>> Narrator: From around the globe, it's theCube. With digital coverage of VMworld 2020. Brought to you by VMware and its ecosystem partners. >> Hello, and welcome back to theCube virtual coverage of VMworld 2020. I'm John Furrier, host of theCube. VMworld's not in person this year, it's on the virtual internet. A lot of content, check it out, vmworld.com, a lot of great stuff, online demos, and a lot of great keynotes. Here we got a great conversation to unpack, the NVIDIA, the AI and all things Cloud Native. With Krish Prasad, who's the SVP and GM of Cloud Platform, Business Unit, and Manuvir Das head of enterprise computing at NVIDIA. Gentlemen, great to see you virtually. Thanks for joining me on the virtual Cube, for the virtual VMworld 2020. >> Thank you John. >> Pleasure to be here. >> Quite a world. And I think one of the things that obviously we've been talking about all year since COVID is the acceleration of this virtualized environment with media and everyone working at home remote. Really puts the pressure on digital transformation Has been well discussed and documented. You guys have some big news, obviously on the main stage NVIDIA CEO, Jensen there legend. And of course, you know, big momentum with with AI and GPUs and all things, you know, computing. Krish, what are your announcements today? You got some big news. Could you take a minute to explain the big announcements today? >> Yeah, John. So today we want to make two major announcements regarding our partnership with NVIDIA. So let's take the first one, and talk through it and then we can get to the second announcement later. In the first one, as you well know, NVIDIA is the leader in AI and VMware as the leader in virtualization and cloud. This announcement is about us teaming up, deliver a jointly engineered solution to the market to bring AI to every enterprise. So as you well know, VMware has more than 300,000 customers worldwide. And we believe that this solution would enable our customers to transform their data centers or AI applications running on top of their virtualized VMware infrastructure that they already have. And we think that this is going to vastly accelerate the adoption of AI and essentially democratize AI in the enterprise. >> Why AI? Why now Manuvir? Obviously we know the GPUs have set the table for many cool things, from mining Bitcoin to really providing a great user experience. But AI has been a big driver. Why now? Why VMware now? >> Yes. Yeah. And I think it's important to understand this is about AI more than even about GPUs, you know. This is a great moment in time where AI has finally come to life, because the hardware and software has come together to make it possible. And if you just look at industries and different parts of life, how is AI impacting? So for example, if you're a company on the internet doing business, everything you do revolves around making recommendations to your customers about what they should do next. This is based on AI. Think about the world we live in today, with the importance of healthcare, drug discovery, finding vaccines for something like COVID. That work is dramatically accelerated if you use AI. And what we've been doing in NVIDIA over the years is, we started with the hardware technology with the GPU, the Parallel Processor, if you will, that could really make these algorithms real. And then we worked very hard on building up the ecosystem. You know, we have 2 million developers today who work with NVIDIA AI. That's thousands of companies that are using AI today. But then if you think about what Krish said, you know about the number of customers that VMware has, which is in the hundreds of thousands, the opportunity before us really now is, how do we democratize this? How do we take this power of AI, that makes every customer and every person better and put it in the hands of every enterprise customer? And we need a great vehicle for that, and that vehicle is VMware. >> Guys, before we get to the next question, I would just want to get your personal take on this, because again, we've talked many times, both of you've been on theCube on this topic. But now I want to highlight, you mentioned the GPU that's hardware. This is software. VMware had hardware partners and then still software's driving it. Software's driving everything. Whether it's something in space, it's an IOT device or anything at the edge of the network. Software, is the value. This has become so obvious. Just share your personal take on this for folks who are now seeing this for the first time. >> Yeah. I mean, I'll give you my take first. I'm a software guy by background, I learned a few years ago for the first time that an array is a storage device and not a data structure in programming. And that was a shock to my system. Definitely the world is based on algorithms. Algorithms are implemented in software. Great hardware enables those algorithms. >> Krish, your thoughts. we live we're living in the future right now. >> Yeah, yeah. I would say that, I mean, the developers are becoming the center. They are actually driving the transformation in this industry, right? It's all about the application development, it's all about software, the infrastructure itself is becoming software defined. And the reason for that is you want the developers to be able to craft the infrastructure the way they need for the applications to run on top of. So it's all about software like I said. >> Software defined. Yeah, just want to get that quick self-congratulatory high five amongst ourselves virtually. (laughs) Congratulations. >> Exactly. >> Krish, last time we spoke at VMworld, we were obviously in person, but we talked about Tanzu and vSphere. Okay, you had Project Pacific. Does this expand? Does this announcement expand on that offering? >> Absolutely. As you know John, for the past several years, VMware has been on this journey to define the Hybrid Cloud Infrastructure, right? Essentially is the software stack that we have, which will enable our customers to provide a cloud operating model to their developers, irrespective of where they want to land their workloads. Whether they want to land their workloads On-Premise, or if they want it to be on top of AWS, Google, Azure, VMware stack is already running across all of them as you well know. And in addition to that, we have around, you know, 4,000, 5,000 service providers who are also running our Platform to deliver cloud services to their customers. So as part of that journey, last year, we took the Platform and we added one further element to it. Traditionally, our platform has been used by customers for running via VMs. Last year, we natively integrated Kubernetes into our platform. This was the big re architecture of vSphere, as we talked about. That was delivered to the market. And essentially now customers can use the same platform to run Kubernetes, Containers and VM workloads. The exact same platform, it is operationally the same. So the same skillsets, tools and processes can be used to run Kubernetes as well as VM applications. And the same platform runs, whether you want to run it On-Premise or in any of the clouds, as we talked about before. So that vastly simplifies the operational complexity that our customers have to deal with. And this is the next chapter in that journey, by doing the same thing for AI workload. >> You guys had great success with these Co-Engineering joined efforts. VMware and now with NVIDIA is interesting. It's very relevant and is very cool. So it's cool and relevant, so check, check. Manuvir, talk about this, because how do you bring that vision to the enterprises? >> Yeah, John, I think, you know, it's important to understand there is some real deep Computer Science here between the Engineers at VMware and NVIDIA. Just to lay that out, you can think of this as a three layer stack, right? The first thing that you need is, clearly you need the hardware that is capable of running these algorithms, that's what the GPU enable. Then you need a great software stack for AI, all the right Algorithmics that take advantage of that hardware. This is actually where NVIDIA spends most of its effort today. People may sometimes think of NVIDIA as a GPU company, but we have much more a software company now, where we have over the years created a body of work of all of the software that it actually takes to do good AI. But then how do you marry the software stack with the hardware? You need a platform in the middle that supports the applications and consumes the hardware and exposes it properly. And that's where vSphere, you know, as Krish described with either VMs or Containers comes into the picture. So the Computer Science here is, to wire all these things up together with the right algorithmics so that you get real acceleration. So as examples of early work that the two teams have done together, we have workloads in healthcare, for example. In cancer detection, where the acceleration we get with this new stack is 30X, right? The workload is running 30 times faster than it was running before this integration just on CPUs. >> Great performance increase again. You guys are hiring a lot of software developers. I can attest to knowing folks in Silicon Valley and around the world. So I know you guys are bringing the software jobs to the table on a great product by the way, so congratulations. Krish, Democratization of AI for the enterprise. This is a liberating opportunity, because one of the things we've heard from your customers and also from VMware, but mostly from the customer's successes, is that there's two types of extremes. There's the, I'm going to modernize my business, certainly COVID forcing companies, whether they're airlines or whatever, not a lot going on, they have an opportunity to modernize, to essentially modern apps that are getting a tailwind from these new digital transformation accelerated. How does AI democratize this? Cause you got people and you've got technology. (laughs) Right? So share your thoughts on how you see this democratizing. >> That's a very good question. I think if you look at how people are running AI applications today, like you go to an enterprise, you would see that there is a silo of bare metal sun works on the side, where the AI stack is run. And you have people with specialized skills and different tools and utilities that manage that environment. And that is what is standing in the way of AI taking off in the enterprise, right? It is not the use case. There are all these use cases which are mission critical that all companies want to do, right? Worldwide, that has been the case. It is about the complexity of life that is standing in the way. So what we are doing with this is we are saying, "hey, that whole solution stack that Manuvir talked about, is integrated into the VMware Virtualized Infrastructure." Whether it's On-Prem or in the cloud. And you can manage that environment with the exact same tools and processes and skills that you traditionally had for running any other application on VMware infrastructure. So, you don't need to have anything special to run this. And that's what is going to give us the acceleration that we talked about and essentially hive the Democratization of AI. >> That's a great point. I just want to highlight that and call that out, because AI's every use case. You could almost say theCube could have AI and we do actually have a little bit of AI and some of our transcriptions and work. But it's not so much just use cases, it's actually not just saying you got to do it. So taking down that blocker, the complexity, certainly is the key. And that's a great point. We're going to call that out after. Alright, let's move on to the second part of the announcement. Krish Project Monterey. This is a big deal. And it looks like a, you know, kind of this elusive, it's architectural thing, but it's directionally really strategic for VMware. Could you take a minute to explain this announcement? Frame this for us. >> Absolutely. I think John, you remember Pat got on stage last year at Vmworld and said, you know, "we are undertaking the biggest re architecture of the vSphere platform in the last 10 years." And he was talking about natively embedding Kubernetes, in vSphere, right? Remember Tanzu and Project Pacific. This year we are announcing Project Monterrey. It's a project that is significant with several partners in the industry, along with NVIDIA was one of the key partners. And what we are doing is we are reimagination of the data center for the next generation applications. And at the center of it, what we are going to do is rearchitect vSphere and ESX. So that the ESX can normally run on the CPU, but it'll also run on the Smart Mix. And what this gives us is the whole, let's say data center, infrastructure type services to be offloaded from running on the CPU onto the Smart Mix. So what does this provide the applications? The applications then will perform better. And secondly, it provides an extra layer of security for the next generation applications. Now we are not going to stop there. We are going to use this architecture and extended it so that we can finally eliminate one of the big silos that exist in the enterprise, which is the bare metal silo. Right? Today we have virtualized environments and bare metal, and what this architecture will do is bring those bare metal environments also under ESX management. So you ESX will manage environments which are virtualized and environments which are running bare metal OS. And so that's one big breakthrough and simplification for the elimination of silo or the elimination of, you know, specialized skills to keep it running. And lastly, but most importantly, where we are going with this. That just on the question you asked us earlier about software defined and developers being in control. Where we want to go with this is give developers, the application developers, the ability to really define and create their run time on the Fly, dynamically. So think about it. If dynamically they're able to describe how the application should run. And the infrastructure essentially kind of attaches computer resources on the Fly, whether they are sitting in the same server or somewhere in the network as pools of resources. Bring it all together and compose the runtime environment for them. That's going to be huge. And they won't be constrained anymore by the resources that are tied to the physical server that they are running on. And that's the vision of where we are taking it. It is going to be the next big change in the industry in terms of enterprise computing. >> Sounds like an Operating System to me. Yeah. Run time, assembly orchestration, all these things coming together, exciting stuff. Looking forward to digging in more after Vmworld. Manuvir, how does this connect to NVIDIA and AI? Tie that together for us. >> Yeah, It's an interesting question, because you would think, you know, okay, so NVIDIA this GPU company or this AI company. But you have to remember that INVIDIA is also a networking company. Because friends at Mellanox joined us not that long ago. And the interesting thing is that there's a Yin and Yang here, because, Krish described the software vision, which is brilliant. And what this does is it imposes a lot on the host CPU of the server to do. And so what we've be doing in parallel is developing hardware. A new kind of "Nick", if you will, we call it a DPU or a Data Processing Unit or a Smart Nick that is capable of hosting all this stuff. So, amusingly when Krish and I started talking, we exchanged slides and we basically had the same diagram for our vision of where things go with that software, the infrastructure software being offloaded, data center infrastructure on a chip, if you will. Right? And so it's a very natural confluence. We are very excited to be part of this, >> Yeah. >> Monterey program with Krish and his team. And we think our DPU, which is called the NVIDIA BlueField-2, is a pretty good device to empower the work that Krish's team is doing. >> Guys it's awesome stuff. And I got to say, you know, I've been covering Vmworld now 11 years with theCube, and I've known VMware since its founding, just the evolution. And just recently before VMworld, you know, you saw the biggest IPO in the history of Wall Street, Snowflake an Enterprise Data Cloud Company. The number one IPO ever. Enterprise tech is so exciting. This is really awesome. And NVIDIA obviously well known, great brand. You own some chip company as well, and get processors and data and software. Guys, customers are going to be very interested in this, so what should customers do to find out more? Obviously you've got Project Monterey, strategic direction, right? Framed perfectly. You got this announcement. If I'm a customer, how do I get involved? How do I learn more? And what's in it for me. >> Yeah, John, I would say, sorry, go ahead, Krish. >> No, I was just going to say sorry Manuvir. I was just going to say like a lot of these discussions are going to be happening, there are going to be panel discussions there are going to be presentations at Vmworld. So I would encourage customers to really look at these topics around Project Monterey and also about the AI work we are doing with NVIDIA and attend those sessions and be active and we will have a ways for them to connect with us in terms of our early access programs and whatnot. And then as Manuvir was about to say, I think Manuvir, I will give it to you about GTC. >> Yeah, I think right after that, we have the NVIDIA conference, which is GTC, where we'll also go over this. And I think some of this work is a lot closer to hand than people might imagine. So I would encourage watching all the sessions and learning more about how to get started. >> Yeah, great stuff. And just for the folks @vmworld.com watching, Cloud City's got 60 solution demos, go look for the sessions. You got the EX, the expert sessions, Raghu, Joe Beda amongst other people from VMware are going to be there. And of course, a lot of action on the content. Guys, thanks so much for coming on. Congratulations on the news, big news. NVIDIA on the Bay in Virtual stage here at VMworld. And of course you're in theCube. Thanks for coming. Appreciate it. >> Thank you for having us. Okay. >> Thank you very much. >> This is Cube's coverage of VMworld 2020 virtual. I'm John Furrier, host of theCube virtual, here in Palo Alto, California for VMworld 2020. Thanks for watching. (upbeat music)

>> Announcer: Live, from Las Vegas, it's the Cube. Covering Dell Technologies World 2018. Brought to you by Dell EMC and it's ecosystem partners. >> And welcome back live here on the Cube as we continue our coverage of Dell Technologies World 2018. We're live at the Sands and it is now my pleasure for the first time today to say, "My partner's Stu Miniman". Stu, how you been? >> Awesome John, great to be talking on the Cube with you and our great guest. >> It's been too long, that's for sure! Good to see you again. We're joined by Manuvir Das who's the senior vice-president GM of unstructured data at Dell EMC. Thanks for being with us. We appreciate it. >> It's my pleasure to be here. >> Let's talk about your world, this exponential growth, this unpredictable growth, all this unstructured data, and now it's worth something, right? >> Yes, it is. >> So people are turning out to realize what an asset, what a resource that it's become. >> In fact, it's funny you say "Asset" because, the whole theme and tagline for my team is data capital, because I think people are coming to realize that just like you have capital assets in your factories and your people, data is part of the capital of a company now, right? And you really need to turn it into something, so I think it's an exciting time. For my team, we basically work in file and object storage, Isilon has been a market leader for some time. We have an object storage product called ECS, and we are the market leader, and we have been for some time, but it's a very interesting time because data is growing so greatly now that the leader today can be a nobody five years from now, right? So, what I tell my team every day is how are we going to disrupt ourselves before we get disrupted so that we can still be the leader five years from now when that exponential growth has continued, right? So that's what we do every day. We think about what are the ways, on behalf of the customer, the world of unstructured storage is being disrupted and how are we going to be there on the other side with the customer? >> Manuvir, I'm wondering if you could bring us inside the customers 'cuz we've been talking about unstructured data at least five years. Data data everywhere, but how is it changing customers' lives? How is it changing their businesses? What's the update on the customer's viewpoint on unstructured data? >> So, we have an interesting perspective because our business really grew up with working with specific verticals. Like media, entertainment, life sciences, automotive, and we see that there. For example, in the automotive industry, we have a lot of customers that are doing Adax and so they're basically driving vehicles around, capturing videos of a child running across the street, of a bicycle on the road, and they're bringing all that data back to our storage system so that they can train their software that runs the car, so that when the situation happens in real life, the software does the right thing, right? In media entertainment now, with 4K streaming and more and more digitized movies, how do you produce these movies, right? How does Pixar and everybody produce these movies? In life sciences, it's all about Genomix. It's started in the research domain with Genomix, and now it's going into hospitals where people want to use Genomix to make real-time decisions about what to do for their patients. And these are all ways in which these existing industries are really using unstructured data now as their lifeblood to change their business. So, it's an interesting change, really. >> You mentioned five years from now, we want to make sure that we're the disruptor, and I read a number that by five years out, all data or unstructured data, will be 93% of all data, So that kind of growth when you see that mushroom occurring, does that put a little fear, does that put the challenge? >> It's a great opportunity, right? It's a great opportunity, and it's an opportunity not just for us at Dell EMC, right? It's an opportunity for everybody. The public cloud vendors, start-ups, and our only interest is, let's take the customer to the right place, and if we can participate in that in some way, I believe there are opportunities so big, that we will be happy with whatever share of it we have. As long as the customer gets what they need. And I think every customer's going to have some mix of On-Premises storage, appliances, software defined storage, storage in the public cloud. It'll all sort of come together and I think we have a role to play, right? If I may, there's really four things we see about how the data is changing say from now to five years from now. The first thing is Flash, right? Flash is no longer just for high-end storage. Flash is everywhere in storage. The second thing is the public cloud. More and more data going into the public cloud. The fourth thing is analytics. Who is going to pay to store all of this data unless they can actually put it to use, right? And so, how do you provide the analytics? And then the fourth thing is archiving because the truth of the matter is, when you expand your data at that scale, most of the data is not useful at any point in time. It may be useful tomorrow, but it's not useful today. So how do you use technologies like optic storage to really economically store the bulk of the data? So these are the four trends we see, flash, the public cloud, analytics, and advent of object, and everything we're doing at Dell EMC with unstructured storage, is to embrace these four trends. So that we can come out the other side with the customer on these. >> There was one thing that caught my ear during the keynote this morning, there were many things that stood out, but one of them I could have sworn Michael said something about Isilon. We've googled cloud, and I'm googling, I'm looking around, obviously object storage, I think very much in the public crowd, seeing growth elsewhere, but maybe you can explain what that is and what's going on. >> So this is an Isilon file storage, is now available for customer's of Google in the Google Cloud. So, for years our customers have used Isilon On-Premise because it's really the only solution in the market where you can get a very large file system that performs well. You don't have this technology in the public cloud today. And, we have all these customers who run their workloads on prem using Isilon. And they're looking to use the computer in the public cloud, but if they don't have Isilon there, they would have to re-write their application. So, we worked out a model with Google where we host our Isilon gear, our physical Isilon clusters in the same place where Google has their cloud, and their compute, so now a customer can run their application, on the compute VMs of Google cloud, but they have some millisecond access to an Isilon cluster that is dedicated to them that is right there. So in this way, they can take the journey to the public cloud, but not have to change their application because they still use Isilon. So, this is the model we came up with. We just launched it, so that's what Michael was referring to. We're very excited about it. I think it's really an opportunity for the customer to embrace the cloud, and the thing I'm trying to tell every customer that we have because we've been on premises for a long time, is "Look, I believe in the public cloud." I actually worked on building one of those at Microsoft years ago, and all we want is, we want to help the customers get to the public cloud by giving them the same technology there, that they've had On-Premise. And, so I think everybody wins. >> Yeah, that's exciting. Thank you so much for going through that. Your team, it's up there in Seattle, so much going on. Have there been customers on beta on this? Is this available now? Give some of the speeds and feeds. >> So, in the cloud terminology, people usually start with a what they call a tech preview or an early adoptive program, so that's where we're at right now. We have the first customer already running operational on it, and they will talking about it in some of our breakout sessions as well, so we're in the early the adoptive program right now, so anybody's that's interested can join the early adoptive program. It's fully operational, but we're sort of controlling how many customers adopt it first, and then we expand from there. >> Look at the, if you would, the risk side of this, with all that data, it's a treasure trove in some respects to a company, but it's also a very alluring target. So from a security standpoint, what kind of emphasis are you shifting towards that, knowing that you have that much more waterfront to cover now? >> I think it is the key issue really, and so that's why, even John in this move to the public cloud, that we just talked about, we have not done this as some kind of multi-tenant, shared kind of environment. Every customer has a dedicated environment, their Isilon is in a cage, everybody can't get into that cage, and all the security protocols are in place. So that's a very important aspect of this. And then whether it's in the cloud or On-Premise, they're constantly raising the bar on the security protections. How does the data flow internally between the servers in the cluster? Everything's encrypted, authenticated, protected, so I think that is really the key issue going forward. Well, I know it's a challenge, but as you said, it's also an opportunity. So, good luck meeting the challenge, and I hope five years from now, we're still talking about you. >> Yes, we'll see where we are. >> Hey, how do you like the music, by the way? >> Uh, it's great. >> It's a little loud. >> That's right, a little loud. >> Manuvir, thanks for being with us. >> Sure my pleasure. >> We'll continue from a floor that's starting to get a little more energy to it. Here live at the Sands, we are at Dell Technologies World 2018.

>> Announcer: Live From Las Vegas, it's The Cube, covering Dell EMC World 2017. Brought to you by Dell EMC. >> Hey, welcome back everyone. We're here live in Las Vegas for Dell EMC World 2017. This is The Cube, I'm John Furrier with my co-host, Paul Gillin. And our next guest Manuvir Das, Senior Vice President of Product Management, Dell EMC, former Microsoft Asure, historic role at Microsoft, been at the EMC for a few years. Welcome to The Cube, good to see you. >> Thank you, it's nice to be here. >> So the last year we had a conversation. We were talking about some of the technology and the kind of direction it was going, so first question is from last year to this year, what's changed and what's the news? >> We've brought together two pretty well-known platforms that we did, Isilon for Scalar file and ECS for Scalar object. It one team that are now around called the Unstructured Data Storage Team. And we've done this really big because from the point of view of the customer, what we see is this confluence between file and object really in the space of unstructured storage, and we think we have some ideas of how to put that together in just the right solution for the customer. So that's why we brought these teams together and we've got a lot of great stuff to talk about this year. >> How are you positioning file versus object right now? It seems like object is the rage, but file is still going to be around for a long time. How do you position that? >> Yes, I think it will be. I think basically, if I may, it's not just two, but we see three pillars of unstructured storage. The first is file, which is really more towards compatibility with traditional workloads. A lot of the application ecosystem is comfortable programming against NFS or SMB, and that ecosystem is going to remain for a long time. For instance, in the space-like video surveillance. So that's where we see file. It's optimized more for performance rather than Scale, although you do get Scale. The next level was really object, which is more for your modern workloads, for your web and mobile sort of workloads. Optimized more for Scale rather than performance. And then, the third pillar that we see that we'd be working on now is really realtime data, or what you call streaming data, from things like IOT, where you're getting a firehose of information coming out and you got to store it very, very quickly. So we see these are three different pillars of unstructured storage. And really, what we've been working on in our Unstructured Data Storage Team is how to bring all of these three together in the right solution for the customer. >> So tell us about the group that you're in because this is kind of a new, not new industry, we're talking about unstructured data for many years, going on eight years, but it's becoming super important now as you have this horizontal data fabric development. We talked a little bit about it last year, but you can see a clear line of sight now with apps using data very dynamically. So you need under-the-hood storage, but now you need addressability of data. And so, there's a challenge of getting the right data from the right database to the right place on the app in less than a hundred milliseconds. I mean, that's like the nirvana. >> So I think there's a couple of things happening. Firstly, the advances in hardware have changed the game a fair bit, because you can take a software stack that was not optimized for latency to begin with, you can put it on all Flash hardware and you can reduce the roundtrip a lot, that's one thing. The other thing I see is that especially with the advancement of object >> For the stage of life in IT, you have research background, PhD in Computer Science, I mean, it's a pretty awesome time to be in computer science right now. There's a ton of opportunity that applies from that. Machine learning, all this goodness there. What's your vision of how the next 30 years are going to play out? Because Michael Dell said, "Hey, it's been 33 years," since he's started the company, the next 33 are going to be amazing, and I believe that to be true as well given the science opportunities. How do you look at this, from a personal level and also from a Dell EMC? >> I think what's really going to change is, up 'til now, a lot of things that have been done with computing have started with the thought of, "How much data can I really have?" And then, once I've decided how much data I can really have, what am I going to do with it? And I think sort of the innovation that's happened in storage that I'm a part of, what has really changed is it said, "You don't have to stop and think "about how much data you're going to have." You can just keep all of it. And so, what that means is I don't have to figure out upfront what I'm going to do with this data. I'm just going to bring it all in, it's going to be really cheap, the systems are really scalable that can hold it, and everything is sort of tagged in such a way that after the fact, five years from now, I can go do something with this data that I hadn't envisioned when I brought it in. And I think that just opens up a range of things that were hard to imagine. The other thing I think is, >> Programmatically meaning, from a software standpoint. Discoverability, >> That's right, I think as you said, machine learning is a big part of it. Because I think machine learning unlocks opportunities to mind the data that people hadn't really thought of before. And it comes back to the same thing that when I bring data in, whether it's from sensors or aircraft engines or what have you, I have no idea what I'm going to do with the data, so I have no idea which part of the data is important and which part of the data is less important. But when I can apply things like machine learning after the fact, I don't actually have to worry about that. I just bring it all in, and the algorithms themselves will figure out which part of the data is the useful part of the data. >> Your ScaleUp product line and ScaleOut product line, how are you positioning those two application-wise to your customers? >> So I think there is distinction between tier one storage and tier two storage. I think when you think about tier one storage, it's not just about the numbers, like latency and IOPS, but it's about the whole experience of tier one storage. Do I have, for my disaster recovery, do I have RPO-0, which means I can recover to the exact point in time I was at when I failed over data center. How does my replication work, what data services that I have? So I think our ScaleUp technologies are very well oriented towards the tier one kind of capabilities. And then our ScaleOut technologies are very well oriented towards sort of the ubiquitous tier two storage, which is much more deployable at Scale. It's pretty good performance in two, actually, but not with that complete set of capabilities you think about with tier one in terms of RPO-0s, synchronist replication, those kinds of things. So I think there's a very natural sort of mace between the two. And really, I think from a storage vision, what we see is the tier two storage is so scalable and so cheap, that all of your bools of tier one storage on the top tier down automatically into the tier two storage. And what that means is for our customers, if you think about how much tier one storage they have to provision today, they should be able to provision less of that, because they should be able to tier more of that down to the tier two storage, which is now capable enough to hold the rest of the data. >> And be available. >> And be available, >> Okay so, customers want to do this, a no brainer. So when we hear Amazon talk about this all the time, Jeff Bezos was just talking about just the other day a new chassis, they've got the recognition software so you see facial recognition, a lot of great stuff happening all over the Cloud world with this kind of modeling, with the power of computes that's available. What are the customers do now? Because now they get it, it's a no brainer obviously. Now they've got to change how they did IT 30 years to be agile for tomorrow. What's the playbook? >> So what we're seeing is, the step one that we're seeing more and more today, and have seen really for the last couple of years with Isilon and with DCS, is what I would call Consolidation of the Tier Two. So where we had 12 different clustered silos of storage for the different use cases, let's buy into this model that I can just build one large storage cluster, and it can handle the 12 different use cases at the same time. And that's what we've been proving out for the last few years. I think customers have really, enterprise customers are really getting there. And now, what we're beginning to see this year is the next phase, whether it's the industrial internet with the automotives, et cetera, the more IOT style use cases. In fact, on Wednesday, we'll be talking about a new thing we've got called Project Nautilus, which is the third leg of our stool with the streaming storage that is built on top of Isilon and ECS. And we're now at the point where are first customers are beginning to work with that, where they're saying, "From my sensors, "in the automobiles, on the cameras, "I'm going to bring in this firehouse of data, "I'm going to store it all with you, "but later on, I'm going to do analytics on it. "As it's coming in, I'm going to do "some real-time analytics on it, "and then after the fact, I'm going to do "the more batch style." >> I know Paul Scott wants to jump in, but I want you to just back up because I missed the three pillars. >> The three pillars were file, for which we have Isilon, object for your modern applications and web workloads, for which we have ECS, and then streaming storage for IOT. >> Which is Nautilus? >> Which is Project Nautilus, >> Okay, got it. >> The way I put it to people is traditional storage systems, ScaleUp or ScaleOut, file or object, they need resilience. So when you write the data, you have to write and think at the same time, because you have to record all kinds of information about it, you have to take locks, et cetera. For IOT, you need a storage system that writes now, and thinks later, so that you can just suck it all in. >> It sounds like an operating system. You've got a storage that's turning into like LUNs, provisioning, hardware. It's essentially intelligence software that has to compile, runtime, assembly, all this stuff's going on. >> And there's all these fancy names like LAN Architecture and all that kind of stuff. And what that's all saying is, "I bring the data in "and as it's coming in, "there's some things I already want to do with it, "I do that analytics in real-time. "There's other things when I go tag it, "who was in the photo, where was it, "and then the rest of it, I'm going to do later." And who knows what and when, and that's a beautiful thing. >> You're way along the thinking curve on this obviously, but where are your customers? I mean, you're talking about a pretty radically, different approach to processing and storing data even in realtime. Machine learning, meta tagging, there's a lot for them to absorb. >> And I think that part, it's a vertical driven, use-case driven thing. So there's some industries where we see a lot of uptake on that. Automotive is a great example. >> Financial services, >> Financial services, fraud detection, those kinds of things. And there's other verticals where it's not time for that yet. Like I said, healthcare is a great example. So in those verticals, we see more of just the storage consolidation, let me build one pool of tier two storage, if you will, and consolidate my 12 use cases sort of what we refer to as the Data Lake in our words, but I think it's specific verticals. And that's fine, if you look at even the traditional unstructured storage, I think it really started with certain verticals like media and entertainment, life sciences, and that's sort of where it kicked up from. And I think for the streaming storage, it's these verticals that are more oriented towards IOT, your automotive, your fraud detection, those kinds of things where it's really kicking off, and then it'll sort of broaden from there. >> How is this playing into the Dell server strategy? >> It's really a fantastic thing, I don't want to say so much for us as for our customer, because I've talked to a number of people in these verticals where the customer wants a complete solution for IOT. And what that means is number one: on the edge, do I have the right equipment with the right horsepower and the right software on the edge to bring in all the data from the edge and do the part of the processing that needs to be done right there on the edge of realtime, and then it has to be backed by stuff in the backing environment that can process massive amounts of data. And with Dell, we have the opportunity for the first time that we didn't have with the EMC alone to do the complete solution on both ends of it, both the equipment on the edge as well as the backing IT, so I think it's a great opportunity. >> You bring up so many awesome conversations because it's boring storage, now storage is not boring anymore because it's fundamental to the heartbeat of a company. >> Exactly. >> So here's a question for you, kind of like thinking out loud and riffing with you. So some debate, like, "Listen, I want to find "the needle in the haystacks, "but the haystacks are getting bigger," so there's a problem with that. I got to do more design and more gig digging, if you will. And the second point is customers are saying, to at least to us on The Cube and privately is, "I got a data lake that's turning "into a data swamp, "so help me not have swamps of data, "and I want more needles, "but the stack's getting bigger." What's your advice to those CXOs? Could be a CDO, chief data officer, a CS CISCO, these are the fundamental questions. >> I would say this, whatever technology you're evaluating, whether it's an on-premise technology or a hosted technology from a vendor like us, or it's a service out there in the Public Cloud, if you will, ask yourself two questions. One is, "If I size out what I need right now, "and I multiply it by 10 or 100, "what is it going to cost? "And is it really going to work the same way, "is it going to scale the same way?" Look at the algorithmics inside the product, not the Power Point and say, "The way "they've designed this thing, "when I put 100 times the data "on 100 times the number of servers "on this storage system, "are things actually going to work the same way or not?" >> So it's a scale question, kind of what are the magnitude thinking you need to kind of go out and size it up a bit. >> Because I see right now, the landscape is full of new technologies for storage, and a lot of them sound great and look great on the PowerPoint, and you go do a POC with four nodes or eight nodes, and you put Flash in there and it works really well. But the thing is, when you have 200 nodes of that, when you've got a 30 petabyte cluster and you've got to fail it over because your data center went down, how does that go? >> Well, it's also who's going to run it, too. You want less obstacles, not more, and you don't them to be huge, expensive developers. >> TierPoint, that's the other thing. We really don't talk to our customers in terms of storage acquisition costs anymore, we talk in terms TCO, total cost of ownership. You look at power, you look at cooling. >> That killed the Duke, basically, it was so hard to run and total cost of of ownership. Michael Dell was just on, I was interviewing Michael and I asked him like, "Where's the Cloud strategy?" I was just busting his chops a little bit, 'cause I know he's messaging, trying to get him off his messaging. But he made an interesting comment and metaphor. He goes, "Well John, I remember the days "during the internet days, where's you internet strategy?" Look where that happened, the bubble popped. But ultimately, everything played out as according to plan. There's pet food online, now we've got food delivery, DoorDash, all this stuff's happening. So he kind of was using it to compare to the Cloud today. There's a lot of hope and promise, where's your Cloud strategy? But yet, his point was it's going to be everywhere. >> Yeah, and I would say this, I think people sometimes confuse Cloud with Public Cloud. And I think what happened is, having that issue myself, I would say that Public Cloud exposed a certain model that had some benefits for the customer base that were new. That is, I can use as a service, I don't worry about operationalizing things, I can pay as I go, so I get that, it's elastic. But it also came with a lot of drawbacks. I don't have the kind of control that I would like to have. A normal thing that any person who takes a dependency on infrastructure has is, "Today's my Superbowl Sunday. "Don't touch my environment today." Now you go to a Public Cloud and you use a service that is used by thousands of other customers, so which day is Superbowl Sunday? Every day is Superbowl Sunday for somebody. >> It was a metaphor, Public cloud was a metaphor for virtualization that would effect the entire environment. >> And so, I think the journey we're all in, all the vendors, the Public Cloud suppliers, everybody is, "What are the right set of models "that are going to cover the space for all our customers?" There's not going to be one. There's several. I think the dedicated private Cloud models are certainly very appealing in a number of ways if you do the economics right. And I think that's the journey we're all on sort of together. >> I tweeted a little bit of the jewels out there this morning. True, Private cloud is going to be a $265 billion dollar market, but they were the first ones to actually size that, let's say true private public means essentially hybrid, but on-prem with a data center. That's huge numbers, it's not like rounding errors. >> We believe that, too. And that's why one of the neatest things we've announced this year with ECS object storage is something called ECS Dedicated Cloud, which is basically saying, "You can take the object storage "from us, but it's going to run in our data centers." We operate it, it's actually the developers who wrote the code from my team who are actually operating it, and you can do a variety of hybrid things. You can keep some of it on-prem, some of it off-prem, you can keep all of it off-prem. But regardless, it's your stuff. You can hug it, it's dedicated to you. You're not sharing the cluster with anybody else. You get to decided when you update your version, when you take a maintenance window or what have you. So, we're all searching for that sweet spot, if you will. >> I want to ask you about something, some of the different containers. The hottest thing right now in infrastructure, lack of persistent storage has been a real problem for containers. Is that a problem that's yours to solve or is it Docker's to solve? >> No, I think it is ours to solve with them. So, I'll say a couple of things. Firstly, our modern products, ECS and object storage as well as ScaleIO, our block ScaleOut storage, these are built with containers. So for instance, if you take ECS today, every ECS appliance that we ship, if you look inside very server, it's running Linux with Docker. And all the ECS code is running on Docker containers. That's just how it works. So A: we believe in containers, and two: I think we have been doing the work to provide that persistence ecosystem for containers using our storage. So we have a great team at Dell EMC called EMC Code. And these are people, they do a lot of this integration stuff, they work very closely with Docker and a number of the other frameworks to really plug our storage in. And I think it's a very open ecosystem. There are APIs there now, so you can plug anybody's storage in. And I think that's really if you compare VM-based infrastructures with container-based infrastructures. That's really the gap, because when you operationalize the stuff, you need things like that. You need persistent storage, you need snapshots, you need a VR-storage, you need those kinds of things, but I think that'll all come. >> Well, we're looking to continuing the conversation, I know time's tight. We'd like to follow up with you after the show, maybe bring you into our studio via Skype. You're in a hot area, you got the storage, you got the software, you got some Cloud action going on. Thank you very much for coming on The Cube, appreciate it. >> My pleasure for being here, thank you for having me. >> This is TheCube, live coverage here at Dell EMC World 2017. And I'm John Furrier with Paul Gillin, we'll be right back. Stay with us. (bright tech tones)

>> Okay. We want to pick up on a couple of themes that Mick discussed, you know, supercharging your business with AI, for example, and this notion of getting hybrid right. So right now we're going to turn the program over to Rob Bearden, the CEO of Cloudera and Manuvir Das who's the head of enterprise computing at NVIDIA. And before I hand it off to Rob, I just want to say for those of you who follow me at the Cube, we've extensively covered the transformation of the semiconductor industry. We are entering an entirely new era of computing in the enterprise and it's being driven by the emergence of data intensive applications and workloads. No longer will conventional methods of processing data suffice to handle this work. Rather, we need new thinking around architectures and ecosystems. And one of the keys to success in this new era is collaboration between software companies like Cloudera and semiconductor designers like NVIDIA. So let's learn more about this collaboration and what it means to your data business. Rob, take it away. >> Thanks Mick and Dave. That was a great conversation on how speed and agility is everything in a hyper competitive hybrid world. You touched on AI as essential to a data first strategy in accelerating the path to value and hybrid environments. And I want to drill down on this aspect. Today, every business is facing accelerating change. Everything from face-to-face meetings to buying groceries has gone digital. As a result, businesses are generating more data than ever. There are more digital transactions to track and monitor now. Every engagement with coworkers, customers and partners is virtual. From website metrics to customer service records and even onsite sensors. Enterprises are accumulating tremendous amounts of data and unlocking insights from it is key to our enterprises success. And with data flooding every enterprise, what should the businesses do? At Cloudera, we believe this onslaught of data offers an opportunity to make better business decisions faster and we want to make that easier for everyone, whether it's fraud detection, demand forecasting, preventative maintenance, or customer churn. Whether the goal is to save money or produce income, every day that companies don't gain deep insight from their data is money they've lost. And the reason we're talking about speed and why speed is everything in a hybrid world and in a hyper competitive climate, is that the faster we get insights from all of our data, the faster we grow and the more competitive we are. So those faster insights are also combined with the scalability and cost benefit that cloud provides. And with security and edge to AI data intimacy, that's why the partnership between Cloudera and NVIDIA together means so much. And it starts with a shared vision, making data-driven decision-making a reality for every business. And our customers will now be able to leverage virtually unlimited quantities and varieties of data to power an order of magnitude faster decision-making. And together we turbo charged the enterprise data cloud to enable our customers to work faster and better, and to make integration of AI approaches a reality for companies of all sizes in the cloud. We're joined today by NVIDIA's Manduvir Das, and to talk more about how our technologies will deliver the speed companies need for innovation in our hyper competitive environment. Okay, Manuvir, thank you for joining us. Over to you now. >> Thank you Rob, for having me. It's a pleasure to be here on behalf of NVIDIA. We're so excited about this partnership with Cloudera. You know, when, when NVIDIA started many years ago, we started as a chip company focused on graphics. But as you know, over the last decade, we've really become a full stack, accelerated computing company where we've been using the power of GPU hardware and software to accelerate a variety of workloads, AI being a prime example. And when we think about Cloudera, and your company, your great company, there's three things we see Rob. The first one is that for the companies that were already transforming themselves by the use of data, Cloudera has been a trusted partner for them. The second thing we've seen is that when it comes to using your data, you want to use it in a variety of ways with a powerful platform, which of course you have built over time. And finally, as we've heard already, you believe in the power of hybrid, that data exists in different places and the compute needs to follow the data. Now, if you think about NVIDIA's mission going forward to democratize accelerated computing for all companies, our mission actually aligns very well with exactly those three things. Firstly, you know, we've really worked with a variety of companies to date who have been the early adopters using the power acceleration by changing their technology and their stacks. But more and more we see the opportunity of meeting customers where they are with tools that they're familiar with, with partners that they trust. And of course, Cloudera being a great example of that. The second part of NVIDIA's mission is we focused a lot in the beginning on deep learning where the power of GPU is really shown through. But as we've gone forward, we found that GPU's can accelerate a variety of different workloads from machine learning to inference. And so again, the power of your platform is very appealing. And finally, we know that AI is all about data, more and more data. We believe very strongly in the idea that customers put their data, where they need to put it. And the compute, the AI compute, the machine learning compute, needs to meet the customer where their data is. And so that matches really well with your philosophy, right? And, and Rob, that's why we were so excited to do this partnership with you. It's come to fruition. We have a great combined stack now for the customer and we already see people using it. I think the IRS is a fantastic example where, literally, they took the workflow they had, they took the servers they had, they added GPUs into those servers. They did not change anything. And they got an eight times performance improvement for their fraud detection workflows, right? And that's the kind of success we're looking forward to with all customers. So the team has actually put together a great video to show us what the IRS is doing with this technology. Let's take a look. >> How you doing? My name's Joe Ansaldi. I'm the branch chief of the technical branch in RAS. It's actually the research division, research and statistical division of the IRS. Basically, the mission that RAS has is we do statistical and research on all things related to taxes, compliance issues, fraud issues, you know, anything that you can think of basically, we do research on that. We're running into issues now that we have a lot of ideas to actually do data mining on our big troves of data, but we don't necessarily have the infrastructure or horsepower to do it. So our biggest challenge is definitely the, the infrastructure to support all the ideas that the subject matter experts are coming up with in terms of all the algorithms they would like to create. And the diving deeper within the algorithm space, the actual training of those algorithms, the number of parameters each of those algorithms have. So that's, that's really been our challenge now. The expectation was that with NVIDIA and Cloudera's help and with the cluster, we actually build out to test this on the actual fraud detection algorithm. Our expectation was we were definitely going to see some speed up in computational processing times. And just to give you context, the size of the data set that we were, the SME was actually working her algorithm against was around four terabytes. If I recall correctly, we had a 22 to 48 times speed up after we started tweaking the original algorithm. My expectations, quite honestly, in that sphere, in terms of the timeframe to get results, was it that you guys actually exceeded them. It was really, really quick. The definite now term, short term, what's next is going to be the subject matter expert is actually going to take our algorithm run with that. So that's definitely the now term thing we want to do. Going down, go looking forward, maybe out a couple of months, we're also looking at procuring some A-100 cards to actually test those out. As you guys can guess, our datasets are just getting bigger and bigger and bigger, and it demands to actually do something when we get more value added out of those data sets is just putting more and more demands on our infrastructure. So, you know, with the pilot, now we have an idea with the infrastructure, the infrastructure we need going forward and then also just our in terms of thinking of the algorithms and how we can approach these problems to actually code out solutions to them. Now we're kind of like the shackles are off and we can just run a, you know, run to our heart's desire, wherever our imaginations takes our SMEs to actually develop solutions. Now have the platforms to run them on. Just kind of to close out, we really would be remiss, I've worked with a lot of companies through the year and most of them been spectacular. And you guys are definitely in that category, the whole partnership, as I said, a little bit early, it was really, really well, very responsive. I would be remiss if I didn't thank you guys. So thank you for the opportunity. Doing fantastic. and I'd have to also, I want to thank my guys. my staff, Raul, David worked on this, Richie worked on this, Lex and Tony just, they did a fantastic job and I want to publicly thank them for all the work they did with you guys and Chev, obviously also is fantastic. So thank you everyone. >> Okay. That's a real great example of speed and action. Now let's get into some follow up questions guys, if I may, Rob, can you talk about the specific nature of the relationship between Cloudera and NVIDIA? Is it primarily go to market or are you doing engineering work? What's the story there? >> It's really both. It's both go to market and engineering The engineering focus is to optimize and take advantage of NVIDIA's platform to drive better price performance, lower cost, faster speeds, and better support for today's emerging data intensive applications. So it's really both. >> Great. Thank you. Manuvir, maybe you could talk a little bit more about why can't we just use existing general purpose platforms that are, that are running all this ERP and CRM and HCM and you know, all the, all the Microsoft apps that are out there. What, what do NVIDIA and Cloudera bring to the table that goes beyond the conventional systems that we've known for many years? >> Yeah. I think Dave, as we've talked about the asset that the customer has is really the data, right? And the same data can be utilized in many different ways. Some machine learning, some AI, some traditional data analytics. So, the first step here was really to take a general platform for data processing, Cloudera data platform, and integrate with that. Now NVIDIA has a software stack called rapids, which has all of the primitives that make different kinds of data processing go fast on GPU's. And so the integration here has really been taking rapids and integrating it into a Cloudera data platform so that regardless of the technique the customer is using to get insight from the data, the acceleration will apply in all cases. And that's why it was important to start with a platform like Cloudera rather than a specific application. >> So, I think this is really important because if you think about, you know, the software defined data center brought in, you know, some great efficiencies, but at the same time, a lot of the compute power is now going towards doing things like networking and storage and security offloads. So the good news, the reason this is important is because when you think about these data intensive workloads, we can now put more processing power to work for those, you know, AI intensive things. And so that's what I want to talk about a little bit, maybe a question for both of you, maybe Rob, you could start. You think about AI that's done today in the enterprise. A lot of it is modeling in the cloud, but when we look at a lot of the exciting use cases, bringing real-time systems together, transaction systems and analytics systems, and real-time AI inference, at least even at the edge, huge potential for business value. In a consumer, you're seeing a lot of applications with AI biometrics and voice recognition and autonomous vehicles and the liking. So you're putting AI into these data intensive apps within the enterprise. The potential there is enormous. So what can we learn from sort of where we've come from, maybe these consumer examples and Rob, how are you thinking about enterprise AI in the coming years? >> Yeah, you're right. The opportunity is huge here, but you know, 90% of the cost of AI applications is the inference. And it's been a blocker in terms of adoption because it's just been too expensive and difficult from a performance standpoint. And new platforms like these being developed by Cloudera and NVIDIA will dramatically lower the cost of enabling this type of workload to be done. And what we're going to see the most improvements will be in the speed and accuracy for existing enterprise AI apps like fraud detection, recommendation engine, supply chain management, drug province. And increasingly the consumer led technologies will be bleeding into the enterprise in the form of autonomous factory operations. An example of that would be robots. That AR, VR and manufacturing so driving better quality. The power grid management, automated retail, IOT, you know, the intelligent call centers, all of these will be powered by AI, but really the list of potential use cases now are going to be virtually endless. >> I mean, Manufir, this is like your wheelhouse. Maybe you could add something to that. >> Yeah. I mean, I agree with Rob. I mean he listed some really good use cases, you know, The way we see this at NVIDIA, this journey is in three phases or three steps, right? The first phase was for the early adopters. You know, the builders who assembled use cases, particular use cases like a chat bot from the ground up with the hardware and the software. Almost like going to your local hardware store and buying piece parts and constructing a table yourself right now. Now, I think we are in the first phase of the democratization. For example, the work we do with Cloudera, which is for a broader base of customers, still building for a particular use case, but starting from a much higher baseline. So think about, for example, going to Ikea now and buying a table in a box, right. And you still come home and assemble it, but all the parts are there, the instructions are there, there's a recipe you just follow and it's easy to do, right? So that's sort of the phase we're in now. And then going forward, the opportunity we really look forward to for the democratization, you talked about applications like CRM, et cetera. I think the next wave of democratization is when customers just adopt and deploy the next version of an application they already have. And what's happening is that under the covers, the application is infused by AI and it's become more intelligent because of AI and the customer just thinks they went to the store and bought a table and it showed up and somebody placed it in the right spot. Right? And they didn't really have to learn how to do AI. So these are the phases. And I think we're very excited to be going there. >> You know, Rob, the great thing about, for your customers is they don't have to build out the AI. They can, they can buy it. And just in thinking about this, it seems like there are a lot of really great and even sometimes narrow use cases. So I want to ask you, you know, staying with AI for a minute, one of the frustrations, and Mick I talked about this, the GIGO problem that we've all, you know, studied in college, you know, garbage in, garbage out. But, but the frustrations that users have had is really getting fast access to quality data that they can use to drive business results. So do you see, and how do you see AI maybe changing the game in that regard, Rob, over the next several years? >> So yeah, the combination of massive amounts of data that had been gathered across the enterprise in the past 10 years with an open APIs are dramatically lowering the processing costs that perform at much greater speed and efficiency. And that's allowing us as an industry to democratize the data access while at the same time delivering the federated governance and security models. And hybrid technologies are playing a key role in making this a reality and enabling data access to be quote, hybridized, meaning access and treated in a substantially similar way, irrespective of the physical location of where that data actually resides. >> And that's great. That is really the value layer that you guys are building out on top of all this great infrastructure that the hyperscalers have have given us. You know, a hundred billion dollars a year that you can build value on top of, for your customers. Last question, and maybe Rob, you could, you could go first and then Manuvir, you could bring us home. Where do you guys want to see the relationship go between Cloudera and NVIDIA? In other words, how should we as outside observers be, be thinking about and measuring your project, specifically in the industry's progress generally? >> Yes. I think we're very aligned on this and for Cloudera, it's all about helping companies move forward, leverage every bit of their data and all the places that it may be hosted and partnering with our customers, working closely with our technology ecosystem of partners, means innovation in every industry and that's inspiring for us. And that's what keeps us moving forward. >> Yeah and I agree with Rob and for us at NVIDIA, you know, we, this partnership started with data analytics. As you know, Spark is a very powerful technology for data analytics. People who use Spark rely on Cloudera for that. And the first thing we did together was to really accelerate Spark in a seamless manner. But we're accelerating machine learning. We're accelerating artificial intelligence together. And I think for NVIDIA it's about democratization. We've seen what machine learning and AI have done for the early adopters and help them make their businesses, their products, their customer experience better. And we'd like every company to have the same opportunity.

>> Live from Las Vegas, it's theCUBE, covering Dell Technologies World 2018. Brought to you by Dell EMC and its Ecosystem partners. >> Welcome back to day three of Dell Technologies World, the inaugural Dell Technologies World. My name is Dave Vellante and you're watching theCUBE, the leader in live tech coverage. This is our kickoff of day three, we got a little analyst roundtable, Keith Townsend is with me, Stu Miniman, Peter Burris, the co-host, tri-hosts, quad-hosts of this show, long-time Dell EMC watchers and guys, let's unpack what's going on here. We're a couple years in now, the merger between Dell and EMC. I've said all along this was inevitable because of the pressures of cloud. It's very clear that Michael Dell is taking control of this company, it's the Dell brand, Dell Technologies, Dell Technologies World, EMC is sort of fading into the past, we'll talk about that Stu, we'll talk about the culture and the implications there, but I want to start with you Keith, let's talk about the customer perspective. What are you hearing from customers? What are the challenges that they're facing? Some of the concerns they may have with Dell and some of the positives? >> So one of the challenges, customers were worried that Dell EMC, Dell Technologies, would just be another HPE too big to solve their challenges, just how do you find solutions in the company with such a large portfolio? In reality, customers are pleasantly surprised that Dell Technologies has been able to surface up solutions, and not just focus on solutions, and also partner with their existing ecosystem of vendors, which is a surprise. One of the things I challenged Michael on as a customer, was hey you know what, this deal with Nutanix, this deal with XE, what are you leaning with from a hyperconverged solution perspective? Dell has been able to walk that line extremely well, We had a Datrium customer on day one, couldn't be happier with the relationship, then we talked to a couple of folks from the product team, 62% of the client meetings this week has been about VxRail, VxRack. Talked to another Fortune 500 customer that's all in on VxRail VxRack, not just for standard workloads, for SAP HANA which is not even certified for VxRail VxRack, so customers really happy with the overall ability of Dell to bring solutions to the table. I've seen, though we still have some time to tell if they'll be able to keep that momentum as they grow, as they continue to partner, and if they can continue to find solutions to challenges. >> Keith, if I can actually just follow up on one thing there, it's very clear that Dell will streamline the portfolio. Had Michael Dell, Jeff Clark, people from the marketing organization said absolutely, and we're telegraphing to customers as soon as we've sorted everything out we're gonna communicate it. Is there any concern from the customers? Michael said, we won't leave any customer behind, but absolutely the past of what EMC had with so many storage products they couldn't figure it out, there will be a lot less of them by the time we get to next year. >> So I think one of the things that you hit on when you talk about culture, I think customers still are very happy with the EMC brand, I think Dell did a really great job of not just getting rid of the EMC brand, customers still very much trust EMC. EMC had an extremely capable support organization, there's question about whether that support, that white glove support that we've gotten in the past from EMC will exist going forward. You know, Dell got rid of EMC cold, they brought Scale IO to a hardware-only solution versus the open ecosystem, so there's questions around where the cost-cutting will impact customer operations and support, but overall customers are happy with the progression. >> Peter Burris, one of the questions that Stu asked both Michael Dell and Clark yesterday is look you've got some of your bigger hardware competitors like IBM, like HP and HPE running away from head-to-head and I think Jeff Clark said "well I don't know how you can do end-to-end without both heads." So from your standpoint, from a customer perspective, is there an advantage to that head-to-head? We certainly heard it over the years, we used to hear it from HP a lot, we used to hear it from IBM a lot, they've retreated from that, Dell's sort of banging that end-to-end drum, does it matter from a customer perspective? >> Well of course, but it matters not just for what the customer wants but also the applications required. So, look, the biggest challenge, the most obvious, best end-to-end solution, if you take a very narrow view, it's gonna be AWS, Azure, some of these others. But the question is, is all of your data going to be in that public cloud? So the fundamental engineering challenge that every enterprise is gonna have is where am I gonna put my data? Some of the data is naturally gonna go to the public cloud, some of the data is not. What Dell needs to do over the course of the next couple of years is pick up on that as aggressively as they possibly can, try to not just convince people, but to show them that their organization of their digital business increasingly is going to be defined in terms of where their data assets are located, the practical realities of what that means, and therefore what types of fundamental support are they going to have to bring to bear on it? Keith, you said something interesting about HPE. The reason why Dell was not HPE, a little bit less so on IBM, is that Dell, Dell EMC have over the past 10, 15 years have made good bets, HP did not make good bets. You want to understand the history of HP over the last 10 years and why they're not the same, it's because HP gyrated all over the place to try to buy companies that were kind of at that moment a good price, let's just go for scale as best as we can, and Dell hasn't done that. Well Michael and his team have stayed relatively close to a simple vision of what types of engagement model they want, they've delivered on that vision, and they've got the assets that they can put into play now, but they just have to convince the enterprise that the play is where do you put your data, because you're gonna put your processing close to your data, and you're not gonna put it all in one place, right customer? And that's not going to be an easy, that's going to be a very challenging set of conversations over the next few years. We think how it's gonna play out is that Dell EMC is gonna be just fine because the enterprises are not gonna want to give all of their data up, and they can't give all their data up, so we'll see what happens. >> Well Stu let's talk about that, I mean Dell's cloud strategy is pretty clear, they want to be an arms dealer to the cloud. HPE, that's really their only choice, obviously IBM owns a cloud so it's a little different there, Oracle owns its own cloud, and they have software, that's a whole different ballgame. Dell clearly is comfortable being a high-volume, lower margin supplier, throwing off cashflow, throwing off profits. What's your take on the lack of a public cloud and are there issues there? >> Yeah, well you know Peter talked a little bit end-to-end and you see what Azure and AWS are doing. One of the surprising things for me is to see pieces of the public cloud and how the Dell Technologies portfolio are fitting into it. So being we're a native US, we absolutely understood. There's actually an isilon with Google cloud, a solution that I had an interesting discussion with Manuvir Das on day one here, really explained that you know scale out architecture, really get into the cloud. IBM cloud, there's a booth for them, they're here on the expo floor, so we've seen that maturation as hybrid cloud is not that transferring state that people thought but as that pits out we know data and applications are going to live lots of places and a company like Dell needs to be able to live in many of those environments. Edge of course, IOT, a hot issue that they're talking about, but they have portfolio products that will live in many of those places, so good maturation, public cloud is not enemy number one but of course they are a little bit more toward the private cloud, they highlight a bunch that if you go all in your prices are gonna be bad, we're gonna pull it back, Keith mentioned the EMC code team kind of got killed. A bunch of them are actually over at VMware now with an enhanced team, so it's still, we're not at the steady state of where the shift from my data center to public cloud is but it is definitely matured and nuanced and Dell has a lot of good partnerships that are growing. >> Well and selling servers to tier one cloud guys is not a great business, HP exited the business, Dell's in the business but it can't be a high market, it's not a great business I mean we know that. But, you know, nonetheless there's a lot of non-tier one clouds up there. You had a point to make, Pete? >> Yeah really quickly, the thing I was gonna say is, and we've talked about this in the past, and if we think about two things about Dell's portfolio, first off if we look back at what happened with the minicomputer business, and everybody says "oh the microprocessor killed it" well that probably contributed, but what really killed the minicomputer business was TCPIP and CISCO, that's what killed the minicomputer business because before a Dell or a Deck executive or a DG executive would walk into a shop with stuff all over the shop floor and the customer would say "I want to integrate this, you know, bridge it" and CISCO said, flatten the whole thing, bring TCPIP, and all those minicomputer companies went away. There is a gem in this portfolio which is NSX, and the degree to which Vmware, NSX can in fact become that technology for flattening the cloud network, cause that, to me, that's what the next big play in this industry is gonna be. AWS is gonna have its approach, Azure is gonna have its approach, you're gonna have bunch of on-premise stuff, the question is are you gonna be able to flatten those networks and really achieve that end-to-end? And if there's one good option on the table right now in the industry, it's VMware NSX for doing that. The second thing that I would say is, and I had a couple conversations with some folks about this this morning, we're talking about end-to-end, we're talking about greater conversions, hyperconversions, etc, yet Dell is still organized by server, storage, network, and it's going to be interesting to see how that evolves over the course of the next few years as customers increasingly do want a leverage that's end-to-end, diminish the distinctions and take advantage of convergence and whether or not we see Dell have a series of inter-nexian warfares about where that ends up. Because we know Dell does not wanna be RCA, right? >> Well that's really interesting because some of near-term moves that they've made are basically to take some of that converged stuff and put it in- >> That's right. So I love that now the TCPIP and NSX completely agree with you, the one thing that Dell is definitely missing from a customer perspective is the control plane glue they want to lead with the VMware story, you know any workload any cloud, I'm not gonna take my VMware approach to Google, I'm not gonna take that to Azure. So this any workload, any cloud thing, I'm not buying. I don't think customers are buying that. HPE is leading I think with a pretty good message on offering cloud services. It's a really, really difficult problem. >> The Oncenter story, you're talking about. >> The Onecenter story. It's a very difficult problem, enterprise customers want a single solution to consume all files, they want that TCPIP set of protocols, standards- >> They want the cloud to be flat. >> They want the cloud to be flat. NSX flattens it from a networking perspective but from a controlled plane API perspective the industry is a long way before that and I don't think Dell even has any plans for it. >> So, Stu, you know well when people were talking about you know, Michael's gonna sell VMware, you were very vocal about it, "no he's not, only an idiot would think that, I mean there's no way that's gonna happen." I mean, what a gem, in the portfolio, talk about end-to-end. The other thing I wanted to bring up is if you look at Dell's business, about half is the client business, it's doing better than expected so it's throwing off more cash than expected, especially with the storage business being soft, Dell's been pretty transparent about that, well I guess it has to be, but nonetheless there's upside there, but VMware is about 10% of the revenues, it throws off half of the operating cash, so why would you get rid of that, right? It's such a strategic asset 500,000 customers, a key part of the end-to-end, and it just makes this such a more interesting business. >> Yeah I mean Dave, I know you love teasing apart this complex, the tracking stock, all the things there, one of the interesting nuggets out of the Michael Dell interview was oh he said "the tax changes really had no impact, you know that's not it." You know, people really misunderstand, they understand these finances, it's not that they're hurting for cash, they can't make cash positions. >> So with my senses it's probably a slight negative but with the tax legislation, you're right, it's basically a net neutral for these guys. It's way overblown. >> Yeah, but you know, what's changed, we knew, when Dell went private, there were a bunch of changes in-company, I knew a lot of people that left the company for different things. The EMC acquisition, it's been a lot of change in the last 18 to 24 months, it'll still be rolling out there, you know, I live right in the heart of the old EMC country and there's some changes there, who's running it, you see a lot of former Dell executives, legacy Dell executives, there's still some strong people from the EMC side but Jeff Clark, very strong engineering culture, actually the more I've gotten to know him the more he reminds me of what EMC was 10 or 15 years ago in a good way, sharp, technical, getting on it. So I think the EMC brand, by the time we come here next year will be gone, but it doesn't mean the EMC people or products like the powermac are gonna be going anywhere. >> Well let me push at that a little bit, cause one of the things that Jeff Clark is doing is he's simplifying the portfolio, and Joe did the opposite, he complexified the portfolio because he said overlaps are better than gaps. And Jeff Clark's taking a different approach, is there a concern for customers? Wow, I might be left behind. They've got to be a little bit careful with that message, don't they? >> Yeah, but I mean we've touched on it a little bit, Dave, there's still some of the core product, you know powermac comes out there, this is the legacy of b macs, still supports the mainframe, you know, there's a business for this, and they're not gonna leave their customers behind. But what we said, Dave, when they put this portfolio together they need to turn the crank a little bit to get the operating margins where they need to be, not be overlapping so much with marketing and some of these other places. So, they're going to be very smart in how they do this, they say they're going to overcommunicate to not only their customers but their partner. I've talked to a bunch of (inaudible) partners, pretty happy. You know, there were a little bit of bumps over the last 18 to 24 months as to "oh wait I had this account rep and now they brought in this overlay and then they flopped who owned it." So it's been interesting to watch some of those and- >> Well look. >> It's a people business, and some of that changed- >> At the end of the day, Dell's portfolio can all be placed in service to the customer with relevance and competency today. That's a much better problem to have than a company that has either been building a bunch of stuff that's not gonna matter or has bought a bunch of stuff that's not gonna matter. It means if they can sustain a degree of focus that allows them to pay down their debt and do the financial engineering and Tom Sweet's a stud, the CFO's a stud, it means that they can listen to customers and continue to service what the customer needs because their portfolio is easily applied to customer problems unlike a lot of other companies. That's a pretty decent position. They can pursue all of these things because the portfolio is relevant. Now, are there gonna be some challenges? Well, one of the reasons why EMC complexified the portfolio was because they had salespeople who were deeply engaged in their accounts and they used that as an advantage, and so the salespeople said "I need something" and so Dell EMC, like CISCO did for years, went off, or EMC, went off and found it. Dell still has a different channel organization and a different channel approach, much more partnership-oriented, if there's tension in the model, I don't know what you think about this, Keith If there's tension in the model it's we're going through a major transformation in the industry right now. How close do you have to be to the customer, is this going to be a partner-led transformation or are you gonna want your people handling the transformation? EMC's approach was your people led the complex portfolio. Dell's approach, simplify the portfolio, are you making the relationships more complex as a result? >> That's a great point, we touched on this with Marius, because essentially, in Marius' organization you have an overlay EMC salesforce which is used to belly-to-belly, and he said "look we're working it out" and it requires great leadership. >> It's gotta be somewhere, is it gonna be in the portfolio or the engagement model? >> And from the engagement model, just look at the Dell Technologies family themselves. When I was a EMC VMware customer, I didn't have combined meetings with EMC and VMware, two belly-to-belly relationships. When that Dell EMC merger took place, Dell came in and flexed the muscle, you know desktops, laptops, end-to-end vision, VMware became, you know, you could sense the tension in the room. I just talked to another big Dell EMC VMware customer and they'll say you know what at VMworld, Dell Technologies World, the messaging here has been incredible. You get in the real world, you talk to your Dell Technologies or Dell EMC rep, one set of products, you talk to the VMware rep, a completely different set of products. >> And then you talk to partners, and what are they saying? So where's the complexity gonna be? EMC said the complexity's gonna be in the portfolio, the engagement model is gonna be simple. Dell's saying the portfolio is gonna be more simple, but what's gonna happen to the engagement model? Because customers, this transformation stuff we're talking about is hard. >> Let's break down, we've got a couple minutes left, let's break down the competitive landscape, the horses in the track as we like to say. We obviously got AWS, you know the megatrend factor sucking up a lot of demand. Everybody says that people are coming back on prem, more people are going to the cloud. 49% growth. So that's clear, but you got traditional server competitors which really is I guess HPE and Lenovo, right? We're gonna focus on the enterprise stuff because that's kind of our wheelhouse. You've got the storage guys, you know that app seems to be back, Pure is continuing to do its thing, small in the grand scheme of 80 billion dollars. >> Their best friend will be Nutanix. >> Right, yeah right, and you got that funky relationship, you got an interesting CISCO relationship going on, so how do you describe the competitive landscape? Start with you, Stu. >> Yeah, it's a little bit complicated. Listen to what Peter was saying there, EMC was pretty cut and dry, you know. Storage, that's where we're gonna live, and everything else, we're gonna partner, even all the server companies that need to sell storage, they have great partnerships with IBM and HP and everything like that with the first one you had to partner with EMC because they were dominant in that space. Dell at the core of it, server company still so it was interesting, one of the interviews I did, it was, you know, VxRail, if you're not in hyperconverted space, if you don't own the server, you're not in the right thing. And I'm like, we got Datrium and Nutanix and all these other partners that are here in the ecosystem that are living on top of the Dell platform, so there's a little bit of that give and take, it's more coopatition than I used to see, you used to go to Dell World, they'd have that rack of OEMs with all those different vessels out there, so you know, where does Dell want to go? How do they maximize, you know, the investment that they made in the biggest merger in tech history? So it's still playing out, I hear relatively good things from the partners, and the customers at least aren't getting stuck in the middle. You know, with CISCO sometimes it was really a punch in the face and if we're not 100% on board we're not gonna let you have it and then the channel would just sort it out themselves. >> I mean AWS and the cloud, it is what it is. The VMware partnership, you know good move, gives them some near-term maybe even mid-term runway, we'll see what happens long-term. In the server business it's HBE, right? Is the main competitor. What do you guys think? >> We got IBM. >> Yeah, IBM for sure, yeah. >> The powermacs that just got announced, when that comes out the second half of this year, that goes right after CISCO UCS. Not a lot of talk about CISCO, the VxBlock business is a three to four billion dollar business between the Dell family and the CISCO family and this is gonna put them at loggerheads really soon. >> Yeah I talked to customers, they love the Dell EMC certainly, powermacs has been one of the top conversations, they can't wait to connect their powermacs to their HPE blades, that's gonna be awesome. Which is good. The other piece of that is the NetApp story. NetApp did a great job of talking about data fabric and being a data copy, I don't know if they're there yet, did a great job talking about it. Dell EMC- >> Good investments, they hired great people, so they're on that path. >> Two men in my peer community, a man and woman said NetApp's cloud story is legit, they're good. >> They're a software company. >> They're a software company. Dell EMC's cloud story, specifically around storage, you know, the isilon announcement was a partnership but you know I think customers are really looking at that again, that API is about the data and how do I move my data on-prem, off-prem, I don't know if Dell EMC has their story yet and they have the product portfolio to back it. >> So, here's what I'd say Dave. At the end of the day, there's a whole bunch of transformations and I'll try to be as succinct as I can. First off, data has to be acknowledged as an asset. Number one. That's a transition in itself. Number two. Investment in technology has to be regarded as an investment in improving the value of that data asset which means that ultimately the money in this industry is gonna follow the value of the data, that's the simplest most straightforward way of thinking about this. So, when we think about, for example, the server business, we're saying "you're not gonna put all your data up in a public cloud because the data's not gonna allow you to do that." Well, what's the difference between saying you're not going to put all your data in a public cloud and saying oh you're going to move all of your data to some server somewhere? There's, yeah it's a little bit more approximate, but it's still not, you're gonna move your data closer to more intelligent storage, more intelligent networks, and they'll go find the compute that they need. And that's not how Dell is set up today. That's just not how they're set up today. So if we think about five to ten years, we're talking about a whole bunch of processing power being moved closer and closer and closer to the data in the form of, you know, routines that are being run right there at the storage machine. We're talking about much more programmable control planes, data-driven data-first control planes, that are being in the network and defined by what the network can do, and the compute is increasingly gonna be regarded as important, not unimportant, but it's gonna be an increasingly distributed world where you can't have your cake and eat it too, you can't say don't go up to the public cloud but go up to our big honking server. There's something that doesn't quite watch there. >> Well, great analysis Peter, and to your point organizational structures really matter and I think today Dell's organization is really optimized for the continued integration, streamlining that piece, getting that right, making sure the processes are there, and then we'll see how it goes over time. Alright, thanks you guys. That was awesome. Good kickoff for day three. Okay, this is day three, you're watching theCUBE, keep it right there we'll be back with our next guest right after this short break.