>>Hey everyone. Welcome back to Miami, Miami Beach. Specifically, not a bad location to have a conference. Lisa Martin here with the Cube live at IFS Unleashed. We're gonna be having a great conversation next about Ization moments of Service Rules. Royces here, as is the C of IFS for aerospace and defense. Scott Camani. Nick Ward joins us as well, the VP of Digital Systems at Roll Royce. Guys, excited to have you on the program and welcome back. >>Thank you very much. Nice to be back. It's >>Been three years since the last IFS show. I love How's Scott? I was talking with Darren Roots earlier today and I said, Well, didn't it used to be IFS world? And he said, Yes. And I said, I love the name. I would love to, to unpack that with your cheek marketing officer because it, there's a lot of, of, of power behind Unleash. A lot of companies do such and such world or accelerate, but we're talking about unleashing the power of the technology to help customers deliver those moments of service. Yes. Love it. So Scott, start us off here. Talk about ization. That's a relatively new term to me. Sure. Help me understand what it means, because IFS is a pioneer in this sense. >>We are. So one of the things that IFS is always trying to do is to try to find a way to help our customers to realize a moment of service. And that moment of service is really when they found the ability to delight their customers. And when we look at the way in which we're trying to drive those business outcomes for our customers, ization seems to be at the core of it. So whether it's the ability for a company to use a product, a service, or an outcome, they're driving ization in a way where they're shaping their business. They're orchestrating their customers and their people and their assets behind a val value chain that helps them to provide a delightful experience for their customers. And with IFS being focused on Lifecycle asset management, we no longer have customers that have to choose from best of suite or best of breed. They can actually have both with ifs. And that's something we're really excited to provide to our customers and more excited for our customers to realize that value with their customers, their partners. Along the way. >>You, you mentioned customer delight and it's a term that we, we all use it, right? But there's so much power and, and capabilities and metrics behind that phrase, customer delight, which will unpack Nick bringing you into the conversation. Talk to us a little bit about what your role is at Rolls Royce. My first thought when I saw you was, oh, the fancy cars, but we're talking about aerospace and the fence, so give us a little bit of a history. >>Okay. So yes, we don't make cars is the first point. So we are, we are power, we do power as a service. So we are most well known, I guess for large aircraft airliners. You know, if you've, if you've flown here to Miami, there's probably a 50 50 chance you've flown on a Rod Roy powered aircraft. Our market segment is what we call wide bodied aircraft where you go on, there's two aisles. So the larger section of the market, and we, we provide power, so we provide the engines, but more importantly, we've been a ization company, a service company for at least two decades. We, we have a, a service relationship we call total care. And the whole idea of total care is, yes, I have my engine, it's on my aircraft, but I take care of it. I make sure it's available to fly when you need to fly it. And all of the things that have to come together to make that happen, it's a service company. >>Service company. Talk to me a little bit about, and I wanna get got your perspective as well, but the relationship that Roll Royce and IFS have this is a little bit unique. >>Well, I can start, but I I think Nick's gonna be better served to tell us about that as our customer. Nick and I actually started this journey about four years ago, and what we did was, is we were working closely with our perspective customer Rolls-Royce identified what they were looking for as a desired business outcome. And then we found a way through the technology and the software that we provide to all of our enterprise customers globally to find a solution that actually helped to provide a, an outcome not only to Rolls-Royce, but also to our collective downstream customers, commercial operators around the globe. So that's where we started the journey and we're continuing our discussions around other solutions, but that's how we started and it's been an incredible partnership. We're so happy and proud to have Nick as a customer and a advocate of all things ifs and I'll let him kind of continue from his point of view how he sees the partnership in the relationship. >>No, thank you Scott. I think we've, we've always, we've valued the kind of relationship that we have because I think IFS has always got Rolls Royce in terms of strategic direction. What do we try to do? I said, we're a service company. You know, we, we are, we have to have a service relationship with our, our customers, our airlines. To have a service relationship, you have to be able to connect to your service customer. And ifs is a big part of how we connect for data. That's how do we understand what the airline is doing with the engines, but it's also how we return data back into the airline. So we are, we're get a very close integrated relation between us, our airlines, through a bridge that, that ifs create through the maintenance product. Got it. So it works really well. >>I I think I'd make one other point. One of the things that we've always focused on is quantifiable business value. The only way a partnership like this could possibly work is if we have a desired business outcome, but if we're providing value, So the value work that we did in conjunction with Rolls Royce and really identifying that helped to support the business case that allowed this partnership to really begin and flourish. So I I, I'd be remiss if I didn't mention that business value element that's really core to everything we do and all the, the conversations that Nick and I have. >>Well, it's all about outcomes. Absolutely. It's all about outcomes. It >>Is, it has to be about, it's about moments of service, right? That's why we're here, right? So perhaps a moment of service for Robs Royce is every time you're a passenger, you're going through the terminal. You expect your aircraft to be there, ready, waiting for you to get on and depart on time. And our moment of service is every aircraft takes off on time, every time we live. When we die by the quality of that statement, how well we live up to that statement, I think I checked this morning, there's something alike, 600 aircraft in the sky right now with Rolls Royce power carrying passengers. All of those passengers have relied on that moment. Service happening regularly like clockwork. Every single time you don't get any forgiveness for a delay, you get very little forgiveness for a cancellation that has to happen. And then so many things have to come together for that to happen. >>Those 600 aircraft, that's maybe 200,000 people right now in the sky, Wow. Those 200,000 people are trying to connect, They're trying to connect with friends, they're trying to connect with loved ones, family, colleagues, whatever the purpose is of that trip. It's really important to them. And we just have to make sure that that happens for us. We've had something like a million flights so far this year, 300 million people relying on that moment of so is happening. So I really resonate with, with the language that Scott users about the importance of sort of that focal point on when does it all come together? It comes together when as a passenger, I get on the plane and it goes and I get no issues. >>Right. Well people don't tolerate fragmented experiences anymore. No, no. I think one of the things that was in short supply during the pandemic was patience and tolerance. Sure. Not sure how much of that's gonna come back, right? But those integrated connected experiences, as you described so eloquently, Nick, those are table stakes for the customers, but also the brands behind them because of customers are unhappy, the churn rates go way up. And you see that reflected in obviously the success of the business and what you guys are doing together is seems to be quite powerful. Now then when you were on the cube with us three years ago in Boston at IFS back then you first introduced the intelligent engine and the Blue Data thread. Let's talk about the intelligent engine. Just give our audience a refresher of what that actually entails. >>So perhaps if we just step one one step back for that, just to understand how this fits in. So Roro is a service organization. We talked about that. What that means is we take a lot of the, the risk and the uncertainty away from our airline customers on the availability, the costs and maintenance effort associated with having a, having a chat engine. These are incredibly complicated and complex and sophisticated pieces of equipment. The most expensive, most sophisticated pieces of an aircraft. Managing that is, is difficult. And every airline does not want to have to focus on that. They wanna focus on being able to get the passenger on the air after, fly it, look after the airframe. So our role in that is to take that risk away, is to manage those engines, look after their health, look after their life, make sure they're available to fly whenever they need to fly. >>So for us to understand that, we then have to have data, we have to understand the state of every engine, where it is, the health of the engine, the life of that engine, what do we need to do next to that engine? And we can't do that unless we have data and that data flows into a digital platform. The intelligent engine, which is our cloud based ai, big data, all of the iot, all of the big buzzwords are there, right? So the data flows into that, that lets us run the models. It lets us understand, I can see something maybe it's a, it's a small issue, but if I leave it alone, it become a bigger issue. And maybe that will cause disruption further down the line. So we need to understand that we need to preempt it. So preemptive predictive maintenance is a, is a big part of the intelligent engine, but it's more than just that. >>It's also, we can understand how that engine is being flown. We can understand is it having a really intense flight? Is it having a more benign, gentle flight? Wow. That change time after the flight, typically after the flight. But what that means is we can then understand, actually we can keep that engine on the wing longer then you might otherwise have to do, If you have no data, you have to be conservative, safety rules, everything. Sure. So data allows you to say, actually I'm being overly conservative in this space. I can get more flying bios, flying hours from my product by extending the interval between maintenance and the intelligent engine has a large part to play in us justifying that we're able to do that. And then the final part that it does is eventually the engine is gonna have to come off from maintenance. >>These things fly 5 million miles between overhauls. You imagine you try to do that in your family car. It's, it doesn't happen. It's incredibly sophisticated thing can fly 5 million miles and then we take it off for a major overhaul. But there are thousands of these engines in the fleet. We have to understand which engine is going to come off when for what reason, and prepare our maintenance network to then receive the engine and deal with it and get it back to the customer. So the intelligent engine has a massive part to play in understanding the maintenance demand that the flying fleet is then creating. >>Wow, that's fascinating. And so you talked about that three years ago. What's next for that? I imagine there's only more evolution that's gonna happen. >>It keeps growing. It keeps growing. It's driven by the data. The more data we have, the more that we can do with that. I think as well that, you know, one of the big places that we've we've gone is you can do as much predictive analytics as you, like, there's a lot of people we'll talk about doing predictive analytics, but if you don't do the hard yards of turning predictive analytics into outcome Yeah. Then what did you get? You, you got a bit of smart advice. So we, we take that maintenance demand, we then have to understand how that drives the orchestration and the management of all the parts, the people, the work scope definition, the allocating an engine into a maintenance slot, exactly when it's gonna go. And what are we gonna do to, how do we control and manage our inventory to make sure that engine is gonna go through. >>How do we then actually execute the work inside our, our our overall shops? How do we get that engine back and and integrate our logistics process. So the intelligent engine is, if you like, the shiny front end of a process, it's all the buzzwords, but actually the hard yards behind the scene is just as if not more important to get right. And again, this is why I really like the moment of service concept. Because without that, the moment of service doesn't happen. The engine's not there, the part wasn't there. The field service maintenance guy wasn't there to go fix it. >>And brands are affected >>An, an aircraft on the ground earns no revenue for anybody. No. It's, it's a cost. It's it's a big sink of cost. It >>Is, it is. Absolutely. >>And you're helping aircraft only earn engines only earn when they fly. Yeah, >>Yeah. Absolutely. And what a fascinating, the intelligent engine. Scott, talk a little bit about, we talking about power, we can't not talk about sustainability. Yes, I understand that IFS has a new inaugural awards program that Rolls Roys was a recipient of the Change for Good sustainability awards. Congratulations. Thank you very much. And to Scott, talk to me a little bit about the Change for Good program sustainability program. What types of organizations across the industries of expertise are you looking for and why does Rules ROY really highlight what a winner embodies? >>So since Darren has joined IFS as the ceo, he's had a lot of intentional areas that we focused on. And sustainability has been one that's at the top of the list. IFS has a US ambassador Lewis Pew, who's our Chief Sustainability officer, and he helps us to provide worldwide coverage of the efforts around sustainability. So it's not just about ifss ability to become a more sustainable organization, but it's the solutions that IFS is putting together in the five verticals that we focus on that can help those organizations achieve a level of sustainability for their, for their downstream customers, their partners, and for their enterprises themselves. So when we look at, you know, the social ability for us to be more conscientious about leaving the world a better place or trying to do our best to leave the world not as bad as we came into it, sustainability is a real focus for us. And, you know, the way in which we can support an organization like Rolls Royce and Nickel obviously share those areas of focus from Rolls Royce. It's a perfect fit. And congratulations again for the award. Thank you. We're, we're, we're so excited to, to have shared that with you. We have some other customers that have achieved it across different categories, but it's an area of current and continuous focus for ifs. >>Nick, talk to us, take us out here as our last question is the, the focus on sustainability at Rolls Royce. Talk to us a little bit about that and what some of the major efforts are that you've got underway. >>I think, you know, very similar as, as, as Scott taught there, the focus within Rolls Royce as a strategic group level is really high aviation particularly, I mean we're a, we're an engineering company. We're a power company. Power inherently consumes natural resources. It tends to generate climate affecting outcomes. But at the same time, we are an innovative organization and if anybody's gonna help solve climate challenges, it's gonna be organizations like Rolls Royce who are able to bring different technologies into the market. So we have a responsibility to manage and, and optimize the behavior of our, our existing product suite. But we also have a, a vested interest in trying to move aviation on into the next, the next phase. We talk about sustainable aviation. Aviation has to earn the right to exist. People have choices. We've come out of covid, people are used to doing zoom and not flying. >>People are used to doing things when they don't necessarily get on an aircraft and do something. The aviation business always has to earn the right from the public to exist. And increasingly people will make choices about how they fly when they fly, how far they fly based on the sustainability footprint. So it's really important to us to help both our customers operate the aircraft in as sustainable and climate friendly way as we can. It's really important to find those, those balance points between the cost of an operation and it's the impact of an operation. If you go all over and say, I am going to be net, well, not even net to, but zero carbon by almost inference, that means I'm not gonna operate. You have to operate to get to an outcome. But how do I do that? Why I manage my cost, I manage the, the profitability, the organization doing it, right? >>So it has to be financially sustainable, it has to be sustainable for the people operating within it. It has to be sustainable for the planet, right? So we do that in lots of different ways in small places and, and in big places. So small things we do is we help the operator understand if you change your flight profile, you'll generate fewer emissions. You may avoid controls if you flying a different way, maybe you create trails, you'll lose, you'll lose less fuel while you're doing that. So it's cost effective for you. There was always a balance point there between the wear and tear on the engine versus the, the, the environmental impact. And you find that optimum place. One of the first things we started doing with, with Scott is we have a, a way that we life our engine components. And one of the very simple outcomes of that is using that data, the blue data for connection to the customer. >>If we can see, effectively see inside the engine about how well it's wearing and we can extend those maintenance intervals as we talked about, what that eventually does is it reduces the need to take the engine off, ship it around the world. Probably on a great big 7, 4 7 or maybe year or two ago on an Anson off four big engines flying a long distance trek, shipping our engine to an overhaul facility. We're avoiding something like 200 of those shop visit overhauls a year. So every year that's 200 flights there and back again, which don't happen, right? Collectively that's around about 15,000 automobile equivalent emissions just don't happen. So simple things we can do just starts to have accumulative effect, >>Right? Simple things that you're doing that, that have a huge impact. We could talk for so much longer on stability, I'm sure we're out of time, but I can see why Roll Royce was, was the winner of the Inocular award. Congratulations. Well deserved. Well >>Deserved. I well >>Deserved. So interesting to hear about the intelligent engine. So you're gonna have to come back. Hopefully we'll be here next year and we can hear more of the evolution. Cuz I have a feeling there's never a dual moment in what you're doing. >>It's never a dull moment. There's never an end point. >>No. >>Okay, >>Going Scott, Nick, thank you so much for joining me on the program today. Thank you, Lisa. It's great to have you talk through what's going on at ifx and the partnership with Rolls Royce. We >>Appreciate, and again, Nick, Nick, thank you for your continued support in the partnership. >>I thank you, Scott. We appreciate it. Likewise, thank >>You. Kudos all around. All right, for my guests, I'm Lisa Martin, you're watching a Cube live from Miami. We're at IFS unleashed. We'll be back shortly after a break with our next guests. So stick around.

>>data by its very nature is distributed and siloed. But most data architectures today are highly centralized. Organizations are increasingly challenged to organize and manage data and turn that data into insights this idea of a single monolithic platform for data, it's giving way to new thinking. We're a decentralized approach with open cloud native principles and Federated governance will become an underpinning underpinning of digital transformations. Hi everybody, this is Day Volonte. Welcome back to HP discover 2021 the virtual version. You're watching the cubes continuous coverage of the event and we're here with Matt Mako is the field C T O for Israel software at H P E. And we're gonna talk about HP software strategy and esmeralda and specifically how to take a I analytics to scale and ensure the productivity of data teams. Matt, welcome to the cube. Good to see you. >>Good to see you again. Dave thanks for having me today. >>You're welcome. So talk a little bit about your role as CTO. Where do you spend your time? >>Yeah. So I spend about half of my time talking to customers and partners about where they are on their digital transformation journeys and where they struggle with this sort of last phase where we start talking about bringing those cloud principles and practices into the data world. How do I take those data warehouses, those data lakes, those distributed data systems into the enterprise and deploy them in a cloud like manner. And then the other half of my time is working with our product teams to feed that information back so that we can continually innovate to the next generation of our software platform. >>So when I remember I've been following HP and HP for a long, long time, the cube is documented. We go back to sort of when the company was breaking in two parts and at the time a lot of people were saying, oh HP is getting rid of the software business to get out of software. I said no, no, no hold on, they're really focusing and and the whole focus around hybrid cloud and and now as a service and so you're really retooling that business and sharpen your focus. So so tell us more about asthma, it's cool name. But what exactly is as moral software, >>I get this question all the time. So what is Israel? Israel is a software platform for modern data and analytics workloads using open source software components. And we came from some inorganic growth. We acquired a company called citing that brought us a zero trust approach to doing security with containers. We bought blue data who came to us with an orchestrator before kubernetes even existed in mainstream. They were orchestrating workloads using containers for some of these more difficult workloads, clustered applications, distributed applications like Hadoop. And then finally we acquired Map are which gave us this scale out, distributed file system and additional analytical capabilities. And so what we've done is we've taken those components and we've also gone out into the marketplace to see what open source projects exist, to allow us to bring those club principles and practices to these types of workloads so that we can take things like Hadoop and spark and Presto and deploy and orchestrate them using open source kubernetes, leveraging Gpu s while providing that zero trust approaches security. That's what Israel is all about. Is taking those cloud practices and principles but without locking you in again using those open source components where they exist and then committing and contributing back to the open source community where those projects don't exist. >>You know, it's interesting. Thank you for that history. And when I go back, I always been there since the early days of big data and Hadoop and so forth. The map are always had the best product. But but they can't get back then. It was like Kumbaya open source and they had this kind of proprietary system, but it worked and that's why it was the best product. And so at the same time they participated in open source projects because everybody that that's where the innovation is going. So you're making that really hard to use stuff easier to use with kubernetes orchestration. And then obviously I'm presuming with the open source chops, sort of leaning into the big trends that you're seeing in the marketplace. So my question is, what are those big trends that you're seeing when you speak to technology executives, which is a big part of what you do? >>Yeah. So the trends I think are a couple of fold and it's funny about Duke, I think the final nails in the coffin have been hammered in with the Hadoop space now. And so that that leading trend of of where organizations are going. We're seeing organizations wanting to go cloud first, but they really struggle with these data intensive workloads. Do I have to store my data in every cloud? Am I going to pay egress in every cloud? Well, what if my data scientists are most comfortable in AWS? But my data analysts are more comfortable in Azure. How do I provide that multi cloud experience for these data workloads? That's the number one question I get asked. And that's the probably the biggest struggle for these Chief Data Officers. Chief Digital Officer XYZ. How do I allow that innovation but maintaining control over my data compliance especially, we talk international standards like G. D. P. R. To restrict access to data, the ability to be forgotten in these multinational organizations. How do I sort of square all of those components and then how do I do that in a way that just doesn't lock me into another appliance or software vendors stack? I want to be able to work within the confines of the ecosystem. Use the tools that are out there but allow my organization to innovate in a very structured, compliant way. >>I mean I love this conversation. And just to me you hit on the key word which is organization. I want to I want to talk about what some of the barriers are. And again, you heard my wrap up front. I I really do think that we've created not only from a technology standpoint and yes, the tooling is important, but so is the organization. And as you said, you know, an analyst might want to work in one environment, a data scientist might want to work in another environment. The data may be very distributed. They maybe you might have situations where they're supporting the line of business. The line of business is trying to build new products. And if I have to go through this, hi this monolithic centralized organization, that's a barrier uh for me. And so we're seeing that change that kind of alluded to it upfront. But what do you see as the big, you know, barriers that are blocking this vision from becoming a reality? >>It very much is organization dave it's the technology is actually no longer the inhibitor here. We have enough technology, enough choices out there. That technology is no longer the issue. It's the organization's willingness to embrace some of those technologies and put just the right level of control around accessing that data because if you don't allow your data scientists and data analysts to innovate, they're going to do one of two things, they're either going to leave and then you have a huge problem keeping up with your competitors or they're gonna do it anyway, and they're gonna do it in a way that probably doesn't comply with the organizational standards. So the more progressive enterprises that I speak with have realized that they need to allow these various analytical users to choose the tools, they want to self provision those as they need to and get access to data in a secure and compliant way. And that means we need to bring the cloud to generally where the data is because it's a heck of a lot easier than trying to bring the data where the cloud is while conforming to those data principles. And that's, that's Hve strategy, you've heard it from our CEO for years now, everything needs to be delivered as a service. It's essential software that enables that capability, such as self service and secure data provisioning, etcetera. >>Again, I love this conversation because if you go back to the early days of the Duke, that was what was profound about. Do bring bring five megabytes of code, do a petabyte of data and it didn't happen. We shoved it all into a data lake and it became a data swamp. And so it's okay, you know, and that's okay. It's a one dato maybe maybe in data is is like data warehouses, data hubs data lake. So maybe this is now a four dot Oh, but we're getting there. Uh, so an open but open source one thing's for sure. It continues to gain momentum. It's where the innovation is. I wonder if you could comment on your thoughts on the role that open source software plays for large enterprises. Maybe some of the hurdles that are there, whether they're legal or licensing or or or just fears. How important is open source software today? >>I think the cloud native development, you know, following the 12 factor applications microservices based, pave the way over the last decade to make using open source technology tools and libraries mainstream, we have to tip our hats to red hat right for allowing organizations to embrace something. So core is an operating system within the enterprise. But what everyone realizes that its support, that's what has to come with that. So we can allow our data scientists to use open source libraries, packages and notebooks. But are we going to allow those to run in production? And so if the answer is no, then that if we can't get support, we're not going to allow that. So where HP es Merrill is taking the lead here is again embracing those open source capabilities, but if we deploy it, we're going to support it or we're going to work with the organization that has the committees to support it. You call HPD the same phone number you've been calling for years for tier 1 24 by seven support and we will support your kubernetes, your spark your presto your Hadoop ecosystem of components were that throat to choke and we'll provide all the way up to break fix support for some of these components and packages giving these large enterprises the confidence to move forward with open source but knowing that they have a trusted partner in which to do so >>and that's why we've seen such success with, say, for instance, managed services in the cloud or versus throwing out all the animals in the zoo and say, okay, figure it out yourself. But of course what we saw, which was kind of ironic was we, we saw people finally said, hey, we can do this in the cloud more easily. So that's where you're seeing a lot of data. A land. However, the definition of cloud or the notion of cloud is changing no longer. Is it just this remote set of services somewhere out there? In the cloud? Some data center somewhere. No, it's, it's moving on. Prem on prem is creating hybrid connections you're seeing, you know, co location facility is very proximate to the cloud. We're talking now about the edge, the near edge and the far edge deeply embedded, you know? And so that whole notion of cloud is, is changing. But I want to ask you, there's still a big push to cloud, everybody is a cloud first mantra. How do you see HP competing in this new landscape? >>I I think collaborating is probably a better word, although you could certainly argue if we're just leasing or renting hardware than it would be competition. But I think again, the workload is going to flow to where the data exists. So if the data is being generated at the edge and being pumped into the cloud, then cloud is prod, that's the production system. If the data is generated, the on system on premises systems, then that's where it's going to be executed, that's production. And so HBs approach is very much coexist, coexist model of if you need to do deaf tests in the cloud and bring it back on premises, fine or vice versa. The key here is not locking our customers and our prospective clients into any sort of proprietary stack, as we were talking about earlier, giving people the flexibility to move those workloads to where the data exists. That is going to allow us to continue to get share of wallet. Mindshare, continue to deploy those workloads and yes, there's going to be competition that comes along. Do you run this on a G C P or do you run it on a green lake on premises? Sure. We'll have those conversations. But again, if we're using open source software as the foundation for that, then actually where you run it is less relevant. >>So a lot of, there's a lot of choices out there when it comes to containers generally and kubernetes specifically, uh, you may have answered this, you get zero trust component, you've got the orchestrator, you've got the, the scale out, you know, peace. But I'm interested in hearing in your words why an enterprise would or should consider s morale instead of alternatives to kubernetes solutions? >>It's a fair question. And it comes up in almost every conversation. We already do kubernetes, so we have a kubernetes standard and that's largely true. And most of the enterprises I speak to their using one of the many on premises distributions of the cloud distributions and they're all fine. They're all fine for what they were built for. Israel was generally built for something a little different. Yes, everybody can run microservices based applications, devoPS based workloads, but where is Meryl is different is for those data intensive and clustered applications. Those sort of applications require a certain degree of network awareness, persistent storage etcetera, which requires either a significant amount of intelligence. Either you have to write in go lang or you have to write your own operators or Israel can be that easy button. We deploy those state full applications because we bring a persistent storage later that came from that bar we're really good at deploying those stable clustered applications and in fact we've open sourced that as a project cube director that came from Blue data and we're really good at securing these using spiffy inspire to ensure that there is that zero trust approach that came from side tail and we've wrapped all of that in kubernetes so now you can take the most difficult, gnarly, complex data intensive applications in your enterprise and deploy them using open source and if that means we have to coexist with an existing kubernetes distribution, that's fine. That's actually the most common scenario that I walk into is I start asking about what about these other applications you haven't done yet? The answer is usually we haven't gotten to him yet or we're thinking about it and that's when we talk about the capabilities of s role and I usually get the response, oh, a we didn't know you existed and be, well, let's talk about how exactly you do that. So again, it's more of a coexist model rather than a compete with model. Dave >>Well, that makes sense. I mean, I think again, a lot of people think, oh yeah, Kubernetes, no big deal, it's everywhere. But you're talking about a solution, I'm kind of taking a platform approach with capabilities, you've got to protect the data. A lot of times these microservices aren't some micro uh and things are happening really fast, You've got to be secure, you've got to be protected. And like you said, you've got a single phone number, you know, people say one throat to choke, Somebody said the other day said no, no single hand to shake, it's more of a partnership and I think that's a proposed for HPV met with your >>hair better. >>So you know, thinking about this whole, you know, we've gone through the pre big data days and the big data was all, you know, the hot buzz where people don't maybe necessarily use that term anymore, although the data is bigger and getting bigger, which is kind of ironic. Um where do you see this whole space going? We've talked about that sort of trends are breaking down the silos, decentralization. Maybe these hyper specialized roles that we've created maybe getting more embedded are lined with the line of business. How do you see it feels like the last, the next 10 years are going to be different than the last 10 years. How do you see it matt? >>I completely agree. I think we are entering this next era and I don't know if it's well defined, I don't know if I would go out on an edge to say exactly what the trend is going to be. But as you said earlier, data lakes really turned into data swamps. We ended up with lots of them in the enterprise and enterprises had to allow that to happen. They had to let each business unit or each group of users collect the data that they needed and I. T. Sort of had to deal with that down the road. And so I think the more progressive organizations are leading the way they are again taking those lessons from cloud and application developments, microservices and they're allowing a freedom of choice there, allowing data to move to where those applications are. And I think this decentralized approach is really going to be king. And you're gonna see traditional software packages, you're gonna see open source, you're going to see a mix of those. But what I think we'll probably be common throughout all of that is there's going to be this sense of automation, this sense that we can't just build an algorithm once released and then wish it luck that we've got to treat these these analytics and these these data systems as living things that there's life cycles that we have to support, which means we need to have devops for our data science. We need a ci cd for our data analytics. We need to provide engineering at scale like we do for software engineering. That's going to require automation and an organizational thinking process to allow that to actually occur. And so I think all of those things that sort of people process product, but it's all three of those things are going to have to come into play. But stealing those best ideas from cloud and application development, I think we're going to end up with probably something new over the next decade or so >>again, I'm loving this conversation so I'm gonna stick with it for a second. I it's hard to predict, but I'll some takeaways that I have matt from our conversation. I wonder if you could, you could comment. I think, you know, the future is more open source. You mentioned automation deV's are going to be key. I think governance as code, security designed in at the point of code creation is going to be critical. It's not no longer to be a bolt on and I don't think we're gonna throw away the data warehouse or the data hubs or the data lakes. I think they become a node. I like this idea and you know, jim octagon. But she has this idea of a global data mesh where these tools lakes, whatever their their node on the mesh, they're discoverable. They're shareable. They're they're governed uh in a way and that really I think the mistake a lot of people made early on in the big data movement, Oh we have data, we have to monetize our data as opposed to thinking about what products that I can I build that are based on data that then I can, you know, can lead to monetization. And I think and I think the other thing I would say is the business has gotten way too technical. All right. It's an alienated a lot of the business lines and I think we're seeing that change. Um and I think, you know, things like Edinburgh that simplify that are critical. So I'll give you the final thoughts based on my rent. >>I know you're ready to spot on. Dave. I think we we were in agreement about a lot of things. Governance is absolutely key. If you don't know where your data is, what it's used for and can apply policies to it, it doesn't matter what technology throw at it, you're going to end up in the same state that you're essentially in today with lots of swamps. Uh I did like that concept of of a note or a data mesh. It kind of goes back to the similar thing with a service smashed or a set of a P I is that you can use. I think we're going to have something similar with data that the trick is always how heavy is it? How easy is it to move about? And so I think there's always gonna be that latency issue. Maybe not within the data center, but across the land, latency is still going to be key, which means we need to have really good processes to be able to move data around. As you said, government determine who has access to what, when and under what conditions and then allow it to be free, allow people to bring their choice of tools, provision them how they need to while providing that audit compliance and control. And then again, as as you need to provision data across those notes for those use cases do so in a well measured and govern way. I think that's sort of where things are going. But we keep using that term governance. I think that's so key. And there's nothing better than using open source software because that provides traceability, the audit ability and this frankly openness that allows you to say, I don't like where this project is going. I want to go in a different direction and it gives those enterprises that control over these platforms that they've never had before. >>Matt. Thanks so much for the discussion. I really enjoyed it. Awesome perspectives. >>Well, thank you for having me. Dave are excellent conversation as always. Uh, thanks for having me again. >>All right. You're very welcome. And thank you for watching everybody. This is the cubes continuous coverage of HP discover 2021 of course, the virtual version next year. We're gonna be back live. My name is Dave a lot. Keep it right there. >>Yeah.

>>from around the globe. It's the Cube covering HP. Discover Virtual Experience Brought to you by HP >>Everyone welcome to the Cube studios here in Palo Alto, California We here for remote conversation. Where for HP Discover virtual experience. 2020. We would Kumar, Sri Context, chief technology officer and head of Software Cube alumni. We've been following Kumar since he started Blue Data. Now he's heading up the software team and CTO at HP and Robert Christensen, VP of Strategy of Office of the CTO Robert Both Cube alumni's Robert, formerly with CTP, now part of the team that's bringing the modernization efforts around enterprises in this fast changing world that's impacting the operating models for businesses. We're seeing that playing out in real time with Covert 19 as customers are modernizing the efforts. Guys, thanks for coming on. Taking the time. >>You're welcome, John. Good to be back here, >>Kumar. First I have to ask you, I have to ask you your new role at HP sent it up to CTO but also head of the software. How >>do you >>describe that role Because you're CTO and also heading up? This offers a general manager. Could you take him in to explain this new role and why It's important. >>Thank you. Thank you, John. And so good to be back. You get two for one with me and Robert didn't. Yeah, it's very exciting to be here as the CTO of HB. And as Antonio described in in his announcement, we consider software will be very key, essential part of the our people as a service. And, uh, we want we see that it's an opportunity for not only layer division but help drive the execution of that reason. Both organic them in our. So we we see we want to have a different change of software that helps the customers, too, to get us to the workloads optimized, or are there specific solutions? >>You guys were both on the Cube in November, Pre cove it with the minimum John Troyer talking about the container platform news, leveraging the acquisitions you guys have done at HP Kumar, your company Blue Data map, our CTP, Robert, the group. You're there really talking about the strategies around running these kinds of workloads. And if you think about Cove in 19 this transformation, it's really changing work. Workforces, workplaces, workloads, work flows everything to do with work and people are at home. That's an extension of the on premise environment. VPN provisions were under provisional hearing all these stories, exposing all the things that need to be worked on because no one ever saw this kind of direction. It highlights the modern efforts that a lot of your customers are going through rubber. Can you explain? And Kumar talk about this digital transformation in this cove it and then when we come out of it, the growth strategies that need to be put in place and the projects take a minute to explain. >>Go ahead. Robert Cover has been spending a lot of time with our customers, and I would like to go ahead. >>Yeah, thank you so much. It's Ah, uh, accelerators. What's happened? Many of our clients have been forced into the conversation about how do I engage our customers, and how do we engage our broad constituents, including our employees and colleagues, in a more rapid and easier way? And many of the systems that were targeted to make their way to a public cloud digital transformation process did not get the attention just because of their size and breadth and depth effort. So that's really put an accelerator down on what are we gonna do? So we have to be able to bring a platform into our clients organizations that have the same behavior characteristics or what we call you know, the same cloud experiences that people are expecting public. Bring it close to our client's data and their applications without having that you don't have a platform by which you can have an accelerated digital transformation because it's historically a public cloud. But the only path to get that done, what we're really considering, what we introduced a while ago was platform near our clients applications. That data that gives them that ability to move quicker and respond to these industries, situations and specifically, what's happened with company really pushes it harder for real solutions Now that they can act on >>Kumar, your thoughts on this pre coded >>Yeah, yeah, this is the piece of acceleration for the digital transformation is just is a longer dynamically multiplied the code. But I think as you pointed out, John the remote working and the VPN is the security. We were as an edge to the Cloud platform company we were already in that space, so it's actually very, very. As Robert pointed out, it's actually nice to see that transformation is his transition or rapidly getting into the digitization. But one thing that is very interesting to note here is you can you can lift and shift of data has gravity. And you actually saw we actually see the war. All the distributor cloud. We see that we're glad to see what we've seen we've been talking about prior to the Kool Aid. And recently even the industry analysts are talking about we believe there is a computer can happen where the data is on. But this is actually an interesting point for me to say. This is why we have actually announced our new software platform, which we as well, which is our our key differentiator pillar for our as a service people that companies are facing. >>Could you talk about what this platform is? You guys are announcing the capabilities and what customers can expect from this. Is that a repackaging? Is there something new here? What's is it something different, Making something better? What? Can you just give us a quick taste of what this is and what it means. >>Good love alive. >>Yeah, so yeah, that's a great question. Is it repackage There's actually something. Well, I'm happy to say. It's a combination of a lot of existing assets that come together in the ecosystem, I think a platform that is super unique. You know, you look at what the Blue data container Onda adoption of communities holistically is a control plane as well as our data fabric of motion to the market with Matt Bahr and you combine that with our network experiences and our other platform very specific platform solutions and your clients data that all comes together in intellectual property that we have that we packed together and make it work together. So there's a lot of new stuff in there, But more importantly, we have a number of other close partners that we've brought together to form out our as moral platform. We have a new, really interesting combination of security and authentication. Piece is through our site L organization that came underneath with us a few months back and are aggressive motion towards bringing in strong networking service that complexity as well. So these all come together and I'm sure leaving a few out there are specifically with info site software to continue to build out a Dr solution on premises that provides that world class of services that John >>Sorry, Johnny, was the question at the beginning is, what is that? Why the software role is This is exactly what I was waiting for that that that moment where Robert pointed out, our goal is we have a lots of good assets. In addition to a lot of good partnerships, we believe the market is the customers want outcome based solutions. Best motion not. I want peace meal. So we have an opportunity to provide the customers the solution from the top to the bottom we were announced, or the Discover ML ops as a service which is actually total top to the bottom and grow, and customers can build ml solutions on the top of the Green lake. This is built on HP is moral, so it's not. I wouldn't use the word repackaging, but it is actually a lot of the inorganic organic technologies that have come together that building the solution. >>You know, I don't think it's ah, negative package something up in >>Toto. So I wouldn't >>I didn't think >>negative, but I was just saying that it is. It's Ah, it's a lot of new stuff, but also, as Robert said included, or you built a very powerful container platform. As you said, you just mentioned it that you've gone. We announced the well. >>One of the things I liked about your talk on November was that the company is kind of getting in the weeds, but stateless versus State. Full data's a big part >>of >>it, but you don't get the cloud and public cloud and horizontal scalability. No one wants Peace meal, that word you guys just mentioned or these siloed tools and about the workforce workplace transformation with Cove it it's exposing the edge, everybody. It's not just a nightie conversation. You need to have software that traverses the environment. So you now looking at not so much point solutions best to breed but you guys have had in the past, but saying Okay, I got to look at this holistically and say, How do I make sure I make sure security, which is the new perimeter, is the home right or wherever is no perimeter anymore is everywhere, So >>this is now >>just a architectural concept. Not so much a point solution, right? I mean, is that kind of how you're thinking about it? >>That's correct. In fact, as you said, the data is generated at the edge and you take the compute and it's been edge to the cloud platform. What we have, actually what we are actually demonstrating is we want to give a complete solution no matter where the processing needs are. And with HP, you have no that cloud like experience both as UNP prime as well as what we call a hybrid. I think let's be honest, the world is going to be hybrid and you can actually see the changes that is happening even from the public cloud vendors. They're trying to come on pram. So HP is being established player in this, and with this technology I think provides that solution, you can process where the data is. >>Yeah, I would agree it's hybrid. I would say Multi cloud is also, you know, code word for multi environment, right? And Robert, I want todo as you mentioned in your talk with stew minimum in November, consistency across environments. So when you talk to customers. Robert. What are they saying? Because I can imagine them in zoom meetings right now or teleconferencing saying, Look it, we have to have an operating model that spans public on premise. Multiple environments, whether it's edge or clouds. I don't wanna have different environments and being managed separately and different data modeling. I won't have a control plane, and this is architectural. I mean, it's kind of complex, but customers are dealing with this right now. What are you hearing from customers? How are they handling and they doubling down on certain projects? Are they reshaping some of their investments? I mean, what's the mindset of the customer >>right now? The mindset is that the customers, under extreme pressure to control costs and improve automation and governance across all their platforms, the business, the businesses that we deal with have established themselves in a public cloud, at least to some extent, with what they call their systems of engagement. Those are all the lot of the elastic systems, the hype ones that the hyper scale very well, and then they have all of their existing on premises, stuff that you typically heavily focused on. A VM based mindset which is being more more viewed as legacy, actually, and so they're looking for that next decade of operating. While that spans both the public and the private cloud on Premises World and what's risen up, that operating model is the open source kubernetes orchestration based operating model, where they gives them the potential of walking into another operating model that's holistic across both public and private but more importantly, as a way for their existing platforms to move into this new operating model. That's what you're talking about, using state full applications that are more legacy minded, monolithic but still can run in the container based platform and move to a new ballistic operating model. Nobody's under the impression, by the way, that the existing operating model we have today on premises is compatible with the cloud operating model. Those two are not compatible in any shape. Before we have to get to an operating model that holistic in nature. We see that, >>and that's a great tee up for the software question Robert, I want to go to. Come on, I want to get thoughts because I know you personally and I've been following your career. Certainly you know. Well, well, well, deep in computer science and software. So I think it's a good role for you. But if you look at what the future is, this is the conversation we're having with CIOs and customers on the Cube is when I get back to work postcode. But I've gotta have a growth strategy. I need to reset, reinvent and have growth strategy. And all the conversations come back to the APS that they have to redevelop or modernize, right? So workloads or whatever. So what that means is they really want true agility, not just as a punch line or cliche. They gotta move security into the Dev Ops pipeline ing. They got to make the application environment. Dev Ops and Dev Ops was kind of a fringe industry thing for about a decade. And now that's implement. That's influencing I T ops, security ops and network ops. These are operational systems, not just, you know, Hey, let's sling some kubernetes and service meshes around. This is like really nuts and bolts business operations. So, you know, I t Ops has impacted SEC ops isn't impacted. They're working us not for the faint of Heart Dev Ops I get that now it's coming everywhere. What's your thoughts on that? What's your reaction? >>We see those things coming together, John. So again, going back to the Israel were the world we believe this innovative software is. It can run on any infrastructure to start with, whether it's HP hardware knowledge we are with. It's called Hybrid. And as we said we talked about, it is it is, um it's whether it is an edge already where the processing is. We also committed to providing integrated, optimized, secure, elastic and automate our solutions. Right. This is, I think, your question of are it's not just appealing to the one segment of the organization. I think there's going to be a I cannot just say I'm only giving you the devil ops solution, but it has to have a security built into. This is why we are actually committed to making our solutions more elastic, more scalable. We're investing in building a complete runtime stack and making sure it has the all the fleet compose. It's not only optimized for the work solution which we call the work runtime stack, it's also has this is our Green Lake solution that that brings these two pieces together. Robert? Yeah. Sorry. Go ahead. >>Robert, you mentioned automation earlier. This is where the automation dream comes in. The Mission ml ops service. What you're really getting at is program ability for the developer across the board, right? Is that kind of what you're thinking? Or? >>Well, there's two parts of that. This is really important. The developer community is looking for a set of tools that they could be very creative and movement right. They don't want to have to be worried about provisioning managing, maintaining any kind of infrastructure. And so there's this bridge between that automation and the actual getting things done. So that's number one. But more importantly, I think this is hugely important, as you look about pushing into the on premises world for for H, P E or anybody else to succeed in that space, you have to have a high degree of automation that takes care of potential problems that humans would otherwise have to get involved with. And that's when they cost. So you have to drive in a commercial. I'm gonna fleet controls of Fleet management services that automate their behavior and give them an S L A that are custom to public cloud. So you've got two sets of automation that you really have to be dealing with. Not only are you talking about Dev ops, the second stage you just talked about, but you gotta have a corresponding automation bake back into drive. A higher user experience at both levels >>and Esmeraldas platforms is cool. I get that. I hear that. So the question next question on that Kumar is platforms have to enable value. What are you guys enabling for the value when you talk to customers? Because who everyone sees the platform play as the as the architecture, but it has to create disruptive, enabling value. What do you >>Yeah, that I'll go on as a starter, I think way pointed out to you. This is the when we announced the container platform, it's off, the very unique. It's not only it's open source Cuban it is. It has a persistent one of the best underlying persistent stories integrated the original map or a file system, as I pointed out, drones one of the world's largest databases, and we can actually allow the customers to run both both state full and stateless workloads. And as I said a few minutes ago, we are committed to having the run times off they run and both which we are. We're not a hardware, so the customers have the choice on. In addition to all of that, I think we're in a very unique solutions. We're offering is ML ops as we talked about and this is only beginning, and we have lots of other examples of Robert is working on a solution. Hopefully, we'll announce sometime soon, which is similar to that. Some of the key elements that we're seeing in the marketplace, the various solutions that goes from the top of the bar >>Robert to you on the same question. What's in it for me in the customer? Bottom line. What's the what's in it for me? >>Well, so I think, just the ease of simplicity. What we are ultimately want to provide for a client is one opportunity to solve a bunch of problems that otherwise have to stitch together myself. It's really about value and speed to value. If I have to solve the same computer vision problem in manufacturing facility and I need a solution and I don't have the resource of the wherewithal stacks like that, but I got to bring a bigger solution. I want a company that knows how to deliver a computer vision solution there or within an airport or wherever, where I don't need to build out sophisticated infrastructure or people are technologies necessary, is point on my own or have some third party product that doesn't have a vested interest in the whole stack. H P E is purposely have focused on delivering that experience with one organization from both hardware and software up to the stack, including the applications that we believe with the highest value to the client We want to be. That organization will be an organization on premises. >>I think that's great, consistent with what we're hearing if you can help take the heavy lifting away and have them focus on their business and the creativity. And I think the application renaissance and transformation is going to be a big focus both on the infrastructure side but also just straight up application developers. That's gonna be really critical path for a lot of these companies to come out of this. So congratulations on that love that love the formula final conclusion question for both you guys. This is something that a lot of people might be asking at HP. Discover virtual experience, or in general, as they have to plan and get back to work and reset, reinvent and grow their organizations. Where is HP heading? How do you see HP heading? How would you answer that question? If the customers like Kumar Robert, where's HP heading? How would you answer that? >>Go ahead, Robert. And then I can >>Yeah, yeah. Uh huh, Uh huh. I see us heading into the true distributed hybrid platform play where that they would look to HP of handling and providing all of their resource is and solutions needs as they relate to technology further and further into what their specific edge locations would look like. So edge is different for everybody. And what HP is providing is a holistic view of compute and our storage and our solutions all the way up through whether they be very close to the edge. Locations are all the way through the data center and including the integration with our public cloud partners out there. So I see HP is actually solving real value business problems in a way that's turnkey and define it for our clients. Really value >>John. I think I'll start with the word Antonio shared. We are edge to the cloud, everything as a service company and I think the we're actually sending is HPE is Valley Legend, and it's actually honored to be part of the such a great company. I think what we have to change with the market transformation the customer needs and what we're doing is we're probably in the customers that innovative solution that you don't have to. You don't have to take your data where the computers, as opposed to you, can take the compute where the data is and we provide you the simplified, automated, secure solutions no matter where you very rare execution needs are. And that is through the significant innovation of the software, both for as Model and the Green Lake. >>That's awesome. And, you know, for all of us, have been through multiple ways of innovation. We've seen this movie before. It's essentially distributive computing, re imagine and re architected with capability is the new scale. I mean, it's almost back to the old days of network operating systems and networking and Os is and it's a you know, >>I that's a very, very good point. And I will come through the following way, right? I mean, it is, It's Ah, two plus two is four no matter what university, Gordo. But you have to change with the market forces. I think the market is what is happening in the marketplace. As you pointed out, there was a shadow I t There's a devil Ops and his idea off the network ops and six years. So now I think we see that all coming together I call this kubernetes is the best equalizer of the past platform. The reason why it became popular is because it's provided that abstraction layer on. I think what we're trying to do is okay, if that is where the customers want and we provide a solution that helps you to build that very quickly without having to lock into any specific platform. >>I think you've got a good strategy there. I would agree with you. I would call that I call it the old TCP I p. What that did networking back in the day. Kubernetes is a unifying, disruptive enabler, and I think it enables things like a runtime stack. Things that you're mentioning. These are the new realities. I think Covad 19 has exposed this new architectures of the world. >>Yeah, one last year, we were saying >>once, if not having something in place >>started. So the last thing I would say is it we're not bolting coolness to anything. Old technologies. It's a fresh it's built in. It's an open source. And it is as a salaries, it can run on any platform that you choose to run. Now. >>Well, next time we get together, we'll refund, observe ability and security and all that good stuff, because that's what's coming next. All the basic in guys. Thank you so much, Kumar. Robert. Thanks for spending the time. Really appreciate it here for the HP Discover Virtual Spirits Cube conversation. Thanks for Thanks for joining me today. >>Thank you very much. >>I'm John Furrier with Silicon Angle. The Cube. We're here in our remote studios getting all the top conversations for HP Discover virtual experience. Thanks for watching. Yeah, >>yeah, yeah.

>> Male Voice: From around the globe, it's theCUBE covering HPE Discover Virtual Experience brought to you by HPE. >> Hi everybody, you're watching theCUBE. And this is Dave Vellante in our continuous coverage of the Discover 2020 Virtual Experience, HPE's virtual event, theCUBE is here, theCUBE virtual. We're really excited, we got a great session here. We're going to dig deep into machine intelligence and artificial intelligence. Dr. Arti Garg is here. She's the Head of Advanced AI Solutions and Technologies at Hewlett Packard Enterprise. And she's joined by Dr. Sorin Cheran, who is the Vice President of AI Strategy and Solutions Group at HPE. Folks, great to see you. Welcome to theCUBE. >> Hi. >> Hi, nice to meet you, hello! >> Dr. Cheran, let's start with you. Maybe talk a little bit about your role. You've had a variety of roles and maybe what's your current situation at HPE? >> Hello! Hi, so currently at HPE, I'm driving the Artificial Intelligence Strategy and Solution group who is currently looking at how do we bring solutions across the HPE portfolio, looking at every business unit, but also on the various geos. At the same time, the team is responsible for building the strategy around the AI for the entire company. We're working closely with the field, we're working closely with the things that are facing the customers every day. And we're also working very closely with the various groups in order to make sure that whatever we build holds water for the entire company. >> Dr. Garg, maybe you could share with us your focus these days? >> Yeah, sure, so I'm also part of the AI Strategy and Solutions team under Sorin as our new vice president in that role, and what I'm focused on is really trying to understand, what are some of the emerging technologies, whether those be things like new processor architectures, or advanced software technologies that could really enhance what we can offer to our customers in terms of AI and exploring what makes sense and how do we bring them to our customers? What are the right ways to package them into solutions? >> So everybody's talking about how digital transformation has been accelerated. If you're not digital, you can't transact business. AI infused into every application. And now people are realizing, "Hey, we can't solve all the world's problems with labor." What are you seeing just in terms of AI being accelerated throughout the portfolio and your customers? >> So that's a very good idea, because we've been talking about digital transformation for some time now. And I believe most of our customers believed initially that the one thing they have is time thinking that, "Oh yes I'm going to somehow at one point apply AI "and somehow at one point "I'm going to figure out how to build the data strategy, "or how to use AI in my different line of businesses." What happened with COVID-19 and in this area is that we lost one thing: time. So I think discussed what they see in our customers is the idea of accelerating their data strategy accelerating, moving from let's say an environment where they would compute center models per data center models trying to understand how do they capture data, how they accelerate the adoption of AI within the various business units, why? Because they understand that currently the way they are actually going to the business changed completely, they need to understand how to adapt a new business model, they need to understand how to look for value pools where there are none as well. So most of our customers today, while initially they spend a lot of time in an never ending POC trying to investigate where do they want to go. Currently they do want to accelerate the application of AI models, the build of data strategies, how then they use all of this data? How do they capture the data to make sure that they look at new business models, new value pools, new customer experience and so on and so forth. So I think what they've seen in the past, let's say three to six months is that we lost time. But the shift towards an adoption of analytics, AI and data strategy is accelerated a lot, simply because customers realize that they need to get ahead of the game. >> So Dr. Garg, what if you could talk about how HPE is utilizing machine intelligence during this pandemic, maybe helping some of your customers, get ahead of it, or at least trying to track it. How are you applying AI in this context? >> So I think that Sorin sort of spoke to one of the things with adopting AI is, it's very transformational for a business so it changes how you do things. You need to actually adopt new processes to take advantage of it. So what I would say is right now we're hearing from customers who recognize that the context in which they are doing their work is completely different. And they're exploring how AI can help them really meet the challenges of those context. So one example might be how can AI and computer vision be coupled together in a way that makes it easier to reopen stores, or ensures that people are distancing appropriately in factories. So I would say that it's the beginning of these conversations as customers as businesses try to figure out how do we operate in the new reality that we have? And I think it's a pretty exciting time. And I think just to the point that Sorin just made, there's a lot of openness to new technologies that there wasn't before, because there's this willingness to change the business processes to really take advantage of any technologies. >> So Dr. Cheran, I probably should have started here but help us understand HPE's overall strategy with regard to AI. I would certainly know that you're using AI to improve IT, the InfoSite product and capability via the Nimble acquisition, et cetera, and bringing that across the portfolio. But what's the strategy for HPE? >> So, yeah, thank you. That's (laughs) a good question. So obviously you started with a couple of our acquisition in the past because obviously Nimble and then we talked a lot about our efforts to bring InfoSite across the portfolio. But currently, in the past couple of months, let's say close to a year, we've been announcing a lot of other acquisitions and we've been talking about Tuteybens, we've been talking about Scytale we've been talking about Cray, and so on, so forth, and now what we're doing at HPE is to bring all of this IP together into one place and try to help our customers within their region out. If you're looking at what, for example, what did they actually get when Cray play was not only the receiver, but we also acquire and they also have a lot of software and a lot of IP around optimization and so on and so forth. Also within our own labs, we've been investigating AI around like, for example, some learning or accelerators or a lot of other activity. So right now what we're trying to help our customers with is to understand how do they lead from the production stage, from the POC stage to the production stage. So (mumbles) what we are trying to do is we are trying to accelerate their adoption of AI. So simply starting from an optimized platform infrastructure up to the solution they are actually going to apply or to use to solve their business problems and wrapping all of that around with services either consumed on-prem as a service and so on. So practically what we want to do is we want to help our customers optimize, orchestrate and operationalize AI. Because the problem of our customers is not to start in our PLC, the problem is how do I then take everything that I've been developing or working on and then put it in production at the edge, right? And then keep it, maintaining production in order to get insights and then actually take actions that are helping the enterprise. So basically, we want to be data driven assets in cloud enable, and we want to help our customers move from POC into production. >> Or do you work with obviously a lot of data folks, companies or data driven data scientists, you are hands on practitioners in this regard. One of the challenges that I hear a lot from customers is they're trying to operationalize AI put AI into production, they have data in silos, they spend all their time, munging data, you guys have made a number of acquisitions. Not a list of which is prey, obviously map of, data specialist, my friend Kumar's company Blue Data. So what do you see as HPE's role in terms of helping companies operationalize AI. >> So I think that a big part of operationalizing AI moving away from the PLC to really integrate AI into the business processes you have and also the sort of pre existing IT infrastructure you talked about, you might already have siloed data. That's sort of something we know very well at HPE, we understand a lot of the IT that enterprises already have the incumbent IT and those systems. We also understand how to put together systems and integrated systems that include a lot of different types of computing infrastructure. So whether that being different types of servers and different types of storage, we have the ability to bring all of that together. And then we also have the software that allows you to talk to all of these different components and build applications that can be deployed in the real world in a way that's easy to maintain, and scale and grow as your AI applications will almost invariably get more complex involved, more outputs involved and more input. So one of the important things as customers try to operationalize AI is think is knowing that it's not just solving the problem you're currently solving. It's not just operationalizing the solution you have today, it's ensuring that you can continue to operationalize new things or additional capabilities in the future. >> I want to talk a little bit about AI for good. We talked about AI taking away jobs, but the reality is, when you look at the productivity data, for instance, in the United States, in Europe, it's declining and it has for the last several decades and so I guess my point is that we're not going to be able to solve some of the world problems in the coming decades without machine intelligence. I mean you think about health care, you think about feeding populations, you think about obviously paying things like pandemics, climate change, energy alternatives, et cetera, productivity is coming down. Machines are potential opportunity. So there's an automation imperative. And you feel, Dr. Cheran, the people who are sort of beyond that machines replacing human's issue? Is that's still an item or has the pandemic sort of changed that? >> So I believe it is, so it used to be a very big item, you're right. And every time we were speaking at a conference and every time you're actually looking at the features of AI, right? Two scenarios are coming to plays, right? The first one where machines are here, actually take a walk, and then the second one as you know even a darker version where terminator is coming, yes and so forth, right? So basically these are the two, is the lesser evil in the greater evil and so on and so forth. And we still see that regular thing coming over and over again. And I believe that 2019 was the year of reckoning, where people are trying to realize that not only we can actually take responsible AI, but we can actually create an AI that is trustworthy, an AI that is fair and so on and so forth. And that we also understood in 2019 it was highly debated everywhere, which part of our jobs are going to be replaced like the parts that are mundane, or that can actually be easily automated and so on and so forth. With the COVID-19 what happened is that people are starting to look at AI differently, why? Because people are starting to look at data differently. And looking at data differently, how do I actually create this core of data which is trusted, secure and so on and so forth, and they are trying to understand that if the data is trusted and secure somehow, AI will be trusted and secure as well. Now, if I actually shifted forward, as you said, and then I try to understand, for example on the manufacturing floor, how do I add more machines? Or how do I replace humans with machines simply because, I need to make sure that I am able to stay in production and so on and so forth. From their perspective, I don't believe that the view of all people are actually looking at AI from the job marketplace perspective changed a lot. The view that actually changes how AI is helping us better certain prices, how AI is helping us, for example, in health care, but the idea of AI actually taking part of the jobs or automating parts of the jobs, we are not actually past yet, even if 2018 and even more so in 2019, it was the year also where actually AI through automation replaced the number of jobs but at the same time because as I was saying the first year where AI created more jobs it's because once you're displacing in one place, they're actually creating more work more opportunities in other places as well. But still, I don't believe the feeling changed. But we realize that AI is a lot more valuable and it can actually help us through some of our darkest hours, but also allow us to get better and faster insights as well. >> Well, machines have always replaced humans and now for the first time in history doing so in a really cognitive functions in a big way. But I want to ask you guys, I'll start with Dr. Arti, a series of questions that I think underscore the impact of AI and the central role that it plays in companies digital transformations, we talk about that a lot. But the questions that I'm going to ask you, I think will hit home just in terms of some hardcore examples, and if you have others I'd love to hear them but I'm going to start with Arti. So when do you think Dr. or machines will be able to make better diagnoses than doctors? We're actually there today already? >> So I think it depends a little bit on how you define that. And I'm just going to preface this by saying both of my parents are physicians. So I have a little bit of bias in this space. But I think that humans can bring creativity in a certain type of intelligence that it's not clear to me. We even know how to model with the computer. And so diagnoses have sometimes two components. One is recognizing patterns and being able to say, "I'm going to diagnose this disease that I've seen before." I think that we are getting to the place where there are certain examples. It's just starting to happen where you might be able to take the data that you need to make a diagnosis as well understood. A machine may be able to sort of recognize those subtle patterns better. But there's another component of doing diagnosis is when it's not obvious what you're looking for. You're trying to figure out what is the actual sort of setup diseases I might be looking at. And I think that's where we don't really know how to model that type of inspiration and creativity that humans still bring to things that they do, including medical diagnoses. >> So Dr. Cheran my next question is, when do you think that owning and driving your own vehicle will become largely obsolete? >> (laughs) Well, I believe my son is six year old now. And I believe, I'm working with a lot of companies to make sure that he will not get his driving license with his ID, right? So depending who you're asking and depending the level of autonomy that you're looking at, but you just mentioned the level five most likely. So there are a lot of dates out there so some people actually say 2030. I believe that my son in most of the cities in US but also most of the cities in Europe, by the time he's 18 in let's say 2035, I'll try to make sure that I'm working with the right companies not to allow them to get the driving license. >> I'll let my next question is from maybe both of you can answer. Do you take the traditional banks will lose control of payment system? >> So that's an interesting question, because I think it's broader than an AI question, right? I think that it goes into some other emerging technologies, including distributed ledgers and sort of the more secure forms of blockchain. I think that's a challenging question to my mind, because it's bigger than the technology. It's got Economic and Policy implications that I'm not sure I can answer. >> Well, that's a great answer, 'cause I agree with you already. I think that governments and banks have a partnership. It's important partnership for social stability. But similar we've seen now, Dr. Cheran in retail, obviously the COVID-19 has affected retail in a major way, especially physical retail, do you think that large retail stores are going to go away? I mean, we've seen many in chapter 11. At this point, how much of that is machine intelligence versus just social change versus digital transformation? It's an interesting question, isn't it? >> So I think most of the... Right now the retailers are here to stay I guess for the next couple of years. But moving forward, I think their capacity of adapting to stores like to walk in stores or to stores where basically we just go in and there are no shop assistants and just you don't even need the credit card to pay you're actually being able to pay either with your face or with your phone or with your small chips and so on and so forth. So I believe currently in the next couple of years, obviously they are here to stay. Moving forward then we'll get artificial intelligence, or robotics applied everywhere in the store and so on and so forth. Most likely their capacity of adapting to the new normal, which is placing AI everywhere and optimizing the walk in through predicting when and how to guide the customers to the shop, and so on and so forth, would allow them to actually survive. I don't believe that everything is actually going to be done online, especially from the retailer perspective. Most of the... We've seen a big shift at COVID-19. But what I was reading the other day, especially in France that the counter has opened again, we've seen a very quick pickup in the retailers of people that actually visiting the stores as well. So it's going to be some very interesting five to 10 years, and then most of the companies that have adapted to the digital transformation and to the new normal I think they are here to stay. Some of them obviously are going to take sometime. >> I mean, I think it's an interesting question too that you really sort of triggering in my mind is when you think about the framework for how companies are going to come back and come out of this, it's not just digital, that's a big piece of it, like how digital businesses, can they physically distance? I mean, I don't know how sports arenas are going to be able to physically distance that's going to be interesting to see how essential is the business and if you think about the different industries that it really is quite different across those industries. And obviously, digital plays a big factor there, but maybe we could end on that your final thoughts and maybe any other other things you'd like to share with our audience? >> So I think one of the things that's interesting anytime you talk about adopting a new technology, and right now we're happening to see this sort of huge uptick in AI adoption happening right at the same time but this sort of massive shift in how we live our lives is happening and sort of an acceptance, I think that can't just go back to the way things work as you mentioned, they'll probably be continued sort of desire to maintain social distancing. I think that it's going to force us to sort of rethink why we do things the way we do now, a lot, the retail, environments that we have the transportation solutions that we have, they were adapted in many cases in a very different context, in terms of what people need to do on a day-to-day basis within their life. And then what were the sort of state of technologies available. We're sort of being thrust and forced to reckon with like, what is it I really need to do to live my life and then what are the technologies I have available to meet to answer that and I think, it's really difficult to predict right now what people will think is important about a retail experience, I wouldn't be surprised if you start to find in person retail actually be much less, technologically aided, and much more about having the ability to talk to a human being and get their opinion and maybe the tactile sense of being able to like touch new clothes, or whatever it is. And so it's really difficult I think right now to predict what things are going to look like maybe even a year or two from now from that perspective. I think that what I feel fairly confident is that people are really starting to understand and engage with new technologies, and they're going to be really open to thinking about what those new technologies enable them to do in this sort of new way of living that we're going to probably be entering pretty soon. >> Excellent! All right, Sorin, bring us home. We'll give you the last word on this topic. >> Now, so I wanted to... I agree with Arti because what these three months of staying at home and of busy shutting down allowed us to do was to actually have a very big reset. So let's say a great reset but basically we realize that all the things we've taken from granted like our freedom of movement, our technology, our interactions with each other, and also for suddenly we realize that everything needs to change. And the only one thing that we actually kept doing is interacting with each other remotely, interacting with each other with our peers in the house, and so on and so forth. But the one thing that stayed was generating data, and data was here to stay because we actually leave traces of data everywhere we go, we leave traces of data when we put our watch on where we are actually playing with our phone, or to consume digital and so on and so forth. So what these three months reinforced for me personally, but also for some of our customers was that the data is here to stay. And even if the world shut down for three months, we did not generate less data. Data was there on the contrary, in some cases, more data. So the data is the main enabler for the new normal, which is going to pick up and the data will actually allow us to understand how to increase customer experience in the new normal, most likely using AI. As I was saying at the beginning, how do I actually operate new business model? How do I find, who do I partner with? How do I actually go to market together? How do I make collaborations more secure, and so on and so forth. And finally, where do I actually find new value pools? For example, how do I actually still enjoy for having a beer in a pub, right? Because suddenly during the COVID-19, that wasn't possible. I have a very nice place around the corner, but it's actually cheaply stuff. I'm not talking about beer but in general, I mean, so the finance is different the pools of data, the pools (mumbles) actually, getting values are different as well. So data is here to stay, and the AI definitely is going to be accelerated because it needs to use data to allow us to adopt the new normal in the digital transformation. >> A lot of unknowns but certainly machines and data are going to play a big role in the coming decade. I want to thank Dr. Arti Garg and Dr. Sorin Cheran for coming on theCUBE. It's great to have you. Thank you for a wonderful conversation. Really appreciate it. >> Thank you very much. >> Thanks so much. >> All right. And thank you for watching everybody. This is Dave Vellante for theCUBE and the HPE 2020 Virtual Experience. We'll be right back right after this short break. (upbeat music)

>>from around the globe. It's the Cube covering HP Discover Virtual experience brought to you by HP. >>Hi. Welcome back. I'm Stew Minimum, and this is the cube covers of HP Discover 2020. The virtual experience gonna be digging into Green Lake and help me with that. Happy to welcome to the program. First time guest Arwa Fedora. She is the vice president of worldwide sales for Green Lake with Hewlett Packard Enterprise are a thanks so much for joining us. >>Thanks for having me. All >>right. So as I teed up, you're relatively new in the role. So if you could just >>give us a little bit >>about your background, what brought you to HP And what your focus is there? >>Yeah, absolutely. Thanks for having me Weeks seven. So definitely new in the role, um, came from sort >>of ah, public cloud. Ah, >>cloud native ah, set of experiences through Microsoft. And previous to that it was Amarin where we focused on a lot of mobile application development. Ultimately, what brought me toe hp? To be honest is the fact that while cloud has brought a ton of innovation to, you know, many companies, many industries, many applications. I think I also see the opportunity that it's not just about public cloud, but it's about bringing cloud experience everywhere. And so, looking at the agility, the innovation, the speed, um, you know, some of the cost savings that the cloud has brought companies. Um, I believe that from a green Lake perspective, we now have an opportunity to modernize I t infrastructure and bring it to our customers in a way that they've never seen before. And so ultimately that that was what brought me >>to HP. >>All right, well, what excited me about having the discussion with you is you talked about some of the application modernization cloud native pieces that you've got history on, you know, my background infrastructure, but has an infrastructure person. We know the role of infrastructure really is to support those application. A term I've used for a number of years now is you want to modernize the platform and then you and modernize the applications on top of you know, what are you hearing from customers? You know, when I talk to developers, often it is, you know, hybrid model of how they're building things that is no longer a monolithic things are changing and moving everywhere. Data, of course, has huge import. Help us understand that role of the application and data when it comes to Green Lake. >>Yeah, and I think one of the great point that you know, whether it's research or our customers. What we ultimately know is 70% of absent data remain on premises today, right? Whether that's the data center, it's in co location or at the edge. Right? And that's where a good business reason that they have to remain in those data centers, right? We have things like, you know, late and see that we have to deal with. We have governance and security. We have data gravity. We have application dependencies, right? And so, being able to think >>about well, how do you solve that >>problem for the remaining 70% of applications? So if they can't move into >>the cloud well, how >>do we bring the cloud to them? Right. And that's exactly where Green Lake then, which is let's create that cloud like experience from everything, for you know, the obvious things that pay as you go the, um, sort of the self service be managed for you right, bringing that in to the customers, you know, Data center again. Coehlo The edge, I think, becomes a really powerful value prop and again, from my experience, right. Not every application is going to be a cloud native application that is being built newly for cloud only capabilities on. And there's still a lot of great applications that can still be built on Prem with cloud like experiences that are brought to you by Green Lake. >>Alright, so are you have the, you know, the sales title. And when I think about HP, HBs had a number of offering customers along that journey towards that cloud model that you're talking about. Ah, lot of them. You know, I think back, you know, go back Seven years ago, it was very much, you know, here is our stack and we have hybrid models and we're working with service providers. Green Lake is very much managed service, So help us understand a little bit, you know, from from the go to market standpoint, the sales standpoint, that mind shift of going from, you know, here's gear or here's the stack we're doing to really It is a managed services offering. So I would think it's it's a different It's if you will. It's a mindset. It's different, necessarily who you might be selling it >>absolutely. And I think if I had to think about what we're announcing at Discover right and how we're evolving Green Lake, it really starts to focus on launching new cloud services like containers, virtual machines, storage, compute right, sort of the core cloud offerings. But then also adding things like machine learning ops, you know, data protection for cloud and on Prem in networking services, right? And from a Green Lake perspective, I think if I had to think about the go to market, it's yes, managed services. But what does that mean, Right? That means new self service cloud experiences the Agree Lake Central, which has very detailed on sort of consumption and billing data to allow you to have that transparency. It also gives you self service capable abilities, right so that you can, you know, spin, spin up virtual machines or configure the services that you need or that you've purchased from us. Um and then also having the ability now to have new work load optimized, sort of T shirt size building blocks, right? So, being ableto very quick really find out from our customers, What is it that they need having sort of small, medium large capabilities again, thinking about those workloads that they're trying to support And then in under 14 days, being able to deliver the capability to their doors and have that spun up and ready to go? >>Yeah. One of the advantages, of course, is, you know, rather than thinking about okay, I've got all of these products. It's now more like a service catalog. I have a lot of different ways. Ah, and you've got things that like Oh, wait, you know, can that running there? You talked about the ML and the analytics. Of course, he's done a few acquisitions in this base to help enhance that light like map Are I know we've been talking a bit about, you know, Blue Data and, like, I'm curious from, you know, the touch points that you're having in customer. Is it shifting from you know, it's not necessarily, I think the person that buys the server, you know, cloud often was the line of business driving from the application down. So how does that alignment between the field and the customer shifting. And how do you expect Green Lake to kind of move that along even more? >>Yeah, that's right. It becomes a business sort of driven conversation, right? So what are the outcomes that our customers are driving for from a business transformation perspective? So if you think about what they're trying to do is they don't want to have to worry about delivering their own I t, which often is slow on, maybe contains supply chain risks. And then, of course, there's sort of the over provisioning risks that come with that as well. The way I see our role from a go to market perspective is we do have to engage, and we are engaging new audiences that we probably haven't been intimately sort of familiar with in the past. And that includes the line of business that includes also, you know, the architect internally within companies that are designing sort of best of breed architectures to deliver the technology infrastructures that will power their next generation of internal applications or even their own solutions to the market it includes. You know, if you're talking about ml ops, it includes talking to data scientists right and understanding. You know, what is that specific machine learning scenario that they are trying to, you know, train a model around? And how do we help deliver the best solution for them? Because we also know that putting that in how most of the time is too far away from your data or the edge, Um, from which you are collecting data from which again becomes super expensive. You have latency issues, and it's not a really great way to solve ml ops, right? We feel like we have a much better solution. And in talking to some of those audiences that are trying to solve those business challenges within our customer base, um, we are finding ourselves also talking to a lot of new audiences. And, you know, one audience that I'm intimately familiar with is obviously the developer audience, right. Developers don't want to worry about i t infrastructure. They don't want to have to walk over and tell someone that day. I need you to configure X y Z in order for me to start, you know, testing my code or my you know, sort of MPP. They want to know that it's all managed that it's quick time to value and that when they're ready to go, the infrastructure is there and ready to be deployed against the project that they're trying to execute. So those are really important audiences that I feel like we're starting to nurture, and we will have a lot more content and relevance for going forward with Green Lake. >>Yeah, a really important point there. I want also, you know, how do you kind of there's There's a big ecosystem around Green Lake. So, you know, give me a little bit about the you know, the differentiation of HP compared to some of the other hybrid solutions out there. And because I look, there's obviously hardware soft where solutions that HP has internally. But then you've also got, you know, VM ware, Nutanix, Red hat and others that are our partners, you know, how do you help customers sort through those? >>Yeah, absolutely. And I think it begins with delivering choice to our customers right. At the end of the day, we need to make sure that we're up optimizing for what our customers are looking to do. So there has to be an element of openness with HP Green Lake that we're pretty proud to deliver. So we have multiple I SD partnerships, partnerships. You mentioned some of them, you know, VM Ware and Nutanix. With respect to delivering some of our solutions, I think from a competitive advantage, you know, I go back to the fact that you know the 70% of absent data that are still sitting on Prem or, you know, in a polo and edges our competitive advantage comes from being able to bring a true cloud experience. Um, to those absent data where I would argue no one else can do this in a way that has, you know, speed from a time to value perspective, scalability, right. Being able to sort of go up and down a managed for you, a true pay per use model and billing at that level of granularity, um, and the self service right, allowing you to self provisioned and do some of those things once we've delivered the core capabilities for you. So from a competitive advantage, I feel like we cover off more of the cloud like experience does than anyone else that does in the market. And then we also have the partnerships and the ability to bring in some of those third party I SP solutions that work incredibly well on relate. >>Yeah. One of the challenges we've seen in the field is, you know, customers they do have Ah e I guess we know he always is added So, you know, you mentioned you know, their shifts. But customers Absolutely. They have their data centers. They're using often multiple public clouds out there. And they are. You know, we've talked a lot to be about the edge, so help us understand. You know, where green Lake fits and how the portfolio helps customers as they need to be able >>to >>manage and optimize what they're doing across all those disparate environment. >>Yeah, I think you're absolutely right. Customers. First of all, we're going to have a multi cloud and sort of a multimodal strategy, right? Some things they're going to put in the different public clouds and some things they're going to maintain on Prem or in a in a polo. And and then some things, of course, work better in an edge scenario. The great part about Green Lake is we solve the on Prem State problem in a really effective and cost effective and time to value perspective really, really well. But with Green Lake Central, we also give you the transparency to manage your public cloud footprint just as well. So we allow you to unify across that the different footprints that you want tohave. And we're also, you know, not proprietary when it comes to Green Lake Central, right? You can again, um, other pieces versus, you know, maybe some of the hyper scaler is that are trying to create more of a walled garden or a lock in scenario where, yes, you get transparency, but only as long as you're within their solution. >>Alright, So I understand there's about 1000 customers. We've passed 1000 customers Happy Green Lake, according to another interview that I did. So you've got sales, give us a little bit, you know, which we expect for kind of customer adoption. And what else do you expect us to be looking at from the Green Lake offerings? >>Yeah, absolutely. And I think from, you know, a customer Women term perspective. It has just been fantastic to be part of this journey, at least for me. For the past seven weeks, and to see our customers really embrace this new way of how we deliver I t. Infrastructure to them, I think, in a way that meet them where they are right as they're transforming. We're bringing that on Prem Cloud like experience to their doorstep without them having to feel the pressure of migrating everything, whether it makes sense or not into the cloud again in terms of what's coming new, Um, I would reiterate the fact that it is looking at all of the basic services like containers VM storage, Compute. It's also starting to optimize around specific workloads again, Teoh the point earlier about ML ops, Um, but from what's new and exciting, I get really excited about Hey, I don't want our customer spending time thinking about how to architect and how to design the right i t. Or infrastructure offering. I want to be able to do that for them in order to deliver that experience that they need. And again, what that helps our customers with is cost time to value and the ability to get a pre configured solution that is already optimized right. We don't want our customers spending all of their time having to configure an architect. I t infrastructure. We want them to worry about the business outcomes and then tell us what they need. And then we create those pre configured solutions on their behalf, given their input. So so again, it's a very cloud like way to deliver value to our customers. And I think it also frees up our customers to focus the resources on the real innovation that they need to drive at their business level versus focusing on things that, you know we're experts in. And we can bring to them in a much quicker and more value of >>way. Absolutely. Thank you so much. You actually what We've heard loud. And they need to be able to shift away from things that they don't have, differentiated, and then don't add value to the business and focus on this business. FN our congratulations on the new position and definitely look forward to watching the continued progress. Good buzz around Green Lake >>and test. Thank you. Still thanks for having me. >>Alright. Stay tuned for lots more coverage from HP. Discover the virtual experience. I'm Stew Minimum And thank you for watching the Cube. Yeah, yeah, yeah, yeah

>>from around the globe. It's the Cube covering HP Discover virtual experience brought to you by HP. >>Hi. And welcome back to the Cube's coverage of HP Discover 2020. The virtual experience. I'm stew minimum, and we're gonna be talking about the Green Lake solution. Of course, this manage services of from Hewlett Packard Enterprise. Happy to welcome to the program. Vice president of Green Lake Scott. Yeah, with HP. Thanks so much for joining us. >>Stew. Thanks for having me super excited to be here and hello to all of you in the audience. And welcome to the Discover virtual experience. >>All right, So, Scott, give us a little bit of you know, your background and, you know, the purview that you have in your role. >>Absolutely. So we've been very busy in the factory over the last couple of years, really bringing together experts from across the company to build out our portfolio of I P for hybrid cloud. I lead the development effort for HP Green Lake, and, uh, we have a number of exciting announcements that we're making during discover and talk a little bit about that later on in the conversation. But, um, you know, think about Green Lake is our answer to a consumption driven hybrid cloud experience. >>Yeah, And Scott, you know, hybrid is a word. You know, I think back to a dozen years ago when, you know, cloud and public and private we had this term for hybrid cloud. But it feels to me like we've really defined it and understood it and matured it over the last couple of years. So HP has partnerships with a lot of companies. So maybe just clarify for our audience when you say hybrid, what that means. And you know, some of those key partnership that you're delivering the solutions for customers >>with? Yeah, absolutely. So I think, Look, as you point out, hybrid cloud is a bit of a loaded term. And there are a number of companies out there that are building out an alternative hybrid cloud strategies. And maybe I'll sort of comment on a few of them and talk a little bit about how what we're doing is different. Um, of course it's It's hard to have a conversation about Cloud without thinking about what AWS is doing. And, of course, about a year ago, a little over a year ago, they announced Outpost, which is really their answer to the hybrid cloud challenge, right? And if you think about an outpost, right, fundamentally, what AWS is doing is taking a rack of equipment that sits in their public cloud facilities today. Replicating that and dropping it inside the four walls right of a customer's data center. And then that has some interesting pros and cons obviously benefit. That is, to have a very congruent eight of us experience inside your own corporate data center. I think the challenge to that is you're still sort of vertically integrated into that AWS architecture, and it it's really a walled garden that sits inside your you know, your on prem environment. It doesn't seamlessly connect to all of your existing I t. >>Now, of >>course, Dell VM, where you know they have their answer to Hyper Cloud, which is almost the exact opposite of what the outpost guys. And let's take a rack of architecture, that technology stack for VM ware and replicate that in a public cloud, right? And you know that has a different set of benefits, right? You know, the benefit there is that now you have a VM ware right on Prem that you can burst into capacity that sits in in this case, AWS right? But that has the opposite challenge in that that VM Ware environment that's sitting inside AWS right? It's a walled garden that doesn't give you full access to all of the benefits that the public cloud brings to the table right aws, serverless technologies and so on and so forth with Green Lake. We think that there is an alternative approach, 1/3 approach to thinking about hybrid, which is, rather than create vertically integrated stacks that span multiple different data centers to create an environment where we can seamlessly connect to all of the native services that sit in azure in Google in AWS. Because hybrid is not just about on Prem and off brands, it's about multi cloud, but also connect all of those richness of public cloud services on Prem as well, and make the on Prem environment available to a multiple set of technologies. Whether it's containers, virtual machines or bare metal. And with Green Lake and Green Lake Central, we provide the ability to control and manage workloads in a very congruent fashion across that entire state. So we think that the approach we bring to the table is a forward looking. You know, acknowledging that hybrid doesn't just mean multiple different on Prem off prem environments, but it means multiple public cloud providers and potentially multiple different on Prem environments as well. >>Right? And it's very much a partner. Focus my understanding of this Scott. If if I understand right you can connect to the public clouds out there and then in your on premises solution, which is a managed offering, you have a few different stack options, depending on you know what management layer. They're so Microsoft VM ware on Nutanix that some of the flavors that you've got to it Do I have that right? >>Exactly. So of course, where we're at with HPE, he's had a rich, deep partnership with Microsoft for a number of years. You know, Azure is an extension of that. So we're partnering with as a partner with AWS Google and then on Prem you probably have heard about and you actually mentioned the work we're doing with Nutanix. We also have work we're doing with Google there and of course, we have a long standing partnership with VM ware. So all of these technologies are are of the Green Lake experience. But increasingly, we're also embedding a lot more of our own I e. Right. So we will have an opinionated technology stack that we will make as an available option for Green Lake that embeds the HP container platform that we announced in general. I think it was January as well as map are for a data fabric and our own kubernetes distribution. So a lot of different options that are going to be made available there, one of which is going to be our own vertically integrated stack that provides the hardware that kubernetes environment and the storage fabric as an option for being like as well, >>excellent. And you mentioned, Ah, you know, here at Discover there's some additional updates. Why don't you share with us? The news >>Absolutely so super excited about some of the announcements were making this week at Discover one. It really revolves around AI and ML, and it's an ML ops as a service machine learning off as a service. And if we think about what is ml ops, side of service means the easiest way to think about it is that its Dev Ops or AI and ML workloads And one of the challenges that we've heard from customers is that data scientists are amazingly skilled at being able to define models, understanding how to train them and that whole part of the life cycle. But they're not necessarily good. Dev Ops engineers, right? So what we bring to the table with Green Lake is a curated environment that takes our kubernetes distribution right. It takes, you know, that came from Blue Data. It takes our high performance hardware, our Apollo hardware, which is some of the highest performance machines available in the industry today. And we offer that entire pipeline of ml ops tool sets, think about public and so flow spark High Torch Cafe exception. We manage that entire Dev Ops pipeline for all those tools, and we make them available for a Dev Ops and excuse me as a data scientist so that they can focus on building the models, training the models, not having to run the underlying pipeline so that entire stack is gonna be made available for Green Lake. We're excited about that, and we're also making available right it out as a service. So essentially, what this solution for really does is it brings the cloud experience inside the data center. Um, we provide all of the infrastructure automation through Green Lake Central to be able to provision workloads, manage them, operate them in the same way as public cloud. We allow the ability to import existing images and were close right, whether they're, you know, am I Z or VM ware and so on and so forth. And we provide a set of tool kits like terraform, for example, that brings the same way to manage those workloads on Prem as they are today in the public cloud. So really thinking about how from a hybrid perspective, bringing that cloud experience to the data center and allowing our customers to operate it, manage it and really enable digital transformation inside the data center. >>So, Scott Digital transformation is something we've been talking about for a number of years. There's been a real spotlight on it, you know, this year in 2020 with the global pandemic. So of course, you know, companies that have really gone through transformation, hopefully they're getting the agility and they're being able to respond faster But, you know, it's one of those things that many people heard anecdotally, uh, you know, are accelerating or needing toe have the results of digital transformation today. So I'm curious what you've been seeing from your customer base with everything that's been happening for the last few months. >>Well, you know, it's it's it's been a really a benefit for us. We have over 1000 customers, you know, Green Lake today. So we have the opportunity to obviously solicit, you know, a fair bit of feedback. And, you know, one of the if you kind of think about the growth in data, right and the desire if we just think about the pandemic in general, you know the ability to run training models to be able to test out new types of drugs to understand what the options are available to move forward to help address both from a prevention perspective, right? As well as a treating perspective, the ability to use the right high performance hardware and put it in a place where the data already exists drastically accelerates, right, The time to result. Um, if you think about, for example, the ml ops workflow that I talked about. You know this. The data likely already exists inside a customer data center, and we can bring the tools to the data right. Bring the cloud to the data, which allows a very quick turn up of being able to use those services as opposed to having to move all of that data into a different facility before you can run these training models and tools on. So there's a lot of different examples that we have. You know, there's There are also examples around things like why it's when we think about hybrid environment and particularly now, with endemic, you know, we may have data that's fragmented across multiple different data centers across the globe. Being able to understand who is accessing what data right from what location and making sure that that hybrid I t environment is provided with things like we're in the financial industry. Gpr or maybe, um, compliance frameworks. Like I s O Green Lake Central is constantly monitoring thousands of parameters and looking at how data is accessed and works flowing, and we provide a dashboard that helps our customers understand if there are areas that they need to look at if they're in compliance or not. So as we think about hybrid, it's not necessarily just the provisioning of all of the workloads and the operation of management. But it's also the governance aspect. >>Yeah, I'm glad you brought up governance. That kind of leads me. Scott, What about security? So, you know, we understand, You know, Cloud in General has gone through some maturation when it comes to security for, you know, early part of the year it was I might not want to do it before a security Now Cloud gives me the opportunity. Think about rethink my security. And these days, it really is a discussion of, you know, it's a shared responsibility model. So with a manage service, what's the interaction between what you're doing with Green Lake and how the customer handles security? What is that interaction? >>And they have security. I think it's a good point that most of our customers, all of our customers, are going to have a group dedicated to looking at what that particular enterprise or business requires from a security perspective, and they're gonna have various different frameworks. So one of the things that we've done within Green Lake is to make it flexible to adopt and embed existing security profiles into Green Lake. So, for example, many times they're versions of an operating system that have special security patches. There may be kernel extensions or different certified golden images, if you will, that are compliant with existing security parameters and profiles that an organization they have, we can embed those natively so we don't necessarily provide any any barrier to utilizing the existing frameworks that already exists. Yeah, so I think that's one piece. The second piece is when we think about the delivery of the Green Lake solution. HP has taken security. HP is taking security very seriously, and for a number of years now, we've been embedding security technology straight into our hardware. So enabling, for example, is looking root of trust, having a very, very vertically integrated security profile and monitoring set of technologies that we can embed to make sure that we prevent against malware, assertion and things of that nature. So all of those are happening, and over the next number of months you're gonna probably see some new announcements about what we're doing to increase the level of security that's embedded right into our systems. And of course, when we deliver those as part of Green Lake, the technology that we're building leverage is all of that embedded security technologies built into the hardware as well. >>Alright, Scott, you mentioned that you've now got 1000 customers on Green Lake. You know what visible like can you share as to the adoption of it? You know how important what you're doing with Green Lake is for our customers. >>So, you know, great. Did you mention I mentioned we have about 1000 customers are like today. And I will tell you our experience with these customers has been overwhelmingly positive. And I can tell you, we have over 99% 99.9 actually, percent really well right on Green Lake. And typically those customers one or two of them that have moved off of Green Lake has been because they had the ability to move back to a Capex model that additional funding and finance is available to move from consumption back to a Capex model. But really, it's been deployed across a number of industries. We have financial, retail, oil and gas research, pharmaceuticals. Take your pick. We have really like probably deployed in that particular vertical. And what we found is that you know the bulk of these deployments many times, customers just being able to take the green light technology and look at what's being deployed, where, what they're spending, having the ability to understand. What would it cost me to deploy this workload in a public cloud versus my green like environment that actually facilitates a significant amount growth? As a matter of fact, we had one a customer that started with about 100 virtual machines. We're running 4500 virtual machines on Green Lake today, so we get it in there. The experiences tends to be overwhelmingly positive. With Greenlee, we bring the best of what HP has to offer right the premium hardware that we build right, the support in deployment services. We have a dedicated, bring like delivery engineer that works with our customers to understand what workloads they have to be able to run on Green Lake, what the growth and scale ability for those workloads look like. And we were proactively to make sure that that Green Lake environment is curated for that customer. So it's been overwhelmingly positive and I think it really showcases the best of what, as a company between hardware, software and services, we can bring into the solution. >>Excellent. Well, Scott, I'll give you the final word. Ah, obviously a lot of sessions happening this week at the Discover Virtual experience. What do you want people to? You know, What do you recommend that they dig into and what you want them to take away from this week when it when it comes to your solution set. >>So there's a lot of great additional sessions as well, by the way, on a white has a good session. I would encourage you to see that if you're interested more to learn about things like Central and some of our technology stack, I have a few sessions on that as as well as Google, my colleague. But E. Guess I would sort of leave it with this thought that when we think about digital transformation, uh, and we think about modernizing the way we build operate manage workloads. The traditional destination has been to use public cloud, and with Green Lake, we aim to bring that cloud experience to the data center. Green Lake not only enables a pay as you go I t service offer. But it brings the digital transformation technologies to your data center and allows you to build, operate and manage in a modern way without having to move your data to a public cloud. So we think that's a very, very powerful message. And we think that it really has the ability to transform the way I tee gets, too. Boyd scaled, operated. Um, now into the future. Alright? >>Well, Scott, really appreciate the updates and congratulations on the progress. >>Appreciate the time to do. >>Alright. Stay tuned for lots more coverage with the cube at HP. Discover the virtual experience. I'm stew minimum. And thank you. For what? The cube. >>Yeah, yeah, >>yeah.

>>from around the globe. It's the Cube covering HP. Discover Virtual experience Brought to you by HP. >>Welcome back to the Cube's coverage of HP Discover. 2020. The virtual experience. The Cube. The Cube has been virtualized. My name is Dave Vellante. I'm here with Stuart Minuteman and our good friend Tim Crawford is here. He's a strategic advisor to see Io's with boa. Tim, Great to see you. Stuart. Thanks for coming on. >>Great to see you as well, Dave. >>Yes. So let's unpack. What's going on in that Discover Antonio's, He notes, Maybe talk a little bit about the prospects for HP of coming forward in this decade. You know, last decade was not a great one for HP, HP. I mean, there was a lot of turmoil. There was a botched acquisitions. There was breaking up the company and spin merges and a lot of distractions. And so now that companies really and you hear this from Antonio kind of positioning for innovation for the next decade. So So I think this is probably a lot of excitement inside the company, but I want to touch on a couple of points and then you get your guys reaction, I guess, you know, to start off. Obviously, Antonio's talking about Cove in the role that they played in that whole, you know, pandemic and the transition toe the the isolation economy. But so let me start with you, Tim. I mean, what is the sort of posture amongst cios that you talk to? How strategic is HB H B two? The folks that you talk to in your community? >>Well, I think if you look at how CIOs are thinking, especially as we head into covert it into Corona virus and kind of mapping through that, that price, um, it really came down to Can they get their hands on technology? Can they get people back to work working from home? Can they do it in a secure fashion? Um, keeping people productive. I mean, there was a lot of block and tackling, and even to this day, there's still a fair amount of that was taking place. Um, we really haven't seen the fallout from the cybersecurity impact of expanding our foot print. Um, quite. But we'll see that, probably in the coming months. There are some initial inklings there when it comes to HP specifically I think it comes back to just making sure that they had the product on hand, that they understood that customers are going through dramatic change. And so all bets are off. You have to kind of step back and say, Okay, those plans that I had 60 9100 and 20 days ago those strategies that I may have already started down the path with those are up for grabs. I need to step back from those and figure out What do I do now? And I think each company, HP included, needs to think about how do they start to meld themselves, to be able to address those changing customer needs? And I think that's that's where this really kind of becomes the rubber hits the road is is HP capable of doing that? And are they making the right changes? And quite frankly, that starts with empathy. And I think we've heard pretty clearly from Antonio that he is sympathetic to the plight of their customers and the world >>on the whole. >>Yeah, and I think culturally 10 minutes do I mean I think you know HP is kind of getting back to some of its roots, and Tony has been there for a long time. I think people I think is very well liked. Andi, I think, ease of use, and I'm sure he's tough. But he's also a very fair individual, and he's got a vision and he's focused. And so, you know, I think again, as they said, looking forward to this decade, I think could be one that is, you know, one of innovation. Although, you know, look, you look at the stock price, you know, it's kind of piqued in November 19. It's obviously down like many stocks, so there's a lot of work to do there, and it's too. We're certainly hearing from HP. This notion of everything is a service that we've talked about green like a lot. What's your sense of their prospects going forward in this, you know, New Era? >>Yeah, I mean, Dave, one of the biggest attacks we've heard about H E in the last couple of years, you know the line Michael Dell would use is you're not going to grow by, say, abstraction. But as a platform company, HP is much more open. From what I've seen in the HP that I remember from, you know, 5 to 10 years ago. So you look at their partner ecosystem. It's robust. So, you know, years ago, it seemed to be if it didn't come out of HP Labs, it wasn't a product, you know. That was the services arm all wanted to sell HP here. Now, in this software defined world working in a cloud environment, they're much more open to finding that innovation and enabling it. So, you know, we talk about Green Lake Day. Three lakes got about 1000 customers right now, and a big piece of that is a partner. Port Police, whether it's VM Ware Amazon Annex, were H B's full stack themselves. They have optionality in there, and that's what we hear from from users is that they want flexibility they don't want. You know, you look at the cloud providers, it's not, you know, here's a solution. You look at Amazon. There's dozens of databases that you can use from Amazon or, if you use on top of Amazon, so H p e. You know, not a public cloud provider, but looking more like that cloud experience. They've done so many acquisitions over the years. Many of them were troubled. They got rid of some of the pieces that they might have over paid for. But you look at something like CTP them in this multi cloud world in the networking space, they've got a really cool, open source company, the company behind spiffy, inspire. And, you know, companies that are looking at containers and kubernetes, you know, really respond to say, Hey, these are projects that were interesting Oh, who's the company that that's driving that it's HP so more open, more of a partner ecosystem definitely feels that there's a lot there that I respect and like that hp >>well, I mean, the intent of splitting the company was so that HP could be more focused but focused on innovation was the intent was to be the growth company. It hasn't fully played out yet. But Tim, when you think about the conversations that CIOs are having with with HPI today versus what they were having with hpe HP, the the conglomerate of that the Comprising e ds and PCs, I guess I don't know, in a way, more more Dell like so Certainly Michael Dell's having strategic conversations, CIOs. But you got to believe that the the conversations are more focused today. Is that a good thing or a jury's still out? >>No, it absolutely is a good thing. And I think one of the things that you have to look at is we're getting back to brass tax. We're getting back to that focus around business objectives. So no longer is that hey, who has the coolest tech? And how can we implement that tax? Kind of looking from a tech business? Ah, spectrum, you're now focused squarely is a C i. O. You have to be squarely focused on what are the business objectives that you are teamed up for, and if you're not, you're on a very short leash and that doesn't end well. And I think the great thing about the split of HP HP e split and I think you almost have to kind of step back for a second. Let's talk about leadership because leadership plays a very significant role, especially for CIOs that are thinking about long term decisions and strategic partners. I don't think that HP necessarily had the right leadership in place to carry them into that strategic world. I think Antonio really makes a change there. I mean, they made some really poor decisions. Post split. Um, that really didn't bode well for HP. Um, and frankly, I talked a bit about that I know wasn't really popular within HP, but quite frankly, they needed to hear it. And I think that actually has been heard. And I think they are listening to their customers. And one of the big changes is they're getting back into the software business. And when you talk about strategic initiatives, you have to get beyond just the hardware and start moving up the proverbial stack, getting closer to those business initiatives. And that is software. >>Yeah, well, Antonio talked about sort of the insights. I mean, something I've said a lot about borrowed from the very Meeker conversations that that data is plentiful. Something I've always said. Insights aren't. And so you're right. You've seen a couple of acquisitions, you know, Matt bahr They picked up, I think pretty inexpensively. Kind of interesting cause, remember, HP hp had an investment in Horton works, which, of course, is now Cloudera and Blue Data. Ah Kumar Conte's company, you know, kind of focusing on maybe automating data, you know, they talked about Ed centric, cloud enabled, data driven. Nobody's gonna argue with those things. But you're right, Tim. I mean, you're talking more software than kind of jettisons the software business and now sort of have to rebuild it. And then, of course, do this cloud. What do you make of HP ease Cloud play? >>Yeah, well, I >>mean, >>Dave, you the pieces. You were just talking about math bar and blue data, where HP connects it together is, you know, ai ops. So you know, where are we going with infrastructure? There needs to be a lot more automation. We heard a great quote. I love from automation anywhere. Dave was, if you talk about digital transformation without automation, it's hallucination. So, you know, HP baking that into what they're doing. So, you know, I fully agree with Tim software software software, you know, is where the innovation is. So it can't just be the infrastructure. How do you have eyes and books into the applications? How are you helping customers build those new pieces? And what's the other software that you build around that? So, you know, absolutely. It's an interesting piece. And you know, HP has got a lot of interesting pieces. You know, you talk about the edge. Aruba is a great asset for that kind of environment and from a partnership, that is a damn point. Dave. They have. John Chambers was in the keynote. John, of course. Long time partners. He's with Cisco for many years Intel. Cisco started eating with HP on the server business, but now he's also the chairman of pensando. HP is an investor in pensando general availability this month of that solution, and that's going to really help build out that next generation edge. So, you know, a chip set that HP E can offer similar to what we see how Amazon builds outpost s. So that is a solution both for the enterprise and beyond. Is as a B >>yeah course. Do. Of course, it's kind of, but about three com toe. Add more fuel to that tension. Go ahead, Tim. >>Well, I was going to pick apart some of those pieces because you know, at edge is not an edge is not an edge. And I think it's important to highlight some of the advantages that HP is bringing to the table where Pensando comes in, where Aruba comes in and also we're really comes in. I think there are a number of these components that I want to make sure that we don't necessarily gloss over that are really key for HP in terms of the future. And that is when you step back and you look at how customers are gonna have to consume services, how they're going to have to engage with both the edge and the cloud and everything in between. HP has a great portfolio of hardware. What they haven't necessarily had was the glue, that connective tissue to bring all of that together. And I think that's where things like Green Lake and Green Lake Central really gonna play a role. And even their, um, newer cloud services are going to play a role. And unlike outposts and unlike some of the other private cloud services that are on the market today, they're looking to extend a cloud like experience all the way to the edge and that continuity creating that simplicity is going to be key for enterprises. And I think that's something that shouldn't be understated. It's gonna be really important because when I look at in the conversations I'm having when we're looking at edge to cloud and everything in between. Oh my gosh, that's really complicated. And you have to figure out how to simplify that. And the only way you're going to do that is if you take it up a layer and start thinking about management tools. You start thinking about autumn, and as companies start to take data from the edge, they start analyzing it at the edge and intermediate points on the way to cloud. It's going to be even more important to bring continuity across this entire spectrum. And so that's one of the things that I'm really excited about that I'm hearing from Antonio's keynote and others. Ah, here at HP Discover. >>Yeah, >>well, let's let's stay on that stupid. Let's stay on that for a second. >>Yeah, I wanted to see oh interested him because, you know, it's funny. You think back. You know, HP at one point in time was a leader in, you know, management solutions. You know, HP one view, you know, in the early days, it was really well respected. I think what I'm hearing from you, I think about outpost is Amazon hasn't really put management for the edge. All they're doing is extending the cloud piece and putting a piece out of the edge. It feels like we need a management solution that built from the ground up for this kind of solution. And do I hear you right? You believe that to be as some of those pieces today? >>Well, let's compare and contrast briefly on that. I think Amazon and the way Amazon is well, is Google and Microsoft, for that matter. The way that they are encompassing the edge into their portfolio is interesting, but it's an extension of their core business, their core public cloud services business. Most of the enterprise footprint is not in public cloud. It's at the other end of that spectrum, and so being able to take not just what's happening at the edge. But what about in your corporate data center in your corporate data center? You still have to manage that, and that doesn't fall under the purview of Cloud. And so that's why I'm looking at HP is a way to create that connective tissue between what companies are doing within the corporate data center today, what they're doing at the edge as well as what they're doing, maybe in private cloud and an extension public cloud. But let's also remember something else. Most of these enterprises, they're also in a multi cloud environment, so they're touching into different public cloud providers for different services. And so now you talk about how do I manage this across the spectrum of edge to cloud. But then, across different public cloud providers, things get really complicated really fast. And I think the hints of what I'm seeing in software and the new software branding give me a moment of pause to say, Wait a second. Is HP really gonna head down that path? And if so, that's great because it is of high demand in the enterprise. >>Well, let's talk about that some more because I think this really is the big opportunity and we're potentially innovation is. So my question is how much of Green Lake and Green Lake services are really designed for sort of on Prem to make that edge to on Prem? No, I want to ask about Cloud, how much of that is actually delivering Cloud Native Services on AWS on Google on Azure and Ali Cloud etcetera versus kind of creating a cloud like experience for on Prem in it and eventually the edge. I'm not clear on that. You guys have insight on how much effort is going into that cloud. Native components in the public cloud. >>Well, I would say that the first thing is you have to go back to the applications to truly get that cloud native experience. I think HP is putting the components together to a prize. This to be able to capitalize on that cloud like experience with cloud native APS. But the vast majority of enterprise app they're not cloud native. And so I think the way that I'm interpreting Green Lake and I think there are a lot of questions Greenland and how it's consumed by enterprises there. There was some initial questions around the branding when it first came out. Um, and so you know it's not perfect. I think HP definitely have some work to do to clarify what it is and what it isn't in a way that enterprises can understand. But from what I'm seeing, it looks to be creating and a cloud like experience for enterprises from edge to cloud, but also providing the components so that if you do have applications that are shovel ready for cloud or our cloud native, you can embrace Public Cloud as well as private cloud and pull them under the Green Lake >>Rela. Yeah, ostensibly stew kubernetes is part of the answer to that, although you know, as we've talked about, Kubernetes is necessary containers and necessary but not sufficient for that experience. And I guess the point I'm getting to is, you know we do. We've talked about this with Red Hat, certainly with VM Ware and others the opportunity to have that experience across clouds at the Edge on Prim. That's expensive from an R and D standpoint. And so I want to kind of bring that into the discussion. HP last year spent about 1.8 billion in R and D Sounds like a lot of money. It's about 6% of its of it's revenues, but it's it's spread thin now. It does are indeed through investments, for instance, like Pensando or other acquisitions. But in terms of organic R and D, you know, it's it's it's not at the top of the heap. I mean, obviously guys like Amazon and Google have surpassed them. I've written about this with regard to IBM because they, like HP, spend a lot on dividends on share buybacks, which they have to do to prop up the stock price and placate Wall Street. But it But it detracts from their ability to fund R and d student your take on that sort of innovation roadmap for the next decade. >>Yeah, I mean, one of the things we look at it in the last year or so there's been what we were talking about earlier, that management across these environments and kubernetes is a piece of it. So, you know, Google laid down and those you've got Microsoft with Azure, our VM ware with EMS. Ooh! And to Tim's point, you know, it feels like Green Lake fits kind of in that category, but there's there's pieces that fall outside of it. So, you know, when I first thought of Green Lake, it was Oh, well, I've got a private cloud stack like an azure stack is one of the solutions that they have there. How does that tie into that full solution? So extending that out, moving that brand I do here, you know good things from the field, the partners and customers. Green Lake is well respected, and it feels like that is, that is a big growth. So it's HB 50 from being more thought of, as you know, a box seller to more of that solution in subscription model. Green Lake is a vehicle for that. And as you pointed out, you know, rightfully so. Software so important. And I feel when that thing I'd say HPI ee feels toe have more embracing of software than, say, they're closest competitors. Which is Dell, which, you know, Dell Statement is always to be the leading infrastructure writer, and the arm of VM Ware is their software. So, you know, just Dell alone without VM ware, HP has to be that full solution of what Dell and VM ware together. >>Yeah, and VM Ware Is that the crown jewel? And of course, HP doesn't have a VM ware, but it does have over 8000 software engineers. Now I want to ask you about open source. I mean, I would hope that they're allocating a large portion of those software engineers. The open source development developing tooling at the edge, developing tooling from multi cloud certainly building hooks in from their hardware. But is HP Tim doing enough in open source? >>Well, I don't want to get on the open source bandwagon, and I don't necessarily want to jump off it. I think the important thing here is that there are places where open source makes sense in places where it doesn't, um, and you have to look at each particular scenario and really kind of ask yourself, does it make sense to address it here? I mean, it's a way to to engage your developers and engage your customers in a different mode. What I see from HP E is more of a focus around trying to determine where can we provide the greatest value for our customers, which, frankly, is where their focus should be, whether that shows up in open source for software, whether that shows up in commercial products. Um, we'll see how that plays out. But I think the one thing that I give HP e props on one of several things I would say is that they are kind of getting back to their roots and saying, Look, we're an infrastructure company, that is what we do really well We're not trying to be everything to everyone. And so let's try and figure out what are customers asking for? How do we step through that? I think this is actually one of the challenges that Antonio's predecessors had was that they tried to do jump into all the different areas, you know, cloud software. And they were really X over, extending themselves in ways that they probably should. But they were doing it in ways that really didn't speak to their four, and they weren't connecting those dots. They weren't connecting that that connective tissue they needed to dio. So I do think that, you know, whether it's open source or commercial software, we'll see how that plays out. Um, but I'm glad to see that they are stepping back and saying Okay, let's be mindful about how we ease into this >>well, so the reason I bring up open source is because I think it's the mainspring of innovation in the industry on that, but of course it's very tough to make money, but we've talked a lot about H B's strength since breath is, we haven't talked much about servers, but they're strong in servers. That's fine We don't need to spend time there. It's culture. It seems to be getting back to some of its roots. We've touched on some of its its weaknesses and maybe gaps. But I want to talk about the opportunities, and there's a huge opportunity to the edge. David Flores quantified. He says that Tam is four. Trillion is enormous, but here's my question is the edge Right now we're seeing from companies like HP and Dell. Is there largely taking Intel based servers, kind of making a new form factor and putting them out on the edge? Is that the right approach? Will there be an emergence of alternative processors? Whether it's our maybe, maybe there's some NVIDIA in there and just a whole new architecture for the edge to authority. Throw it out to you first, get Tim Scott thoughts. >>Yeah, So what? One thing, Dave, You know, HP does have a long history of partnering with a lot of those solutions. So you see NVIDIA up on stage when you think about Moonshot and the machine and some of the other platforms that they felt they've looked at alternative options. So, you know, I know from Wicky Bon standpoint, you know, David Foyer wrote the piece. That arm is a huge opportunity at the edge there. And you would think that HP would be one of the companies that would be fast to embrace that >>Well, that's why I might like like Moonshot. I think that was probably ahead of its time. But the whole notion of you know, a very slim form factor that can pop in and pop out. You know, different alternative processor architecture is very efficient, potentially at the edge. Maybe that's got got potential. But do you have any thoughts on this? I mean, I know it's kind of Yeah, any hardware is, but, >>well, it is a little hardware, but I think you have to come back to the applicability of it. I mean, if you're taking a slim down ruggedized server and trying Teoh essentially take out, take off all the fancy pieces and just get to the core of it and call that your edge. I think you've missed a huge opportunity beyond that. So what happens with the processing that might be in camera or in a robot or in an inch device? These are custom silicon custom processors custom demand that you can't pull back to a server for everything you have to be able to to extend it even further. And, you know, if I compare and contrast for a minute, I think some of the vendors that are looking at Hey, our definition of edge is a laptop or it is this smaller form factor server. I think they're incredibly limiting themselves. I think there is a great opportunity beyond that, and we'll see more of those kind of crop up, because the reality is the applicability of how Edge gets used is we do data collection and data analysis in the device at the device. So whether it's a camera, whether it's ah, robot, there's processing that happens within that device. Now some of that might come back to an intermediate area, and that intermediate area might be one of these smaller form factor devices, like a server for a demo. But it might not be. It might be a custom type of device that's needed in a remote location, and then from there you might get back to that smaller form factor. Do you have all of these stages and data and processing is getting done at each of these stages as more and more resources are made available. Because there are things around AI and ML that you could only do in cloud, you would not be able to do even in a smaller form factor at the edge. But there are some that you can do with the edge and you need to do at the edge, either for latency reasons or just response time. And so that's important to understand the applicability of this. It's not just a simple is saying, Hey, you know, we've got this edge to cloud portfolio and it's great and we've got the smaller servers. You have to kind of change the vernacular a little bit and look at the applicability of it and what people are actually doing >>with. I think those are great points. I think you're 100% right on. You are going to be doing AI influencing at the edge. The data of a lot of data is going to stay at the edge and I personally think and again David Floor is written about this, that it's going to require different architectures. It's not going to be the data center products thrown over to the edge or shrunk down. As you're saying, That's maybe not the right approach, but something that's very efficient, very low cost of when you think about autonomous vehicles. They could have, you know, quote unquote servers in there. They certainly have compute in there. That could be, you know, 2344 $5000 worth of value. And I think that's an opportunity. I'd love to see HP Dell, others really invest in R and D, and this is a new architecture and build that out really infuse ai at the edge. Last last question, guys, we're running out of time. One of the things I'll start with you. Still what things you're gonna watch for HP as indicators of success of innovation in the coming decade. As we said last decade, kind of painful for HP and HP. You know, this decade holds a lot of promise. One of the things you're gonna be watching in terms of success indicators. >>So it's something we talked about earlier is how are they helping customers build new things, So a ws always focuses on builders. Microsoft talks a lot. I've heard somethin double last year's talk about building those new applications. So you know infrastructure is only there for the data, and the applications live on top of it. And if you mention Dave, there's a number of these acquisitions. HP has moved up the stack. Some eso those proof points on new ways of doing business. New ways of building new applications are what I'm looking for from HP, and it's robust ecosystem. >>Tim. Yeah, yeah, and I would just pick you back right on. What's do was saying is that this is a, you know, going back to the Moonshot goals. I mean, it's about as far away as HP ease, and HP is routes used to be and that that hardware space. But it's really changing business outcomes, changing business experiences and experiences for the customers of their customers. And so is far cord that that eight p e can get. I wouldn't expect them to get all the way there, although in conversations I am having with HP and with others that it seems like they are thinking about that. But they have to start moving in that direction. And that's actually something that when you start with the builder conversation like Microsoft has had, an Amazon has had Google's had and even Dell, to some degree has had. I think you missed the bigger picture, so I'm not saying exclude the builder conversation. But you have to put it in the right context because otherwise you get into this siloed mentality of right. We have solved one problem, one unique problem, and built this one unique solution. And we've got bigger issues to be able to address as enterprises, and that's going to involve a lot of different moving parts. And you need to know if you're a builder, you've it or even ah ah, hardware manufacturer. You've got to figure out, How does your piece fit into that bigger picture and you've got to connect those dots very, very quickly. And that's one of the things I'll be looking for. HP as well is how they take this new software initiative and really carry it forward. I'm really encouraged by what I'm seeing. But of course the future could hold something completely different. We thought 2020 would look very different six months ago or a year ago than it does today. >>Well, I wanna I want to pick up on that, I think I would add, and I agree with you. I'm really gonna be looking for innovation. Can h P e e get back to kind of its roots? Remember, H B's router invents it was in the logo. I can't translate its R and D into innovation. To me, it's all about innovation. And I think you know cios like Antonio Neri, Michael Dell, Arvind Krishna. They got a They have a tough, tough position because they're on the one hand, they're throwing off cash, and they can continue Teoh to bump along and, you know, placate Wall Street, give back dividends and share buybacks. And and that's fine. And everybody would be kind of happy. But I'll point out that Amazon in 2007 spent spend less than a $1,000,000,000 in R and D. Google spent about the back, then about the same amount of each B E spends today. So the point is, if the edge is really such a huge opportunity, this $4 trillion tam is David Foyer points out, there's a There's a way in which some of these infrastructure companies could actually pull a kind of mini Microsoft and reinvent themselves in a way that could lead to massive shareholder returns. But it was really will take bold vision and a brave leader to actually make that happen. So that's one of things I'm gonna be watching very closely hp invent turn r and D into dollars. And so you guys really appreciate you coming on the Cube and breaking down the segment for ah, the future of HP be well, and, uh and thanks very much. Alright. And thank you for watching everybody. This is Dave Volante for Tim Crawford and Stupid men. Our coverage of HP ease 2020 Virtual experience. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah.

>>live from Boston, Massachusetts. It's the Q covering I. F s World Conference 2019. Brought to you by I. F s. >>Welcome back to I f s world Everybody, This is David Dante with Paul Dillon and you're watching the Cube, The leader in live tech coverage. Where here from? From the Heinz Auditorium. Nick Ward is here. He's the head of OM Digital Solutions for Rolls Royce and Scott Helmer, president of the F S aerospace and defense. Gentlemen, welcome to the Cube. Thanks for coming on. Thank you. Scott. I want to start with you. We heard a lot about digital transformation. You guys are in the heart of that. Ah, defense. Aerospace is one of those industries that hasn't been dramatically disrupted. Like publishing. Are you seeing taxis? It's a It's a high risk business. It's one that's highly in trench, but it's not safe from disruption. What are the major trends that you're seeing in your space and paint a picture for us? If you would, >>uh, that's a very good question. You're right. The same level of disruption related digital transformation has not yet common aerospace. Defense is that has come to some of the other league leading industries. But this is a whether it's land based operations, naval operations or aircraft operations. This is an asset intensive industry. It's characterized by a very connected network of organizations. Be the manufacturer's operators, subsystem, part suppliers or just maintainers. They stay connected throughout the asset life cycle in its entirety. I f F f s has a portfolio capability. There's four purpose underpinning the critical business processes of those organizations that enables us to be the digital thread to continue the connection of those organizations throughout that outs of life cycle, if you will, that sees this fall come to come to be at the heart of asset lifecycle Management on provides us with the opportunity to inform information insights for our customers. Like return on experience data on aircraft engines where an old GM like Rolls Royce, for example, can harvest that data to analyze the performance of those assets and ultimately optimized thereafter after service offerings. >>Who are the customers? I mean, there's a limited number of companies that make aircraft engines so you don't have a huge domain been numbers of those kinds of companies. But are the customers channel their partners the supply chain network >>Well, the ecosystem is actually large and extensive. They're very recognizable names, and it's certainly an industry that's characterized by significant growth. On the commercial side. Amaro continue is in the midst of a boom and is likely to continue to grow, are expected to continue to grow for at least another decorate decade. And on the defense side, we see military budgets continue or increasingly moving towards sustainment and serve it ization on a performance basis. So the number of organizations that are participating in that value chain whether they're just the upstream, only am so I should just upstream. But the Austrian Williams participate in the design and development are moving into the aftermarket sustainment and service support parts and subsystem supply, or ultimately, third part repair organizations. It's actually quite an extensive network participating in that asset life cycle. >>So, Nick, you know people here Rolls Royce, they think you know the iconic brand. We're gonna talk about cars, talk about your role at Rolls Royce and what's going on in your business. >>So my role I lead our product management function looking are digitally enabled. Service's so for 20 years we've been running a service we call total care. Total care is like a fixed dollar rate. Every time an aircraft flies, we paid a dollar rate for it. Flying. What's really great about that is we're incentivizing. No, I am exactly the same way that airline isn't said device. Keep the aircraft flying. It owns revenue for the airline. It owns revenue for us on that revolutionized relationship between oh am on operator. So within my role, it's about taking four division we call The Intelligent Engine. Intelligent Engine is recognizing the way that digital is starting to pervade the way we think about service is so we've talked about physical engine, big rotating piece of metal that people see service. Is that wrap around that on the digital brain that sits behind all of those sources? That's what we call the intelligent engine. >>Yes, so people sometimes think the mission critic critical piece of air travel is the reservation system. It's not. It's the thinness of the engines available that was lost in critical system, right? You mean like it? If you don't get your reservation Oh, well, somebody else will get it. Not not the end of the world But for the maintenance piece, that's all right. >>Job. You know, our fundamental mission is every rose was powered. Aircraft flies on time every time. All right, there's no disruption. There's no delay that works for the operator, for the airlines are owner of the aircraft. It works for us. And this is why the confluence of our incentives comes together and it really works well. >>So what role has technology played in terms of evolving that that experience? I mean, I'm sure, you know, years ago, it used to be a lot of tribal knowledge. Gut feel. Joe the mechanic really knew his stuff. Etcetera, etcetera, Powers. Technology evolved and changed your your business. >>So you had to go back to the business model, right? So technology should follow. The business model business model is fundamental risk transfer. So we take the risk off cost, fluctuation, availability, whatever it is away from the airline and we take it on to us is the Obama's Rolls Royce said the money's at risk. You gotta get really good forecasting. Four. Custom becomes your core skill almost because you've got to understand all the risk drivers understand how to optimize him, understand out of work around that in order to have a successful business. And you can't forecast without data without digital twins without all I ot and cloud and all the while the enablers allow you to sort of new to new generations of capability. >>So you're forecasting what probability of, ah, component failure, the life of ah, failure. How long it takes to bring stuff back on sure >>cost really on three different levels. So we do an engine forecast which is looking at the health of the life of the components in the engine, looking for any reasons why the engine might be forced off the wing. We're looking at a fleet level. So we're looking at all of the things that might affect the global fleet in terms of maintenance demands need for overhaul of those such things. And we forecast that out after 30 years, really accurately, as an engine leaves the factory, we know pretty much within 90 something percent everything that engine is going to require from the maintenance 20 to 30 years and then a network level. We're forecasting the capacity demand that we then need to meet within our maintenance shops globally. >>Well, He's obviously Paul. Been progress, right? We used to fly with very common four engine plains across the pond right now. Two engines. In fact, you don't want to fly in the four engine to engine more reliable. >>You've You've been a Rolls Royce for over 15 years. What have you seen as a result of all this technology is predicted maintenance technology. What impact is that? Had on equipment of reliability on life cycle on fuel efficiency. >>Huge, huge. I think if you don't have the data and you don't have the digital twin kind of capability behind you, you have to treat every engine like it's the worst engine in the fleet because you don't have the data tell you it isn't right. So everything is treated extremely extreme conservatism. If you have the data and you have the models and you have everything else around you, you treat engines, individuals. They have individual histories, individual configuration, individual experiences. Because of individuals. You tailor your maintenance intervention to keep that engine flying as long as you can on, you don't have to be his conservative. You can weed that conservatism out of the process, and that means it stays on wing 40 50% longer. It's flying for the airline that much longer. Revenues. Passengers are flying. There's less disruption. >>So what do you What do you do with my f s? What's the what's >>So Because we created this intelligent engine kind of next generation leap forward in that capability, we need data. So we have, ah, program we call the Blue Data Threat. The blue data traded in a global initiative that we're rolling through all of our 200 plus airline customers. How do we form a win win transaction with the airlines? Give us better data will make smarter decisions. You'll see less disruption, more availability. We'll share our data. Back with you is an operator. So this is a very simple, very nice cashless transactions. So with my intern X, because we share a number of customers, Scott has got a number of airline customers. Big airline customers were operating the maintenance system. What way do together? Is reform a plug in? It's like for us. We can go to an airline, and we can say you have total care inside to borrow an intel phrase. So he complied into the rosary service is seamlessly automated. The data can flow very little burden or effort on to the I t group of the outline. The data flows into our organization. We do what we do when we can push our date again back into the airline systems with updated form, their availability >>so key to that key to that value, Jane is obviously that common customer base. But critical to the work that Rolls Royce stuns does is the accuracy and reliability of the data They get to inform their own performance analysis and maintenance, availability information and the eye if it's made installed. Base leverage is a very rich data from the return on experience of the engine utilization that Nick and is able to use this part of the Blue data threat offering back to their customers. And together we're able to deliver unprecedented levels of value to airline customers and optimizing the availability of their assets. >>Nick, have you? Are you finding new ways to monetize this data beyond just improving the customer experience, a bond with your customers or their new revenue avenues >>for you? So I think within this is absolutely key that everybody within this transaction recognizes this is this is not a revenue opportunity for Rosa. This is a cashless transactions because there's a lot of sensitivity that data belongs to the airline, right? So you have to be very clear and open. That data is driving Rolls Royce to make internal improvements, so we will save a little bit on our bottom line of delivering the service's they've already bought in order to get better. Outcomes of those service is so It's a little early for the service. You were thinking about >>this a little bit like security. In that sense, you know of bad guys are trying to get there. So So the good guys to share data. It's a cashless transaction, and everybody we >>believe is a market collaboration on data is got to be the way Ford's >>Scott could. You double click on the Ecosystem and A and D, obviously different from the sort of core traditional you know, e r. P world. The importance of the ecosystem may be what it looks like, described the >>That's an insightful question, Dave, certainly the partner ecosystem in inner space and defense is somewhat differentiated. I don't want to go so far as to say that it's unique, but it's somewhat differentiated from Corey RPS. As you duly noted partner, our four persecuted for four purpose capability around the critical process is for manufacturers. Maintainers on, uh, parts and subsystem supply organizations is all the potential, and it's a promise. But that value can only be realized to the collaboration with partners who doom or an aerospace and defense and just support delivery and implementation capability. They provide value added service is around business process, reengineering, change, enablement as well as their partners and co innovation as well. Certainly the collaboration we have with Rolls Royce is certainly a new level of collaboration around innovation that hasn't been seen before. So those partners are critical to our ability to deliver that value to our customers. Secondarily, we have our partners are actually a route to market in the traditional sense of referral system like you would see in Corriere P. But more importantly, as an indirect route to market as channels to their end customers, almost I s v ng. Our capability to support the delivery of service is to their customers. >>So it's the it's the manufacturers of the Plains, For example, it's the airlines themselves. It's manufactured the engine defectors, >>the maintainers. So the M R organizations that do the work around repair, and it's the entire ecosystem of organizations to support the supply chain. Our partners are both in themselves as well as partners in delivering the capability to those organizing. >>And it's a data pipeline throughout that value chain a digital thread that you guys actually have visibility on, correct your value. Add to the and >>we have the opportunity to play a vital role between within that equal system in allowing and enabling the connective ity of that network between Williams and their customers between the operators and their maintainers. For example, we've got a collaboration with an airline right now where we're going to connect them directly with the third party organizations that they rely on for airframe repair. For example, >>I want to ask you about the aerospace business it used to be that used to be a very small market in terms of the number of customers. Now we've got Space X. We've got the private areas, three private aerospace companies. We've got different countries now. India, China getting involved. What impact is that having on your business. >>Certainly we're seeing the emergence of spatial program's playing a taking up a larger share of off of government or public sector budgets. And people are beginning to think about how to leverage or harvest the value from utilization of spatial assets and again are enabling capability. To be a collector of that data and supply it back as an information in sight to those were reliant on the data that is collected is a vital role that we play in that ecosystem. >>So when I was when you were describing the ecosystem value chain, it strikes me that there's there's clearly a whole lot of metrics going on. Are there new levers, new metrics, emerging new levers that you can pull to really drive a flywheel effect in the industry? One of the key key performance indicators that you're really trying to optimize visiting? This is >>Certainly this is certainly an industry that characterizes as an intensive, complex mobile and in this case complex in mobile or a pseudonym for very expensive assets. So everything around availability, reliability are all key drivers are performance indicators of our customers ability to realise the value from those assets and our role in that is to provide them with the information inside to be able to make optimal decisions to maximize that availability. >>Anything you dad, >>I think in this day and age things like technical dispatcher alive. Relative engines is so high, high 99 sort of percentage. You have to start focusing on things like the maintenance costs to achieve that. Driving your maintenance costs down, but still retaining your really high availability. That becomes a really interesting balance. You could have under percent of relevancy. What it's gonna cost a fortune. You don't want that. >>Well, gentlemen, thanks so much for coming on. The cute, really fascinating discussion. Thank you. Great to have you. All right, you're welcome. And keep it right there, buddy. Paul Gill on day Volante from I F s World in Boston. You're watching the Cube right back Right after this short break

from our studios in the heart of Silicon Valley Palo Alto California this is a cute conversation hi and welcome to the cube Studios for another cube conversation where we go in-depth with thought leaders driving innovation across the tech industry I'm your host Peter Burris AI is on the forefront of every board in every enterprise on a global basis as well as machine learning deep learning and other advanced technologies that are intended to turn data into business action that differentiates the business leads to more revenue leads to more profitability but the challenge is is that all of these new use cases are not able to be addressed with the traditional ways that we've set up the workflows that we've set up to address them so as a consequence we're going to need greater opera's the operationalization of how we translate business problems into ml and related technology solutions big challenge we've got a great guest today to talk about it non-division diof is a distinguished technologist and lead data scientists at HPE in the blue data team nonde welcome to the cube thank you happy to be here so ananda let's start with this notion of a need for an architected approach to how we think about matching AI ml technology to operations so that we get more certain results better outcomes more understanding of where we're going and how the technology is working within the business absolutely yeah ai and doing AI in an enterprise is not new there have been enterprise-grade tools in the space before but most of them have a very prescribed way of doing things sometimes you use custom sequel to use that particular tool or the way you present data to that tool requires some level of pre-processing which makes you copy the data into the tool so you have already data fidelity maybe at risk and you have a data duplication happening and then the scale right when you talk about doing AI at the scale that is required now considering data is so big and there is a variety of data sets for the scale it can probably be done but there is a huge cost associated with that and you may still not meet the variety of use cases that you want to actually work on so the problem now is to make sure that you empower your users who are working in the space and augment them with the right set of technologies and the ability to bring data in a timely manner for them to work on these solutions so it sounds as though what we're trying to do is simplify the process of taking great ideas and turn it into great outcomes but you mentioned users I think it's got to start with or let me ask you if we have to start here that we've always thought about how is going to center in the data science or the data scientist as these solutions have start to become more popularized if diffused across the industry a lot more people are engaging are all roles being served as well as you need to be absolutely I think that's the biggest challenge right in the past you know when we talk about very prescribed solutions end to end was happening within those tools so the different user persona were probably part of that particular solution and also the way these models came into production which is really making it available for a consumer is read coding or redeveloping this in technologies that were production friendly which is you're rewriting that and sequel you're recording that and C so there is a lot of details that are lost in translation and the third big problem was really having visibility or having a say from a developer's point of view or a data scientist point of view in how these things are performing in production that how do you actually take it back take that feedback back into deciding you know is this model still good or how do you retrain so when you look at this lifecycle holistically this is an iterative process it is no longer you know workflow where you hand things off this is not a water flow methodology anymore this is a very very continuous and iterative process especially in the New Age data science the tools that are developing where you build the model that developer decides what the run time is and the run times are capable of serving those models as is you don't have to recode you don't have to lose things during translation so with this back to your question of how do you serve two different roles now all those personas and all those roles have to be part of the same project and they have to be part of the same experiment they're just serving different parts of the lifecycle and now you've whatever tooling you provide or whatever architecture technologies you provide have to look at it holistically there has to be continuous development there has to be collaboration there has to be central repositories that actually cater to those needs so each so the architected approach needs to be able to serve each of the roles but in a way that is collaborative and is ultimately put in service to the outcome and driving the use of the technology forward well that leads to another question should it should the should this architected approach be tied to one or another set of algorithms or one or another set of implementation infrastructure or does it have to be able to serve a wide array of Technology types yeah great question right this is a living ecosystem we can no longer build for you know you plant something for the next two years or the next three years technologies are coming every day and the reason is because the types of use cases are evolving and what you need to solve that use case is completely different when you look at two different use cases so whatever standards you come up with you know the consistency has to be across how a user is on-boarded into the system a consistency has to be about data access about security about how does one provision these environments but as far as what tool is used or how is that tool being applied to a specific problem there's a lot of variability in there and it has to cater your architecture has to make sure that this variability is addressed and it is growing so HPE spends a lot of time with customers and you're learning from your customer successes and how you turn that into tooling that leads to this type of operator operationalization but give us some visibility into some of those successes that really stand out for you that have been essential to how HP has participated in this journey to create better tools for better AI and m/l absolutely you know traditionally with blue data HPE now you know we've been exposed to a lot of big data processing technologies where the current landscape the data is different data is not always at rest data is not structured you know data is coming it could be a stream of data it could be a picture and in the use cases like we talked about you know it could be image recognition or a voice recognition where the type of data is very different right so back to how we've learnt from our customers like in my role I talked to you know tens of customers on a daily or weekly basis and each one of them are at a different level of maturity in their life cycle and these are some very established customers but you know the various groups that are adopting this new age technologies even within an organization there is a lot of variability so whatever we offered them we have to help support all of that particular user groups there are some who are coming from the classic or language background there are some that are coming from Python background some are doing things in Scala someone doing things in SPARC and there are some commercial tools that they're using like h2o driverless AI or data iku so what we have to look at is in this life cycle we have to make sure that all these communities are represented and/or addressed and if they build a model in a specific technology how do we consume that how do we take it in then how do we deploy that from an end to point of view it doesn't matter where a model gets built it does matter how end-users access it it doesn't matter how security is applied to it it does matter how scaling is applied to it so really there is a lot of consistency is required in the operationalization and also in how you onboard those different tools how do you make sure that consistency or methodology or standard practices are applied in this entire lifecycle and also monitoring that's a huge aspect right when you have deployed a model and it's in production monitoring means two different things to people where is it even available you know when you go to a website when you click on something is a website available very similarly when you go to an endpoint or you're scoring against a model is that model available do you have enough resources can it scale depending on how much requests come in that's one aspect of monitoring and the second aspect is really how was the model performing you know is that what is the accuracy what is the drift when is it time to retrain so you no longer have the luxury to look at these things in isolation right so it we want to make sure that all these things can be addressed in a manner knowing that this iteration sometimes can be a month sometimes it can be a day sometimes it's probably a few hours and that is why it can no longer be an isolated and even infrastructure point of view some of these workloads may need things like GPU and you may need it for a very short amount of time let how do you make sure that you give what is needed for that duration that is required and take it back and assign it to something else because these are very valuable resources so I want to build on if I may on that notion of onboarding the tools we're talking about use cases that enterprises are using today to create business value we're talking about HPE as an example delivering tooling that operationalize is how that's done today but the reality is we're gonna see the state of the art still evolve pretty dramatically over the next few years how is HPE going about ensuring that your approach and the approach you working with your customers does not get balkanized does not get you know sclerotic that it's capable of evolving and changing as folks learn new approaches to doing things absolutely you know it this has to start with having an open architecture you know you have to there has to be standards without which enterprises can't run but at the same time those standards shouldn't be so constricting that it doesn't allow you to expand into newer use cases right so what HP EML ops offers is really making sure that you can do what you do today in a best-practice manner or in the most efficient manner bringing time to value you know making sure that there is you know instant provisioning or access to beta or making sure that you don't duplicate data compute storage separation containerization you know these are some of the standard best practice technologies that are out there making sure that you adopt those and what these sets users for is to make sure that they can evolve with the later use cases you can never have you know you can never have things you know frozen in time you just want to make sure that you can evolve and this is what it sets them up for and you evolve with different use cases and different tools as they come along nada thanks very much has been a very it's been a great conversation we appreciate you being on the cube thank you Peter so my guest has been non Division I of the distinguished technologists and lead data scientists at HPE blue data and for all of you thanks for joining us again for another cube conversation on Peter burst see you next time you [Music]

all right we opening tight on Dave in five four three we're back with Patrick Osbourne right Patrick let's let's wrap up here and summarize we heard how you gonna help data science teams right yep speed agility time to value all right and and I know a bunch of folks at blue data the tech is the engineering team is very very strong so you picked up a good asset there yeah it means amazing technology the founders have a long lineage of software development and an adoption in the market so we're just gonna we're gonna invested them and let them loose and then we heard they're sort of better together story from you you got a you got a roadmap you're making some investments here yeah I mean so for really focused on hybrid cloud and we want to have all these as a services experience whether it's through Green Lake or providing innovation AI GPUs as a service is something that we're gonna be you know continuing to provide our customers as we move along okay and then we heard the data science angle and the data science community and the partner angle that's that's exciting yeah I mean it's it's I think it's two approaches as well to we have data scientists right so we're gonna bring that capability to bear whether it's through the product experience or through our professional services organization and then number two you know this is a very dynamic ecosystem from an application standpoint there's commercial applications there's certainly open source and we're gonna bring a fully vetted full stack experience for our customers that they can feel confident in this you know it's a very dynamic space excel well thank you very much thank you all right now it's your turn go into the crowd chat and start talking ask questions we're gonna have polls we've got experts in there so let's crouch at clear too

>> Announcer: Live from Midtown Manhattan. It's the CUBE. Covering Big Data New York City 2017. Brought to you by Silicon Angle Media and its ecosystem sponsor. (electronic music) >> Hey, welcome back everyone, live here in New York. This is the CUBE here in Manhattan for Big Data NYC's three days of coverage. We're one day three, things are starting to settle in, starting to see the patterns out there. I'll say it's Big Data week here, in conjunction with Hadoop World, formerly known as Strata Conference, Strata-Hadoop, Strata-Data, soon to be Strata-AI, soon to be Strata-IOT. Big Data, Mike Maccaux who's the Global Big Data Practice Lead at Dell EMC. We've been in this world now for multiple years and, well, what a riot it's been. >> Yeah, it has. It's been really interesting as the organizations have gone from their legacy systems, they have been modernizing. And we've sort of seen Big Data 1.0 a couple years ago. Big Data 2.0 and now we're moving on sort of the what's next? >> Yeah. >> And it's interesting because the Big Data space has really lagged the application space. You talk about microservices-based applications, and deploying in the cloud and stateless things. The data technologies and the data space has not quite caught up. The technology's there, but the thinking around it, and the deployment of those, it seems to be a slower, more methodical process. And so what we're seeing in a lot of enterprises is that the ones that got in early, have built out capabilities, are now looking for that, how do we get to the next level? How do we provide self-service? How do we enable our data scientists to be more productive within the enterprise, right? If you're a startup, it's easy, right? You're somewhere in the public cloud, you're using cloud based API, it's all fine. But if you're an enterprise, with the inertia of those legacy systems and governance and controls, it's a different problem to solve for. >> Let's just face it. We'll just call a spade a spade. Total cost of ownership was out of control. Hadoop was great, but it was built for something that tried to be something else as it evolved. And that's good also, because we need to decentralize and democratize the incumbent big data warehouse stuff. But let's face it, Hadoop is not the game anymore, it's everything else. >> Right, yep. >> Around it so, we've seen that, that's a couple years old. It's about business value right now. That seems to be the big thing. The separation between the players that can deliver value for the customers. >> Matt: Yep. >> And show a little bit of headroom for future AI things, they've seen that. And have the cloud on premise play. >> Yep. >> Right now, to me, that's the call here. What do you, do you agree? >> I absolutely see it. It's funny, you talk to organizations and they say, "We're going cloud, we're doing cloud." Well what does that mean? Can you even put your data in the cloud? Are you allowed to? How are you going to manage that? How are you going to govern that? How are you going to secure that? So many organizations, once they've asked those questions, they've realized, maybe we should start with the model of cloud on premise. And figure out what works and what doesn't. How do users actually want to self serve? What do we templatize for them? And what do we give them the freedom to do themselves? >> Yeah. >> And they sort of get their sea legs with that, and then we look at sort of a hybrid cloud model. How do we be able to span on premise, off premise, whatever your public cloud is, in a seamless way? Because we don't want to end up with the same thing that we had with mainframes decades ago, where it was, IBM had the best, it was the fastest, it was the most efficient, it was the new paradigm. And then 10 years later, organizations realized they were locked in, there was different technology. The same thing's true if you go cloud native. You're sort of locked in. So how do you be cloud agnostic? >> How do you get locked in a cloud native? You mean with Amazon? >> Or any of them, right? >> Okay. >> So they all have their own APIs that are really good for doing certain things. So Google's TensorFlow happens to be very good. >> Yeah. Amazon EMR. >> But you build applications that are using those native APIS, you're sort of locked. And maybe you want to switch to something else. How do you do that? So the idea is to-- >> That's why Kubernetes is so important, right now. That's a very key workload and orchestration container-based system. >> That's right, so we believe that containerization of workloads that you can define in one place, and deploy anywhere is the path forward, right? Deploy 'em on prem, deploy 'em in a private cloud, public cloud, it doesn't matter the infrastructure. Infrastructure's irrelevant. Just like Hadoop is sort of not that important anymore. >> So let me get your reaction on this. >> Yeah. So Dell EMC, so you guys have actually been a supplier. They've been the leading supplier, and now with Dell EMC across the portfolio of everything. From Dell computers, servers and what not, to storage, EMC's run the table on that for many generations. Yeah, there's people nippin' at your heels like Pure, okay that's fine. >> Sure. It's still storage is storage. You got to store the data somewhere, so storage will always be around. Here's what I heard from a CXO. This is the pattern I hear, but I'll just summarize it in one conversation. And then you can give a reaction to it. John, my life is hell. I have application development investment plan, it's just boot up all these new developers. New dev ops guys. We're going to do open source, I got to build that out. I got that, trying to get dev ops going on. >> Yep. >> That's a huge initiative. I got the security team. I'm unbundling from my IT department, into a new, difference in a reporting to the board. And then I got all this data governance crap underneath here, and then I got IOT over the top, and I still don't know where my security holes are. >> Yep. And you want to sell me what? (Matt laughs) So that's the fear. >> That's right. >> Their plates are full. How do you guys help that scenario? You walk in, actually security's pretty much, important obviously you can see that. But how do you walk into that conversation? >> Yeah, it's sort of stop the madness, right? >> (laughs) That's right. >> And all of that matters-- >> No, but this is all critical. Every room in the house is on fire. >> It is. >> And I got to get my house in order, so your comment to me better not be hype. TensorFlow, don't give me this TensorFlow stuff. >> That's right. >> I want real deal. >> Right, I need, my guys are-- >> I love TensorFlow but, doesn't put the fire out. >> They just want spark, right? I need to speed up my-- >> John: All right, so how do you help me? >> So, what we'd do is, we want to complement and augment their existing capabilities with better ways of scaling their architecture. So let's help them containerize their big data workload so that they can deploy them anywhere. Let's help them define centralized security policies that can be defined once and enforced everywhere, so that now we have a way to automate the deployment of environments. And users can bring their own tools. They can bring their data from outside, but because we have intelligent centralized policies, we can enforce that. And so with our elastic data platform, we are doing that with partners in the industry, Blue Talent and Blue Data, they provide that capability on top of whatever the customer's infrastructure is. >> How important is it to you guys that Dell EMC are partnering. I know Michael Dell talks about it all the time, so I know it's important. But I want to hear your reaction. Down in the trenches, you're in the front lines, providing the value, pulling things together. Partnerships seem to be really important. Explain how you look at that, how you guys do your partners. You mentioned Blue Talent and Blue Data. >> That's right, well I'm in the consulting organization. So we are on the front lines. We are dealing with customers day in and day out. And they want us to help them solve their problems, not put more of our kit in their data centers, on their desktops. And so partnering is really key, and our job is to find where the problems are with our customers, and find the best tool for the best job. The right thing for the right workload. And you know what? If the customer says, "We're moving to Amazon," then Dell EMC might not sell any more compute infrastructure to that customer. They might, we might not, right? But it's our job to help them get there, and by partnering with organizations, we can help that seamless. And that strengthens the relationship, and they're going to purchase-- >> So you're saying that you will put the customer over Dell EMC? >> Well, the customer is number one to Dell EMC. Net promoter score is one of the most important metrics that we have-- >> Just want to make sure get on the record, and that's important, 'cause Amazon, and you know, we saw it in Net App. I've got to say, give Net App credit. They heard from customers early on that Amazon was important. They started building into Amazon support. So people saying, "Are you crazy?" VMware, everyone's saying, "Hey you capitulated "by going to Amazon." Turns out that that was a damn good move. >> That's right. >> For Kelsinger. >> Yep. >> Look at VM World. They're going to own the cloud service provider market as an arms dealer. >> Yep. >> I mean, you would have thought that a year ago, no way. And then when they did the deal, they said, >> We have really smart leadership in the organization. Obviously Michael is a brilliant man. And it sort of trickles on down. It's customer first, solve the customer's problems, build the relationship with them, and there will be other things that come, right? There will be other needs, other workloads. We do happen to have a private cloud solution with Virtustream. Some of these customers need that intermediary step, before they go full public, with a hosted private solution using a Virtustream. >> All right, so what's the, final question, so what's the number one thing you're working on right now with customers? What's the pattern? You got the stack rank, you're requests, your deliverables, where you spend your time. What's the top things you're working on? >> The top thing right now is scaling architectures. So getting organizations past, they've already got their first 20 use cases. They've already got lakes, they got pedabytes in there. How do we enable self service so that we can actually bring that business value back, as you mentioned. Bring that business value back by making those data scientists productive. That's number one. Number two is aligning that to overall strategy. So organizations want to monetize their data, but they don't really know what that means. And so, within a consulting practice, we help our customers define, and put a road map in place, to align that strategy to their goals, the policies, the security, the GDP, or the regulations. You have to marry the business and the technology together. You can't do either one in isolation. Or ultimately, you're not going to be efficient. >> All right, and just your take on Big Data NYC this year. What's going on in Manhattan this year? What's the big trend from your standpoint? That you could take away from this show besides it becoming a sprawl of you know, everyone just promoting their wares. I mean it's a big, hyped show that O'Reilly does, >> It is. >> But in general, what's the takeaway from the signal? >> It was good hearing from customers this year. Customer segments, I hope to see more of that in the future. Not all just vendors showing their wares. Hearing customers actually talk about the pain and the success that they've had. So the Barclay session where they went up and they talked about their entire journey. It was a packed room, standing room only. They described their journey. And I saw other banks walk up to them and say, "We're feeling the same thing." And this is a highly competitive financial services space. >> Yeah, we had Packsotta's customer on Standard Bank. They came off about their journey, and how they're wrangling automating. Automating's the big thing. Machine learning, automation, no doubt. If people aren't looking at that, they're dead in my mind. I mean, that's what I'm seeing. >> That's right. And you have to get your house in order before you can start doing the fancy gardening. >> John: Yeah. >> And organizations aspire to do the gardening, right? >> I couldn't agree more. You got to be able to drive the car, you got to know how to drive the car if you want to actually play in this game. But it's a good example, the house. Got to get the house in order. Rooms are on fire (laughs) right? Put the fires out, retrench. That's why private cloud's kicking ass right now. I'm telling you right now. Wikibon nailed it in their true private cloud survey. No other firm nailed this. They nailed it, and it went viral. And that is, private cloud is working and growing faster than some areas because the fact of the matter is, there's some bursting through the clouds, and great use cases in the cloud. But, >> Yep. >> People have to get the ops right on premise. >> Matt: That's right, yep. >> I'm not saying on premise is going to be the future. >> Not forever. >> I'm just saying that the stack and rack operational model is going cloud model. >> Yes. >> John: That's absolutely happening, that's growing. You agree? >> Absolutely, we completely, we see that pattern over and over and over again. And it's the Goldilocks problem. There's the organizations that say, "We're never going to go cloud." There's the organizations that say, "We're going to go full cloud." For big data workloads, I think there's an intermediary for the next couple years, while we figure out operating pulse. >> This evolution, what's fun about the market right now, and it's clear to me that, people who try to get a spot too early, there's too many diseconomies of scale. >> Yep. >> Let the evolution, Kubernetes looking good off the tee right now. Docker containers and containerization in general's happened. >> Yep. >> Happening, dev ops is going mainstream. >> Yep. >> So that's going to develop. While that's developing, you get your house in order, and certainly go to the cloud for bursting, and other green field opportunities. >> Sure. >> No doubt. >> But wait until everything's teed up. >> That's right, the right workload in the right place. >> I mean Amazon's got thousands of enterprises using the cloud. >> Yeah, absolutely. >> It's not like people aren't using the cloud. >> No, they're, yeah. >> It's not 100% yet. (laughs) >> And what's the workload, right? What data can you put there? Do you know what data you're putting there? How do you secure that? And how do you do that in a repeatable way. Yeah, and you think cloud's driving the big data market right now. That's what I was saying earlier. I was saying, I think that the cloud is the unsubtext of this show. >> It's enabling. I don't know if it's driving, but it's the enabling factor. It allows for that scale and speed. >> It accelerates. >> Yeah. >> It accelerates... >> That's a better word, accelerates. >> Accelerates that horizontally scalable. Mike, thanks for coming on the CUBE. Really appreciate it. More live action we're going to have some partners on with you guys. Next, stay with us. Live in Manhattan, this is the CUBE. (electronic music)