in the DoE labs trickles down to the enterprise space, trickles down to the commercial space because these guys know how to do it at scale, they know how to do it efficiently and they know how to hit the mark. And so a lot of customers say, "Hey we want what CTS-2 does," right? And so it's very interesting. The way I love it is their process the way they do the RFP process. Matt talked about the benchmarks and helping us understand, hey here's kind of the mark you have to hit. And then at the same time, you know if we make them successful then obviously it's better for all of us, right? You know, I want to secure nuclear stock pile so I hope everybody else does as well. >> The software stack you mentioned, I think Tia? >> TOSS. >> TOSS. >> Yeah. >> How did that come about? Why did you feel the need to develop your own software stack? >> It originated back, you know, even 20 years ago when we first started building Linux clusters when that was a crazy idea. Livermore and other laboratories were really the first to start doing that and then push them to larger and larger scales. And it was key to have Linux running on that at the time. And so we had the. >> So 20 years ago you knew you wanted to run on Linux? >> Was 20 years ago, yeah, yeah. And we started doing that but we needed a way to have a version of Linux that we could partner with someone on that would do, you know, the support, you know, just like you get from an EoS vendor, right? Security support and other things. But then layer on top of that, all the HPC stuff you need either to run the system, to set up the system, to support our user base. And that evolved into to TOSS which is the Tri-Lab Operating System. Now it's based on the latest version of Redhead Enterprise Linux, as I mentioned before, with all the other HPC magic, so to speak and all that HPC magic is open source things. It's not stuff, it may be things that we develop but it's nothing closed source. So all that's there we run it across all these different environments as I mentioned before. And it really originated back in the early days of, you know, Beowulf clusters, Linux clusters, as just needing something that we can use to run on multiple systems and start creating that common environment at Livermore and then eventually the other laboratories. >> How is a company like Dell, able to benefit from the open source work that's coming out of the labs? >> Well, when you look at the open source, I mean open source is good for everybody, right? Because if you make a open source tool available then people start essentially using that tool. And so if we can make that open source tool more robust and get more people using it, it gets more enterprise ready. And so with that, you know, we're all about open source we're all about standards and really about raising all boats 'cause that's what open source is all about. >> And with that, we are out of time. This is our 28th interview of SC22 and you're taking us out on a high note. Armando Acosta, director of HPC Solutions at Dell. Matt Leininger, HPC Strategist, Lawrence Livermore National Laboratories. Great discussion. Hopefully it was a good show for you. Fascinating show for us and thanks for being with us today. >> Thank you very much. >> Thank you for having us >> Dave it's been a pleasure. >> Absolutely. >> Hope we'll be back next year. >> Can't believe, went by fast. Absolutely at SC23. >> We hope you'll be back next year. This is Paul Gillin. That's a wrap, with Dave Nicholson for theCUBE. See here in next time. (soft upbear music)

(bright upbeat music) >> Welcome back to Detroit guys and girls. Lisa Martin here with John Furrier. We've been on the floor at KubeCon + CloudNativeCon North America for about two days now. We've been breaking news, we would have a great conversations, John. We love talking with CUBE alumni whose companies are just taking off. And we get to do that next again. >> Well, this next segment's awesome. We have former CUBE host, Brian Gracely, here who's an executive in this company. And then the entrepreneur who we're going to talk with. She was on theCUBE when it just started now they're extremely successful. It's going to be a great conversation. >> It is, Idit Levine is here, the founder and CEO of solo.io. And as John mentioned, Brian Gracely. You know Brian. He's the VP of Product Marketing and Product Strategy now at solo.io. Guys, welcome to theCUBE, great to have you here. >> Thanks for having us. >> Idit: Thank so much for having us. >> Talk about what's going on. This is a rocket ship that you're riding. I was looking at your webpage, you have some amazing customers. T-Mobile, BMW, Amex, for a marketing guy it must be like, this is just- >> Brian: Yeah, you can't beat it. >> Kid in a candy store. >> Brian: Can't beat it. >> You can't beat it. >> For giant companies like that, giant brands, global, to trust a company of our size it's trust, it's great engineering, it's trust, it's fantastic. >> Idit, talk about the fast trajectory of this company and how you've been able to garner trust with such mass organizations in such a short time period. >> Yes, I think that mainly is just being the best. Honestly, that's the best approach I can say. The team that we build, honestly, and this is a great example of one of them, right? And we're basically getting the best people in the industry. So that's helpful a lot. We are very, very active on the open source community. So basically it building it, anyway, and by doing this they see us everywhere. They see our success. You're starting with a few customers, they're extremely successful and then you're just creating this amazing partnership with them. So we have a very, very unique way we're working with them. >> So hard work, good code. >> Yes. >> Smart people, experience. >> That's all you need. >> It's simple, why doesn't everyone do it? >> It's really easy. (all laughing) >> All good, congratulations. It's been fun to watch you guys grow. Brian, great to see you kicking butt in this great company. I got to ask about the landscape because I love the ServiceMeshCon you guys had on a co-located event on day zero here as part of that program, pretty packed house. >> Brian: Yep. >> A lot of great feedback. This whole ServiceMesh and where it fits in. You got Kubernetes. What's the update? Because everything's kind of coming together- >> Brian: Right. >> It's like jello in the refrigerator it kind of comes together at the same time. Where are we? >> I think the easiest way to think about it is, and it kind of mirrors this event perfectly. So the last four or five years, all about Kubernetes, built Kubernetes. So every one of our customers are the ones who have said, look, for the last two or three years, we've been building Kubernetes, we've had a certain amount of success with it, they're building applications faster, they're deploying and then that success leads to new challenges, right? So we sort of call that first Kubernetes part sort of CloudNative 1.0, this and this show is really CloudNative 2.0. What happens after Kubernetes service mesh? Is that what happens after Kubernetes? And for us, Istio now being part of the CNCF, huge, standardized, people are excited about it. And then we think we are the best at doing Istio from a service mesh perspective. So it's kind of perfect, perfect equation. >> Well, I'll turn it on, listen to your great Cloud cast podcast, plug there for you. You always say what is it and what isn't it? >> Brian: Yeah. >> What is your product and what isn't it? >> Yeah, so our product is, from a purely product perspective it's service mesh and API gateway. We integrate them in a way that nobody else does. So we make it easier to deploy, easier to manage, easier to secure. I mean, those two things ultimately are, if it's an internal API or it's an external API, we secure it, we route it, we can observe it. So if anybody's, you're building modern applications, you need this stuff in order to be able to go to market, deploy at scale all those sort of things. >> Idit, talk about some of your customer conversations. What are the big barriers that they've had, or the challenges, that solo.io comes in and just wipes off the table? >> Yeah, so I think that a lot of them, as Brian described it, very, rarely they had a success with Kubernetes, maybe a few clusters, but then they basically started to on-ramp more application on those clusters. They need more cluster maybe they want multi-class, multi-cloud. And they mainly wanted to enable the team, right? This is why we all here, right? What we wanted to eventually is to take a piece of the infrastructure and delegate it to our customers which is basically the application team. So I think that that's where they started to see the problem because it's one thing to take some open source project and deploy it very little bit but the scale, it's all about the scale. How do you enable all those millions of developers basically working on your platform? How do you scale multi-cloud? What's going on if one of them is down, how do you fill over? So that's exactly the problem that they have >> Lisa: Which is critical for- >> As bad as COVID was as a global thing, it was an amazing enabler for us because so many companies had to say... If you're a retail company, your front door was closed, but you still wanted to do business. So you had to figure out, how do I do mobile? How do I be agile? If you were a company that was dealing with like used cars your number of hits were through the roof because regular cars weren't available. So we have all these examples of companies who literally overnight, COVID was their digital transformation enabler. >> Lisa: Yes. Yes. >> And the scale that they had to deal with, the agility they had to deal with, and we sort of fit perfectly in that. They re-looked at what's our infrastructure look like? What's our security look like? We just happened to be right place in the right time. >> And they had skillset issues- >> Skillsets. >> Yeah. >> And the remote work- >> Right, right. >> Combined with- >> Exactly. >> Modern upgrade gun-to-the-head, almost, kind of mentality. >> And we're really an interesting company. Most of the interactions we do with customers is through Slack, obviously it was remote. We would probably be a great Slack case study in terms of how to do business because our customers engage with us, with engineers all over the world, they look like one team. But we can get them up and running in a POC, in a demo, get them through their things really, really fast. It's almost like going to the public cloud, but at whatever complexity they want. >> John: Nice workflow. >> So a lot of momentum for you guys silver linings during COVID, which is awesome we do hear a lot of those stories of positive things, the acceleration of digital transformation, and how much, as consumers, we've all benefited from that. Do you have one example, Brian, as the VP of product marketing, of a customer that you really think in the last two years just is solo.io's value proposition on a platter? >> I'll give you one that I think everybody can understand. So most people, at least in the United States, you've heard of Chick-fil-A, retail, everybody likes the chicken. 2,600 stores in the US, they all shut down and their business model, it's good food but great personal customer experience. That customer experience went away literally overnight. So they went from barely anybody using the mobile application, and hence APIs in the backend, half their business now goes through that to the point where, A, they shifted their business, they shifted their customer experience, and they physically rebuilt 2,600 stores. They have two drive-throughs now that instead of one, because now they have an entire one dedicated to that mobile experience. So something like that happening overnight, you could never do the ROI for it, but it's changed who they are. >> Lisa: Absolutely transformative. >> So, things like that, that's an example I think everybody can kind of relate to. Stuff like that happened. >> Yeah. >> And I think that's also what's special is, honestly, you're probably using a product every day. You just don't know that, right? When you're swiping your credit card or when you are ordering food, or when you using your phone, honestly the amount of customer they were having, the space, it's like so, every industry- >> John: How many customers do you have? >> I think close to 200 right now. >> Brian: Yeah. >> Yeah. >> How many employees, can you gimme some stats? Funding, employees? What's the latest statistics? >> We recently found a year ago $135 million for a billion dollar valuation. >> Nice. >> So we are a unicorn. I think when you took it we were around like 50 ish people. Right now we probably around 180, and we are growing, we probably be 200 really, really quick. And I think that what's really, really special as I said the interaction that we're doing with our customers, we're basically extending their team. So for each customer is basically a Slack channel. And then there is a lot of people, we are totally global. So we have people in APAC, in Australia, New Zealand, in Singapore we have in AMEA, in UK and in Spain and Paris, and other places, and of course all over US. >> So your use case on how to run a startup, scale up, during the pandemic, complete clean sheet of paper. >> Idit: We had to. >> And what happens, you got Slack channels as your customer service collaboration slash productivity. What else did you guys do differently that you could point to that's, I would call, a modern technique for an entrepreneurial scale? >> So I think that there's a few things that we are doing different. So first of all, in Solo, honestly, there is a few things that differentiated from, in my opinion, most of the companies here. Number one is look, you see this, this is a lot, a lot of new technology and one of the things that the customer is nervous the most is choosing the wrong one because we saw what happened, right? I don't know the orchestration world, right? >> John: So choosing and also integrating multiple things at the same time. >> Idit: Exactly. >> It's hard. >> And this is, I think, where Solo is expeditious coming to place. So I mean we have one team that is dedicated like open source contribution and working with all the open source community and I think we're really good at picking the right product and basically we're usually right, which is great. So if you're looking at Kubernetes, we went there for the beginning. If you're looking at something like service mesh Istio, we were all envoy proxy and out of process. So I think that by choosing these things, and now Cilium is something that we're also focusing on. I think that by using the right technology, first of all you know that it's very expensive to migrate from one to the other if you get it wrong. So I think that's one thing that is always really good at. But then once we actually getting those portal we basically very good at going and leading those community. So we are basically bringing the customers to the community itself. So we are leading this by being in the TOC members, right? The Technical Oversight Committee. And we are leading by actually contributing a lot. So if the customer needs something immediately, we will patch it for him and walk upstream. So that's kind of like the second thing. And the third one is innovation. And that's really important to us. So we pushing the boundaries. Ambient, that we announced a month ago with Google- >> And STO, the book that's out. >> Yes, the Ambient, it's basically a modern STO which is the future of SDL. We worked on it with Google and their NDA and we were listed last month. This is exactly an example of us basically saying we can do it better. We learn from our customers, which is huge. And now we know that we can do better. So this is the third thing, and the last one is the partnership. I mean honestly we are the extension team of the customer. We are there on Slack if they need something. Honestly, there is a reason why our renewal rate is 98.9 and our net extension is 135%. I mean customers are very, very happy. >> You deploy it, you make it right. >> Idit: Exactly, exactly. >> The other thing we did, and again this was during COVID, we didn't want to be a shell-for company. We didn't want to drop stuff off and you didn't know what to do with it. We trained nearly 10,000 people. We have something called Solo Academy, which is free, online workshops, they run all the time, people can come and get hands on training. So we're building an army of people that are those specialists that have that skill set. So we don't have to walk into shops and go like, well okay, I hope six months from now you guys can figure this stuff out. They're like, they've been doing that. >> And if their friends sees their friend, sees their friend. >> The other thing, and I got to figure out as a marketing person how to do this, we have more than a few handfuls of people that they've got promoted, they got promoted, they got promoted. We keep seeing people who deploy our technologies, who, because of this stuff they're doing- >> John: That's a good sign. They're doing it at at scale, >> John: That promoter score. >> They keep getting promoted. >> Yeah, that's amazing. >> That's a powerful sort of side benefit. >> Absolutely, that's a great thing to have for marketing. Last question before we ran out of time. You and I, Idit, were talking before we went live, your sessions here are overflowing. What's your overall sentiment of KubeCon 2022 and what feedback have you gotten from all the customers bursting at the seam to come talk to you guys? >> I think first of all, there was the pre-event which we had and it was a lot of fun. We talked to a lot of customer, most of them is 500, global successful company. So I think that people definitely... I will say that much. We definitely have the market feed, people interested in this. Brian described very well what we see here which is people try to figure out the CloudNative 2.0. So that's number one. The second thing is that there is a consolidation, which I like, I mean STO becoming right now a CNCF project I think it's a huge, huge thing for all the community. I mean, we're talking about all the big tweak cloud, we partner with them. I mean I think this is a big sign of we agree which I think is extremely important in this community. >> Congratulations on all your success. >> Thank you so much. >> And where can customers go to get their hands on this, solo.io? >> Solo.io? Yeah, absolutely. >> Awesome guys, this has been great. Congratulations on the momentum. >> Thank you. >> The rocket ship that you're riding. We know you got to get to the airport we're going to let you go. But we appreciate your insights and your time so much, thank you. >> Thank you so much. >> Thanks guys, we appreciate it. >> A pleasure. >> Thanks. >> For our guests and John Furrier, This is Lisa Martin live in Detroit, had to think about that for a second, at KubeCon 2022 CloudNativeCon. We'll be right back with our final guests of the day and then the show wraps, so stick around. (gentle music)

(inspiring music) >> Announcer: theCUBE presents HPE Discover 2022. Brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022, from the Venetian in Las Vegas, the first Discover since 2019. I really think this is my 14th Discover, when you include HP, when you include Europe. And I got to say this Discover, I think has more energy than any one that I've ever seen, about 8,000 people here. Really excited to have one of HPE's longstanding partners, Veeam CTO, Danny Allen is here, joined by David Harvey, Vice President of Strategic Alliances at Veeam. Guys, good to see you again. It was just earlier, let's see, last month, we were together out here. >> Yeah, just a few weeks ago. It's fantastic to be back and what it's telling us, technology industry is coming back. >> And the events business, of course, is coming back, which we love. I think the expectations were cautious. You saw it at VeeamON, a little more than you expected, a lot of great energy. A lot of people, 'cause it was last month, it was their first time out, >> Yes. >> in two years. Here, I think people have started to go out more, but still, an energy that's palpable. >> You can definitely feel it. Last night, I think I went to four consecutive events and everyone's out having those discussions and having conversations, it's good to be back. >> You guys hosted the Storage party last night, which is epic. I left at midnight, I took a picture, it was still packed. I said, okay, time to go, nothing good happens after midnight kids. David, talk about the alliance with HPE, how it's evolved, and where you see it going? >> I appreciate it, and certainly this, as you said, has been a big alliance for us. Over 10 years or so, fantastic integrations across the board. And you touched on 2019 Discover. We launched with GreenLake at that event, we were one of the launch partners, and we've seen fantastic growth. Overall, what we're excited about, is that continuation of the movement of the customer's buying patterns in line with HPE's portfolio and in line with Veeam. We continue to be with all their primary, secondary storage, we continue to be a spearhead position with GreenLake, which we're really excited about. And we're also really excited to hear from HPE, unfortunately under NDA, some of their future stuff they're investing in, which is a really nice invigoration for what they're doing for their portfolio. And we see that being a big deal for us over the next 24 months. >> Your relationship with HPE predates the HP, HPE split. >> Mmm. >> Yes. >> But it was weird, because they had Data Protector, and that was a quasi-competitor, or really not, but it was a competitor, a legacy competitor, of what you guys have, kind of modern data protection I think is the tagline, if I got it right. Post the split, that was an S-curve moment, wasn't it, in terms of the partnership? >> It really was. If you go back 10 years, we did our first integration sending data to StoreOnce and we had some blueprints around that. But now, if you look what we have, we have integrations on the primary side, so, 3PAR, Primera, Nimble, all their top-tier storage, we can manage the snapshots. We have integration on the target side. We integrate with Catalyst in the movement of data and the management of data. And, as David alluded to, we integrate with GreenLake. So, customers who want to take this as a consumption model, we integrate with that. And so it's been, like you said, the strongest relationship that we have on the technology alliance side. >> So, V12, you announced at VeeamON. What does that mean for HPE customers, the relationship? Maybe you guys could both talk about that. >> Technology side, to touch on a few things that we're doing with them, ransomware has been a huge issue. Security's been a big theme, obviously, at the conference, >> Dave: Yeah, you bet. and one of the things we're doing in V12 is adding immutability for both StoreOnce and StoreEver. So, we take the features that our partners have, immutability being big in the security space, and we integrate that fully into the product. So a customer checks a box and says, hey, I want to make sure that the data is secure. >> Yeah, and also, it's another signification about the relationship. Every single release we've done has had HPE at the heart of it, and the same thing is being said with V12. And it shows to our customers, the continual commitment. Relationships come and go. They're hard, and the great news is, 10 years has proven that we get through good times and tricky situations, and we both continue to invest, et cetera. And I think there's a lot of peace of mind and the revenue figures prove that, which is what we're really excited about. >> Yeah I want to come back to that, but just to follow up, Danny, on that immutability, that's a feature that you check? It's service within GreenLake, or within Veeam? How does that all work? >> We have immutability now depending on the target. We introduced the ability to send data, for example, into S3 two years ago, and make it immutable when you send it to an S3 or S3 compatible environment. We added, in Version 11, the ability to take a Linux repository and make it, and harden it, essentially make it immutable. But what we're doing now is taking our partner systems like StoreOnce, like StoreEver, and when we send data there, we take advantage of an API flag or whatever it happens to be, that it makes the data, when it's written to that system, can't be deleted, can't be encrypted. Now, what does that mean for a customer? Well, we do all the hard work in the back end, it's just a check box. They say, I want to make it immutable, and we manage how long it's immutable. Because if you made everything immutable forever, that's hugely expensive, right? So, it's all about, how long is that immutable before you age it out and make sure the new data coming in is immutable. >> Dave: It's like an insurance policy, you have that overlap. >> Yes. >> Right, okay. And then David, you mentioned the revenue, Lou bears that out. I got the IDC guys comin' on later on today. I'll ask 'em about that, if that's their swim lane. But you guys are basically a statistical tie, with Dell for number one? Am I getting that right? And you're growing at a faster rate, I believe, it's hard to tell 'cause I don't think Dell reports on the pace of its growth within data protection. You guys obviously do, but is that right? It's a statistical tie, is it? >> Yeah, hundred percent. >> Yeah, statistical tie for first place, which we're super excited about. When I joined Veeam, I think we were in fifth place, but we've been in the leader's quadrant of the Gartner Magic- >> Cause and effect there or? (panelists laughing) >> No, I don't think so. >> Dave: Ha, I think maybe. >> We've been on a great trajectory. But statistical tie for first place, greatest growth sequentially, and year-over-year, of all of the data protection vendors. And that's a testament not just to the technology that we're doing, but partnerships with HPE, because you never do this, the value of a technology is not that technology alone, it's the value of that technology within the ecosystem. And so that's why we're here at HPE Discover. It's our joint technology solutions that we're delivering. >> What are your thoughts or what are you seeing in the field on As-a-service? Because of course, the messaging is all about As-a-service, you'd think, oh, a hundred percent of everything is going to be As-a-service. A lot of customers, they don't mind CapEx, they got good, balance sheet, and they're like, hey, we'll take care of this, and, we're going to build our own little internal cloud. But, what are you seeing in the market in terms of As-a-service, versus, just traditional licensing models? >> Certainly, there's a mix between the two. What I'd say, is that sources that are already As-a-service, think Microsoft 365, think AWS, Azure, GCP, the cloud providers. There's a natural tendency for the customer to want the data protection As-a-service, as well for those. But if you talk about what's on premises, customers who have big data centers deployed, they're not yet, the pendulum has not shifted for that to be data protection As-a-service. But we were early to this game ourselves. We have 10,000, what we call, Veeam Cloud Service Providers, that are offering data protection As-a-service, whether it be on premises, so they're remotely managing it, or cloud hosted, doing data protection for that. >> So, you don't care. You're providing the technology, and then your customers are actually choosing the delivery model. Is that correct? >> A hundred percent, and if you think about what GreenLake is doing for example, that started off as being a financial model, but now they're getting into that services delivery. And what we want to do is enable them to deliver it, As-a-service, not just the financial model, but the outcome for the customer. And so our technology, it's not just do backup, it's do backup for a multi-tenant, multi-customer environment that does all of the multi-tenancy and billing and charge back as part of that service. >> Okay, so you guys don't report on this, but I'm going to ask the question anyway. You're number one now, let's call you, let's declare number one, 'cause we're well past that last reporting and you're growin' faster. So go another quarter, you're now number one, so you're the largest. Do you spend more on R&D in data protection than any other company? >> Yes, I'm quite certain that we do. Now, we have an unfair advantage because we have 450,000 customers. I don't think there's any other data protection company out there, the size and scope and scale, that we have. But we've been expanding, our largest R&D operation center's in Prague, it's in Czech Republic, but we've been expanding that. Last year it grew 40% year on year in R&D, so big investment in that space. You can see this just through our product space. Five years ago, we did data protection of VMware only, and now we do all the virtual environments, all the physical environments, all the major cloud environments, Kubernetes, Microsoft 365, we're launching Salesforce. We announced that at VeeamON last month and it will be coming out in Q3. All of that is coming from our R&D investments. >> A lot of people expect that when a company like Insight, a PE company, purchases a company like Veeam, that one of the things they'll dial down is R&D. That did not happen in this case. >> No, they very much treat us as a growth company. We had 22% year-over-year growth in 2020, and 25% year-over-year last year. The growth has been tremendous, they continue to give us the freedom. Now, I expect they'll want returns like that continuously, but we have been delivering, they have been investing. >> One of my favorite conversations of the year was our supercloud conversation, which was awesome, thank you for doing that with me. But that's clearly an area of focus, what we call supercloud, and you don't use that term, I know, you do sometimes, but it's not your marketing, I get that. But that is an R&D intensive effort, is it not? To create that common experience. And you see HPE, attempting to do that as well, across all these different estates. >> A hundred percent. We focus on three things, I always say, our differentiators, simplicity, flexibility, and reliability. Making it simple for the customers is not an easy thing to do. Making that checkbox for immutability? We have to do a lot behind the scenes to make it simple. Same thing on flexibility. We don't care if they're using 3PAR, Primera, Nimble, whatever you want to choose as the primary storage, we will take that out of your hands and make it really easy. You mentioned supercloud. We don't care what the cloud infrastructure, it can be on GreenLake, it can be on AWS, can be on Azure, it can be on GCP, it can be on IBM cloud. It is a lot of effort on our part to abstract the cloud infrastructure, but we do that on behalf of our customers to take away that complexity, it's part of our platform. >> Quick follow-up, and then I want to ask a question of David. I like talking to you guys because you don't care where it is, right? You're truly agnostic to it all. I'm trying to figure out this repatriation thing, cause I hear a lot of hey, Dave, you should look into repatriation that's happened all over the place, and I see pockets of it. What are you seeing in terms of repatriation? Have customers over-rotated to the cloud and now they're pullin' back a little bit? Or is it, as I'm claiming, in pockets? What's your visibility on that? >> Three things I see happening. There's the customers who lifted up their data center, moved it into the cloud and they get the first bill. >> (chuckling) Okay. >> And they will repatriate, there's no question. If I talk to those customers who simply lifted up and moved it over because the CIO told them to, they're moving it back on premises. But a second thing that we see is people moving it over, with tweaks. So they'll take their SQL server database and they'll move it into RDS, they'll change some things. And then you have people who are building cloud-native, they're never coming back on premises, they are building it for the cloud environment. So, we see all three of those. We only really see repatriation on that first scenario, when they get that first bill. >> And when you look at the numbers, I think it gets lost, 'cause you see the cloud is growing so fast. So David, what are the conversations like? You had several events last night, The Veeam party, slash Storage party, from HPE. What are you hearing from your alliance partners and the customers at the event. >> I think Danny touched on that point, it's about philosophy of evolution. And I think at the end of the day, whether we're seeing it with our GSI alliances we've got out there, or with the big enterprise conversations we're having with HPE, it's about understanding which workloads they want to move. In our mind, the customers are getting much smarter in making that decision, rather than experimenting. They're really taking a really solid look. And the work we're doing with the GSIs on workplace modernization, data center transformation, they're really having that investment work up front on the workloads, to be able to say, this works for me, for my personality and my company. And so, to the point about movement, it's more about decisive decision at the start, and not feeling like the remit is, I have to do one thing or another, it's about looking at that workflow position. And that's what we've seen with the revenue part as well. We've seen our movement to GreenLake tremendously grow in the last 18 months to two years. And from our GSI work as well, we're seeing the types of conversations really focus on that workload, compared to, hey, I just need a backup solution, and that's really exciting. >> Are you having specific conversations about security, or is it a data protection conversation still, (David chuckles) that's an adjacency to security? >> That's a great question. And I think it's a complex one, because if you come to a company like Veeam, we are there, and you touched on it before, we provide a solution when something has happened with security. We're not doing intrusion detection, we're not doing that barrier position at the end of it, but it's part of an end-to-end assumption. And I don't think that at this particular point, I started in security with RSA and Check Point, it was about layers of protection. Now it's layers of protection, and the inevitability that at some point something will happen, so about the recovery. So the exciting conversations we're having, especially with the big enterprises, is not about the fear factor, it's about, at some point something's going to occur. Speed of recovery is the conversation. And so for us, and your question is, are they talking to us about security, or more, the continuity position? And that's where the synergy's getting a lot simpler, rather than a hard demark between security and backup. >> Yeah, when you look at the stock market, everything's been hit, but security, with the exception of Okta, 'cause it got that weird benign hack, but security, generally, is an area that CIOs have said, hey, we can't really dial that back. We can maybe, some other discretionary stuff, we'll steal and prioritize. But security seems to be, and I think data protection is now part of that discussion. You're not a security company. We've seen some of your competitors actually pivot to become security companies. You're not doing that, but it's very clearly an adjacency, don't you think? >> It's an adjacency, and it's a new conversation that we're having with the Chief Information Security Officer. I had a meeting an hour ago with a customer who was hit by ransomware, and they got the call at 2:00 AM in the morning, after the ransomware they recovered their entire portfolio within 36 hours, from backups. Didn't even contact Veeam, I found out during this meeting. But that is clearly something that the Chief Information Security Officer wants to know about. It's part of his purview, is the recovery of that data. >> And they didn't pay the ransom? >> And they did not pay the ransom, not a penny. >> Ahh, we love those stories. Guys, thanks so much for coming on theCUBE. Congratulations on all the success. Love when you guys come on, and it was such a fun event at VeeamON. Great event here, and your presence is, was seen. The Veeam green is everywhere, so appreciate your time. >> Thank you. >> Thanks, Dave. >> Okay, and thank you for watching. This is Dave Vellante for John Furrier and Lisa Martin. We'll be back right after this short break. You're watching theCUBE's coverage of HPE Discover 2022, from Las Vegas. (inspiring music)

(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS, and our community partners. >>Hi everyone. Welcome back to the cubes. Virtual coverage of AWS reinvent 2020 virtual. We are the cube virtual I'm John ferry, your host with my coach, Dave Alante for keynote analysis from Swami's machine learning, all things, data huge. Instead of announcements, the first ever machine learning keynote at a re-invent Dave. Great to see you. Thanks Johnny. And from Boston, I'm here in Palo Alto. We're doing the cube remote cube virtual. Great to see you. >>Yeah, good to be here, John, as always. Wall-to-wall love it. So, so, John, um, how about I give you my, my key highlights from the, uh, from the keynote today, I had, I had four kind of curated takeaways. So the first is that AWS is, is really trying to simplify machine learning and use machine intelligence into all applications. And if you think about it, it's good news for organizations because they're not the become machine learning experts have invent machine learning. They can buy it from Amazon. I think the second is they're trying to simplify the data pipeline. The data pipeline today is characterized by a series of hyper specialized individuals. It engineers, data scientists, quality engineers, analysts, developers. These are folks that are largely live in their own swim lane. Uh, and while they collaborate, uh, there's still a fairly linear and complicated data pipeline, uh, that, that a business person or a data product builder has to go through Amazon making some moves to the front of simplify that they're expanding data access to the line of business. I think that's a key point. Is there, there increasingly as people build data products and data services that can monetize, you know, for their business, either cut costs or generate revenue, they can expand that into line of business where there's there's domain context. And I think the last thing is this theme that we talked about the other day, John of extending Amazon, AWS to the edge that we saw that as well in a number of machine learning tools that, uh, Swami talked about. >>Yeah, it was great by the way, we're live here, uh, in Palo Alto in Boston covering the analysis, tons of content on the cube, check out the cube.net and also check out at reinvent. There's a cube section as there's some links to so on demand videos with all the content we've had. Dave, I got to say one of the things that's apparent to me, and this came out of my one-on-one with Andy Jassy and Andy Jassy talked about in his keynote is he kind of teased out this idea of training versus a more value add machine learning. And you saw that today in today's announcement. To me, the big revelation was that the training aspect of machine learning, um, is what can be automated away. And it's under a lot of controversy around it. Recently, a Google paper came out and the person was essentially kind of, kind of let go for this. >>But the idea of doing these training algorithms, some are saying is causes more harm to the environment than it does good because of all the compute power it takes. So you start to see the positioning of training, which can be automated away and served up with, you know, high powered ships and that's, they consider that undifferentiated heavy lifting. In my opinion, they didn't say that, but that's clearly what I see coming out of this announcement. The other thing that I saw Dave that's notable is you saw them clearly taking a three lane approach to this machine, learning the advanced builders, the advanced coders and the developers, and then database and data analysts, three swim lanes of personas of target audience. Clearly that is in line with SageMaker and the embedded stuff. So two big revelations, more horsepower required to process training and modeling. Okay. And to the expansion of the personas that are going to be using machine learning. So clearly this is a, to me, a big trend wave that we're seeing that validates some of the startups and I'll see their SageMaker and some of their products. >>Well, as I was saying at the top, I think Amazon's really trying, working hard on simplifying the whole process. And you mentioned training and, and a lot of times people are starting from scratch when they have to train models and retrain models. And so what they're doing is they're trying to create reusable components, uh, and allow people to, as you pointed out to automate and streamline some of that heavy lifting, uh, and as well, they talked a lot about, uh, doing, doing AI inferencing at the edge. And you're seeing, you know, they, they, uh, Swami talked about several foundational premises and the first being a foundation of frameworks. And you think about that at the, at the lowest level of their S their ML stack. They've got, you know, GPU's different processors, inferential, all these alternative processes, processors, not just the, the Xav six. And so these are very expensive resources and Swami talked a lot about, uh, and his colleagues talked a lot about, well, a lot of times the alternative processor is sitting there, you know, waiting, waiting, waiting. And so they're really trying to drive efficiency and speed. They talked a lot about compressing the time that it takes to, to run these, these models, uh, from, from sometimes weeks down to days, sometimes days down to hours and minutes. >>Yeah. Let's, let's unpack these four areas. Let's stay on the firm foundation because that's their core competency infrastructure as a service. Clearly they're laying that down. You put the processors, but what's interesting is the TensorFlow 92% of tensor flows on Amazon. The other thing is that pie torch surprisingly is back up there, um, with massive adoption and the numbers on pie torch literally is on fire. I was coming in and joke on Twitter. Um, we, a PI torch is telling because that means that TensorFlow is originally part of Google is getting, is getting a little bit diluted with other frameworks, and then you've got MX net, some other things out there. So the fact that you've got PI torch 91% and then TensorFlow 92% on 80 bucks is a huge validation. That means that the majority of most machine learning development and deep learning is happening on AWS. Um, >>Yeah, cloud-based, by the way, just to clarify, that's the 90% of cloud-based cloud, uh, TensorFlow runs on and 91% of cloud-based PI torch runs on ADM is amazingly massive numbers. >>Yeah. And I think that the, the processor has to show that it's not trivial to do the machine learning, but, you know, that's where the infrared internship came in. That's kind of where they want to go lay down that foundation. And they had Tanium, they had trainee, um, they had, um, infrared chow was the chip. And then, you know, just true, you know, distributed training training on SageMaker. So you got the chip and then you've got Sage makers, the middleware games, almost like a machine learning stack. That's what they're putting out there >>And how bad a Gowdy, which was, which is, which is a patrol also for training, which is an Intel based chip. Uh, so that was kind of interesting. So a lot of new chips and, and specialized just, we've been talking about this for awhile, particularly as you get to the edge and do AI inferencing, you need, uh, you know, a different approach than we're used to with the general purpose microbes. >>So what gets your take on tenant? Number two? So tenant number one, clearly infrastructure, a lot of announcements we'll go through those, review them at the end, but tenant number two, that Swami put out there was creating the shortest path to success for builders or machine learning builders. And I think here you lays out the complexity, Dave butts, mostly around methodology, and, you know, the value activities required to execute. And again, this points to the complexity problem that they have. What's your take on this? >>Yeah. Well you think about, again, I'm talking about the pipeline, you collect data, you just data, you prepare that data, you analyze that data. You, you, you make sure that it's it's high quality and then you start the training and then you're iterating. And so they really trying to automate as much as possible and simplify as much as possible. What I really liked about that segment of foundation, number two, if you will, is the example, the customer example of the speaker from the NFL, you know, talked about, uh, you know, the AWS stats that we see in the commercials, uh, next gen stats. Uh, and, and she talked about the ways in which they've, well, we all know they've, they've rearchitected helmets. Uh, they've been, it's really a very much database. It was interesting to see they had the spectrum of the helmets that were, you know, the safest, most safe to the least safe and how they've migrated everybody in the NFL to those that they, she started a 24%. >>It was interesting how she wanted a 24% reduction in reported concussions. You know, you got to give the benefit of the doubt and assume some of that's through, through the data. But you know, some of that could be like, you know, Julian Edelman popping up off the ground. When, you know, we had a concussion, he doesn't want to come out of the game with the new protocol, but no doubt, they're collecting more data on this stuff, and it's not just head injuries. And she talked about ankle injuries, knee injuries. So all this comes from training models and reducing the time it takes to actually go from raw data to insights. >>Yeah. I mean, I think the NFL is a great example. You and I both know how hard it is to get the NFL to come on and do an interview. They're very coy. They don't really put their name on anything much because of the value of the NFL, this a meaningful partnership. You had the, the person onstage virtually really going into some real detail around the depth of the partnership. So to me, it's real, first of all, I love stat cast 11, anything to do with what they do with the stats is phenomenal at this point. So the real world example, Dave, that you starting to see sports as one metaphor, healthcare, and others are going to see those coming in to me, totally a tale sign that Amazon's continued to lead. The thing that got my attention was is that it is an IOT problem, and there's no reason why they shouldn't get to it. I mean, some say that, Oh, concussion, NFL is just covering their butt. They don't have to, this is actually really working. So you got the tech, why not use it? And they are. So that, to me, that's impressive. And I think that's, again, a digital transformation sign that, that, you know, in the NFL is doing it. It's real. Um, because it's just easier. >>I think, look, I think, I think it's easy to criticize the NFL, but the re the reality is, is there anything old days? It was like, Hey, you get your bell rung and get back out there. That's just the way it was a football players, you know, but Ted Johnson was one of the first and, you know, bill Bellacheck was, was, you know, the guy who sent him back out there with a concussion, but, but he was very much outspoken. You've got to give the NFL credit. Uh, it didn't just ignore the problem. Yeah. Maybe it, it took a little while, but you know, these things take some time because, you know, it's generally was generally accepted, you know, back in the day that, okay, Hey, you'd get right back out there, but, but the NFL has made big investments there. And you can say, you got to give him, give him props for that. And especially given that they're collecting all this data. That to me is the most interesting angle here is letting the data inform the actions. >>And next step, after the NFL, they had this data prep data Wrangler news, that they're now integrating snowflakes, Databricks, Mongo DB, into SageMaker, which is a theme there of Redshift S3 and Lake formation into not the other way around. So again, you've been following this pretty closely, uh, specifically the snowflake recent IPO and their success. Um, this is an ecosystem play for Amazon. What does it mean? >>Well, a couple of things, as we, as you well know, John, when you first called me up, I was in Dallas and I flew into New York and an ice storm to get to the one of the early Duke worlds. You know, and back then it was all batch. The big data was this big batch job. And today you want to combine that batch. There's still a lot of need for batch, but when people want real time inferencing and AWS is bringing that together and they're bringing in multiple data sources, you mentioned Databricks and snowflake Mongo. These are three platforms that are doing very well in the market and holding a lot of data in AWS and saying, okay, Hey, we want to be the brain in the middle. You can import data from any of those sources. And I'm sure they're going to add more over time. Uh, and so they talked about 300 pre-configured data transformations, uh, that now come with stage maker of SageMaker studio with essentially, I've talked about this a lot. It's essentially abstracting away the, it complexity, the whole it operations piece. I mean, it's the same old theme that AWS is just pointing. It's its platform and its cloud at non undifferentiated, heavy lifting. And it's moving it up the stack now into the data life cycle and data pipeline, which is one of the biggest blockers to monetizing data. >>Expand on that more. What does that actually mean? I'm an it person translate that into it. Speak. Yeah. >>So today, if you're, if you're a business person and you want, you want the answers, right, and you want say to adjust a new data source, so let's say you want to build a new, new product. Um, let me give an example. Let's say you're like a Spotify, make it up. And, and you do music today, but let's say you want to add, you know, movies, or you want to add podcasts and you want to start monetizing that you want to, you want to identify, who's watching what you want to create new metadata. Well, you need new data sources. So what you do as a business person that wants to create that new data product, let's say for podcasts, you have to knock on the door, get to the front of the data pipeline line and say, okay, Hey, can you please add this data source? >>And then everybody else down the line has to get in line and Hey, this becomes a new data source. And it's this linear process where very specialized individuals have to do their part. And then at the other end, you know, it comes to self-serve capability that somebody can use to either build dashboards or build a data product. In a lot of that middle part is our operational details around deploying infrastructure, deploying, you know, training machine learning models that a lot of Python coding. Yeah. There's SQL queries that have to be done. So a lot of very highly specialized activities, what Amazon is doing, my takeaway is they're really streamlining a lot of those activities, removing what they always call the non undifferentiated, heavy lifting abstracting away that it complexity to me, this is a real positive sign, because it's all about the technology serving the business, as opposed to historically, it's the business begging the technology department to please help me. The technology department obviously evolving from, you know, the, the glass house, if you will, to this new data, data pipeline data, life cycle. >>Yeah. I mean, it's classic agility to take down those. I mean, it's undifferentiated, I guess, but if it actually works, just create a differentiated product. So, but it's just log it's that it's, you can debate that kind of aspect of it, but I hear what you're saying, just get rid of it and make it simpler. Um, the impact of machine learning is Dave is one came out clear on this, uh, SageMaker clarify announcement, which is a bias decision algorithm. They had an expert, uh, nationally CFUs presented essentially how they're dealing with the, the, the bias piece of it. I thought that was very interesting. What'd you think? >>Well, so humans are biased and so humans build models or models are inherently biased. And so I thought it was, you know, this is a huge problem to big problems in artificial intelligence. One is the inherent bias in the models. And the second is the lack of transparency that, you know, they call it the black box problem, like, okay, I know there was an answer there, but how did it get to that answer and how do I trace it back? Uh, and so Amazon is really trying to attack those, uh, with, with, with clarify. I wasn't sure if it was clarity or clarified, I think it's clarity clarify, um, a lot of entirely certain how it works. So we really have to dig more into that, but it's essentially identifying situations where there is bias flagging those, and then, you know, I believe making recommendations as to how it can be stamped. >>Nope. Yeah. And also some other news deep profiling for debugger. So you could make a debugger, which is a deep profile on neural network training, um, which is very cool again on that same theme of profiling. The other thing that I found >>That remind me, John, if I may interrupt there reminded me of like grammar corrections and, you know, when you're typing, it's like, you know, bug code corrections and automated debugging, try this. >>It wasn't like a better debugger come on. We, first of all, it should be bug free code, but, um, you know, there's always biases of the data is critical. Um, the other news I thought was interesting and then Amazon's claiming this is the first SageMaker pipelines for purpose-built CIC D uh, for machine learning, bringing machine learning into a developer construct. And I think this started bringing in this idea of the edge manager where you have, you know, and they call it the about machine, uh, uh, SageMaker store storing your functions of this idea of managing and monitoring machine learning modules effectively is on the edge. And, and through the development process is interesting and really targeting that developer, Dave, >>Yeah, applying CIC D to the machine learning and machine intelligence has always been very challenging because again, there's so many piece parts. And so, you know, I said it the other day, it's like a lot of the innovations that Amazon comes out with are things that have problems that have come up given the pace of innovation that they're putting forth. And, and it's like the customers drinking from a fire hose. We've talked about this at previous reinvents and the, and the customers keep up with the pace of Amazon. So I see this as Amazon trying to reduce friction, you know, across its entire stack. Most, for example, >>Let me lay it out. A slide ahead, build machine learning, gurus developers, and then database and data analysts, clearly database developers and data analysts are on their radar. This is not the first time we've heard that. But we, as the kind of it is the first time we're starting to see products materialized where you have machine learning for databases, data warehouse, and data lakes, and then BI tools. So again, three different segments, the databases, the data warehouse and data lakes, and then the BI tools, three areas of machine learning, innovation, where you're seeing some product news, your, your take on this natural evolution. >>Well, well, it's what I'm saying up front is that the good news for, for, for our customers is you don't have to be a Google or Amazon or Facebook to be a super expert at AI. Uh, companies like Amazon are going to be providing products that you can then apply to your business. And, and it's allowed you to infuse AI across your entire application portfolio. Amazon Redshift ML was another, um, example of them, abstracting complexity. They're taking, they're taking S3 Redshift and SageMaker complexity and abstracting that and presenting it to the data analysts. So that, that, that individual can worry about, you know, again, getting to the insights, it's injecting ML into the database much in the same way, frankly, the big query has done that. And so that's a huge, huge positive. When you talk to customers, they, they love the fact that when, when ML can be embedded into the, into the database and it simplifies, uh, that, that all that, uh, uh, uh, complexity, they absolutely love it because they can focus on more important things. >>Clearly I'm this tenant, and this is part of the keynote. They were laying out all their announcements, quick excitement and ML insights out of the box, quick, quick site cue available in preview all the announcements. And then they moved on to the next, the fourth tenant day solving real problems end to end, kind of reminds me of the theme we heard at Dell technology worlds last year end to end it. So we are starting to see the, the, the land grab my opinion, Amazon really going after, beyond I, as in pass, they talked about contact content, contact centers, Kendra, uh, lookout for metrics, and that'll maintain men. Then Matt would came on, talk about all the massive disruption on the, in the industries. And he said, literally machine learning will disrupt every industry. They spent a lot of time on that and they went into the computer vision at the edge, which I'm a big fan of. I just loved that product. Clearly, every innovation, I mean, every vertical Dave is up for grabs. That's the key. Dr. Matt would message. >>Yeah. I mean, I totally agree. I mean, I see that machine intelligence as a top layer of, you know, the S the stack. And as I said, it's going to be infused into all areas. It's not some kind of separate thing, you know, like, Coobernetti's, we think it's some separate thing. It's not, it's going to be embedded everywhere. And I really like Amazon's edge strategy. It's this, you, you are the first to sort of write about it and your keynote preview, Andy Jassy said, we see, we see, we want to bring AWS to the edge. And we see data center as just another edge node. And so what they're doing is they're bringing SDKs. They've got a package of sensors. They're bringing appliances. I've said many, many times the developers are going to be, you know, the linchpin to the edge. And so Amazon is bringing its entire, you know, data plane is control plane, it's API APIs to the edge and giving builders or slash developers, the ability to innovate. And I really liked the strategy versus, Hey, here's a box it's, it's got an x86 processor inside on a, throw it over the edge, give it a cool name that has edge in it. And here you go, >>That sounds call it hyper edge. You know, I mean, the thing that's true is the data aspect at the edge. I mean, everything's got a database data warehouse and data lakes are involved in everything. And then, and some sort of BI or tools to get the data and work with the data or the data analyst, data feeds, machine learning, critical piece to all this, Dave, I mean, this is like databases used to be boring, like boring field. Like, you know, if you were a database, I have a degree in a database design, one of my degrees who do science degrees back then no one really cared. If you were a database person. Now it's like, man data, everything. This is a whole new field. This is an opportunity. But also, I mean, are there enough people out there to do all this? >>Well, it's a great point. And I think this is why Amazon is trying to extract some of the abstract. Some of the complexity I sat in on a private session around databases today and listened to a number of customers. And I will say this, you know, some of it I think was NDA. So I can't, I can't say too much, but I will say this Amazon's philosophy of the database. And you address this in your conversation with Andy Jassy across its entire portfolio is to have really, really fine grain access to the deep level API APIs across all their services. And he said, he said this to you. We don't necessarily want to be the abstraction layer per se, because when the market changes, that's harder for us to change. We want to have that fine-grained access. And so you're seeing that with database, whether it's, you know, no sequel, sequel, you know, the, the Aurora the different flavors of Aurora dynamo, DV, uh, red shift, uh, you know, already S on and on and on. There's just a number of data stores. And you're seeing, for instance, Oracle take a completely different approach. Yes, they have my SQL cause they know got that with the sun acquisition. But, but this is they're really about put, is putting as much capability into a single database as possible. Oh, you only need one database only different philosophy. >>Yeah. And then obviously a health Lake. And then that was pretty much the end of the, the announcements big impact to health care. Again, the theme of horizontal data, vertical specialization with data science and software playing out in real time. >>Yeah. Well, so I have asked this question many times in the cube, when is it that machines will be able to make better diagnoses than doctors and you know, that day is coming. If it's not here, uh, you know, I think helped like is really interesting. I've got an interview later on with one of the practitioners in that space. And so, you know, healthcare is something that is an industry that's ripe for disruption. It really hasn't been disruption disrupted. It's a very high, high risk obviously industry. Uh, but look at healthcare as we all know, it's too expensive. It's too slow. It's too cumbersome. It's too long sometimes to get to a diagnosis or be seen, Amazon's trying to attack with its partners, all of those problems. >>Well, Dave, let's, let's summarize our take on Amazon keynote with machine learning, I'll say pretty historic in the sense that there was so much content in first keynote last year with Andy Jassy, he spent like 75 minutes. He told me on machine learning, they had to kind of create their own category Swami, who we interviewed many times on the cube was awesome. But a lot of still a lot more stuff, more, 215 announcements this year, machine learning more capabilities than ever before. Um, moving faster, solving real problems, targeting the builders, um, fraud platform set of things is the Amazon cadence. What's your analysis of the keynote? >>Well, so I think a couple of things, one is, you know, we've said for a while now that the new innovation cocktail is cloud plus data, plus AI, it's really data machine intelligence or AI applied to that data. And the scale at cloud Amazon Naylor obviously has nailed the cloud infrastructure. It's got the data. That's why database is so important and it's gotta be a leader in machine intelligence. And you're seeing this in the, in the spending data, you know, with our partner ETR, you see that, uh, that AI and ML in terms of spending momentum is, is at the highest or, or at the highest, along with automation, uh, and containers. And so in. Why is that? It's because everybody is trying to infuse AI into their application portfolios. They're trying to automate as much as possible. They're trying to get insights that, that the systems can take action on. >>And, and, and actually it's really augmented intelligence in a big way, but, but really driving insights, speeding that time to insight and Amazon, they have to be a leader there that it's Amazon it's, it's, it's Google, it's the Facebook's, it's obviously Microsoft, you know, IBM's Tron trying to get in there. They were kind of first with, with Watson, but with they're far behind, I think, uh, the, the hyper hyper scale guys. Uh, but, but I guess like the key point is you're going to be buying this. Most companies are going to be buying this, not building it. And that's good news for organizations. >>Yeah. I mean, you get 80% there with the product. Why not go that way? The alternative is try to find some machine learning people to build it. They're hard to find. Um, so the seeing the scale of kind of replicating machine learning expertise with SageMaker, then ultimately into databases and tools, and then ultimately built into applications. I think, you know, this is the thing that I think they, my opinion is that Amazon continues to move up the stack, uh, with their capabilities. And I think machine learning is interesting because it's a whole new set of it's kind of its own little monster building block. That's just not one thing it's going to be super important. I think it's going to have an impact on the startup scene and innovation is going, gonna have an impact on incumbent companies that are currently leaders that are under threat from new entrance entering the business. >>So I think it's going to be a very entrepreneurial opportunity. And I think it's going to be interesting to see is how machine learning plays that role. Is it a defining feature that's core to the intellectual property, or is it enabling new intellectual property? So to me, I just don't see how that's going to fall yet. I would bet that today intellectual property will be built on top of Amazon's machine learning, where the new algorithms and the new things will be built separately. If you compete head to head with that scale, you could be on the wrong side of history. Again, this is a bet that the startups and the venture capitals will have to make is who's going to end up being on the right wave here. Because if you make the wrong design choice, you can have a very complex environment with IOT or whatever your app serving. If you can narrow it down and get a wedge in the marketplace, if you're a company, um, I think that's going to be an advantage. This could be great just to see how the impact of the ecosystem this will be. >>Well, I think something you said just now it gives a clue. You talked about, you know, the, the difficulty of finding the skills. And I think that's a big part of what Amazon and others who were innovating in machine learning are trying to do is the gap between those that are qualified to actually do this stuff. The data scientists, the quality engineers, the data engineers, et cetera. And so companies, you know, the last 10 years went out and tried to hire these people. They couldn't find them, they tried to train them. So it's taking too long. And now that I think they're looking toward machine intelligence to really solve that problem, because that scales, as we, as we know, outsourcing to services companies and just, you know, hardcore heavy lifting, does it doesn't scale that well, >>Well, you know what, give me some machine learning, give it to me faster. I want to take the 80% there and allow us to build certainly on the media cloud and the cube virtual that we're doing. Again, every vertical is going to impact a Dave. Great to see you, uh, great stuff. So far week two. So, you know, we're cube live, we're live covering the keynotes tomorrow. We'll be covering the keynotes for the public sector day. That should be chock-full action. That environment is going to impact the most by COVID a lot of innovation, a lot of coverage. I'm John Ferrari. And with Dave Alante, thanks for watching.

>> Narrator: From around the globe, it's theCUBE, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi, and welcome back to theCUBE's coverage of HPE Discover 2020 the virtual experience. I'm your host Stu Miniman. I'm really happy to be joined on the program two of our CUBE alumni, we have the Daves from Hewlett Packard labs. Sitting in the screen next to me is Dave Husak he is a fellow and general manager for the Cloudless Initiative. And on the other side of the screen, we have Dave Larson, vice president and CTO of the Cloudless Initiative. Dave and Dave, thank you so much for joining us again. >> Delighted to be here. >> All right, so specifically we're going to be talking a bit about security, obviously, you know, very important in the cloud era. And as we build our native architect, you know, Dave Husak, I guess, why don't you set the stage for us a little bit, of you know, where security fits into, you know, HPE overall and, you know, the mission that you know, last year a lot of buzz and discussion and interest around Cloudless. So just put that as a start and then we'll, get into a lot of discussion about security. >> Right yeah, last year we did, you know, launch the initiative and, you know, we framed it as, it composed of three components, one of which in fact, the most important aspect of which it was the trust fabric Cloudless Trust Fabric, which was you know, built on the idea of intrinsic security for all workload end points, right. And this is a theme that you see playing out, you know, a year later playing out, I think across the industry. You hear that language and that, you know, that kind of idea of being promoted in the context of zero trust, you know, new capabilities being launched by VMware and other kinds of runtime environments, right. And you know, the way I like to say it is that we have entered an era of security first in IT infrastructure. It's no longer going to be practical to build IT infrastructure and then, you know, have products that secure it, right. You know, build perimeters, do micro-segment or anything like that. Workload end points need to be intrinsically secure. And you know, the upshot of that really at this point is that all IT infrastructure companies are security companies now. The you know it, acknowledge it, like it or not, we're all security companies now. And so, you know, a lot of the principles applying in the Cloudless Trust Fabric are those zero trust principles are based on cryptographic, workload, identity, leverage unique aspects of HPs products and infrastructure that we've already been delivering with hardware and Silicon root of trust built into our reliance servers and other capabilities like that. And you know, our mission, my mission is to propel that forward and ensure that HP is, you know, at the forefront of securing everything. >> Yeah, excellent definitely, you know love the security first discussion. Every company we've talked to absolutely security is not only a sea level, but you know, typically board level discussion, I guess my initial feedback, as you would say, if every company today is a security company, many of them might not be living up to the expectation just yet So Dave Larson, let's say, you know, applications are, you know, at the core of what we've look at it in cloud native. It's new architectures, new design principles. So give us some, what is HPE thoughts and stuff, how security fits into that, and what's different from how we might've thought about security in the past the applications? Well, I think Dave touched on it, right? From a trust fabric perspective, we have to think of moving to something where the end points themselves, whether their workloads or services are actually intrinsically secure and that we can instantiate some kind of a zero trust framework that really benefits the applications. It really isn't sufficient to do intermediate inspection. In fact, the real, the primary reason why that's no longer possible is that the world is moving too encryption everywhere. And as soon as all packets are encrypted in flight, not withstanding claims to the contrary, it's virtually impossible to do any kind of inference on the flows to apply any meaningful security. But the way we see it is that the transition is moving to a modality where all services, all workloads, all endpoints can be mutually attested, cryptographically identified in a way that allows a zero trust model to emerge so that all end points can know what they are speaking to on the remote end and by authorization principals determine whether or not they're allowed to speak to those. So from a HPE perspective, the area where we build is from the bottom up, we have a Silicon root of trust in our server platform. It's part of our ILO five Integrated lights out baseboard management controller. We can actually deliver a discreet and measurable identity for the hardware and projected up into the workload, into the software realm. >> Excellent, Ty I heard you mentioned identity makes me think of the Cytel acquisition that the HPE made early this year, people in the cloud native community into CubeCon you know, SPIFFE of course, is a project that had gotten quite a bit of attention. Can give us a little bit as to how that acquisition fits into this overall discussion we were just having? >> Oh yeah, so we acquired Cytel into the initiative, beginning of this year. As you, understand Stu, right. Cryptographic identity is fundamental to zero trust security because we're no longer, like Dave pointed out we're no longer relying, on intermediary devices, firewalls, or other kinds of functions to manage, you know, authorize those communications. So the idea of building cryptographic identity into all workload endpoints, devices and data is sort of a cornerstone of any zero trust security strategy. We were delighted to bring the team on board. Not only from the standpoint that they are the world's experts, original contributors, and moderators and committers in the stewardship of SPIFFE and SPIRE the two projects in the CNCF. But you know, the impact they're going to have on the HPs product development, hardware and software is going to be outsized. And it also, you know, as a, I'll have to point this out as well, you know, It is the, this is the most prominent open source project that HP is now stewarding, right. In terms of its acceptance, of SPIFFE and SPIRE, or both poised to be I have an announcement here shortly, probably. But we expect they're going to be promoted to the incubating phase of CNCF maturity from the Sandbox is actually one of the first Sandbox projects in the CNCF. And so it's going to join that Pantheon of know, you know, top few dozen out of I think 1,390 projects in the CNCF. So like you pointed out Stu you know, SPIFFE and SPIRE are right now, you know, the world's leading candidate as, you know, sort of the certificate standard for cryptographic workload endpoint identity. And we're looking at that as a very fundamental enabling technology for this transformation, that the industry is going to go through. >> Yeah, it's really interesting if we pull on that open source thread a little bit more, you know, I think back to earlier in my career, you know, 15, 20 years ago, and if you talk to a CIO, you know, security might be important to them, but they keep what they're building and how their IT infrastructure, is something that they keep very understood. And if you were a vendor supplying to them, you had to be under NDA to understand, because that was a differentiation. Now we're talking about lifting cloud, we're talking about open source, you know, even when I talked to the financial institutions, they're all talking amongst themselves the how do we share best practices because it's not, am I secure? It's we all need to be secure. I wonder if you can comment a little bit on that trend, you know, how the role of open source. Yeah, this is an extension of Kerckhoffs's principle, right? The idea that a security system has to be secure, even if you know the system, right. That's it's only the contents of the ease in the communication letter, that are important. And that is playing out, at the highest level in our industry now, right. So it is, like I said, cryptographic identity and identity based encryption are the cornerstones of building a zero trust fabric. You know, one of the other things is, cause you mentioned that, we also observed is that the CNCF, the Apache foundation. The other thing that's, I think a contrast to 15 years ago, right back 15, 20 years ago, open source was a software development phenomenon, right. Where, you know, the usual idea, you know, there's repositories of code, you pull them down, you modify them for your own particular purposes and you upstream this, the changes and such, right. It's less about that now. It is much more a model for open source operations than it is a model for open source development. Most of the people that are pulling down those repositories unless they are using them, they're not modifying them, right. And as you also, I think understand, right. The framework of the CNCF landscape comprehensive, right? You can build an entire IT infrastructure operations environment by you know, taking storage technologies, security technologies, monitoring management, you know, it's complete, right. And it is, you know, becoming really, you know, a major operational discipline out there in the world to harness all of that development harness, the open source communities. Not only in the software, not only in the security space, but I think you know comprehensively and that engine of growth and development is I think probably the largest, you know manpower and brainpower, and you know, operational kind of active daily users model out there now, right. And, it's going to be critical. I think for the decade, this decade that's coming. That the successful IT infrastructure companies have to be very tightly engaged with those communities in that process, because open source operations is the new thing. It's like, you know DevOps became OpsDev or something like that is the trend. >> Yeah, and I'm glad you brought that up you know I think about the DevOps movement, really fused security, it can't be a bolt on it can't be an afterthought. The mantra I've heard over the last few years, is security is everyone's responsibility. Dave Larson, you know, the question I have for you is, how do we make sure, you know, policy is enforced you know, even I think about an organization everyone's responsible for it, you know, who's actually making sure that things happen because, you know, if everybody's looking after it, it should be okay. But, you know, bring us down a little bit from the application standpoint. >> Well, I would say, you know, first of all, you have to narrow the problem down, right? The more we try to centralize security with discreet appliances, that's some kind of a choke point, the explosion, the common editorial explosion of policy declaratives that are necessary in order to achieve that problem to achieve the solution becomes untenable, right? There is no way to achieve the right kind of policy enforcement unless we get as close to the actual workloads themselves, unless we implement a zero trust model where only known and authorized end points are allowed to communicate with each other, you know. We've lived with a really unfortunate situation in the internet at large, for the last couple of decades where an IP address is both a location and an identifier. This is problem because that can be abused. it's something that can be changed. It's something that is easily spoofed, and frankly the nature of that element of the way we connect applications together is the way that almost virtually all exploits, get into the environment and cause problems. If we move to a zero trust model where the individual end points will only speak with only respond to something that is authorized and only things that are authorized and they trust nothing else, we eliminate 95 to 99% of them problem. And we are in an automated stance that will allow us to have much better assurance of the security of the connections between the various endpoints and services. >> Excellent, so, you know, one of the questions that always comes up, some of the pieces we're talking about here are open source. You talk about security and trust across multiple environments. How does HPE differentiate from, you know, everything else out there and, you know, how are you taking the leadership position? I'd love to hear both of your commentary on that. >> Yeah, well, like I said, initially, the real differentiation for us is that HPE was the market leader for industry standard servers, from a security perspective. Three years ago in our ProLiant gen 10 servers, when we announced them, they had the Silicon root of trust and we've shipped more than a million and a half servers into the market with this capability that is unique in the market. And we've been actively extending that capability so that we can project the identity, not just to the actual hardware itself, but that we can bind it in a multi-factor sense, the individual software components that are hosted on that server, whether it's the operating system, a hypervisor, a VM, a container framework, or an actual container, or a piece of it code from a serverless perspective. All of those things need to be able to be identified and we can bring a multi-factor identity capability to individual workloads that can be the underpinning for this zero across connection capability. >> Great and David, anything you'd like to add there? >> No, like what he said I think HP is uniquely positioned you know, the depth and the breadth of our installed base of platforms that are already zero trust ready, if you will, right. Coupled with the identity technology that we're developing in the context of the Cytel acquisition and David, my work in a building, the cloudless trust fabric, you know, are the, like I said, the cornerstones of these architectures, right? And HP has a couple of unfair advantages here you know, okay breadth and depth of our, the customer base and the installed base of the system is already put out there. While the world is transitioning, you know, inevitably to these, you know, these kinds of security architectures, these kinds of IT infrastructure architectures, HP has a, you know, a leadership team position by default here that we can take advantage of. And our customers can reap the benefits of without, well, you know, without you know, rebuilding forklift upgrading, or otherwise, you know, it is, yeah as Dave talked about, you know, a lot will change, right. There's more to do, right? As we move from, you know, IP addresses and port numbers, as identities for security, because we know that perimeter security, network security like that is busted, right. It is, you know, every headline making, you know, kind of advanced persistent threat kind of vulnerabilities it's all at the root of all those problems, right. There are technologies like OPA, right you know, policy has to be reframed in the context of workload identity, not in network identity know. Like call this legal sort of the microsegmentation fallacy, right. You know that, you know, perimeters are broken, not a valid security strategy anymore. So the answer can't be, let's just draw smaller perimeters, especially since we're now filling them up with evermore, you know, dynamic evanescent kind of workload endpoints, you know, containers coming and going at a certain pace. And serverless instances, right. All of those things springing up and, and being torn down, you know, on, you know, very short life cycle that's right. It is inconceivable that traditional, you know perimeter based micro-segmentation based security frameworks can keep up with the competent tutorial explosion and the pace with which we are going to be where, you know, orchestration frameworks are going to be deploying these end points. There are, you know, there's a lot more to do, you know, but this is, the transformation story. This is of the 2020s, you know, infrastructure, IT infrastructure school is very different in two, five, 10 years from now than it does today. And you know that's you know we believe HP has, like I said, a few unfair advantages to lead the world in terms of those transformations. >> Excellent, well, appreciate the look towards the future as well as where we are today. Dave and Dave, thanks so much for joining. Thank you, Stu. >> Thanks, dude, pleasure. >> All right, we'll be back with lots more coverage. HPE Discover 2020 the Virtual Experience. I'm Stu Miniman and thank you for watching theCUBE. (upbeat music)

>> Narrator: Live, from San Francisco, celebrating 10 years of high-tech coverage, It's theCUBE! Covering VMworld 2019. Brought to you by VMware, and its ecosystem partners. >> And, welcome back here on theCUBE, we're at the Moscone Center here at downtown San Francisco. Gorgeous day outside, by the way. Picture perfect day. Chamber of Commerce weather, but a lot of big news happening inside here for VMworld 2019, along with John Troyer. I'm John Walls, we're joined by Pierluca Chiodelli, who's the Vice President of Product Management at Dell EMC. And, Pierluca, good to see you, Sir. >> Thank you, it's awesome to be here. >> Great, thanks for being here. And Muneyb Minhazuddin, whose the VP of solutions product marketing at VMware. And Muneyb, I know you're right just hot off the presentation stage. >> Yes I am. >> Catch your breath, it's all going to be fine. How was your audience? I'm sure standing remotely. >> Yeah, it was thirteen hundred plus >> Excellent, yeah. Been a big week, already. >> Of course it has, yeah. >> For you and your team. So, first off, let me just, let's step back, talk about the vibe of the show, the theme of the show we saw Pat on the stage. >> Muneyb: Perfect. >> About an hour and a half this morning, just your thoughts about day one and the big announcements that VMware's been making. >> It's been a great week, and it's actually been a great approaching week. As you know, on Thursday we announced intent and acquire both Pivotal and Carbon Black for close to about $5,000,000,000. So, that's, kind of a big announcement by itself, and then how do you kind of bring in and keep day one where you're not too focused on those two, but get the narrative of VMworld across. And really, you know, where we have, you know, CUBE has been with us on this journey for a long time. >> Right. >> We've seen that data center shift into kind of two tangents. One is, you know, workloads into data center break out into public clouds. Second, rerouting into cloud native applications. And, if you've seen our strategy wall when that was kind of the key messages. Hey, we're embracing both the modern app development, the focus on Kubernetes and Tanzoo announcement, was all about to say, "VMware platforms ready "for the breakout of both tangents." First, Cloud Native, we've got Kubernetes, we're bringing it right into vSphere, so that everybody in the audience can support it. Second, the breadth of our cloud everywhere, right, so, we've gone from Amazon to IBM to Google to Ajour. So, it'll give you the infrastructure for your workloads to be your choice. Modernize or migrate. (chuckles) That was a key message for us to kind of land today. For a lot of our audience who are kind of stuck in that same piece of, "What am I doing with my workloads? "What is that platform I got to build on?" And, you know, the key foundational platform being VMware Cloud Foundation. Right, that was our strategy, and I think last year we called out VMware Cloud Foundation in Pat's keynote, because I wrote it 44 times. (laughs) (group laughter) We didn't do it that many times, this time. We only said that's the platform that lands in Amazon, GCP, Ajour, IBM, and 4,200, you know, cloud provider partners. That gives you really that public cloud extension. The second part being modern apps, Kubernetes is a new, kind of, modern app development platform, vSphere is embedded into that project pacific and the whole Tanzoo announcement, right? So, really, a powerful message, what do you think? Was that successfully landed? >> I think so. John, do you feel good about what you heard today? >> Yeah, absolutely, I think VCF is super interesting. I'm also kind of, so there was an announcement today also about the Dell Technologies Cloud Validated Designs for using VCF. So, VCF the layer, which is kind of the VMware stack with some extra magic in it, that can be in, can make a private hybrid cloud, you know, everywhere. So, talk to us a little bit about Dell Technologies Cloud. As I call it, "DTC." The, it's a lot, there's a lot of stuff in that as well, so, but we have two very complicated solutions stacks that are, we're talking about now, so. >> Yeah, absolutely. >> Can you talk a little bit about the validated design and what came out of that? >> Absolutely, so before we go into the validated design, I think it's very important as Muneyb said. When we think about the Dell Technology Cloud, really, it's a component of the best (murmurs) technology from our storage, networking, and also compute, but we did the VMware VCS on top. So, we work very closely with VMware, and today we are announcing today the Cloud Validated Design. As we announce at the Dell Technology World in May, we said Dell Technology Cloud is this, now we want to tell to the people, how you can easily deploy this. What is make this tangible? So, what we are doing today is rapid time to value. We did design and pretested configuration, that we put in Dell Technologies Cloud Validated Design, as we said. The other important things as Muneyb said, right? It's... And, I heard this also from theCUBE. There was a debate with Stu and other people about, what is the Cloud? How I deploy the Cloud? When we think about Dell Technologies we speak with different peoples, and two set of peoples. One is the app, right? The Cloud app, all the app people that, they want to build have all the automation, DevOps operation and all these things. But, behind those people, there's still an infrastructure. So, we are speaking on both things. So, it's very important this paradigm is there, where you can have people that they can consume the technology, and understand how to build the infrastructure to be automated, and build that automation for the Cloud. So, that's what is the Dell Technologies Font Validation Design. Right. So, one of the biggest things here that we announced, is not only the Cloud Validation Design. It's the first one but also the ability to have compute, storage and network together, and also use it primary storage as a primary citizen of the VCF. So, we should talk about that later but that's-- >> Absolutely, and I think to catch onto that, you know, talking about the applications et cetera, you know, again, in the evolution of Cloud, and we've been on the journey for 10 years is, we've had, the first few years of the Cloud journey was, felt a little like a one way street, which was, kind of meant where people were shutting down data centers and going to all these public cloud providers, was always a one-way street. Now, VMware, and if you followed us closely, we had a service call VMware, you know VCHS, which is VMware Hybrid Cloud Service before the vCloud Air and then we came out with this solution, right? The idea was, we thought there's going to be movement back-and-forth but it wasn't the case. People were seriously shutting down and going one way. As we made all these partnerships of you know, Amazon, IBM, we started seeing, and you heard stories of IHS, Freddie Mac on stage where they take six weeks to move 100 applications one way into the Cloud, customers started asking us some questions, say, 'If it's so easy to go that way, is it also that easy to bring it back?' >> Come back! >> Right? And, that kind of lead to the whole kind of Dell partnership, Dell announcement within the Dell Cloud Foundation, you know, VMware Cloud Foundation, Dell Technologies Cloud Platform to say that, "Hey, it's actually..." There's a notion of not going from hardware-specific, you know, just high-tuned for workloads to commodity hardware in the Public Cloud. There's now a need for having common hardware platform on both on-PRAM, off-PRAM because there is a need for customers to take EC2 workloads or, you know, Ajour workloads and bring it on PRAM again. That was just a notion of how fast it is. I add that point because it is so critical to know that your hardware is performing in tuned, to perform for a high business critical applications. People forgot about them the first few phases of going to the Cloud, and now as they think about a hybrid, true hybrid Cloud nature, they want optimal performance in the software layer, in the hardware layer. You know, hence our announcement of Dell Technologies Cloud, Cloud Foundation, Validated Design. It's really supporting that customer notion. >> So, it's like this optimal, or maximized flexibility is what you're trying to give people. I mean, is that-- >> Pierluca: With the Cloud simplicity, that's really the key. >> But what drives that? I know that you have, you've, you know, whether you're on-PRAM or you're off-PRAM, you're going to decide what workload's going to go on what space on, so forth, but is some of that kind of hedging bets for future workloads because you can't predict where they're going to be done or where you want them done? Or is it just providing flexibility today, and let's not worry about tomorrow? You know, it just seems like there's a lot of runway here, if you will. >> Yeah, and I think there's no right or wrong answer. One of the big workshops I do with our customers is really kind of say have you figured out what's your three to five-year application strategy? Because again, in that first phase of that fast migration to the Public Cloud, people were just like CIOs I know, it's like, I have a cloud for strategy, what does that mean? I'm shutting down all data centers, I'm going to the Cloud. Right or wrong, and that's my Cloud First strategy. Now, what they've come to realize is not all workloads work effectively in the Cloud, right? So, they kind of like, hey, put an application strategy to say what are the most optimal applications that will get the benefit of Cloud? These are like, e-commerce retail. They have to have, you know, Black Friday, expanding elasticity. If you got no slow, mundane, you know backend processes doing batch processes of massive storage of in a bank ledger in the back end, they're not going to get that elasticity. I know what it is, I know how many, you know, batch processes I got to run. So, people are getting smarter about which ones get the benefit of, you know, modern app development, or Cloud elasticity, which ones don't really need to have that. So, we've seen best practice customers actually have a very good app strategy, three to five years, and then decide how much of my app strategy is gone to the right, you know, or gone to the left, right? It's pretty much to say, "I don't have to change." 60, 70% of my Eastern European customers, their banking ledgers are still on mainframes. They're not in a hurry to go to the Cloud, whereas, you know Fintech on the East Coast is going, "I'm going to the, I'm going to the Cloud", right? So, it's really that strategy that's, they should take the app strategy and decide what the infrastructure strategy is on the top shelf. >> I think from the storage business, we see that really clear, right? The app is definitely what is moving the things, right? It's not, people they're not thinking anymore because the transformation is in the way that you consume the infrastructure. They not thinking anymore about what I put there, but is about what app I need to run, how I build my app. So, it's the environment. And, I don't think personally I meet a lot of customer. There is not one right way or wrong way, it's an end, right? As you can see also in VCF we have Vsend, VxRail and primary storage. If you look at two years ago, we will be sitting here and say, you know, "It's only this, not the other things." When we, I been in governor conference, three years ago was like, it's all Cloud. It's reality is the world, the information technology world is always the same, where is a natural genius things. Because people, they need to have the trust, right? You cannot run your entire things on something that you don't know or you didn't prove. So, what we give here today with our technology is the flexibility. You can have a Cloud approach, but use the trusted PowerMax, for example, in conjunction with Vsend, in conjunction with the Unity. So, not all these is the proof that you can preserve your investment. But, is the proof that you can start to build those up. And, if you've seen what paths say today, then those app can live everywhere. So, you can go, you can move, it's much easier to move, and you can just trust what you're doing. >> And, you hit an important point on the move part, right? And, people are so easy, like, "Hey I moved a thousand applications in six weeks "to VMC and AWS." The fundamental notion where that was not possible before, was compute, network, storage. Like, we've been doing vSphere for a long time, you know that. And, it wasn't that easy because what used to happen is people thought, "Hey, a virtualized computer, I can move it." But, what did not happen as you moved that, was your databases, you know, your storage, rules didn't follow you into the Cloud. Your networking QOS and, you know, policies, and you know, priorities didn't follow you into the Cloud. So, that was kind of like, you know, you know, I'm an Australian, so it was a half-assed solution, right? (group laughing) So bear with my language, right. It was a half-assed solution, but really what needs to happen is your compute, your network, your storage has to all work together. And, that's where Cloud Foundation was powerful. And, what we're lighting with this Validated Designs is also that capability that your computer, or storage is one unit from a app. Once you package it and make it available in all the platforms, then that migration becomes six weeks, two weeks to move that. Because once you break it apart, it's a nightmare. There's not a lot of folks who have survived database migrations. (laughs) >> I mean maybe Pierluca, you can kind of sum us up here. This conversation's been a lot around evolution, right? And, there's also been an evolution of data center design and what to expect with that, you know, just buying things off the shelf and getting a Var and, you know, the VMAX, and we've been through this whole, and now, we've talked about VxRail, which can be part of this solution. But, can you talk, just, maybe, take us in, take us out with the, or into the future with the Dell Technologies Cloud as the idea of the Validated Design, the idea of this stack from Dell Technologies in storage et cetera, what can we expect in the near future? And, how much guidance will folks get? >> Yeah, absolutely. So, without breaking any NDA things, but this is only the first step. So, the Cloud Validated Design is just the first step where we said, 'Okay, we are tasked in this, "we putting this together." We are working very closely to also solve the entire things that VCF allow you to do first day deployment, allow you to expand the infrastructure, and allow you also to do life cycle management. For example, with the VxRail we already have the life cycle management part. We are working in way to do that also for our storage and other things. So, if you think about that then it becomes as you said, all the policy we put, like with Vworld, will be strategically in that sense, the policies can be carried over. So, then you can go to VMC, you can go to another place where the software and infrastructure can move back. So, because people can do this on PRAM, a replicate exactly but not only replicate the application, but replicate the (murmurs). What do you do on the QOS, all these key things that makes people running enterprise application, right? So that's, I think, it's very exciting moment. I think it's just the starting of this dream. >> Absolutely. >> Gentlemen, thanks for the time. >> Thank you. >> And you're all, you paint a pretty exciting future, don't ya? >> I hope so. >> So, I can't wait to look forward to even VMworld 2020? >> Wait 'til Barcelona, come on? (laughs) >> All right, well I'm not making that road trip, so unfortunately-- >> We going to more out there. >> But, Barcelona's going to be good. >> Yes, thank you for having us. >> No, I'm not the best guy, so, all right good. Hey, gentlemen, thank you for the time. >> Thank you >> Thank you. >> I appreciate it very much, great discussion. >> Thank you very much. >> Thanks for having us. >> Back with more from San Francisco right after this. (techno music)

>> Live, from Las Vegas, it's theCube! Covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, And their ecosystem partners. >> Hey, welcome back everyone, live here, in Las Vegas, Amazon Web Services AWS re:Invent 2018. 52,000 people here. Two days. Second day of three days of wall to wall coverage here at theCUBE. I'm John, with Dave Vellante. Dave, six years, we've been doing theCUBE. We've been to all re:Invents except for the first year. We've been a customer, we've been following these guys. >> Plus the summits! >> Plus the summits. Great ecosystem. And VMware and VMworld, similar dynamic. I want to talk about that now, obviously the new announcement, on-premise, is huge. Want to dig in to it with our guest, Sanjay Poonen, who's the Chief Operating Officer of VMware. Sanjay, great to see you. Cube alumni, many times, thanks for coming back again. >> John and Dave, pleasure to be on your show. >> Thanks for coming on, great to see you. >> Congratulations on all this success, you've got a wonderful booth and presence here, and I think this is becoming like the Mecca of all IT events. >> You know, we have our new video cloud service on AWS, we're ingesting over 110 videos, we'll have 500 short video clips behind it. Tons of blog posts, tons of coverage. There's an insatiable appetite for Amazon Web Services content as Andy pointed out in my interview with him. And it's just the beginning. You guys at VMware really, I mean, talk about a seminal moment in the history of the computer industry, and VMware was, when you guys recognized the sea change of operators on IT and cloud developers coming together, you guys were very proactive two years ago. Raghu, yourself, and the team, Pat. We're going to, hey you know what? Let's just align. Culture's a fit with Amazon. Let's co-develop. Let's ride the wave together, and let's see where the chips fall. Which is basically, I'm oversimplifying, but that's kind of what's happened. So much has happened. I saw Raghu last night at the Greylock partner event. This is a historic moment. Good outcome so far, deep partnership, meaningful partnership. A lot of resonance in the marketplace, you guys are iterating and raising the bar. That's Amazon talk for success. How do you feel? >> Yeah, no, I think it's, absolutely, John. We, if you think about how this has evolved, you know five years ago when I joined VMware, I felt like cloud and containers, the two C's, were our big headwinds. We've turned those headwinds now into tailwinds, but it took some catharsis from us. We had vCloud Air, our own public cloud. We had to divest that. And I think the Amazon VMware coming together, when we announced it two and a half years ago, was like a Berlin Wall moment, where you had the US and the Soviet Union getting together. That was good for world peace. People were surprised, because these are two purported enemies now, and it really built trust. And step by step, launching VMware on AWS, announcing RDS on VMware, the beginning of on-premise, and then today, announcing Outposts, it's just an example of not just the validity of VMware as a hybrid cloud leader, but the strength of this partnership. We have a very special relationship with Andy, Pat, myself, Raghu, spent a lot of time together. Often, you can't tell, when our engineering teams meet, when an Amazon engineer and a VMware apart from each other. They're like finishing each other's sentences. That, we don't do, like, Mickey Mouse, Barney, you know press releases. It's real stuff. >> And the culture of, the engineering culture of VMware, which has been a core, cultural thing, the DNA of VMware is technical. Very community oriented. Amazon, technical, very operationally efficient, good community. This is good fit there. I got to get your perspective, though, on how that is going to evolve, specifically around on-premise. Because certainly Andy Jassy validates on-premises with the announcement that VMworld, which you guys covered, Pat Gelsinger uses words like dial tone, Kubernetes, you mentioned containers. Andy, when I asked him, "Andy, you know you told me "in theCUBE, five years ago, "that everything's going to the public cloud. "Change of tune? "You mind if I pin you down?" "No, John, you can pin me down all you want." He says good leaders are self-aware. He said "Our customers wanted this." And he's cool to it. And the partnership with VMware highlights that this is not going to happen overnight, he recognizes the duration, the role of on-premise. And then he also says that the data center's like a big Edge. So, if everything's cloud, what you guys basically announced with Outpost is, cloud, public cloud everywhere. So, just, there's no public, private, it's just cloud. This is a game changer, because-- >> Absolutely. >> Just, why wouldn't I want to buy this product? >> I mean, first off, congratulations on scoring that interview. Not many people have access to Andy that way, and you guys have built a very good relationship. I thought that interview you did with him was phenomenal. There was a special point in that, John, where you tried to get him to talk about Outposts, this was before he announced it, which is will Amazon go on-premise. So a couple of months ago, when Andy called us, and Matt Garman, to talk about this project under NDA, it was a continuation of those RDS type discussions where we basically said, if you want to do anything on-premise, you should do it with VMware, because you're going to have to go through this door called VMware. We are the de facto king of the on-premise private cloud world. Many of these customers are used to our tooling, vSphere, vMotion. They want anything to run on VMware. So from that became a sequence of discussions that really really evolved very quickly, and well, so we can announce this together. I mean, you know, Andy had three guests on stage, and only one partner, and that was VMware. And that's an indication of the strength of this partnership. Vice versa, of the 50,000 people here, probably all of them have VMware on-premise. So if Amazon's going to do more on premise, why not do it with the leader in that area, VMware. And we want to be in the software industry. The de facto standard for software-defined infrastructure. Right? And that's a special space that we can fill. >> Well, the amazing thing to me, is, here's VMware, no public cloud, Amazon wouldn't even say the word hybrid, or private cloud, doesn't use private cloud, but it wouldn't say hybrid before. You've now emerged as the tandem, de facto leader in hybrid cloud. Overnight. With an ecosystem that all wants to connect and partner with VMware and all wants to partner with AWS. Overnight. I mean, it feels that way anyway, 24 months. >> I think that's absolutely right. I mean, we were the first to start using the term hybrid, three or four years ago. As we did, then it took a while, because I think a lot of customers, and some of the public cloud vendors, felt it was going to be binary, all public cloud and no private cloud, but they began to realize you need both. But your point on the ecosystem, also surrounding, I just came back from meeting one of the top SIs in the world. They're betting big with us because they see this as the place for both of them, and they're also betting big with AWS. The System Integrators are all over this. The security vendors, all over this. Palo Alto Networks, Splunk, want to see. Often, many of these companies come to us and say, "You have cracked something special "in your relationship with Amazon. "How did you do that and how can we follow that model?" We're happy to share our playbook of how we think about ecosystems. So, we want to create a platform, just like Amazon's a platform, where everybody, SIs, tech vendors, software vendors, can all plug in to. >> And the other observation I make is, you know, previously the distance between infrastructure players and the guys who really are driving application value, the application developers, was quite a distance. And now it's closing, with infrastructure as code. And it's just so transformative for organizations. >> I think, and one of the things that's making that is microservices and containers. And as you know, since we last talked, we acquired Heptio. If you think about Heptio, they are the founders of Kubernetes, okay? They left Google, started their own company, Craig and Joe, and we're excited about that. That platform will augment PKS, which was our big bet in containers, and become something that could run on-premise, or in a public cloud environment like this. We acquired CloudHealth. CloudHealth is a multi-cloud management tool for costing resource management. That becomes something that could send, a lot of Amazon reps actually refer CloudHealth as the preferred way to get your insights. So we're beginning to see this now a lot more clearly than we did two years ago, thanks to this partnership. >> So, Sanjay, I know that Outposts, super exciting, it's been covered on Silicon Angle, there's a zillion stories on our site on this whole event. But, it's not going to be shipping for about a year. But you guys already have some working products now. What's the current track to that shipping because when that comes out, that'll be a game changer. Why would anyone want to buy hardware again? Michael Dell wins either way because he's got VMware. But others who sell hardware, this is a real, it could be a killer blow. But, I don't want to (laughs), you can comment on that if you want, but what's in-between that one year, you've got a product now, how do customers move along? >> Yeah, I think there's some very tangible things that, first off, VMware Cloud on AWS is, as you've described Dave, the best hybrid cloud option. You get the best of the on-premise world and the public cloud. You know, we announced hundreds of customers, we have a goal to get to thousands of customers, and then tens of thousands of customers. We're going to continue down that march. I want to have a significant number, over 500,000 customers. If Amazon has 40, 50 percent market share, based on some of the numbers that Andy shared today, a significant number of our customers have Amazon, we should get them onto VMC. VMware Cloud and AWS. Secondly, we do have, we announced Project Dimension, some Edge computing capabilities running on existing hardware players, so we are beginning this journey ourselves, in terms of cloud managed on-premise environment. Right? Project Dimension was announced before this, and that will run on Dell and Lenovo hardware, and that's well and good to go. They will have Edge IOT use cases. And then when Amazon comes and gets us ready, we would have learned a lot about this market. Which is really kind of this Edge computing market, cloud-managed. So we're not going to be, we're going to plan and do the other pieces. Much of the software components that VMware is building is not completely from scratch code. We're taking NSX. One of the most important components that VMware is adding to Outposts is NSX. We're not rewriting NSX, we're taking the NSX and applying this now, to a use case that's very much like that because we've adapted NSX now to be container-friendly, cloud-friendly. We've added NSX into the branch, VeloCloud. So those are the things that we're, you know, there's no rest for the weary anymore. >> And that gives you a consistent networking model, which is not trivial, as we've talked about. >> One of the things that I'm excited by, intrigued by, is, I know it's nuanced, but I see it as a key point, containers sometimes don't meet the security boundary issue. So, you guys can run a VM around a container, and run it under the covers. With Lambda. At super lightning speeds. It's not like a ten second instance to stand up. So that means there's more opportunities to create more abstractions around Kubernetes. And maintain security. There's so many benefits from this integrated kind of concept of consistency of operations for the software developer. >> John, you're absolutely right. Part of what we're trying to do is that word you talked about. Consistent infrastructure and operations. Consistent infrastructure and operations. And the container, if you've been seeing some of the ads in the San Francisco airport, we have some in London, and a few of the airports in New York, you'll see an ad that says "Containerware." It's playing on the word "ware", VMware. We want to be everyWARE, W-A-R-E. And if you think about the container being as pervasive as the vm in the future, I'm not going to say we're going to change the name of the company to be Containerware, but we want to be as pervasive as vm has been in VMware. So we have tens of millions of vms, in the twenty years we've had, maybe there'll be ten times as many containers. We want to become that de facto platform and containerware starts to take over. Right? What is that? Kubernetes-based. And we'll partner with the best. We've partnered with Google, we've partnered with Pivotal. Some of it would land on AWS, some of it will land on Azure. And you get a lot of the flexibility you have with that microservices platform. >> So, since you guys are on more of the software side, obviously Amazon's got software, but you guys actually are going to be much more broader, multiple clouds, as Amazon moves up the stack, I would imagine that as customers, I'm not going to buy in to only one cloud, there's other clouds out there, you guys should become a real strategic, traversal between clouds. So, we were debating, will customers have certain instances in, say, different clouds for specific, unique things, but yet run still horizontally, scalable on-premises, with VMware across multiple clouds. >> I think, you know John, it's going to be a lot like the hardware market was 20 years ago. It started to evolve into two or three major players. What's today Dell, HPE, Lenovo, at the time it was IBM, they divested to Lenovo, Cisco. In the storage place, two or three. I think the public cloud is not going to be three, five, ten. It's going to be two or three. Maybe four. And then maybe, in like China, Alibaba. So already, we have certain tools. Like CloudHealth's proposition is to manage costs and resources across multiple clouds. So we began to be already thinking about what is a multi-cloud world do? That said, in areas like this, which is a data center offer, we felt it was good for us to focus and get VMware Cloud and AWS to be the best hybrid cloud option. Give that a couple years, rather than trying to do everything and do it poorly, when you peanut butter your approach and try to do a lot of things with various different, so this is why we put a lot of special attention on VMware Cloud and AWS. We have an offering with IBM. We announced something with Alibaba. In due course VMware will need to have multiple cloud offerings. But I feel like this partnership and the specialness of this has really benefited both sides. >> Well, it's going to be very interesting, because IBM just made a 34 billion dollar validation of multi-cloud, so, and we talk about competition all the time. And it's evolving. >> We have a very good relationship with IBM. And listen, you have to be reasonably nuanced in your partnerships. So we're going to partner very heavily with IBM Global Services. We're going to partner very well with IBM Cloud. We're going to compete really hard with Red Hat! That's okay! Well, we'll compliment Linux. The bulk of their revenue's Linux. >> Of course, yeah. >> But make no mistake, we're going to compete hard with OpenShift. That's okay! That doesn't mean our IBM relationship is competitive. There's one piece of that, a very small part of the Red Hat revenue, OpenShift, that we overlap. The rest of it is complementary. We can be nuanced. It's sort of like walking and chewing gum. We can do both. And that's how we play. >> Before you wrap, now you know what we think of you, we think very highly of you, you're a superstar in our minds. However, you got to interview Sushmita, in India-- >> You know who Sushmita is? >> a true Bollywood superstar. Yes, an amazing actress, beautiful, talented. That must have been quite an experience. >> Well I got to tell ya, I was very intimidated. I opened-- >> I'll bet. >> Cause somehow I get assigned all these interviews to do. Malala, I'm usually on the opposite end. Your end. Malala, and Condoleezza Rice, and I told her I was really intimidated by her, and she said "Why?" I said, it's the first time that, I'm usually not tongue tied, but I did not know how to explain to my wife that I was going to be interviewing Ms. Universe. Okay, and she's like "What do you guys do at VMware? What the heck does Sushmita Sen have to do" But it was a good interview, I mean listen, for the India audience, we were celebrating our 20 year anniversary. She is an amazing woman who has achieved something that very few Indians have. And we wanted our Indian audience there to see that women can be successful. She's a big supporter of more women in business, fairness, equality, no prejudice, equal pay, all those things that we stand for. Which is part of our values. And if it weren't for the India audience she probably, I don't know if she would have worked at a Vmworld. We had Malala there, we had Condoleezza Rice at our last sales kickoff. We do these because we want to both teach our employees something, but also inspire them. And sometimes these speakers help with that cause. >> Sanjay, great to see you, thanks for coming on. I know you got to catch a flight. Big day today for you guys at VMware, congratulations. >> Thank you very much for having me. >> Thanks for all your support, great to see you. Great commentary, great insight. Sanjay Poonen, COO at VMware breaking down the announcement of Outposts, its relevance and impact on the market, and more importantly, the VMware AWS relationship. This is theCUBE bringing you all the action, day two of three days of wall-to-wall coverage. Two sets, hundreds of video assets coming, tons of posts on siliconangle.com, where all the coverage is. We'll be right back with more after this short break. (techno music)

>> Live from Washington DC, it's theCUBE! Covering Inforum DC 2018 brought to you by Infor. >> And good afternoon, or I guess at least Eastern Time, good afternoon. We're in Washington DC, theCUBE live here at Inforum '18. We're at the Washington D.C. Convention Center along with Dave Vellante, I'm John Walls. It's a pleasure to welcome Nanzio Esposito who's a VP and Head of Experience at Infor and you can tell he's the coolest guy in the room right now. (all laughing) Yeah, Nanzio, good to see ya. Thanks for joining us, we appreciate that. >> Thank you, thank you for asking. >> So you had a, as part of your primary responsibility, the in-house creative agency. >> Yep. >> Hook and Loop. First off, let's just deal with design, from an approach standpoint. Why is that so important for Infor to have its own in-house agency? >> Well I mean, we have amazing capabilities, and a lot of, and those capabilities really differentiate us against our competitives that. But what ends up happening is that our end users essentially want to have a more enjoyable and more satisfying experience, through their work. So, the reason why design is extremely important to Infor is because, through design, we get to do things like provide efficiency through workflows. We get to do things like create a design system that helps to escale and empower and enable our development teams to pick up UX best practices and UI assets so that they can build quicker. Or open-sourcing those kind of capabilities to be able to empower our partners and our customers to build apps with kind of a standard code base. So, I would tell you that the reason why design is so important is because we look at things from a very macro view, strategically. Design is very holistic, it's problem-solving. And it's taking the best of some of design's key attributes of modernizing the UI, being able to apply design thinking to understand kind of what the business value needs to come out of the system or the solution that's put in play. And how that mutually creates a beneficial kind of delivery mechanism to each user as they're doing their work. And also looking at kind of just the raw, sheer amount of assets that we have from data and being able to find ways to essentially come up with solutions that businesses today really need. And it's a very competitive landscape. And what best to have a designer be able to try to solve some of your business application needs. >> And does it change depending upon the vertical in which you're working? So, I mean, those have to be considerations too, and the environment, right, from the mobile if you're going to be at the desktop, you're going to be on a laptop or? >> Yep, yep. >> On iPad or whatever. All that factors into that. >> Yeah, definitely. You know, it is interesting. I mean, part of Infor strategy has always been to, you know, have industry-focused cloud suites. And from a design perspective, for us, we do tend to see patterns. So, it depends on user roles, kind of access points, you talked about devices. So we see the use of device in, say, healthcare industry, very different, say, than to the use of a device in manufacturing. But mobile, is really starting to kind of blur those lines. And you brought up something that was part of our mobile strategy, internal that was kind of finished out in October of 2017. Which is essentially what we call mobility in context. So context is very important. Knowing situationally where a user is in a moment so that they can, from one moment, work with, say, some portal. And that portal may be a laptop to a, say, an iPhone or even just an Alexa device, and be able to understand where they are, allow them to continue on in that workflow and make sure that it's integrated, it's smooth and it's direct and to the point. So, that's what has kind of transpired through the evolution of Hook and Loop because design has evolved and it's bigger than just modernizing our user interfaces here at Infor. >> So when we first heard about Hook and Loop, it was through Infor. It was the early part of this decade. The mobile was only five or six years old. I mean, smart phones. >> Yeah. >> At the time. So in was early days, you guys were first, certainly, of all the major software company enterprises to focus on that. Now, subsequently, we hear you've always heard a lot about UI. >> M-hmm. >> And UX. Subsequently, much more recently we're hearing much more around design. You're seeing, you know, you go to conferences like Service Now and they're focusing on this stuff and you guys have always been there. What's the difference between UX, UI, and sort of design at the core? >> Yeah, sure. I mean, I think it, sometimes the lines are blurred, right, and it depends on the industry and it depends on where you're speaking as far as when you say user experience design or if you say just design in general. So, I'm going to just take two steps back. The reason why I didn't go for head of design at Hook and Loop was just because design means, has a certain definition here at Infor. We are obviously an enterprise, it's very vast, it's extremely broad and at that point, each, say, of our major constituents, product management, it could be a product development, it could be a customer, they have different mental models on what design means. So, we wanted to go with something that's a little more elusive. Alright, so Head of Experience. But, essentially, now, through our evolution in our sixth year, we're really focused on product experience. So what that means is taking kind of all the learnings that we've had in the industry around modernizing UI, so that's essentially the way in which the solution manifests itself, how it looks, and the best of user experience. Essentially, what is the flow? What are the click states? How can we provide efficiency in form fields? But now you bring in A.I. and that obviously puts a different dimension on that process. But when it kind of all comes together, it's really just about making a strategic call on what the solution needs to be able to satisfy, all the different configurations in which it needs to account for, and then how to package that in a very lightweight manner. So, it's almost to the point that a company or a user doesn't need any instructional information on how to use it. And that's always been a goal at Hook and Loop. Through the six-year journey, strategically, even with some prior leadership, there was a very amazing strategic call to focus on a more mobile first initiative and mobile first, that brought forward kind of all the responsive web behaviors to our applications. So, that's great. Because that just essentially means that on any device, the application will conform, will render, to kind of provide the best usability that it can. As we're evolving, though, we're realizing that the future of work, and I mentioned this to the analysts yesterday, the future of work, which is now post-Millennial, and I know that sounds crazy 'cause I think we're all still seeing millennials in our workforce and trying to reconfigure, figure out what the company culture is, the purpose is, and how business solutions help to support that. But the article in the New York Times talked about iGen, and you know, the theme that Inforum here is all about human potential. Well, in the iGen generation, it's all about the personal aspects of the way in which they communicate, the way they do work, the way they have social gatherings. And I found it very profound because that essentially really supports what the vision of Hook and Loop is now in this era, which is the personal enterprise. And there's nothing more personal than the device that we choose on a daily level, which is the mobile device. So, at that point, it's extremely innate. And it definitely kind of personifies who we are in our digital world, our digital selves, and because it actually has all this tons of capability that's packed into it, what ends up happening is not about kind of the nine to five anymore, and I think you guys, and myself, we all know that. We're getting notifications and communication to, say, a loved one or some kind of social event that's going on and then getting pinged through some kind of communication or notification of work that we have jobs to do, there's things that have to get done. So, it moves from work-life balance to a work-life blend. And for our enterprise, and through kind of I think the investment that we've done with design, that allows us at Hook and Loop to really push the boundaries of user experience and think about the balance of all those to kind of give our customers always only exactly what the user needs right now. And that's been our new mantra, where we've kind of strategically pivoted, evolved, and been essentially looking at our principles and re-looking at our work, given all this investment in our capabilities. >> We heard this morning in the keynotes that you're basically infusing A.I. into your applications, in an effort to create better outcomes. Giving users advice as to how they maybe could have done things differently, maybe tracking some KPI's and giving feedback to the user, so that they can have better outcomes. How does A.I. from a design standpoint change the way in which you have to think about presenting data and information to the user? And not being intrusive, but being helpful? >> Yeah. I could probably talk about that for like the next two to five hours, but the reality is there's different versions or flavors of A.I. So, some of it could be more backend processes, like you alluded to and presenting, say, best potential outcomes that a user, or paths that a user can navigate or select or go down. One thing that we saw from a design perspective is the fact that you don't want to just present the recommendation. You don't want to lose the human factor. You have to establish trust with A.I. over time. So, in just saying, hey I got that or I got that done or here's the best KPI to use, you want to still have a system that can offer up why. And be able to kind of promote choice. A user doesn't want to feel, essentially, controlled. They want the system to be able to make them feel like they're in control. So, those are some nuances there. When it gets into kind of the more conversational aspects of A.I., you know, and I'm going well beyond kind of chat bots, having conversations and having it kind of leverage some of our CIR capabilities, find business objects and promote it, say through our GUI, conversations get intense. And why I say intense, it's some of the terminology we use at Hook and Loop. But that's just because utterances and variancing in the way in which we communicate, are complex. You might say, OK and I might say yeah. You might say I am on it and I might say, yo, I'm doin' that. And just through-- >> That's exactly right, as a matter of fact, that's exactly what David would say. (all laughing) >> I wasn't trying to say this or that. But they all mean the same thing, or in different contexts or whatever the inquiry was, we have to understand that kind of user intent and be able to map all those correlations. So, it's not so easy as just saying hey, we have A.I. and we'll put it into play. And from a design perspective, the last thing we want to do is ever alienate a user. So. >> A frustrated user. >> And frustrated user, exactly. So, just because you can doesn't mean you should and we really need to think strategically in a way in which we ultimately empower a user. So when I say user we're saying a name for customer's employee, or a new force customer customer. So it's a very interesting strategic place that we sit within Infora in our product development teams. >> Yeah, within user experience and best practices, so obviously there are some general trends or general concepts, what do you find out though amongst your clients and your user base maybe that offers additional insight or is giving you maybe a little sneak peak about something that you are uniquely discovering, if you can talk about that? >> Oh yeah, sure. I mean, I think as we evolved kind of our business model this year and our services, I think one of the things that we've learned over the years is that, like, we're no subject matter experts. Like at all. So it's kind of like, well, how do we get this information? How can we learn more? How can we provide or satisfy or create solutions that satisfy these certain pain points? So what we ended up doing is, ya know, I hear this from my team constantly, it's like who's the customer? Or who's the user? And we need personas. And we need to understand the journey maps. And we lose sight of some of the more internal mechanisms that we have that really kind of give us that information. So, we've, over the last few months, have gotten access to Infor Concierge, which is a tool that Infor created for our customers to be able to kind of understand what's new in the product. If they have any product enhancement requests, issues, that they would love to see, bugs, defects. They're finding that their Infor is working really well in creating kind of a two-way conversation. Well, what best to have design team, which, you know, product experience team, to be able to have access to all of that information. Be able to comb and sift through it. So, we're learning kind of what the customer and the user wants, but they're participating in that. So it's a really interesting orchestration or concert. And then on the flip side, we have a ton of subject matter experts. So, and that goes well beyond just our solution, industry solution, architects. This goes into like, our sales teams, or our solution consultants, or our channel partners. So, strategically over these last six to eight months, I think what we have uncovered is that we have a lot of support. And there's like ways for us to make decisions quicker and be able to test or have successes or failures in a very like small, confined box, so to speak. So that we make decisions that don't necessarily create massive ramifications in the enterprise but get us to kind of create value quicker in a more kind of sizeable chunk in deployment mechanism. So, I think the biggest thing that we've uncovered is the fact that, not only do we have a lot of talent but we have a lot of amazing, bright ideas. And that is why we moved from an in-house design agency to product experience because essentially Infor has grown and our team is everyone's becoming a designer. And that's you want. You want to go from a design organization which was the goal in 2012 to now in 2017, 2018 and where we're headed, to move from a design org to a design culture. And I think that's what is going to definitely going to get Infor to differentiate against its competitive landscape. >> 'Cause one of the problems with design is oftentimes the design, the ideal design, there's a gap between that and the actual functionality of the product. And then you end up with this kind of hybrid. Some of the design intent matches the outcome but then the functionality is sort of becomes roadmap. >> Yeah, and a lot of that was happening, I think 'cause we were going through an evolution. What we noticed is we need to move design closer to our product development teams in Hyderabad, Manila. You know, development is getting done all over the globe. So what we did was, we wanted to ensure that UX practitioners were, ya know, sitting side by side of our development teams so that in a moment's time they can have a conversation, quickly make a decision, and obviously just continue on their way. Another piece, though, is what is the right balance between having massive amounts of engineering capacity to, say, a designer that's in partnership with them? So we started practicing and growing our team to be less focused on some of the more baseline design capabilities and we brought in some really smart and talented engineers that understand design, find ways to translate it. And we're doing that kind of translation right now in building native mobile applications inside of Hook and Loop. And that gives us a mechanism to prove out our work, understand some of our decisions, get kind of the feasibility more done upfront so that when we make strategic calls or we want to scale from there, we start to minimize the gap between wouldn't this be amazing if it could render or do this, to, oh, God, we just did like, patchwork, or it was a quill that we created to get it done. We want to bridge that gap and get closer and closer to what the original concept or the idea was. >> So you announced one of those apps this week. >> Yeah, that was super exciting! >> If you want to talk about that. Congratulations. >> Thank you, thank you. Yeah, I mean leveraging the best of human-centered design, I can't mention the customer's name given the NDA, but we did work with a very large consulting firm that had 18,000 users. And they're kind of road warriors. So, strategically working with our C suite, we were focusing on more agnostic solutions and then scale to more industry-focused solutions, so this is in expense management. But we needed something that was insanely high consumer grade. So really driven by usability. But offered more of the baseline utility. So leveraging the capabilities of XM, this was all kind of like the road warrior, I just need to capture my receipt, potentially build a queue, wait 'til my credit card feeds in these data points, my expenses, match these expenses, submit a report, and like can I just get back on my day 'cause we all hate doing that. So the app that we just released, it's available on Apple iTunes, the Apple Store, today. It's called Infor Expense. It acts as a companion to Infor Expense Management. We say companion because if you're an Infor Expense Management customer today, you have access to it. And it really is a mechanism to kind of promote the best of what Hook and Loop is trying to scale, continues to scale, inside of Infor. At the same time, it's a playground for us. It's a playground for us to test new capabilities, leverage capabilities that are on the device. You know, evolve our design patterns and our UI assets. So that we kind of always stay at the tip of the spear. And that's essentially where Hook and Loop sits for Infor from a product strategy perspective. >> Well if you make expense reports easy, I'm all for it. >> Me too, right? >> I got my parking ticket right here, we can start as soon as we're done. >> Alright, you want me to take a picture of that? (all laughing) >> Nunzio, thanks for the time. >> Awesome. >> Congratulations. I know you're moving into your second year, it'll be an exciting time for you I'm sure. >> Yeah, I'm excited. >> Keynote tomorrow, right? >> Yeah, I'm opening up day two. >> Just give us real quick, sneak peak, what are you going to talk about? >> Yeah, it's, I think it's really just all about design's evolution inside of Infor, really setting the stage that Hook and Loop went from an internal kind of creative agency and is really moving towards product experience. So that's product strategy, product thinking, how do we aggregate all of that capability, from a data and A.I. perspective, and then find deployment mechanisms that not only inspire our internal teams, but more importantly, inspire our customers in the market. >> Good deal. >> Thank you again for the time. Pleasure. >> Alright, thank you. >> See you tomorrow morning. Nunzio Esposito joining us from Infor. Back with more, we're at Inforum '18. We're live in Washington D.C. and you are watching theCUBE. (light upbeat music)

>> Narrator: Live from Las Vegas it's theCube covering AWS reInvent 2017 presented by AWS, Intel and our ecosystem of partners. >> Hello and welcome to theCube's exclusive coverage here in Las Vegas for AWS, Amazon Web Services reinvent 2017, 45,000 people. It's theCube's fifth year in covering AWS, five years ago I think 7,000 people attended, this year close to 45,000, developers and industry participants. And of course this is theCube I'm John Furrier with my co-host Keith Townsend and we're excited to have Cube alumni Sanjay Poonen who's the chief operating officer for VMware. Sanjay great to see you, of course a good friend with Andy Jassy, you went to Harvard Business School together, both Mavericks, welcome to theCube. >> Thank you and you know what I loved about the keynote this morning? Andy and I both love music. And he had all these musical stuff man. He had Tom Petty, he had Eric Clapton. I an not sure I like all of his picks but at least those two, loved it man. >> The music thing really speaks to the artists, artists inside of this industry. >> Yes. >> And we were talking on theCube earlier that, we're in a time now where and I think Tom Siebel said it when he was on, that there's going to be a mass, just extinction of companies that don't make it on the digital transformation and he cited some. You're at VMware you guys are transforming and continue to do well, you've a relationship with Amazon Web Services, talk about the challenge that's in front of business executives right now around this transformation because possibly looking at extinction for some big brands potentially big companies in IT. >> It's interesting that Tom Siebel would say that in terms of where Siebel ended up and where salespersons now I respect him, he's obviously doing good things at C3. But listen that's I think what every company has got to ask itself, how do you build longevity? How do you make yourself sustainable? Next year will be our 20 year anniversary of VMware's founding. The story could have been written about VMware that you were the last good company and then you were a legacy company because you were relevant to yesterday's part of the world which was the data center. And I think the key thing that kept us awake the last two or three years was how do you make them relevant to the other side of history which is the public cloud? What we've really been able to do over the last two or three years is build a story of the company that's not just relevant to the data center and private cloud, which is not going away guys as you know but build a bridge into the public cloud and this partnership has been a key part of that and then of course the third part of that is our end user computing story. So I think cloud mobile security have become the pillars of the new VMware and we're very excited about that and this show, I mean if you combine the momentum of this show and VMworld, collectively at VMworld we have probably about 70, 80,000 people who come to VMworld and Vforums, there's 45,000 people here with all the other summits, there's probably have another 40,000 people, this is collectively about a 100, 150,000 people are coming to the largest infrastructure shows on the planet great momentum. >> And as an infrastructure show that's turning into a developer show line get your thoughts and I want to just clarify something 'cause we pointed this out at VMworld this year because it's pretty obvious what happened. The announcement that you guys did that Ragu and your team did with Ragu with AWS was instrumental. The proof was at VMworld where you saw clarity in the messaging. Everyone can see what's going on. I now know what's happening, my operations are gonna be secure, I can run VSphere on the cloud or on Prem, everything could be called what it is. But the reality was is that you guys have the operators, IT operations and Amazon has a robust cloud native developer community, not that they're conflicting in any way, they're coming together so it was a smart move so I got to ask you, as you guys continue your relationship with AWS, how are you guys tying the new ops role, ops teams with the dev teams because with IoT, this is where it's coming together you can see it right there? Your thoughts? >> I mean listen, the partnership is going great. I just saw Andy Jassy after his exec summit session, gave him a hug. We're very excited about it and I think of any of the technology vendors he mentioned on stage, we were on several slides there, mentioned a few times. I think we're probably one of the top tech partners of his and reality is, there's two aspects to the story. One is the developer and operations come together which you, you eloquently articulated. The other aspect is, we're the king of the private cloud and they're the king of the public cloud, when you can bring these together, you don't have to make it a choice between one or the other, we want to make sure that the private cloud is maximized to its full extent and then you build a bridge into the public cloud. I think those two factors, bringing developer and operations together and marrying the private and public cloud, what we call hybrid cloud computing, a term we coined and now of course many others-- >> I think-- >> On top of the term. Well whoever did. >> I think HP might have coined it. >> But nonetheless, we feel very good about the future about developer and operations and hybrid cloud computing being a good part of the world's future. >> Sanjay, I actually interviewed you 2016 VMworld and you said something very interesting that now I look back on it I'm like, "Oh of course." Which is that, you gave your developers the tools they needed to do their jobs which at the time included AWS before the announcement of VMware and AWS partnership. AWS doesn't change their data center for anyone so the value that obviously you guys are bringing to them and their customers speaks volumes. AWS has also said, Andy on stage says, he tries to go out and talk to customers every week. I joked that before the start of this that every LinkedIn request I get, you're already a connection of that LinkedIn request. How important is it for you to talk to your internal staff as well as your external customers to get the pulse of this operations and developer movement going and infused into the culture of VMware. >> Well Keith I appreciate the kind words. When we decided who to partner with and how to partner with them, when we had made the announcement last year, we went and talked to our customers. We're very customer and client focused as are they. And we began to hear a very proportional to the market share stats, AWS most prominently and every one of our customers were telling us the same thing that both Andy and us were asking which is "Why couldn't you get the best of both worlds? "You're making a choice." Now we had a little bit of an impediment in the sense that we had tried to build a public cloud with vCloud air but once we made the decision that we were getting out of that business, divested it, took care of those clients, the door really opened up and we started to test pulse with a couple of customers under NDA. What if you were to imagine a partnership between us and Amazon, what would you think? And man, I can tell you, a couple of these customers some of who are on stage at the time of the announcement, fell off their chair. This would be huge. This is going to be like a, one customer said it's gonna be like a Berlin Wall moment, the US and the Soviet Union getting together. I mean the momentum building up to it. So now what we've got to do, it's been a year later, we've shipped, released, the momentum still is pretty high there, we've gotta now start to really make this actionable, get customers excited. Most of my meetings here have been with customers. System integrators that came from one of the largest SIs in the world. They're seeing this as a big part of the momentum. Our booth here is pretty crowded. We've got to make sure now that the customers can start realizing the value of VMware and AWS as a build. The other thing that as you mentioned that both sides did very explicitly in the design of this was to ensure that each other's engineering teams were closely embedded. So it's almost like having an engineering team of VMware embedded inside Amazon and an engineering team of Amazon embedded inside VMware. That's how closely we work together. Never done before in the history of both companies. I don't think they've ever done it with anybody else, certainly the level of trying. That represents the trust we had with each other. >> Sanjay, I gotta ask you, we were talking with some folks last night, I was saying that you were coming on theCube and I said, "What should I ask Sanjay? "I want to get him a zinger, "I want to get him off as messaging." Hard to do but we'll try. They said, "Ask him about security." So I gotta ask you, because security has been Amazon's kryptonite for many years. They've done the work in the public sector, they've done the work in the cloud with security and it's paying off for them. Security still needs to get solved. It's a solvable problem. What is your stance on security now that you got the private and hybrid going on with the public? Anything change? I know you got the AirWatch, you're proud of that but what else is going on? >> I think quietly, VMware has become one of the prominent brands that have been talked about in security. We had a CIO survey that I saw recently in network security where increasingly, customers are talking about VMware because of NSX. When I go to the AirWatch conference I look at the business cards of people and they're all in the security domain of endpoint security. What we're finding is that, security requires a new view of it where, it can't be 6000 vendors. It feels like a strip mall where every little shop has got its boutique little thing that you ought to buy and when you buy a car you expect a lot of the things to be solved in the core aspects of the car as opposed to buying a lot of add-ons. So our point of view first off is that security needs to baked into the infrastructure, and we're gonna do that. With products like NSX that bake it into the data center, with products like AirWatch and Workspace ONE that bake it into the endpoint and with products like App Defence that even take it deeper into the core of the hypervisor. Given that we've begun to also really focus our education of customers on higher level terms, I was talking to a CIO yesterday who was educating his board on what are some of the key things in cyber security they need to worry about. And the CIO said this to me, the magic word that he is training all of his board members on, is segmentation. Micro segmentation segmentation is a very simple concept that NSX sort of pioneered. We'll finding that now to become very relevant. Same-- >> So that's paying off? >> Paying up big time. WannaCry and Petya taught us that, patching probably is a very important aspect of what people need to do. Encryption, you could argue a lot of what happened in the Equifax may have been mitigated if the data been encrypted. Identity, multi-factor authentication. We're seeing a couple of these key things being hygiene that we can educate people better on in security, it really is becoming a key part to our stories now. >> And you consider yourself top-tier security provider-- >> We are part of an ecosystem but our point of view in security now is very well informed in helping people on the data center to the endpoint to the cloud and helping them with some of these key areas. And because we're so customer focused, we don't come in at this from the way a traditional security players providing access to and we don't necessarily have a brand there but increasingly we're finding with the success of NSX, Workspace ONE and the introduction of new products like App Defense, we're building a point of security that's highly differentiated and unique. >> Sanjay big acquisition in SD-WAN space. Tell us how does that high stress security player and this acquisition in SD-WAN, the edge, the cloud plays into VMware which is traditionally a data center company, SD-wAN, help us understand that acquisition. >> Good question. >> As we saw the data center and the cloud starting to develop that people understand pretty well. We began to also hear and see another aspect of what people were starting to see happen which was the edge and increasingly IoT is one driver of that. And our customers started to say to us, "Listen if you're driving NSX and its success "in the data center, wouldn't it be good "to also have a software-defined wide area network strategy "that allows us to take that benefit of networking, "software-defined networking to the branch, to the edge?" So increasingly we had a choice. Do we build that ourselves on top of NSX and build out an SD-WAN capability which we could have done or do we go and look at our customers? For example we went and talked to telcos like AT&T and they said the best solution out there is a company that can develop cloud. We start to talk to customers who were using them and we analyzed the space and we felt it would be much faster for us to buy rather than build a story of a software-defined networking story that goes from the data center to the branch. And VeloCloud was well-regarded, I would view this, it's early and we haven't closed the acquisition as yet but once we close this, this has all the potential to have the type of transformative effect like in AirWatch or in nai-si-ra-hat in a different way at the edge. And we think the idea of edge core which is the data center and cloud become very key aspects of where infrastructure play. And it becomes a partnership opportunity. VeloCloud will become a partnership opportunity with the telcos, with the AWSs of the world and with the traditional enterprises. >> So bring it all together for us. Data center, NSX, Edge SD-WAN, AirWatch capability, IOT, how does all of that connect together? >> You should look at IoT and Edge being kind of related topics. Data center and the core being related topics, cloud being a third and then of course the end-user landscape and the endpoint being where it is, those would be the four areas. Data center being the core of where VMware started, that's always gonna be and our stick there so to speak is that we're gonna take what was done in hardware and do it in software significantly cheaper, less complex and make a lot of money there. But then we will help people bridge into the cloud and bridge into the edge, that's the core part of our strategy. Data center first, cloud, edge. And then the end user world sits on top of all of that because every device today is either a phone, a tablet or a laptop and there's no vendor that can manage the heterogeneous landscape today of Apple devices, Google devices, Apple being iOS and Mac, Android, Chrome in the case of Google, or Windows 10 in the case of Microsoft. That heterogeneous landscape, managing and securing that which is what AirWatch and Workspace ONE does is uniquely ours. So we think this proposition of data center, cloud, edge and end-user computing, huge opportunity for VMware. >> Can we expect to see NSX as the core of that? >> Absolutely. NSX becomes to us as important as ESX was, in fact that's kind of why we like the name. It becomes the backbone and platform for everything we do that connects the data center to the cloud, it's a key part of BMC for example. It connects the data center to the edge hence what we've done with SD-WAN and it's also a key part to what connects to the end user world. When you connect network security with what we're doing with AirWatch which we announced two years ago, you get magic. We think NSX becomes a fundamental and we're only in the first or second or third inning of software-defined networking. We have a few thousand customers okay of NSX, that's a fraction of the 500,000 customers of VMware. We think we can take that in and the networking market is an 80 billion dollar market ripe for a lot of innovation. >> Sanjay, I want to get your perspective on the industry landscape. Amazon announcing results, I laid it out on my Forbes story and in Silicon Angle all the coverage, go check it out but basically is, Amazon is going so fast the developers are voting with their workloads so their cloud thing is the elastic cloud, they check, they're winning and winning. You guys own the enterprised data center operating model which is private cloud I buy that but it's all still one cloud IoT, I like that. The question is how do you explain it to the people that don't know what's going on? Share your color on what's happening here because this is a historic moment. It's a renaissance-- >> I think listen, when I'm describing this to my wife or to my mother or somebody who's not and say "There's a world of tech companies "that applies to the consumer." In fact when I look at my ticker list, I divide them on consumer and enterprise. These are companies like Apple and Google and Facebook. They may have aspirations in enterprise but they're primarily consumer companies and those are actually what most people can relate to and those are now some of the biggest market cap companies in the world. When you look at the enterprise, typically you can divide them into applications companies, companies like Salesforce, SAP and parts of Oracle and others, Workday and then companies in infrastructure which is where companies like VMware and AWS and so on fit. I think what's happening is, there's a significant shift because of the cloud to a whole new avenue of spending where every company has to think about themselves as a technology company. And the same thing's happening with mobile devices. Cloud mobile security ties many of those conversations together. And there are companies that are innovators and there companies that you described earlier John at the start of this show that's going to become extinct. >> My thesis is this, I want to get your reaction to this. I believe a software renaissance is coming and it's gonna be operated differently and you guys are already kind of telegraphing your move so if that's the case, then a whole new guard is gonna be developing, he calls it the new garden. Old guard he refers to kind of the older guards. My criticism of him was is that he put a Gartner slide up there, that is as says old guard as you get. Andy's promoting this whole new guard thing yet he puts up the Gartner Magic Quadrant for infrastructure as a service, that's irrelevant to his entire presentation, hold on, the question is about you know I'm a Gardner-- >> Before I defend him. >> They're all guard, don't defend him too fast. I know the buyers see if they trust Gartner, maybe not. The point is, what are the new metrics? We need new metrics because the cloud is horizontally scalable. It's integrated. You got software driving decision making, it's not about a category, it's about a fabric. >> I'm not here to... I'm a friend of Andy, I love what he talked about and I'm not here to defend or criticize Gartner but what I liked about his presentation was, he showed the Gartner slide probably about 20 minutes into the presentation. He started off by his metrics of revenue and number of customers. >> I get that, show momentum, Gartner gives you like the number one-- >> But the number of customers is what counts the most. The most important metric is adoption and last year he said there was about a million customers this year he said several million. And if it's true that both startups and enterprises are adopting this, adopting, I don't mean just buying, there is momentum here. Irrespective, the analysts talking about this should be, hopefully-- >> Alright so I buy the customer and I've said that on theCube before, of course and Microsoft could say, "We listen to customers too and we have a zillion customers "running Office 365." Is that really cloud or fake cloud? >> At the end of the day, at the end of the day, it's not a winner take all market to one player. I think all of these companies will be successful. They have different strategies. Microsoft's strategy is driven from Office 365 and some of what they can do in Windows into Azure. These folks have come up from the bottom up. Oracle's trying to come at it from a different angle, Google's trying to come at a different angle and the good news is, all of these companies have deep pockets and will invest. Amazon does have a head start. They are number one in the market. >> Let me rephrase it. Modern applications could be, I'll by the customer workload argument if it's defined as a modern app. Because Oracle could say I got a zillion customers too and they win on that, those numbers are pretty strong so is Microsoft. But to me the cloud is showing a new model. >> Absolutely. >> So what is in your mind good metric to saying that's a modern app, that is not. >> I think when you can look at the modern companies like the Airbnb, the Pinterest, the Slacks and whoever. Some of them are going to make a decision to do their own infrastructure. Facebook does not put their IaaS on top of AWS or Azure or Google, they built their own data is because they can afford to do and want to do it. That's their competitive advantage. But for companies who can't, if they are building their apps on these platforms that's one element. And then the traditional enterprises, they think about their evolution. If they're starting to adopt these platforms not just to migrate old applications to new ones where VMware fits in, all building new cloud native applications on there, I think that momentum is clear. When was the last time you saw a company go from zero to 18 billion in 10 years, 10, 12 years that he's been around? Or VMware or Salesforce go from zero to eight billion in the last 18 years? This phenomenon of companies like Salesforce, VMware and AWS-- >> It's all the scale guys, you gotta get to scale, you gotta have value. >> This is unprecedented in the last five to 10 years, unprecedented. These companies I believe are going to be the companies of the tech future. I'm not saying that the old guard, but if they don't change, they won't be the companies that people talk about. The phenomenon of AWS just going from zero to 18 is, I personally think-- >> And growing 40% on that baseline. >> Andy's probably one of the greatest leaders of our modern time for his role in making that happen but I think these are the companies that we watch carefully. The companies that are growing rapidly, that our customers are adopting them in the hundreds of thousands if not millions, there's true momentum there. >> So Sanjay, data has gravity, data is also the new oil. We look at what Andy has in his arsenal, all of the date of that's in S3 that he can run, all his MI and AI services against, that's some great honey for this audience. When I look at VMware, there's not much of a data strategy, there's a security the data in transit but there's not a data strategy. What does VMware's data strategy to help customers take math without oil? >> We've talked about it in terms of our data analytics what we're doing machine learning and AI. We felt this year given so much of what we had to announce around security software-defined networking, the branch, the edge, putting more of that into VMworld which is usually our big event where we announce this stuff would have just crowded our people. But we began to lay the seeds of what you'll start to hear a lot more in 2018. Not trying to make a spoiler alert for but we acquired this company Wavefront that does, next-generation cloud native metrics and analytics. Think of it as like, you did that with AppDynamics in the old world, you're doing this with Wavefront in the new world of cloud native. We have really rethought through how, all the data we collect, whether it's on the data center or in the endpoint could be mined and become a telemetry that we actually use. We bought another company Apteligent, formerly called Criticism, that's allowing us to do that type of analytics on the endpoint. You're gonna see a couple of these moves that are the breadcrumbs of what we'll start announcing a lot more of a comprehensive analytics strategy in 2018, which I think we're very exciting. I think the other thing we've been cautious to do is not AI wash, there's a lot of cloud washing and machine learning washing that happened to companies-- >> They're stopping a wave on-- >> Now it's authentic, now I think it's out there when, when Andy talks about all they're doing in AI and machine learning, there's an authenticity to it. We want to be in the same way, have a measured, careful strategy and you will absolutely hear from us a lot more. Thank you for bringing it up because it's something that's on our radar. >> Sanjay we gotta go but thanks for coming and stopping by theCube. I know you're super busy and great to drop in and see you. >> Always a pleasure and thanks-- >> Congratulations-- >> And Keith good to talk to you again. >> Congratulations, all the success you're having with the show. >> We're doing our work, getting the reports out there, reporting here on theCube, we have two sets, 45,000 people, exclusive coverage on siliconangle.com, more data coming, every day, we have another whole day tomorrow, big night tonight, the Pub Crawl, meetings, VCs, I'll be out there, we'll be out there, grinding it out, ear to the ground, go get those stories and bring it to you. It's theCube live coverage from AWS reInvent 2017, we're back with more after this short break.

(upbeat electronic music) >> Narrator: Live from Washington, D.C., it's theCUBE. Covering .conf2017. Brought to you by Splunk. >> Welcome back to the nation's capital, everybody. This is theCUBE, the leader in live tech coverage, and we're here at .conf2017. Splunk's customer event. This is the seventh year that we're covering .conf with theCUBE here in the nation's capital, in the district. I'm Dave Vellante with George Gilbert. For the wrap of day one, we'll be here for two days. George, good day overall. At Splunk, the Splunk ecosystem continues to grow. Splunk evolves as a company. We're talking about a company. We didn't really have time this morning to run this down, but it's about a 1.2 billion dollar company, growing at about 30% a year. It's got a 10 billion dollar market cap, thanks in some part to the Symantec CEO, who'd found that, hey, Splunk might be a good acquisition target. And the stock shot up there for a little bit. Fifteen thousand customers. They've got a billion dollars in cash. Zero debt. So, nice balance sheet. Good growth. Small, but meaningful positive free-cash flow. So, from a financial perspective, this Splunk's looking pretty good right now. New CEO. They had some bumps in the road in the past. Some kind of, you know, guidance issues. But all seems to be pretty good right now. From your financial analyst, put your financial analyst hat on for a second. How's the company look to you? >> I actually think the numbers look better than the, sort of, high level optics, because it's mostly subscription revenue. And, so, you're rather than get, say, one hundred dollars up front from a perpetual license, they're getting, say, 20 to 25 dollars over a period of, you know, x-many years. So that actually depresses your operating margins. >> Dave: Sure >> And so their revenue impact, and their profitability, is better than it looks. >> Dave: Am I mistaken, I thought the vast majority of their revenue was still perpetual license, right? >> George: I think they've been converting to where you pay on the throughput. How much data you ingest per day. And I think that that's, you don't pay for it all up front. >> So they're migrating to a rateable model. >> George: Yeah. >> Which is, often times, crushes companies, but they seem to be managing through that. So, anyway, that's one thing that I wanted to talk about a little bit. Some of the themes that you and I talked about this morning. There were six that you and I kind of laid out. The expansion of the total available market. Really, from a monitoring, log data, into more of an application platform. Part of that is the shift from sim, from a security standpoint, into more analytic oriented >> George: Yeah. >> activities. >> The second one was the whole cloud and hybrid cloud play. Another theme we looked at was admin and dev complexity, and Splunk's recipe for simplifying that. Machine learning. Where does that fit in? Obviously, with some of their ITOM stuff they're trying to be more proactive and anticipatory. Breadth or depth. Meaning, do they go deep within sort of an application silo. Or use case. Or do they sort of more broadly based platform. And then, the last one, number six, is sort of IoT at edge processing. George, that's not something that we were able to spend much time on this morning, or any time. So, I'd like to start there. Everyone talks about IoT. We all know that, at least in concept, all this data is going to be generated. A lot of it is stateless. We talked about that on the wikibon research meeting a couple weeks ago. With serverless. Question. Where does Splunk fit in IoT. If the strategy is to, sort of, send it all back to the cloud, is that a viable approach? And is that their strategy? >> It's not their strategy, it's what their architecture allows today. But they know that doesn't work because in a world of sort of, industrial assets, and, sort of, consumer devices, you're producing so many more devices per year and so many more data elements per device, per time period, that the amount of data is exploding, exponentially. You cannot, for latency and bandwidth reasons, send that all to the cloud, to get an answer and then send it back. So, part of what's happening, and part of what Splunk is building, is the ability to capture that data. Perform low latency analytics, drive an answer to a local device, and then, what they do is, what other IoT platforms do, send up the interesting data. The stuff that doesn't fit. The stuff that you want to make sense out of, where you have to rethink your model. Your predictive model. And then that sort of research and refinement happens in the cloud. And when you think you have a good new model, you push it back out to the edge. This is, again, all theoretical. They haven't talked about it yet other than directionally. But, it's worth saying, as our distinguished CTO reminds us, that something David Floyer, 95% perhaps of the data and analytics, will happen, really the data processing will happen at the edge. More interesting, though, is the division of labor up in the cloud. It's not just retraining a model but we'll have very rich simulations. So, rather than just saying, training a self driving car to, you know, in the snow, to avoid sunlight that obscures it's view of the hazards in the road, you actually might have a simulation where you go through a whole bunch of different essentially, edge conditions >> Dave: Mmm-hmm. >> So the models get very, very rich. And then, those get pushed down to the edge for local processing. >> David: End-end learning is iterative >> George: Yes, yes. >> And that continues >> George: Yes. >> And, OK, so that's cool. That sort of leads to the discussion of cloud and hybrid cloud. We heard even from AWS that much of the processing and analysis can occur on-prem and their model. It's not something that just has to get done in the AWS cloud. Interesting to hear AWS acknowledge that. Whereas, five, six years ago, their dogma was everything goes into the cloud. So they're learning and evolving along with their partners. But what about Splunk's cloud play. Years ago, they announced, you know, cloud offering. We talked earlier much more of their revenue coming from routable models. I think 50% of their new business is cloud only. >> Mmm-hmm. >> Which makes sense. A lot of data analysis is going on in the cloud. What's your sense of their cloud strategy? Is it working? Are you sanguine toward their approach? >> So, we've had, since the dawn of the Pleistocene era in computing we've had multiple platforms. And there has always been a desire to have a common development and runtime environment across different platforms. So that developers are not locked in, or so that they can have a common platform for building apps across platforms >> David: Mmm-hmm. >> And for running them. The same, so like that you had, part of Cisco's success and Oracle's success was that you had the same admin experience no matter what you were running on. >> Dave: So, Linux, obviously. >> Yes >> Dave: Addressed what UNIX never could. >> Yes, yes >> Was the promise of UNIX. Obviously some of Microsoft's ascendancy was given that, you know, binary compatibility with Windows. >> George: Yes. >> OK, so, will we achieve that with cloud. It looks like we're further away from that than ever. >> George: There's choices here. Where, with Splunk, they will have this self contained environment that can run on many platforms. They're run on-prem. They'll have some subset that runs on the edge. They'll have something that runs compatably on Azure and Amazon and Google. But, once they're on the cloud they're these really powerful centrifugal forces that are pulling apart the compatibility of that singular platform. Because you'll have very specialized services. For instance, if you're doing IoT with Amazon, you have the kinesis firehose service, that's pumping data into Splunk or into S3 where other services might be operating on it. Whereas, with Azure you might have different edge services pumping data into could be Splunk, could be Splunk plus other services. For instance, Splunk doesn't have really strong scale-out SQL database. Where you might want to do some advanced analytics as part of your predictions. >> Dave: OK, so I could leverage DynamoDB as an example, or something like that. >> Yes. Yeah. >> Dave: OK. >> Or Redshift on Amazon. Or snowflake as cross platform. That sort of thing. >> Dave: OK, good. Are you here? You're here tomorrow? Yes? >> Yeah. >> At least in the morning? >> Yeah >> OK, homework assignment tonight. Were you participating in the analyst event today? >> Yeah >> OK, so you've got some other inside >> Yeah >> So bring all the NDA stuff. Tonight, like I say, homework assignment, try to distill that down. Would love to have you back if you have the time at the open tomorrow. >> If I have the time. Dave, I flew across the country to sit next to you. >> That's awesome. >> Ha ha ha. >> Great. Alright. Good. So boil it down for us. Tomorrow, why don't you come on and take us through what you learned yesterday Maybe some of the product announcements. And give us your the George Gilbert, kind of, wikibon view of the future for Splunk and this industry, OK? >> OK >> Alright, great. Thank you George for helping me wrap. That is a wrap of day one today. This is theCUBE. We're live all day tomorrow. Watch the replays at siliconangle.tv. Check out siliconangle.com for all the news. Check out wikibon.com for all the research. And go to Twitter. The hashtag of this event is #splunkconf17 and also checkout hashtag #cubegems and you'll see the snippits of today's show. This is theCUBE. The leader in live tech coverage. We're out day one. From the District. See you tomorrow. (upbeat electronic music)

>> Announcer: Live from the Javits Center in New York City, it's theCUBE. Covering Inforum 2017. Brought to you buy Infor. >> Welcome back to Inforum 2017 everybody. This is theCUBE, the leader in live tech coverage. Duncan Angove is here, the President of Infor and a Cube alum. Good to see you again Duncan. >> Hey, afternoon guys. >> So it's all coming together right? When we first met you guys down in New Orleans, we were sort of unpacking, trying to squint through what the strategy is. Now we call it the layer cake, we were talking about off camera, really starting to be cohesive. But set up sort of what's been going on at Infor. How are you feeling? What the vibe is like? >> Yeah it's been an amazing journey over the last six years. And, um, you know, all the investments we put in products, as you know, we said to you guys way back then, we've always put products at the center. Our belief is that if you put innovation and dramatic amounts of investment in the core product, everything else ends up taking care of itself. And we put our money where our mouth was. You know, we're a private company, so we can be fairly aggressive on the level of investment we put into R&D and it's increased double digit every single year. And I think the results you've seen over the last two years, in terms of our financials is that, you know the market's voting in a way that we're growing double digits dramatically faster than our peers. So that feels pretty good. >> So Jim is, I know, dying to get into the AI piece, but lets work our way up that sort of strategy layer cake with an individual had a lot to do with that. So you know, you guys started with the decision of Micro-verticals and you know the interesting thing to us is you're starting to see some of the big SI's join in. And I always joke, that they love to eat at the trough. But you took a lot of the food away by doing that last mile. >> Yeah. >> But now you're seeing them come in, why is that? >> You know I think the whole industry is evolving. And the roles that different and the valor that different companies in that ecosystem play, whether it's an enterprise software vendor or it's a systems integrator. Everything's changing. I mean, The Cloud was a big part of that. That took away tasks that you would sometimes see a systems integrator doing. As larger companies started to build more completely integrated suites, that took away the notion that you need a systems integrator to plug all those pieces together. And then the last piece for us was all of the modifications that were done to those suites of software to cover off gaps in industry functionality or gaps in localizations for a country, should be done inside the software. And you can only do that if you have a deep focus, by industry on going super, super deep at a rapid rate on covering out what we call these last malfeatures. So that means that the role of the systems integrators shifted. I mean they've obviously pivoted more recently into a digital realm. They've all acquired digital agencies. And having to adapt to this world where you have these suites of software that run in The Cloud that don't need as much integration or as much customization. So we were there you know five, six years ago. They weren't quite there. It was still part of this symbiotic relationship with other large vendors. And I think now, you know, the reason for the first time we've got guys like Accenture, and Deloitte, and Capgemini, and Grant Thornton here, is that they see that. And their business model's evolved. And you know those guys obviously like to be where they can win business and like to build practices around companies they see winning business. So the results we've seen and the growth we've seen over the last two to three years, obviously that's something they want a piece of. So I think it's going to work out. >> Alright so Jim, you're going to have to bear with me a second 'cause I want to keep going up the stack. So the second big milestone decision was AWS. >> Duncan: Yeah. >> And we all understand the benefits of AWS. But there's two sides to that cone and one is, when you show your architectural diagram, there's a lot of AWS in there. There's S3, there's DynamoDB, I think I saw Kinesis in there. I'm sure there's some Ec2 and other things. And it just allows you to focus on what you do best. At the same time, you're getting an increasingly complex data pipeline and ensuring end-to-end performance has to be technically, a real challenge for you. So, I wanted to ask you about that and see if you could comment and how you're managing that. >> Yeah so, I mean obviously, we were one of the first guys to actually go all in on Amazon as a Cloud delivery platform. And obviously others now have followed. But we're still one of their top five ISV's on there. The only company that Amazon reps actually get compensated on. And it's a two way relationship right? We're not just using them as a Cloud delivery partner. We're also using some of their components. You know you talked about some of their data storage components. We're also leverage them for AI which we'll get into in a second. But it's a two way relationship. You know, they run our asset management facility for all of their data centers globally. We do all the design and manufacturing of their drones and robots. We're partnered with them on the logistic side. So it's a deep two way relationship. But to get to your question on just sort of the volume and the integration. We work in integrations with staggering volumes right? I mean, retail, you're dealing with billions and billions of data points. And we'll probably get into that in a second you know. The whole asset management space, is one of the fastest growing applications we have. Driven by cycle dynamics of IoT and explosion in device data and all of that. So we've had for a very, very long time, had to figure out an efficient way to move large amounts of data that can be highly chatty. And do it in an efficient way. And sometimes it's less about the pipes in moving it around, it's how you ingest that data into the right technology from a data storage perspective. Ingest it and then turn it into insights that can power analytics or feed back into our applications to drive execution. Whether it's us predicting maintenance failure on a pump and then feeding that back into asset management to create a work order and schedule an engineer on it. Right? >> That's not a trivial calculus. Okay, now we're starting to get into Jim's wheelhouse, which is, you call it, I think you call it the "Age of Network Intelligence". And that's the GT Nexus acquisition. >> Yeah. >> To us it's all about the data. I think you said 18 years of transaction history there. So, talk about that layer and then we'll really get into the data the burst piece and then of course the AI. >> Yeah, so there were two parts to why we called it "The Age of Network Intelligence". And it's not often that technology or an idea comes along in human history that actually bends the curve of progress right? And I think that we said it on stage, the steam engine was one of those and it lead to the combustion engine, it lead to electricity and it lead to the internet and the mobile phone and it all kind of went. Of course it was invented by a British man, an Englishman you know? That doesn't happen very often right? Where it does that. And our belief is that the rise of networks, coupled with the rise of artificial intelligence, those two things together will have the same impact on society and mankind. And it's bigger than Infor and bigger than enterprise software, it's going to change everything. And it's not going to do it in a linear way. It's going to be exponential. So the network part of that for us, from an Infor perspective was, yes it was about the commerce network, which was GT Nexus, and the belief that almost every process you have inside an enterprise at some point has to leave the enterprise. You have to work with someone else, a supplier or a customer. But ERP's in general, were designed to automate everything inside the four walls. So our belief was that you should extend that and encompass an entire network. And that's obviously what the GT Nexus guys spent 18 years building was this idea of this logistics network and this network where you can actually conduct trade and commerce. They do over 500 billion dollars a year on that network. And we believe, and we've announced this as network CloudSuites, that those two worlds will blur. Right? That ultimately, CloudSuites will run completely nakedly on the network. And that gives you some very, very interesting information models and the parallel we always give is like a Linkedin or a Facebook. On Linkedin, there's one version of the application. Right? There's one information model where everyone's contact information is. Everyone's details about who they are is stored. It's not stored in all these disparate systems that need to be synchronized constantly. Right? It's all in one. And that's the power of GT Nexus and the commerce network, is that we have this one information model for the entire supply chain. And now, when you move the CloudSuite on top of that, it's like this one plus one is five. It's a very, very powerful idea. >> Alright Jim, chime in here, because you and I both excited about the burst when we dug into that a little bit. >> Yes. >> Quite impressed actually. Not lightweight vis, you know? It's not all sort of BI. >> Well the next generation of analytics, decision support analytics that infuse and inform and optimize transactions. In a distributed value chain. And so for the burst is a fairly strong team, you've got Brad Peters who was on the keynote yesterday, and of course did the pre-briefing for the analyst community the day before. I think it's really exciting, the Coleman strategy is really an ongoing initiative of course. First of all, on the competitive front, all of your top competitors in this very, I call it a war of attrition in ERP. SAP, Oracle and Microsoft have all made major investments on going in AI across their portfolios. With a specific focus on informing and infusing their respective ERP offerings. But what I conceived from what Infor's announced with the Coleman strategy, is that yours is far more comprehensive in terms of taking it across your entire portfolio, in a fairly accelerated fashion. I mean, you've already begun to incorporate, Coleman's already embedded in several of your vertical applications. First question I have for you Duncan, as I was looking through all the discussions around Coleman, when will this process be complete in terms of, "Colemanizing", is my term? "Colemanizing" the entire CloudSuite and of course network CloudSuite portfolio. That's a huge portfolio. And it's like you got fresh funding, a lot of it, from Koch industries. To what extent can, at what point in the next year or two, can most Infor customers have the confidence that their cloud applications are "Colemanized"? And then when will, if ever, Coleman AI technology be made available to those customers who are using your premises based software packages? >> So yeah, we could spend a long time talking about this. The thing about Coleman and RAI and machine learning capabilities is that we've been at work on it for a while. And you know we created the dynamic science labs. Our team of 65 Ph.D.'s based up in M.I.T. got over three and a half four years ago. And our differentiation versus all the other guys you mentioned is that, two things, one, we bring a very application-centric view of it. We're not trying to build a horizontal, generic, machine learning platform. In the same way that we- >> Yeah you're not IBM with Watson, all that stuff. >> Yeah, no, no. Or even Auricle. >> Jim: Understood. >> Or Microsoft. >> Jim: Nobody expects you to be. >> No, you know, and we've always been the guys that have worked for the Open Source community. Even when you look at like, we're the first guys to provide a completely open source stack underneath our technology with postscripts. We don't have a dog in the hunt like most of the other guys do. Right? So we tap in to the innovation that happens in the Open Source community. And when you look at all the real innovation that's happening in machine learning, it's happening in the Open Source Community. >> Jim: Yes. >> It's not happening with the old legacy, you know, ERP guys. >> Jim: Pencer, Flow and Spark and all that stuff. >> Yeah, Google, Apple, the GAFA. >> Yeah. >> Right? Google, Apple, Facebook, those are the guys that are doing it. And the academic community is light years ahead on top of that of what these other guys will do. So that's what we tap into right? >> Are you tapping into partners like AWS? 'Cause they've obviously, >> Duncan: Absolutely >> got a huge portfolio of AI. >> Yeah, so we. >> Give us a sense whether you're going to be licensing or co-developing Coleman technologies with them going forward. >> Yeah so we obviously we have NDA's with them, we're deeply inside their development organization in terms of working on things. You know, our science is obviously presented to them around ideas we think they need to go. I mean, we're a customer of their AI frameup to machine learning and we're testing it at scale with specific use cases in industries, right? So we can give them a lot of insights around where it needs to go and problems we're trying to solve. But we do that across a number of different organizations and we've got lots and lots of academic collaborations that happen on around all of the best universities that are pushing on this. We've even received funding from DAPA in certain cases around things that we're trying to solve for. You know quietly we've made some machine-learning acquisitions over the last five, six years. That have obviously brought this capability into it. But the point is we're going to leverage the innovation that happens around these frameworks. And then our job is understanding the industries we're in and that we're an applications company, is to bring it to life in these applications in a seamless way, that solves a very specific problem in an industry, in a powerful and unique way. You know on stage I talked about this idea of bringing this AI first mindset to how we go about doing it. >> So it's important, if I can interject. This is very important. This is Infor IP, the serious R&D that's gone into this. It's innovation. 'Cause you know what your competitors are going to say. They're going to deposition and say, oh, it's Alexa on steroids. But it's not. It's substantial IP and really leveraging a lot of the open source technologies that are out there. >> Yeah. So you know, I talked about there were four components to Coleman, right? And the first part of it was, we can leverage machine-learning services to make the CloudSuites conversational. So they can chat, and talk, and see, and hear, and all of that. And yeah, some of those are going to use the technology that sits behind Alexa. And it's available in AWS's Alexa as you guys know. But that's only really a small part of what we're doing. There are some places where we are looking at using computer vision. For example, automated inspection of car rental returns, is one area. We're using it for quality management pilot at a company that normally has humans inspect something on a production line. That kind of computer-vision, that's not Alexa, right? It's you know, I gave the example of image recognition. Some of it can leverage AWS's framework there. But again, we're always going to look for the best platform and framework out there to solve the specific problem that we're trying to solve. But we don't do it just for the sake of it. We do it with a focus to begin with, with an industry. Like, where's a really big problem we can solve? Or where is there a process that happens inside an application today that if you brought an AI first mindset to it, it's revolutionary. And we use this phrase, "the AI is the UI". And we've got some pretty good analogies there that can help bring it to life. >> And I like your approach for presenting your AI strategy, in terms of the value it delivers your customers, to business. You know, there's this specter out there in the culture that AI's going to automate everybody out of a job. Automation's very much a big part of your strategy but you expressed it well. Automating out those repetitive functions so that human beings, you can augment the productivity of human beings, free them up for more value-added activities and then augment those capabilities through conversational chat box. And so forth, and so on. Provide you know, in-application, in process, in context, decision support with recommendations and all that. I think that's the exact right way to pitch it. One of the things that we focus on and work on in terms of application development, disciplines that are totally fundamental to this new paradigm. Recommendation engines, recommender systems, in line to all application. It's happening, I mean, Coleman, that really in many ways, Coleman will be the silent, well not so silent, but it'll be the recommendation engine embedded inside all of your offerings at some point. At least in terms of the strategy you laid out. >> Yeah, no, absolutely right I mean. It's not just about, we all get hung up on machine-learning and deep learning 'cause it's the sexy part of AI, right? But there's a lot more. I mean, AI, all the way back, you can go all the way back to Socrates and the father of logic right? I mean, some of the things you can do is just based on very complex rules and logic. And what used to be called process automation right? And then it extends all the way to deep learning and neural networks and so on. So one of the things that Coleman also does, is it unifies a lot of this technology. Things that you would normally do for prediction or optimization, and optimization normally is the province of operations research guys right? Which again it's a completely different field. So it unifies all of that into one consistent platform that has all of that capability into it. And then it exposes it in a consistent way through our API architecture. So same thing with bots. People always think chat bots are separate. Well that too is unified inside Coleman. So it's a cohesive platform but again, industry focused. >> What's your point of view on developers? And how do you approach the development community and what's your strategy there? >> Yeah, I mean, it's critical right? So we've always, I mean, hired an incredible number of application engineers every year. I think the first 12 months we were here, we hired 1800 right? 'Cause you know, that's kind of what we do. So we believe hugely in smarts. And it sounds kind of obvious, but experience can be learned, smarts is portable. And we have a lot of programs in place with universities. We call it the Education Alliance Program. And I think we have up to 32 different universities around the world where we're actually influencing curriculum, and actually bringing students right out of there. Using internships during the year and then actually bringing them into our development organization. So we've got a whole pipeline there. I mean that's critical that we have access to those. >> And what about outside your four walls, or virtual walls have been four? Is there a strategy to specifically pursue external developers and open up a PAZ layer? >> Yeah we do. >> Or provide an STK for Coleman for example, for developers. >> Yeah so we did, as part of our Infor Operating Service update. Which is, you know, the name for our unified technology platform. We did announce Mongoose platform was a service. Our Mongoose pass. >> Host: Oh Mongoose, sure. >> So that now is being delivered as a platform with a service for application development. And it's used in two ways. It's used for us to build new applications. It's a very mobile-first type development framework too. And obviously Hook and Loop had a huge influence in how that ships. The neat thing about it, is that it ships with plumbing into ION API, plumbing into our security layer. So customers will use it because it leverages our security model. It's easy to access everything else. But it's also used by our Hook and Loop digital team. So those guys are going off and they're building completely differentiated curated apps for customers. And again, they're using Mongoose. So I think between ION API's and between all the things you get in the Infor Operating Service, and Mongoose, we've got a pretty good story around extensibility and application development. As it relates to an STK for Coleman, we're just working through that now. Again, our number one focus is to build those things into the applications. It's a feature. The way most companies have approached optimization and machine learning historically, is it's a discrete app that you have to license. And it's off to the side and you integrate it in. We don't think that's the right way of doing it. Machine-learning and artificial intelligence, is a platform. It's an enabler. And it fuses and changes every part of the CloudSuite. And we've got a great example on how you can rethink demand forecasting, demand planning. Every, regardless of the industry we serve, everyone has to predict demand right? It's the basis for almost every other decision that happens in the enterprise. And, how much to make, how many nurses to put on staff, all of that, every industry, that prediction of demand. And the thinking there really hasn't changed in 20, 30 years. It really hasn't. And some of that's just because of the constraints with technology. Storage, compute, all of that. Well with the access we have to the elastic super-computing now and the advancements in sort of machine-learning and AI, you can radically rethink all of that, and take what we call and "AI First" approach, which is what we've done with building our brand new demand prediction platform. So the example we gave is, you think about when early music players came along on the internet right? The focus was all around building a gorgeous experience for how to build a playlist. It was drag and drop, I could do it on a phone, I could share it with people and it showed pictures of the album art. But it was all around the usability of making that playlist better. Then guys like Spotify and Pandora came around and it took an AI First approach to it. And the machine builds your playlist. There is no UI. AI is the UI. And it can recommend music I never knew I would've liked. And the way it does that, comes back to the data. Which is why I'm going to circle back to Infor here in a second. Is that, it breaks a song down into hundreds if not thousands of attributes about that song. Sometimes it's done by a human, sometimes it's even done by machine listening algorithms. Then you have something that crawls the web, finds music reviews online, and further augments it with more and more attributes. Then you layer on top of that, user listening activity, thumbs up, thumbs down, play, pause, skip, share, purchase. And you find, at that attribute level, the very lowest level, the true demand drivers of a song. And that's what's powering it right? Just like you see with Netflix for movies and so on. Imagine bringing that same thought process into how you predict demand for items, that you've never promoted before. Never changed the price before. Never put in this store before. Never seen before. >> The cold start problem in billing recommendation areas. >> Exactly right, so, that's what we mean by AI First. It's not about just taking traditional demand planning approaches and making it look sexier and putting it on an iPad right? Rethink it. >> Well it's been awesome to watch. We are out of time. >> Yeah, we're out of time. >> Been awesome to watch the evolution, >> We could go on and on with this yeah. >> of Infor as it's really becoming a data company. And we love having executives like you on. >> Yeah >> You know, super articulate. You got technical chops. Congratulations on the last six years. >> Thanks. >> The sort of quasi-exit you guys had. >> Great show, amazing turnout. >> And look forward to watching the next six to 10. So thanks very much for coming out. >> Brilliant, thank you guys. Alright thank you. >> Alright keep it right there everybody, we'll be back with our next guest, this is Inforum 2017 and this is theCUBE. We'll be right back. (digital music)

>> Narrator: It's The Cube covering Sapphire Now 2017. Brought to you by S.A.P. Cloud Platform and Honna Interprise Cloud. >> Hello there, and welcome to The Cube conversation here in Palo Alto Studios, I'm John Furrier with The Cube, and we have a special guest here. Susie Wee, who's the vice president and CTO of DevNet at Cisco Systems for a Cube conversation around what's happening in cloud, and really some of the most important trends that are generating out of a new event that she's starting called DevNet Creative, which The Cube will be there. Susie, welcome to this Cube conversation. >> Hi, John. Thanks, it's great to be here. >> So, you were a pioneer within Cisco. You know, superstar technologist, CTO. You helped really put the Cisco DevNet Developer program together. Which as been a huge success. Congratulations. >> Thank you. >> And that's been, you know, Cisco has a big community of geeks. They're super smart. They like to surf the web and learn, and develop new stuff on Cisco, but there's also a whole nother world, and you created an event called DevNet Create as a new initiative. A new pioneering effort. >> Absolutely. >> Why a new event? What's the big news here? >> It's really interesting. I think that what's going on is in the world of, kind of, the infrastructure, right? So the infrastructure has our networking, our compute, our storage, and all of that is changing in that it's becoming programmable, and so once it's programmable, you're like, "What?" My infrastructure has APIs. Once it has APIs, you can do things like DevOps, right? You can start to do things like really have good flexibility with how you deploy your applications, you can get much more rapid deployment of apps, and you can get, just, fundamentally, different, and improved applications. So, the big thing that's going on is that there's this huge industry transformation in front of us, and the transformation is in how applications meet infrastructure, and this has happened as applications go to the cloud, then how applications meet the cloud, apps are changing, right? Then as the infrastructure becomes programmable, there's APIs into it, so there's this really kind of fresh ground that's ahead of us, and we can make the most of this, and that's what DevNet Create is all about. >> You know, people always ask me, this is our eighth year doing The Cube, "John, you and Dave do such a good job with The Cube." "You always pick the events that are going to be good." (laughter) We did some when we were first on, I do parole, I mean, with Cloud Air, and nobody had heard of Cloud Air. We can sniff the trends out, and to me, I think you're onto something really big here, and this is why I'm excited to bring The Cube to your event. I know it's small, it's inaugural, and it's very community-oriented, but I think you guys are on fault line of a massive shift, and I think you're on the right side of this, and I think the app dynamics acquisition that Cisco did points to some of the things that going to give Cisco, I think, a big lift, and that is, by looking at the plumbing as being automated, certainly relevant, that's not going away, but as you move up the stack, there's going to be the need for rapid, rapid application deployment. >> Susie Wee: Absolutely. >> Conceive, build, ship in minutes. It could be automated with bots and AI and whatnot, so this is the trend. Talk about that dynamic, 'cause that requires a fundamental rethinking and reimagining of the Cloud, security, how packets move. >> Susie Wee: Absolutely. >> Do you agree with that, and obviously, you're running the event, so you probably have some bias there, but more importantly, this big trend. >> Yeah, absolutely. So, kind of the applications themselves, we take apps for granted these days, and we've had applications forever, right? But the applications are how people interact with the system, with the Cloud, with all the surfaces that they use everyday, so we know that everyone's lives have been transformed with apps, and then we also know that the Cloud has been huge. You know, work loads are moving with the Cloud. The Cloud has instant deployment, global resources, again, big stuff there as well, but that's going to shift again, right? So what happens is now that the Cloud is as awesome as it is, now that applications are great as they are, we're going to go to this next generation where the applications get even better, the Cloud gets even better, the way they meet, and therefore, the surfaces that people use get better. Let's have some examples of like, what could be better? Well, now that you have things like app dynamics, you can start to get information from your applications in the infrastructure that give you business insights, so let's say that you have your application running, and then you know how many times different APIs have been called. You know what parts of your systems, or your applications, are called the most. You know who's using them. You know how often they're being used, by whom, and so on. What order are they being used? All of this can start to give you business insight, so then you say, oh, the infrastructure's not just about delivering, compute, network, and storage, it's also about giving the insights into how people are using my stuff, so I can get business insights all of a sudden, and then it's a whole new world. >> Talk about how you got here, and your journey with Cisco being creating the DevNet and now DevNet Create, 'cause I think there's some trends in the industry, and we're going to be covering Sapphire, which is SAP's big show coming up in Orlando, and Cisco has some announcements, I know, I was brief under NDA on that so I really can't talk about it right now, but I do know for a fact it's going to be some significant innovations that's Cisco's bringing to the table, and they're an app provider. Now, they're older version, they're the big ERP, and the big software and framewares, and they announced Cloud Native with iOS development. This notion of, like a new breed of developers is not a mutually exclusive argument against IT, it's just the continuation. There's a dynamic going on between software developments and apps, and not only just on the business model side, but actually, technically. >> Yeah, absolutely. There's a few different things. So, first of all, an app developers can, so we have something called Meraki. Meraki is our wireless access points, it was a big acquisition we did a few years ago, and you can think of, you know, wireless access points as giving you connectivity, wireless connectivity, but now imagine that it also, you have APIs into it and it tells you how many mobile devices are connected. Where are they connected from? And where are the mobile devices located? If someone comes into your store, how many people have been there before? And how many people is it their first time there? So, this is all stuff that you can get from your wireless access points and you can start to do really interesting stuff. I think any app developer would love to have that information of what can I get? Who's in my store, or who's in my venue? And the infrastructure gives you that. >> And you guys run most, if not all the networks in the world. An IOT device and your other things that's connected to a network, wireless or wired. >> Yeah. >> And packets are moving around, so you have that data. >> We have that data, yes. So, yes, exactly. Cisco infrastructure is everywhere. >> But it's been hard to expose that over the years because Cisco's always had this notion that we play at a certain part of the stack and now it's almost like finally, after decades of conversations, I know from folks I talked to at Cisco, let's move up the stack. There's always been this push that does Cisco move up the stack and how? >> Yes, and basically the way that the way and the reason that Cisco can move up the stack now is because the infrastructure is programmable, so now, our kit, the network, is programmable. Now there's analytics that are being built into the network as things are running around, so like having a programmable network, having analytics, where you can either gather information together on how applications and things are being used, or a key, and then how do we move up the stack is when we work with the ecosystem. We work with the community, is that we have a developer program like DevNet, which is why we founded it, is we're going to enable those app developers to come to the world of the enterprise, so right now, when you have an enterprise, you know, who can write an awesome IOT app for a building, or for a casino, or for a mall, or for a hotel, it's whoever that hotel works with. Whatever system integrator they have, and that's all amazing, 'cause, you know, your building's instrumented, >> Yeah, so you don't have to >> Susie Wee: You know where people are. >> It's a horizontal market of developers versus a specific Cisco community, which you have to nurture in and of itself. >> Exactly. >> In the course of business, guys who know how to handle the packets and the networking gear, and know someone who's, hey, I know Cisco's a network provider, a network supplier, I just don't want to have to go get a training certification to get some data; just give it to me. >> That's right, and so what we can do is say, hey, here's the APIs, go to developer.cisco.com. Everything's there. Everything's free. Here's learning labs on how to use the different APIs. Here's use cases. We actually have kit in the clouds so we have a sandbox that lets people use stuff. If you want to write an app for a contact center, 'cause we sell contacts in our stuff, we have a contact center that you can write and deploy your app on. You don't have to buy one to test it, right? So it's really interesting when these apps hit these places, which is that, you know, you need a contact center, well, we'll have one for you. >> Here's the hard question. I want to put you on the spot and bring the heat, if you will. You guys have been great in your own ecosystem. Dominant for Cisco as a company. As you move into this new ecosystem, because ecosystems are now business-model parts of public companies. Cloud Air just went public. Ortenwer's went public. Viewelsoft. A new class of new kind of open-source companies are going public. You guys are not necessarily an open-source company. You have open-source initiatives. You have to now embrace a new kind of ecosystem. >> Absolutely. >> Where's the progress on this? How early is it? 'Cause I think that's what DevNet created to me, and Cisco is now going into a new market and being proactive. >> Absolutely >> The question is are you ready? Do you have the chops? Where are you in the progress of that? (laughter) >> We're ready. Now, it's going to take work to work with the community to get there, but let me just go back 'cause when we first started DeveNet three years ago, we said, hey, are those networkers and those infrastructure guys, are they really ready for programmability and software? We didn't know, and then we had out first DevNet event, and it was packed. We're like, oh my gosh, these guys are so ready, and we didn't know that at the time, so we've made good progress there, but now that we're sitting there to work with the community, I think that I'm hoping that they're going to be embracing so we're certainly going to be open. We've actually opened up, kind of, the thinking within Cisco. We've done a lot of cultural change within Cisco because people have seen the success of DevNet and of the developers outside in the world who are actually jumping in and ready to embrace programmability. >> So, it's the old data. It started home. What you did. >> It started home. >> You did with your own core. >> And then used that to then build out. >> And you guys have apps, we know, again, we go to a lot of events. I've seen Cisco around in a lot of some of the open-stores events. I was at the Nix Foundation. You guys had some presence, but it seemed like a toe in the water. How are you guys going to go big in this? >> That's what changed, is actually Cisco has had some little developer efforts and a lot of heroics done by people within Cisco. Like, hey, I have this great product, I want to run a hackathon, right? So, we've had all of these heroic attempts, but until DevNet came along, we didn't have one centrally funded program with a mandate from the CEO to go and get that programmability and develop our ecosystem out there. That's what we had now for the last three years with DevNet, so now is we go to the next layer. You're right, we do have the people who are out working with the Cloud Native, working with OpenStock, working with OpenDaylight, working in the SDN, the Lennox foundation, and what we're doing is now bringing that to the next level. Again, adding the DevNet power, now that we have kind of established our base to really embrace this, so we hope that we're going to provide a lot more, kind of, foundation so that we can go big in these cases. >> How big is the cultural change within Cisco, just give some color without giving away too many trade secrets, but I know Cisco have, and a lot of my friends worked there I've known for years, from the beginning, I've been intimate with the company's culture, and they've been a case study of dominance, just the way their competitiveness has been, the products have been great. They run the networks, but now they have to move into this open source and the community world. Talk about some of the cultural changes. Any conversations? The CEO, when you talk to him, what's the conversation like there? >> I just met with our CEO, Chuck Robins, a couple weeks ago, updated him on our progress. He actually, he an John Chambers, together, helped found DevNet, so they understand the need for it, and they helped break down the barriers and create the funding and the organization to do it, and we had to do some re-orgs to get it going originally. >> It's not just lip service, they're putting their muscle behind it. >> They're putting their effort behind it and they're dedicated to it, and they understand it. Chuck is fully behind it. He sees the importance of programmability. He actually understands the applications meet infrastructure and the transformation that can happen there, so he is super supportive all the way. He sent me a text this morning and said, "Yeah, when is DevNet Create again?" >> Great. >> So he's on top of it. He knows what we're doing. >> We'll have him on The Cube for sure. >> Absolutely. >> So applications meets infrastructure is the DevOps ethos, and that really highlights your theme. >> It does. Now, some of the other cultural change that has happened is, for example, we have something called systems engineers in our sales force. So what happens is, in our sales force, we have technical folks. We have 6,000 sales engineers around the world. Systems engineers, and they understand the technical side. They're all taking DevNet training. They're taking DevNet learning labs. They're learning to code. They're learning to use our APIs and now, the other thing is that they're now running DevNet events around the world. These guys are not only getting trained, but they are running their own developer events, and so they've picked it all up. This is a transformation that, you know, we've partnered with them on, and that's really changed what they're doing and they're realizing that, hey, there's a conversation, like, we can finally have the assets to help out app developers, and the app developers, they do need help. People have been rating mobile apps for years. Not that many of them are making money, right? The question is how do you do good to those app developers? How do you bring those app developers into the enterprise? How do you take it and make sure that when you have the newest things, like... >> I've always said: feed it data. >> Feed it data. >> Data is a great life blood of applications. >> Absolutely, and so then the applications have data. Then you start to analyze it, you get the intelligence from it right there, and then all new insight. >> The automation around provisioning all that network plumbing is really, really hard and nuanced. If you can automate that away, developers will just have parade to your door. >> Absolutely. >> Alright, so, personal question. You've been very successful in building DevNet. Building developer programs is everyone's holy grail right now. There are people in companies: "We got to build a developer program." "Throw some money at it." They might have some lip service from the CEO or full commitment. What is the key to success. To get the companies and to actually conceive, to build, and deploy a successful developer program for a company? >> Yeah, that's a good question. I have to say that building the developer program is not as easy as you would think. I would think it should be easy, like get out there, go find some web service that's running free developer community stuff >> Someone creates a free code. >> Give 'em code, and that's it? But it's actually not that at all. There is actually a few things that have been key to what we've done. One of them, and actually, I spoke about this at the Evan's developer relations conference a few weeks back, but one of the keys there is just be entrepreneurial. You actually have to be an entrepreneur even if you're in a big company, then you especially have to be entrepreneurial. >> John: You got to hustle harder. >> And what I mean is you have to hustle hard and, with few resources, you have to show quick wins fast, and you have to make bets, right? What are the kind of things we do? Well, when we first started, we actually didn't have an organization. It was me. It was a couple rebels from different parts of the org who are like, we need this, and we were making proposals. >> Skull and crossbones kind of thing going on, yeah, big time. >> And we pretended that, hey, just pretend that we have a full-blown developer program. What would you do? What we did was, we went out there, we went made developer.cisco.com, we made one site, we brought all of the APIs into one place so that developers could access it, and it was just going through and kind of building that site, which is really hard in a big company like Cisco with APIs all over the place, and we just silently launched it, and then people started discovering it. Like, oh, all of Cisco's stuff is here. Holy Cow. That was one thing. >> Go humble early. Learned from Lennox himself. >> And we actually got kind of blasted on the Twittershpere because actually on our developer page, we had one section that was actually going to just product information and not having APIs in it, and so this guy was like, that's all product stuff. That's not about APIs, so we got blasted. We were like holy crap, he's right. We went, we changed it. Got rid of all that. >> That's agile. >> And fixed it and then he became our biggest fan, right? We changed and we learned from feedback from the community. >> You applied the entrepreneurial hustle. Hustle hard and make bets. >> Susie: Make bets. >> What's your big bet that your hustling now for, and I mean hustle in a good way, DevNet Create. What's your bet? >> Our first bet back then, big bet, was the DevNet's own at Cisco Live, was let's have a developer conference at Cisco Live. We have no idea if people are going to be interested, but let's just do it. So, we got second floor of Mosconi's. >> You're going big or going home. >> Yeah, exactly, so we like boom! Kind of got the same place they have Google IO and Dreamforce. We got the space, kind of created it, didn't know if anybody would come. It was jampacked. We're like, oh my God. John Chambers came by. He told his whole staff, like, you guys have to see what's happening. The DevNet zone's now the busiest part of Cisco Live. That was our big bet then, and fortunately it paid off, and I think that's what made us part of the fabric that let us continue on, but now our big bet is DevNet Create. It's about applications hitting the infrastructure and really ensuring that the infrastructure is giving benefit to app developers. >> John: Real benefit. >> Real benefit. It's not just for the sake of business, it's actually because, to me, there's a real inflection going on in the industry. Apps can just ride on top, and then just do whatever the infrastructure can provide for them, and that'll get us to one place, but once you really think about it, then you say, okay, where does the data for the apps need to sit? Oh my gosh, there's data sovereignty issues, so it can't just sit anywhere. How do we scale out? Like, when we scale out, and you could just say, oh yeah, just go buy it and Amazon, Google, someone else will take care of it for me. Well, some of it will, and you should absolutely use... We're using all of those >> The policy stuff. >> As well, but there's policy, there's, you know, so when you're really working to scale out and understand what's critical for your business, there's more that can be had, and then now you can go to the next level of where apps can get value added business insights from the network like what we were talking about before, and then, a really big thing is just when I kind of think forward to the world of IOT, and you say again, this building is now IOT enabled. This building has APIs. It's the infrastructure, and app developers would love to get access to that. >> Peter Barris and I were talking at The Cube about a new standard we want to see. All data should be presented in less than 100 milliseconds from any database. >> Susie: Nice, nice. >> That's a moon shot, but let's think about that. That's what we want. Okay, so final question. Congratulations on all your success, and I do believe that a trend is there, the question is when will it get there. Upcoming for DevNet Create, what do you hope to bring to the community? What do you want the community to look for and expect? And what will they see? >> Absolutely. What we want is, we hope that DevNet Create is just a catalyst for this to happen. For this transformation that's happening, and we want it to help drive things with the community in a faster way than if we just let it go itself. There's basically going to be two tracks at DevNet Create. One is on Cloud and DevOps, and the other is on IOT and apps. With Cloud, there's all these questions of how are we going to take monolithic legacy apps and turn them into micro surfaces? We have the world of containers. We have the world of container orchestration and everything there. That's all really hot stuff, but the way that we move this together, bring it into full production and get all of the apps really embracing that is key. What we're hoping will happen at DevNet Create is that the world of Cloud developers, the world of app developers, IOT developers will come together with those that are working in DevOps, those in the infrastructure to really understand what are the benefits that can happen across these layers? I'm not saying that every app developer needs to become an infrastructure developer, right? I'm not saying that every developer must be an operator, but there's benefits that can happen in the right way. Really, what we're hoping is that with DevNet Create, we can drive that conversation at the event itself and then continue with the ongoing community. >> And who are you targeting specifically to the event? Non-Cisco developers or Cisco developers with a plus, with a twist, or? >> Non-Cisco developers as well as some Cisco developers as well, but it's really about the industry. Where as when you go to a traditional DevNet event, you're going to be hearing all about Cisco APIs and Cisco products and how they play together in these solutions, but at DevNet Create, 90% or more of the talks are non-Cisco. We had a call for papers. I was really nervous when we had the call for papers and I was super relieved because we had great papers come in. Actually, the only problem is that we didn't have enough slots for the great papers. We even had to turn around some really good ones. Turn away some really good ones. We have a really strong agenda, and we actually said no to more Cisco talks because we wanted it from the ecosystem. We have people from Google, from Amazon, from Howdy. There's just lots of... >> And so will this be a Cisco event going forward? Or an industry event? Because there's a trend in the event world where people are going in for the big DreamForce and the big one show, big tent, zillion people, and then a series of industry shows around open-source communities with governance. Are you guys going to make this a Cisco managed show? Or thinking about opening it up to the community to manage? What's your thoughts on the vision of that? >> We're hoping to catalyze it. We will continue to have our other Cisco DevNet events that are really about the Cisco APIs themselves and really training and bringing along that core community, and we invite all the developers to attend that as well, but we really view DevNet Create to really be an event for the community. We'd be open to doing this with cosponsors and hosting it with others. >> So you're open. >> We're open. We're actually doing this with Lennox Foundation as well, so we have them involved. Many of them are on our advisory board. We are very open. We're actually working with SiliconANGLE and The Cube. We want to do it in the most open way as possible. >> As I said, we like to sniff out all the hot events. This is one inaugural event. I think it's really, really important because it really shows Cisco's commitment to open source in a way that's been toe in the waters in the past, like you said, little rebels in the organization doing their thing trying to get the word inside Cisco, but now with the cultural shift, I think you guys have it with app dynamics. There's a business path. I see a path there and I think the community only benefits. >> Absolutely, and if the community benefits, and our goal is to actually make our community and our developers successful. That's actually our only goal. For them to be successful in their careers and their business, and that will, in turn, make Cisco successful, but really, it's really about making the community successful. >> I mean if you think about the 5G end-to-end. I mean, end-to-end architectures are winning. We do a whole segment on end-to-end, but to make it end-to-end work that's not just one company, you'd need to have a strong developer community, and I think this is kind of where I see the event's importance is true network transformation and programmability. The ethos of DevOps needs to go to the next level so cars can program themselves. I mean, everything. 5G's coming too, so a lot of new stuff happening. >> Absolutely. I don't think any major industry transformation happened with one company alone. It really takes a community, right? Be it a community of product makers, a community of solutions providers, surface providers, and consumers themselves. This is really about the community. >> Susie, congratulations on all your success, and we're looking forward to seeing DevNet Create's inaugural opening in May. Appreciate it, and great to talk to you about some of the mega trends and your perspective on that. >> And thank you for helping to drive this vision and agenda. I think that we'll be able to do this together. >> Susie, with CTO at Cisco Systems, DevNet creator and pioneer with her team of rebels, now a full on group. Really talking about the app meets infrastructure total transformation enabling all the AI in terms of vehicles, smart cities, smart home. Thanks for joining us. This is a Cube conversation. I'm John Furrier and thanks for watching. (upbeat music)

>> Narrator: Live from Silicon Valley, it's theCUBE, covering Google Cloud, Next 17. >> Hey, welcome back everyone. We're here live in the Palo Alto Studios, SiliconANGLE Media, is theCUBE's new 4400 square foot studio, here in our studio, this is our sports center. I'm here with Stu Miniman, analyst at Wikibon on the team. I was at the event all day today, drove down to Palo Alto to give us the latest in-person updates, as well as, for the past two days, Stu has been at the Analyst Summit, which is Google's first analyst summit, Google Cloud. And Stu, we're going to break down day one in the books. Certainly, people starting to get onto there. After-meetups, parties, dinners, and festivities. 10,000 people came to the Google Annual Cloud Next Conference. A lot of customer conversations, not a lot of technology announcements, Stu. But we got another day tomorrow. >> John, first of all, congrats on the studio here. I mean, it's really exciting. I remember the first time I met you in Palo Alto, there was the corner in ColoSpace-- >> Cloud Air. >> A couple towards down for fries, at the (mumbles) And look at this space. Gorgeous studio. Excited to be here. Happy to do a couple videos. And I'll be in here all day tomorrow, helping to break down. >> Well, Stu, first allows us to, one, do a lot more coverage. Obviously, Google Next, you saw, was literally a blockbuster, as Diane Greene said. People were around the block, lines to get in, mass hysteria, chaos. They really couldn't scale the event, which is Google's scale, they nailed the scale software, but scaling event, no room for theCUBE. But we're pumping out videos. We did, what? 13 today. We'll do a lot more tomorrow, and get more now. So you're going to be coming in as well. But also, we had on-the-ground, cause we had phone call-ins from Akash Agarwal from SAP. We had an exclusive video with Sam Yen, who was breaking down the SAP strategic announcement with Google Cloud. And of course, we have a post going on siliconangle.com. A lot of videos up on youtube.com/siliconangle. Great commentary. And really the goal was to continue our coverage, at SiliconANGLE, theCUBE, Wikibon, in the Cloud. Obviously, we've been covering the Cloud since it's really been around. I've been covering Google since it was founded. So we have a lot history, a lot of inside baseball, certainly here in Palo Alto, where Larry Page lives in the neighborhood, friends at Google Earth. So the utmost respect for Google. But really, I mean, come on. The story, you can't put lipstick on a pig. Amazon is crushing them. And there's just no debate about that. And people trying to put that out there, wrote a post this morning, to actually try to illustrate that point. You really can't compare Google Cloud to AWS, because it's just two different animals, Stu. And my point was, "Okay, you want to compare them? "Let's compare them." And we're well briefed on the Cloud players, and you guys have the studies coming out of Wikibon. So there it is. And my post pretty much sums up the truth, which is, Google's really serious about the enterprise. Their making steps, there's some holes, there's some potential fatal flaws in how they allow customers to park their data. They have some architectural differences. But Stu, it's really a different animal. I mean, it's apples and oranges in the Cloud. I don't think it's worthy complaining, because certainly Amazon has the lead. But you have Microsoft, you have Google, you have Oracle, IBM, SAP, they're all kind of in the cluster of this, I call "NASCAR Formation", where they're all kind of jocking around, some go ahead. And it really is a race to get the table stake features done. And really, truly be serious contender for the enterprise. So you can be serious about the enterprise, and say, "Hey, I'm serious about the enterprise." But to be serious winner and leader, are two different ball games. >> And a lot to kind of break down here, John. Because first of all, some of the (mumbles) challenges, absolutely, they scaled that event really big. And kudos to them, 10,000 people, a lot of these things came together last minute. They treated the press and analysts really well. We got to sit up front. They had some good sessions. You just tweeted out, Diane Greene, in the analyst session, and in the Q&A after, absolutely nailed it. I mean, she is an icon in the industry. She's brilliant, really impressive. And she's been pulling together a great team of people that understand the enterprise. But who is Google going after, and how do they compete against so of the other guys, is really interesting to parse. Because some people were saying in the keynote, "We heard more about G Suite "than we heard about some of the Cloud features." Some of that is because they're going to do the announcements tomorrow. And you keep hearing all this G Suite stuff, and it makes me think of Microsoft, not Amazon. It makes me think of Office 365. And we've been hearing out of Amazon recently, they're trying to go after some of those business productivity applications. They're trying to go there where Microsoft is embedded. We know everybody wants to go after companies like IBM and Oracle, and their applications. Because Google has some applications, but really, their strength is been on the data. The machine the AI stuff was really interesting. Dr. Fei-Fei Li from Stanford, really good piece in the keynote there, when they hired her not that long ago. The community really perked up, and is really interesting. And everybody seems to think that this could be the secret weapon for Google. I actually asked them like, in some of the one-on-ones, "Is this the entry point? "Are most people coming for this piece, "when it's around these data challenges in the analytics, "and coming to Google." And they're like, "Well, it's part of it. "But no, we have broad play." Everything from devices through G Suite. And last year, when they did the show, it was all the Cloud. And this year, it's kind of the full enterprise suite, that they're pulling in. So there's some of that sorting out the messaging, and how do you pull all of these pieces together? As you know, when you've got a portfolio, it's like, "Oh well, I got to have a customer for G Suite." And then when the customer's up there talking about G Suite for a while, it's like, "Wait, it's--" >> Wait a minute. Is this a software? >> "What's going on?" >> Is this a sash show? Is this a workplace productivity show? Or is this a Cloud show? Again, this is what my issue is. First of all, the insight is very clear. When you start seeing G Suite, that means that they've got something else that they are either hiding or waiting to announce. But the key though, that is the head customers. That was one important thing. I pointed out in my blog post. To me, when I'm looking for it's competitive wins, and I want to parse out the G Suite, because it's easy just to lay that on, Microsoft does it with 365 of Office, Oracle does it with their stuff. And it does kind of make the numbers fuzzy a little bit. But ultimately, where's the beef on infrastructure as a service, and platform as a service? >> And John, good customers out there, Disney, Colgate, SAP as a partner, HSBC, eBay, Home Depot, which was a big announcement with Pivotal, last year, and Verizon were there. So these are companies, we all know them. Dan Greene was joking, "Disney is going to bring their magic onto our magic. "And make that work." So real enterprise use cases. They seem to have some good push-around developers. They just acquired Kaggle, which is working in some of that space. >> Apogee. >> Yeah, Apogee-- >> I think Apogee's an API company, come on. What does that relate to? It has nothing to do with the enterprise. It's an API management solution. Okay, yes. I guess it fits the stack for Cloud-Native, and for developers. I get that. But this show has to nail the enterprise, Stu. >> And John, you remember back four years ago, when we went to the re:Invent show for the first time, and it was like, they're talking to all the developers, and they haven't gotten to the enterprise. And then they over-pivoted to enterprise. And I listen to the customers that were talking and keynote today, and I said, "You know, they're talking digital transformation, "but it's not like GE and Nike getting up on stage, "being like, "'We're going to be a software company, "'and we're hiring lots--'" >> John: Moving our data center over. >> They were pulling all of over stuff, and it's like, "Oh yeah, Google's a good partner. "And we're using them--" >> But to be fair, Stu. Let's be fair, for a second. First of all, let's break down the keynotes. And then we'll get to some of the things about being fair. And I think, one, people should be fair to Diane Greene, because I think that the press and the coverage of it, looking at the media coverage, is weak. And I'll tell you why it's weak. Cause everyone has the same story as, "Oh, Google's finally serious about Cloud. "That's old news. "Diane Greene from day one says "we're serious with the Cloud." That's not the story. The story is, can they be a serious contender? That's number one. On the keynote, one, customer traction, I saw that, the slide up there. Yeah, the G Suite in there, but at least they're talking customers. Number two, the SAP news was strategic for Google. SAP now has Google Cloud platform, I mean, Google Cloud support for HANA, and also the SAP Cloud platform. And three, the Chief Data Science from AIG pointed. To me, those were the three highlights of the keynote. Each one, thematically, represents at least a positive direction for Google, big time, which is, one, customer adoption, the customer focus. Two, partnerships with SAP, and they had Disney up there. And then three, the real game changer, which is, can they change the AI machine learning, TensorFlow has a ton of traction. Intel Xeon chips now are optimized with TensorFlow. This is Google. >> TensorFlow, Kubernetes, it's really interesting. And it's interesting, John, I think if the media listened to Eric Schmidt at the end, he was talking straight to them. He's like, "Look, bullet one. "17 years ago, I told Google that "this is where we need to go. "Bullet two, 30 billion dollars "I'm investing in infrastructure. "And yes, it's real, "cause I had to sign off on all of this money. And we've been all saying for a while, "Is this another beta from Google. "Is it serious? "There's no ad revenue, what is this?" And Diane Greene, in the Q&A afterwards, somebody talked about, "Perpetual beta seems to be Google." And she's like, "Look, I want to differentiate. "We are not the consumer business. "The consumer business might kill something. "They might change something. "We're positioning, "this a Cloud that the enterprise can build on. "We will not deprecate something. "We'll support today. "We'll support the old version. "We will support you going forward." Big push for channel, go-to-market service and support, because they understand that that-- >> Yeah, but that's weak. >> For those of us that used Google for years, understand that-- >> There's no support. >> "Where do I call for Google?" Come on, no. >> Yeah, but they're very weak on that. And we broke that down with Tom Kemp earlier, from Centrify, where Google's play is very weak on the sales and marketing side. Yeah, I get the service piece. But go to Diane Greene for a second, she is an incredible, savvy enterprise executive. She knows Cloud. She moved from server to virtualization. And now she can move virtualization to Cloud. That is her playbook. And I think she's well suited to do that. And I think anyone who rushes to judgment on her keynote, given the fail of the teleprompter, I think is a little bit overstepping their bounds on that. I think it's fair to say that, she knows what she's doing. But she can only go as fast as they can go. And that is, you can't like hope that you're further along. The reality is, it takes time. Security and data are the key points. On your point you just mentioned, that's interesting. Because now the war goes on. Okay, Kubernetes, the microservices, some of the things going on in the applications side, as trends like Serverless come on, Stu, where you're looking at the containerization trend that's now gone to Kubernetes. This is the battleground. This is the ground that we've been at Dockercon, we've been at Linux, CNCF has got huge traction, the Cloud Native Compute Foundation. This is key. Now, that being said. The marketplace never panned out, Stu. And I wanted to get your analysis on this, cause you cover this. Few years ago, the world was like, "Oh, I want to be like Facebook." We've heard, "the Uber of this, and the Airbnb of that." Here's the thing. Name one company that is the Facebook of their company. It's not happening. There is no other Facebook, and there is no other Google. So run like Google, is just a good idea in principle, horizontally scalable, having all the software. But no one is like Google. No one is like Facebook, in the enterprise. So I think that Google's got to downclock their messaging. I won't say dumb down, maybe I'll just say, slow it down a little bit for the enterprise, because they care about different things. They care more about SLA than pricing. They care more about data sovereignty than the most epic architecture for data. What's your analysis? >> John, some really good points there. So there's a lot of technology, where like, "This is really cool." And Google is the biggest of it. Remember that software-defined networking we spent years talking about? Well, the first big company we heard about was Google, and they got up of stage, "We're the largest SDN deployer in the world on that." And it's like, "Great. "So if you're the enterprise, "don't deploy SDN, go to somebody else "that can deliver it for you. "If that's Google, that's great." Dockercon, the first year they had, 2014, Google got up there, talked about how they were using containers, and containers, and they spin up and spin down. Two billion containers in a week. Now, nobody else needs to spin up two billion containers a week, and do that down. But they learned from that. They build Kubernetes-- >> Well, I think that's a good leadership position. But it's leadership position to show that you got the mojo, which again, this is again, what I like about Google's strategy is, they're going to play the technology card. I think that's a good card to play. But there are some just table stakes they got to nail. One is the certifications, the security, the data. But also, the sales motions. Going into the enterprise takes time. And our advice to Diane Greene was, "Don't screw the gold Google culture. "Keep that technology leadership. "And buy somebody, "buy a company that's got a full blown sales force." >> But John, one of the critiques of Google has always been, everything they create, they create like for Google, and it's too Googley. I talked to a couple of friends, that know about AWS for a while, and when they're trying to do Google, they're like, "Boy, this is a lot tougher. "It's not as easy as what we're doing." Google says that they want to do a lot of simplicity. You touched on pricing, it's like, "Oh, we're going to make pricing "so much easier than what Amazon's doing." Amazon Reserved Instances is something that I hear a lot of negative feedback in the community on, and Google's like, "It's much simpler." But when I've talked to some people that have been using it, it's like, "Well, generally it should be cheaper, "and it should be easier. "But it's not as predictable. "And therefore, it's not speaking to what "the CFO needs to have. "I can't be getting a rebate sometime down the road. "Based on some advanced math, "I need to know what I'm going to be getting, "and how I'm going to be using it." >> And that's a good point, Stu. And this comes down to the consumability of the Cloud. I think what Amazon has done well, and this came out of many interviews today, but it was highlighted by Val Bercovici, who pointed out that, Amazon has made their service consumable by the enterprise. I think that's important. Google needs to start thinking about how enterprises want to consume Cloud, and hit those points. The other thing that Val and I teased at, was kind of some new ground, and he coined the term, or used the term, maybe he coined it, I'm not sure, empathy. Enterprise empathy. Google has developer empathy, they understand the developer community. They're rock solid on open source. Obviously, their mojo's phenomenal on technology, AI, et cetera, TensorFlow, all that stuff's great. Empathy for the enterprise, not there. And I think that's something that they're going to have to work on. And again, that's just evolution. You mentioned Amazon, our first event, developer, developer, developer. Me and Pat Gelsinger once called it the developer Cloud. Now they're truly the enterprise Cloud. It took three years for Amazon to do that. So you just can't jump to a trajectory. There's a huge amount of diseconomies of scale, Stu, to try and just be an enterprise player overnight, because, "We're Google." That's just not going to fly. And whether it's sales motions, pricing and support, security, this is hard. >> And sorting out that go-to-market, is going to take years. You see a lot of the big SIs are there. PwC, everywhere at the show. Accenture, big push at the show. We saw that a year or two ago, at the Amazon show. I talked to some friends in the channel, and they're like, "Yeah, Google's still got work to do. "They're not there." Look, Amazon has work to do on the go-to-market, and Google is still a couple-- >> I mean, Amazon's not spring chicken here. They're quietly, slowly, ramming up. But they're not in a good position with their sales force, needs to be where they want to be. Let's talk about technology now. So tomorrow we're expecting to see a bunch of stuff. And one area that I'm super excited about with Google, is if they can have their identity identified, and solidified with the mind of the enterprise, make their product consumable, change or adjust or buy a sales force, that could go out and actually sell to the enterprise, that's going to be key. But you're going to hear some cool trends that I like. And if you look at the TensorFlow, and the relationship, Intel, we're going to see Intel on stage tomorrow, coming out during one of the keynotes. And you're going to start to see the Xeon chip come out. And now you're starting to see now, the silicon piece. And this has been a data center nuisance, Stu. As we talked about with James Hamilton at Amazon, which having a hardware being optimized for software, really is the key. And what Intel's doing with Xeon, and we talked to some other people today about it, is that the Cloud is like an operating system, it's a global computer, if you want look at that. It's a mainframe, the software mainframe, as it's been called. You want a diversity of chipsets, from two cores Atom to 72 cores Xeon. And have them being used in certain cases, whether it's programmable silicon, or whether it's GPUs, having these things in use case scenarios, where the chips can accelerate the software evolution, to me is going to be the key, state of the art innovation. I think if Intel continues to get that right, companies like Google are going to crush it. Now, Amazon, they do their own. So this is going to another interesting dynamic. >> Yeah, it was actually one of the differentiating points Google's saying, is like, "Hey, you can get the Intel Skylake chip, "on Google Cloud, "probably six months before you're going to be able to "just call up your favorite OEM of choice, "and get that in there." And it's an interesting move. Because we've been covering for years, John, Google does a ton of servers. And they don't just do Intel, they've been heavily involved in the openPOWER movement, they're looking at alternatives, they're looking at low power, they're looking at from their device standpoint. They understand how to develop to all these pieces. They actually gave to the influencers, the press, the analysts, just like at Amazon, we all walked home with Echo Dot, everybody's walking home with the Google Homes. >> John: Did you get one? >> I did get one, disclaimer. Yeah, I got one. I'll be playing with it home. I figured I could have Alexa and Google talking to each other. >> Is it an evaluation unit? You have to give it back, or do you get to keep? >> No, I'm pretty sure they just let us keep that. >> John: Tainted. >> But what I'm interested to see, John, is we talk like Serverless, so I saw a ton of companies that were playing with Alexa at re:Invent, and they've been creating tons of skills. Lambda currently has the leadership out there. Google leverages Serverless in a lot of their architecture, it's what drives a lot of their analytics on the inside. Coming into the show, Google Cloud Functions is alpha. So we expect them to move that forward, but we will see with the announcements come tomorrow. But you would think if they're, try to stay that leadership though there, I actually got a statement from one of the guys that work on the Serverless, and Google believes that for functions, that whole Serverless, to really go where it needs to be, it needs to be open. Google isn't open sourcing anything this week, as far as I know. But they want to be able to move forward-- >> And they're doing great at open source. And I think one of the things, that not to rush to judgment on Google, and no one should, by the way. I mean, certainly, we put out our analysis, and we stick by that, because we know the enterprise pretty well, very well actually. So the thing that I like is that there are new use cases coming out. And we had someone who came on theCUBE here, Tarun Thakur, who's with Datos, datos.io. They're reimagining data backup and recovery in the Cloud. And when you factor in IoT, this is a paradigm shift. So I think we're going to see use cases, and this is a Google opportunity, where they can actually move the goal post a bit on the market, by enabling these no-use cases, whether it's something as, what might seem pedestrian, like backup and recovery, reimagining that is huge. That's going to take impact as the data domains of the world, and what not, that (mumbles). These new uses cases are going to evolve. And so I'm excited by that. But the key thing that came out of this, Stu, and this is where I want to get your reaction on is, Multicloud. Clearly the messaging in the industry, over the course of events that we've been covering, and highlighted today on Google Next is, Multicloud is the world we are living in. Now, you can argue that we're all in Amazon's world, but as we start developing, you're starting to see the emergence of Cloud services providers. Cloud services providers are going to have some tiering, certainly the big ones, and then you're going to have secondary partner like service providers. And Google putting G Suite in the mix, and Office 365 from Microsoft, and Oracle put in their apps in their Clouds stuff, highlights that the SaaS market is going to be very relevant. If that's the case, then why aren't we putting Salesforce in there, Adobe? They all got Clouds too. So if you believe that there's going to be specialism around Clouds, that opens up the notion that there'll be a series of Multicloud architectures. So, Stu-- >> Stu: Yeah so, I mean, John, first of all-- >> BS? Real? I mean what's going on? >> Cloud is this big broad term. From Wikibon's research standpoint, SaaS, today, is two-thirds of the public Cloud market. We spend a lot of time talking-- >> In revenue? >> In revenue. Revenue standpoint. So, absolutely, Salesforce, Oracle, Infor, Microsoft, all up there, big dollars. If we look at the much smaller part of the world, that infrastructures a service, that's where we're spending a lot of time-- >> And platforms a service, which Gartner kind of bundles in, that's how Gartner looks at it. >> It's interesting. This year, we're saying PaaS as a category goes away. It's either SaaS plus, I'm sorry, it's SaaS minus, or infrastructure plus. So look at what Salesforce did with Heroku. Look at what company service now are doing. Yes, there are solutions-- >> Why is PaaS going away? What's the thesis? What's the premise of that for Wikibon research? >> If we look at what PaaS, the idea was it tied to languages, things like portability. There are other tools and solutions that are going to be able to help there. Look at, Docker came out of a PaaS company, DockCloud. There's a really good article from one of the Docker guys talking about the history of this, and you and I are going to be at Dockercon. John, from what I hear, we're going to spending a lot of time talking about Kubernetes, at Dockercon. OpenStack Summit is going to be talking a lot about-- >> By the way, Kubernetes originated at Google. Another cool thing from Google. >> All right, so the PaaS as a market, even if you talk to the Cloud Foundry people, the OpenShift people. The term we got, had a year ago was PaaS is Passe, the nice piffy line. So it really feeds into, because, just some of these categorizations are what we, as industry watchers have a put in there, when you talk to Google, it's like, "Well, why are they talking about G Suite, "and Google Cloud, and even some of their pieces?" They're like, "Well, this is our bundle "that we put together." When you talk to Microsoft, and talk about Cloud, it's like, "Oh, well." They're including Skype in that. They're including Office 365. I'm like, "Well, that's our productivity. "That's a part of our overall solutions." Amazon, even when you talk to Amazon, it's not like that there are two separate companies. There's not AWS and Amazon, it's one company-- >> Are we living in a world of alternative facts, Stu? I mean, Larry Ellison coined the term "Fake Cloud", talking about Salesforce. I'm not going to say Google's a fake Cloud, cause certainly it's not. But when you start blending in these numbers, it's kind of shifting the narrative to having alternative facts, certainly skewing the revenue numbers. To your point, if PaaS goes away because the SaaS minuses that lower down the stack. Cause if you have microservices and orchestration, it kind of thins that out. So one, is that the case? And then I saw your tweet with Sam Ramji, he formally ran Cloud Foundry, he's now at Google, knows his stuff, ex-Microsoft guy, very strong dude. What's he take? What's his take on this? Did you get a chance to chat with Sam at all? >> Yeah, I mean, it was interesting, because Sam, right, coming from Cloud Foundry said, what Cloud Foundry was one of the things they were trying to do, was to really standardize across the clouds. And of course, little bias that he works at Google now. But he's like, "We couldn't do that with Google, "cause Google had really cool features. And of course, when you put an abstraction layer on, can I actually do all the stuff? And he's like, "We couldn't do that." Sure, if you talked to Amazon, they'll be like, "Come on. "Thousand features we announced last year, "look at all the things we have. "It's not like you can just take all of our pieces, "and use it there." Yes, at the VM, or container, or application microservices layer, we can sit on a lot of different Clouds, public or private. But as we said today, the Cloud is not a utility. John, you've been in this discussion for years. So we've talked about, "Oh, I'm just going "to have a Cloud broker, "and go out in a service." It's like, this is not, I'm not buying from Domino's and Pizza Hut, and it's pepperoni pizza's a pepperoni pizza. >> Well, Multicloud, and moving workloads across Clouds, is a different challenge. Certainly, I might have to some stuff here, maybe put some data and edge my bets on leveraging other services. But this brings up the total cost of ownership problem. If you look at the trajectory, say OpenStack, just as a random example. OpenStack, at one point, had a great promise. Now it's kind of niched down into infrastructural service. I know you're going to be covering that summit in Boston. And it's going to be interesting to see how that is. But the word in the community is, that OpenStack is struggling because of the employment challenges involved with it. So to me, Google has an opportunity to avoid that OpenStack kind of concept. Because, talking about Sam Ramji, open source is the wildcard in all of this. So if you look at a open source, and you believe that that PaaS layer's thinning down, to infrastructure and SaaS, then you got to look at the open source community, and that's going to be a key area, that we're certainly watching, and we've identified, and we've mentioned it before. But here's my point. If you look at the total cost of ownership. If I'm a customer, Stu, I'm like, "Okay, if I'm just going to move to the Cloud, "I need to rely and lean on my partner, "my vendor, my supplier, "Amazon, or Google, or Microsoft, whoever, "to provide really excellent manageability. "Really excellent security. "Because if I don't, I have to build it myself." So it's becoming the shark fin, the tip of the iceberg, that you don't see the hidden cost, because I would much rather have more confidence in manageability that I can control. But I don't want to have to spend resources building manageability software, if the stuff doesn't work. So there's the issue about Multicloud that I'm watching. Your thoughts? Or is that too nuance? >> No, no. First of all, one of the things is that if I look at what I was doing on premises, before versus public Cloud, yes, there are some hidden costs, but in general I think we understand them a little bit better in public Cloud. And public Cloud gives us a chance to do a do-over for this like security, which most of us understand that security is good in public Cloud. Now, security overall, lots of work to do, challenges, not security isn't the same across all of them. We've talked to plenty of companies that are helping to give security across Clouds. But this Multicloud discussion is still something that is sorting out. Portability is not simple, but it's where we're going. Today, most companies, if I'm not really small, have some on-prem pieces. And they're leveraging at least one Cloud. They're usually using many SaaS providers. And there's this whole giant ecosystem, John, around the Cloud management platforms. Because managing across lots of environment, is definitely a challenge. There's so many companies that are trying to solve them. And there's just dozens and dozens of these companies, attacking everything from licensing, to the data management, to everything else. So there's a lot of challenges there, especially the larger you get as a company, the more things you need to worry about. >> So Stu, just to wrap up our segment. Great day. Wanted to just get some color on the day. And highlighting some parody from the web is always great. Just got a tweet from fake Andy Jassy, which we know really isn't Andy Jassy. But Cloud Opinion was very active to the hashtag, that Twitter handle Cloud Opinion. But he had a medium post, and he said, "Eric Schmidt was boring. "Diane Greene was horrible. "Unfortunately, day one keynote were missed opportunity, "that left several gaps, "failed to portray Google's vision for Google Cloud. "They could've done the following, A, "explain the vision for the Cloud, "where do they see Google Cloud going. "Identify customer use cases that show samples "and customer adoption." They kind of did that. So discount that. My favorite line is this one, "Differentiate from other Cloud providers. "'We're Google damn it,' isn't working so well. "Neither is indirect shots as S3 downtime, "didn't work either as well as either. "Where is the customer's journey going? "And what's the most compelling thing for customers?" This phrase, "We're Google damn it," has kind of speaks to the arrogance of Google. And we've seen this before, and always say, Google doesn't have a bad arrogance. I like the Google mojo. I think the technology, they run hard. But they can sometimes, like, "Customer support, self-service." You can't really get someone on the phone. It's hard to replies from Google. >> "Check out YouTube video. "We own that too, don't you know that?" >> So this is a perception of Google. This could fly in the face, and that arrogance might blow up in the enterprise, cause the enterprises aren't that sophisticated to kind of recognize the mojo from Google. And they, "Hey, I want support. "I want SLAs. "I want security. "I want data flexibility." What's your thoughts? >> So Cloud Opinion wrote, I thought a really thoughtful piece leading up to it, that I didn't think was satire. Some of what he's putting in there, is definitely satire-- >> John: Some of it's kind of true though. >> From the keynote. So I did not get a sense in the meetings I've been in, or watching the keynote, that they were arrogant. They're growing. They're learning. They're working with the community. They're reaching out. They're doing all the things we think they need to do. They're listening really well. So, yes, I think the keynote was a missed opportunity overall. >> John: But we've got to give, point out that was a teleprompter fail. >> That was a piece of it. But even, we felt with a little bit of polish, some of the interactions would've been a little bit smoother. I thought Eric Schmidt's piece was really good at end. As I said before, the AI discussion was enlightening, and really solid. So I don't give it a glowing rating, but I'm not ready to trash it. And tomorrow is when they're going to have the announcements. And overall, there's good buzz going at the show. There's lots going on. >> Give 'em a letter. Letter grade. >> For the keynote? Or the show in general? >> So far, your experience as an analyst, cause you had the, again, to give them credit, I agree with you. First analyst conference. They are listening. And the slideshow, you see what they're doing. They're being humble. They didn't take any real direct shots at its competitors. They were really humble. >> And that is something that I think they could've helped to focus one something that differentiated a little bit. Something we had to pry out of them in some of the one-on-ones, is like, "Come on, what are you doing?" And they're like, "We're winning 50, 60% of our competitive deals." And I'm like, "Explain to us why. "Because we're not hearing it. "You're not articulating it as well." It's not like we expect them, it's like, "Oh wait, they told us we're arrogant. "Maybe we should be super humble now." It's kind of-- >> I don't think they're thinking that way. I think my impression of Google, knowing the companies history, and the people involved there, and Diane Greene in particular, as you know from the Vmware days. She's kind of humble, but she's not. She's tough. And she's good. And she's smart. >> And she's bringing in really good people. And by the way, John, I want to give them kudos, really supported International Women's Day, I love the, Fei-Fei got up, and she talked about her, one of her compatriots, another badass woman up there, that got like one of the big moments of the keynote there. >> John: Did they have a woman in tech panel? >> Not at this event. Because Diane was there, Fei-Fei was there. They had some women just participating in it. I know they had some other events going on throughout the show. >> I agree, and I think it's awesome. I think one of the things that I like about Google, and again, I'll reiterate, is that apples and oranges relative to the other Cloud guys. But remember, just because Amazon's lead is so far ahead, that you still have this jocking of position between the other players. And they're all taking the same pattern. Again, this is the same thing we talked about at our other analysis, is that, certainly at re:Invent, we talked about the same thing. Microsoft, Oracle, IBM, and now Google, are differentiating with their apps. And I think that's smart. I don't think that's a bad move at all. It does telegraph a little bit, that maybe they got, they could add more to show, we'll see tomorrow. But I don't think that's a bad thing. Again, it does make the numbers a little messy, in terms of what's what. But I think it's totally cool for a company to differentiate on their offering. >> Yeah, definitely. And John, as you said, Google is playing their game. They're not trying to play Amazon's game. They're not, Oracle's thing was what? You kind of get a little bit of the lead, and kind of just make sure how you attack and stay ahead of what they're doing, going to the boating analogy there. But Google knows where they're going, moving themselves forward. That they've made some really good progress. The amount of people, the amount of news they have. Are they moving fast enough to really try to close a little bit on the Amazon's world, is something I want to come out of the show with. Where are customers going? >> And it's a turbulent time too. As Peter Burris, our own Peter Buriss at Wikibon, would say, is a turbulent time. And it's going to really put everyone on notice. There's a lot to cover, if you're an analyst. I mean, you have compute, network storage, services. I mean, there's a slew of stuff that's being rolled out, either in table stakes for existing enterprises, plus new stuff. I mean, I didn't hear a lot of IoT today. Did you hear much IoT? Is there IoT coming to you at the briefing? >> Come on. I'm sure there's some service coming out from Google, that'll help us be able to process all this stuff much faster. They'll just replace this with-- >> So you're in the analyst meeting. I know you're under NDA, but is there IoT coming tomorrow? >> IoT was a term that I heard this week, yes. >> So all right, that's a good confirmation. Stu cannot confirm or deny that IoT will be there tomorrow. Okay, well, that's going to end day one of coverage, here in our studio. As you know, we got a new studio. We have folks on the ground. You're going to start to see a new CUBE formula, where we have in-studio coverage, and out in the field, like our normal CUBE, our "game day", as we say. Getting all the signal, extracting it from that noise out there, for you. Again, in-studio allows us to get more content. We bring our friends in. We want to get the content. We're going to get the summaries, and share that with you. I'm John Furrier, Stu Miniman, day one coverage. We'll see you tomorrow for another full day of special coverage, sponsored by Intel, two days of coverage. I want to thank Intel for supporting our editorial mission. We love the enterprise, we love Cloud, we love big data, love Smart Cities, autonomous vehicles, and the changing landscape in tech. We'll be back tomorrow, thanks for watching.

(The Cube Theme) >> Voiceover: Live from Silicon Valley, it's the Cube, covering Google Cloud Next '17. >> Hey, welcome back here, and we're here live in Palo Alto for a special two days of coverage of Google Next 2017. I've John Furrier here in The Cube. We have reporters and analysts on the ground who are calling in, getting reaction on all the great news, and of course, Google's march to the enterprise cloud really is the big story, of course, they have their cloud they've been powering with their infrastructure and it had great presence, powering their own stuff, just like Amazon.com had Amazon webservices, Google Cloud now powering Google and others. Diane Green, new CEO, taking the reins, making things happen, we covered that news, and for an entrepreneurial perspective we have Tarun Thakur who is a co-founder and CEO Datos.io, former entrepreneur at Data Domain, been in the business, newly funded, Series A entrepreneur funded with True Ventures and Lightspeed. >> That is correct, John, thank you. >> Thanks for coming on. Tell us what you guys do first. Explain what you guys as a company are doing. >> Absolutely. I'd love to first thank you for the opportunity. It's a pleasure to be here. About Datos, I'll sort of zoom out a little bit and if you really see what's really happening out in the industry, our founding premise, me and my co-founder, Prasenjit, our founding principle is very simple. There are some transformative changes happening in the application era. I was just listening to Akash talk rom SAP, and enterprise workloads are moving to the cloud. That was our founding premise, that not only do you not have those IOT workloads, these SAS workloads, the real time analytics workloads, being born in the cloud, but you have all these traditional workloads that are moving as fast as they can to the cloud. So if you really look at that transformative change, we have a very simple founding premise: applications define the choice of the IT stack underneath it. What do we mean by that? The choice of the database, the choice of the storage, the choice of all the data management tooling around it, starting with protection, starting with governance, compliance, and so on and so forth, right? So if the application workloads are under disruption, and they're moving to the cloud, the impact it has on the IT stack underneath is phenomenal. >> So Tarun, you guys had a great write-up in the Register, Chris Miller, who is well known in the story, 'cause we all follow him, he's a great guy, and very fair, but he can be critical, too, he's very snarky. We like his columns. He called you guys the Tesla of the backup world. What does he mean by that? Does he mean it like you have all the bells and whistles of a modern thing, or is there a specific nuance to why he's calling you the Tesla of the backup world? >> No, this is excellent, John. You know, we are fortunate and we're honored. >> Electric backup? I mean, what's happening here? (laughing) I mean, what does he mean by that? What's the meaning? >> Couldn't have given us a better privilege than what he gave. Had a chance to host him in the office, small office, much smaller than what you have here, in December, and a 45 minute session became a two hour session and really he dug into why the Tesla, and essentially it goes back to, John, you had the traditional workloads running on your traditional databases, classical scale-operational databases like Oracle and SQL. Now, you're dealing with these next generation, hyperscale distributed applications. IOT real time analytic is building on that team, those are being deployed fundamentally on distributed architectures. Your Apache Cassandra, your Amazon Dynamo DB, your Google Spanner, now that we're talking in the context of Google Cloud Next, right? When you look at those distributed architectures, there's so much fundamental shift. You don't run them on shared storage, you don't have media servers anymore in the cloud- >> You have the edge. You have the edge out there. >> You have the edge computing. Given all those changes, you have to fundamentally rethink of backup, and that's essentially what we did. Just going back to Tesla, Tesla was started with a fundamentally seminal architecture. >> So you thought this from the ground up. That's essentially one point, and the other one is that it's modern in the sense of it's really taken advantage of the new architecture. >> That's absolutely right, you know, when we started, again, back in June of 2014, we really started with the end in mind, ten years, the next ten years ahead of us, and the end in mind was, "Look, it's going to be distributed architectures, "it's going to be your hyperscale applications, the webscale applications, and you need to be able to understand data and protect it and recover it and manage your data at that scale. >> Okay, so you guys are also Google partners, so you have an interesting perspective. You're on the front lines, Series A entrepreneur, you haven't cleared the runway yet. You still have to prove yourself. The game is just starting; you don't end it with the financing. That's just validation for the vision and the mission, and you've had some good press so far from Chris, now as you execute, you have a partner in Google. What's your analysis of Google, and as someone who's close to them, certainly as an entrepreneur, you're nimble, you're fast, you understand the tech, you mentioned Spanner, great horizontal scale of opportunity, but some of the enterprises might be a little slower, and they have different orientation, so help us understand what's Google doing? What's their main focus? >> I'll give you an answer in three part series. Number one, we are, again, a start-up, seriously, as you said, we have a lot ahead of us, even though we've been out here for three years, it feels like yesterday. (laughing) >> John: It's a grind. >> It is a grind, but to partner Google Cloud, one of our key marquee customers, a Fortune 100 home improvement retailer, under NDA, cannot take their name out of respect. >> John: Well the register says Home Depot. (laughing) >> Okay. >> Okay, so- >> I'll let Chris do the honor, but it's a Fortune 100 home improvement retailer, John, and their line of business, their entire e-commerce platform, the CIO down has moved their entire platform, migrated from DB2 to Google Cloud. It's not running on DB2 on Google Cloud platform, it's running all on a distributed massive scale- >> So did they sunset DB2 or did they completely- >> Tarun: Completely migrated away from DB2. >> Okay. >> It's part of the digital transformation journey Home Depot is at. They are three years in, they have two more years to go, and as part of the digital transformation journey they're on, they are now running their e-commerce website, which, think of you and I going to Thanksgiving and buying your home tools, and that application runs on a highly scalable Apache Cassandra database on Google Cloud. Now, second part, going back to large-scale enterprises, Home Depot, being how progressive they are, they understood cloud does not mean recoverability. Cloud gives me the scale, cloud gives me the economics, cloud gives me the availability, but it doesn't give me the point in time, and I need myself to be covered against that "what if" moment. We have hold-the-delta moments, we have hold-the-gitlack moments, SalesForce.com down with that human error, right? You don't want to be in that position as a Home Depot. >> You mean Amazon went down? >> Tarun: And Amazon. >> Yeah, Amazon went down. >> And if you read the analysis, the analysis was, "We're sorry guys, there was a human error. "Somebody was meant to change this directory; "he changed that directory." >> So this is a whole new game. One of the fears that the enterprises have is that in a new architecture, besides security, which is a huge issue, we'll have another segment on that shortly, but is that I want to leverage the capabilities of the partner in the cloud, because manageability, certain things, I don't want to build on my own, and so I can see you guys being a new modern piece because the data piece is so important because I'm storing at the edge, I'm not moving data around, so there's no data in motion as much as it is on premise. Is that a big part of this? >> It is, from a, I'll zoom out again, from a CIO perspective, we pitched this to about 100+ CIOs so far. From there it is truly, and I hate to use this word, but it's truly a multi-cloud world, John. They have invested in private clouds and an on-prem infrastructure that ain't going anywhere anytime soon. They are moving some of their SAP instances to a CenturyLink, MSPs, the managed service providers, but they know, as a CIO, I have my application developers and I have my lines of businesses- >> John: And they have their operations guys, too. >> Who want to go as fast as they can. I'll come back to the operations in a second because you'll be very surprised to hear this, but again from a CIO down, he wants to make his application developers to go as fast as they can, and he wants the lines of business just to go open up the next applications- >> John: Because that's top-line revenue right there. >> That's top-line revenue right there. So they want scale, they want agility, but they don't want to sacrifice that insurance piece. Going back to the IT ops and the dev-ops and the classical ops, you'll be surprised, we've been working with this team, our lead-in to the Fortune 100 home improvement retailer was a line of business, but right now it's all about their core IT team. Their IT ops team, the database admins, the database ops people, they are the ones who are really running this product day-to-day, day in and day out, and scaling it, and using it at the pace they need to. >> What's the big misconception, if you could point to, about Google, because one of the things we're trying to surface is that Amazon and Google, it's not apples to apples comparison, they're different clouds, and it is multi-cloud, I want to get you to that question today, but we can get to that in a second, what your definition of that means, but for now, what is the big misconception in your mind, people might misconstrue with Google? >> That's a great question, John, and I was hearing your previous interview with Akash, and again, I'll give you our partner-centric view; a young start-up built something disruptive for that platform. We got Amazon as the first platform. We have a good set of customers running on Amazon, and of course, this home improvement retailer took us to Google Cloud, "Hey guys, if you want to work with us, "you have to support Google Cloud." We went to Google Cloud, and the amount of pull that we got from Google Cloud folks to make it happen in less than three months was phenomenal. They didn't stop at that. They brought their solution architect team, Google Cloud, wrote a paper about Datos, their team, and posted it on their website. "How to use Datos on Google Cloud." Fascinating. Amazon has never done that. It, again, speaks to if you see all the announcements that came out yesterday, Google Cloud has been a significant- >> Well Google's partnering, Google's partnering, one of the things that came out of today's news that has been teased out is Diane Green said in the keynote, "I like partnering." She used the word, "I like partnering," meaning Google, and she has that DNA. She's from VM, where she knows the valley game, she understands ecosystems. She also likes to work on some cool stuff, which could be a double-edged sword. She's always been innovating. But Google has the tech, and she knows enterprise, so they're marching down that road. What areas would you say Google needs to sharpen up a little bit to kind of move faster on? I mean, obviously there's no critique on them; they're pedaling as fast as they can, but in the areas you think they should work on, is it security, is it the data side, what are the things that you think they've got to pedal a little faster on. >> I would definitely start with enterprising touch. I think they need to really amp up the game around enterprise. >> John: You mean the people, the process? >> The people, the processes, the onboarding, the deployment, giving them the blue templates, giving them reference architectures, giving them, hand ruling them a little bit, and I think that'll go a long ways- >> John: The basic enterprise motions. >> Yes, you need that. You're a cloud; that doesn't mean my database guy is not going to need the help of a Google Cloud admin to help me onboard. They need that wrap-up. From their point on they build phenomenal scalable services. Snap invested two billion dollars in Google Cloud. They understand- >> And Amazon got the other half, but- >> The underlying infrastructure is there. >> Yeah but this is the thing. The problem that, the problem is that there's two perspectives of what we see. One is people want to run like Google in the sense of how they're scaling, but not everyone has Google-like infrastructure, so I think Google has to kind of, they want the developers, in my mind, they get a A+ there, with open source, what they do with Kubernetes and whatnot, the operational orientation is something they've got to work on, SLAs are more important than price. >> Managing the orchestration piece, giving them the visibility, letting them come on and come off, and going back to multi-cloud, I'll tell you again, the same customer took us to a use case, which is so fascinating, John. They want on-prem backup and recovery. Remember, protection is the Trojan horse. Protection, it all starts with protection. >> It's always one of those things that's always been front and center. You saw that. It used to be kind of a throw-away thing. "Oh, what about backup? "Oh, we didn't factor in." Now it's front and center, certainly cloud is going to be impacted because data's everywhere. Data's going to be highly frictionless. Okay, question, and final question on this piece, where we talk about what you guys are doing, what does multi-cloud mean, or two questions: what is the definition of multi-cloud, and what does cloud-native mean to you? Define those terms. >> Absolutely. Those two terms are very, very close to us. So multi-cloud, I'll begin with that. I'll give you a customer use case that will hopefully ground the conversation. A multi-cloud essentially means from a customer perspective, I'm going to run on-prem infrastructure, I want to be able to recover or manage that data in the cloud, I don't want to make multiple copies, I don't want to duplicate data, I want to recover a version of that data in the cloud, why? Because I have my application developers who want to test staff. I want my DR to be in a different cloud. I do not want to put all my eggs in one basket. So again, it is truly- >> John: It's a diversity issue. >> It is, and they want multiple-use cases to be spread across clouds. Some clouds have strength in DR, some clouds, like Amazon, have strength in orchestration, and onboarding, and some cloud platforms like Google Cloud have strengths in, hey, you can bring your application developers and you don't have to worry about retail. Some of the retailers, like Gap, like Safeway, like eBay, those guys will hesitate to go to Amazon because they know Amazon, at the heart, is a retail business. >> So conflict there. Now, cloud-native. Define cloud-native. >> Cloud-native, to us, is you have Oracle running that database natively within the services of the cloud. For example, take Amazon Dynamo DB. It's a beautiful example of a cloud-native service. You don't run Dynamo DB on-prem. It was built ultimately for the cloud. Cloud Spanner, another example of cloud-native. It is built for that infrastructure, floor ground up, and has been nurtured for the last ten years for the elastic infrastructure. >> Alright, Tarun, great to have you on. Quick plug for what you guys are doing. What's next? You got the Series A, you're getting customers, you got a big customer you can't talk about, but it's in the Register article, Home Depot. What other things are you working on? What's the key priorities? Hiring? You've got some new announcements coming up I hear. Rumor mill, I won't say who they are, but you're partnering. What's the key focus? What's your key objectives? >> No, we only stay focused on building, and as you early on said, it's still early for us. We want to stay focused on getting customer acquisition, customer momentum, deploying those customers, making them happy customers, having them become referenceable customers for us, and of course, the next big focus for me personally is going to be bringing some of the people in the team, some of the people who can help me scale the company- >> John: Engineering- >> Engineering, marketing, business development, sales, go to market, so that's going to be second we're to focus, and third, and again, you'll hear the announcement coming very quickly, we're going to be partnering with some of the leading enterprise infrastructure companies, both on their enterprise traditional storage companies, and some of the leading, I'm just going to leave it at that. >> And True Ventures is the seed investor and Lightspeed on the Series A, the True company on the Series A with them. 'Cause they tend to follow, they don't leave you hanging. >> Yeah, Puneet is excellent. I love him. >> Yeah, John Callahan's company's got great stuff. And they had some great eggs, they had FitBit and they've got a lot of great stuff going on. >> Well they're excellent, excellent pro-entrepreneur people. Great to work with as well. >> High integrity, great people. Tarun, thanks for coming on and sharing the entrepreneurial perspective, the innovation perspective, certainly as a Google partner, good to have your reaction and analysis. >> Thank you, John. >> It's The Cube, bringing you all the action from Google Next here in our studio. More Google Next coverage after this short break. (The Cube Theme)

from the noise it's the cube covering vmworld 2015 brought to you by vmware and it's ecosystem sponsors and now your host dave vellante we're back at Moscone everybody this is the cube SiliconANGLE Wikibon it's continuous production of vmworld 2015 we're riding the data wave Eric Harris dog is here he's a vice president marketing IBM storage in the Hawaiian shirt great to see you again my friend well Dave thank you very much as I keep telling people it's not about data lakes people have oceans a day to these days yes I oceans a day to dos today that oceans a data now so what's the story get the Hawaiian shirt on what do you got going on across the straw our big thing really is oceans of data so between all the solutions we have from a storage solution set a platform computing environment our joint deal that we do with Cisco with what we call the versus stack and our spectrum family of software now our customers are saying everything's going digital and it doesn't matter whether you're a global enterprise a midsize company or even an SMB with everything going digital it isn't about lakes of data it's about oceans of data so let's start maybe at the versus stack as a hyper converge is sort of taken the world by storm you're seeing vmware's obviously talking about it you got a bunch of startups talking about it when you guys made the move to to sell the the server business the x86 server business to lenovo BNT the acquisition of B&C went with it opened up whole new opportunities for IBM from a partnership standpoint and one of the first guys you went to a cisco so talk about that well we've had a great partnership with Cisco we deliver the versus tak through our mutual channel partners so globally so we have channel partners in all of the gos that are selling the versus stack solution we started originally with our v7000 product which allows us to not only provide a strong mid to your offering but because of our integration of our spectrum virtualized actually will virtualize heterogeneous torso over 300 arrays from our competitors can be virtualized giving any data center or cloud deployment single way to replicate single way to snapshot and of course a single way actually my great dinner which is a huge issue obviously in big deployment well and the same volume controller was really the first platform to do that that was the right gold standard and the whole the original you know tier 1 tier two storage sort of was defined by the sand volume controller kept really now you've built those capabilities into an end to the array so we started with our v7000 storwize was the first with a versus tack we announced last week two new versions one hour v nine thousand which incorporates that same value of the sand volume controller but an all-flash array okay that product is been incredibly successful for us we have thousands of customers we have deployed more petabytes than anyone in the industry and more units than anyone in the issue for you know some of those analysts that track the number side of the business we've done more than any pricing it right is what you're telling me we are definitely pricing it right we do north petabytes more minutes and more units than anybody by far but not the most revenue second most revenue so you well we're a fair price for a fair job as opposed to a high price for okay job that's what we believe in delivering more value for the money so we've got that so that opens up heavy virtualized environments heavy cloud environments big data analytics all those applications were all flash high-end Oracle deployments SP Hana configs all those sort of things are ideal same time you brought in the v5000 at the lower entry place of the mid-tier and it's with the UCS mini from Cisco so it gives you a lower entry price and allows a couple things one you can go in department until deployments a big enterprise to you can go into remote office deployments and also of large enterprise but three it allows you to take the value of a converged infrastructure down into smaller customers because it's a lower entry price point it's got all the value of the virtualization engine we have in all of our V family of products that v5 to be seven in the v9 all flash but it's at a much lower price point with a lower cost UCS mini and a lower cost switch infrastructure from from Cisco so it's a great solution for those big offices but again remote and department level and ideal though to move converged infrastructure down into smaller companies so so cisco has been incredibly successful with that space when Cisco first came out I a misunderstood I said how they going to fall flat in their face and servers and I was totally wrong about that because I didn't understand that they were trying to change the game what's it like partnering with those guys and how is it added value to your business well it's been very strong for us one they've got an excellent channel two they have a great direct sales model as does IBM three we've been partnering them for ages and ages and ages in fact in the 90s we sold a bunch of our networking technology to Cisco and is now deployed by Cisco so some of the networking technology at Cisco puts out there to the to their end users to their channel partners into you know their big telcos that actually came from IBM when we sold our networking division to Cisco in the mid-90s so strong partnership ever since then so let's talk more about the portfolio particularly i'm sickly interested in the whole TSM vs TSM came over to the storage group which thrilled me i think there was a great move by IBM to do that whoever made that decision smart move how has that affected having that storage software capability embedded into the storage business how has that affected your ability to go to market well it's been great so that's our spectrum family there are six elements to that spectrum protect which used to be TSM spectrum control which used to be the tsc product spectrum virtualized which is a software version of the sand volume controller so you can get as a software-only solution spectrum archive spectrum accelerate which is a scale-out block solution think of it as a software version of our XIV platform but software only and spectrum scale which gives incredible scale-out nas capability in fact spectrum scale has a number of customers in the enterprise side not in the HPC market but in global enterprises over 100 petabytes and we even have one customer that has one exabyte in production under spectrum scale exabyte one exabyte in production and not an hpc customer or not not one of the big universities not one of the think tanks but a commercial large global fortune 500 company we an exabyte with spectrum scale so so talk a little bit more about the strategy I think people all times misunderstand IBM's approach they say okay IBM getting out of the hardware business which they think Inferno must get another storage business you're not get out of the storage business obviously they hired hogging store oh so talk more about the strategy and how you're you know pursuing that yeah well I'd say a couple things so first of all our commitment to storage is very strong we're investing a billion in all flash technology and a billion in spectrum software in addition to our normal engineering development for our store wise family and our other members of our products that we've already had so a billion extra in flash and a billion extra in our software family in addition to that we've got a method of consumption that we're looking at so some end users want a full storage solution our ds8000 our flash systems are storwize some customers want to move to the software-defined storage and in several cases such as XIV software only spectrum virtualize okay we've got a number of different ways that you can consume the product and then lastly in several of the products such as spectrum scale spectrum accelerate and a lite version of spectrum control that we call spectrum control storage insights available through a cloud consumption model so if the customer wants a comprehensive solution we have it if the customer wants software-defined storage we have it if the customer wants integrated infrastructure with our vs stack we have it and if the customer wants a cloud storage model of consumption we have that too and quite honestly we think in bigger accounts they may have multiple consumption models for example core data center might go for a full storage solution but guess what the cloud solutions would be ideal for a remote or branch office so talk to me more about the cloud you're talking about the SoftLayer we here we go to the IBM shows you a soft layer of bluemix you know so a lot of money or the devops crowd what's going on bactrim accelerate spectrum scale and spectrum control are all available as a soft layer offering they are not targeting test and Dev they are not targeting you know just the bluemix out these are targeting core data center they could be testing dev or they could be remote office branch office opportunities for large enterprises that want to spend a full storage solution and spend that money on the core data center but for the remote office have spectrum scale delivered over softlayer an ideal solution and various consumption models which ever fits their need so David flora just wrote a piece on Wikibon calm of talking about latency and capacity storage at a very high level sort of segmenting the market those ways it's sort of sizing it up and projecting some of the trends and obviously latency storage he's thinking you know more flash oriented capacity storage more more disk spinning disk and tape is that a reasonable way to look at the business and how does it apply to your portfolio so we do think that's a reasonable way to look at it you have if you will a performance segment and a capacity segment depending the number of things that people need to really look at when they buy storage first of all I'm a storage guy for 30 years no one cares about storage it's all about the data it's all about the data that your storage optimizes it's about the workload the activation the use case for me I do too but unfortunately almost every time you know see how it's going to say almost every CIO is a software guy so it's how does the storage optimize my software environment and that's what's critical to them so we see certain applications that are very performance exit certain SLA s they need to meet we have some that are medium sensitive and we have some that of course are very capacity oriented which is our spectrum scale one exabyte with a single customer now that's capacity that's an ocean of data but we also have solutions we're able to put it together so for example in a lot of data analytics workloads that would run in spectrum scale we actually sell a lot of our all flash flash systems use the flash to ingest the data use flash to manage the metadata use the flash to run the search engine in a big giant config such as that and when you're running an analytics workload you run the analytics workload on that flash yet you're really doing a very large deployment hundreds of petabytes to an exabyte with our spectrum scale so we see if you will a continuum and the key thing as IBM offers all of the various piece parts to any level of the continuum and in that example I just gave combining high performance and deep high capacity software in a single solution to meet a business I mean IBM is an unbelievable company think about Watson cloud bluemix the analytics business deep deep heavy rd z mainframe so you got all the pieces how is the storage business how can it better leverage those other pieces and and is it or is it is it relevant or is it just just take the storage hill so we see our storage products as integrating with our other so for example we do a lot of deals where they buy a mainframe in our ds8000 sure we offer integrated infrastructure not only with cisco but actually with the power family as well it's called pure power and that has an integrated v7000 with a power server and we're looking at deepening that relationship as well a lot of analytics were lot alex workloads going scale so whether they buy the big insights whether they use in Watson we've got several customers use Watson but by flash systems because it's obviously very compute intensive so they use flash systems to do that so you know we fit in at the same time we have plenty of customers that don't buy anything else from IBM and just buy storage so we are appealing to a very broad audience those that are traditional IBM shops that by a lot of different products from IBM and those that go in fact one of our public references general mills they had not bought anything from any division of IBM for 50 years and one of our channel partners in Minnesota we are able to get in there with our XIV product and now not only do they buy XIV and some spectrum protect for backup but they've actually started to buy some other technology from IBM and for 50 years they bought nothing from IBM from any division so in that case storage led the way so again in certain accounts we're in there with the ds8000 and Z or were in there with Watson and flash systems and other accounts were pioneering and in some cases we're the only product they buy they don't buy from IBM we will meet whichever need they have now in periods in the last I mean it's been Evan flow in the storage business for IBM periods the last decade IBM deep rd but the products couldn't seem to go to market now you shared with me under under NDA so we can't talk about it in detail but shared with me the roadmap and and the product roadmap is accelerating from release maybe it's just my impression from what I'm used to should we expect to see a much more you know steady cadence of product delivery from IBM going forward absolutely so keeping in our spirit of oceans we ride the wave we don't fight the way and in today's era in any era of high-tech not just in store it doesn't matter whether storage whether its servers whether it's web to know whatever it is it's all about innovation and doing it quickly so we're going to ride that wave of innovation we're going to have a regular cadence of releases we released four different members of spectrum plus two verses stocks and next quarter you'll see five really five major product releases in one quarter and then in q1 you're going to see another three so we're making sure that as this trajectory of innovation hits all of high tech in all segments that IBM storage is not going to be left behind and we're going to continue to innovate on an accelerated pace that pace is is really important you know IBM again spends a lot of money on R&D it's key to get that product into the pipeline let's talk about vmware and vmworld obviously we're here at vmworld so on vmware very important constituency a lot of customers you got a you got to talk to vmware if you want to be in the data center today what is your strategy around vmware specifically but also generally as it relates to multi cloud environments whether it's your own cloud or other clouds OpenStack or what if you could talk about those so let's take virtualization first so we support a number of different hypervisors we support VMware extensively we support hyper-v we support kvm we support ovm we support open initiatives like OpenStack cinder we support Hadoop we have Hadoop connectors in many of our products so whether it's a cloud deployment or a virtual deployment we want to make sure we support everybody for example spectrum protect was announced last week with support for softlayer as a target device basically a tier well guess what in 1h we're going to support amazon and as you're not just softlayer so again we want to make sure we support everything with VMware specifically for the first time ever VMware has invited IBM storage on stave at three questions iBM has done things in the server world in the past but we have never ever ever been invited by VMware to their technical sessions in fact when is it five o'clock today it's called Project capstone which they publicly announced last week and it's about deploying Oracle environments in VMware virtualization it's a partnership with VMware with IBM flash systems all flash and with HP superdome servers and that's going to be on stage at five o'clock today here at moscone center awesome so we're starting to see a tighter relationship with with VMware building out the portfolio what do you say to the customer says yeah I hear you but vmware's doing all this sort of interesting stuff around things like v san what do you what do you tell a customer you know what about that so we see the San as it you know in this era of behemoths everyone is your partner everyone is your competitor but we work with Intel all the time other divisions of IBM think Intel's a major competitor some of our server division work with some of our storage competitors so we think you know we will work with everyone and while we work with VMware a number of angles so if he sounds a little bit of a competitor that's fine and we see an open space for all of the solutions in the market today we got to leave it there the last question so take us through sort of your objectives for IBM storage over the you know near and midterm what do you what should we be well so our big thing is to make sure we keep the cadence up there's so much development going on whether that be in software defined and integrated infrastructure in all flash in all the areas that we are going to make sure that we continue to develop in every area we've got the billion dollars in all flash in the billion dollars in software to find we are going to spend it and we're going to bring those products to market that fit the need so that the oceans of data that everyone is dealing with can be handled appropriately cost-effectively and quite honestly that oceans of data it's about the business value of the data not the storage underneath so we're going to make sure that for all those oceans a data we will allow them to drive real business value and make sure that those data oceans are protected meet their SLA s and are always available to their end user base I love it yet the Steve Mills billion-dollar playbook obviously worked in Linux it was well over a billion in analytics business IBM's a leader they're applying it to flash great acquisition of Texas memory systems you become a leader they're now going after the software to find Eric Herzog thanks very much for coming to the cubes great very much we love to have all right everybody will be back with our next guest right after this World we're live from vmworld and Moscone keep right there you