>> Narrator: Live, from Las Vegas, it's The Cube, covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. >> Hi everybody, welcome back to Las Vegas, my name is Dave Vellante and this is day three of The Cube's live wall to wall coverage of Hewlett Packard Enterprise, HPE Discover. This is The Cube, the leader and live tech coverage. We have a little reveal here, JR Fuller is here, he's the Global Business Development Manager IoT Edgeline at Hewlett Packard Enterprise and he's joined by Doug Smith, who is the CEO of Texmark. Gentleman, welcome. >> Thank you. >> Thank you for having us. >> Alright lay it on us Doug, what is Texmark all about? We're going to have, like I say, a little virtual reveal here-- >> Sure. And first of all, thanks for having me here-- >> Dave: You're very welcome. >> And, Texmark Chemical is a 50 year-old company, located in Galena Park, Texas, which is right on the Houston Ship Channel outside of the city of Houston. We are a manufacturer of specialty chemicals, one being DCPD, which stands for dicyclopentadiene. We have been making significant capital investments in the physical plant, over the last 20 years. And about two years ago, we realized we needed to move forward in a control system, a new control system, initiative at the plant, as well as a baseline mechanical integrity. Initiative. And so we're a small organization of 53 people and we looked to our contacts and got in touch with HPE and started a conversation. We don't have a normal client-customer relationship. We have a partnership of people, HPE people, Texmark people. >> Absolutely. >> So JR, pick it up from HPE's side. So, you guys have made a big push into this whole IoT business and you need partners like Doug's firm. >> Yeah, absolutely. So it's kind of interesting the way we got started. You probably remember last year, we had the big pump. The pump demo, the Filzer pump demo, so that was a project of mine, and Dough had heard about that from a mutual friend and ... Gracious. Very gracious of him, he invited us to come out at Texmark and actually install that at his facility. And he said "I got this bug pond over there, you can put that in there." And then you have a production version of that, 'cause we had the proof of concept version in our lap, and I said "That is really nice and very sweet, but no. "Let's figure out what we can do that will really benefit you, 'cause that won't really benefit you." And that started a dialogue that's, been about a year that we've been talking about this and I think it was in August, I proposed to him and said, "What do you think about "doing a refinery of the future?" And his words to me were, "JR, I don't know what "it is, but I love it." And I said, "Well, let's figure out what it is "for Texmark and let's go from there." And that's kind of how we started the genesis of this entire journey, of what we're doing. >> So you kind of laid out the vision, which is fantastic-- >> JR: Right. >> Sort of your North Star. And then just for the audiences benefit, you know, everyone here discovered there was this amazing floor exhibit, and it was pumps and tubes and pipes. >> JR: We've seen learning and, yeah. >> And it was all kinds of data, that was flowing through there, and sort of I guess, a digital twin if you will. >> Exactly. >> Of the factory floor ... >> Doug: Well of a plant, yes. And that's a great segway into Texmark and how we have synergy between our two organizations is that Texmark, although a small chemical process facility, we have all the equipment that the huge companies have. We have boilers, we have pipes, we have distillation columns, and we need to move forward, with our people to instrument, to gather data, to data analytics on the edge to have a connected facility with wifi capabilities, so that's where the conversation started. >> So much of the data ... Maybe even most of data today, historically anyway, analog data, is that correct? >> It is a combination. >> Dave: Okay. >> What we are doing, once again, we are a small organization. We have one IT person. And that person is contract, so how we're approaching it is, Texmark stays in the chemical, we use the analogy of, swim lanes. We are swimming towards profitability in the chemical business. HPE is swimming in the lane with-- >> All the technology. >> Technology. And then we're working together on this voyage of discovery, out here, that we're figuring out along the way. >> And for sure, you're not IT, you're operations. >> Doug: Yes, sir. >> Right? And you guys are IT. >> Exactly. >> So talk more about the partnership. What is that all about? >> Doug: People. >> JR: It's totally about people and it's interacting with each other, it's showing up ever day, it's working towards things. It's, when you do run into a problem ... And Doug's got a great story of when we had a problem. When you do run into a problem, you have the mutual of how to solve this problem together. In a typical customer-vendor relationship, there's some kind of built-in tension that's there and you know, you're worried about, "Oh, the vendor's trying to do this to me" , or "Oh, the customer if trying to get something from me." And we don't have any of that. We actually have a very solid partnership and occasionally, if one of my team or one of his team gets off track on that, we bring them back to the fold and say, "No, no, no. We're plowing road here." We need them to cut trees, we need us to cut trees, we all need to be heading in the same direction. You can't stop and go, "How come this isn't paved?" Because it hasn't been done before. >> And it's that shared objective of the refinery of the future that you're working towards. So, can we describe in a little bit more detail, the refinery of the future. >> Doug: Sure. Let me just jump in on that, because in this voyage of discovery, with these conversations, we talked about, what do we need to achieve the goals that we want? And so, first there is the hardware component. What do we here to achieve these goals? We'll just take the example of the pump. The pump is the heart of any process facility. If you have a critical pump go down, it can put you out of operation. There's a cost associated with that, and so what we need to do ... There's a cost associated with putting wiring from our control center to an actual pump. If we can have a wireless network and a censor on a pump, we eliminate the cost of physical wiring. The wireless network was provided by one of our content partners, Aruba, and so that is installed. We are working-- >> Dave: You know those guys? >> JR: I do, I do. >> He's heard of them. So then, what do we do with that data when it comes in? So, we have two Edgeline servers in there, and we have one in our control room, and then we have one, and it's super. They have one here, on the floor here, at the Discovery, the Micro-data center, which is for our place, everybody's like ... (sings) (laughter) >> It's fantastic-- >> Dave: It's data in a box. >> Yes, sir.And what that does, we have the ... I'll just give you an example. So we have our old system, the old server over here, size of a refrigerator, and I have used this numerous times when explaining the project to people here at Discover is that, I have to explain what we're doing to my 81 year-old mother. And when I say we have a refrigerator over there that used to run the plant, and now we have this one little thing the size of a little tablet-- (JR laughs) >> She goes ... And it saves money. It increases efficiency, she gets that. So those are some of the phases of the project, and now I'll pass it over to JR 'cause we then identify how are we going to use this cool hardware to achieve objectives? >> Yeah. So when we look at the refinery future, we usually have a three phrase project, alright? You don't boil the ocean, you bring it down into ... So phase one for us was putting in the Aruba wifi network out in the entire facility. We've done that. And because it's a petro chemical plant, it needs to go into a special enclosure. So we have a partner with Extronics, out in the U.K., that creates this protective enclosure. >> Dave: Like militarize. >> Yeah. Well, it's actually even beyond that, because in type one, dib one environments, there is a potential for hazardous gas to be out in there, and so electronic equipment would be sparking and stuff like that, and gas that can explode. Not a good combination. So, these div one boxes, make it so that, if there is an interaction with a spark, and some flammable gas, and there's an explosion, it's contained in that box, and not contaminates to the whole factory, which would be-- >> Plant. (laughs) >> Plant, the whole plant. Where it would actually create problems for everybody else, so that first phase was putting those div one compliant wifi AP's out there from Aruba. We also put in our beacons, with our location-based services, the meridian system out there, so they can do wave-finders and get to the right pump to fix it. And also, they're clear pass, so putting clear pass out there so it's a secured network, right? We don't want anybody to be able to go in there and mess with anything. >> So basic productivity, the security to allow that, all that basic infrastructure. >> So that was to-- >> To connect the ... >> Exactly. That was phase one. Phase two was, they had rack of other people's compute in there and we replaced all of that, like Doug said, with two of our Edgeline EL 4000 Converge systems. >> Dave: Okay. >> One of those, we actually mounted on the control room floor, so right out on the Edge, not in a data center environment, not in a temperature-controlled place, per say, and what we consider our data center. And then that other one, we actually did get an HPE Micro-data center, and we put the other one in there. It's secured, it's badge-access only. Only a couple people in Texmark have badge access to actually be able to get that. And when we look at the compute needs growing, that's where they're going to probably grow into, is that data. >> So phase two was bring the the compute. >> So I call those two, phase one and phase two, my infrastructure phase, 'cause now I've got what I need to do. Now phase three is really interesting because that's where we're going to start doing IoT stuff, right? So there are five projects that we're doing on IoT. So the first one is predictive analytics. This is both at the discreet and the process level. So, when we talk about that pump that we saw last year, that's a discreet machine. We're doing predicted analytics on that machine. But that machine feeds a process, so how can we predict what's happening on this machine, what's the impact of that to this process? So that's the first one. >> Doug: Can I hop in? >> Yeah, go for it. >> So, JR is using the example of the pump, and I mentioned the pump earlier, being the heart of the organization. So, it's been interesting being at Discover for the first time for me and the way that I have been talking with people, you have people that are extremely interested in the human component, and how is it affecting people? Also there is, the critical bottom line. How is it going to make me money and save me money? >> Dave: Right. >> So this pump is an excellent example that addresses both of those. So, if have a pump fail, there is a significant cost if it shuts us down for the day. We're a seven acre facility, and let's just throw a number out for easy math. Let's just say it costs us $100,000 a day, if that pump goes down. If you have a facility that's 100,000 times larger, just let me pull out my calculator and your math can tell this solves a problem. From a human perspective, it's just like your heart stopping, there's a risk associated with that pump going down within the facility. >> Okay, so we're very tight on time. >> Sorry. >> That's okay. So, you got the five phases for five IoT projects, within phase three, predictive analytics. Let's run through them and ... >> The second one is video is a sensor, so this is-- >> Cool. >> Using video to detect things that are going on and using the Edge analytics to be able to power that. The third one is safety and security. So these are things like, man down. Directive response, those types of things. The fourth one is, connected worker. And I define this as, location-based context-aware content. So, just very quickly, if you have three different people at the pump. One is a operations person, one's a maintenance person, one's a finance person, and they're all using that augmented reality that we saw, they're going to see three different dashboards. Locations base, context-aware content. And then the fifth one is, we're going to tie into the two sister projects that are going on out there with the DCS upgrade and the aneo-spalatio mechanical integrity program, and do a full life cycle as that management. So these are big projects. >> Dave: So now you've got the fully instrumented refinery is where you're at. Now you got all this data flowing. What happens to the data? Where does it get analyzed, where does it end up? Where do you go from there? >> Sure, so of course, having the Edgeline servers there, we're doing data analytics on the Edge so we can have real time, right there information to help our workers work safely and efficiently. And then we have this wealth of historical data that we can start analyzing, either on-premise or off-premise, to help us-- >> JR: Help probe the models. >> Better. And then also, this is one really cool aspect from a Texmark perspective is, we do a significant amount of total processing. That means, somebody comes to us and says, "Here, Dave. Make this for us." And we will run it through our equipment and give them an end product. If we can improve the way we cook, whatever our process, whatever it is that they want, there is a significant value added to that. >> Dave: And that historical data, in the lake if you will, lives on Prim, it lives in the Cloud, or you don't know yet. >> Everything is on Prim. The Cloud applications that we'll probably use are around safety and security when talking about weather, humidity, and those types of things. >> Dave: So bring in some outside data or models that you apply. >> Right. Yes. Texmark is a single facility, so leveraging the Cloud to communicate to other locations and things like that isn't really a necessary driver. Although it would be, completely would be, for some of the target customers that we want to sell this to initially. >> But the vast majority of the data is staying at-- >> JR: On Prim, yeah. >> Correct? So, it confirms the assumptions that we've been making, that 90% of the data is this world is going to be analyzed at the Edge and maybe trickle some stuff back, some nuggets back to the Cloud. >> Absolutely. >> Guys, we got to go. That's a fascinating story. Thank you so much. >> Thanks, you could tell I like the camera a lot in this. Thank you, Dave, I really appreciate it. >> Dave: My pleasure, thank you. Alright, keep it right there, everybody. We'll be back with our next guest as The Cuber live from HPE Discover in Las Vegas, 2017. We'll be right back. (electronic music)

(soft music) >> Welcome back to HPE Discover 2021, the virtual version, my name is Dave Vellante and you're watching theCUBE and we're here with Guido Appenzeller, who is the CTO of the Data Platforms Group at Intel. Guido, welcome to theCUBE, come on in. >> Aww, thanks Dave, I appreciate it. It's great to be here today. >> So I'm interested in your role at the company, let's talk about that, you're brand new, tell us a little bit about your background. What attracted you to Intel and what's your role here? >> Yeah, so I'm, I grew up with the startup ecosystem of Silicon Valley, I came from my PhD and never left. And, built software companies, worked at software companies worked at VMware for a little bit. And I think my initial reaction when the Intel recruiter called me, was like, Hey you got the wrong phone number, I'm a software guy, that's probably not who you're looking for. And, but we had a good conversation but I think at Intel, there's a realization that you need to look at what Intel builds more as this overall system from an overall systems perspective. That the software stack and then the hardware components are all getting more and more intricately linked and, you need the software to basically bridge across the different hardware components that Intel is building. So again, I was the CTO for the Data Platforms Group, so that builds the data center products here at Intel. And it's a really exciting job. And these are exciting times at Intel, with Pat, I've got a fantastic CEO at the helm. I've worked with him before at VMware. So a lot of things to do but I think a very exciting future. >> Well, I mean the, the data centers the wheelhouse of Intel, of course your ascendancy was a function of the PCs and the great volume and how you change that industry but really data centers is where, I remember the days people said, Intel will never be at the data center, it's just the toy. And of course, you're dominant player there now. So your initial focus here is really defining the vision and I'd be interested in your thoughts on the future what the data center looks like in the future where you see Intel playing a role, what are you seeing as the big trends there? Pat Gelsinger talks about the waves, he says, if you don't ride the waves you're going to end up being driftwood. So what are the waves you're driving? What's different about the data center of the future? >> Yeah, that's right. You want to surf the waves, that's the way to do it. So look, I like to look at this and sort of in terms of major macro trends, And I think that the biggest thing that's happening in the market right now is the cloud revolution. And I think we're well halfway through or something like that. And this transition from the classic, client server type model, that way with enterprises running all data centers to more of a cloud model where something is run by hyperscale operators or maybe run by an enterprise themselves of (indistinct) there's a variety of different models. but the provisioning models have changed. It's much more of a turnkey type service. And when we started out on this journey I think the, we built data centers the same way that we built them before. Although, the way to deliver IT have really changed, it's going through more of a service model and we really know starting to see the hardware diverge, the actual silicon that we need to build and how to address these use cases, diverge. And so I think one of the things that is probably most interesting for me is really to think through, how does Intel in the future build silicon that's built for clouds, like on-prem clouds, edge clouds, hyperscale clouds, but basically built for these new use cases that have emerged. >> So just a quick, kind of a quick aside, to me the definition of cloud is changing, it's evolving and it used to be this set of remote services in a hyperscale data center, it's now that experience is coming on-prem it's connecting across clouds, it's moving out to the edge it's supporting, all kinds of different workloads. How do you see that sort of evolving cloud? >> Yeah, I think, there's the biggest difference to me is that sort of a cloud starts with this idea that the infrastructure operator and the tenant are separate. And that is actually has major architectural implications, it just, this is a perfect analogy, but if I build a single family home, where everything is owned by one party, I want to be able to walk from the kitchen to the living room pretty quickly, if that makes sense. So, in my house here is actually the open kitchen, it's the same room, essentially. If you're building a hotel where your primary goal is to have guests, you pick a completely different architecture. The kitchen from your restaurants where the cooks are busy preparing the food and the dining room, where the guests are sitting, they are separate. The hotel staff has a dedicated place to work and the guests have a dedicated places to mingle but they don't overlap, typically. I think it's the same thing with architecture in the clouds. So, initially the assumption was it's all one thing and now suddenly we're starting to see like a much cleaner separation of these different areas. I think a second major influence is that the type of workloads we're seeing it's just evolving incredibly quickly, 10 years ago, things were mostly monolithic, today most new workloads are microservice based, and that has a huge impact in where CPU cycles are spent, where we need to put an accelerators, how we build silicon for that to give you an idea, there's some really good research out of Google and Facebook where they run numbers. And for example, if you just take a standard system and you run a microservice based an application but in the microservice-based architecture you can spend anywhere from I want to say 25 in some cases, over 80% of your CPU cycles just on overhead, and just on, marshaling demarshaling the protocols and the encryption and decryption of the packets and your service mesh that sits in between all of these things, that created a huge amount of overhead. So for us might have 80% go into these overhead functions really all focus on this needs to be on how do we enable that kind of infrastructure? >> Yeah, so let's talk a little bit more about workloads if we can, the overhead there's also sort of, as the software as the data center becomes software defined thanks to your good work at VMware, it is a lot of cores that are supporting that software-defined data center. And then- >> It's at VMware, yeah. >> And as well, you mentioned microservices container-based applications, but as well, AI is coming into play. And what is, AI is just kind of amorphous but it's really data-oriented workloads versus kind of general purpose ERP and finance and HCM. So those workloads are exploding, and then we can maybe talk about the edge. How are you seeing the workload mix shift and how is Intel playing there? >> I think the trends you're talking about is definitely right, and we're getting more and more data centric, shifting the data around becomes a larger and larger part of the overall workload in the data center. And AI is getting a ton of attention. Look if I talk to the most operators AI is still an emerging category. We're seeing, I'd say five, maybe 10% percent of workloads being AI is growing, they're very high value workloads. And they're very challenging workloads, but it's still a smaller part of the overall mix. Now edge is big and edge is two things, it's big and it's complicated because of the way I think about edge is it's not just one homogeneous market, it's really a collection of separate sub markets It's, very heterogeneous, it runs on a variety of different hardware. Edge can be everything from a little server, that's fanless, it's strapped to a phone, a telephone pole with an antenna on top of it, to aid a microcell, or it can be something that's running inside a car, modern cars has a small little data center inside. It can be something that runs on an industrial factory floor, the network operators, there's pretty broad range of verticals that all looks slightly different in their requirements. And, it's, I think it's really interesting, it's one of those areas that really creates opportunities for vendors like HPE, to really shine and address this heterogeneity with a broad range of solutions, very excited to work together with them in that space. >> Yeah, so I'm glad you brought HPE into the discussion, 'cause we're here at HPE Discover, I want to connect that. But so when I think about HPE strategy, I see a couple of opportunities for them. Obviously Intel is going to play in every part of the edge, the data center, the near edge and the far edge, and I gage HPE does as well with Aruba. Aruba is going to go to the far edge. I'm not sure at this point, anyway it's not yet clear to me how far, HPE's traditional server business goes to the, inside of automobiles, we'll see, but it certainly will be at the, let's call it the near edge as a consolidation point- >> Yeah. >> Et cetera and look the edge can be a race track, it could be a retail store, it could be defined in so many ways. Where does it make sense to process the data? But, so my question is what's the role of the data center in this world of edge? How do you see it? >> Yeah, look, I think in a sense what the cloud revolution is doing is that it's showing us, it leads to polarization of a classic data into edge and cloud, if that makes sense, it's splitting, before this was all mingled a little bit together, if my data centers my basement anyways, what's the edge, what's data center? It's the same thing. The moment I'm moving some workloads to the clouds I don't even know where they're running anymore then some other workloads that have to have a certain sense of locality, I need to keep closely. And there are some workloads you just can't move into the cloud. There's, if I'm generating lots of all the video data that I have to process, it's financially a completely unattractive to shift all of that, to a central location, I want to do this locally. And will I ever connect my smoke detector with my sprinkler system be at the cloud? No I won't, this stuff, if things go bad, that may not work anymore. So I need something that's that does this locally. So I think there's many reasons, why you want to keep something on premises. And I think it's a growing market, it's very exciting, we're doing some very good stuff with friends like HPE, they have the ProLiant DL, one 10 Gen10 Plus server with our latest a 3rd Generation Xeons on them the Open RAN, which is the radio access network in the telco space. HP Edgeline servers, also a 3rd Generation Xeons there're some really nice products there that I think can really help addressing enterprises, carriers and a number of different organizations, these edge use cases. >> Can you explain, you mentioned Open RAN, vRAN, should we essentially think of that as kind of the software-defined telco? >> Yeah, exactly. It's software-defined cellular. I actually, I learned a lot about that over the recent months. When I was taking these classes at Stanford, these things were still done in analog, that doesn't mean a radio signal will be processed in an analog way and digest it and today typically the radio signal is immediately digitized and all the processing of the radio signal happens digitally. And, it happens on servers, some of them HPE servers. And, it's a really interesting use case where we're basically now able to do something in a much, much more efficient way by moving it to a digital, more modern platform. And it turns out you can actually virtualize these servers and, run a number of different cells, inside the same server. And it's really complicated because you have to have fantastic real-time guarantees versus sophisticated software stack. But it's a really fascinating use case. >> A lot of times we have these debates and it's maybe somewhat academic, but I'd love to get your thoughts on it. And debate is about, how much data that is processed and inferred at the edge is actually going to come back to the cloud, most of the data is going to stay at the edge, a lot of it's not even going to be persisted. And the counter to that is, so that's sort of the negative is at the data center, but then the counter that is there going to be so much data, even a small percentage of all the data that we're going to create is going to create so much more data, back in the cloud, back in the data center. What's your take on that? >> Look, I think there's different applications that are easier to do in certain places. Look, going to a large cloud has a couple of advantages. You have a very complete software ecosystem around you, lots of different services. You'll have first, if you need very specialized hardware, if I wanted to run the bigger learning task where somebody needed a 1000 machines, and then this runs for a couple of days, and then I don't need to do that for another month or two, for that is really great. There's on demand infrastructure, having all this capability up there, at the same time it costs money to send the data up there. If I just look at the hardware cost, it's much much cheaper to build it myself, in my own data center or in the edge. So I think we'll see, customers picking and choosing what they want to do where, and that there's a role for both, absolutely. And so, I think there's certain categories. At the end of the day why do I absolutely need to have something at the edge? There's a couple of, I think, good use cases. One is, let me actually rephrase a little bit. I think it's three primary reasons. One is simply a bandwidth, where I'm saying, my video data, like I have a 100 4K video cameras, with 60 frames per second feeds, there's no way I'm going to move that into the cloud. It's just, cost prohibitive- >> Right. >> I have a hard time even getting (indistinct). There might be latency, if I need want to reliably react in a very short period of time, I can't do that in the cloud, I need to do this locally with me. I can't even do this in my data center. This has to be very closely coupled. And, then there's this idea of fade sharing. I think, if I want to make sure that if things go wrong, the system is still intact, anything that's sort of an emergency kind of a backup, an emergency type procedure, if things go wrong, I can't rely on the big good internet connection, I need to handle things, things locally, that's the smoke detector and the sprinkler system. And so for all of these, there's good reasons why we need to move things close to the edge so I think there'll be a creative tension between the two but both are huge markets. And I think there's great opportunities for HP ahead to work on all these use cases. >> Yeah, for sure, top brand is in that compute business. So before we wrap up today, thinking about your role, part of your role is a trend spotter. You're kind of driving innovation righty, surfing the waves as you said, skating to the puck, all the- >> I've got my perfect crystal ball right here, yeah I got. >> Yeah, all the cliches. (Dave chuckles) puts a little pressure on you, but, so what are some of the things that you're overseeing that you're looking towards in terms of innovation projects particularly obviously in the data center space, what's really exciting you? >> Look, there's a lot of them and I pretty much all the interesting ideas I get from talking to customers. You talk to the sophisticated customers, you try to understand the problems that they're trying to solve and they can't solve right now, and that gives you ideas to just to pick a couple, one thing what area I'm probably thinking about a lot is how can we build in a sense better accelerators for the infrastructure functions? So, no matter if I run an edge cloud or I run a big public cloud, I want to find ways how I can reduce the amount of CPU cycles I spend on microservice marshaling demarshaling, service mesh, storage acceleration and these things like that. And so well clearly, if this is a large chunk of the overall cycle budget, we need to find ways to shrink that to make this more efficient. So then I think, so this basic infrastructure function acceleration, sounds probably as unsexy as any topic would sound but I think this is actually really, really interesting area and one of the big levers we have right now in the data center. >> Yeah, I would agree Guido, I think that's actually really exciting because, you actually can pick up a lot of the wasted cycles now and that drops right to the bottom line, but please- >> Yeah, exactly. And it's kind of funny we're still measuring so much with SPEC and rates of CPU's performances, it's like, well, we may actually be measuring the wrong thing. If 80% of the cycles of my app are spent in overhead, then the speed of the CPU doesn't matter as much, it's other functions that (indistinct). >> Right. >> So that's one. >> The second big one is memory is becoming a bigger and bigger issue, and it's memory cost 'cause, memory prices, they used to sort of decline at the same rate that our core counts and then clock speeds increased, that's no longer the case. So we've run to some scaling limits, there's some physical scaling limits where memory prices are becoming stagnant. And this has become a major pain point for everybody who's building servers. So I think we need to find ways how we can leverage memory more efficiently, share memory more efficiently. We have some really cool ideas in that space that we're working on. >> Well, yeah. And Pat, let me just sorry to interrupt but Pat hinted to that and your big announcement. He talked about system on package and I think is what you used to talk about what I call disaggregated memory and better sharing of that memory resource. And that seems to be a clear benefit of value creation for the industry. >> Exactly. If this becomes a larger, if for our customers this becomes a larger part of the overall costs, we want to help them address that issue. And the third one is, we're seeing more and more data center operators that effectively power limited. So we need to reduce the overall power of systems, or maybe to some degree just figure out better ways of cooling these systems. But I think there's a lot of innovation that can be done there to both make these data centers more economical but also to make them a little more Green. Today data centers have gotten big enough that if you look at the total amount of energy that we're spending, this world as mankind, a chunk of that is going just to data center. And so if we're spending energy at that scale, I think we have to start thinking about how can we build data centers that are more energy efficient that are also doing the same thing with less energy in the future. >> Well, thank you for laying those out, you guys have been long-term partners with HP and now of course HPE, I'm sure Gelsinger is really happy to have you on board, Guido I would be and thanks so much for coming to theCUBE. >> It's great to be here and great to be at the HP show. >> And thanks for being with us for HPE Discover 2021, the virtual version, you're watching theCUBE the leader in digital tech coverage, be right back. (soft music)

(soft music) >> Welcome back to HPE Discover 2021, the virtual version, my name is Dave Vellante and you're watching theCUBE and we're here with Guido Appenzeller, who is the CTO of the Data Platforms Group at Intel. Guido, welcome to theCUBE, come on in. >> Aww, thanks Dave, I appreciate it. It's great to be here today. >> So I'm interested in your role at the company, let's talk about that, you're brand new, tell us a little bit about your background. What attracted you to Intel and what's your role here? >> Yeah, so I'm, I grew up with the startup ecosystem of Silicon Valley, I came from my PhD and never left. And, built software companies, worked at software companies worked at VMware for a little bit. And I think my initial reaction when the Intel recruiter called me, was like, Hey you got the wrong phone number, I'm a software guy, that's probably not who you're looking for. And, but we had a good conversation but I think at Intel, there's a realization that you need to look at what Intel builds more as this overall system from an overall systems perspective. That the software stack and then the hardware components are all getting more and more intricately linked and, you need the software to basically bridge across the different hardware components that Intel is building. So again, I was the CTO for the Data Platforms Group, so that builds the data center products here at Intel. And it's a really exciting job. And these are exciting times at Intel, with Pat, I've got a fantastic CEO at the helm. I've worked with him before at VMware. So a lot of things to do but I think a very exciting future. >> Well, I mean the, the data centers the wheelhouse of Intel, of course your ascendancy was a function of the PCs and the great volume and how you change that industry but really data centers is where, I remember the days people said, Intel will never be at the data center, it's just the toy. And of course, you're dominant player there now. So your initial focus here is really defining the vision and I'd be interested in your thoughts on the future what the data center looks like in the future where you see Intel playing a role, what are you seeing as the big trends there? Pat Gelsinger talks about the waves, he says, if you don't ride the waves you're going to end up being driftwood. So what are the waves you're driving? What's different about the data center of the future? >> Yeah, that's right. You want to surf the waves, that's the way to do it. So look, I like to look at this and sort of in terms of major macro trends, And I think that the biggest thing that's happening in the market right now is the cloud revolution. And I think we're well halfway through or something like that. And this transition from the classic, client server type model, that way with enterprises running all data centers to more of a cloud model where something is run by hyperscale operators or maybe run by an enterprise themselves of (indistinct) there's a variety of different models. but the provisioning models have changed. It's much more of a turnkey type service. And when we started out on this journey I think the, we built data centers the same way that we built them before. Although, the way to deliver IT have really changed, it's going through more of a service model and we really know starting to see the hardware diverge, the actual silicon that we need to build and how to address these use cases, diverge. And so I think one of the things that is probably most interesting for me is really to think through, how does Intel in the future build silicon that's built for clouds, like on-prem clouds, edge clouds, hyperscale clouds, but basically built for these new use cases that have emerged. >> So just a quick, kind of a quick aside, to me the definition of cloud is changing, it's evolving and it used to be this set of remote services in a hyperscale data center, it's now that experience is coming on-prem it's connecting across clouds, it's moving out to the edge it's supporting, all kinds of different workloads. How do you see that sort of evolving cloud? >> Yeah, I think, there's the biggest difference to me is that sort of a cloud starts with this idea that the infrastructure operator and the tenant are separate. And that is actually has major architectural implications, it just, this is a perfect analogy, but if I build a single family home, where everything is owned by one party, I want to be able to walk from the kitchen to the living room pretty quickly, if that makes sense. So, in my house here is actually the open kitchen, it's the same room, essentially. If you're building a hotel where your primary goal is to have guests, you pick a completely different architecture. The kitchen from your restaurants where the cooks are busy preparing the food and the dining room, where the guests are sitting, they are separate. The hotel staff has a dedicated place to work and the guests have a dedicated places to mingle but they don't overlap, typically. I think it's the same thing with architecture in the clouds. So, initially the assumption was it's all one thing and now suddenly we're starting to see like a much cleaner separation of these different areas. I think a second major influence is that the type of workloads we're seeing it's just evolving incredibly quickly, 10 years ago, things were mostly monolithic, today most new workloads are microservice based, and that has a huge impact in where CPU cycles are spent, where we need to put an accelerators, how we build silicon for that to give you an idea, there's some really good research out of Google and Facebook where they run numbers. And for example, if you just take a standard system and you run a microservice based an application but in the microservice-based architecture you can spend anywhere from I want to say 25 in some cases, over 80% of your CPU cycles just on overhead, and just on, marshaling demarshaling the protocols and the encryption and decryption of the packets and your service mesh that sits in between all of these things, that created a huge amount of overhead. So for us might have 80% go into these overhead functions really all focus on this needs to be on how do we enable that kind of infrastructure? >> Yeah, so let's talk a little bit more about workloads if we can, the overhead there's also sort of, as the software as the data center becomes software defined thanks to your good work at VMware, it is a lot of cores that are supporting that software-defined data center. And then- >> It's at VMware, yeah. >> And as well, you mentioned microservices container-based applications, but as well, AI is coming into play. And what is, AI is just kind of amorphous but it's really data-oriented workloads versus kind of general purpose ERP and finance and HCM. So those workloads are exploding, and then we can maybe talk about the edge. How are you seeing the workload mix shift and how is Intel playing there? >> I think the trends you're talking about is definitely right, and we're getting more and more data centric, shifting the data around becomes a larger and larger part of the overall workload in the data center. And AI is getting a ton of attention. Look if I talk to the most operators AI is still an emerging category. We're seeing, I'd say five, maybe 10% percent of workloads being AI is growing, they're very high value workloads. So (indistinct) any workloads, but it's still a smaller part of the overall mix. Now edge is big and edge is two things, it's big and it's complicated because of the way I think about edge is it's not just one homogeneous market, it's really a collection of separate sub markets It's, very heterogeneous, it runs on a variety of different hardware. Edge can be everything from a little server, that's (indistinct), it's strapped to a phone, a telephone pole with an antenna on top of it, to (indistinct) microcell, or it can be something that's running inside a car, modern cars has a small little data center inside. It can be something that runs on an industrial factory floor, the network operators, there's pretty broad range of verticals that all looks slightly different in their requirements. And, it's, I think it's really interesting, it's one of those areas that really creates opportunities for vendors like HPE, to really shine and address this heterogeneity with a broad range of solutions, very excited to work together with them in that space. >> Yeah, so I'm glad you brought HPE into the discussion, 'cause we're here at HPE Discover, I want to connect that. But so when I think about HPE strategy, I see a couple of opportunities for them. Obviously Intel is going to play in every part of the edge, the data center, the near edge and the far edge, and I gage HPE does as well with Aruba. Aruba is going to go to the far edge. I'm not sure at this point, anyway it's not yet clear to me how far, HPE's traditional server business goes to the, inside of automobiles, we'll see, but it certainly will be at the, let's call it the near edge as a consolidation point- >> Yeah. >> Et cetera and look the edge can be a race track, it could be a retail store, it could be defined in so many ways. Where does it make sense to process the data? But, so my question is what's the role of the data center in this world of edge? How do you see it? >> Yeah, look, I think in a sense what the cloud revolution is doing is that it's showing us, it leads to polarization of a classic data into edge and cloud, if that makes sense, it's splitting, before this was all mingled a little bit together, if my data centers my basement anyways, what's the edge, what's data center? It's the same thing. The moment I'm moving some workloads to the clouds I don't even know where they're running anymore then some other workloads that have to have a certain sense of locality, I need to keep closely. And there are some workloads you just can't move into the cloud. There's, if I'm generating lots of all the video data that I have to process, it's financially a completely unattractive to shift all of that, to a central location, I want to do this locally. And will I ever connect my smoke detector with my sprinkler system be at the cloud? No I won't (Guido chuckles) this stuff, if things go bad, that may not work anymore. So I need something that's that does this locally. So I think there's many reasons, why you want to keep something on premises. And I think it's a growing market, it's very exciting, we're doing some very good stuff with friends like HPE, they have the ProLiant DL, one 10 Gen10 Plus server with our latest a 3rd Generation Xeons on them the Open RAN, which is the radio access network in the telco space. HP Edgeline servers, also a 3rd Generation Xeons there're some really nice products there that I think can really help addressing enterprises, carriers and a number of different organizations, these edge use cases. >> Can you explain, you mentioned Open RAN, vRAN, should we essentially think of that as kind of the software-defined telco? >> Yeah, exactly. It's software-defined cellular. I actually, I learned a lot about that over the recent months. When I was taking these classes at Stanford, these things were still done in analog, that doesn't mean a radio signal will be processed in an analog way and digest it and today typically the radio signal is immediately digitized and all the processing of the radio signal happens digitally. And, it happens on servers, some of them HPE servers. And, it's a really interesting use case where we're basically now able to do something in a much, much more efficient way by moving it to a digital, more modern platform. And it turns out you can actually virtualize these servers and, run a number of different cells, inside the same server. And it's really complicated because you have to have fantastic real-time guarantees versus sophisticated software stack. But it's a really fascinating use case. >> A lot of times we have these debates and it's maybe somewhat academic, but I'd love to get your thoughts on it. And debate is about, how much data that is processed and inferred at the edge is actually going to come back to the cloud, most of the data is going to stay at the edge, a lot of it's not even going to be persisted. And the counter to that is, so that's sort of the negative is at the data center, but then the counter that is there going to be so much data, even a small percentage of all the data that we're going to create is going to create so much more data, back in the cloud, back in the data center. What's your take on that? >> Look, I think there's different applications that are easier to do in certain places. Look, going to a large cloud has a couple of advantages. You have a very complete software ecosystem around you, lots of different services. You'll have first, if you need very specialized hardware, if I wanted to run the bigger learning task where somebody needed a 1000 machines, and then this runs for a couple of days, and then I don't need to do that for another month or two, for that is really great. There's on demand infrastructure, having all this capability up there, at the same time it costs money to send the data up there. If I just look at the hardware cost, it's much much cheaper to build it myself, in my own data center or in the edge. So I think we'll see, customers picking and choosing what they want to do where, and that there's a role for both, absolutely. And so, I think there's certain categories. At the end of the day why do I absolutely need to have something at the edge? There's a couple of, I think, good use cases. One is, let me actually rephrase a little bit. I think it's three primary reasons. One is simply a bandwidth, where I'm saying, my video data, like I have a 100 4K video cameras, with 60 frames per second feeds, there's no way I'm going to move that into the cloud. It's just, cost prohibitive- >> Right. >> I have a hard time even getting (indistinct). There might be latency, if I need want to reliably react in a very short period of time, I can't do that in the cloud, I need to do this locally with me. I can't even do this in my data center. This has to be very closely coupled. And, then there's this idea of fade sharing. I think, if I want to make sure that if things go wrong, the system is still intact, anything that's sort of an emergency kind of a backup, an emergency type procedure, if things go wrong, I can't rely on the big good internet connection, I need to handle things, things locally, that's the smoke detector and the sprinkler system. And so for all of these, there's good reasons why we need to move things close to the edge so I think there'll be a creative tension between the two but both are huge markets. And I think there's great opportunities for HP ahead to work on all these use cases. >> Yeah, for sure, top brand is in that compute business. So before we wrap up today, thinking about your role, part of your role is a trend spotter. You're kind of driving innovation righty, surfing the waves as you said, skating to the puck, all the- >> I've got my perfect crystal ball right here, yeah I got. >> Yeah, all the cliches. (Dave chuckles) puts a little pressure on you, but, so what are some of the things that you're overseeing that you're looking towards in terms of innovation projects particularly obviously in the data center space, what's really exciting you? >> Look, there's a lot of them and I pretty much all the interesting ideas I get from talking to customers. You talk to the sophisticated customers, you try to understand the problems that they're trying to solve and they can't solve right now, and that gives you ideas to just to pick a couple, one thing what area I'm probably thinking about a lot is how can we build in a sense better accelerators for the infrastructure functions? So, no matter if I run an edge cloud or I run a big public cloud, I want to find ways how I can reduce the amount of CPU cycles I spend on microservice marshaling demarshaling, service mesh, storage acceleration and these things like that. And so well clearly, if this is a large chunk of the overall cycle budget, we need to find ways to shrink that to make this more efficient. So then I think, so this basic infrastructure function acceleration, sounds probably as unsexy as any topic would sound but I think this is actually really, really interesting area and one of the big levers we have right now in the data center. >> Yeah, I would agree Guido, I think that's actually really exciting because, you actually can pick up a lot of the wasted cycles now and that drops right to the bottom line, but please- >> Yeah, exactly. And it's kind of funny we're still measuring so much with SPEC and rates of CPU's performances, it's like, well, we may actually be measuring the wrong thing. If 80% of the cycles of my app are spent in overhead, then the speed of the CPU doesn't matter as much, it's other functions that (indistinct). >> Right. >> So that's one. >> The second big one is memory is becoming a bigger and bigger issue, and it's memory cost 'cause, memory prices, they used to sort of decline at the same rate that our core counts and then clock speeds increased, that's no longer the case. So we've run to some scaling limits, there's some physical scaling limits where memory prices are becoming stagnant. And this has become a major pain point for everybody who's building servers. So I think we need to find ways how we can leverage memory more efficiently, share memory more efficiently. We have some really cool ideas in that space that we're working on. >> Well, yeah. And Pat, let me just sorry to interrupt but Pat hinted to that and your big announcement. He talked about system on package and I think is what you used to talk about what I call disaggregated memory and better sharing of that memory resource. And that seems to be a clear benefit of value creation for the industry. >> Exactly. If this becomes a larger, if for our customers this becomes a larger part of the overall costs, we want to help them address that issue. And the third one is, we're seeing more and more data center operators that effectively power limited. So we need to reduce the overall power of systems, or maybe to some degree just figure out better ways of cooling these systems. But I think there's a lot of innovation that can be done there to both make these data centers more economical but also to make them a little more Green. Today data centers have gotten big enough that if you look at the total amount of energy that we're spending, this world as mankind, a chunk of that is going just to data center. And so if we're spending energy at that scale, I think we have to start thinking about how can we build data centers that are more energy efficient that are also doing the same thing with less energy in the future. >> Well, thank you for laying those out, you guys have been long-term partners with HP and now of course HPE, I'm sure Gelsinger is really happy to have you on board, Guido I would be and thanks so much for coming to theCUBE. >> It's great to be here and great to be at the HP show. >> And thanks for being with us for HPE Discover 2021, the virtual version, you're watching theCUBE the leader in digital tech coverage, be right back. (soft music)

(uplifting music) >> Hello and welcome to this Cube Conversation. I'm John Furrier, host of theCube here in Palo Alto, California. We've got two great remote guests to talk about some big news hitting with Scality and Hewlett Packard Enterprise. Jerome Lecat CEO of Scality and Chris Tinker, Distinguished Technologist from HPE, Hewlett Packard Enterprise, Jerome, Chris, great to see you both Cube alumnis from an original gangster days as we'd say back then when we started almost 11 years ago. Great to see you both. >> It's great to be back. >> Good to see you John. >> So, really compelling news around kind of this next generation storage cloud native solution. Okay, it's really kind of an impact on the next gen, I call next gen, dev ops meets application, modern application world and something we've been covering heavily. There's some big news here around Scality and HPE offering a pretty amazing product. You guys introduced essentially the next gen piece of it, Artesca, we'll get into in a second, but this is a game-changing announcement you guys announced, this is an evolution continuing I think is more of a revolution, but I think, you know storage is kind of abstractionally of evolution to this app centric world. So talk about this environment we're in and we'll get to the announcement, which is object store for modern workloads, but this whole shift is happening Jerome. This is a game changer to storage and customers are going to be deploying workloads. >> Yeah, Scality really, I mean, I personally really started working on Scality more than 10 years ago, close to 15 now. And if we think about it I mean the cloud has really revolutionized IT. And within the cloud, we really see layers and layers of technology. I mean, it all start at around 2006 with Amazon and Google and Facebook finding ways to do initially what was consumer IT at very large scale, very low credible reliability and then slowly creeped into the enterprise. And at the very beginning, I would say that everyone was kind of wizards trying things and really coupling technologies together. And to some degree we were some of the first wizard doing this, but we, we're now close to 15 years later and there's a lot of knowledge and a lot of experience, a lot of tools. And this is really a new generation. I'll call it cloud native, or you can call it next gen whatever, but there is now enough experience in the world, both at the development level and at the infrastructure level to deliver truly distributed automated systems that run on industry standard servers. Obviously good quality server deliver a better service than others, but there is now enough knowledge for this to truly go at scale. And call this cloud or call this cloud native. Really the core concept here is to deliver scalable IT at very low cost, very high level of reliability, all based on software. And we've, we've been participated in this motion, but we feel that now the breadth of what's coming is at the new level, and it was time for us to think, develop and launch a new product that's specifically adapted to that. And Chris, I will let you comment on this because the customers or some of them, you can add a customer, you do that. >> Well, you know, you're right. You know, I've been in the, I've been like you I've been in this industry for a, well, along time. Give a long, 20 to 21 years in HPE in engineering. And look at the actual landscape has changed with how we're doing scale-out software-defined storage for particular workloads. And we're a catalyst has evolved here is an analytics normally what was only done in the three letter acronyms and massively scale-out parallel namespace file systems, parallel file systems. The application space has encroached into the enterprise world where the enterprise world needed a way to actually take a look at how to, how do I simplify the operations? How do I actually be able to bring about an application that can run in the public cloud or on premise or hybrid, be able to actually look at a workload optimized step that aligns the actual cost to the actual analytics that I'm going to be doing the workload that I'm going to be doing and be able to bridge those gaps and be able to spin this up and simplify operations. And you know, and if you, if you are familiar with these parallel processes which by the way we actually have on our truck, I, I do engineer those, but they are, they are, they are they have their own unique challenges, but in the world of enterprise where customers are looking to simplify operations, then take advantage of new application, analytic workloads whether it be smart, Mesa, whatever it might be, right. I mean, if I want to spin up a Mongo DB or maybe maybe a, you know, last a search capability how do I actually take those technologies, embrace a modern scale-out storage stack that without without breaking the bank, but also provide a simple operations. And that's, that's why we look for object storage capabilities because it brings us this massive parallelization. Back to you John. >> Well before we get into the product. I want to just touch on one thing Jerome you mentioned, and Chris, you, you brought up the DevOps piece next gen, next level, whatever term you use. It is cloud native, cloud native has proven that DevOps infrastructure is code is not only legit. It's being operationalized in all enterprises and add security in there, you have DevSecOps, this is the reality and hybrid cloud in particular has been pretty much the consensus is that standard. So our defacto center whatever you want to call it, that's happening. Multicloud are on the horizon. So these new workloads are have these new architectural changes, cloud on premises and edge. This is the number one story. And the number one challenge all enterprises are now working on. How do I build the architecture for the cloud on premises and edge? This is forcing the DevOps team to flex and build new apps. Can you guys talk about that particular trend? And is it, and is that relevant here? >> Yeah, I, I now talk about really storage anywhere and cloud anywhere and and really the key concept is edge to go to cloud. I mean, we all understand now that the edge will host a lot of that time and the edge is many different things. I mean, it's obviously a smartphone, whatever that is, but it's also factories, it's also production. It's also, you know, moving moving machinery, trains, planes, satellites that that's all the edge, cars obviously. And a lot of that I will be both produced and process there, but from the edge who will want to be able to send the data for analysis, for backup, for logging to a call, and that call could be regional, maybe not, you know, one call for the whole planet, but maybe one corporate region the state in the U.S. And then from there you will also want to push some of the data to public cloud. One of the thing that we see more and more is that the D.R that has centered the disaster recovery is not another physical data center. It's actually the cloud, and that's a very efficient infrastructure very cost efficient, especially. So really it, it, it's changing the paradigm on how you think about storage because you really need to integrate these three layers in a consistent approach especially around the topic of security because you want the data to be secure all along the way. And data is not just data, its data, and who can access the data, who can modify the data what are the conditions that allow modification all automatically erasure of the data? In some cases, it's super important that the data automatically erased after 10 years and all this needs to be transported from edge to core to cloud. So that that's one of the aspects. Another aspects that resonates for me with what you said is a word you didn't say, but it's actually crucial this whole revolution. It's Kubernetes I mean, Kubernetes is in now a mature technology, and it's, it's just, you know the next level of automatized operation for distributed system, which we didn't have 5 or 10 years ago. And that is so powerful that it's going to allow application developers to develop much faster system that can be distributed again edge to go to cloud, because it's going to be an underlying technology that spans the three layers. >> Chris, your thoughts hybrid cloud. I've been, I've been having questions with the HPE folks for God years and years on hybrid clouds, now here. >> Right (chuckles) >> Well, you know, and, and it's exciting in a layout right, so you look at like a, whether it be enterprise virtualization, that is a scale-out general purpose virtualization workloads whether it be analytic workloads, whether it be no data protection is a paramount to all of this, orchestration is paramount. If you look at that DevSecOps, absolutely. I mean, securing the actual data the digital last set is, is absolutely paramount. And if you look at how we do this look at the investments we're making, we're making enough and look at the collaborative platform development which goes to our partnership with Scality. It is, we're providing them an integral aspect of everything we do, whether we're bringing in Ezmeral which is our software we use for orchestration look at the veneer of its control plane, controlling Kubernetes. Being able to actually control the active clusters and the actual backing store for all the analytics that we just talked about. Whether it be a web-scale app that is traditionally using a politics namespace and now been modernized and take advantage of newer technologies running an NBME burst buffers or a hundred gig networks with Slingshot network of 200 and 400 gigabit looking at how do we actually get the actual analytics, the workload to the CPU and have it attached to the data at risk. Where's the data, how do we land the data? How do we actually align, essentially locality, locality of the actual asset to the computer. And this is where, you know, we can look leverage whether it be a Zair or Google or name your favorite hybrid, hyperscaler, leverage those technologies leveraging the actual persistent store. And this is where Scality is, with this object store capability has it been an industry trendsetter, setting the actual landscape of how provide an object store on premise and hybrid cloud run it in a public cloud, but being able to facilitate data mobility and tie it back to, and tie it back to an application. And this is where a lot of things have changed in the world of analytics, because the applications that you, the newer technologies that are coming on the market have taken advantage of this particular protocol as threes. So they can do web scale massively parallel concurrent workloads. >> You know what let's get into the announcement. I love cool and relevant products. And I think this hits the mark. Scality you guys have Artesca, which is just announced. And I think it, you know, we obviously we reported on it. You guys have a lightweight true enterprise grade object store software for Kubernetes. This is the announcement, Jerome, tell us about it. What's the big deal? Cool and relevant, come on, this is cool. Right, tell us. >> I'm super excited. I'm not sure, if you can see it as well on the screen, but I'm super, super excited. You know, we, we introduced the ring 11 years ago and they says our biggest announcements for the past 11 years. So yes, do pay attention. And, you know, after, after looking at, at all these trends and understanding where we see the future going. We decided that it was time to embark (indistinct) So there's not one line of code that's the same as our previous generation product. They will both exist, they both have a space in the market. And Artesca was specifically designed for this cloud native era. And what we see is that people want something that's lightweight especially because it had to go to the edge. They still want the enterprise grid that Scality is known for. And it has to be modern. What we really mean by modern is, we see object storage now being the primary storage for many application more and more applications. And so we have to be able to deliver the performance, that primary storage expects. This idea of a Scality of serving primary storage is actually not completely new. When we launched Scality 10 years ago, the first application that we were supporting was consumer email for which we were, and we are still today, the primary storage. So we have, we know what it is to be the primary store. We know what's the level of reliability you need to hit. We know what, what latency means and latency is different from throughput, you really need to optimize both. And I think that still today we're the only object storage company that protects data from both replication and original encoding Because we understand that replication is faster, but the original encoding is more better, and more, of file where fast internet latency doesn't matter so much. So we we've been being all that experience, but really rethinking of product for that new generation that really is here now. And so where we're truly excited, I guess people a bit more about the product. It's a software, Scality is a software company and that's why we love to partner with HPE who's producing amazing servers, you know for the record and the history. The very first deployment of Scality in 2010 was on the HP servers. So this is a long love story here. And so to come back to our desk is lightweight in the sense that it's easy to use. We can start small, we can start from just one server or one VM I mean, you would start really small, but he can grow infinitely. The fact that we start small, we didn't, you know limit the technology because of that. So you can start from one to many and it's cloud native in the sense that it's completely Kubernetes compatible it's Kubernetes office traded. It will deploy on many Kubernetes distributions. We're talking obviously with Ezmeral we're also talking with zoo and with the other all those of communities distribution it will also be able to be run in the cloud. Now, I'm not sure that there will be many true production deployment of Artesca going the cloud, because you already have really good object storage by the cloud providers but when you are developing something and you want to test that, you know just doing it in the cloud is very practical. So you'll be able to deploy our Kubernetes cloud distribution, and it's more than object storage in the sense that it's application centric. A lot of our work is actually validating that our storage is fit for this single purpose application. And making sure that we understand the requirement of these application, that we can guide our customers on how to deploy. And it's really designed to be the primary storage for these new workloads. >> The big part of the news is your relationship with Hewlett Packard Enterprise is some exclusivity here as part of this and as you mentioned the relationship goes back many, many years. We've covered the, your relationship in the past. Chris also, you know, we cover HP like a blanket. This is big news for HPE as well. >> This is very big news. >> What is the relationship, talk about this exclusivity Could you share about the partnership and the exclusivity piece? >> Well, there's the partnership expands into the pan HPE portfolio. we look, we made a massive investment in edge IOT device. So we actually have how did we align the cost to the demand. Our customers come to us, wanting to looking at think about what we're doing with Greenlake, like in consumption based modeling. They want to be able to be able to consume the asset without having to do a capital outlay out of the gate. Number two, look at, you know how do you deploy technology, really demand. It depends on the scale, right? So in a lot of your web skill, you know, scale out technologies, it putting them on a diet is challenging. Meaning how skinny can you get it. Getting it down into the 50 terabyte range and then the complexities of those technologies at as you take a day one implementation and scale it out over you know, you know, multiple iterations over quarters, the growth becomes a challenge so working with Scality we, we believe we've actually cracked this nut. We figured out how to a number one, how to start small, but not limit a customer's ability to scale it out incrementally or grotesquely. You can eat depending on the quarters, the month, whatever whatever the workload is, how do you actually align and be able to consume it? So now whether it be on our Edgeline products our DL products go right there, now what that Jerome was talking about earlier you know, we, we, we ship a server every few seconds. That won't be a problem. But then of course, into our density optimized compute with the Apollo products. And this where our two companies have worked in an exclusivity where they scale the software bonds on the HP ecosystem. And then we can, of course provide you, our customers the ability to consume that through our GreenLake financial models or through a CapEx partners. >> Awesome, so Jerome and, and Chris, who's the customer here obviously, there's an exclusive period. Talk about the target customer and how the customers get the product and how they get the software. And how does this exclusivity with HP fit into it? >> Yeah, so there there's really a three types of customers and we've really, we've worked a lot with a company called UseDesign to optimize the user interface for each the types of customers. So we really thought about each customer role and providing with each of them the best product. So the, the first type of customer are application owners who are deploying an application that requires an object storage in the backend, you typically want a simple object store for one application, they want it to be simple and work. Honestly they want no thrill, just want an object store that works. And they want to be able to start as small as they start with their application. Often it's, you know, the first deployment maybe a small deployment, you know applications like a backup like VML, Rubrik, or analytics like (indistinct), file system that now, now available as a software, you know like CGI does a really great departmental NAS that works very well that needs an object store in the backend. Or for high performance computing a wake-up house system is an amazing file system. We will also have vertical application like road peak, for example, who provides origin and the view of the software broadcasters. So all these are application, they request an object store in the backend and you just need a simple high-performance working well object store and I'll discuss perfect for that. Now, the second type of people that we think will be interested by Artesca are essentially developer who are currently developing some capabilities or cloud native application, your next gen. And as part of their development stack, it's getting better and better when you're developing a cloud native application to really target an object storage rather than NFS, as you're persistent. It just, you know, think about generations of technologies and NFS and filesystem were great 25 years ago. I mean, it's an amazing technology. Now, when you want to develop a distributed scalable application object storage is a better fit because it's the same generation. And so same thing, I mean, you know, they're developing something they need an object store that they can develop on. So they want it very lightweight, but they also want the product that their enterprise or their customers will be able to rely on for years and years on. And this guy's really great fit to do that. The third type of customer are more architects, I would say are the architects that are designing a system where they are going to have 50 factories, a thousand planes, a million cars, they are going to have some local storage which will they want to replicate to the core and possibly also to the cloud. And as the design is really new generation workloads that are incredibly distributed but with local storage Artesca are really great for that. >> And tell about the HPE exclusive Chris. What's the, how does that fit in? Do they buy through Scality? Can they get it for the HP? Are you guys working together on how customers can procure it? >> Both ways, yeah both ways they can procure it through Scality. They can secure it through HPE and it's, it's it's the software stack running on our density optimized compute platforms which you would choose and align those and to provide an enterprise quality. Cause if it comes back to it in all of these use cases is how do we align up into a true enterprise stack, bringing about multitenancy bringing about the, the, the fact that you know, if you look at like a local coding one of the things that they're bringing to it, so that we can get down into the DL325. So with the exclusivity, you actually get choice. And that choice comes into our entire portfolio whether it be the Edgeline platform the DL325 AMD processing stack or the Intel 380, or whether it be the Apollos or like I said, there's, there's, there's so many ample choices there that facilitate this, and it's this allows us to align those two strategies. >> Awesome, and I think the Kubernetes piece is really relevant because, you know, I've been interviewing folks practitioners and Kubernetes is very much maturing fast. It's definitely the centerpiece of the cloud native both below the, the line, if you will below under the hood for the, for the infrastructure and then for apps, they want a program on top of it that's critical. I mean, Jerome, this is like, this is the future. >> Yeah, and if you don't mind like to come back to the myth on the exclusivity with HP. So we did a six month exclusive and the very reason we could do this is because HP has such breadth of server portfolio. And so we can go from, you know, really simple, very cheap you know, DL380, machine that we tell us for a few dollars. I mean, it's really like simple system, 50 terabyte. We can have the DL325 that Chris mentioned that is really a powerhouse all NVME, clash over storage is NVME, very fast processors you know, dense, large, large system, like the APOE 4,500. So it's a very large graph of portfolio. We support the whole portfolio and we work together on this. So I want to say that you know, one of the reason I want to send kudos to HP for the breadth of their server line really. As mentioned, Artesca can be ordered from either company. In hand-in-hand together, so anyway, you'll see both of us and our field working incredibly well together. >> Well, just on that point, I think just for clarification was this co-design by Scality and HPE, because Chris you mentioned, you know, the, the configuration of your systems. Can you guys, Chris quickly talk about the design. >> From, from, from the code base the software is entirely designed and developed by Scality, from testing and performance, so this really was a joint work with HP providing both a hardware and manpower so that we could accelerate the testing phase. >> You know, Chris HPE has just been doing such a great job of really focused on this. I know I've been covering it for years before it was fashionable. The idea of apps working no matter where it lives, public cloud, data center, edge. And you mentioned edge line's been around for awhile, you know, app centric, developer friendly, cloud first, has been an HPE kind of guiding first principle for many, many years. >> Well, it has. And, you know, as our CEO here intended, by 2022 everything will be able to be consumed as a service in our portfolio. And then this stack allows us the simplicity and the consumability of the technology and the granulation of it allows us to simplify the installation. Simplify the actual deployment bringing into a cloud ecosystem, but more importantly for the end customer. They simply get an enterprise quality product running on an optimized stack that they can consume through a orchestrated simplistic interface. That customers that's what they're wanting for today's but they come to me and ask, hey how do I need a, I've got this new app, new project. And, you know, it goes back to who's actually coming. It's no longer the IT people who are actually coming to us. It's the lines of business. It's that entire dimension of business owners coming to us, going this is my challenge. And how can you, HPE help us? And we rely on our breadth of technology, but also our breadth of partners to come together in our, of course Scality is hand in hand and our collaborative business unit our collaborative storage product engineering group that actually brought, brought this to market. So we're very excited about this solution. >> Chris, thanks for that input and great insight. Jerome, congratulations on a great partnership with HPE obviously great joint customer base. Congratulations on the product release here. Big moving the ball down the field, as they say. New functionality, clouds, cloud native object store. Phenomenal, so wrap, wrap, wrap up the interview. Tell us your vision for Scality and the future of storage. >> Yeah, I think I started in, Scality is going to be an amazing leader, it is already. But yeah, so, you know I have three things that I think will govern how storage is going. And obviously Marc Andreessen said it software is everywhere and software is eating the world. So definitely that's going to be true in the data center in storage in particular, but the three trends that are more specific are first of all, I think that security performance and agility is now basic expectation. It's, it's not, you know it's not like an additional feature. It's just the basic tables, security performance and our job. The second thing is, and we've talked about it during this conversation is edge to go. You need to think your platform with edge, core and cloud. You know, you, you don't want to have separate systems separate design interface point for edge and then think about the core and then think about cloud, and then think about the diverse power. All this needs to be integrated in a design. And the third thing that I see as a major trend for the next 10 years is data sovereignty. More and more, you need to think about where is the data residing? What are the legal challenges? What is the level of protection, against who are you protected? What is your independence strategy? How do you keep as a company being independent from the people you need to be in the band? And I mean, I say companies, but this is also true for public services. So these, these for me are the three big trends. And I do believe that software defined distributed architecture are necessary for these trends but you also need to think about being truly enterprise grade. and that has been one of our focus with design of Artesca. How do we combine a lightweight product with all of the security requirements and data sovereignty requirements that we expect to have in the next thing? >> That's awesome. Congratulations on the news Scality, Artesca. The big release with HPE exclusive for six months, Chris Tinker, Distinguished Engineer at HPE. Great to see you Jerome Lecat CEO of Scality, great to see you as well. Congratulations on the big news. I'm John Furrier from theCube. Thanks for watching. (uplifting music)

>> Narrator: From around the global its theCUBE, covering HPE Discover Virtual Experience, brought to you by HPE. >> Hi, I'm Stu Miniman and this is theCUBE's coverage of HPE, discover the virtual experience for 2020, getting to talk to Hp executives, their partners, the ecosystem, where they are around the globe, this session we're going to be digging in about artificial intelligence, obviously a super important topic these days. And to help me do that, I've got two guests from Nvidia, sitting in the window next to me, we have Paresh Kharya, he's director of product marketing and sitting next to him in the virtual environment is Kevin Deierling, who is this senior vice president of marketing as I mentioned both with Nvidia. Thank you both so much for joining us. >> Thank you, so great to be here. >> Great to be here. >> All right, so Paresh when you set the stage for us? AI, obviously, one of those mega trends to talk about but just, give us the stages, where Nvidia sits, where the market is, and your customers today, that they think about AI. >> Yeah, so we are basically witnessing a massive changes that are happening across every industry. And it's basically the confluence of three things. One is of course, AI, the second is 5G and IOT, and the third is the ability to process all of the data that we have, that's now possible. For AI we are now seeing really advanced models, from computer vision, to understanding natural language, to the ability to speak in conversational terms. In terms of IOT and 5G, there are billions of devices that are sensing and inferring information. And now we have the ability to act, make decisions in various industries, and finally all of the processing capabilities that we have today, at the data center, and in the cloud, as well as at the edge with the GPUs as well as advanced networking that's available, we can now make sense all of this data to help industrial transformation. >> Yeah, Kevin, you know it's interesting when you look at some of these waves of technology and we say, "Okay, there's a lot of new pieces here." You talk about 5G, it's the next generation but architecturally some of these things remind us of the past. So when I look at some of these architectures, I think about, what we've done for high performance computing for a long time, obviously, you know, Mellanox, where you came from through NVIDIA's acquisition, strong play in that environment. So, maybe give us a little bit compare, contrast, what's the same, and what's different about this highly distributed, edge compute AI, IOT environment and what's the same with what we were doing with HPC in the past. >> Yeah, so we've--Mellanox has now been a part of Nvidia for a little over a month and it's great to be part of that. We were both focused on accelerated computing and high performance computing. And to do that, what it means is the scale and the type of problems that we're trying to solve are just simply too large to fit into a single computer. So if that's the case, then you connect a lot of computers. And Jensen talked about this recently at the GTC keynote where he said that the new unit computing, it's really the data center. So it's no longer the box that sits on your desk or even in Iraq, it's the entire data center because that's the scale of the types of problems that we're solving. And so the notion of scale up and scale out, the network becomes really, really critical. And we're doing high-performance networking for a long time. When you move to the edge, instead of having, a single data center with 10,000 computers, you have 10,000 data centers, each of which as a small number of servers that is processing all of that information that's coming in. But in a sense, the problems are very, very similar, whether you're at the edge or you're doing massive HPC, scientific computing or cloud computing. And so we're excited to be part of bringing together the AI and the networking because they are really optimizing at the data center scale across the entire stack. >> All right, so it's interesting. You mentioned, Nvidia CEO, Jensen. I believe if I saw right in there, he actually could, wrote a term which I had not run across, it was the data processing unit or DPU in that, data center, as you talked about. Help us wrap our heads around this a little bit. I know my CPU, when I think about GPUs, I obviously think of Nvidia. TPUs, in the cloud and everything we're doing. So, what is DPUs? Is this just some new AI thing or, is this kind of a new architectural model? >> Yeah. I think what Jensen highlighted is that there's three key elements of this accelerated disaggregated infrastructure that the data center has becoming. And so that's the CPU, which is doing traditional single threaded workloads but for all of the accelerated workloads, you need the GPU. And that does massive parallelism deals with massive amounts of data, but to get that data into the GPU and also into the CPU, you need really an intelligent data processing because the scale and scope of GPUs and CPUs today, these are not single core entities. These are hundreds or even thousands of cores in a big system. And you need to steer the traffic exactly to the right place. You need to do it securely. You need to do it virtualized. You need to do it with containers and to do all of that, you need a programmable data processing unit. So we have something called our BlueField, which combines our latest, greatest, 100 gig and 200 gig network connectivity with Arm processors and a whole bunch of accelerators for security, for virtualization, for storage. And all of those things then feed these giant parallel engines which are the GPU. And of course the CPU, which is really the workload at the application layer for non-accelerated outs. >> Great, so Paresh, Kevin talked about, needing similar types of services, wherever the data is. I was wondering if you could really help expand for us a little bit, the implications of it AI at the edge. >> Sure, yeah, so AI is basically not just one workload. AI is many different types of models and AI also means training as well as inferences, which are very different workloads or AI printing, for example, we are seeing the models growing exponentially, think of any AI model, like a brain of a computer or like a brain, solving a particular use case a for simple models like computer vision, we have models that are smaller, bugs have computer vision but advanced models like natural language processing, they require larger brains or larger models, so on one hand we are seeing the size of the AI models increasing tremendously and in order to train these models, you need to look at computing at the scale of data center, many processors, many different servers working together to train a single model, on the other hand because of these AI models, they are so accurate today from understanding languages to speaking languages, to providing the right recommendations whether it's for products or for content that you may want to consume or advertisements and so on. These models are so effective and efficient that they are being powered by AI today. These applications are being powered by AI and each application requires a small amount of acceleration, so you need the ability to scale out or, and support many different applications. So with our newly launched MPR architecture, just couple of weeks to go that Jensen announced, in the virtual keynote for the first time, we are now able to provide both, scale up and scale out both training data analytics as well as imprints on the single architecture and that's very exciting. >> Yeah, so look at that. The other thing that's interesting is you're talking about at the edge and scale out versus scale up, the networking is critical for both of those. And there's a lot of different workloads. And as Paresh was describing, you've got different workloads that require different amounts of GPU or storage or networking. And so part of that vision of this data center as the computer is that, the DPU lets you scale independently, everything. So you can compose, you desegregate into DPUs and storage and CPUs, and then you compose exactly the computer that you need on the fly container, right, to solve the problem that you're solving right now. So these new way of programming is programming the entire data center at once and you'll go grab all of it and it'll run for a few hundred milliseconds even and then it'll come back down and recompose itself onsite. And to do that, you need this very highly efficient networking infrastructure. And the good news is we're here at HPE Discover. We've got a great partner with HPE. You know, they have our M series switches that uses the Mellanox hundred gig and now even 200 and 400 gig ethernet switches, we have all of our adapters and they have great platforms. The Apollo platform for example, is break for HPC and they have other great platforms that we're looking at with the new telco that we're doing or 5G and accelerating that. >> Yeah, and on the edge computing side, there's the edge line set of products which are very interesting, the other sort of aspect that I wanted to touch upon, is the whole software stack that's needed for the edge. So edge is different in the sense that it's not centrally managed, the edge computing devices are distributed remote locations. And so managing the workflow of running and updating software on it is important and needs to be done in a very secure manner. The second thing that's, that's very different again, for the edges, these devices are going to require connectivity. As Kevin was pointing out, the importance of networking so we also announced, a couple of weeks ago at our GTC, our EGX product that combines the Mellanox NIC and our GPUs into a single a processor, Mellanox NIC provides a fast connectivity, security, as well as the encryption and decryption capabilities, GPUs provide acceleration to run the advanced DI models, that are required for applications at the edge. >> Okay, and if I understood that, right. So, you've got these throughout the HPE the product line, HPE's got long history of making, flexible configurations, I remember when they first came out with a Blade server it was, different form factors, different connectivity options, they pushed heavily into composable infrastructure. So it sounds like this is just a kind of extending, you know, what HP has been doing for a couple of decades. >> Yeah, I think HP is a great partner there and these new platforms, the EGX, for example that was just announced, a great workload there is a 5G telco. So we'll be working with our friends at HPE to take that to market as well. And, you know, really, there's a lot of different workloads and they've got a great portfolio of products across the spectrum from regular servers. And 1U, 2U, and then all the way up to their big Apollo platform. >> Well I'm glad you brought up telco, I'm curious, are there any specific, applications or workloads that, where the low hanging fruit or the kind of the first targets that you use for AI acceleration? >> Yeah, so you know, the 5G workload is just awesome. We're introduced with the EGX, a new platform called Ariel which is a programming framework and there were lots of partners there that were part of that, including, folks like Ericsson. And the idea there is that you have a software defined hardware accelerated radio area network, so a cloud RAM and it really has all of the right attributes of the cloud and what's nice there is now you can change on the fly, the algorithms that you're using for the baseband codex without having to go climb a radio tower and change the actual physical infrastructure. So that's a critical part. Our role in that, on the networking side, we introduced the technology that's part of EGX then are connected, It's like the DX adapter, it's called 5T for 5G. And one of the things that happens is you need this time triggered transport or a telco technology. That's the 5T's for 5G. And the reason is because you're doing distributed baseband unit, distributed radio processing and the timing between each of those server nodes needs to be super precise, 20 nanosecond. It's something that simply can't be done in software. And so we did that in hardware. So instead of having an expensive FPGA, I try to synchronize all of these boxes together. We put it into our NIC and now we put that into industry standard servers HP has some fantastic servers. And then with the EGX platform, with that we can build, really scale out software to client cloud RAM. >> Awesome, Paresh, anything else on the application side you'd like to add in just about what Kevin spoke about. >> Oh yeah, so from application perspective, every industry has applications that touch on edge. If you take a look at the retail, for example, there is, you know, all the way from supply chain to inventory management, to keeping the right stock units in the shelves, making sure there is a there is no slippage or shrinkage. So to telecom, to healthcare, we are re-looking at constantly monitoring patients and taking actions for the best outcomes to manufacturing. We are looking to automate production detecting failures much early on in the production cycle and so on every industry has different applications but they all use AI. They can all leverage the computing capabilities and high-speed networking at the edge to transform their business processes. >> All right, well, it's interesting almost every time we've talked about AI, networking has come up. So, you know, Kevin, I think that probably ease up a little bit why, Nvidia, spent around $7 billion for the acquisition of Mellanox and not only was it the Mellanox acquisition, Cumulus Networks, very known in the network space for software defined really, operating system for networking but give us strategically, does this change the direction of Nvidia, how should we be thinking about Nvidia in the overall network? >> Yeah, I think the way to think about it is going back to that data center as the computer. And if you're thinking about the data center as computer then networking becomes the back plane, if you will of that data center computer and having a high performance network is really critical. And Mellanox has been a leader in that for 20 years now with our InfiniBand and our Ethernet product. But beyond that, you need a programmatic interface because one of the things that's really important in the cloud is that everything is software defined and it's containerized now and there is no better company in the world then Cumulus, really the pioneer and building Cumulus clinics, taking the Linux operating system and running that on multiple homes. So not just hardware from Mellanox but hardware from other people as well. And so that whole notion of an open networking platform more committed to, you need to support that and now you have a programmatic interface that you can drop containers on top of, Cumulus has been the leader in the Linux FRR, it's Free Range Routing, which is the core routing algorithm. And that really is at the heart of other open source network operating systems like Sonic and DENT so we see a lot of synergy here, all the analytics that Cumulus is bringing to bear with NetQ. So it's really great that they're going to be part here of the Nvidia team. >> Excellent, well thank you both much. Want to give you the final word, what should they do, HPE customers in their ecosystem know about the Nvidia and HPE partnership? >> Yeah, so I'll start you know, I think HPE has been a longtime partner and a customer of ours. If you have accelerated workloads, you need to connect those together. The HPE server portfolio is an ideal place. We can combine some of the work we're doing with our new amp years and existing GPUs and then also to connect those together with the M series, which is their internet switches that are based on our spectrum switch platforms and then all of the HPC related activities on InfiniBand, they're a great partner there. And so all of that, pulling it together, and now as at the edge, as edge becomes more and more important, security becomes more and more important and you have to go to this zero trust model, if you plug in a camera that's somebody has at the edge, even if it's on a car, you can't trust it. So everything has to become, validated authenticated, all the data needs to be encrypted. And so they're going to be a great partner because they've been a leader and building the most secure platforms in the world. >> Yeah and on the data center, server, portfolio side, we really work very closely with HP on various different lines of products and really fantastic servers from the Apollo line of a scale up servers to synergy and ProLiant line, as well as the Edgeline for the edge and on the super computing side with the pre side of things. So we really work to the fullest spectram of solutions with HP. We also work on the software side, wehere a lot of these servers, are also certified to run a full stack under a program that we call NGC-Ready so customers get phenomenal value right off the bat, they're guaranteed, to have accelerated workloads work well when they choose these servers. >> Awesome, well, thank you both for giving us the updates, lots happening, obviously in the AI space. Appreciate all the updates. >> Thanks Stu, great to talk to you, stay well. >> Thanks Stu, take care. >> All right, stay with us for lots more from HPE Discover Virtual Experience 2020. I'm Stu Miniman and thank you for watching theCUBE. (bright upbeat music)

>> Narrator: From around the globe its the Cube, covering HPE Discover Virtual Experience brought to you by HPE. >> Hi everybody this is Dave Vellante and welcome back to the Cube's coverage of HPE's Discover 2020 the Virtual Experience the Cube. The Cube has been virtualized We like to say Am very happy to welcome in Neil McDonalds, he's the General Manager for Compute at HPE. Great to see you again Neil, wish we were face to face, but this will have to do. >> Very well, it's great to see you Dave. Next time we'll do this face to face. >> Next time we have hopefully next year. We'll see how things are going, but I hope you're safe and your family's all good and I say it's good to talk to you, you know we've talked before many times you know, it's interesting just to know the whole parlance in our industry is changing even you know Compute in your title, and no longer do we think about it as just sort of servers or a box you guys are moving to this as a service notion, really it's kind of fundamental or, poignant that we see this really entering this next decade. It's not going to be the same as last decade, is it? >> No, I think our customers are increasingly looking at delivering outcomes to their customers in their lines of business, and Compute can take many forms to do that and it's exciting to see the evolution and the technologies that we're delivering and the consumption models that our customers are increasingly taking advantage of such as GreenLake. >> Yes so Antonio obviously in his Keynote made a big deal in housing previous Keynotes about GreenLake, a lot of themes on you know, the cloud economy and as a service, I wonder if you could share with our audience, you know what are the critical aspects that we should know really around GreenLake? >> Well, GreenLake is growing tremendously for us we have around a thousand customers, delivering infrastructure through the GreenLake offerings and that's backed by 5,000 people in the company around the world who are tuning an optimizing and taking care of that infrastructure for those customers. There's billions of dollars of total contract value under GreenLake right now, and it's accelerating in the current climate because really what GreenLake is all about is flexibility. The flexibility to scale up, to scale down, the ability to pay as you use the infrastructure, which in the current environment, is incredibly helpful for conserving cash and boosting both operational flexibility with the technology, but also financial flexibility, in our customer's operations. The other big advantage of course at GreenLake is it frees up talent most companies are in the world of challenges in freeing up their talent to work on really impactful business transformation initiatives, we've seen in the last couple of quarters, an even greater acceleration of digital transformation work for example and if all of your talent is tied up in managing the existing infrastructure, then that's a drain on your ability to transform and in some industries even survive right now, so GreenLake can help with all of those elements and, with all of the pressure from COVID, it's actually becoming even more consumed, by more and more customers around the world it's- >> Yeah right I mean that definitely ties into the whole as a service conversation as well I mean to your point, you know, digital transformation you know, the last couple of years has really accelerated, but I feel yeah, I feel like in the last 90 days, it's accelerated more than it has in the last three years, because if you weren't digital, you really had no way to do business and as a service has really played into that so I wonder if you could talk about yours as a service, you know, posture and thinking. >> Well you're absolutely right Dave organizations that had not already embarked on a digital transformation, have rapidly learned in our current situation that it's not an optional activity. Those that were already on that path are having to move faster, and those that weren't are having to develop those strategies very rapidly in order to transform their business and to survive. And the really new thing about GreenLake and the other service offerings that we provide in that context is how it can accelerate the deployment. Many companies for example, have had to deal with VDI deployments in order to enable many more of their workforce to be productive when they can't be in the office or in the facility and a solution like GreenLake can really help enable very rapid deployment and build up but not just VDI many other workloads in high performance Compute or in SAP HANA for example, are all areas that we're bringing value to customers through that kind of as a service offering. Yeah, a couple of examples Nokia software is using GreenLake to accelerate their research and development as they drive the leadership and the 5G revolution, and they're doing that at a fraction of the cost of the public cloud. We've got Zanotti, which has built a private cloud for artificial intelligence and HPC is being used to develop the next generation of autonomous software for cars. And finally, we've got also Portion from Arctic who have built a fully managed hybrid cloud environment to accelerate all the application development without having to bear the traditional costs of an over-provisioned complex infrastructure. So all of our customers are relying on that because Compute and Innovation is just at the core of the digital transformations that everybody is embarked on as they modernize their businesses right now and it's exciting to be able to be part of that and to be able to do there, to help. >> So of course in the tech business innovation is the you know the main spring of growth and change, which is constant in our industry and I have a panel this week with Doctor Go talking about swarm learning in AI, and that's some organic innovation that HPE is doing, but as well, you've done some, M&A as well. Recently, you guys announced and we covered it a pretty major investment in Pensando Systems. I wonder if you could talk a little bit about what, that means to the Compute business specifically in, HPE customers generally. >> So that partnership with Pensando was really exciting, and it's great to see the momentum that its building in delivering value to our customers, at the end of the day we've been successful with Pensando in building that momentum in very highly regulated industries and the value that is really intrinsic to Pensando is the simplifying of the network architecture. Traditionally, when you would manage an enterprise network environment, you would create centralized devices for services like load balancing or firewalls and other security functionality and all the traffic in the data center would be going back and forth, tromboning across the infrastructure as you sought to secure your underlying Compute. The beauty of the Pensando technology is that we actually push that functionality all the way out to the edge at the server so whether those servers are in a data center, whether they're in a colocation facility, whether they're on the edge, we can deliver all of that security service that would traditionally be required in centralized expensive, complex, unique devices that were specific to each individual purpose, and essentially make that a software defined set of services running in each node of your infrastructure, which means that as you scale your infrastructure, you don't have a bottleneck. You're just scaling that security capability with the scaling of your computer infrastructure. It takes traffic off your core networks, which gives you some benefits there, but fundamentally it's about a much more scalable, responsive cost-efficient approach to managing the security of the traffic in your networks and securing the Compute end points within your infrastructure. And it's really exciting to see that being picked up, in financial services and healthcare, and other segments that have you know, very high standards, with respect to security and infrastructure management, which is a great complement to the technology from Pensando and the partnership that we have with Pensando and HPE. >> And it's compact too we should share with our audience it's basically a card, that you stick inside of a server correct Neil? >> That's exactly right. Pensando's PCIe card together with HPE servers, puts that security functionality in the server, exactly where your data is being processed and the power of that is several fold, it avoids the tromboning that we talked about back across the whole network every time you've got to go to a centralized security appliance, it eliminates those complex single purpose appliances from the infrastructure, and that of course means that the failure domain is much smaller cause your failure demands a single server, but it also means that as you scale your infrastructure, your security infrastructure scales with the servers. So you have a much simpler network architecture, and as I say, that's being delivered in environments with very high standards for security, which is a really a great endorsement of the Pensando technology and the partnership that HPE and Pensando will have in bringing that technology to market for our customers. >> So if I understand it correctly, the Pensando is qualified for Pro-Lite, Appollo and in Edgelines. My question is, so if I'm one of those customers today, what's in it for me? Are they sort of hopping on this for existing infrastructure, or is it part of, sort of new digital initiatives, I wonder if you could explain. >> So if you were looking to build out infrastructure for the future, then you would ask yourself, why would you continue to carry forward legacy architectures in your network with these very expensive custom appliances for each security function? Why not embrace a software defined approach that pushes that to the edge of your network whether the edge are in course or are actually out on the edge or in your data centers, you can have that security functionality embedded within your Compute infrastructure, taking advantage of Pensandos technologies. >> So obviously things have changed is specifically in the security space, people are talking about this work from home, and this remote access being a permanent or even a quasi-permanent situation. So I wonder if we could talk about the edge and specifically where Aruba fits in the edge, how Pensando compliments. What's HPE's vision with regard to how this evolves and maybe how it's been supercharged with the COVID pandemic. >> So we're very fortunate to have the Aruba intelligent edge technology in the HPE portfolio. And the power of that technology is its focus on the analysis of data and the development of solutions at the site of the data generated. Increasingly the data volumes are such that they're going to have to be dealt with at the edge and given that, you need to be building edge infrastructure that is capable enough and secure enough for that to be the case. And so we've got a great compliment between the, intelligent edge technology within the Aruba portfolio, with all of the incredible management capabilities that are in those platforms combined with technologies like Pensando and our HPE Compute platforms, bring the ability to build a very cohesive, secure, scalable infrastructure that tackles the challenges of having to do this computer at the edge, but still being able to do it in both a secure and easily managed way and that's the power of the combination of Aruba, HPE Compute and Pensando. >> Well, with the expanded threat surface with people working from home organizations are obviously very concerned about compliance, and being able to enforce consistent policies across this sort of new network, so I think what you're talking about is it's very important that you have a cohesive system from a security standpoint you're not just bolting on some solution at the tail end, your comments. >> Well security, always depends on all the links in the chain and one of the most critical links in the chain is the security of the actual Compute itself. And within the HPE compliant platforms, we've done a lot of work to build very differentiated and exclusive capability with our hardware, a Silicon Root of Trust, which is built directly into Silicon. And that enables us to ensure the integrity of the entire boot chain on the security of the platform, drones up in ways that can't be done with some of the other hardware approaches that are prevalent in the industry, and that's actually brought some benefit, in financial terms to our customers because of the certifications that are enabled in the, Cyber Catalyst designations that we've earned for the platforms. >> So we also know from listening to your announcements with Pensando just observing security in general, that this notion of micro-segmentation is very important being able to have increased granularity as opposed to kind of a blob, maybe you could explain why that's important you know, the so what behind micro-segmentation if you will. >> Well it's all about minimizing the threat perimeter on any given device and if you can minimize the vectors through which your infrastructure will interact on the network, then you can provide additional layers of security and that's the power of having your security functionality right down at the edge, because you can have a security processor sitting right in the server and providing great security of the node level you're no longer relying on the network management and getting all of that right and you also have much greater flexibility because you can easily in a software defined environment, push the policies that are relevant for the individual pieces of infrastructure in an automated policy driven way, rather than having to rely on someone in network security, getting the manual configuration of that infrastructure, correct to protect the individual notes. And if you take that kind of approach, and you embed that kind of technology in servers, which are fundamentally robust in terms of security because of the Silicon Root of Trust that we've embedded across our platform portfolio whether that's Pro-line or Synergy or BladeSystem or Edgeline, you get a tremendous combination, as a result of these technologies, and as I mentioned, the being Cyber Catalyst designation is a proof point of that. Last year there we're over 150 security products, put forward for the Sovereign Capitalist designation, and the only a handful were actually awarded I think 17, of which two were HPE Compute and Aruba. And the power of is that many organizations are not having to deal with insurance for Cybersecurity events. And the Catalyst designation can actually lead to lower premiums for the choice of the infrastructure that you've made to such as HPE Compute, has actually enabled you to have a lower cost of insuring your organization against cybersecurity issues, because infrastructure matters and the choice of infrastructure with the right innovation in it is a really critical choice for organizations moving forward in security and in so many other ways. >> Yeah, you mentioned a lot of things there software defined, that's going to enable automation and scale, you talked about the perimeter you know, the perimeter of the traditional moat around the castle that's gone the perimeter, there is no perimeter anymore, it's everywhere so that whole you know, weakest link in the chain and the chain of events. And then the other thing you talked about was the layers you know very important when you're talking to security practitioners you know, building layers in so all of this really is factoring in security in particular, is factoring into customer buying decisions. Isn't it? >> Well security is incredibly important for so many of our customers across many industries. And having the ability to meet those security needs head on is really critical. We've been very successful in leveraging these technologies for many customers in many different industries, you know, one example is we've recently won multiple deals with the Defense Intelligence Systems Agency, who you will imagine have very high standards for security, worth hundreds of millions of dollars of that infrastructure so there's a great endorsement, from the customer set who are taking advantage of these technologies and finding that they deliver great benefits for them in the operational security of their infrastructure. >> Yeah what if I could ask you a question on the edge. I mean, as somebody who is you know, with a company that is really at the heart of technology, and I'm sure you're constantly looking at new companies, M&A you know et cetera, you know inventing tech, but I want to ask you about the architectures for the edge and just in thinking about a lot of data at the edge, not all the data is going to come back to the data center or the cloud, there's going to be a lot of AI influencing going on in real time or near real time. Do you guys see different architectures emerging to support that edge? I mean from a Compute standpoint or is it going to be traditional architectures that support that. >> It's clearly an evolving architectural approach because for the longest time, infrastructure was built with some kind of hub you know, whether or not some data center or in the cloud, around all of the devices at the edge would be essentially calling home, so edge devices historically have been very focused on connectivity on acquisition of data, and then sending that data back for some kind of processing and action at some centralized location. And the reality is that given the amount of data being generated at the edge now given the capability even of the most modern networks, it's simply not possible to be moving those kinds of data volumes all the way back to some remote processing environment, and then communicating a decision for action all the way back up to the edge. First of all, the networks kind of handle the volume data's involved if every device in the world was doing that, and secondly, the latencies are too slow. They're not fast enough in order to be able to take the action needed at the edge. So that means that you have to countenance systems at the edge that are not actually storing data, that are not actually computing upon data, and in a lot of edge systems historically, they would evolve from very proprietary, very vertically integrated systems to Brax PC controller based systems with some form of IP connectivity back to, some central processing environment. And the reality is that if you build your infrastructure that way, you finish up with a very unmanageable fleet, you finish up with a very fragmented, disjointed infrastructure and our perspective is that companies that are going to be successful in the future have to think themselves as an edge to cloud approach. They have to be pursuing this in a way that views, the edge, the data center, and the cloud as part of an integrated continuum, which enables the movement of data when needed you heard about the swarm learning that you talked about with my colleague Doctor Go, where there's a balance of what is computed, where in the infrastructure, and so many other examples, but you need to be able to move Compute to where the data is, and you need to be able to do that efficiently with a unified approach to the architecture. And that's where assets like the HPE Data Fabric come into play, which enable that kind of unification across the different locations of equipment. It also means you need to think differently about the actual building blocks themselves, in a lot of edge environments, if you take a Classic 19 interact mode Compute device, that was originally designed for the data center it's simply not the right kind of infrastructure. So that's why we have offerings like the Edgeline portfolio and the HPE products there, because they're designed to operate in those environments with different environmentals than you find the data center with different interfaces to systems of action and systems of control, than you'd typically find in a data center environment yet still bringing many of the security benefits and the manageability benefits that we've talked about earlier in our conversation today Dave. So it's definitely going to be an evolving, a new architectural approach at the edge, and companies that are thoughtful about their choice of infrastructure, are going to be much more successful than those that take a more incremental approach, and we were excited to be there to help our customers on that journey. >> Yeah Neil it's a very exciting time I mean you know, much of the innovation in the last decade was found inside the data center and in your world a lot of times you know, inside the server itself but what you're describing is this, end-to-end system across the network and that systems view, and then there's going to be a ton of innovation there and we're very excited for you thanks so much for coming on the Cube it was great to see you again. >> It is great to be here and we're just excited to be here to help our customers, and giving them the best volume for the workloads whether that's taking advantage of GreenLake, taking advantage of the innovative security technologies that we've talked about, or being the edge to cloud platform as a service company that can help our customers transform in this distributed world from the edge to the data center to the cloud. Thanks for having me Dave. >> You very welcome, awesome summary and its always good to see you Neil. Thank you for watching everybody this David Vellante, for the Cube our coverage of the HPE Discover 2020 Virtual Experience, will be right back to the short break. (soft upbeat music)

>> From the SiliconANGLE Media Office in Boston, Massachusetts, it's The Cube! Now, here's your host, Dave Velante. >> We're back with Patrick Osborne. All right Patrick, we've been talking about how customers want to be data-driven, they're doing digital transformation, they want to put data at the core of the enterprise. All sounds good. What's your strategy as HPE in terms of helping them get there? >> Yeah so, for our customers, this is a common theme, right. Some feel that they're going to be disrupted, they've been disrupted, right, and one of the key threads that runs through that is that they want to get more AI driven, right, so they want to use analytics as a way to provide new services around their products, get these services out faster, be able to use all that data they have in their enterprise. So for us, it's being able to have that conversation of whether the data sits out in the edge, right, you guys are very familiar with our Edge strategy, using Edgeline and Aruba, our core infrastructure in the data center, which we've had-- for a long history of helping customers with that, and then more recently around Hybrid Cloud, right, so most of the products, services, experiences we have there have Hybrid Cloud built in from the ground up. So for us, all those conversations have to do with data. >> So you recently made an acquisition of BlueData. >> Correct. >> What was that all about? Was that your AI play? Was it a software-as-a-service play? Explain that. >> Yeah, certainly a little bit of both. BlueData's a fantastic platform and it allows you to virtualize, containerize the application, so we know that in the market, you've got mode one applications, you've got mode two applications, a lot of mode one apps, you know, business applications, mission critical applications, have been virtualized. But what we also see is that a lot of the new product development is around these mode two applications that are using things like big data, whether it's a dupe in H-D-F-S, fast data - some of the streaming services - and now you're doing things around A-I inferencing, modeling, all using essentially containers as a way to do that, fuel that application development. So when we saw BlueData, it's essentially a platform to be able to virtualize all of these container-based applications. And as customers, big data and analytics and A-I platforms and their pipeline gets bigger and more complicated, it allows us to, A) manage that, increase their time to value, unlock a lot of the resources on the data scientists side, right, who have the responsibility of managing all of those applications, and it's a really great platform, great people, right, so they have a team of data scientists to be able to help customers implement this, not only within the product but within their own enterprise. And then we've got some really, really big logos that we're going to build off of for the BlueData ecosystem. >> So things are moving very fast. You've got all this data, you're applying machine intelligence and quickly moving from a world that was all batch to one that's real time, and we blinked and real time flew by. Now you've got this machine intelligence world where systems are acting, they're sensing, they're hearing, they're smelling... >> Yup. >> And so, is that what you're seeing with customers? Are they trying to build these sort of new systems that will act on their behalf? >> Absolutely. We see it on our own. If you take a look at some of our strategy, as HPE, especially within our storage and big data division, one of the big things that we're doing is introducing all of our products with the capability of A-I ops, right. And so all of our products that go out the door, using platforms like Infosite, will have this A-I ops capability to, not only just start with support automation, predictive analytics, and now you've got predictive A-I driving the actual management experience of these products. And it lets our customers ultimately unlock those resources that were doing mundane, repeatable tasks to focus on where they're going to add value. >> So I got to ask you, you guys do-- obviously a lot of your revenue comes from indirect channels. So you've seen the cloud, the cloud is not about selling boxes anymore, now you're seeing all this machine intelligence and automation. What does all this mean for partners? Where's the opportunity for those guys? >> Yeah so, I would say that when we go and make an acquisition like Blue Data, it's a great, like we said before, it's a great product, it's a good platform, right, they've got great engineers and great people within the organization and certainly some big logos. The reason why they got those logos was partly based on the product, but it's also a very services led methodology. So for-- I'd say for our partner community, being able to do discovery services, to understand what they're requirements are, a lot of folks that use BlueData and these type of platforms are builders. They're building a platform that has services on it for their end user customers. So being able to gather those requirements, do implementation, certainly be able to take a lot of this dynamic application ecosystem that is either very new, it's nascent, when you take a look at A-I or it's even in the open source arena, being able to de-risk that for the customers, from a services perspective, is a huge opportunity. >> Okay, great, so that's exciting because it's new frontier for those folks. So think about HPE, the tech that you guys have, the partner opportunity that you just described, how are you going to change the life of a data scientist? And maybe we could add in some other personas as well. >> Yeah, so, as a lot of our customers and partners certainly know, data scientists don't grow on trees, right, and they're very important folks within these large organizations, right, so you want to unlock their capabilities. So for us at the end of the day, we're trying to have a platform and as a service experience around A-I that unlocks the value of these data scientists. So for example, if I have a production environment or a U-A-T or a test dev environment, I can very quickly spin up your entire toolchain as a data scientist, right, so your toolchain, your models, your H-D-F-S data lakes, you can tap into existing data lakes, all of my streaming data, Kafka, Spark, all this stuff, very dynamic ecosystem, complex application dependencies. What I can do is I can sandbox that, I can test it, I can iterate, and I can very, very quickly provide that type of environment for your developers and your data scientists (snaps) just like that. >> So, in addition to the data scientist, is the chief data officer somebody that you guys are interacting with? There's also the application developer. Are you trying to sort of effect this collaboration amongst those different roles and personas? >> Yeah I think one of the greatest things for the partners and we've seen this at HPE too, is that you're going to be calling on new buyer personas. Right, so in the case of infrastructure, working a lot with enterprise architects, data center manager, infrastructure manager, C-I-O. In the case of BlueData and some of these A-I and analytics projects, right, you're at the front of the budget cycle, right, so you're talking to line of business, application developers, data scientists, analytics team, and now the rise of the C-D-O, the chief data officer. So you not only get to establish value with the infrastructure team, who are going to have to support this, right, you're going to go make some new friends and be able to get on the front of the budget cycle with a whole new set of buyer personas, and I think that's very exciting for partners. >> So, we talk a lot about A-I and, sort of this machine learning environment, machine intelligence. Software-defined is a hot topic. It's kind of a buzzword but it has meaning. What does it mean to you? Where does it fit in this whole equation? >> It's very adjacent to the big data and A-I analytics conversation. I think that what we see in software-defined, it's heavy on scale, right, so now that you're into petabytes, tens of petabytes, hundreds of petabytes, scaling, scaling, scaling, you need some new architectures to be able to do that cost-effectively. And you think about automated cars for example. They're-- each car is spinning off terabytes of data a day, so think about how am I going to store that, it's a monumental task. You got scale on your mind, you also have automation, right, so not only the scale of being able to store that effectively from a price-point, to be able to automate that. So you want to keep your-- the folks who are managing that infrastructure, they're going to have to increase the amount of systems, capacity under management, and the only way you can achieve that is through automation. And so, we see some themes around that and software-defined is really, kind of stepping in in that angle where you've got N-V-M-E, S-S-Ds, can saturate-- two N-V-M-E can saturate a C-P-U at this point, right, and now you're moving to hundred gig fabrics, so this rack-scale architecture that you can provide and paint on different software-defined personalities onto it is something that customers are definitely leaning in towards right now. >> And what you've been describing-- you mentioned autonomous vehicles-- data's at the edge, it's at the core, it's everywhere, and so, easier to bring, maybe, let's call it, ten meg of code to a petabyte of data than the reverse. >> Yeah, and what we see too is customers want to-- they want to dip their toe in this water, right, starting with very large enterprises, and we're able to, as HPE, bring a vetted ecosystem, whether from a workload perspective, 'cause we always talk about follow the workload, in software-defined, if you need something like scale-out file for A-I workloads, or you need scale-out file for more of a high performance, capacity-driven architecture, you're looking for object storage, you're looking for hyper-converged secondary, right, we bring an ecosystem of partners running on our infrastructure that's scalable, automated, and customers can feel confident in. >> Awesome. Well thank you Patrick, love the story. >> Yeah, thank you so much. >> You're welcome. (upbeat music)

>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Velante. >> Hi everybody, this is Dave Velante. Welcome to this special CUBE Conversation. Years ago, large computer companies would set up shop, direct sales, in NFL cities. Well, that's changed quite dramatically and there's been a lot of other changes. We're moving from a world of pure box selling to where partners and channel partners are adding value in new ways, and the cloud has really accelerated that move with focus on things like security and infrastructure value added, and other factors that can bring margin for the channel partners. We're here to talk about that with Terry Richardson, who is the vice president of North America Channels and Alliances at Hewlett-Packard Enterprise. Terry, thanks for coming on theCUBE. >> Thanks for having me Dave. Pleasure to be here. >> So I was saying up front how things have changed a lot in the channel. We're kind of moving from a box selling mentality to a value add. Is that accurate? What's happening in the channel? What are really the market trends? So I think that's absolutely accurate. There's really three things happening simultaneously. Vendors like HPE are transforming, channel partners themselves are transforming, and customers are transforming. And for the first time, at least in my career, over three decades in this industry, it's all happening simultaneously. So with respect to the partners, their business is absolutely needing to shift from one that's product centric to one that's much more software and services centric. In order to continue to be the trusted advisor to their customers, they need to evolve and deliver solutions to customers that are addressing today's business problems. >> And channel partners have always been very customers focused, very close to the customers, they have intimate relationships with them. So when you talk about the customers transforming, everybody talks about digital transformation, it sounds like a big buzzword, but every company you go to is trying to get digital right, aren't they? >> They're trying to get digital right either to take advantage of market opportunity leadership, or frankly because of the threat of being disrupted and playing defense, and so they're absolutely focused on their own transformations. And it's hard because most customers IT budgets are locked up in just running the infrastructure they have today, and they're trying to figure out a way to innovate and bring on new applications that can be revenue drivers or allow them to compete in new and different ways, and it's difficult to get that balance right. And so partners play a critical role in advising how clients can achieve their goals in the constraints of the budgets they have today. >> And so from an infrastructure standpoint, the applications and data have traditionally been locked and loaded and hardened in these silos, which was kind of the right thing to do when you wanted to optimize on availability and reliability and security. But now people wanna share data across the enterprise, with partners, there's no more perimeter, and that's a real challenge for customers from an infrastructure perspective, isn't it? >> Right, and the way that not only vendors like HPE but our partners address their client needs, it's rapidly changing. In reality, to use a term that I've heard in the past, applications follow data, and infrastructure follows applications. So you really need to understand what the clients intended outcome is, and what are the business objectives that they're trying to achieve, and that will allow you to focus more on workloads and applications, which ultimately will lead to an infrastructure sale, but starting with infrastructure is the wrong way to do it. >> Let's talk about some of the channel concerns. Obviously the channel wants to make margins, they want a partner that's not gonna head fake them, and change the rules of the game, and they want to work with a leader. Talk about what you're hearing from channel partners. What are their major concerns today? Is it cloud taking over their business? Is it the things I just mentioned? Elaborate. >> I think you hit on a few. Certainly, cloud is an an enabler for some customers in some ways, but it's a potential disruptor to channel partners. And their business has to morph to take advantage of what the cloud brings and position themselves not to be disrupted by it. So that's certainly a change in partners, and the other thing that partners are struggling with is how do they keep their technical talent, not only how do they retain the talent, but how do they acquire the requisite skills that are necessary for today's market demands? And just having a strong set of network engineers, or security experts, or storage resources is frankly not enough. Now you're looking at people with DevOps skills, and people that really know how to architect the 2.0 and 3.0 solutions for customers today. So that retaining, acquiring, and ultimately training that technical talent becomes a real challenge, and then of course finding salespeople that can sell in a solution centric manner as opposed to a product centric manner, is also a challenge. >> So, Terry, how specifically is HPE addressing those concerns with partners? >> So, a couple ways, the cloud becomes an enabler, right? One of the premises of our overriding business strategy is around making hybrid IT simple for customers. So part of that is acknowledging that public clouds have a place. There'll be workloads that are appropriate with SaaS providers, and helping the customer navigate what applications and data need to remain on-prem, and what should be in the cloud and how to manage that, and how to potentially move workloads from off-prem to on-prem and vice versa is really a challenge. But one of the big attractions when there was a race to the cloud, was a different way to consume technology. The public cloud providers made it very easy, kind of pay-as-you-go, pay-what-you-use, and so HPE innovated with a technology that we call GreenLake, which essentially offers the customer the same experience from a consumption standpoint, only pay for what you use, there's capacity available to meet peak requirements already on-site, but the customer has a very predictable way to pay for it, which we're starting to see real market traction. >> Yeah, we always talk about, on theCUBE, bringing the cloud experience to your data, wherever it lives, that's an example. When you talk about making hybrid IT simple, and of course I've heard this tagline from HPE for a while now, it's interesting because hybrid IT is anything but simple, so the channel partners must love that narrative, because they're part of making it simple. >> They're part of making it simple and we've actually extended our outreach to partners. We recently announced something called Tech Pro Community, which is a way to, we've outreached to all the technical constituents at our partner, it's actually around the globe, not just in North America. And we've created a community where we train our partner's technical resources exactly the same way we train our own engineers. So, they're consuming the same content in the same training sessions together, so it provides multiple benefits, not the least of which is building strong relationships, because we often see our technical resources and partner's technical resources collaborating in front of customers to deliver real world solutions. And that's important. >> You're essentially saying that's transparent to customers. They don't really see the difference or? >> Because the training is so substantially similar. So often times a partner may be in alone, completely representing HPE, often at times we're together, or they may be times where a partner doesn't have resources in a city, they may ask HPE to augment their own capabilities. >> So a partner, if they choose, can essentially white label your expertise and services? >> They absolutely can if they choose to do that, or the other end of the spectrum, if we allow partners partners to build services, practices, around our infrastructure. So if they choose to deliver their own services around our infrastructure, that's an option, too. >> I could see it going both ways. I could see partners wanting to draft off the HPE brand, I could see partners saying hey, we want the customer to just see us. >> Because that's part of their value prop to their customers. >> Is that unique in the marketplace, where you're able to give the partners that flexibility? I know, for instance, some vendors say no, it's our brand, and that brand, the color scheme, etc., has to be front and center. >> I don't think it's completely unique. What I think is unique is HPE continues to show itself, not only as being the vendor that is fully committed to the channel and have been for decades, but really showing the flexibility to adapt with the changing times. So we tend not to dictate, thou shalt do it this way, thou must do it this way. >> From a channel perspective, this is kind of an out in left field question, but it just popped in my head; when HPE split in two, and you guys focused on infrastructure, was that good news for the channel? Or was it harder for you as the channel partner because you got less in the bag to offer? >> I think it was a little bit of a mixed bag. It was initially harder for customers 'cause they now had to deal with two vendors instead of one, but I think the overwhelming benefit, it certainly played out with the success of our counterparts at HP Inc., that equity's done very well and the company's done terrific in the market, as has HPE. So, still a broad enough portfolio because we cover all the infrastructure elements from compute to storage networking and services, that's certainly enough to keep us busy and keep the partner's focused. >> And I would think that you're more focused as well. >> Absolutely. We're building deeper relationships with our partners, we're being focused and as we transition from selling products to delivering effective solutions to customers in this new hybrid world, and let's not ignore the opportunity at the edge, it really gives us an opportunity to really zero in on what the partners need in order to successfully scale their businesses. >> I'm glad you brought up the edge, because a couple misconceptions where the cloud was just going to take over and swipe a credit card and you don't have to worry about IT anymore, cloud brought a lot of complexities, particularly in terms of governance, security, data migration, >> Sovereignty. >> Sovereignty, right. Now you've got the edge which is kind of redefining what the cloud is all about. >> It's redefining, really, the definition of data center. >> Right. >> Right, because for many customers, what they're recognizing is with the technology advances, and the requirements on their business to make decisions with the data that's produced outside the data center at the edge, processing storage, analytics have to happen right there, real time. And then, it's really a booming part of the market, so we're starting to see partners that have historically been data center focused taking advantage of this redefinition of what the data center is, and how IT operations, and traditional systems and application vendors that operated outside the data center, are really now relevant in order to allow that customer to achieve their business objective. So it just kind of widens the opportunity for channel partners. >> In thinking about the edge, I know HPE was one of the first to really go hard after the edge in terms of starting to build an ecosystem in its early days, but I've talked to a number of HPE and ecosystem partners that are more IOT related or edge related. So, what does that mean for the partners? Are they able to tap into that ecosystem? Is it still too early? >> No, I think we're definitely in the earlier days, Dave, but partners are able to tack into the ecosystem. We have edge specific products on the server in compute and storage side, we have technologies that brand under the name Edgeline. We certainly have Aruba because wireless networking at the edge is a pervasive technology and the associated security and other software elements that the Aruba team brings. That's available now, and we've been on the forefront of forming new partnerships with entities that have relevant business applications to allow customers to complete their edge projects. And it's cutting across industry, so it's an exciting time on the one hand, on the other hand, it's putting pressure on the partners to learn yet something new, and like any business, you kind of have to make your bets, where you wanna invest, 'cause not all partners are gonna be expert in everything. >> Yeah, they gotta be careful about getting stretched too thin. At the same time, they want new opportunities that they can lean into. Alright, bring us home here. I'd love you to summarize why HPE, talk to the partners out there and explain to them, why HPE? >> Well, really I think it's a multifaceted set of reasons. I think number one, HPE is a vendor that you can trust. We've certainly earned that over more than three decades of being fully committed to the channel. We have invested in infrastructure, if you wanna take trust all the way to the customer, that we focus on security like nobody else, down to the silicon level. So there's real comfort in the solutions that HPE produces for clients and for partners to sell. We have a portfolio that's better than ever, and it's comprised really of three distinct elements. We continue to invest in R&D, so organic development innovation. We've done some really smart acquisitions that allow us to further deliver on our stated strategies. And we're approaching partnerships like never before. So, companies of all types, whether it's ISV software providers, global systems integrators, kind of everybody in between, and that technology partnership approach is allowing us to extend the portfolio. So partners have never had a better suite of offerings to provide to customers. We continue to have the industry's richest program when it comes to partner compensation, and we have increased commitment to sell with, co-sell with the channel. >> Well, Terry, partners are a critical part of the value chain, very clearly as I said before, a lot of intimate customer relationships, they gotta move fast to stay competitive. Thanks so much for coming to theCUBE and talking about some of these trends. >> Thanks for having me. >> You're welcome. Alright and thank you for watching, we'll see you next time. This is Dave Velante, you're watching theCUBE. (bright techno music)

>> Announcer: Live from Nashville, Tennessee, it's theCUBE, covering Commvault GO 2018. Brought to you by Commvault. >> Welcome back to Nashville, Tennessee, the home this week of Commvault GO with Keith Townsend. I'm Stu Miniman and you're watching theCUBE. Happy to welcome to the program a regular on our program, Patrick Osborne, who's the vice president and general manager of Big Data and secondary storage at Hewlett-Packard Enterprise. Patrick, great to you see. >> Great, thanks for having me. Love to be on theCUBE. Appreciate it. >> Yeah, so we've had you on theCUBE in lots of places, but a first in Nashville 'cause it's the first time we've been here. Keith's second time at the show, my first. What's your impression so far? >> Yeah, so this is our first major presence here at Commvault GO. I think it's going pretty well so far, certainly a great venue. We actually, we do a couple things here for our own presales folks. So first impressions, love the fact that we have a whole conference dedicated to secondary storage, certainly getting a lot of importance lately within customer conversations as well overall investment in the industry, so I'm pretty impressed, pretty lively crowd here. >> Yeah, I really liked, we started off the morning talking to Chris Powell, the CMO of Commvault, talking about how Commvault is a 20-year-old company, and therefore there were certain things that a 20-year-old company has. If you think about their pricing, you think about how people's perception of them are, you work at a company with plenty of history. HPE can partner with whomever they'd like to. >> Yep. >> Stu: Why's it important for HPE to partner with Commvault? >> Yeah, 20 years for Commvault, 78 for HPE, right, so we got a lot of chops there. For us, secondary storage is certainly becoming very important for customers, and it's being driven by new user stories, new capabilities centered around data. So what we look for is, as a technology company, we want to provide an entire solution, vertically oriented, that not only includes our compute networking, storage, secondary storage, cloud, but as well as a very vibrant ecosystem. So we've been working, certainly, with our customers and in the partner ecosystem with Commvault for a number of years, and now we've formalized that and codified it with a couple technology announcements, certainly on the go-to market side, and then some offerings we've done as a service, so backup as a service. >> So let's talk about some of these technology announcements. Talk to us about the significance of the store wants, Commvault integration. Got a great deduplication appliance the store wants, now you're bringing Commvault to the scene, to the solution. What advantage does that bring the customer, first off? >> Yeah, so we have a couple specific integrations we've done. We have our primary all-flash arrays, Nimble and 3PAR, certainly within the Intellus Map umbrella. We've worked with them in the past. We've worked with Commvault recently to deliver some support for our deduplication algorithms. We have our, what we call catalysts. It's the ability to dedupe anywhere, right, within the data center and even outside the data center. So they support that. It really helps out with, certainly, high-speed performance for backup so you can meet those aggressive SLAs. We feel like we've got pretty differentiated technology on the dedupe side, so it helps our customers save in terms of the storage that they have on disk. And then the other big thing is that they've also integrated with Cloudbank, right, so it's our ability to store archived backup data for very, very long periods of time in either Azure or out in Amazon, and essentially using Commvault as the workflow and the catalog, and being able to plug into the ability for us to federate primary, secondary in the cloud is a pretty powerful integration for customers who might already have HPE, might already have Commvault, so it definitely brings a lot of value into that. >> Yeah, Patrick, we've seen a real maturation of that, really, the multi-cloud model in the last couple of years. It seems like that's a foundational piece of the partnership between Commvault and HP. What are you hearing from customers, and what differentiates this solution from others in the market? >> Yeah, so I mean, I think that secondary storage is one that's always rife for having a multi-cloud storage, whether it's people just wanting to do something like I don't want a secondary data center, I want to use the cloud. I want to replace tape. There's a number of different reasons why. I think the differentiation part comes in the technology that I talked about before and making that very seamless for customers and being able to move workloads out to the public cloud for the purposes of long-term data retention. The other key thing is that we're providing this to customers in completely as a service style. So not only from a technology perspective, but the way you consume it now. So we're able to provide primary, secondary, your Commvault solution, the Azure capacity, for example, advisory services, and we're all able to package that up on a per-terabyte or a per-metric basis that customers consume in an elastic manner, like you would the cloud. >> Yeah, HP was one of the first, forgive me if I say legacy, 78-year-old company, people automatically assume companies like AWS and even Azure move that way, but where have you seen customers and their readiness, both from a people standpoint as well as a procurement model for that model, and as I've said, HPE's one of the first ones, the big traditional players, that helped push that model. >> Yeah, so the desire's there. We pitched this every day, ever week, and it's got a lot of legs from a customer interest perspective. We are transacting, and we'll start to build our business and it helps us financially as well, too, right? 'Cause for us to offer those as a service, that's a reoccurring revenue, it's bookings, it's not just your traditional CAPEX hardware acquisition. So it helps us. And a little known fact is that HPE Financial Services, when you talk about an established company, we have a very, very high Net Promoter Score for HPEFS, and that's one of the capabilities that allows us to provide these really, really granular, flexible services for our customers. We've got a lot of things going at HPE. Being a more established, mature company with a very large install base. Not only technology piece, but the financial aspects of it is something we can offer as well. >> Patrick, talk to me about some of the advantages as a service, from an agility perspective. When I think of consuming HPE physical hardware on-prem through HP Financial Services, and I'm consuming this as a service, how does that enable agility for your customers? >> Well, it enables agility in the financial model, number one, so a lot of customers are asking us for as a service, subscription models, moving from CAPEX to OPEX. And not just an OPEX lease, right, 'cause that doesn't count anymore. The rules are changing. So what we're able to do is we provide an actual service. The customer hands over the architecture reins to us, so we have an established methodology of how we implement this, so no snowflakes. We can build on a wealth of experience we have with a number of other customers to be able to essentially deliver a number of outcomes. So it comes very agile in the fact that at the end of the day, secondary storage, some of the user stories are pretty mundane. They're very repeatable, right? And so if you hand that over to us, we're able to help you with that, not only financially but architecturally, and from our operations perspective, and you can focus your talent that you have in your organization on differentiation for your business, right? 'Cause backups, maybe at the end of the day that's not where you're going to hang your hat on your digital transformation as a customer, but it's certainly something you need. So we could both partner together on making that a better experience. >> Stu: All right, go ahead. >> What I was going to ask, what's the interface? How do customers consume these as a service solutions, whether it's the secondary storage or if it's a service living in the cloud? >> Mm, so we have a number of examples of these. So you take a look at a service that we have, for example HPE Cloud Volumes, right? It has a portal, you log in, you can put your credit card in, you can add, let's say, your cloud credentials into that as well, and then you are essentially off and running on dollars per terabyte, and you can scale that up, you can scale that down. So at the end of the day, we're really trying to provide an experience for customers that's very similar to the public cloud. And I think the other area that we've done, we've made some acquisitions in the space, Cloud Technology Partners, RedPixie, Cloud Cruiser, so not only on the being able to use the consumption methodology and the metering that we provide, but also the advisory services, is something that you get from HPE. You actually get to talk to people that know how to do this and have done it before and can help you arbitrate and make you very successful. >> All right, so Patrick, the last 18 to 24 months, the secondary storage space has just been buzzing, almost frothy if you will. >> Yes. >> Commvault's been around for 20 years. Five years ago, there wasn't the excitement in the space. There's the startups, there's companies like Commvault and Veritas and Veen who have established a customer base in there. Why do you see so much excitement there? Is it the new AI of availability? I've got plenty of background in the storage industry, where just data is so critically important that it's right there. What do you see? >> I see it as a massive shift in thinking from TCO to ROI, right? Five years ago, you were having conversation as how can I do this as cheaply as possible, right? It's a non-differentiation life insurance policy at the end of the day. Now it's all about what can I do to maximize the return on that data? And it could be things that are not super sexy, but test verification, sandbox labs, being able to provide copies of data for your developers to get a better experience and a better quality experience for their customers at the end of the day. There's a number of things that we've been able to unlock in the secondary storage area, and some people call it copy data management, hyperconverged for secondary storage, I mean, there's lots of different names and nomenclatures applied to it. But it's essentially, from what I see, people unlocking the value of that data where it used to be captured, siloed, untouchable, but now you've unlocked a number of possibilities for this data, and it's multi-use, right? It's the new currency. >> Yeah, we always argue, at the show, Commvault's saying that data is the new water, but Dave Alante, well water often is a scarce resource and something we all have to fight for. Data, the ability to unlock the data, is we can use it multiple times in lots of different ways, and the more I use the data, the more valuable it is, not like traditional resources. >> Yeah, and also, too, some of the big bats you've seen from HPE, certainly big investment on edge-centric computing as well, too. So our Edgeline, the build out of 5G, certainly the ubiquitous wireless networks that we provide with Aruba. So there's a huge amount of capability of either moving the process outside the data center, but that data's still data. It needs to be protected, you need to be able to use it, so I think we're just getting started in some of these areas, certainly around secondary storage. >> So, let's talk about value that DotNext brings to the mix. We're talking about some pretty advanced use cases, the edge, the data center, the cloud. Stitching this together isn't quite simple. Tell us about the DotNext story and how they helped extend the capability beyond just throwing zeros and ones. >> I think there's a lot of our folks that cover customers, account teams, sales folks that really ensure our customer success, they view this area as very rife for certainly advisory services. I think one of the things is that having the capability of doing this, you guys have seen in the past couple years, people have scaled back dedicated storage admins, right? Dedicated backup admins, unless you're in a very large shop, really don't exist. You've moved towards essentially hypervisor admins, generalist, right? So I think that our capability is we have those services, we have that expertise in-house, and for us to be able to provide very good reference architectures that touch all parts of the stack, because secondary storage is, it's not just selling an all-flash array, or some capacity-optimized disk. It touches everything. It's questions around what's your SLA, what are the apps, what are you trying to do? So for us, we have a wealth of resources and knowledge in this space, and bringing in companies like Cloud Technology Partners and RedPixie into our services organization, that gives us the ability to help customers make that move to hybrid cloud as well, too, which is very important. >> Yeah, Patrick, the other message we're hearing loud and clear from Commvault is the roadmap. There's a lot of automation. There's the intelligence. You talk about all those admins. It was funny, they put up all these roles up on the board in the keynote this morning, and all of them, really, were bots (laughs) underneath. >> Yeah. (laughs) >> Automation can do that. Have us look forward. How does the HPE roadmap and the Commvault roadmap, how much synergy with those visions? >> Yeah, so right now we're definitely running along some parallel lines. They'd probably fire me if I didn't get off-stage here without talking about InfoSight, because it's a huge investment for us. We think it's a huge opportunity. You guys have seen the proof in the pudding from that in terms of automated support, we've got predictive analytics now. So for us, the more that you can build in from an AI and ML perspective, we think the value is in a couple area. Certainly cross stack, so going all the way from the app down through the infrastructure, and we're providing that through InfoSight. And then we're also expanding some of the use cases to include things like secondary storage, right? So if you see, let's say we have a signature that we can see, right? A certain IO pattern, right? We'll make some predictive calls to the infrastructure to say hm, that looks like Ransomware. Maybe you should take a full clone of that and then encrypt it and shove it up in the cloud. Or the change rate on your database just elevated two orders of magnitude. Maybe I should think about moving some workloads that are adjacent to that off that system. So as we expand those and then allow that type of workflow to enable our partners as well, too, you can see where that value would head as well, too, where you start to integrate some of the telemetry from HPE, telemetry from a vendor and ISV partner like Commvault. You could do some really powerful things across the stack. >> All right, last thing for you, Patrick. You're going to be on the keynote tomorrow. Show us a little bit for our audience here what to expect from HPE. >> We talked a little bit about today, we're going to focus our talk tomorrow on some of the new consumption models, as as a service, and we're certainly going to highlight some of the things that we've done so far in AI and ML, certainly making the lives of our storage and data customers a lot easier, and a little bit of a vision as to where we're going with both of those two. >> All right, well Patrick, always a pleasure to catch up with you. Thanks for joining us, and look forward to catching up at the next event. >> Thanks for having me. >> All right, for Keith Townsend, I'm Stu Miniman. We'll be back with more coverage here from Commvault GO here in Nashville, Tennessee. Thanks for watching theCUBE. (upbeat electronic music)

>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE! Now, here's your host, Dave Vellante. >> Hi, everybody, welcome to this special CUBE Conversation. You know, big data workloads have evolved, and the infrastructure that runs big data workloads is also evolving. Big data, AI, other emerging workloads need infrastructure that can keep up. Welcome to this special CUBE Conversation with Patrick Osborne, who's the vice president and GM of big data and secondary storage at Hewlett Packard Enterprise, @patrick_osborne. Great to see you again, thanks for coming on. >> Great, love to be back here. >> As I said up front, big data's changing. It's evolving, and the infrastructure has to also evolve. What are you seeing, Patrick, and what's HPE seeing in terms of the market forces right now driving big data and analytics? >> Well, some of the things that we see in the data center, there is a continuous move to move from bare metal to virtualized. Everyone's on that train. To containerization of existing apps, your apps of record, business, mission-critical apps. But really, what a lot of folks are doing right now is adding additional services to those applications, those data sets, so, new ways to interact, new apps. A lot of those are being developed with a lot of techniques that revolve around big data and analytics. We're definitely seeing the pressure to modernize what you have on-prem today, but you know, you can't sit there and be static. You gotta provide new services around what you're doing for your customers. A lot of those are coming in the form of this Mode 2 type of application development. >> One of the things that we're seeing, everybody talks about digital transformation. It's the hot buzzword of the day. To us, digital means data first. Presumably, you're seeing that. Are organizations organizing around their data, and what does that mean for infrastructure? >> Yeah, absolutely. We see a lot of folks employing not only technology to do that. They're doing organizational techniques, so, peak teams. You know, bringing together a lot of different functions. Also, too, organizing around the data has become very different right now, that you've got data out on the edge, right? It's coming into the core. A lot of folks are moving some of their edge to the cloud, or even their core to the cloud. You gotta make a lot of decisions and be able to organize around a pretty complex set of places, physical and virtual, where your data's gonna lie. >> There's a lot of talk, too, about the data pipeline. The data pipeline used to be, you had an enterprise data warehouse, and the pipeline was, you'd go through a few people that would build some cubes and then they'd hand off a bunch of reports. The data pipeline, it's getting much more complex. You've got the edge coming in, you've got, you know, core. You've got the cloud, which can be on-prem or public cloud. Talk about the evolution of the data pipeline and what that means for infrastructure and big data workloads. >> For a lot of our customers, and we've got a pretty interesting business here at HPE. We do a lot with the Intelligent Edge, so, our Edgeline servers in Aruba, where a a lot of the data is sitting outside of the traditional data center. Then we have what's going on in the core, which, for a lot of customers, they are moving from either traditional EDW, right, or even Hadoop 1.0 if they started that transformation five to seven years ago, to, a lot of things are happening now in real time, or a combination thereof. The data types are pretty dynamic. Some of that is always getting processed out on the edge. Results are getting sent back to the core. We're also seeing a lot of folks move to real-time data analytics, or some people call it fast data. That sits in your core data center, so utilizing things like Kafka and Spark. A lot of the techniques for persistent storage are brand new. What it boils down to is, it's an opportunity, but it's also very complex for our customers. >> What about some of the technical trends behind what's going on with big data? I mean, you've got sprawl, with both data sprawl, you've got workload sprawl. You got developers that are dealing with a lot of complex tooling. What are you guys seeing there, in terms of the big mega-trends? >> We have, as you know, HPE has quite a few customers in the mid-range in enterprise segments. We have some customers that are very tech-forward. A lot of those customers are moving from this, you know, Hadoop 1.0, Hadoop 2.0 system to a set of essentially mixed workloads that are very multi-tenant. We see customers that have, essentially, a mix of batch-oriented workloads. Now they're introducing these streaming type of workloads to folks who are bringing in things like TensorFlow and GPGPUs, and they're trying to apply some of the techniques of AI and ML into those clusters. What we're seeing right now is that that is causing a lot of complexity, not only in the way you do your apps, but the number of applications and the number of tenants who use that data. It's getting used all day long for various different, so now what we're seeing is it's grown up. It started as an opportunity, a science project, the POC. Now it's business-critical. Becoming, now, it's very mission-critical for a lot of the services that drives. >> Am I correct that those diverse workloads used to require a bespoke set of infrastructure that was very siloed? I'm inferring that technology today will allow you to bring those workloads together on a single platform. Is that correct? >> A couple of things that we offer, and we've been helping customers to get off the complexity train, but provide them flexibility and elasticity is, a lot of the workloads that we did in the past were either very vertically-focused and integrated. One app server, networking, storage, to, you know, the beginning of the analytics phase was really around symmetrical clusters and scaling them out. Now we've got a very rich and diverse set of components and infrastructure that can essentially allow a customer to make a data lake that's very scalable. Compute, storage-oriented nodes, GPU-oriented nodes, so it's very flexible and helps us, helps the customers take complexity out of their environment. >> In thinking about, when you talk to customers, what are they struggling with, specifically as it relates to infrastructure? Again, we talked about tooling. I mean, Hadoop is well-known for the complexity of the tooling. But specifically from an infrastructure standpoint, what are the big complaints that you hear? >> A couple things that we hear is that my budget's flat for the next year or couple years, right? We talked earlier in the conversation about, I have to modernize, virtualize, containerizing my existing apps, that means I have to introduce new services as well with a very different type of DevOps, you know, mode of operations. That's all with the existing staff, right? That's the number one issue that we hear from the customers. Anything that we can do to help increase the velocity of deployment through automation. We hear now, frankly, the battle is for whether I'm gonna run these type of workloads on-prem versus off-prem. We have a set of technology as well as services, enabling services with Pointnext. You remember the acquisition we made around cloud technology partners to right-place where those workloads are gonna go and become like a broker in that conversation and assist customers to make that transition and then, ultimately, give them an elastic platform that's gonna scale for the diverse set of workloads that's well-known, sized, easy to deploy. >> As you get all this data, and the data's, you know, Hadoop, it sorta blew up the data model. Said, "Okay, we'll leave the data where it is, "we'll bring the compute there." You had a lot of skunk works projects growing. What about governance, security, compliance? As you have data sprawl, how are customers handling that challenge? Is it a challenge? >> Yeah, it certainly is a challenge. I mean, we've gone through it just recently with, you know, GDPR is implemented. You gotta think about how that's gonna fit into your workflow, and certainly security. The big thing that we see, certainly, is around if the data's residing outside of your traditional data center, that's a big issue. For us, when we have Edgeline servers, certainly a lot of things are coming in over wireless, there's a big buildout in advent of 5G coming out. That certainly is an area that customers are very concerned about in terms of who has their data, who has access to it, how can you tag it, how can you make sure it's secure. That's a big part of what we're trying to provide here at HPE. >> What specifically is HPE doing to address these problems? Products, services, partnerships, maybe you could talk about that a little bit. Maybe even start with, you know, what's your philosophy on infrastructure for big data and AI workloads? >> I mean, for us, we've over the last two years have really concentrated on essentially two areas. We have the Intelligent Edge, which is, certainly, it's been enabled by fantastic growth with our Aruba products in the networks in space and our Edgeline systems, so, being able to take that type of compute and get it as far out to the edge as possible. The other piece of it is around making hybrid IT simple, right? In that area, we wanna provide a very flexible, yet easy-to-deploy set of infrastructure for big data and AI workloads. We have this concept of the Elastic Platform for Analytics. It helps customers deploy that for a whole myriad of requirements. Very compute-oriented, storage-oriented, GPUs, cold and warm data lakes, for that matter. And the third area, what we've really focused on is the ecosystem that we bring to our customers as a portfolio company is evolving rapidly. As you know, in this big data and analytics workload space, the software development portion of it is super dynamic. If we can bring a vetted, well-known ecosystem to our customers as part of a solution with advisory services, that's definitely one of the key pieces that our customers love to come to HP for. >> What about partnerships around things like containers and simplifying the developer experience? >> I mean, we've been pretty public about some of our efforts in this area around OneSphere, and some of these, the models around, certainly, advisory services in this area with some recent acquisitions. For us, it's all about automation, and then we wanna be able to provide that experience to the customers, whether they want to develop those apps and deploy on-prem. You know, we love that. I think you guys tag it as true private cloud. But we know that the reality is, most people are embracing very quickly a hybrid cloud model. Given the ability to take those apps, develop them, put them on-prem, run them off-prem is pretty key for OneSphere. >> I remember Antonio Neri, when you guys announced Apollo, and you had the astronaut there. Antonio was just a lowly GM and VP at the time, and now he's, of course, CEO. Who knows what's in the future? But Apollo, generally at the time, it was like, okay, this is a high-performance computing system. We've talked about those worlds, HPC and big data coming together. Where does a system like Apollo fit in this world of big data workloads? >> Yeah, so we have a very wide product line for Apollo that helps, you know, some of them are very tailored to specific workloads. If you take a look at the way that people are deploying these infrastructures now, multi-tenant with many different workloads. We allow for some compute-focused systems, like the Apollo 2000. We have very balanced systems, the Apollo 4200, that allow a very good mix of CPU, memory, and now customers are certainly moving to flash and storage-class memory for these type of workloads. And then, Apollo 6500 were some of the newer systems that we have. Big memory footprint, NVIDIA GPUs allowing you to do very high calculations rates for AI and ML workloads. We take that and we aggregate that together. We've made some recent acquisitions, like Plexxi, for example. A big part of this is around simplification of the networking experience. You can probably see into the future of automation of the networking level, automation of the compute and storage level, and then having a very large and scalable data lake for customers' data repositories. Object, file, HTFS, some pretty interesting trends in that space. >> Yeah, I'm actually really super excited about the Plexxi acquisition. I think it's because flash, it used to be the bottleneck was the spinning disk, flash pushes the bottleneck largely to the network. Plexxi gonna allow you guys to scale, and I think actually leapfrog some of the other hyperconverged players that are out there. So, super excited to see what you guys do with that acquisition. It sounds like your focus is on optimizing the design for I/O. I'm sure flash fits in there as well. >> And that's a huge accelerator for, even when you take a look at our storage business, right? So, 3PAR, Nimble, All-Flash, certainly moving to NVMe and storage-class memory for acceleration of other types of big data databases. Even though we're talking about Hadoop today, right now, certainly SAP HANA, scale-out databases, Oracle, SQL, all these things play a part in the customer's infrastructure. >> Okay, so you were talking before about, a little bit about GPUs. What is this HPE Elastic Platform for big data analytics? What's that all about? >> I mean, we have a lot of the sizing and scalability falls on the shoulders of our customers in this space, especially in some of these new areas. What we've done is, we have, it's a product/a concept, and what we do is we have this, it's called the Elastic Platform for Analytics. It allows, with all those different components that I rattled off, all great systems in of their own, but when it comes to very complex multi-tenant workloads, what we do is try to take the mystery out of that for our customers, to be able to deploy that cookie-cutter module. We're even gonna get to a place pretty soon where we're able to offer that as a consumption-based service so you don't have to choose for an elastic type of acquisition experience between on-prem and off-prem. We're gonna provide that as well. It's not only a set of products. It's reference architectures. We do a lot of sizing with our partners. The Hortonworks, CloudEra's, MapR's, and a lot of the things that are out in the open source world. It's pretty good. >> We've been covering big data, as you know, for a long, long time. The early days of big data was like, "Oh, this is great, "we're just gonna put white boxes out there "and off the shelf storage!" Well, that changed as big data got, workloads became more enterprise, mainstream, they needed to be enterprise-ready. But my question to you is, okay, I hear you. You got products, you got services, you got perspectives, a philosophy. Obviously, you wanna sell some stuff. What has HPE done internally with regard to big data? How have you transformed your own business? >> For us, we wanna provide a really rich experience, not just products. To do that, you need to provide a set of services and automation, and what we've done is, with products and solutions like InfoSight, we've been able to, we call it AI for the Data Center, or certainly, the tagline of predictive analytics is something that Nimble's brought to the table for a long time. To provide that level of services, InfoSight, predictive analytics, AI for the Data Center, we're running our own big data infrastructure. It started a number of years ago even on our 3PAR platforms and other products, where we had scale-up databases. We moved and transitioned to batch-oriented Hadoop. Now we're fully embedded with real-time streaming analytics that come in every day, all day long, from our customers and telemetry. We're using AI and ML techniques to not only improve on what we've done that's certainly automating for the support experience, and making it easy to manage the platforms, but now introducing things like learning, automation engines, the recommendation engines for various things for our customers to take, essentially, the hands-on approach of managing the products and automate it and put into the products. So, for us, we've gone through a multi-phase, multi-year transition that's brought in things like Kafka and Spark and Elasticsearch. We're using all these techniques in our system to provide new services for our customers as well. >> Okay, great. You're practitioners, you got some street cred. >> Absolutely. >> Can I come back on InfoSight for a minute? It came through an acquisition of Nimble. It seems to us that you're a little bit ahead, and maybe you say a lot a bit ahead of the competition with regard to that capability. How do you see it? Where do you see InfoSight being applied across the portfolio, and how much of a lead do you think you have on competitors? >> I'm paranoid, so I don't think we ever have a good enough lead, right? You always gotta stay grinding on that front. But we think we have a really good product. You know, it speaks for itself. A lot of the customers love it. We've applied it to 3PAR, for example, so we came out with some, we have VMVision for a 3PAR that's based on InfoSight. We've got some things in the works for other product lines that are imminent pretty soon. You can think about what we've done for Nimble and 3PAR, we can apply similar type of logic to Elastic Platform for Analytics, like running at that type of cluster scale to automate a number of items that are pretty pedantic for the customers to manage. There's a lot of work going on within HPE to scale that as a service that we provide with most of our products. >> Okay, so where can I get more information on your big data offerings and what you guys are doing in that space? >> Yeah, so, we have, you can always go to hp.com/bigdata. We've got some really great information out there. We're in our run-up to our big end user event that we do every June in Las Vegas. It's HPE Discover. We have about 15,000 of our customers and trusted partners there, and we'll be doing a number of talks. I'm doing some work there with a British telecom. We'll give some great talks. Those'll be available online virtually, so you'll hear about not only what we're doing with our own InfoSight and big data services, but how other customers like BTE and 21st Century Fox and other folks are applying some of these techniques and making a big difference for their business as well. >> That's June 19th to the 21st. It's at the Sands Convention Center in between the Palazzo and the Venetian, so it's a good conference. Definitely check that out live if you can, or if not, you can all watch online. Excellent, Patrick, thanks so much for coming on and sharing with us this big data evolution. We'll be watching. >> Yeah, absolutely. >> And thank you for watcihing, everybody. We'll see you next time. This is Dave Vellante for theCUBE. (fast techno music)

(upbeat electronic music) >> Welcome back, everyone, to this special Cube conversation. I'm John Furrier in the Cube's Palo Alto Studios. My next guest is Dr. Tom Bradicich, he's a friend of the Cube, works at Hewlett Packard Enterprise, heads up the IOT. He's general manager and vice president of servers, converged edge, IOT systems. But we're here to talk about, not so much HPE but really that work that Tom's done in a topic called First Mover, a book that he's writing. It hasn't come out yet, so we'll get an early preview of what it's like to create a category innovation and how to use process to your advantage, not make it your enemy. (chuckles) How to use creativity and how to motivate people and how to sell it through organizations, whether it's venture capitalists or managers. Tom, you've got great experience, thanks for spending time to come into the studio. >> Great to be here, thanks for having me and I'm happy to have this discussion. >> If you go back to the Cube videos, folks watching that know you, seen all the videos at HPE Discover or HP Discover, back in the day, you had a great career. You were an engineer, built the first notebook computer with IBM, you've done a lot of groundbreaking things and I like the topic of your book, First Mover, 'cause it speaks to your mindset. Entrepreneurial, innovative, breaking through walls, you probably got a lot of scar tissue. So, I want to talk about that. Because this is what the opportunity many entrepreneurs have as you know, in the Cube, we really believe that a renaissance in software development is coming. It's so obvious, open source is growing at a extraordinary pace, reuse of code. >> Right. >> You got IOT. >> You're involved in, you got crypto currency, block chain, all these new waves are coming all at once. >> Yes. >> I wish I was 22 again. >> Because this is a great opportunity to innovate. But this improving things, what are some of those things? Let's jump in, what do you see as the playbook? What have you learned and what can you share? >> Well, sure, I've been blessed, I've had a career where I've been able to do a lot of innovation but also, I like to separate the notion of innovation from differentiation. Now see, it's possible to be innovated and not different. Like it's possible for you and I to have the same new suit. It's new, it's innovative, but it's not different. And differentiation is really where one can have a first mover advantage because differentiation by definition is new, is innovation. But it's not always the other way around. So, I always tell my teams and I always focus on, how can we be two things, both different and better. It's possible also to be different and not as good. You can have the highest failure rate in the industry, you're different but that's not good. >> Right? >> Yeah. >> So, the concept here is how do you be different, not just new and innovative but how to be different and how do you be good. And I've actually faced three risks in mostly the big corporate culture that we've had to innovation. And the first risk is, of course, the obvious one, will customers buy it, that's called market risk. Is it something that's good enough to be purchased at a profit? The second risk is, can it be manufactured at quality and at a rate of consumption. The third risk is your own company, does the company have what it takes, actually, to take on the risk of a brand new product category, not just a new product. But a new category of products that, by definition, have never been done before. And when one can do that, when one can figure that out, and I've had some significant experience with this, you can catapult your careers, you can catapult your company and your customers to new levels because you enjoy the benefits of the first mover. That's the name of the book, The First Mover. >> Well, I'm looking forward to seeing it. But I want to ask, this is super important because a lot of people are really good at something and they run hard, they break through a wall but might have missed something. So, you kind of bring up this holistic picture. What are some of the things that folks should focus in on? Say I have a breakthrough idea, I have a prototype I've been running, it's in market, I think it's the best thing since sliced bread, I'm pushing it hard, people are just going to lap this up, this is going to be great, I know it's innovative but no one else knows it. >> Right, right, yeah. >> What do I do? >> What's the process, what do you recommend? >> Well, what I like to do is portion the benefits into two categories. There's supply side benefits that's to your company. Why is this good for your company to do this? And then there are demand side benefits. Meaning, why is it good for the customer? Most people tend to focus mostly on the demand side. Oh, it's solves this problem and the customers will love it and that's important and I would call that a necessary but not a sufficient condition. The other condition is why is this good for your company? And many times, when it's a brand new product category, those inside a company aren't quite in tune with why it's good for the customer. Because, again, it's a new thing, it's a new product category. Why is an automobile better than a horse and buggy, right? Why is a laptop computer better than a desktop computer? These are the ideas where it may be intuitive, it may be instructive to talk about that but when you can get a business model first and start with that, well, the reason is, we can enjoy this margin. The reason is, we can enjoy this particular first mover advantage, the halo effect, the reputation of being the leader. The reason is because we can penetrate a new market. The reason is we can now overcome a falling revenue in a shrinking tam. Now we can accelerate in another tam, perhaps, as well. So, by coming up with both the demand side and the supply side, you have a better case to go forward for support and funding inside a big corporation. >> There's always product market fit, I hear the buzzwords, I got to get the cashflow positive, break even. There's always a motivating force to get something done. How should someone organize the order of their operations to get something done, to the market, if it's an innovative, groundbreaking, differentiating? Because a lot of the big challenge is, some people call it landing span, I heard that buzzword too but you get a champion inside a company and that champion embraces it and most people think, oh man, I got a customer. But then that person has to sell it through and then it has to be operationalized, meaning, people got to get used to it. These are really challenges. >> They are, yes. >> What is your view of how an entrepreneur or a business executive or practitioner to get through that? >> Well, you have to get people on your side and it's really important. Somebody's got to believe in, either, you not even understanding what you're proposing but they'd say, well, you have a track record. For some reason, I believe what you're saying. And then, secondly, getting customers. So, I have personally never done anything major without a customer that I call an inspiration customer. That's a name I just made up. So, a customer, by definition, is an end user that will buy something from you, that's the definition of a customer. And an inspiration customer is one that will help you that is okay with seeing your dirty laundry, okay with mistakes you might make because they see the value in it and they also see the value in them being a first mover. And I like to tell my team, we want to be a first mover and a trendsetter, so our customers can also be trendsetters in their business as well. So therefore, by getting that customer support, and that's in the form of POCs or in trials or in just customer testimony, combine that now with a second dimension called the analyst community, which you're team resides in as well, also saying well, I think this is good as well, brings a lot credibility because there's a saying, a verse in the bible that a prophet is not without honor except in his own home town. Now, if you think about that, a lot of times, you're own company that you reside in has a lower point of view because it's very consumed with, indeed, what is next and doing the right thing, by the way. I have to make this quarter, right. We have to protect the brand. We have to keep the cashflow coming in. These are all important things, so how do you get someone to focus on that? Many times, it's not you anymore, it's outside. And I call that the second C. The first C is internal, the company. The second C is your customers and the community. That also could include, by the way, analysts, the media, other experts, consultants, those type of Cs around there. Now the third C is the competition. This is a little bit controversial. What happens when the idea is now exploited by the competition first; sometimes that is a motivator for a company to jump on it as well and make the market. But, again, if you follow the competition, you're not the first mover, you don't enjoy the benefits of first mover advantage. Higher margin, the halo effect of being the innovators and also, learning, that's an important one. When you're a first mover, you're out there learning so that you can respond to the second generation in a better way. >> I like the notion of differentiation and innovation as two different variables. >> Yes. >> Because it's super important. You can be different and not innovative. You can be innovative and not different. Again, it's all contextual but I want to get back to the pioneering of the first movers. So, statistically speaking, a lot of the best entrepreneurs are first movers and they're often "misunderstood", you hear that all the time. >> Yes. >> Or being a visionary is the difference being 10 years in the future versus an hour, can make the difference between success. (chuckles) We are crazy on one end and you're brilliant on the other because the time to value catches up with that profit, if you will. So the question is that, how does first movers continue to win 'cause I've seen situations where first movers come in, get a position and win and stay, keep the lead. Other times, first movers come in, set the market up, create all the attention and then have arrows on their back. >> And a second mover enjoys the benefit. >> Yeah, so the second mover comes in, bigger scale, so this competition, competitive strategy overlaid on this. Which even complicates it even further. >> Indeed, yes. >> So, your thoughts on that. >> Yes, indeed. Well, one way to look at this is the way to move forward is again, when you can get some momentum that's not you. That's the number one as a... >> John: Market growth, number of subscribers, doing the internet as a trend. >> Yes. >> Mobile users. >> Yes. >> And a third party consultant who's highly respected, a greaser, an analyst. I ran into an analyst recently in a coffee shop who agreed with some of this first mover work we're doing and converged edge systems, which is a new class of products as well. But it's really important that you can't be discouraged, let me point this out. What I tell my team, and I tell students, I lecture at universities and I've been edge professor, those younger in their career, is if you cast and vision and you have an idea and nobody gets it, don't be discouraged, that's a good sign. That's sounds a little funny. Why is it a good sign? Because if everybody gets it right away, it's likely not that novel, it's likely rather ordinary, it's likely been thought of before as well. So, by the very nature and definition that the average person might think it's discouraging. Oh, nobody understands me, nobody gets this idea, should be an encouragement, and a motivation. Now the risk here, is people not getting it is also a sign of a stupid idea. So, usually, when people don't get it, it's either, really not good. >> Or really good. >> Or really amazing that, eventually, they'll come around to it. I had a boss in one of my career opportunities told me to stop working on a product. I don't want to give too much detail, but he literally told me that. And I said, I didn't want to be insubordinate to a boss, we have them and I said, can I please just keep working on it, okay, don't let it interfere with the other stuff. Dah, dah, dah. Today that market is a nine billion dollar market as well. >> Of that product that you-- >> Of that very product that I was told by a very astute person, one of my colleagues, my bosses, that I don't see the future in this, let's not do this, you know, as well. But, being able to have a second thing. So, number one is don't be discouraged by people not getting it. By definition, that's supposed to happen. >> Yeah. >> When you have new-- >> Good point, you want to finish that? >> I just want to get-- >> Get one more thing. >> If I may add a second one. And as you're moving forward with this as well is seek out and find those who do agree with you and stick with them very, very closely. And I have, I can say a couple of names. There's one, we've created this new product class called Converge Edge Systems. Alan Andriole is senior vice president at HP. >> Cube alumni. >> And he's a Cube alumni. >> Super smart. And I'm pointing him out because he has publicly taken on this idea that this product category can really, really work and he's worked-- >> John: Cloud Nine? >> Oh, the converge edge system called Edgeline. >> Okay, got it. >> The Edgeline product brand. >> You know it as well. So therefore, when you find someone who had authority-- >> Eagles fly together, you want to get a good peer group. >> Absolutely. >> Here's a question for you. >> One of my experiences, and I want to just get your reaction and add on to it, your thoughts is, most entrepreneurs or pioneers are misunderstood, so I agree, don't be discouraged, but also, keep validating and be a data seeker, get the data. But a lot of the times, just getting something in the market or getting it going creates movement and inertia to get rolling and sometimes the original idea is actually the big idea turns into it as you get more data. An example is like Air B&B wasn't... What it is, it was basically air mattresses and selling cereal. >> Yes, yes. >> That was the original story, right. And then it turned into, but conceptually, it was the same thing, so you don't have to be 100% right on the semantics. >> It's well known that most startups don't end up being successful with the product they start with. That's well known fact but that's true also in large companies with a product idea as well. So, you have to have this interesting balance. It's very interesting as I've thought about this in study. You have to have deep philosophical and conviction of principles. And here's why: If you don't, you will be swayed by everybody's opinion and you'll never get anything done because oh, well, that's a good idea, maybe I should do this well, that's a good idea, maybe I should do this. Now, I'm not saying that's bad to listen to others but if you don't have a grounding of principles. Example, we established the seven principles of the IOT over two years ago, and we've held on to them and created the success we have based on those principles. Now that's not to say we didn't modify them a little bit but the point is, we were convicted with something and when somebody would come up with a counter to it, we had a way to defend our convictions, if you will, in internal debates and external debates as well. And then, secondly, you got to be also okay with being the sole inhabitant of that field of discourse. Being a visionary can be a very lonely job because of that, right. And, again, it's because you are and your team is, it's not always a lone person right, the team is actually creating something that literally nobody's ever seen before. Nobody understand before. >> What process do you wrap around this? Because Dave Alonzo and I always talk about this on the Cube and after the Cube is that the process has to be your friend, not your enemy. It has to work for you. >> I always say that, yeah. >> Also says that as well on Amazon. But also Charlie Munger, Warren Buffet's partner always says I'm not a big fan of master plans, meaning, because become a slave to the plan rather than the opportunity. >> Yep, yep. >> So these are process kind of things, right. So how does an innovator that's a first mover that wants to create a category, 'cause categories killers or category creators are huge opportunities financially. So they create a lot of value wealth and opportunity. What process is best? Is there a view, is it conditional on certain things? What's your thoughts on... >> Well, let me say, I'm going to give you a big company or a medium size company context, not a startup, I think they're distinctly different. I have limited experience with a startup but I've had significant experience with bigger, medium and large, now, companies as well. You can't try to change the system because now you have two variables. You got this new product that nobody's ever heard of and now you're trying to change the whole system. Now, again, this is just advice for bigger companies. So be careful how many things you want to change, how many things you want to stop. So you want to take this new thing and align it with existing processes and existing core competencies as much as you can, even though it's new, it has to have some alignment; I'll give you an example. When we built the converged edge systems, the Edgeline brand, we aligned it with compute. It's not only compute, but we aligned it with compute, why? Because HPE or HP, at the time, was and is and now, number one in compute when it comes to data center. Compute systems when it comes to high performance computing and mission critical, right. So therefore, that was easy to understand so you're okay, you're familiar with this, but now, let me tell you this new twist on it. And I would assume, and I don't know this for sure, but I would assume Steve Jobs and the Apple team that was thinking of this smartphone concept, the iPhone as well, they had to align it with some level of compute capabilities, right. And if you notice, as it emerged, it also included something that already exists called the iPod which was already aligned with their laptop computers and their desktops, right. Your music would be downloaded as an app to connectivity, but now you can take it with you and by the way, now I'll add a phone to it and so this incrementally built and by the way, you ain't seen nothing yet, I'm going to add a GPS system, I'm going to add a camera, your flashlight, your wallet, I'm going to add all that in. So, I think, by incrementally moving but not upsetting the system, like you said, in a large company really, really helps because you can't change everything too quickly. You got to be okay being alone-- >> Well, I want to interrupt you there for a second. Peter Buress and I talk all the time; I love his quote, Peter Buress, head Cube on research says, the iPhone was a computer that happened to make phone calls. Okay, and that's the smartphone, it's category creator and we know what happened, the rest is history. However, you mentioned talking to customers, having an inspiration customer, I love that concept. Because you need a muse as an innovator. You got to have someone you can trust that knows what you're trying to do that understands the mission. If Steve Jobs went into the marketplace and did market research, he would have probably had the customer feedback to build the best Blackberry. A better Blackberry or another device. Instead, he used is gut, was on his mission and then he understood the inspirational customer, whether it was real or not, he was going down a different road. It takes guts but also some discipline. >> I hear you and I agree with this 100%. When I had the great fortune of leading a team that created the first enterprise blade server or converge system, and today that is pushing about a 10 billion dollar market opportunity, and not one customer asked me for it. Now, that doesn't mean I didn't listen, okay. But I had to bring it to them. So here's the difference, we're not responding to trends, this is a key point, we're creating a trend. And what I tell my team is, you must create trends, not follow them. Many of competitors, are by the way making good money and doing good business, I'm not knocking that, but I'm saying they're not creating a trend, they're actually following one. They're in an exploding tam. >> Pretty lucrative trend. >> It can be. >> Very mature, big market. >> Dave Thomas with Wendy's followed a trend called hamburgers and he did pretty well. He didn't create the hamburger market but he followed one. Now, this is really rather interesting. So when you come in, and then you're saying I want to actually set a trend and create one, it really gives you this opportunity to redefine what is happening. So now, quick story, you may have heard this, maybe your viewers have heard this. A manager of a shoe company sends two guys to an island. He says, I want you to sell shoes on this island. They get to the island, the first guy calls back and says, boss, this is terrible, everybody is barefoot. There's no opportunity to sell shoes. This is terrible, I'm coming home. The second guy calls and says, boss, you're not going to believe this, there's not a shoe on this island and I have a tam that's 100% of the market to sell shoes. I believe, as you pointed out, Steve Jobs didn't go and say well, what apps do you own on your Blackberry. What he did is reversed it and this is what we're doing, we're reversing, we're saying, if you could watch a full length high definition movie in your hand, would you? Well, I can but I can't do it on this device. But if you could, right. So now, in the IOT, I hear this all the time from my competitors and even some colleagues out in the industry, well, we ask them what apps they run at the Edge. We ask them what they do at the Edge. That's good, that's necessary but not sufficient. You have to say, but if you had this product, wouldn't you, for example, run an entire database? Would you compile your machine learning models at the Edge, do it in the cloud now, wouldn't you do that, if you had it? Well, I never thought of that because I don't have that capability, just like, well, I never thought of being able to take pictures and watch full length high definition movies 'cause I never had it. But what if you did, would you do it? So you always got to be setting that trend, not responding to it only. >> That's awesome. >> Dr. Tom Bradicich, writing a book called First Mover really about being innovative. Give you the final word, thanks for coming in, appreciate you sharing the advice. What's going on with HPE and your IOT work? Take a minute to talk about what's happening at HPE. >> Well, thanks, pretty exciting, we've been able to move forward with some really great customer wins. I'm hoping to go public with them. We're in many ways, I know this is an abused term, but we're revolutionizing the industrial IOT in particular and manufacturing floors. We have the large auto-manufacturer that has chosen Edgeline as the standard to produce more and more vehicles per day. That's their goal, how many more vehicles can I get into my customer's hands per day. We have snack company making potato chips. Looking at what we're doing with sulfur, defining operations. We have even, we've talked about this before, space travel, engage with what the space edge is all about. In many ways, we're potato chips to space ships. >> Data centers on Mars. >> Data centers everywhere. >> And then, also, converging OT, just like the smartphone converged the camera and the GPS system, we're converging control systems, data acquisition systems. It's pretty exciting, I've been fortunate to have a company and our new CEO, Antonia Neery, has been very supportive, I was with him this morning and we talked about that new, first-of-a-kind product that we have at this auto-- >> So, is Antonio going to let us come in and do an exclusive interview since he's been a Cube alumni multiple times? >> Yes, I think he should. >> Tell him we said hello. >> I will, I will. >> Tom, great to see you. >> Thanks for having me. >> Tom Bradicich, great thought leader, really around category killers, category creators, being innovative and different, that's the key to success. Thanks for sharing. This is the Cube Conversation here in Palo Alto, I'm John Furrier, thanks for watching. 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>> Announcer: Live from Madrid, Spain. It's the Cube. Covering HPE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid everybody. This is the Cube, the leader in live tech coverage, and this is day two of HPE Discover 2017. I'm Dave Vellante with my co-host, Peter Burris, Alain Andreoli is here. He's the Senior Vice President and general manager of the hybrid IT group at HPE. Great to see you again. >> Great to see you David, great to see you Peter. >> So, a lot of good energy here, the story Alain is coming together. >> Alain: Yes. >> We've seen it over the last five years but really fine-tuned the organization and seems like things are going well. >> We have more clarity on our strategy than I've ever seen in a company, and this was not easy to do because the market is changing so fast. We addressing $120 billion market in hybrid IT, we lead the market in compute, we lead the market in storage, we lead the market with private cloud, we have invented composable, we are ramping up our Harper converge offering, and now on top of the infrastructure, we building these layers of one sphere, which is managing a multi-cloud environment for the data, and we are adjusting our services to become advisory and consumption models. This is having such an impact on our customers, 74 percent of our customers are going for hybrid IT journey. So we have organized ourselves to make this journey to be basically the partner of choice for our customers as they go through that. >> I mean so cloud of the last five, seven years, cloud and open-source software have really disrupted our industry. You've had to respond to that, and basically bringing cloud-like operating models to your customers. >> Alain: Yes. >> How have you done that, how do you rate your progress and where are you to date in that regard? >> So the first decision we had to make is are we a neutral party to our customers? (laughing) >> Dave: Yeah. >> We need to redo it. (laughing) >> They're getting you back, right? So, I don't know if you can see that, alright? Alain came by on his scooter, here we go, let's catch this. Here we go, this is called payback. (laughing) During Dr. Tom's interview, Alain came by with his scooter. (laughing) >> I will get you, I will get you for this. (laughing) >> It's great fun on the Cube. >> We can kid, that's alright. >> That's good. >> So the decision we had to make is are we the partner for our customers to go to the cloud or are we saying on PRIM is better? >> Dave: Yeah. >> And we 'vedecided to be this partner. Because we believe there is value for everyone and we believe it is not a one-way street. And we see actually that 32 percent of the customers who have moved work loads to the cloud are bringing these work loads back on PRIM. So we had to advise them. We helped them go through this journey, we really mean it, we helped them to go on Amazon, we helped them to go on Azure, we helped them to go on Google, and we helped them make it work, and this is why it's a service-led journey. The problem if you go on the public cloud is that we don't really know how much it is going to cost you, and you don't really have a single pane of glass to have all your data being managed across, what is now an ecosystem. We enabled them to do that. And the market we are directly addressing on PRIM is not shrinking. We still see huge pockets of growth, in flash storage, in HPC, you've seen the results we have in HPC. In Mission-Critical X86, in Hyperconvert, so we are basically moving from the one-size fits all type of organization of freeing X86 and start off storage, to become a company that offers value to customers, in specialized pools of compute, of storage, of networking, and offering them the end to end journey across the different stack. What I think is going to make a huge difference, if you look at the five-year horizon, is the growth of The Edge and the fact that 70 percent of the data are going to come from The Edge, and then you will really see the power of our strategy of private IT which goes from The Edge, to the core, to the cloud, because we will be able to enable our customers to have their data moving seamlessly across this journey. And we have exactly organized the company that way. >> One of the obvious use cases from what I like to call machine intelligence or artificial intelligence is really infusing artificial intelligence into infrastructure for predictive analytics and predictive maintenance, IT operations management, Infocyte, you got through an acquisition of Nimble and have been impressed with the pace at which you pushed that throughout the portfolio, I wondered if you could address that. >> We've been almost surprised. We looked at, we wanted to become the flash company because we saw that the market over three years, would completely move to flash. And when there is such a pendulum shift, you want to be at the forefront. >> Dave: Right. >> So we looked at all these companies who were having very strong positions on flash and Nimble intrigued us because they had, by far, when we talked to their customers, the highest customer satisfaction, I think it was something like 87 percent. >> The NPS is off the charts. >> The NPS is off the charts, right? And then we peeled the onion and we saw Infocyte, which was almost enough to start south because it was not part of our list, right? Initially of our list of this is how we are gonna select a company we want to acquire, and when we got into Infocyte, how it works, how we can actually port easily these to three power and then to SimpliVity and then to the rest of the portfolio we felt this is the crown jewel that is going to be the foundation of us making >> Dave: And not just the storage portfolio. >> No, end to end so we're gonna do these for everything, now we cannot do it in one day. The priority was to give a seamless experience to customers going three power or Nimble, so we've done that very quickly. We acquired the company six months ago and it's already there for three power. Next one will be Simplivity, very soon in a few weeks, then we go to the whole computes platform as well, then finally to networking. I hope, it's not a commitment, but I hope that by the end of next year, and under a year, we will be done for the whole infrastructure portfolio. >> And explain the benefit to customers. >> And then the benefit is that you basically have, you eliminate the need for level one and level two support because it's proactively, now you have to be wanting to have your device calling home, right? Because otherwise, if you want your device to be in the data center and insulated from communicating with the network effect, that is not going to work, so but assuming you want your device to be connected centrally, so that it can be monitored centrally the artificial intelligence that is embedded in Infocyte is basically going to monitor the behavior of your device compared with hundreds of thousands of other ones and therefore anything that is deviant will be flagged as a potential problem and resolved before you even know about it. That's one. So when you end up having a problem eventually, which is becoming very, very rare, then you directly call the level three engineer who is an expert and who has, on the screen, the behavior of your device for the last month compared to others, and the resolution is in less than a minute. So it's a revolution in the way to do service. >> So, one of the things that we've observed as we've talked to customers is that the characteristics of the problems that they're now trying to solve have real world elements, and that's really what The Edge is about in many respects. For the first 50 years of IT, we were doing accounting, and HR, and supply chain, and we were able to define what the data models looked like, we could therefore say, the data's going to be here, the processing is going to be here, we could build data centers. Now as you said, 70 percent of the data is going to be coming from The Edge. It's not clear, necessarily where the best place to process that data is. Where's the compute going to be? How's it going to integrate with people? In many respects, hybrid IT is about diminishing the degree to which infrastructure dictates the way the problem gets solved. Would you agree with that? It's kind of like where does, let the data reside where it needs to reside, and make sure that the business is a natural infrastructure that reflects and corresponds to the work that needs to get done. >> I totally agree with your problem statement, and the way you position the question. In terms of semantics, I would just say we need to make infrastructure invisible. It's still there because it's all running on infrastructure. The iPhone is infrastructure, your PC is infrastructure, your camera is infrastructure, it's all there. >> A C.I.O said to me not too long ago... >> But you know what? We are having this interview, we are not thinking about what makes it happen. >> Peter: Right, right, right. >> Our business is to talk and communicate right now, this all has got to be seamless and that's how we need to make IT, seamless. >> I had a conversation with a C.I.O. >> Invisible. >> Yeah, who said that the value of my infrastructure is inversely proportional to the degree to which anybody knows anything about it. So, is that kind of what the HP promise is, is we're gonna let the data and the work loads define where the infrastructure goes and ensure we have those options? >> It's exactly right and the vehicle to do that, we call it autonomous data centers. Your phone is a data center. Your data center is a data center. Your off-frame cloud is a data center that you are subcontracting, right? So we want all of these to be autonomous, in terms of self-healing and everything else, and then the intelligence of where these data are being moved and how you use what and when is the single pane of glass that we are developing around one sphere. And how to get the customers to move their work loads and their business around that is what we do with point next with services. This is our strategy. >> So let me break that down a little bit. So, we've got devices that are powerful enough that we could put new types of control, new types of work loads there if we wanted to, we've got now the ability to package infrastructure, and have a single pane of glass, and have a common management framework. >> Right. >> But when you say the autonomous data center, it's we have a common business approach thinking about policy, thinking about value, thinking about how we're gonna do things, and we can put that into this entire vision, and let it actually execute how that manifests itself from a business standpoint. >> Exactly right. >> Have I got that right? >> It's exactly right. I love the way you put it. That's exactly what we are trying to do. it's not going to be done in one day, but that is our strategy, and we have organized, once again, the whole company around it, to execute this strategy and to make it happen for our customers. >> So if we think about what an HPE customer is gonna look like in, you know a really good HPE customer in 2023, what.. >> Alain: That's a long time. >> That's, five years, but I'm giving you that much run way, because you're right, it's not there yet and if it's too ambitious then so be it, but how is a business person going to think differently about working, about the role that IT is going to play in the business, and what it means to have a great partnership with a company like HP? >> Yeah, so we are basically, our motto is One size doesn't fit all, so we are first trying to understand the business of the customer, and then we will apply solutions to enhance this business, or to empower this business, right? So, we have the biggest brace of infrastructure that you can think of, think about this infrastructure becoming self-healing, but this infrastructure is more and more specialized, there is HPC, there is Mission-Critical, we just found Superdome flex, or SAP, we have all these specializations that, for those customers to optimize their business outcome. Then we have the single pane of glass that allows everything to seamlessly operate the data around, and then our point-neck services are going to work with the customers to architect their IT model in a way that their work loads are optimized. And one of the key is the right mix. The right mix of what you do yourself, what you got from multi-cloud, how much do you pay for it, how much do you anticipate that you're gonna pay for it, do you want this to be CAPEX, do you want this to be OPEX? And then how do you manage The Edge, and with Aruba and with Edgeline, and then with all your IT platforms that can manage the data across The Edge. We have the capability to also let the customer decide, do I want a lot of analytics and decisions to be made at The Edge, in my devices, and this is highly valuable depending on what customer business model we are talking about, or, do I want all the data from the analog world through the censors to come straight back to the ranch. All of these decisions, we are gonna have platforms to allow customers to make these decisions, to decide, kind of templates if you want, this is how I want it to run, and to be executed, and then to be automatically, autonomously operated. That's our vision of how we can help our customers moving forward. >> Last question, so the attendees of Discover, your customers, when they go back and he or she talks to their boss, what do you want them to say about Discover 2018? >> I invested two or three days of my time to come to HPE Discover. It was really exciting because I felt that it's like a new company, it's the company I know. I know they are customer first and customer last, and they are the ones who help me when I have a problem, whether they created it or not, they are here to help me. This is not going away, but they are taking us to the new world. They are gonna help us to build our hybrid IT model, and I think we need to trust them to have a seat at the table when we make these decisions, boss. >> Intimacy, innovation... >> Alain: Yeah, innovation. >> Trust. >> HPE's no longer wandering in the desert. (laughing) >> Alain Andreoli thanks so much for coming on the Cube, it is always a pleasure. >> It was a pleasure. Take care, thanks Peter. >> Keep it right there, everybody, Peter and I will be back with our next guest, right after this short break, we're live from Madrid. You're watching the Cube. (techno music)

>> Narrator: Live from Madrid, Spain, it's theCUBE, covering HPE Discover Madrid 2017, brought to you by Hewlett Packard Enterprise. >> Welcome back to Madrid, Spain, everybody. This is theCUBE, the leader in live tech coverage, and this is day two of our exclusive coverage of HPE Discover 2017. I'm Dave Vellante with my co-host Peter Burris. Last night was a great night of customer meetings. We stumbled into the CIO meeting, we were at the-- >> And were quickly ushered out. (both laugh) >> We were at the analyst event, and of course we met our good friend Dr. Tom Bradicich at the analyst meeting. This is the man who brought a lot of the IOT Initiative into HPE. He's the general manager of the IOT and Systems division. Great to see you again, Dr. Tom. Thanks so much for coming on. >> Thank you Dave and Peter, it's great to be here at theCUBE, great to be here at HPE Discover Madrid. Lots of great things happening, I can't wait to tell you about 'em. >> So we're very excited to have you on. John Furg and I interviewed you in the very early days after you came over from your previous company, and you had this sort of vision of, you know, bringing the HPE into the intelligent edge. >> Yes. >> And we're like okay, this sounds really complicated. You got ecosystem, you got all kinds of technologies that you gotta develop. Hardware, software. And you're making it happen. It's become a meaningful portion of HPE's business, so I know you got a long way to go, but congratulations on the progress so far. >> Thank you. Give us the update on the-- >> Well, first of all, thank you for that, I appreciate it. I must give credit to my team, I tell them all the time that if you don't execute and do the work, I'm just a science fiction writer. (interviewers laugh) And the vision has come about, and we have real customer deployments of course that the, you know, the proof of it. >> Right. >> At first we had no products and no customers, now we have these products that we'll talk about, and we have the customer deployments, and we're changing things for businesses at the edge, and again the edge is just not the data center. And the manufacturing floor, we'll talk about refineries, oil rigs, those type of edges. We're doing a lot of work there. And it's been exciting to see the ideas that we have get adopted by not only customers, but the industry, so we're seeing other analysts pick up on two dimensions: computing at the edge, and a little more complicated one, a little more difficult to grasp, is converged OT and IT at the edge, the two worlds of operational technology converging with IT. We were on theCUBE talking with an OT partner, National Instruments, a long while ago, and now we literally have those products in the market in the hands of customers. National Instruments is reselling the Edgeline 1000, the Edgeline 4000 products, as well as of course us selling it, and it's pretty exciting to see this happening. >> Well what I love about that conversation is, you know, when we first started to talk to you, we said okay, let's play the skeptic, analysts are skeptic. >> Sure. >> And we said one of the big problems you're gonna face is bringing the organizations together, OT and IT. They're just different worlds, oil and water, you know, you got hardcore engineers and you got IT guys, and then subsequent to that conversation, you bring on National Instrument, right? >> Yes. >> And we have that conversation. Okay, so we sit down, I check that box, at least they're having conversations. Can you talk about how that convergence is actually occurring, and what's in it for the customer? >> Well great. To talk about this convergence, the best thing to do is say it can happen at several levels. It can happen at a solutions level, it can happen at a software level and a hardware, physical level. Let's talk about a physical level, it's a little more tangible to understand. Let me use the smartphone, which everybody has. Like Peter, you have one there. If you hold that up, you will notice inside the manufacturer of that phone converged, or integrated, those are synonyms, many consumer devices. Such as what? A music player, of course, the phone, of course. But also many other things. A GPS system. >> Camera. >> A camera. The list goes on, right? We can go on. Oh, the flashlight, and by the way, your wallet. Maybe not your wallet, but a millennial and younger's wallet-- >> Yeah, sure. >> Is in that phone. >> My wallet's in it. >> My wallet's in it. >> In it, and-- >> Venmo, baby. >> That's right. (all laugh) >> I have my kids' wallets in there too. >> Oh that's great, you've done that switch. So what is happening there obviously is the notion of we're, you know, software defining and we're converging. Now the benefits of that are irrefutable. One thing you buy, it's less energy. One thing to manage, the convenience of carrying it around. Let's take that metaphor and impute it at, let me say a manufacturing floor edge. There's lots of edges out there. We go to a manufacturing floor edge, we see several devices, just like the early pioneers of the smartphone saw a consumer with a camera around his neck, a GPS on his belt, text, right, a flashlight, a wallet, and all this. We see all these devices out there, and what are they? Some of 'em are OT, as you mentioned. Operational technology devices such as control systems, such as data acquisition systems. >> Real-time systems. >> Real-time systems, industrial networks. CAN, PROFIBUS, SCADA solutions and networks. And the second thing we see is some IT. Most of it's closed, so this is important. It's good IT, meaning computing and storage, but a lot of it is closed systems. It's not the open EXEDY 6 architecture that we so enjoy in the data center. So those things are out there. We looked at 'em and we put them all in one box, just like the smartphone is one device. What are the benefits? Lower space, there's not a lot of space at the edge. Lower energy, there's not a lot of energy, right, at the edge. But the more profound benefits that we're seeing, and we have a large auto manufacturer who has deployed this on their manufacturing line, is it keeps uptime higher. In other words, it reduces downtime. So if the manufacturing line stops, there's nothing worse than a manufacturing line stopped, except perhaps an empty one. But the point is, when a manufacturing line stops, you can't put out product. You can't put out product, you can't recognize revenue get it in the consumer's hands. It's very obvious. It's an air-tight business case, actually. So we're able to reduce any downtime, why? Because first of all, everything's together, and secondly, we're able to manage it just like we're managing the data center because it's an open EXEDY 6 architecture. >> So you're converging tasks as well as hardware. >> As well as hardware, and then the next step is software, you know, as well. We just launched a new class of software called the Edgeline Services Platform, and this is OT software. So we're talking OT functions like aggregators and things that do OT technologies and some IT, but because we have so much compute power and it's open, it's EXEDY 6, it can run software like VMware, Microsoft Products, even database products as well. But because we have that, we're able to software define. When you software define, and I'll use the wallet again. You don't have a billfold with your license anymore. Plastic and leather has been software defined, and therefore it's less to deal with. It's much more efficient. So that announcement of our software strategy along now with our hardware strategy is very exciting for us, and customers are very much interested in it. >> So do you have some examples, you know, some real world examples? Customers that you can talk about where you're bringing together OT and IT disciplines? >> Yeah, you bet. Yeah, you bet. Let me talk about a large global beverage and snack company, and they make snacks, and in this case, potato chips. So a potato chip is a product, and the idea of having them come out of the line in the bag and be a higher quality is important. So we took an Edgeline System, the EL 1000, and we put it at the edge, and we were able to software define several of their IT and OT components and get it to a consolidation and integration in one box. Now what that did is it allowed the, and will do, is allowed the foods to move faster. So if they move across the conveyor belt faster, you can bag them faster, get 'em out to the consumer. The second thing is because it's so powerful, this is interesting. Now they can use video cameras to inspect the quality. Now think about that. That's not necessarily a new idea, but what is new is the notion that you can take video, which I think you'd agree is the largest data, is that right? A video is big, big data. >> We know that well. >> Especially if it's high, Yeah, especially if it's higher resolution, and your hosting costs are telling you that as well, right? Of all these videos. But if it's high resolution, and because you're looking for, you know, defects, indeed, one has to process that not only in high resolution, massive data, number one. Number two, quickly, because the thing is moving, and you wanna know to knock it off or stop or whatever the case may be. So what has happened there is my team and I did not think of that. Our customers thought that, well because you gave us this platform, we can now enhance it with a new type of sensor called a camera, with a new type of data, called video, to enhance our quality and keep our process moving faster. >> So keeping this converged notion going, you're converging the hardware, which is, you know, important. You're converging a lot of the administrative tasks. >> Yes. >> Which reduces the likelihood of any single human failure bringing the whole system down, but now you're talking about, in the whole sense, infer, and act loop that typifies what happens at the edge, you're converging new technologies into that loop by being able to add new data type, bring modeling, machine learning, analytics, in the infer, and then being able to act right there, which allows you to think about new invention, new innovation very, very rapidly because you have the processing power to converge all that new function as it becomes better understood. Have I got that right? >> You got it right. I serve as an adjunct professor at university, so let me position it in an easy way to learn. You said sense, infer, and act. Let's just call 'em the three A's. Acquire, analyze, and act. >> Okay. >> It's just easier to remember. And let me talk to that too, but this is actually just synonyms. So the acquisition of the data is through sensors in D to A conversion, or let me say A to D, analog to digital. Because most of these phenomenon, video for example, it has to be, is a light phenomenon. Moisture, pressure. At Duke Energy, for example, the second largest energy provider I worked on that industrial internet of things solution, and vibration was the thing that needed to be acquired and then analog to digital. Now the analysis has to take place. There are seven reasons to analyze at the edge. There are seven reasons not to send the data to the cloud. In the past, we have talked about it. One of them's latency, one of them's cost, one of them's bandwidth, another one is security, another one is reliability, another one is geofencing and policy, another one is duplication and security, you know, hostile or just, you know, reliability drop packets. There's a lot of issues to do that analysis there. But because we have a non-compromised full EXEDY 6, in fact, 64 in one box. 64 Xeon, Intel Xeon product in one box. We don't have to compromise the stack. We can take it directly out of the data center and run things like artificial intelligence, machine learning algorithms. We can virtualize, we can containerize, we can run Citrix applications at the edge to have better access to the data and of course the application. But you're absolutely right, and then the second thing in this point is we move from the middle A, analysis right, to the action. The reason, I've learned this doing many IOT deployments. The reason people do an IOT deployment is to act. Yes, it's exciting to collect data. It's also exciting to analyze it. But have you ever been in a business meeting where you sit and you analyze data and you give tremendous insights, and one conclusion is pit against another conclusion and it cancels out all conclusiveness, and then you talk and you analyze, and you walk out and nothing happens, there's no action. Many of us have been in that. That's the idea here. You can't stop at the analysis, even though artificial intelligence, deep algorithms, moving averages, signatures that we can compare are very powerful. Well, what do you do when you do that? Because we have control and actuation systems built into Edgeline, we literally in a physically space, as well as in a logical process, as you pointed out, close that loop. >> Right. >> Acquire, analyze, act, acquire, analyze, act. Yes, connect to the cloud or the data center if we need to, but the issue is you don't have to. Now here's what's profound about that. This system at the edge can be managed and run the same stacks as any cloud or data center. I'm gonna use those as synonyms because a cloud is just a data center that nobody's supposed to know where it is. So a data center far away on the corporate campus or in a public or private cloud somewhere, is managed the same way. When that happens, we are revolutionizing workload management. Now, I spent a lot of years in my former time in IT and building data centers and building some of the first clouds, workload management's a big deal. How do you shift the workload to the free server? >> Peter: Right. >> Or to the free resources, right? To optimize, obviously. And it's a packing problem many times in the data center. Well now we've introduced another place to workload manage. >> Right. >> It's called the edge, it's far away. So we workload managed in the data center, then the cloud was invented, that's the first off premises. The next off premises is now the edge. So the other off premise is the edge. So now we have a workload management capability. Do you wanna do 100% processing at the edge where the action is, and where the acquisition is? Do you wanna do 100% in the cloud? That's still possible. Do you wanna do 50-50? Would you like to do 10-90? Would you like to do 30-70? You get my point. >> Totally. >> I can shift this, and depending on the season, depending on issues like disaster recovery, depending on your workloads, you can now do that, and again, you can do this with the Edgeline 1000, the Edgeline 4000, because of the processing power and the converged OT inside it. >> Well our observation is that it's not about bringing your business to the cloud, it's about bringing the cloud to your business. >> Yes. >> So bringing that sense of workload management. You know, you might say the cloud is just a virtualized data center when you come right down to it. So bringing all those capabilities and bringing them to wherever the data requires it. And there's gonna be a lot of instances where the data is gonna be at the edge, stay at the edge, but that doesn't mean you don't want all the benefits of how you run computing data at the edge where that data is. >> Yeah, and we're not obviating, we're offering choice. >> Right. >> But again, there are seven reason I went over why you do it here, but I've had a customer say none of those seven matter. So okay, we send everything to the cloud, and we have great cloud hybrid IT products that do that. >> Yeah. >> And we've envisioned a three-tier data model, you know, real time at the edge. >> Yes. >> Maybe you don't persist everything, but like you said, there are a lot of reasons not to move all the data back. But there is maybe a spot where you aggregate some of that data from discrete devices, and sure, if you wanna do some deep modeling in the cloud, go for it. And that cloud might be the public cloud, it might be your own private cloud. Does that seem reasonable to you? >> Very reasonable, and another reason for a cloud is it's an aggregation point for other, in this case, manufacturing lines where other smart cities to come together, because you're not gonna connect every city, every plant, any to any. You'll have a hub and spoke model where the cloud serves as that hub. So there are always reasons, and that's why, you know, if you look at our company, the pillars of our company, Pointnext services, the second pillar is hybrid IT, primarily focused on cloud and data centers, and the third is the intelligent edge. And those all play very, very closely together, in fact we have edge to core strategies, we have edge to core offerings with partners like NVIDEA, with partners like SAP, with partners like SAS, we have edge to core. For example, Schneider as well, Schneider Electric. All of them are looking at this idea, GE, Microsoft Azure, let's go to the edge. And two years ago, that was not the case, right? Let's go there, when you go to the edge, what are you gonna run it on? Well, let's not force our software partners to re-architect like they used to have to to run at the edge, which is like I'd call that drive-by analytics. You just have to cut out everything because it only ran on a wimpy core somewhere or a little device. No, let's move the entire data center capability out to the edge, when I was presenting this to one of our partners, the CEO of the company, I was presenting this vision, and he was texting during my talk 'cause I was boring. (interviewers laugh) And then I said this, this is a very powerful company, I won't mention names. Then I said, we're gonna move data center class technology out to the edge. It's not gonna be in compromised cores or limited memory or a little bit of storage. It's the very things in the data center we'll harden called Edgeline. We'll add controls systems and data acquisition, we'll put it out at the edge. He stopped texting. Then he looked up at me and said, "Wow, you're really moving a data center out to the edge." and you just said that, right? It's the cloud is coming. It's almost a reverse idea of what was happening before. >> Well you wrote a blog recently. >> Yes. >> About the space edge. So I wanted to ask you about that. What's going on in the space, and that's the ultimate edge, I guess. >> The infinite edge. >> The infinite edge. Explain what you guys are doing there and why it's important. >> Well, this is exciting. Space travel for exploration and eventually colonization, if you would believe that, is happening. We have the first supercomputer technology in a NASA spaceship now. It has orbited the Earth well over 1,000 times and it is doing thousands of benchmarks and is doing very well, isn't failing. Now, why is that profound? Because again, that edge is so far away and the ability to push that back to Earth now, which we could call the data centers on Earth, is limited. It takes minutes, sometimes even longer. There's issues with reliability as well. So we were able to do that, and then we've created a new thing called Project Extreme Edge, where we're going to build Edgeline systems that will fit better with lower energy, smaller size in spaceships, and eventually in colonization, but we're just going into space travel and exploration right now. And I'd like to mention that HP Labs is a great participant in this because they're working on a technology, and the name of it is called the Dot-Product Engine. And dot-product is a mathematical operation needed in high-performance computing and artificial intelligence. But we're able to use that technology because it's small, it's fast, faster than we believe anything else on the market, and also it has a low energy profile. And those are all any edge, obviously, but it's also great for the space edge, and I like to quote Frank Sinatra when he said if I can make it there, I can make it anywhere, New York, New York. (laughs) Well, if we can make it in the space edge, these Earth edges will benefit as well. Some of the same challenges. >> All right, we're out of time, but I gotta ask you. Meg stopped by yesterday, and was giving great support for the intelligence. >> She has, yes. >> The company's now reporting the intelligent edge is gonna be one of the main areas. What about the new guy? Antonio. >> Antonio Neri. >> You know, what's your relationship with him, experience? Has he been focused on this area? >> Support? >> He's been great, he supports in three ways, let me just sum up in three ways. Number one, he supports in customer visits. He and I have been on customer visits together, it's always wonderful to have the president and now the new CEO with you affirming what we're doing. That's number one of three, number two of three, he supports the work we're doing with our new global IoT innovation labs, in fact our first grand opening, the first one in Houston, we will have one in Singapore opening in February, and then we'll have one in Europe and perhaps one in India, we're opening these labs for innovation, but my point is, the one in Houston, our first grand opening, Antonio Neri came personally and did the ribbon cutting and sponsored that as well. And then third, he is of course funding my business unit, and he's been very, very supportive and I'm really happy that he's staying with us and he'll be CEO. >> Excellent, Dr. Tom, thanks so much for coming on theCUBE. Congratulations, as you say, I know there's a long way to go, but looks like you're off to a great start and have some real traction. >> Tom: Thank you very much. >> So we appreciate your time and your insights. Okay, keep it right there buddy, we'll be back with our next guest. This is theCUBE, we're live from Madrid. Be right back. (upbeat electronic music)

>> Announcer: Live, from Las Vegas, It's the cube, covering VMWorld 2017, brought to you by VMWare and its ecosystem partners. (techno music) >> Welcome back, I'm Stu Miniman, joined by Keith Townsend, welcome back to the program, a multi-time cube-along. Patrick Osborne, who's the senior director of product management with Hewlett-Packard Enterprise. Patrick, great to see you. >> Great to be back, thanks for having me. >> Yeah, uh, what number VMWorld is this for you? >> Oh gosh, uh, it's, it's, I can't count it at this point, too many. >> Yeah, it's like I've been working with VMWare for 15 years, it's the eighth one of these for me. Keith, I know you've been few, so what's your take so far, the show? Big ecosystem, a lot of news going on. What do you think so far? >> Yeah so I mean, from my perspective, VMWare has been such a huge ecosystem partner for HP for forever, y'know? It covers everything from, y'know, from our perspective on the compute networking, storage side, certainly services. So um, y'know for me it's always good to catch up with, y'know, old colleagues and kind of understand what's going on in the industry. A lot of talk today around private cloud, multi-cloud, y'know, what people are doing around automation. Y'know certainly a lot of things around software defined, software defined networks, software defined storage, so uh, a lot of good topics, um, it's always good to see the customers here too, as well. >> Yeah uh, the joke a few years ago was VMWorld became storage world, so uh, y'know, in your space of availability, and data protection, y'know, and I walk through the show floor, HP's got a big boot but I see a lot of companies that are attacking different angles of that. You brought up the cloud being a, y'know increasing piece. >> What's top of mind, of a customers that are coming to you, and what sort of things are you working on these days? >> Yeah so, um, from our perspective on the storage and data management landscape, I think that you see a lot of vendors in the space right now. Some of them are certainly part of our ecosystem, you see folks like Veem and, y'know, other folks that we partner with out on the floor. There is an increased look from the customer perspective on availability. It's, the segment's changing, the requirements are changing. I don't think people are tackling availability in the same way as sort of traditional data protection architectures. So we see customers, especially when they're looking for certain inflection points in their infrastructure, like, I'm going to go to all flash, or y'know, deploy some new storage. They're definitely rethinking the way they're doing availability from an application standpoint. So we're uh, we're trying to y'know, meet those market demands through our own technologies, as well as having a pretty robust ecosystem here that we barter with. >> So a lot of talk, not just at this show, but at previous HP shows about hybrid IT. It's obvious the data center isn't going anywhere for the majority of customers, but we have the complexity of cloud. How does cloud impact, practically, data protection, data availability. >> Yeah so uh, from our perspective it's certainly an opportunity, right, to help customers out. We have a, we've, y'know, from a strategy standpoint, we've put a couple solutions and things into market that we hope address some of these cases. So y'know, when you talk about Nimble cloud volumes, right, being able to have your data in a co-located facility very close to, y'know, public clouds so you can do some compute arbitrage, and ultimately be able to, y'know, control your data. And then we do other things for example, Store one's cloud bay, being able to back up to the cloud, which is a pretty established use case. I think from our perspective, helping customers make that move in terms of, um, y'know, you can set up the data path, and make the bits move, but when we talk to mid-size, especially large enterprise customers, the governance around that, I think is really important, And the user experience, to make sure that what you're sending out to the cloud is certainly protected, it's audited. We've even had customers coming to us, we just had a big customer that you've had on here before, 21st Century Fox, right, a big customer of HPE talk last week about, I want to back up workloads that are in the cloud to the cloud, right? There's not a lot of great tools for that today, and I want that audited, and I want y'know, a paper trail around that for their own internal uh, capabilities. So I think there's a lot of opportunities in the space. It's very nascent. >> Yeah, Patrick I think you're bringing up a great point. We were talking a lot at this show, kind of the multi-cloud world. I've got my maturation of what's happening in my data center, deploying a bunch of sass on one or multiple public clouds. And there's certain things like security or y'know, data protection availability. I need to get my arms around all of it. HPE's looking to fill some of those y'know, gaps, and help customers, y'know. What's the overriding story in y'know how you're not one of the big three public cloud providers, but why does HP have a position in this discussion, and maybe you can help us kind of round out that story a little. >> Yeah so, we have a position in that discussion because of, y'know, we are very large infrastructure provider to a lot of customers, right? In terms of providing on-prem, hybrid IT experiences. From a public cloud perspective, we're very sort of, public in our strategy of not having a public cloud within HPE, but we certainly partner with folks and we've got a very long standing partnership with Microsoft. We come to market with things like Azure Stack, and we have a number of integrations we do with things like Nimble, and um, in that area we resell y'know, Azure, from an HPE standpoint. So we're really looking to provide y'know, a full experience for customers in that space. And y'know, the other day, like you said before, people are still going to buy and deploy in their data center, right? But, they want to buy and deploy in their data center with the thought that um, y'know multi-cloud is going to be a possibility, and they want to have the infrastructure that's going to allow them to do that. So what we're doing is incrementally, in our product portfolio, I care about storage, right, is to be able to provide those experiences. I buy a 3PAR all flash, I want to be able to tier that or back that up to the cloud. I have Nimble, right, I want to be able to replicate that to a co-located provider that provides Nimble cloud volumes, and then assign compute to and from the cloud, right. So a bunch of things that we want to get customers ready for, and make it easier for them. >> So can we talk a little bit more about that Nimble story? Y'know, the 3PAR, we understand it. It is, covers a great depth of use cases in enterprise, where does Nimble fit in the strategy? Yeah, um so we're super excited to have Nimble in the portfolio for three reasons. They have a great team, number one, they bring a really good go to market engine, and the sales team, y'know, with that, and they have great products. So from the product angle, which we're very interested in, is a couple different areas. Infosite, predictive analytics, right, is something that we want to apply to our entire product line, hands down. So the things that they do around VM Vision, right, with um, with VMWare, we want to apply that to 3PAR, right, and essentially give the people the simplicity that it takes to manage a very large virtualized environment. They have a lot of things that they've done that are very unique. I mentioned Nimble cloud volumes before, that's a use case for primary storage, but could easily be extended to backup, data protection, object storage, right, as not only just a technology provider, but as a way to price it, consume that type of storage. And then they also bring a number of things around, in the availability space, which we find is very interesting. Secondary flash, right. So you think, all flash as high performance maybe a higher cost, right? But certainly is going to help you with that application acceleration. They just, we just released the Nimble secondary flash array for workloads that are tech-dev cloned workloads, y'know, things you can automate, and that you need some performance on it. But it's more performance than your backup storage, not as much cost and not as much storage as your primary. So think about secondary flash as flash for secondary workloads. Very cost optimized. More performance, maybe a little bit more expensive than your backup tier. So there's a lot of things that they bring to the table from a technology standpoint that we want to take advantage of. >> Patrick, HPE's got a broad portfolio, but still to meet all the needs of the customers, especially in like, the divergals niche ecosystem, acquires a lot of partnerships. Where are the, kind of the deep integrations that your team's been doing, where are the places where customers have been asking you to kind of pull things in, and any solutions that you want to highlight specifically? Yeah so, um, I think more and more what you start to see is portfolio vendors, like HPE, they bring great technology that we build organically, or that we go and acquire. I think one of the big things that customers rely on us as well, that doesn't get a lot of air play is that we bring in a vetted ecosystem to a customer. Y'know, so the whole kit and caboodle, from compute networking storage, services to bring that all together, and an ecosystem that's supported, and we basically HPE stamp of quality and support behind that so, y'know when it comes to VMWare, obviously this has a huge ecosystem. So we do a lot with, y'know, innovating with VMWare. I mentioned Nimble, VM Vision, things we're doing there to make hypervisor environments quite a bit more easy to implement for customers from a storage angle. You talked to Jessie from the SimpliVity standpoint. We do a lot around data protection, with certain things, with 3PAR, Nimble. So there's a lot on integrations that we do in, for VMWare specifically, and then in other areas of the portfolio, especially automation, right. So we've got fully supported solutions, I think we've got one of the best docker implementations for storage with Nimble. Huge partnerships with Puppet and Kubernetes, and Sheb, all these great things around the automation side. So when we go out and partner with somebody, we're going to go provide a whole solution, a complete solution to a customer that's vetted, RA's, supported, so from my perspective, partnering is actually one of the most important things we do at HPE. >> So, from a customer's perspective, HPE hugely important, key industry player for most CIO's, you guys are still very very trusted in that area, you have a huge ecosystem, huge portfolio, what should CIO's, CTO's, high level architects be focused on at this point? What's like, the consistent theme that you're telling your customers you really need to pay atttention to this part of the industry? >> So, from a corporate perspective, we've got a couple of things that we're working on, right. So we talk about hybrid IT, right. And that sort of transformation from, I would call it established methodologies of application and development to y'know, sort of new style. And we're definitely helping customers along that journey, and a lot of it is around bringing this vetted portfolio and ecosystem along with the services. So the services I think is one thing that, um, y'know HP is very unique in the fact that we've got a very very broad set of services, in terms of, y'know, we can go and help CIO's and CFO's and CTO's understand y'know, where are you along that journey, right. All the way to implementation, I think one of the things that we're going to be very very focused on over the next couple of years, is providing everything in our portfolio as consumption based pricing, right. So all the things that you like about the cloud, right, the things that are implied there are elasticity, right, agility, consumption based. You're moving from a cap-ex to an op-ex model, making that more predictable. So we want to be able to model that, and provide those experiences. Definitely one of the things that we're really focused on in HPE is IOT in the edge, right, so, that's a very fundamental part of our business that we're going to be looking at to make a lot of investments in big data. Certainly, some of the assets are on Edgeline and Aruba, and all the implications around security for that. So those are some of the key areas that we are, y'know, we talk to CIO's every day about. >> Patrick, from an availability and data protection standpoint, what does something like IOT mean? I have to think, we're not going to store all the data, lots of it's just going to be processed at the edge, we're talking a lot about edge so, I'm curious, what are the things that you're looking at, maybe start there, I think about like, containers, or a lot of times going to be something that is going to fit at that kind, maybe even serverless at the edge, so y'know, I seem to think back, y'know, when we talk about like oh, we're going to go to object store and therefore the way I do everything changes. So y'know, are we going to, couple years from now, is this going to be a very different discussion? >> Well I think, yeah, it's an interesting topic, right. When you talk about that volume of data, right, and the fact that it's very dispersed, right, being able to do, apply traditional availability techniques to something like that is um, it's difficult, it's next to impossible, right? So, um, y'know what we see is customers buying, in these type of ecosystems, you're not buying along horizontal lines, right. You're not buying a specific server vendor, or a networking vendor, or y'know, a storage vendor, and then going best of breed, trying to integrate that yourself. A lot of these things are vertically oriented now in terms of you're buying a stack, y'know, from a portfolio vendor or going to a service, y'know, an integrator. And I think with he volume of data that it takes to, to do some of these implementations, so we have very large customers, autonomous cars, y'know big, big implementations of Hadoop and analytics. I mean a lot of that stuff is built in. I think one thing you're starting to see is that, those types of deployments are outstripping or outpacing, y'know running away from the support of the traditional IT folks. So we have customers that are operationalizing, very large Hadoop customers for example, who don't have methodologies for backing that up and replicate it, so I think there's a lot of technology that needs to catch up with some of these implementations, we see it all the time. So, y'know, I think there's different techniques from a technology standpoint. Y'know, when we try to approach these from a customer perspective, we want to provide a full stack for edge, IOT, um, and but, from a data protection availability standpoint, that's a difficult problem to solve. >> Stu: Well Patrick Osborne, always a pleasure to catch up with you, thanks for all the updates here. Looking forward to tracking some of those, y'know, emerging areas that you were just-- >> Yeah, I look forward to talking to you guys in Discover in Madrid. >> Absolutely, so The Cube, so many events, check out siliconangle.tv, or actually thecube.net is where you're going to be able to see everything. Nice shorter url, you're going to keep the branding of The Cube, for Keith Townsend, I'm Stu Miniman, stay with us, watch more coverage here still to come. VM World 2017, you're watching The Cube. (techno music)

>> Presenter: Live from Las Vegas it's theCUBE covering HPE Discover 2017, brought to you by Hewlett Packard Enterprise. (light techno music) >> Okay welcome back everyone we are here live in Las Vegas for HP Discover 2017. This is SiliconANGLE's, theCUBE is our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, the co-founder and co-CEO of SiliconANGLE with my co-founder and co-CEO Dave Vellante with Wikibon, and our next guest is Alain Andreoli, who's the Senior Vice and President General Manager of the DCIG, the Data Center Infrastructure Group at HPE. Great to see you, welcome back to theCUBE. >> Thank you, it's a pleasure to be here again. >> Great show, you guys have a lot of great innovations. Notable was the analyst press conference that we were at. You were feeling all the questions, the buzz around Gen10 and all the action you guys are putting inside the new service from security to all the innovation that's happening, pretty great opportunity and the true private cloud numbers coming out of Wikibon are showing fastest growth is cloud on-prem. This points to significant opportunities, your thoughts? >> Yeah, well, the need for compute is clearly growing and you continue to grow forever. What we see is that the compute points are also expanding so it can be on-prem, it can be off-prem, it can be in the edge, and on-prem there is a bit of a revolution which is coming from the experience of the public cloud, and so, private clouds are becoming very, very fancy. So you see on-prem compute basically turning into two families, very specialized for high-performance computing, for mission-critical, for AI, and others. The things that are really, very critical to the business. And then for all the other workloads, they need flexibility like a public cloud but on-prem because they can keep control, they want to mimic the agility and they want to have the same economic level. So we are playing on both fronts, we are doing very well on the specialized front with HPC Acquisitions of HDI and so on, and we are making a breakthrough on the private cloud with Synergy and soon with the new stack. >> So the whole notion of DevOps and cloud have opened up the doors and certainly you guys have been very clear with the simplicity message. Big data is big part of the application process, cloud providers, multiple clouds, so this right mix conversation-- >> Alain: The right mix, the right mix >> Is what Meg is putting out their is a nice message, and what you're saying is "hey the on-prem is not going "anywhere and we have the data to prove it." But you look at the big clients, they want the control. What is the conversation that you're having when you say, "Hey I need more capabilities," obviously high-performance computing, powering AI, and machine-learning, we're seeing, obviously those things. But from the business model side, what are the customers asking from you for solutions? What are the key things they want from HPE right now? What is that-- >> In terms of economic control? >> Solutions that are top priorities. When they sit down and say, "Well, you know, I need more compute." Okay, what does than mean? What specifically are you building for customers to help them with the digital transformation, to simplify the business model of on-prem with cloud and to deal with the multi-cloud world. >> So, they believe that the management of the mix between the different alternatives that they have right now with, certainly, a complexity and they rely on us to take this complexity away. So we are very bullish about the project New Stack because we think that this will allow data to be managed across the different horizons in the data center, across multiclouds and with more and more data being created and eventually computed at the edge. So these three horizons together make intelligent distributed computing, which will be more self-tuning, which will be extreme data analytics, and ultimately, this will allow customers to manage data seamlessly across everything. We think that this is kind of strategically where our customers want to be. Then the way they get there depends. Some customers have a view, which is just modernization of what they have right now. Some of the customers want to be more dramatic and run everything they have as if it was a seamless cloud, and then they have to decide the mix between on-prem and on-prem. Most of the customers, I was looking at what is actually making the public cloud. More than 50% are born from the cloud, they are people who never had the data center and may never have one until they grow up because then when they grow up, they need one. >> John: (chuckles) For control? >> What we have learned, for control-- >> John: And expense-- >> Dave: The Cloud Cliff. >> Expense, That's The Cloud Cliff. So, more than half of the public cloud customers never had a data center. About 15%, 15, 16% of the customers of the public cloud are consumers. And then, you have a small third which are enterprises. That's the first thing to realize, right? That the move of the enterprise is still pretty small. I was discussing with the largest systems integrator in Germany yesterday, and their view is the German perspective, because here in the US we have a tendency to believe that everything is public cloud or will be. The German view is totally different, for instance. So, I think, you know, we have gone through a cycle which has been public-cloud-heavy in terms of marcom where the market believed that public cloud was going to be everything, and we are now landing in a reality zone where this mix is an opportunity for the customers. They have some trivial workloads that can go on the public cloud, but we see that on-prem remains, basically, what people are doing. >> That last point's really important because even though you said, "Well, less than maybe a third is enterprises "in the public cloud," if you look and feel the workloads that are going to the public cloud, it's not the core of enterprise IT workloads. >> So what I believe is that we are thinking it the wrong way when we think in public cloud and which workload goes there. The workloads are not going to the public cloud. It's that a lot of the workloads that used to be run on-prem are now coming from the cloud, SaaS-- >> John: Right. >> That's different, that is very different. So, customers are not deciding what is on-prem, off-prem, they are now looking at software packages that come from the cloud, like Salesforce, or others. And this means that while they're running their data center as vital applications that don't come from the cloud, so it's more and more specialized, and then they have a variety of applications that don't come from the cloud, that they will run on their public cloud. This is why I see these two topologies, if you want, of specialized-- >> John: Yeah. >> Super compute and data-centric, and then, very fluid, and this where Synergy plays so well, because Synergy allows this fluidity-- >> John: Yeah. >> Of pools of resources, and you can basically adjust to the various applications that you have. >> Oh, this is classic early adopter kind of behavior, you mentioned the SaaS coming in and being influenced because they're easy to get into right? You can get some subscription and get some value, but then I think the true private cloud is interesting to me because what it really shows, to extend your point, is that the business models are changing for the agility piece, that's the DevOps. So, as you see IT consumption changing to cloud-like, or true private cloud-- >> Dave: Yep, yep, yep, yep. >> Essentially, that is an OPEX business model. So, the business transformation is now where the rubber hits the road for what digital is. So to me, we see this dynamic so with that being said, what aspects of HP taking advantage of? You mention Synergy, what else do you guys have cookin' up? What's out there that customers are using to turn the knob and go faster on the acceleration on that? >> With customers, I wouldn't like us to look at customers only as being enterprises, because as more and more business is being generated from the cloud, people who do business from the cloud, whether they are enterprise service providers, or software providers, or business born from the cloud, these people also acquire technology, and they have need for services, and they require infrastructure. So, this is a segment of the market where we're going to to double down in the future. So, we are looking, we call them, like, Tier 2, Tier 3's, because the very large ones have a tendency to try to build their own things-- >> John: Yeah, service providers-- >> But, a lot of other service providers and there are-- >> John: Cloud service providers. >> You know, a small third of the market also demand technology and support from us. So, we are going to expand our cloud line strategy. We are going to offer open systems, and be very aggressive there, both for compute, storage and for networking. So there are kind of two prevalent markets. If you want more, there is a market of completely open systems, we call them whiteboxes, you know, we call them for the cloud, Cloudline, which is now a multi-billion dollar business for us. And then you have the people who want products that offer a lot of value that are differentiated, like Synergy, like Proliant, like Blade Systems, like 3PAR, like Nimble, and so on, and obviously we are doubling down on these as well with our Acquisitions and own development like Gen10. >> So the narrative from Hewlett Packard Enterprise and all of your competitors is, you know, hybrid is the reality, fair enough-- >> Alain: That's for sure. >> And we agree, but there is an aspect of zero-sum game here in that the markets at the macro level are not growing like they used to. So, market share becomes very, very important. You've put up a slide in your keynote, 81 straight quarters of leadership. Now, we all know that you can play games with the numbers, but the most important metric we would argue is revenue share. If you're number one in revenue, that's the true market leadership. So you've had 81 straight quarters of leadership, as we've just defined leadership. That's 20 years. >> In this quarter, we had leadership, and next quarter I think we'll have leadership as well-- >> Dave: How have you been able to do that? >> We are not looking at market share for the sake of market share. We want to bring value to our customers and to our shareholders. So if there is, moving forward, a part of the market that does not yield value for either party, we may not want to measure our market share against that because we may not define this as being our own market. But so far, we are leading the overall market in compute. We are now a strong number two in storage, with the acquisition of Nimble, and we're happy to be there. But our strategy is not being number one for the sake of being number one. >> Now on Dave's point, I'm very critical on this, I've been readin' about it, and again I may be overstepping my boundaries here, but I believe that if we're going to a new era of modern computing, dull metrics don't apply because everybody seems to be number one at something. I go to so many shows where I go to Dave where I'm number one in this, I'm-- So, the question is if the old is shifting to a new model, and it's horizontally scalable, vertically specialized kind of a marketplace, which you guys are addressing with some of your tech, what are the metrics? So that we're asking ourselves the question, what should be the benchmark standard? >> So I have a strong point of view and I was discussing with an analyst last night, we had dinner, and I've had the same point of view for the last couple of years. The history of the market is to measure by product category: rack, towers, old flash arrays, disk arrays, mixed arrays, and so on. I think this is a rear mirror view, it doesn't matter. The decisions that customers are making are: what is my specialized computing? Which includes computing, storage, networking. What is my specialized data center, basically. What is my private cloud? Then what is my consumption of IT coming from service providers and therefore, you have the service provider market, which itself can be separated into different segments. That's the way to measure the business. So, I want to be leader in specialized compute. I want to be leader in private cloud because this is what enterprise will be consuming. And basically, we're already leaders there, but I want to be continue to be leader in providing gear to service providers, who have decided to rely on partners to build their data centers and not build them themselves. This makes sense, because then you look at the market differently, you're not looking at micro-territory-- >> John: I agree, I 100% agree with you. >> Density, optimized whatever, you're saying, okay, what is a service provider going to need in the future? What is going to be specialized computing in the future? What is going to be a private cloud in the future? Once you have covered that-- >> John: Yeah. >> What is going to be compute at the edge in the future? And what do you need to orchestrate all the data? These are the clusters of the market that matters. They are the ones we are pressuring and they are the ones-- >> And you could be building technology-- 100% agree with you, I would also add, by the way, I agree with you 100%, and I would even amplify it by saying you could be building something new, like a server, chips, silicon security, that has no category. So how does that relate into things-- (laughing) >> Well, Synergy is the category. >> Dave: Right. >> You know, it's-- >> 'Cause it's horizontally scalable, so again, you could be number one, two, or three by the old categories, but be wholistically number one in the market. >> So, I think it's more, you know, it's more categories of business outcomes. >> John: Yeah. >> Like, specialized high performance, you know, flexibility, agility of a private cloud. I think that's, you know, so, if you make a parallel with the car industry, you can say is the market, like, diesel engine, or gas engine, or electric engine, or is it like sport cars, SUVs, or whatever. I want us to look at SUVs and sport cars, how do we do the best SUV? How do we do the best sports car? Versus, you know-- >> John: The components, and do how you have-- >> This technical view of it's a rack or it's a tower. >> Yeah. >> And how do you add the most value for customers-- >> Yeah. >> That is profitable for shareholders? >> At the end of the day, when we have our argument in our office about this on the research side, we say, "Look, at the end of the day, "let's identify some of these new catego-- and try 'em, not measurement points, but customers and revenue can't lie. If you have customers, here it is, number of customers. >> And so, the problem then is to measure it. Once you have defined what is right metrics, can you measure it? >> John: Right. >> And so, unfortunately, the analyst today cannot measure the market where it has evolved. So we are still looking at rack and towers, and so on, and I think this is wrong, the wrong view. >> Okay, so, talk about the hot thing that we like is the Root of Trust product, the silicon thing that's called the Root of Trust, you know, with the firmware thing. This seems to be getting a lot of buzz to show. It's innovation, we had some independent testers on with your guys, and the Gen10, this is pretty impressive. Thoughts on, is this the kind of direction you continue to go with, what's your thoughts on this security-- >> Well, we think security's super important and, you know, you open the newspaper or the TV today, and you see what's happening, it's quite amazing, including today, what's happening today, here in the US. So, it's incidental the we come in just today with our new generation of compute, but it's taken two years of interviews with customers to really understand what's most important to them. And the risk of cyber threat has turned enormous, and I think that you have been interviewing experts from the FBI, and so on-- >> John: Yeah, right. >> During this session, who came here and help us to build this solution. And I think we're coming at the right time with the right solution that will take a few years to our competitors to try to match that, and then we'll go in this direction because that's the only way technically you can do it. >> John: Yeah. >> It's at the silicon level, so you basically have unique encoding on your server in silicon, and the firmware always, you know, compares itself throughout the whole life cycle of the server, even before the server is finally built through this Root of Trust. I think we've done this extremely well, I'm very, very proud of our ingenious. >> And it's been validated against the The NIST, NIST Securities Team, and so, congratulations on that. >> Alain: And these are the most stringent startups in the industry, right? >> It's pretty impressive, I mean, this has been a trend that we've been seeing, the silicon, the silicon angle, no pun intended. But it's interesting, and always, security's come up in the past, people want that. And with IoT, the support, the attack vectors can be sealed up pretty well-- >> And so are our Edgeline products, they have IDOL 5, and so, they will also have access to this technology. >> Great innovation, thanks for coming on theCUBE, really appreciate you share the insight. I'll give you a final word here. Share with the audience something you think they should know about HPE right now that they may not know about, I know the messaging's pretty simple, you got the nice messaging, but going beyond the messaging, what would you like to share with the audience about your group and HPE's innovation coming out of Discover 2017? >> You feel the buzz here, you can see, I think we have never been in such a focused and clear position, we exactly know the businesses we are pressuring, the Hybrid IT make it simpler, and the edge, and the service to make it happen. We are just crystal clear. But when you put the three together, you get to this dimension of intelligent distributed computing, and this is a market that we will lead in the future. Also, we are such a strong and stable company. We will have over $12 billion of cash net in our balance sheet by the end of next month. And this puts us in a position to continue to double down on these bets we have made for the future of the market. So we are very, very confident that we are in a great spot, and frankly, it's great now because it feels like we are starting to be a destination. The last 18 months, we separated from some of our legacy friends, and now, not only are we on our own, but we have a clear strategy moving forward. We are proving that we are implementing it with the six acquisitions that we have made over the last few months, and more in the pipeline, continuing to deliver the capability to integrate these acquisitions, and the capability to continue to motivate our customers to be with us. >> And the spotlight is on you guys, we'll be tracking it, thanks for coming on theCUBE, really appreciate it, Senior Vice President, General Manager of the Data Center Infrastructure Group, sharing his opinion here on what's happening and where's it going in the future for HPE. We'll be back with more live coverage with theCUBE, here in Las Vegas after the short break. I'm John Furrier with Dave Vellante, we'll be right back, stay with us. (light techno music)

>> Announcer: Live from Las Vegas, it's theCUBE, covering HPE Discover 2017. Brought to you by Hewlett Packard Enterprise. (upbeat techno music) >> Welcome back everyone, we're here live in Las Vegas for theCUBE's exclusive three days of coverage for Hewlett Packard Enterprise's Discover 2017, also known as HPE Discover, I'm Jeff Furrier siliconANGLE, here is my co-host, David Villante with Wikibon.org Our next guests are Jeff Carlat, Senior Director, Solutions Good Market for HPE, Internet of Things and Tushar Halgali, who's the IoT Senior Manager at Deloitte these guys putting together all the solutions. Welcome back to theCube, great to meet you, thanks for joining us. >> Jeff: You bet, it's great to be here. Great to see you guys again. >> So one of the things, actually, digital transformation which is really overblown we all know we are in this digital transformation wave. But the thing that we've been hearing on the queue over the past, I'd say 6 months of event coverage, the consistent theme with digital transformation is business transformation, and really people putting it into action. And that really is whether it's a service provider we've heard from earlier, and also just businesses trying to get their value chains and reconstruct their architectures at a business level but then having their infrastructure be responsive to that. And that's cool, but really IoT has kind of changed the equation, right, that's what you guys are doing so I want just dig right into it, IoT wave that's hitting here. >> Jeff: Right >> John: Your thoughts on the impact to customers in real time to their world. I mean obviously they have refresh cycles they're going through all kinds of infrastructure they had apps, Cloud-native on the horizon, Hybrid Cloud what's the impact to their business? How has IoT changed the game for the customers? >> Jeff: Well I'll start it, you can add on. First off, IoT brings the promise of changing the game, but not everyone is really realizing that yet, first-off because right now there's still many, many business challenges for companies of all sizes. Ya know the lack of internal corporate sponsorship to do a massive transformation and change, or the organization and the culture within. Cause you're talkin' a full life cycle digitization rather than, ya know investing or dropping new applications technology wise we've got problems, IoT represents IT merging with OT, so you've got this partnership and your solutions and offerings need to transcend your core data center and your IT technologies with the traditional operational technologies. You're talking companies that have been, Bosch and National Instruments, and folks that have been in the marketplace for some time so it's harder, it's heavy lifting, and there're limitations in the customer environment around the current IT architecture, so first and foremost to get the benefit, you've got to get them across the chasm to be able to deliver that new transformation. >> John: Tushar, I want you to weigh-in on this because the question also kind of digging in here a bit kind of subtext of the original question, where's the mindset of the customer? Are they having a wake-up call moment, are they beyond that? Where are they in the progress bar, if you will, on the IoT? Yeah, they've had some pre-existing infrastructure, operational technologies, sensors. Is it a wake-up call? Where are they? >> Tushar: Yeah, so I mean I think what is happening really is that a lot of organizations are now beginning to look into business outcomes and what technology does for them, right. A lot of them are saying "Well why should we invest on anything else?" So, companies are becoming really focused on top line growth ya know, bottom line cost optimization, and ultimately margin improvement for their shareholders. So, as industry lines are blurring, as new entrants are coming into markets, and new threats are being created there is more pressure from shareholders to come up with new growth opportunities. IoT as a field is sort of encapsulates, and takes all these different technology domains and puts it all together. Case and example, I mean, since 1970 to 2010 the worldwide productivity for manufacturing was about four percent every year, and then it just dropped to one percent. Now that's a really big deal, right. Manufacturing costs are about 18-20 percent of the costs of goods sold for a manufacturing client, so how do you increase the productivity because any impact on the productivity, or reduced down time for a manufacturing client, not only has cause on revenue but also a lot on the profit margin, right. The same thing around retailers. Because of the online presence, and because of the sales are increasing over there retail margins have reduced from 10.5 percent to about 9 percent. So retailers are asking "Well, how do we increase our sales in the in-store channel?" Where 85 percent of their sales are coming. So IoT is a huge component in delivering that. >> John: You bring up a good point. What I love about the IoT, and some of the stuff you guys are doing, is that it's the confluence of big data meets real infrastructure, and what you're referring to we hear this in the ad business all the time. "I don't know where my spins going." It's an instrumentation game, right. So talk about that impact because now actually not an art it's actually science as well. You can actually instrument it and focus on those areas. >> Tushar: I mean absolutely, just to build on the marketing story that you just talked about, that's a huge piece in retail, right. So if you have a multi-brand retailer you want to be able to not only see what your customers are doing, but also try and monetize the data. So one channel is to look into who your marketers are, advertisers are, and then be able to place the ad at the right place, in the right context with the consumer that you might have in your store. And a lot of this is about in-store data attribution right. What is the ROI that marketers and the advertisers are getting back for the spin that they have. And so ROI with the help of, Beacons and Colts and wifi all these technologies, is able to sort of capture all of that location data the contextual data, the behavioral data of the clients along with wireless infrastructure data. Put it all together and create that picture. >> Jeff: And what I'm seeing customers are kind of one of two camps. Those that understand a grocket, but they don't know where to start. How do I truly start digitizing? Then the other ones are they don't fully realize the value and the necessity to start transforming, or their going to be out of business. >> Tushar: Yep. >> Jeff: I mean go look at a lot of examples, your brick and mortars >> Tushar: Yep. >> Jeff: talk about your retails. I think this is where we're coming together to really deliver and make it easier for those clients... >> John: It's the classic case of early adopters. Believers and non-believers, and the believers kind of go jump in the deep end, waffle around, learn how to swim. And then the non-believers become believers cause they get bitten in the butt with cost >> Jeff: Yeah. >> John: or some sort of impact. >> Jeff: Exactly right. >> Tushar: Or their out of business. >> David: But it's a really hard problem for organizations. So and you mentioned it before, is that companies have to go through their digital transformation, but they have to fund it. And it's hard to fund it if your having to grow your top-line, and cut the cost of your legacy systems. Okay so part of the problem is you talk about digital transformation, it's all about technology, it's all about data certainly IoT plays into that as John pointed out but people really don't understand the value of their data. The accounting industry doesn't recognize value of data on the balance sheet. There's really no standards. People don't know how to monetize data. So how can you guys help customers through those really gnarly problems? Where do you start? >> Tushar: Well I mean what we started with was an industry focused view, right. So Deloitte goes to the market by industry, so let's take retail and manufacturing, whichever the case might be, and what we really are looking into is an industrial digital value chain transformation story. So we'll take the value chain off an industry, break it down into processes, and then break that down further into use cases. We'll look at a use case, look at the value drivers of the use case. See what economic impact, or the business outcomes that might be derived of those use cases. And then when you aggregate all of them it starts creating a shareholder value impact, and that becomes really interesting. So case and example, for a retailer you can look at improving the basket size, or in-store conversion improving the the foot fall traffic. All of that improves the growth, increases the revenue. You talk about asset efficiency or improving the resources or the associates, their utilization to store the supply chain operations improvement. All of that improves the cost optimization and together impacts the margin. So we put that picture together for our clients to see in real economic terms. >> David: And data sits at the center of that analysis, right? >> Tushar: Well, correct. So the enablement of the use cases happen through technology and as the various facets of technology, the ERB system, the CRM the point-of-sales, the Beacons, the wifi all work together. The data generated will create 360 degree views of the customer, which then leads to all of these outcomes. >> John: Tushar talk about the value chain piece on that. Because I think that's indicative of IoT's impact as well as other things that are digitally connected. What is the difference between the digital value chain, in terms of its configuration its value, verus non-digital? How they used to approach it from a management perspective, and obviously digital is a little bit different. Is there any characteristics you can point out that you've seen in your observations, and with your engagement with customers, that jump out? >> Tushar: Sure, I mean the traditional value chain I think is very linear, right. If you take a manufacturing value chain for example a lot of it was let's do R&D, come up with a product, then let's go procure the product, the raw materials. Then make the product, then you ship it, logistics, and then you do after sale services. It's very linear one after the other. With the admit of data and the way you capture at every stage of the value chain. Well different stages now talk to one another. So as a machine is about to break you can create a new order, and then it improves the production. So it's less linear and more interrelated, and so the value chain is no longer very simple it's very complex, but by showing visibility into each stage of the value chain, that's where value created and captured from. >> David: And the data model is very complex, >> Tushar: Absolutely. >> David: Before you've got external data and now you've got a whole new data quality challenge >> Tushar: That's right. >> David: and data access challenge. Okay so back to John's question about where are we on the maturity meter? Is it sort of second inning here or the game is just starting, national anthem? >> Jeff: Well, hey for certain industries I think we're on second inning. You go look at areas like oil and gas, I mean there is a lot of historical work going on around machine learning, AI. Go and look at automotive, autonomous vehicles semi-autonomous vehicles, I think that's advancing and advancing rapidly. But I'll guarantee there are many, many industries that they don't even realize how much data they have. And yes there may be tag in two to three percent of that. This is a new wave. This is a really, really exciting time. >> John: So Jeff, on that point are you finding that, that makes a lot of sense actually if people have existing operational technologies, they have some legacy experience in some systems. It may not be connected to IT so they have some legacy with respect to that piece. >> Jeff: Perfect, perfect example. Part of our joint partnership and the announcement that we're making together around IoT is not only deliver the consulting the advisory services, but we're delivering prepackaged offerings specifically for vertical use margins. Asset maintenance and monitoring, we're coming together, bringing together our edge line capabilities we're bringing together PTC and National Instruments from the center. Bringing all this together in consortium, building an appliance and its going through consulting of nature of proof of concept to show and prove through proof of concepts the value that a customer can achieve by harnessing all that data, and being able to actually drive predictive analytics and then well once they see the benefits of that the value, the proof in the pudding, they will expand that across their entire production line, then its just going to go skyrocket. >> John: Alright talk about the relationship with Deloitte. I'd like you guys to just take us through a day in the life of a use case and how someone would envision and engage with you guys. Obviously Deloitte well known on the services side you guys got great credibility and track record, also with you guys IoT new market, how do you guys engage? What does a joint relationship look like? Take us through an example. >> Jeff: Well I'll start. First off we're building off of twenty years of joint partnership together, and a day in the life is we strategically sit down and we take the assets we can bring to the table as the new HPE, and that spans heavily the infrastructure and some of the support, point next services capability and we bring that in with the capabilities of Deloitte and we build these offerings, and we build a comprehensive program to take it to market, and have those discussions at the right level of the organization and hold their hand through this whole transformation process. Don't worry we got ya covered. We can help you get through this, and we can demonstrate the value on the returns. >> Tushar: So yeah, I'll just build on this. Some of the offerings that we have built together now, so as we get a client who's let's say interested in IoT what we'd actually do is sort of work with them and say let's do an IoT workshop, right. It might be a one day workshop, we might get our industry experts that are very focused on the vertical. We might get our technology experts. We might get our ecosystem partners who are doing startups and things of that sort, so they kind of know what is going on in the marketplace. We're together then we'll sit down we'll figure out what's a value chain transformation story. What are the things, let's say a manufacturing client just take for example, needs to do to go from a modern factory to connected factory to a smart factory to do that manufacturing transformation story. What are those 50 60 use cases that they need to go through. And out of that what are the one or two use cases that they need to do today that'll deliver near term tangible value. So for those 50-60 let's create the business case that delivers the enterprise shareholder return. Today what do they need to do to get that quick win. Take those two-three use cases, the offerings that Jeff spoke about, let's take those offerings and within 8 weeks let's deliver a proof of concept that shows the client I can take one of your assets, connect them, get the data out, show the inside, and then create the roadmap for scaling it out to make it a reality. >> Jeff: Start small, think big, and scale fast. That's what we say. >> John: Alright that's a great point I'm glad you brought that up because I want to ask the tough question. Cause this is the bottom line, we hear a lot of customers through our research Wikibon team, and we get a lot of "There's tons of barriers in front of me." So I want to ask you what are the barriers and how do they get over those obstacles, but also privately a lot of CXOs say to us, "Look it, this is like a four year sports contract, if I'm not up and running in four years, I'm out of job." So the notion of bringing the consultant, and HP, and we're going to do a focus group, and we're going to lay this out. The old days, back in the early ERP days, those time cycles were 18 months just to get going, and do the organizational transformation. They need proof on the table immediately. >> Tushar: That's right. >> John: So the Ford CEO was replaced, not sayin that was because of this, but people have short tenure, they need to see results immediately. >> Tushar: That's right. >> John: So the psychology of the pressure, with the work that needs to get done are two huge issues. What are the obstacles? And then the psychology of showing the results immediately. >> Tushar: I think in terms of the sort of business challenges we have a lot of centers around leadership and sponsorship. Do you have a tech focused culture in the company? Right. Is there collaboration between business and IT? Do you have expertise for IoT within the business, or within the enterprise and outside? Right. Those are some very basic, it's people, people, people all the time. From a technology stand point a lot of this is around the whole IT OT convergence piece of things. Right, it's this very complex domain. Nobody has all the knowledge base, so how do you get that to work? And traditionally IT hasn't played well with OT and vice versa. So how do you get that? Standards are evolving around security, privacy things of that sort, so how do you keep up with that? And finally, there are so many different solutions. How you do make sense out of that? Procurement is painful, right. And that's where some of the solutions like Jeff talked about were made. The solutions were at the procurement cycle becomes really simple. >> John: So tons of choices out there, >> Tushar: Right, >> John: That's an obstacle init of itself. >> Tushar: Exactly >> Jeff: Yeah >> Tushar: So how do we deal with these challenges, and how do we jumpstart the story. If you take the principle of agile and software development that's what we have pulled into our offerings, right. Instead of spending three, four, six months in trying to figure out what the universe is going to look like, and how things will change, it's not like that. We've taken sprint approaches to our delivery, like I shared earlier it's about that one day IoT journey workshop, quickly get that done, get it out of the way. >> John: Not a lot of waterfall, which that prolongs that organizational transformation piece >> Tushar: Correct. And then its constant recalibration, that's what we want to focus on. Let's show some quick wins in eight week increments. >> Jeff: And I'll guarantee as we are showing the quick wins in certain verticals, their dropping like dominoes because when they see their competition all of sudden gain efficiencies and providing greater experience for their clients or their customers, believe me everyone wants a piece of that. >> John: Bottom line there's obstacles to point. Move fast, start small, think big, move fast, I love that. And again there's a psychology out there it's real, and being agile, the waterfall takes too long. Alright guys thanks so much for sharing the inside of IoT, congratulations. Event here, what do you think, what's going on for you guys real quick we'll end the segment, final words. >> Jeff: Final words? >> John: 2017 Discover, what's your take away so far? >> Tushar: Well my take away is we are just at the cusp here. In IoT we are still in the, I'd call it the crawl stages of this. IoT's going to be huge, very exciting times coming, and it's going to impact every industry. >> Jeff: Yeah my parting word, I love to see the partner first mentality we have in here. The fact that we are here with all SIs our OT partners. I also love to see we are now building and designing innovations, such as the HP Edgeline Conversion systems from the ground up, specifically for IoT, same thing with Aruba Portfolios. We got a great set of tools and a great set of partners to work with. >> John: We didn't bring up Aruba, we had a big conversation on that earlier. Tushar, Jeff thanks so much for sharing the insight. Internet of Things, Industrial of Things. This theCube, the video of things here at HPE Discover 2017 I'm John Furrier, Dave Villante. We'll be back with more coverage after this short break. Stay with us. (upbeat techno music)