>> theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hey everyone, guys and gals, good to see you. It's theCUBE live in Barcelona at MWC23. Lisa Martin here with Dave Vellante on day one of four days of wall to wall CUBE coverage. Dave, today is ecosystem day. We've had some great conversations about why the open ecosystem is so important and some of the key players in it. >> Well and I'm in search of disruptors, so I'm looking for, okay, who are the network operators that are going to actually lean into the future and drive it and challenge the existing incumbents. We'll talk about that today. >> And we're going to be talking about that next. We've got one of our alumni back with us. Satish Iyer is here, the Vice President of Emerging Services at Dell. Great to have you back on the program. >> Thank you. >> Richard Leitao is with us as well, the Vice President of National Development at DISH Network. Welcome. >> Pleasure to be here. >> So, lots of, this is day one, the theme is velocity. I feel like the day has gone by so quickly. But Dell and DISH have partnered together on a multi-year initiative to build your nationwide cloud-native 5G network that's going to cover a lot of the US. Talk a little bit about that partnership, we'll get both of your perspectives. Richard, we'll start with you. >> Sure. So thank you again for having me. So DISH had the opportunity of, of going through this experience, of innovating once more. For the ones that know DISH, DISH is a company that was founded in 1980 by an innovator, a disruptor. Of course, in the course of the next 40 years, we had the opportunities of even disrupting ourselves. We launched our first satellite TV service. We then launched the first streaming, video streaming platform, disrupting our own satellite business. And since 2008, we have been acquiring Spectrum and, you know, Spectrum, the most valuable asset of a wireless operator. We felt that this was the right opportunity, having 5G , having O-RAN, and we decided to go full in in a greenfield project building national network, 5G O-RAN cloud-based network, one of a kind network in in the US and, and most of all, using O-RAN, it's very important to us, what, what it can bring and it can bring to DISH but to the entire ecosystem of, of this sector in the US. >> Satish, talk a little bit about the partnership from Dell's perspective and some of the unique advantages that Dell is delivering to DISH. >> Oh absolutely. Again, like Richard was saying, I mean the telecom network is being desegregated as we speak. You know, companies like DISH and everybody else is looking at what are the best-in-class technologies we can bring to the table. I would like to say that, you know, the cloud is coming to the telco world, right? A lot of us have seen the tremendous transformation in the cloud world in the last few years. Now, you know, DISH is a big enterprise company. As you know, you know, we are pretty strong within the cloud space and enterprise space. So what we try to work with DISH is Dell, is to bring to DISH is, you know, that notion of cloud scale and the cloud ecosystem into telecom, right? By means best-in-class infrastructure products, best-in-class software products, to allow somebody like DISH to innovate and incre, you know, basically expand and build their O-RAN network. So it's absolutely important for us as we build and get into the telecom space to work with somebody like DISH who's also disrupting as a carrier in that space. >> So it's early days for Open RAN but you've decided, "okay, we're all in". >> Yeah. >> Right? So (chuckling) you burn the bridge, as they say, "go for it". (Lisa chuckles) So when you talk to most people, they say, "okay, it's, it's, it's, it's immature." It's got to be able to get to the levels of, of the, the the hardened stack reliability. But of course it brings the advantage of flexibility and speed. Are you optimizing for one or the other right now? How are you dealing with that balance? >> Well, it, it's, it's not mature in the sense that most of operators that think about it, they have a legacy network. And in order to go full in on the O-RAN side, they need to scrap a lot of things that they have and honestly, they don't want, and it doesn't make sense. So being a greenfield operator, give us that advantage. Give us the advantage and, and desegregation, it's all about chip sets, boxes and software and the chip sets part and what I like the most in desegregation is the time of innovation. The time that we can use new chip sets coming into the market, the size of the boxes that we are using. Obviously our footprint onsite is much smaller than traditional carriers or proprietary systems. So all of that Dell has been critical in supporting us. Supporting us having the best chip sets, having the smallest footprint and, you know, the software, the cycle of innovation is much faster than in proprietary systems. So ma-, it's maturing. I'm glad to say that probably two years ago here O-RAN was more like a, a pilot type of technology. It is not, we are live, we are live for more than 30 million customers in the US and, you know, the performance levels are very similar to traditional networks. >> So you don't just buy a nationwide cloud-native 5G network out of the box, you got to- >> No, you don't. >> You got to build it. So I'm curious as to what Dell's role is in that, in that build out. >> Right? >> How and how, I'm really curious how to, how you would grade Dell but we'll get there. >> Yeah, I mean, look, yes, you don't. So I think the, the, the first and foremost is again, as, as we, Dell, comes into the telco space, one of the things we have to look at is to understand what makes Dell better in the enterprise space, right? It is the best-in-class infrastructure. It is the software ties together. As you talk about desegregated networks, it's important to understand lot of these piece parts have to still be touched together, right? So I think the integration and integration aspects becomes really key which is really Dell is very good at. So one of the things we are working really closely with DISH Tech, you know Richard was alluding to, is bringing all, not just bringing all the software and hardware assets together, but how do you continuously innovate and keep fixing things faster, right? So in the old days, traditional ways, you have a software stack, it takes you 18 months, 20 months to actually get an upgrade done. Here we have continuously CI/CD pipelines where if you want to a change done within, within a week's or within a few days, where we can actually go and test and make sure these things work. So I think a lot of the best enterprise software practices, cloud practices, combined with whatever needs for telco, actually is what makes it very unique. >> I, I saw that this started out as an FCC compliance initiative that turned into a partnership, obviously a very successful one. Richard, talk about what DISH saw in Dell that really made it the right choice, knowing you have choices, you have options. >> You know, we saw the capability to execute, but we also saw the capability to innovate. From an execution level, at the end of the day, like we were talking, we started the project in the middle of COVID, and we had the first mandate to cover 20% of the US population by June, 2022. And now we have a second one, 70% of US population by June 2023. At the beginning of the project, it was all about availability of materials, logistics, how to distribute, how to transport material. So Dell has a world-class supply chain, we felt that working with Dell through all these challenges made things easier. So from an execution perspective, whenever you need to build a network and you, you are building thousands of sites, you need to have materials, you need to distribute them and you need to install them. Dell helped us across the board. Our expectations obviously will change. We have a network, we want to cooperate with Dell in many other areas. We want to, you know, leverage on Dell ability to reach the enterprise market, to have private 5G offers. So hopefully this collaboration will endure in time and, and, you know, will change and evolve in time. >> And it's a big bet. I mean, it's not like a single, it's not like a little transaction that you guys are doing. I feel like, you know Michael Dell and Eric Carlson had dinner and they said, "okay, we're going to, we're going to partner up and this is going to be a multi-decade partnership. You had to be transparent, "Hey, we're new at this, even though we're really good at enterprise tech and so you're going to, obviously if you take a chance on us, here's what we promise you." >> Absolutely. >> And vice versa, you guys had to say, "all right, hey, we're willing to roll the dice because we're trying to change the world." So what was that dynamic like? I mean, how did, I'm curious as to this has to be a lot of different levels, engineering, senior management, board level discussions. >> You know, we felt a huge buy-in from Dell on the Open RAN concept. >> Right. >> Yeah, okay. >> And, you know, edge computing and, and the ability to get us the best product and evolve the best product, Intel is is critical in all these offerings. Intel has a great relationship with Dell. Dell helped us. Dell sponsored the DISH program and some of these suppliers, So it was definitely good to have their support and the buy-in on the O-RAN concept. We felt it from day one and we felt secure on that. >> Yeah, I mean, I, to add to that, I mean, you know DISH was very instrumental in driving, dictating and executing to our roadmap, right? They're one of the key, I mean, since they are out there and they're really turning in a way, it's important that a customer who's actually at the out front of innovation, helps us drive our own roadmap. So to Richard's point, a lot of our product roadmaps, in terms of what have you built and all that, was based on what DISH thinks as going to be market-based requirements. They also helped us a lot in the integration aspects. Like I said, one of the things about open desegregation of these networks is there is a lot of integration because, you know, there is, it's not a one, one monolithic pipe smokestack anymore. You are picking up best-in-class pieces, bits and pieces and tying it together. And it's important to understand when you tie it together things will go wrong, right? So there is a lot of learnings from an integration standpoint. Supportability, deployment, one of the things Richard talked about was supply chain, you know. Other Dell's ability to, lot of these deployments, a lot of these configs in the factory, right, in the second part. So especially a lot of these partnerships started during COVID time and as you all know, you know what we went through two years ago. So we had to make sure that lot of these things are done in one place and a factory, and not done in the field because we couldn't do a lot of these things. So there's a lot of, lot of experimentation, lot of, lot, lot of innovation on that. >> So it's 2030, what's this look like? What's the vision if we can work backwards from there? Well, a, a great network coverage to the entire country, bringing new services to enterprises, to verticals, bringing value add to customers and, you know, technology cycles, they are lasting much less than they were. I cannot even say what will happen in three years. 2030, I mean, I know, I know somebody has a vision for 2030. That's another thing. (everyone laughs) >> A lot of it is "build it and they will come", right? >> Yeah. >> I mean it really is right? You put that network in place and then innovation happens on top. That's the best thing. >> Yeah. And look and and I think the biggest people think about Open RAN in terms of cost, which, you know, you, you have some things in cost that you appreciate in Open RAN. The footprint, the the possibility to diversify suppliers and and have more competition. But for me, Open RAN is about innovation and cycles of innovation. I used to work for Nokia, I used to work for Alcatel. I knew from the generation of an idea to an execution and having a feature delivered to a certain customer, it, it took months. We want innovation to take weeks. We are innovating at the speed, speed of the cloud. We are cooperating with new players, players on the cloud and, and we expect things to happen much faster than they traditionally happen on the telecom sector. >> Move fast and break things. >> Well, we also expect that speed- >> Break and fix. (everyone laughs) >> Yeah, thank you for that. >> But speaking of speed, your customers expect that, right? They expect the service to be up 24/7. They expect to be able to access whatever content they want, whenever they want from wherever they are. So comment, Richard, in our last few minutes here of, of how the, the Dell partnership is helping DISH to really deliver the excellent customer experience that your customers just expect that you're going to deliver. >> Well by setting up the system, number one, we are leveraging on a number of services. And I mentioned the supply chain, but in reality Dell made much more than that for our 20% milestone and is supporting our 70% milestone by installing, testing, verifying most of our data center equipment. We found that this offering from Dell was really addressing some of our needs because, you know, we, we believe they know a lot in this area and they, they can provide the best advice and the best speed to market in, in terms of having this equipment. Because we are working on a time clock, we need to have this done as soon as possible. You know for the future, I hope that they can help us in driving more services. I hope they can bring all the infrastructure that we need to offer to our customers. And, you know, we keep committed to O-RAN. O-RAN is really important. We are not compromising that. And I think the future is bright for both of us. >> Yeah, and Dell learns from the experience. >> Exactly. >> Absolutely. >> There's got to be a catalyst for expanding your roadmap and vision in telecom. >> Yeah, I mean, like you said, I mean, you asked a 2030 question and I think that, you know, know six, seven years from now I think people should look at what DISH and Dell and say they were the trailblazers of make, bringing Open RAN to the market and making 5G a reality. I mean, you talk about 5G, but every 5G is on a different stages. I do think that this combination, this partnership has the best chance to be the first ones to actually have a truly Open RAN network to be successful in commercial. >> Awesome guys. Trailblazers, Dell and DISH. Well, we look forward to watching this story unfold. Thank you- >> Thank you. >> for joining Dave and me on the program today talking about what you're doing together. We appreciate it. >> Thanks for having us. >> Our pleasure. >> Thank you, bye. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE live from Barcelona at MWC23. We'll be back after a short break, so we'll see you soon.

>>We're back at Super Computing, 22 in Dallas, winding down the final day here. A big show floor behind me. Lots of excitement out there, wouldn't you say, Dave? Just >>Oh, it's crazy. I mean, any, any time you have NASA presentations going on and, and steampunk iterations of cooling systems that the, you know, it's, it's >>The greatest. I've been to hundreds of trade shows. I don't think I've ever seen NASA exhibiting at one like they are here. Dave Nicholson, my co-host. I'm Paul Gell, in which with us is Satish Ier. He is the vice president of emerging services at Dell Technologies and Satit, thanks for joining us on the cube. >>Thank you. Paul, >>What are emerging services? >>Emerging services are actually the growth areas for Dell. So it's telecom, it's cloud, it's edge. So we, we especially focus on all the growth vectors for, for the companies. >>And, and one of the key areas that comes under your jurisdiction is called apex. Now I'm sure there are people who don't know what Apex is. Can you just give us a quick definition? >>Absolutely. So Apex is actually Dells for a into cloud, and I manage the Apex services business. So this is our way of actually bringing cloud experience to our customers, OnPrem and in color. >>But, but it's not a cloud. I mean, you don't, you don't have a Dell cloud, right? It's, it's of infrastructure as >>A service. It's infrastructure and platform and solutions as a service. Yes, we don't have our own e of a public cloud, but we want to, you know, this is a multi-cloud world, so technically customers want to consume where they want to consume. So this is Dell's way of actually, you know, supporting a multi-cloud strategy for our customers. >>You, you mentioned something just ahead of us going on air. A great way to describe Apex, to contrast Apex with CapEx. There's no c there's no cash up front necessary. Yeah, I thought that was great. Explain that, explain that a little more. Well, >>I mean, you know, one, one of the main things about cloud is the consumption model, right? So customers would like to pay for what they consume, they would like to pay in a subscription. They would like to not prepay CapEx ahead of time. They want that economic option, right? So I think that's one of the key tenets for anything in cloud. So I think it's important for us to recognize that and think Apex is basically a way by which customers pay for what they consume, right? So that's a absolutely a key tenant for how, how we want to design Apex. So it's absolutely right. >>And, and among those services are high performance computing services. Now I was not familiar with that as an offering in the Apex line. What constitutes a high performance computing Apex service? >>Yeah, I mean, you know, I mean, this conference is great, like you said, you know, I, there's so many HPC and high performance computing folks here, but one of the things is, you know, fundamentally, if you look at high performance computing ecosystem, it is quite complex, right? And when you call it as an Apex HPC or Apex offering offer, it brings a lot of the cloud economics and cloud, you know, experience to the HPC offer. So fundamentally, it's about our ability for customers to pay for what they consume. It's where Dell takes a lot of the day to day management of the infrastructure on our own so that customers don't need to do the grunge work of managing it, and they can really focus on the actual workload, which actually they run on the CHPC ecosystem. So it, it is, it is high performance computing offer, but instead of them buying the infrastructure, running all of that by themself, we make it super easy for customers to consume and manage it across, you know, proven designs, which Dell always implements across these verticals. >>So what, what makes the high performance computing offering as opposed to, to a rack of powered servers? What do you add in to make it >>Hpc? Ah, that's a great question. So, I mean, you know, so this is a platform, right? So we are not just selling infrastructure by the drink. So we actually are fundamentally, it's based on, you know, we, we, we launch two validated designs, one for life science sales, one for manufacturing. So we actually know how these PPO work together, how they actually are validated design tested solution. And we also, it's a platform. So we actually integrate the softwares on the top. So it's just not the infrastructure. So we actually integrate a cluster manager, we integrate a job scheduler, we integrate a contained orchestration layer. So a lot of these things, customers have to do it by themself, right? If they're buy the infrastructure. So by basically we are actually giving a platform or an ecosystem for our customers to run their workloads. So make it easy for them to actually consume those. >>That's Now is this, is this available on premises for customer? >>Yeah, so we, we, we make it available customers both ways. So we make it available OnPrem for customers who want to, you know, kind of, they want to take that, take that economics. We also make it available in a colo environment if the customers want to actually, you know, extend colo as that OnPrem environment. So we do both. >>What are, what are the requirements for a customer before you roll that equipment in? How do they sort of have to set the groundwork for, >>For Well, I think, you know, fundamentally it starts off with what the actual use case is, right? So, so if you really look at, you know, the two validated designs we talked about, you know, one for, you know, healthcare life sciences, and one other one for manufacturing, they do have fundamentally different requirements in terms of what you need from those infrastructure systems. So, you know, the customers initially figure out, okay, how do they actually require something which is going to require a lot of memory intensive loads, or do they actually require something which has got a lot of compute power. So, you know, it all depends on what they would require in terms of the workloads to be, and then we do havet sizing. So we do have small, medium, large, we have, you know, multiple infrastructure options, CPU core options. Sometimes the customer would also wanna say, you know what, as long as the regular CPUs, I also want some GPU power on top of that. So those are determinations typically a customer makes as part of the ecosystem, right? And so those are things which would, they would talk to us about to say, okay, what is my best option in terms of, you know, kind of workloads I wanna run? And then they can make a determination in terms of how, how they would actually going. >>So this, this is probably a particularly interesting time to be looking at something like HPC via Apex with, with this season of Rolling Thunder from various partners that you have, you know? Yep. We're, we're all expecting that Intel is gonna be rolling out new CPU sets from a powered perspective. You have your 16th generation of PowerEdge servers coming out, P C I E, gen five, and all of the components from partners like Invidia and Broadcom, et cetera, plugging into them. Yep. What, what does that, what does that look like from your, from your perch in terms of talking to customers who maybe, maybe they're doing things traditionally and they're likely to be not, not fif not 15 G, not generation 15 servers. Yeah. But probably more like 14. Yeah, you're offering a pretty huge uplift. Yep. What, what do those conversations look >>Like? I mean, customers, so talking about partners, right? I mean, of course Dell, you know, we, we, we don't bring any solutions to the market without really working with all of our partners, whether that's at the infrastructure level, like you talked about, you know, Intel, amd, Broadcom, right? All the chip vendors, all the way to software layer, right? So we have cluster managers, we have communities orchestrators. So we usually what we do is we bring the best in class, whether it's a software player or a hardware player, right? And we bring it together as a solution. So we do give the customers a choice, and the customers always want to pick what you they know actually is awesome, right? So they that, that we actually do that. And, you know, and one of the main aspects of, especially when you talk about these things, bringing it as a service, right? >>We take a lot of guesswork away from our customer, right? You know, one of the good example of HPC is capacity, right? So customers, these are very, you know, I would say very intensive systems. Very complex systems, right? So customers would like to buy certain amount of capacity, they would like to grow and, you know, come back, right? So give, giving them the flexibility to actually consume more if they want, giving them the buffer and coming down. All of those things are very important as we actually design these things, right? And that takes some, you know, customers are given a choice, but it actually, they don't need to worry about, oh, you know, what happens if I actually have a spike, right? There's already buffer capacity built in. So those are awesome things. When we talk about things as a service, >>When customers are doing their ROI analysis, buying CapEx on-prem versus, versus using Apex, is there a point, is there a crossover point typically at which it's probably a better deal for them to, to go OnPrem? >>Yeah, I mean, it it like specifically talking about hpc, right? I mean, why, you know, we do have a ma no, a lot of customers consume high performance compute and public cloud, right? That's not gonna go away, right? But there are certain reasons why they would look at OnPrem or they would look at, for example, Ola environment, right? One of the main reasons they would like to do that is purely have to do with cost, right? These are pretty expensive systems, right? There is a lot of ingress, egress, there is a lot of data going back and forth, right? Public cloud, you know, it costs money to put data in or actually pull data back, right? And the second one is data residency and security requirements, right? A lot of these things are probably proprietary set of information. We talked about life sciences, there's a lot of research, right? >>Manufacturing, a lot of these things are just, just in time decision making, right? You are on a factory floor, you gotta be able to do that. Now there is a latency requirement. So I mean, I think a lot of things play, you know, plays into this outside of just cost, but data residency requirements, ingress, egress are big things. And when you're talking about mass moments of data you wanna put and pull it back in, they would like to kind of keep it close, keep it local, and you know, get a, get a, get a price >>Point. Nevertheless, I mean, we were just talking to Ian Coley from aws and he was talking about how customers have the need to sort of move workloads back and forth between the cloud and on-prem. That's something that they're addressing without posts. You are very much in the, in the on-prem world. Do you have, or will you have facilities for customers to move workloads back and forth? Yeah, >>I wouldn't, I wouldn't necessarily say, you know, Dell's cloud strategy is multi-cloud, right? So we basically, so it kind of falls into three, I mean we, some customers, some workloads are suited always for public cloud. It's easier to consume, right? There are, you know, customers also consume on-prem, the customers also consuming Kohler. And we also have like Dell's amazing piece of software like storage software. You know, we make some of these things available for customers to consume a software IP on their public cloud, right? So, you know, so this is our multi-cloud strategy. So we announced a project in Alpine, in Delta fold. So you know, if you look at those, basically customers are saying, I love your Dell IP on this, on this product, on the storage, can you make it available through, in this public environment, whether, you know, it's any of the hyper skill players. So if we do all of that, right? So I think it's, it shows that, you know, it's not always tied to an infrastructure, right? Customers want to consume the best thumb and if we need to be consumed in hyperscale, we can make it available. >>Do you support containers? >>Yeah, we do support containers on hpc. We have, we have two container orchestrators we have to support. We, we, we have aner similarity, we also have a container options to customers. Both options. >>What kind of customers are you signing up for the, for the HPC offerings? Are they university research centers or is it tend to be smaller >>Companies? It, it's, it's, you know, the last three days, this conference has been great. We probably had like, you know, many, many customers talking to us. But HC somewhere in the range of 40, 50 customers, I would probably say lot of interest from educational institutions, universities research, to your point, a lot of interest from manufacturing, factory floor automation. A lot of customers want to do dynamic simulations on factory floor. That is also quite a bit of interest from life sciences pharmacies because you know, like I said, we have two designs, one on life sciences, one on manufacturing, both with different dynamics on the infrastructure. So yeah, quite a, quite a few interest definitely from academics, from life sciences, manufacturing. We also have a lot of financials, big banks, you know, who wants to simulate a lot of the, you know, brokerage, a lot of, lot of financial data because we have some, you know, really optimized hardware we announced in Dell for, especially for financial services. So there's quite a bit of interest from financial services as well. >>That's why that was great. We often think of Dell as, as the organization that democratizes all things in it eventually. And, and, and, and in that context, you know, this is super computing 22 HPC is like the little sibling trailing around, trailing behind the super computing trend. But we definitely have seen this move out of just purely academia into the business world. Dell is clearly a leader in that space. How has Apex overall been doing since you rolled out that strategy, what, two couple? It's been, it's been a couple years now, hasn't it? >>Yeah, it's been less than two years. >>How are, how are, how are mainstream Dell customers embracing Apex versus the traditional, you know, maybe 18 months to three year upgrade cycle CapEx? Yeah, >>I mean I look, I, I think that is absolutely strong momentum for Apex and like we, Paul pointed out earlier, we started with, you know, making the infrastructure and the platforms available to customers to consume as a service, right? We have options for customers, you know, to where Dell can fully manage everything end to end, take a lot of the pain points away, like we talked about because you know, managing a cloud scale, you know, basically environment for the customers, we also have options where customers would say, you know what, I actually have a pretty sophisticated IT organization. I want Dell to manage the infrastructure, but up to this level in the layer up to the guest operating system, I'll take care of the rest, right? So we are seeing customers who are coming to us with various requirements in terms of saying, I can do up to here, but you take all of this pain point away from me or you do everything for me. >>It all depends on the customer. So we do have wide interest. So our, I would say our products and the portfolio set in Apex is expanding and we are also learning, right? We are getting a lot of feedback from customers in terms of what they would like to see on some of these offers. Like the example we just talked about in terms of making some of the software IP available on a public cloud where they'll look at Dell as a software player, right? That's also is absolutely critical. So I think we are giving customers a lot of choices. Our, I would say the choice factor and you know, we are democratizing, like you said, expanding in terms of the customer choices. And I >>Think it's, we're almost outta our time, but I do wanna be sure we get to Dell validated designs, which you've mentioned a couple of times. How specific are the, well, what's the purpose of these designs? How specific are they? >>They, they are, I mean I, you know, so the most of these valid, I mean, again, we look at these industries, right? And we look at understanding exactly how would, I mean we have huge embedded base of customers utilizing HPC across our ecosystem in Dell, right? So a lot of them are CapEx customers. We actually do have an active customer profile. So these validated designs takes into account a lot of customer feedback, lot of partner feedback in terms of how they utilize this. And when you build these solutions, which are kind of end to end and integrated, you need to start anchoring on something, right? And a lot of these things have different characteristics. So these validated design basically prove to us that, you know, it gives a very good jump off point for customers. That's the way I look at it, right? So a lot of them will come to the table with, they don't come to the blank sheet of paper when they say, oh, you know what I'm, this, this is my characteristics of what I want. I think this is a great point for me to start from, right? So I think that that gives that, and plus it's the power of validation, really, right? We test, validate, integrate, so they know it works, right? So all of those are hypercritical. When you talk to, >>And you mentioned healthcare, you, you mentioned manufacturing, other design >>Factoring. We just announced validated design for financial services as well, I think a couple of days ago in the event. So yep, we are expanding all those DVDs so that we, we can, we can give our customers a choice. >>We're out of time. Sat ier. Thank you so much for joining us. Thank you. At the center of the move to subscription to everything as a service, everything is on a subscription basis. You really are on the leading edge of where, where your industry is going. Thanks for joining us. >>Thank you, Paul. Thank you Dave. >>Paul Gillum with Dave Nicholson here from Supercomputing 22 in Dallas, wrapping up the show this afternoon and stay with us for, they'll be half more soon.

(bright music) (crowd talking indistinctly in the background) >> Hey guys, welcome back to Detroit, Michigan. theCUBE is live at KubeCon + CloudNativeCon 2022. You might notice something really unique here. Lisa Martin with our newest co-host of theCUBE, Savannah Peterson! Savannah, it's great to see you. >> It's so good to be here with you (laughs). >> I know, I know. We have a great segment coming up. I always love talking couple things, cars, one, two, with companies that have been around for a hundred plus years and how they've actually transformed. >> Oh yeah. >> Ford is here. You have a great story about how you, about Ford. >> Ford brought me to Detroit the first time. I was here at the North American International Auto Show. Some of you may be familiar, and the fine folks from Ford brought me out to commentate just like this, as they were announcing the Ford Bronco. >> Satish: Oh wow. >> Which I am still lusting after. >> You don't have one yet? >> For the record. No, I don't. My next car's got to be an EV. Although, ironically, there's a Ford EV right behind us here on set today. >> I know, I know. >> Which we were both just contemplating before we went live. >> It's really shiny. >> We're going to have to go check it out. >> I have to check it out. Yep, we'll do that. Yeah. Well, please welcome our two guests from Ford, Satish Puranam, is here, The Technical Leader at Cloud and Rebecca Risk, Principal Architect, developer relations. We are so excited to have you guys on the program. >> Clearly. >> Thanks for joining us. (all laugh) >> Thank you for having us. >> I love you're Ford enthusiasts! Yeah, that's awesome. >> I drive a Ford. >> Oh, awesome! Thank you. >> I can only say that's one car company here. >> That's great. >> Yes, yes. >> Great! Thank you a lot. >> Thank you for your business! >> Absolutely. (all laugh) >> So, Satish, talk to us a little bit about- I mean I think of Cloud as a car company but it seems like it's a technology company that makes cars. >> Yes. Talk to us about Ford as a Cloud first, technology driven company, and then we're going to talk about what you're doing with Red Hat and Boston University. >> Yeah, I'm like everything that all these cars that you're seeing, beautiful right behind us it's all built on, around, and with technology, right? So there's so much code goes into these cars these days, it's probably, it's mind boggling to think that probably your iPhones might be having less code as opposed to these cars. Everything from control systems, everything is code. We don't do any more clay models. Everything is done digital, 3D, virtual reality and all that stuff. So all that takes code, all of that takes technology. And we have been in that journey for the last- since 2016 when we started our first mobile app and all that stuff. And of late we have been like, heavily invested in Google. Moving a lot of these experiences, data acquisition systems AI/ML modeling for like all the autonomous cars. It's all technology and like from the day it is conceived, to the day it is marketed, to the day when you show up for a servicing, and hopefully soon how you can buy and you know, provide feedback to us, is all technology that drives all of this stuff. So it's amazing for us to see everything that we go and immerse ourselves in the technology. There is a real life thing that we can see what we all do for it, right? So- >> Yes, we're only sorry that our audience can't actually see the car, >> Yep. >> but we'll get some B-roll for you later on. Rebecca, talk a little bit about your role. Here we are at KubeCon, Savannah and I and John were talking when we went live this morning, that this is huge. That the show floor is massive, a lot bigger than last year. The collaboration and the spirit of the community is not only alive and well, as we heard in the keynote this morning, it's thriving. >> Yeah. >> Talk about developer relations at Ford and what you are helping to drive in your role. >> Yeah, so my team is all about helping developers work faster with different platforms that my team curates and produces, so that our developers don't have to deal with all of the details of setting up their environments to actually code. And we have really great people, kind of the top software developers in the company, are part of my team to produce those products that other people can use, and accelerate their development. And we have a great relationship with the developers in the company and outside with the different vendor relationships that we have, to make sure that we're always producing the next platform with the next tech stack that our developers will want to continue to use to produce the really great products that we are all about making at Ford. >> Let's dig in there a little bit because I'm curious and I suspect you both had something to do with it. How did you approach your Cloud Native transformation and how do you evaluate new technologies for the team? >> It's sometimes- many a times I would say it's like dogfooding and like experimentation. >> Yeah. Isn't anything in innovation a lot of- >> Yeah, a lot of experimentation. We started our, as I said, the Cloud Native journey back in 2016 with Cloud Foundry and things, technologies around that. Soon realized, that there was like a lot of buzz around that time. Twelve-Factor was a thing, Stateless was a thing. And then all those Stateful needs to drive the Stateless. So where do we do that thing? And the next logical iteration was Kubernetes was bursting upon the scene at that time. So we started doing a lot of experimentation. >> Like the Kool-Aid man, burst on the Kubernetes scene- >> Exactly right. >> Through the wall. >> So, the question is like, why can't we do? I think we were like crazy enough to say that Kubernetes people are talking about our serverless or Twelve-Factor on Kubernetes. We are crazy enough to do Stateful on Kubernetes and we've been doing it successfully for five years. So it's a lot about experimentation. I think good chunk of experiments that we do do not yield the results that we get, but many a times, some of them are like Gangbusters. Like, other aspects that we've been doing of late is like partnering with Becky and rest of the organization, right? Because they are the people who are like closest to the developers. We are somewhat behind the scenes doing some things but it is Becky and the rest of the architecture teams who are actually front and center with the customers, right? So it is the collaborative effort that we've been working through past few years that has been really really been useful and coming around and helping us to make some of these products really beautiful. >> Yeah, well you make a lot of beautiful products. I think we've all, I think we've all seen them. Something that I think is really interesting and part of why I was so excited for this interview, and kind of nudged John out, was because you've been- Ford has been investing in technology in a committed way for decades and I don't think most people are aware of that. When I originally came out to Dearborn, I learned that you've had a head of VR who happens to be a female. For what it's worth, Elizabeth, who's been running VR for you for two and a half decades, for 25 years. >> Satish: Yep. >> That is an impressive commitment. What is that like from a culture perspective inside of Ford? What is the attitude around innovation and technology? >> So I've been a long time Ford employee. I just celebrated my 29th year. >> Oh, wow! >> Congratulations! >> Wow, congrats! That's a huge deal. >> Yeah, it's a huge deal. I'm so proud of my career and all that Ford has brought to me and it's just a testament. I have many colleagues like me who've been there for their whole career or have done other things and come to Ford and then spent another 20 years with us because we foster the culture that makes you want to stay. We have development programs to allow you to upscale and change your role and learn new things and play with the new technologies that people are interested in doing and really make an impact to our community of developers at Ford or the company itself and the results that we're delivering. So to have that, you know, culture for so many years that people really love to work. They love to work with the people that they're working with. They love to stay engaged and they love the fact that you can have many different careers within the same umbrella, which we call the "blue oval". And that's really why I've been there for so long. I think I probably had 13 very unique and different jobs along the way. It's as if I left, and you know shopped around my skills elsewhere. But I didn't ever have to leave the company. It's been fabulous. >> The cultural change and adoption of- embracing modern technology- Cloud Native automotive software is impressive because a lot of historied companies, you guys have been there a long time, have challenges with that because it's really hard to get an entire moving, you'll call it the blue oval, to change and adapt- >> Savannah: I love that. >> and be willing to experiment. So that that is impressive. Talk about, you go by Becky, so I'll call you Becky, >> Rebecca/Becky: Yeah. >> The developer culture in terms of the developers really being the center of the nucleus of influencing the direction in which the company's going. I imagine that they probably are fairly influential. >> Yeah, so I had a very- one of the unique positions I held was a culture change for our department, Information Technology in 2016. >> Satish: Yeah. >> As the teacher was involved with moving us to the cloud, I was responsible- >> You are the transformation team! This is beautiful. I love this. We've got the right people on the show. >> Yeah, we do. >> I was responsible for changing the culture to orient our employees to pay attention to what do we want to create for tomorrow? What are the kind of skills we need to trust each other to move quickly. And that was completely unique. >> Satish: Yeah. >> Like I had men in the trenches delivering software before that, and then plucked out because they wanted someone, you know who had authentic experience with our development team to be that voice. And it was such a great investment that Ford continues to do is invest in our culture transformation. Because with each step forward that we do, we have to refine what our priorities are. And you do that through culture transformation and culture management. And that's been, I think really, the key to our successful pivots that we've made over the last six years that we've been able to continue to refine and hone where we really want to go through that culture movement. >> Absolutely. I think if I could add another- >> Please. >> spotlight to it is like the biggest thing about Ford has been among various startup-like culture, right? So the idea is that we encourage people to think outside the box, right? >> Savannah: Or outside the oval? >> Right! (laughs) >> Lisa: Outside the oval, yes! >> Absolutely! Right. >> So the question is like, you can experiment with various things, new technologies and you will get all the leadership support to go along with it. I think that is very important too and like we can be in the trenches and talk about all of these nice little things but who the heck would've thought that, you know Kubernetes was announced in 2015, in late 2016, we have early dev Kubernetes clusters already running. 2017, we are live with workloads on Kubernetes! >> Savannah: Early adopters over here. >> Yeah. >> Yeah. >> I'm like all of this thing doesn't happen without lot of foresight and support from the leadership, but it's also the grassroot efforts that is encouraged all along to be on the front end of all of these things and try different things. Some of them may not work >> Savannah: Right. >> But that's okay. But how do we know we are doing something, if you're not failing? We have to fail in order to do something, right? >> Lisa: I always say- >> So I think that's been a great thing that is encouraged very often and otherwise I would not be doing, I've done a whole bunch of stuff at Ford. Without that kind of ability to support and have an appetite for, some of those things would not have been here at all. >> I always say failure is not a bad F-word. >> Satish: Yep. >> Savannah: I love that. >> But what you're talking about there is kind of like driving this hot wheel of experimentation. You have to have the right culture and the mindset- >> Satish: Absolutely. >> to do that. Try fail, move on, learn, iterate, go. >> Satish: Correct. >> You guys have a great partnership with Red Hat and Boston University. You're speaking about that later today. >> Satish: Yes. >> Unpack that for us. What, from a technical perspective, what are you doing and what's it resulting in? >> Yeah, I think the biggest thing is Becky was talking about as during this transformation journey, is lot has changed in very small amount of time. So we traditionally been like, "Hey, here's a spreadsheet of things I need you to deliver for me" to "Here is a catalog of things, you can get it today and be successful with it". That is frightening to several of our developers. The goal, one of the things that we've been working with Q By Example, Red Hat and all the thing, is that how can we lower the bar for the developers, right? Kubernetes is great. It's also a wall of YAML. >> It's extremely complex, number one complaint. >> The question is how can I zero on? I'm like, if we go back think like when we talk about in cars with human-machine interfaces, which parts do I need to know? Here's the steering wheel, here's the gas pedal, or here's the brake. As long as you know these two, three different things you should be fairly be okay to drive those things, right? So the idea of some of the things with enablementing we are trying to do is like reduce that barrier, right? Reduce- lower the bar so that more people can participate in it. >> One of the ways that you did that was Q By Example, right, QBE? >> Satish: Yes, Yes. >> Can you tell us a little bit more about that as you finish this answer? >> Yeah, I think the biggest thing with Q By Example is like Q By Example gives you the small bite-sized things about Kubernetes, right? >> Savannah: Great place to start. >> But what we wanted to do is that we wanted to reinforce that learning by turning into a real world living example app. We took part info, we said, Hey, what does it look like? How do I make sure that it is highly available? How do I make sure that it is secure? Here is an example YAML of it that you can literally verbatim copy and paste into your editor and click run and then you will get an instant gratification feedback loop >> I was going to say, yeah, they feel like you're learning too! >> Yes. Right. So the idea would be is like, and then instead of giving you just a boring prose text to read, we actually drop links to relevant blog posts saying that, hey you can just go there. And that has been inspirational in terms of like and reinforcing the learning. So that has been where we started working with the Boston University, Red Hat and the community around all of that stuff. >> Talk a little bit about, Becky, about some of the business outcomes. You mentioned things like upskilling the workforce which is really nice to hear that there's such a big focus on it. But I imagine too, there's more participation in the community, but also from an end customer perspective. Obviously, everything Ford's doing is to serve the end customers >> Becky: Right. How does this help the end customer have that experience that they really, these days, demand with patience being something that, I think, is gone because of the pandemic? >> Right? Right. So one of the things that my team does is we create the platforms that help Accelerate developers be successful and it helps educate them more quickly on appropriate use of the platforms and helps them by adopting the platforms to be more secure which inherently lead to the better results for our end customers because their data is secure because the products that they have are well created and they're tested thoroughly. So we catch all those things earlier in the cycle by using these platforms that we help curate and produce. And that's really important because, like you had mentioned, this steep learning curve associated with Kubernetes, right? >> Savannah: Yeah. >> So my team is able to kind of help with that abstraction so that we solve kind of the higher complex problems for them so that developers can move faster and then we focus our education on what's important for them. We use things like Q By Example, as a source instead of creating that content ourselves, right? We are able to point them to that. So it's great that there's that community and we're definitely involved with that. But that's so important to help our developers be successful in moving as quickly as they want and not having 20,000 people solve the same problems. >> Satish: (chuckles) Yeah. >> Each individually- >> Savannah: you don't need to! >> and sometimes differently. >> Savannah: We're stronger together, you know? >> Exactly. >> The water level rises together and Ford is definitely a company that illustrates that by example. >> Yeah, I'm like, we can't make a better round wheel right? >> Yeah! So, we have to build upon what we have already been built ahead of us. And I think a lot of it is also about how can we give back and participate in the community, right? So I think that is paramount for us as like, here we are in Detroit so we're trying to recruit and show people that you know, everything that we do is not just old car and sheet metal >> Savannah: Combustion. >> and everything and right? There's a lot of tech goes and sometimes it is really, really cool to do that. And biggest thing for us is like how can we involve our community of developers sooner, earlier, faster without actually encumbering them and saying that, hey here is a book, go master it. We'll talk two months later. So I think that has been another journey. I think that has been a biggest uphill challenge for us is that how can we actually democratize all of these things for everybody. >> Yeah. Well no one better to try than you I would suspect. >> We can only try and hope everything turns out well, right? >> You know, as long as there's room for the bumpers on the lane for if you fail. >> Exactly. >> It sounds like you're driving the program in the right direction. Closing question for you, what's next? Is electric the future? Is Kubernetes the future? What's Ford all in on right now, looking forward? (crowd murmuring in the background) >> Data is the king, right? >> Savannah: Oh, okay, yes! >> Data is a new currency. We use that for several things to improve the cars improve the quality of autonomous driving Is Level 5 driving here? Maybe will be here soon, we'll see. But we are all working towards it, right? So machine learning, AI feedback. How do you actually post sale experience for example? So all of these are all areas that we are working to. We are, may not be getting like Kubernetes in a car but we are putting Kubernetes in plants. Like you order a Marquis or you order a Bronco, you see that here. Here's where in the assembly line your car is. It's taking pictures. It's actually taking pictures on Kubernetes platform. >> That's pretty cool. >> And it is tweeting for you on the Twitter and the social media platform. So there's a lot of that. So it is real and we are doing it. We need more help. A lot of the community efforts that we are seeing and a lot of the innovation that is happening on the floor here, it's phenomenal. The question is how we can incorporate those things into our workflows. >> Yeah, well you have the right audience for that here. You also have the right attitude, >> Exactly. >> the right appetite, and the right foundation. Becky, last question for you. Top three takeaways from your talk today. If you're talking to the developer community you want to inspire: Come work for us! What would you say? >> If you're ready to invest in yourself and upskill and be part of something that is pretty remarkable, come work for us! We have many, many different technical career paths that you can follow. We invest in our employees. When you master something, it's time for you to move on. We have career growth for you. It's been a wonderful gift to me and my family and I encourage everyone to check us out careers.ford.com or stop by our booth if you're happen to be here in person. >> Satish: Absolutely! >> We have our curated job openings that are specific for this community, available. >> Satish: Absolutely. >> Love it. Perfect close. Nailed pitch there. I'm sure you're all going to check out their job page. (all laugh) >> Exactly! And what you talked about, the developer experience, the customer experience are inextricably linked and you guys are really focused on that. Congratulations on all the work that you've done. We got to go get a selfie with that car girl. >> Yes, we do. >> Absolutely. >> We got to show them, we got to show the audience what it looks like on the inside too. We'll do a little IG video. (Lisa laughs) >> Absolutely. >> We will show you that for our guests and my cohost, Savannah Peterson. Lisa Martin here live in Detroit with theCUBE at KubeCon and CloudNativeCon 2022. The one and only John Furrier, who you know gets FOMO, is going to be back with me next. So stick around. (all laugh) (bright music)

>> theCUBE presents Dell Technologies World, brought to you by Dell. >> Hey everyone. Happy afternoon. Welcome back to theCUBE. This is Lisa Martin with Dave Vallante. We are on day three of our coverage of Dell Technologies World live from Las Vegas with about 7,000- 8,000 people here. It's been a great two and a half days. Lots of people are still here. We're going to be talking more about Dell Services. I got a couple of guys from Dell Technologies joining us next. Please welcome Patrick Mooney, Senior Vice President of Services Product Management at Dell and Satish Iyer, Vice President of Emerging Services at Dell. Guys, welcome to the program. >> Thank you. Good evening. Great to be here to you. >> Happy to be here. >> So isn't it great to be back in person? >> So great. >> Those hallway conversations you just can't replicate it for video conferencing, right? >> Yeah. >> Priceless. >> It is priceless, I agree. Patrick, let's start with you. Talk to us about from a customer's perspective. What are some of the key services they've been looking for the last couple of years particularly, and how has Dell changed its strategic direction to deliver? >> Great question. Customers want outcomes and services are at the heart of outcomes. So when we look at customers transforming we're continually transforming and modernizing what we do and everything we're doing is centered around making it easy to buy, easy to consume and just centered around the customer. >> What are people looking for these days, Satish? I mean, what's the top three or four priorities. And we know cyber's up there. The cloud. One is when customers are consuming cloud, now there is more and more what we call as customers are looking for full stack solutions. So they start with giving me the best infrastructure on the platforms. Now they're saying, "I'm going to use those infrastructure to drive X, Y, and Z. "Now Mr. Dell, can you come and gimme those tags? "So I don't need to worry about anything "and I can actually consume it in the cloud like way." That's been massive for us. >> So, how do you guys respond to that? I mean, things in our little business things change so fast. And we can, but we're little. We can move fast. Customers are saying, okay, pandemic forced match to digital and now we got to figure it out. And now we got to modernize our HQ. How are you able to keep up? How are you changing your strategy as your customers pull you in different directions? What's going on inside the organization to enable that? >> Yeah. I think the key is that we meet customers where they are and help them plot out where they want to be. And then bring them along that journey. And we've really spent a lot of time developing four practices to help get there. One's around data and applications another around multi-cloud, another around workforce and another around security and resiliency. And no matter where they want to be, whether they want to do it themselves. They want us to help them do it or they want us to do it for them, we're there for them and we'll help them get where they want to be. >> Do you have like formal customer councils or how do you actually, especially the last couple years staying engaged with those customers? >> Absolutely. We're always talking to customers. It is critical to the model and we got a lot of ideas and customers have a lot of ideas and we want to vet those and talk through them. So no matter what point we're at in our product development cycle, we're always talking with customers, "Hey, do we hear you right? "Is this the value you're looking for?" And as we're developing it, can you help us test it? And so on. And we do that through regular conversations, field testing, customer insight councils, and it just feels so great to be having face to face conversations again as well. >> What is- >> Oh, go ahead. >> I was going to say, what are some of the things that you've heard face to face this week in terms of the direction, what Dell Services is delivering? >> Well, one big one for sure is that remote workforce is here to stay. And in our workforce pillar we spent a lot of time around how do we make it easy for customers to manage a remote workforce? It's a big challenge. So we've recently we announced here at Dell World, Lifecycle Hub Services where we it's a managed service where we're helping customers manage their entire device lifecycle around their PC. So imagine this you have a new hire joint or somebody leaves, how do you get 'em that PC? Have it ready? Let Dell take care of all the logistics, we'll we'll store it. We'll configure it. We'll send it to 'em we'll take the old machines back, we'll kit it for 'em anything that's needed and fully integrated it from the customer system into our system. So it's all automated. >> Okay. And all the patching, et cetera, >> Everything. Okay. So you got four pillars, data and apps multi-cloud, workforce and resiliency. What you just described, the automation, does IP and what's the IP portfolio look like? How does it map into those four pillars? >> Sure, you want to take that? >> Sure, so obviously when you look at growth areas and services, it's absolutely important for us to develop sustainable IP. If you look at one of the areas where we have invested and we are growing is cloud managed services platform. So Dell is unique in terms of managing our customer services. We actually do full lifecycle management of the customers. So we invested quite a bit of, I would say time and energy and engineering efforts to basically solve problems in engineered way. So the customer cloud managed services platform allows us to actually bring both, you talked about apex before to our other colleagues. So it allows us to both bring apex services to our customers and also allows us to bring non apex services in terms of fully managed to our customers. >> So multi-cloud must be a rich opportunity's probably almost infinite. There's a lot of gaps there for IP development. What are you seeing and hearing from customer with regard to those gaps? >> So one of the key areas when you talk about multi-cloud is we talk to customers about is the solution things we talked about. So we launched, we announced three solutions one we already launched. And the two of them will be announced is customers want that end-to-end outcome, right? 'Cause they are saying, well we are currently where we started today. We announced cyber security as a service. As you guys know, within the current geopolitical climate, cyber attacks are common, ransomware is common. So, and this is something which we are doing today to customers. What customers want is the simplicity of offering. They're like, you can help us with cyber security when something happens I have an insurance policy, so I can actually go I know where my data sets are. I can record from it, but can you streamline it for me? I don't want all the headaches. Can you make sure that it's easily consumable and Dell can take care of everything for me. And we are also investing on other LED solutions like machine learning, high performance compute. And we are also looking at vertical areas. So our customers, especially in telco, Edge and enterprise applications. So we are looking at those as a full stack offerings so that we can actually educate and take our customers on the journey on our MacCloud platforms. >> I going to talk about Dell Services as a facilitator of multi-cloud Chuck Whitton was on stage, He was here yesterday talking about multi-cloud is here by default. Well, Dell wants to change that to multi-cloud by design. How can Dell Services be a facilitator of that transformation that customers in telco or whatever industry have going from, We've got it by default to now it's actually by design, facilitating that? >> Yeah. I'll jump in and let you take it, we have a a robust consulting practice which can help you come in and understand where you're at and where you want to be and design that future. So that it's not, as you said by default, it's absolutely multi-cloud by design. Anything you want to add? >> Yeah. I mean, look again Dell has been doing multi-cloud for a long time. We just didn't call it multi-cloud. I would probably say 2014, 2015, Dell's been there. We know our customers have a choice. We want to operationalize. We want to help our customers run workloads wherever they want to run. Now, we have a term for it. We have a dedicated way of talking about it. And again, more automation more IP development, more software. And again, taking a lot of the people part away from services and driving more innovation, more IPs where we are going to be able to differentiate. >> So you're a large and pretty sophisticated services organization. We've talked about some of your IP. You now bring that to your customers. What are some of the adoption barriers that they have? How are you addressing those, in terms of taking your IP and your ideas? And you probably say, "Hey, we got this, you can apply this". What are they not ready for? That you sort of advise them, okay you got to do, these are some maybe, some out scope things that you haven't talked about or thought about. >> Yeah. I mean, I'll take one. And I know Patrick will probably touch on, I would say two big ones. I can think about the one is data. One is on security, right? I'll give you the data use case. So data has gravity, right? When customers think about, multi-cloud think about solution, think about these services. It's not easy to take petabytes and terabytes of data and shift all over the place. It's very, very expensive. So a lot of their cloud strategy really hinges on where the data is, and how they're going to optimize those data for the outcomes they want to decide. And that's something a lot of our customers initially don't think about it as we actually go and talk to them about this specific use case and application that actually becomes forefront of the discussion. >> Yeah. On the security front, customers are just overwhelmed with the number of options in a very fragmented, extremely important space. So we've tried to make that very easy for them with our managed detection and response services, bringing the best of the industry and Dell Services together to give them a one stop shop managed service, let us watch for you so that you can run your business. And when we detect something, we'll advise you and help you respond. >> What's the tooling like there. I mean, you have, do you have your preferred tooling? Are the customers saying, well we got to use this vendor or that vendor, how do you manage all that complex? >> Of course we have our preferred tooling and we partner greatly with secure works to do it as well as some other company, but that said what's important to us with the service is that a customer meets specific, they're green in five different categories. And if they're green in those categories, then we're good to help them. And if they don't know how to do that, then we'll come in and do a security assessment to help them get there. And just taking what's very complicated and making it easy. >> On the security front. We've been talking about the cyber skills gap, massive skills gap that's been around for years. How is Dell Services facilitator of organizations being able to close that gap? >> Sure. In a few ways, one, we can just do it for you, right? Two, if you want to do it yourself, we can supplement you with security residents to help you manage through the complexity and cross train while as part of your staff. And then three, we have our Dell Education Services where we can come in and train you as well. So lots of different options on how you want to do it. >> Yeah. >> No matter what you choose, we're here for you. (panelists laughing) >> That people option's important. I mean, people being the biggest threat factor that there is, right. >> Absolutely. >> For sure. >> That's probably one of the hardest ones to augment. >> Yeah. I mean, that's the reason why when you look at cyber security customers, want somebody else to manage it because you don't want the same folks making the same mistake on an insurance policy. So they're like Dell, you manage it for me. So I don't have the same actor is doing same things. So I have somebody managing my data but somebody managing my record option. So in case something goes wrong I know it's a different handset different people who are much more relaxed when things go back >> That's always nice to have somebody that's relaxed in a crisis. >> Absolutely. And I think I'll take that in my personal life too. Guys thank you for joining Dave and me talking about what's new with Dell Services the modernization that you're undergoing and how your customers are really helping to evolve this strategy. We appreciate your insight. >> Thank you, Lisa. >> Thank you so much for your time. Great seeing you. >> Right. Likewise for Dave Vallante, I'm Lisa Martin. You're watching theCUBE. This is day three of our coverage of Dell Technologies World, live from Las Vegas, stick around Dave and I will be right back with our next guest. (bright music)

(upbeat music) >> Hi everybody, we're here in downtown Seattle covering AWS storage day. My name is Dave Vellante with the Cube, and we're really excited. We're going to talk about rethinking data protection in the 2020s. I'm here with Nancy Wong, who is the general manager of AWS backup, and Satish Lakshmanan, the director of storage business development at AWS. Folks, welcome. Good to see you again. So let's talk about the evolution of data protection. You've got three major disruptors going on. There's obviously the data explosion. We talk about that all the time, but there's cloud has changed the way people are thinking about data protection and now you've got cyber. What's AWS's point of view on all this. >> Great question, Dave. You know, in my role as the global head of storage business development and solution architecture for storage, I have the privilege of working with customers all around the globe, in every geography and every segment. And we recently talked to thousands of customers and we did a survey for about 5,000 customers. And many of them told us that they expect to see a ransomware attack once every 11 seconds. So it's top of mind for almost every customer so much so that if you remember earlier this year, the white house issued an executive order, you know, making the nation aware of across public and private sector about cybersecurity and the need for, for, for us to be prepared. Customers as a result, largely think of not only ransomware protection, but also recovery. And they have largely allocated budgets across every geography to make sure that they're well protected. And in the, in the event of an attack, they can recover from it. That's where Nancy's, you know, data protection services and backup services come into play. And maybe she'll add a few comments about how she approaches it from a technology perspective. >> Yeah, sure. Thanks, Satish yeah, as a general manager of AWS backup and our data protection services, it's really my team and my charter to help our customers centralize, automate, and also protect themselves from attacks like ransomware. Right? And so for example, you know, across our many services today we offer AWS backup as a secondary data collection and management across our many AWS regions and also across the aid of many AWS accounts that a single customer must manage, right. And if you recall having multiple copies of your data exist in backups is a core part of any customers ransomware protection strategy. And lastly, I just want to say something that we just launched recently called AWS backup audit manager also helps you operationalize and monitor your backups against any ransomware attack. >> So, the adversary, obviously, as we know, was well-equipped and they're quite sophisticated. And anybody who has inside access can become a ransomware attacker because of things like ransomware as a service. So, what are you specifically doing to address ransomware? >> Yeah. So, in talking to several thousand of our customers, what we have learned is customers are typically vulnerable in one or more of three scenarios, right? The first scenario is when they're not technically ready. What that means is either their software patches are not up to date, or they have too many manual processes that really prevent them from being prepared for defending against an attack. The second is typically around a lack of awareness. These are situations where IT administrators leveraging cloud-based services are recognizing that, or not recognizing per se, that they're easy to instances, Lambda instances have public access and same applies to S3 buckets. And the third is lack of governance and governance based practices. The way we are educating our customers training in enabling them and empowering them, because it's a shared security model, is really through our well-architected framework. That's the way we shared best practices that we have learned across all our customers, across our industries. And we enable it and empower them to not only identify areas of vulnerability, but also be able to recover in the event of an attack. Nancy. >> Yeah, and to add to that right, our team, and now my team and I, for example, watch every ransomware incident and because it really informs the way that we plan our product roadmap and deliver features that help our customers protect, detect, and also recover from ransomware. So there's an ebook out there, suggest you go check it out, of securing your cloud environment against ransomware attacks. And aside from the technical maintenance suggestions that Satish provided, as well as the security awareness suggestions, there's really two things that I usually tell customers who come to me with ransomware questions. Which is one, right, don't rely on the good will of your ransomware attacker to restore your data. Because I mean, just studies show over 90% of ransom payers actually don't successfully recover all of their data because, hey, what if they don't give you the full decryption utility? Or what if your backups are not restorable? Right? So, rather than relying on that good will, make sure that you have a plan in place where you can recover from backups in case you get ransomed. Right? And two, is make sure that in addition to just taking backups, which obviously, you know, as a GM of AWS backup, I would highly recommend you do, right. Is make sure that those backups are actually restorable, right? Do game day testing, make sure that it's configured properly because you'd be surprised at the, just the number and the sheer percentage of customers who when, let's say the attack happens, actually find that they don't have a good set of data to recover their businesses from. >> I believe it. Backup is, one thing as they say, recovery is everything. So you've got the AWS well-architected framework. How does that fit in, along with the AWS data protection services into this whole ransomware discussion? >> Yeah, absolutely. You know, the AWS wall architected framework actually has four design approaches that I usually share with customers that are very relevant to the ransomware conversation. And one is, you know, anticipate where that ransomware attack may come from. Right? And two, make sure that you write down your approaches whereby you can solve for that ransomware attack, right? Three, just like I advocate my teams and customers to do, right. Then look back on what you've written down as your approach and reflect back on what are the best practices or lessons learned that you can gain from that exercise. And make sure as part four, is you consistently plan game days where you can go through these various scenario tests or ransomware game day attacks. And lastly, just as a best practice is ransomware recovery and protection isn't just the role of IT Professionals like us, right. It's really important to also include HR, professional, legal professionals. Frankly, anyone in a business who might come and be compromised by ransomware attack, and make sure that they're involved in your response. And so Satish, I'd love to hear as well, how you communicate to customers and what best practices you offer them. >> Yeah, thanks Nancy. I think in addition to the fantastic points you made, Nancy, Dave, the well architected framework has been built on eight to 10 years worth of customer engagements across all segments and verticals. And essentially it's a set of shared best practices, tools, training, and methodology that we, you know, exchange with customers in order to help them be more prepared to fight ransomware attacks and be able to recover from them. Recently, there've been some enhancements made where we have put industry or use case specific lenses to the well architected framework. For example, for customers looking to build IOT applications, customers who are trying to use server less and Lambda functions, customers who may be within the financial services or healthcare life sciences, where to go, looking to understand best practices from other people who've implemented, you know, some of the technologies that Nancy talked about. In addition, as I talked about earlier, training and enablement is extremely critical to make sure that if companies don't have the skillset, we are basically giving them the skillset to be able to defend. So we do a lot of hands-on labs. Lastly, the well architected framework tool has been integrated into the console, and it gives customers who are essentially managing the workloads, the ability to look at access permissions, ability to look at what risks they have through malware and ransomware detection techniques. Machine learning capability is built into all the services that are native to AWS that allow them to then react to them. If companies don't have the skills, we have a vast network of partners who can help them basically implement the right technologies. And they can always reach out to our technical account manager for additional information as well. >> I love the best practice discussion. For customers, it's a journey. I mean, CSOs tell us their one problem is lack of talent and so they need help. So, last question is what can people expect from AWS? You're the experts. In particular, how you can help them recover from ransomware? >> Yeah, and that conversation is ever evolving, right? As hackers get more sophisticated then clearly we have to get more sophisticated as well. And so one of our mental models that we often share with customers is defense in depth, right? So if you consider all of the layers, including all of the constructs that exist natively on AWS, right? The first layer is through identity access management constructs. So building a trust radius around your workloads, around your applications, whereby you can deny permissions or access permissions to individuals who are not authorized to access your mission critical applications, right. Then beyond that first layer of defense, the second layer should be automated monitoring or observability. For example, if individuals were to penetrate within your security perimeter, and often times I, you know, that could be done through a delayed response where it gives your CSO or your security operations team, the ability to react to such a unauthorized access, for example. And so the third line of defense is if someone were to penetrate both first layer, as well as the second layer, is actually through backups. And this is where it goes back to what I was mentioning earlier is make sure that your backups are ready and able to be restored and have the RTO and SLA guarantees that help your business remain functional even after an attack. >> Excellent. Guys, we got to go. I love that, zero trust layer defenses, got to have the observability in the analytics and then the last resort RTO, and of course, RPO. Guys, thanks so much, really appreciate your insights. >> Good to see you. >> Thank you for watching. Keep it right there for more great content from AWS storage day. (upbeat music)

>> Narrator: From around the globe, it's theCUBE. With digital coverage of AWS re:Invent 2020. Sponsored by intel, AWS, and our community partners. >> Welcome back to the CUBE's coverage of the AWS re:Invent 2020. Three weeks we're here, covering re:Invent. It's virtual. We're not in person. Normally we are on the floor. Instructing *signal from the noise, but we're virtual. This is theCUBE Virtual. We are theCUBE Virtual. I'm John Furrier, your host. Got a great interview here today. Satish Balakrishnan, Vice president of hosted platforms for Red Hat joining us. Satish, great to see you. Thanks for coming on. >> Thank you, John. Great to see you again. >> I wish we were in person, but we're remote because of the pandemic. But it's going to be a lot of action going on, a lot of content. Red Hat's relationship with AWS, and this is a really big story this year, at many levels. One is your relationship with Red Hat, but also the world's evolved. Clearly hybrid cloud's in play. Now you got multiple environments with the edge and other clouds around the corner. This is a huge deal. Hybrids validated multiple environments, including the edge. This is big. On premise in the cloud. What's your new update for your relationship? >> Absolutely, John, yeah. this is so you know, if anything this year has accelerated digital transformation, right The joke that COVID-19 is the biggest digital accelerator, digital transformation accelerator is no joke. I think going back to our relationship with AWS, as you rightly pointed out, we have a very storied and long relationship with AWS, we've been with AWS partnering with AWS since 2007, when we offered the Red Hat Enterprise Linux on AWS since then, you know, we've made a lot of strides, but not in the middle of our products that are layered on AWS, as well as back in 2015, we offered OpenShift dedicated Red Hat OpenShift dedicated, which is our managed offering on AWS, you know, and since then we made a bunch of announcements right around the service broker, and then you know, the operators operator hub, and the operators that AWS has for services to be accessed from Kubernetes. As well as you know, the new exciting joint service that we announced. So you know, by AWS and Red Hat, increasingly, right, our leaders in public cloud and hybrid cloud and are approached by IT decision makers who are looking for guidance or on changing requirements, and they know how they should be doing application development in a very containerized and hybrid cloud world. So you know, excited to be here. And and this is a great event, you know, three week event, but you know, usually we were in Las Vegas, but you know, this week, this year, we will do it on workshop. But you know, nevertheless, the same excitement. And you know, I'm sure there's going to be same set of announcements that are going to come out of this event as well. >> Yeah, we'll keep track of it. Because it's digital. I think it's going to be a whole another user experience personally on the Discovery sites Learning Conference. But that's great stuff. I want to dig into the news, cause I think the relevant story here that you just talked about, I want to dig into the announcement, the new offering that you have with AWS, it's a joint offering, I believe, can you take a minute to explain what was and what's discussed? Cause you guys announced some stuff in May. Now you have OpenShift services. Is it on AWS? Can you take a minute to explain the news here? >> Absolutely John yeah. So I think we had really big announcement in May, you know, the first joint offering with AWS and it is Red Hat open shift service on AWS, it's a joint service with Red Hat and AWS, we're very excited to partner with them, and you know, be on the AWS console. And you know, it's great to be working with AWS engineering team, we've been making a lot of really good strides, it just amplify, as you know, our managed services story. So we are very excited to have that new offering that's going to be completely integrated with AWS console transacted through you know AWS marketplace, but you know, customers will get all the benefit of AWS service, like you know, how just launch it off the console, basically get, you know there and be part of the enterprise discount program and you we're very really excited and you know, that kind of interest has been really, really amazing. So we just announced that, you know, it's in preview we have a lot of customers already in preview, and we have a long list of customers that are waiting to get on this program. So but this offering, right, we have three ways in which you can consume OpenShift on AWS. One is, as I mentioned previously OpenShift dedicated on AWS, which we've had since 2015. Then we have OpenShift container platform, which is our previous self managed offering. And that's been available on AWS, also since 2015. And then, of course, this new service that are that OpenShift servers on AWS. So there's multiple ways in which customers can consume AWS and leverage the power of both OpenShift and AWS. And what I want to do here as well, right, is to take a moment to explain, you know what Red Hat's been doing in managed services, because then it's not very natural for somebody to say, oh, what's the Red Hat doing in managed services? You know, Red Hat believes in choice, right. We are all about try for that it's infrastructure footprint that's public cloud on-prem. It's managed or self managed, that's also tries to be offered to customers. And we've been doing managed services since 2011. That's kind of like a puzzling statement, people will be like, what? And yeah, it is true that we've been doing this since 2011. And in fact, we are one of the, you know, the earliest providers of managed Kubernetes. Since 2015. Right, I think there's only one other provider other than us, who has been doing managed Kubernetes, since then, which is kind of really a testament to the engineering work that Red Hat's been doing in Kubernetes. And, you know, with all that experience, and all the work that we've done upstream and building Kubernetes and making Kubernetes, really the you know, the hybrid cloud platform for the entire IT industry, we are excited to bring this joint offering. So we can bring all the engineering and the management strengths, as well as combined with the AWS infrastructure, and you know and other AWS teams, to bring this offering, because this is really going to help our customers as they move to the cloud. >> That's great insight, thanks for explaining that managed service, cause I was going to ask that question, but you hit it already. But I want to just follow up on that. Can you just do a deeper dive on the offering specifically, on what the customer benefits are here from having this managed service? Because again, you said, You Red Hats get multiple choice consumption vehicles here? What's the benefits? what's under the what's the deep dive? >> Absolutely, absolutely is a really, really good question. right as I mentioned, first thing is choice. like we start with choice customers, if they want, self managed, and they can always get that anywhere in any infrastructure footprint. If they're going to the cloud, most customers tend to think that you know, I'm going to the cloud because I want to consume everything as a service. And that's when all of these services come into play. But before we even get to the customer benefits, there's a lot of advantages to our software product as well. But as a managed service, we are actually customer zero. So we go through this entire iteration, right. And you probably everybody's familiar with, how we take open source projects, and we pull them into enterprise product. But we take it a second step, after we make it an enterprise product, we actually ship it to our multi tenant software system, which is called OpenShift Online, which is publicly available to millions of customers that manage exports on the public Internet, and then all the security challenges that we have to face through and fix, help solidify the product. And then we moved on to our single tenant OpenShift dedicated or you know soon to be the Red Hat OpenShift service on AWS but, you know, pretty much all of Red Hat's mission critical applications, like quedado is a service that's serving like a billion containers, billion containers a month. So that scale is already been felt by the newly shipped product, so that you know, any challenges we have at scale, any challenges, we have security, any box that we have we fix before we really make the product available to all our customers. So that's kind of a really big benefit to just that software in general, with us being a provider of the software. The second thing is, you know, since we are actually now managing customers clusters, we exactly know, you know, when our customers are getting stock, which parts of the stock need to improve. So there's a really good product gap anticipation. So you know, as much as you know, we want still really engage with customers, and we continue to engage with customers, but we can also see the telemetry and the metrics and figure out, you know, what challenges our customers' facing. And how can we improve. Other thing that, you know, helps us with this whole thing is, since we are operators now, and all our customers are really operators of software, it gives us better insights into what the user experience should be, and in how we can do things better. So there's a whole lot of benefits that Red Hat gets out of just being a managed service provider. Because you know, drinking our own champagne really helps us you know, polish the champagne and make it really better for all our customers that are consuming. >> I always love the champagne better than dog food because champagne more taste better. Great, great, great insight. Final question. We only have a couple minutes left, only two minutes left. So take the time to explain the big customer macro trend, which is the on premise to cloud relationship. We know that's happening. It's an operating model on both sides. That's clear as it is in the industry. Everyone knows that. But the managed services piece. So what drives an organization and transition from an on-prem Red Hat cloud to a managed service at Amazon? >> Is a really good question. It does many things. And it really starts with the IT and technology strategy. The customer has, you know, it could be like a digital transformation push from the CEO. It could be a cloud native development from the CPO or it could just be a containerization or cost optimization. So you have to really figure out you know, which one of this and it could be multiple and many customers, it could be all four of them and many customers that's driving the move to the cloud and driving the move to containerization with OpenShift. And also customers are expanding into new businesses, they got to be more agile, they got to basically protect the stuff. Because you know, there are a lot of competitors, you know, that, and b&b and other analogies, you know, how they take on a big hotel chains, it's kind of, you know, customers have to be agile IT is, you know, very strategic in these days, you know, given how everything is digital, and as I pointed out, it has coverts really like the number one digital transformation(mumbles). So, for example, you know, we have BMW is a great customer of ours that uses OpenShift, for all the connected car infrastructure. So they run it out of, you know, their data centers, and, you know, they suddenly want to go to a new geo syn, in Asia, you know, they may not have the speed to go build a data center and do things, so they'll just move to the cloud very easily. And from all our strategy, you know, I think the world is hybrid, I know there's going to be a that single cloud, multi cloud on-pram, it's going to be multiple things that customers have. So they have to really start thinking about what are the compliance requirements? What is the data regulations that they need to comply to? Is that a lift and shift out(mumbles) gistic things? So they need to do cloud native development, as well as containerization to get the speed out of moving to the cloud. And then how are they measuring availability? You know, are they close to the customer? You know, what is the metrics that they have for, you know, speed to the customer, as well, as you know, what databases are they using? So we have a lot of experience with this. Because, you know, this is something that, you know, we've been advocating, you know, for at least eight years now, the open hybrid cloud, a lot of experience with open innovation labs, which is our way of telling customers, it's not just about the technology, but also about how you change processes and how you change other things with people aspects of it, as well as continued adoption programs and a bunch of other programs that Red Hat has been building to help customers with this transformation. >> Yeah, as a speed game. One of the big themes of all my interviews this week, a couple weeks here at reInvent has been speed. And BMW, what a great client. Yeah, shifting into high gear with BMW with OpenShift, you know, little slogan there, you know, free free attribute. >> Thank you, John, >> Shifting the idea, you know, OpenShift. Congratulations, and great announcement. I love the direction always been a big fan of OpenShift. I think with Kubernetes, a couple years ago, when that kind of came together, you saw everything kind of just snap into place with you guys. So congratulations Satish. Final question. What is the top story that people should take away from you this year? Here at reInvent? What's the number one message that you'd like to share real quick? >> Yeah, I think number one is, you know, we have a Joint Service coming soon with AWS, it is one of it's kind work for us. And for AWS, it's the first time that we are partnering with them at such a deep level. So this is going to really help accelerate our customers' move to the cloud, right to the AWS cloud, and leverage all of AWS services very natively like they would if they were using another container service that's coming out of AWS and it's like a joint service. I'm really, really excited about the service because, you know, we've just seen that interest has been exploding and, you know, we look forward to continuing our collaboration with AWS and working together and you know, helping our customers, you know, move to the cloud as well as cloud native development, containerization and digital transformation in general. >> Congratulations, OpenShift on AWS. big story here, >> I was on AWS. I want to make sure that you know we comply with the brand >> OpenShifts on open shift service, on AWS >> on AWS is a pretty big thing. >> Yeah, and ecosys everyone knows that's a super high distinction on AWS has a certain the highest form of compliment, they have join engineering everything else going on. Congratulations thanks for coming on. >> Thank you John. Great talking to you. >> It's theCUBE virtual coverage we got theCUBE virtual covering reInvent three weeks we got a lot of content, wall to wall coverage, cube virtualization. We have multiple cubes out there with streaming videos, we're doing a lot of similar live all kinds of action. Thanks for watching theCUBE (upbeat music)

>> Narrator: From around the globe it's theCUBE with digital coverage of Dell Technologies World. Digital experience brought to you by Dell Technologies. >> Welcome back everybody. Jeff Frick here with theCUBE. Welcome back to our ongoing coverage of Dell Technology World. We've been covering Dell Tech World since it started really. It used to just be Dell World and there was EMC World after the merger and this is the all virtual version but we're excited to be here and we've got a great panel coming up. I think you're going to enjoy it. Our first guest is Rajesh Janey. He is the Senior Vice President of Global Alliances for APJ for Dell Technologies. Rajesh, where are you coming in from today? >> I'm speaking to you from Gurgaon, India. >> Awesome. It's the power of the virtual, right? It's not all bad that we don't have to get on planes all the time. >> Absolutely. >> And joining him is Utpal Bakshi. He is the Vice President and Global Vertical Head High Tech for Wipro. Utpal, good to see you. >> Nice to see you. >> And where are you calling us in from? >> I'm from Dallas, Texas. Actually suburb outside of Dallas called South Lake. >> Oh, excellent. Great to see you and again didn't have to get on a plane to do this so not all bad. And also joining us is Satish Yadavalli. He is the Vice President and Global Practice Head, Cloud and Infrastructure Services for Wipro. Satish, where are you joining us from? >> Hi, I'm joining from Bangalore, India. >> Excellent. Welcome. So gentlemen let's just jump into it. Wipro's a huge services firm, does a lot of work with Dell so I wonder Rajesh if you can talk really about the importance of partnerships and the importance of having somebody like Wipro within the Dell ecosystem. >> Absolutely. Thank you for having us on with Wipro. Wipro and we have had a partnership which is over two decades old and we have a multifaceted 360 degree kind of relationship with Wipro. Wipro is a platinum partner and what's more while we bring a lot of technology and products and the depth of product which are relevant to customer's transformation scenarios today, coupled with Wipro's consulting and services and design abilities this becomes an unbeatable power house so to say whereby we can work closely with a customer to help them transform and live in what we are calling the next normal. >> Yeah that's great. Utpal to you there's a lot of interesting trends going on. We've had cloud and big data been going on for a lot but really the talk in social media is what's driving your digital transformation, the CEO, the CIO or COVID and we all know what the answer is. So we've got a lot of new stuff in terms of digital transformation, working from anywhere, workforce transformation. Wonder if you can speak a little bit about how COVID has accelerated some of the priorities that your customers are trying to get done. >> Yeah. I think that's a great point. Wipro has been transforming over the last several years. We were a strong, large scale system integration partner, large IT organization but over the last several years we pivoted hard into the digital transformation world moving into the design side, leading the design, moving to cloud and helping our clients help make that journey and all of that got accelerated with the whole COVID situation. The work from home became all pervasive and the whole virtualization of the workforce really pivoted with some of our key transformational ideas around live workspace and the virtual desk which we've been working very closely with Dell have taken shape. So that has been a big part of our ongoing strategy. Doing the modernization off the network has also accelerated the customer networks and infrastructure was not necessarily set up for enabling these hybrid work environment. A lot of our clients are coming back and saying they want to modernize and actually accelerate. So that has all changed with COVID. Some of it is very positive actually for the business. >> Right. >> From an SI perspective. >> Satish, you've got cloud and infrastructure in your title. Public cloud really changed the game when Amazon kind of came on the scene and now we're seeing this evolution and change over time between a public cloud and hybrid cloud and multi cloud and cloud on cloud. I wonder if you could speak to and then even have an AWS inside of other people's clouds. They're trying to get it out there. The evolution of cloud both as a technology but really more as a way of thinking in terms of rapid deployment of new functionality to support the business and what you're seeing with your customers today. >> So let me share a perspective, right? Enterprises today are looking at options to extract greater value from hybrid cloud investment. It's a brownfield environment today where customers have their existing data centers but the hyperscalers have really come into play now and right cloud is the strategy which most of our customers embrace to address the market demands which are primarily focused on business outcomes today. As Wipro we have invested in developing a holistic extensible platform led approach called Wipro BoundaryLess Enterprise to drive business outcomes to customers. So the BLE construct is all about providing a ready to use plug-and-play platforms making IT easily consumable from multiple stakeholder personas be it admins, be it line of businesses, developers and partners. So basically we have built a holistic solution and our BLE solutions has majorly five building blocks. The first building block would be the BoundaryLess Data Center. The second is the BoundaryLess Container Platform. The third is the BoundaryLess Data Protection Platform. The fourth is the BoundaryLess Cloud Exchange where we get together all the internet connections and define the software defined network part to give access to the workloads across hybrid environments and the BoundaryLess Integration Platform which we call it as BLIP. Basically this is what we have put together to deliver an outcome to the customers powered by BLE. >> So BLE again, you call it the BoundaryLess Enterprise. What's the most important components of BLE? What are the things that most people are missing to actually implement the strategy? >> So if I actually build on you, right? The five building blocks let me elaborate in detail. The first is on the BoundaryLess Data Center. This enables our clients to deliver an infrastructure as a service across data centers and public clouds and enables customers to seamlessly move workloads from Edge to Cloud and manage them in a consistent and efficient model. That's the first building block of our BLE. The second important building block is container, right? We all know today container orchestration is key across hybrid cloud and with micro services and architectures becoming more prominent we see huge search for managing various Kubernetes enrollments with our clients. So our BLCP platform leverages solutions like VMware Tanzu, which is again a Dell company to enable clients manage the multicloud Kubernetes enrollments through a single pane of glass and provide seamless migration and movement of workloads across cloud environments. That's going to be the key in the future with microservices being dominant and every enterprise embracing microservices architectures this becomes very important building block in our overall solution. The third important stuff is BoundaryLess Data Protection. Now that data is all cross in hybrid cloud environment and application actually consume this data it is important to protect the data which is intellectual property and very critical to every business. So with the BLDP platform we ensure that we deliver availability, solidarity, security and reliability of cloud adoption increasingly and rapidly across multicloud platforms. So our solution leverages the DTC of Dell and other existing Dell storages and data production solutions to offer seamless and right cost models which will be very critical for any cloud transformation and schedules as we move forward. The fourth point which I was talking about is BLCE. This is basically a cloud exchange where in a hybrid cloud environment you need to establish connectivities across PaaS and SaaS platforms as well as on-premise networks to provide seamless access to data and the workloads which are in multicloud scenarios. So that's about BLCE. With respect to BLIP it is an integration platform. Today we are in a software defined world and when I talk about providing a single pane of glass solution it is important for us to have an integration platform where I can bring all EPIs together and do northbound and southbound integrations with the architectures of clients and the cloud providers to spin off workloads, to commission, decommission and provide a seamless consumption experience to clients across multiple hyperscalers and on-premise infrastructure. >> Thank you for that summary. I think you hit on all the big trends. I want to go back to you Rajesh 'cause you said that this is a really unique time. You've been in the business for a very long time. You've seen a lot of other transformations and you've seen a lot of big trends. Why is this one different? What makes where we are today such a unique point in time in this IT industry journey? >> Excellent. I think I would say we are in a period of what is called an enforced innovation. While most of the time transformation in IT has been very, very sequential or continuous I think we are seeing an order of shift in the transformation and this whole situation is forcing everyone to accelerate the pace of innovation and transformation. There are two key priorities for every organization in this time. One, build resilient operations and second employee safety. These two parameters have forced the organization to look at their businesses differently, look at their IT infrastructure differently and created a sort of opportunity you can say which is ripe for Wipro's BoundaryLess Enterprise because there are no boundaries. People are working from home. They're no longer in an office confined or boundary. So that's smart. Coming back we are seeing an accelerated innovation. That means our partnership to deliver customer transformation at scale becomes all the more important. Bringing all the good technologies of Dell on one side and combining it Wipro's size, scale and services help us lead in the marketplace for customer transformation. And what's more, we are adding our Dell financial services solutions as Dell Tech on demand to enable all this to be consumed as a service and with flexible payment options which Wipro helps us translate it to customer offerings. >> That's great. Utpal, I want to go to you and get your perspective on how customers, in terms of this boundaryless, how things have changed since March 15th which at least here in the US, I don't know if in India it was on the same date when everything basically got shut down. So it was this light switch moment. Everybody worked from home, no planning, no thought like ready, set, go to now we're six, seven, eight months into this thing and clearly we're it's a marathon not a sprint and even if we go back to some semblance of what was the old normal the new normal is going to be different and everyone is not going to go back to work full time like they did before. So how, from a customer perspective, from a technology implementation perspective and from an initiative and getting this stuff done how has that changed pre-COVID then oh my goodness, it's the light switch moment and now it's, hey, we're in this for the long term. >> Yeah. I think Rajesh did hit upon that a little bit. This is truly that moment where it was a forced innovation. Some of it was happening anyways and it was bound to happen but I think the COVID kind of accelerated all of it. What has impacted is it all started with, okay, how do we enable work from home? And that is when the whole BoundaryLess infrastructure, the virtual desk solutions and all of that started getting impact. I think after that most companies have realized that this is not a short term fix. It is a longterm it's going to be here for staying so they wanted to have a longterm fix so they wanted to come in with innovation but at the same time from a business perspective they've had impact in business so they wanted very creative business models for them to get set with the technology innovation quicker but they didn't want to do it in a traditional way of paying it all upfront and moving it to that. So that is where the creativity in terms of joint innovation which we did with Dell, in flexible payment options, bringing in some kind of an asset lease model and things like that have gained traction. A lot more conversations are around we want to transform help us find a way to make the transformation sooner with maybe less investment upfront and find a way to fund this from the future savings we'll get so that we can be ready for the future without necessarily impacting the bottom line today. All of that has changed, I would say in summary, has accelerated the adoption and the rate of change but it has also led to all of us thinking some creative business models and new approaches to doing business. >> Right, right. Satish back to you. What are the big conflicts that always exist? There's innovation versus security, right? And enabling innovation and giving people more power, more tools, more data to do things at the same time now your tax surface has increased you don't necessarily have everybody locked down on their home infrastructure and they were forced into this. When people are talking about digital transformation, how do they continue to drive forward and how are you helping them on innovation and enabling innovation at the same time as you talked about keeping the data protected and really thinking about business resiliency and continuity in this to increase the tax surface not only because of mobile, but now with the working from home thing? It's increased exponentially. >> Yeah. So I would just take an example of how Wipro handled this pandemic when it hit us and what solutions we get. So let me just give you a perspective. As we all know the current pandemic has disrupted many industries and we were no exception. Basically COVID has brought to the forefront many crucial factors in terms of business continuity process, the quality of employee experience and the automation connected with the employees. So while we enable our employees to connect, collaborate, and communicate with ease from anywhere from any device in a secure way with a consistent user experience powered by Wipro LiVE Workspace platform which actually takes care of delivering a seamless onboarding of user via the Wipro LiVE Workspace platform and consume all the services the way they used to traditionally consume when they were working from office? So this is something which is the power of Wipro LiVe Workspace platform we have implemented to deliver a seamless employee experience access to the workspaces. That's one but also there are some learnings. When we implemented the solutions on the flip side as businesses we must also acknowledge and be cognizant of the fact that employees are trying hard to juggle between frequent interruptions at home and notifications from various applications we receive both on corporate and personal devices. Basically in a nut shell it is difficult to have the culture of corporate to be working from home. Basically that's another big learning. While all of us are adjusting to this new normal we are in constant touch with our employees and trying to improve the overall employee connect and experience. From a solution perspective let me just give you what we actually did. We have close to 175,000 employees across the globe. Suddenly started working from home post lockdown. What does this mean? The traffic pattern suddenly changed the directions which were traditionally moving on a East to West direction started moving North to South. Basically this means a 100% of the workforce in a corporate started coming from the internet to access the corporate infrastructure and then gain access to the customer network. So basically we had to quickly swing in with our solutions and got our engineering teams to re engineer and tweet the infrastructure and security architecture to this new normal. By leveraging our Wipro BLE and video architectures which is powered by Dell VxRail, NSX we were able to spin off and build capacity on on-prem as well as on cloud in less than 24 hours post one got approvals from the client. Lastly we also deployed a back to work IoT solution which helped our employees to get back to work safely. Basically the solution offers various security parameters. Apart from traditional COVID updates it also helps in scanning the employees' temperatures, employee movement within the office premises, bundled with video analytics and enables secure touch less access to the ODCs for employees who are coming back to work. So we are putting all these solutions together and we pretty much seamlessly were able to navigate from the pandemic situation and get our business back to operations in a matter of days. >> 175,000 People. It's really interesting to think about how that network traffic completely changed from inside the firewalls to everything coming from the outside. It's a lot of people to get working from home right away so congratulations on that. As we come to a close Rajesh, I want to come back to you and talk about again, partnership in the age of this rapid acceleration of technology adoption, new technology move. We talked about the work from home. We've talked about cloud. We haven't talked very much about there's this other big thing that's coming down the pike which is 5G and IoT and kind of this entirely new scale of communication that's machine to machine, not person to person and now these connected devices. The amount of traffic continues to go up into the right at an accelerating rate. Tell us a little bit about the meaningfulness of having a partnership like Wipro that you guys can build solutions around new cutting edge technologies and have that real close connection with the customer or with all the supporting services. >> We'd love to. And maybe first I'll give you a perspective on how our employee base started working from home. Some other statistics that they wanted to show maybe add on towards what Satish said. We transitioned 120,000 employees. Twice the normal to work from home within two weeks and every day we are running something like 20,000 meetings and 16 million zoom minutes per day. That's the kind of traffic IT has seen. >> 16 million zoom minutes per day? >> Zoom minutes per day. >> Wow. >> That's the kind of traffic and our VPN traffic user load just tripled. At software or IT we call Dell digital. It was just a smooth and seamless experience. Now coming back, you said rightly. While we have partnered so far to deliver to the solution which are here today and the customers needs which are here today, what are we going to do for the future needs especially ie 5G IoT? We believe as a corporation that Edge is going to be the next wave of innovation. And next way our customers will benefit. Therefore connectivity to Edge via 5G becomes critical. IoT devices and managing the traffic and contain it there itself rather than flowing it back to data center becomes critical. As an example Wipro and Dell technologies are using our hyper converge solutions along with VMware telco and software for a European telco to provide automation and AI to deliver rapid results for the customer. So these are just early parts of it. We are partnering with Wipro to build solutions around 5G as well as telecom related innovation that'll come into the picture. IoT Satish spoke about a simple example of employee attendance. Imagine this is a need which will only accelerate from every organization, multiply it with the automation and AI that needs to be built into machines and feeding all the data back to drive some intelligence and refine the processes, refine the business outcomes. So I think we are working together on many such things and what's important is in all this, when the universe just explodes to devices and millions of devices, security becomes a paramount feature and we are working with Wipro to build what is called an embedded security into each of the solutions that we are designing. Security cannot be an afterthought or a bolt on it's becoming an integral part of the overall solution as we move towards the Edge. >> Yeah, right. And I think as Satish talked about all the distractions and notifications there're a lot of great opportunities for applied AI too to help people know what to do next. It's hard to be context switching all the time, not only on your work, but also the spouses working from home, the kids are doing homeschooling. It's not an optimal environment at all. Gentlemen thank you for your time. Congratulations on your partnership and hope you have a fantastic Dell Tech World. Sorry we can't be in person but this is not too bad. >> Thank you. >> Jeff >> Thank you >> Thank you Utpal, thank you Satish for your partnership. >> All right. Thank you gentlemen. >> Thank you. >> Alright. Stay with us for continuing coverage of Dell Technologies World 2020. I'm Jeff Frick. Thanks for watching. (upbeat music)

>> connecting with thought leaders all around the world, this is a CUBE Conversation. Hi, everybody this is Dave Vellante of theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SEER model, the most popular SEER model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O our open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these great Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

>> Starting the record, Dave in five, four, three. Hi, everybody this is Dave Vellante, theCUBE, and welcome back to my CXO series. I've been running this through really since the start of the COVID-19 crisis to really understand how leaders are dealing with this pandemic. Sri Ambati is here, he's the CEO and founder of H20. Sri, it's great to see you again, thanks for coming on. >> Thank you for having us. >> Yeah, so this pandemic has obviously given people fits, no question, but it's also given opportunities for companies to kind of reassess where they are. Automation is a huge watchword, flexibility, business resiliency and people who maybe really hadn't fully leaned into things like the cloud and AI and automation are now realizing, wow, we have no choice, it's about survival. Your thought as to what you're seeing in the marketplace. >> Thanks for having us. I think first of all, kudos to the frontline health workers who have been ruthlessly saving lives across the country and the world, and what you're really doing is a fraction of what we could have done or should be doing to stay away the next big pandemic. But that apart I think, I usually tend to say BC is before COVID. So if the world was thinking about going digital after COVID-19, they have been forced to go digital and as a result, you're seeing tremendous transformation across our customers, and a lot of application to kind of go in and reinvent their business models that allow them to scale as effortlessly as they could using the digital means. >> So, think about, doctors and diagnosis machines, in some cases, are helping doctors make diagnoses, they're sometimes making even better diagnosis, (mumbles) is informing. There's been a lot of talk about the models, you know how... Yeah, I know you've been working with a lot of healthcare organizations, you may probably familiar with that, you know, the Medium post, The Hammer and the Dance, and if people criticize the models, of course, they're just models, right? And you iterate models and machine intelligence can help us improve. So, in this, you know, you talk about BC and post C, how have you seen the data and in machine intelligence informing the models and proving that what we know about this pandemic, I mean, it changed literally daily, what are you seeing? >> Yeah, and I think it started with Wuhan and we saw the best application of AI in trying to trace, literally from Alipay, to WeChat, track down the first folks who were spreading it across China and then eventually the rest of the world. I think contact tracing, for example, has become a really interesting problem. supply chain has been disrupted like never before. We're beginning to see customers trying to reinvent their distribution mechanisms in the second order effects of the COVID, and the the prime center is hospital staffing, how many ventilator, is the first few weeks so that after COVID crisis as it evolved in the US. We are busy predicting working with some of the local healthcare communities to predict how staffing in hospitals will work, how many PPE and ventilators will be needed and so henceforth, but that quickly and when the peak surge will be those with the beginning problems, and many of our customers have begin to do these models and iterate and improve and kind of educate the community to practice social distancing, and that led to a lot of flattening the curve and you're talking flattening the curve, you're really talking about data science and analytics in public speak. That led to kind of the next level, now that we have somewhat brought a semblance of order to the reaction to COVID, I think what we are beginning to figure out is, is there going to be a second surge, what elective procedures that were postponed, will be top of the mind for customers, and so this is the kind of things that hospitals are beginning to plan out for the second half of the year, and as businesses try to open up, certain things were highly correlated to surgeon cases, such as cleaning supplies, for example, the obvious one or pantry buying. So retailers are beginning to see what online stores are doing well, e-commerce, online purchases, electronic goods, and so everyone essentially started working from home, and so homes needed to have the same kind of bandwidth that offices and commercial enterprises needed to have, and so a lot of interesting, as one side you saw airlines go away, this side you saw the likes of Zoom and video take off. So you're kind of seeing a real divide in the digital divide and that's happening and AI is here to play a very good role to figure out how to enhance your profitability as you're looking about planning out the next two years. >> Yeah, you know, and obviously, these things they get, they get partisan, it gets political, I mean, our job as an industry is to report, your job is to help people understand, I mean, let the data inform and then let public policy you know, fight it out. So who are some of the people that you're working with that you know, as a result of COVID-19. What's some of the work that H2O has done, I want to better understand what role are you playing? >> So one of the things we're kind of privileged as a company to come into the crisis, with a strong balance and an ability to actually have the right kind of momentum behind the company in terms of great talent, and so we have 10% of the world's top data scientists in the in the form of Kaggle Grand Masters in the company. And so we put most of them to work, and they started collecting data sets, curating data sets and making them more qualitative, picking up public data sources, for example, there's a tremendous amount of job loss out there, figuring out which are the more difficult kind of sectors in the economy and then we started looking at exodus from the cities, we're looking at mobility data that's publicly available, mobility data through the data exchanges, you're able to find which cities which rural areas, did the New Yorkers as they left the city, which places did they go to, and what's to say, Californians when they left Los Angeles, which are the new places they have settled in? These are the places which are now busy places for the same kind of items that you need to sell if you're a retailer, but if you go one step further, we started engaging with FEMA, we start engaging with the universities, like Imperial College London or Berkeley, and started figuring out how best to improve the models and automate them. The SaaS model, the most popular SaaS model, we added that into our Driverless AI product as a recipe and made that accessible to our customers in testing, to customers in healthcare who are trying to predict where the surge is likely to come. But it's mostly about information right? So the AI at the end of it is all about intelligence and being prepared. Predictive is all about being prepared and that's kind of what we did with general, lots of blogs, typical blog articles and working with the largest health organizations and starting to kind of inform them on the most stable models. What we found to our not so much surprise, is that the simplest, very interpretable models are actually the most widely usable, because historical data is actually no longer as effective. You need to build a model that you can quickly understand and retry again to the feedback loop of back testing that model against what really happened. >> Yeah, so I want to double down on that. So really, two things I want to understand, if you have visibility on it, sounds like you do. Just in terms of the surge and the comeback, you know, kind of what those models say, based upon, you know, we have some advanced information coming from the global market, for sure, but it seems like every situation is different. What's the data telling you? Just in terms of, okay, we're coming into the spring and the summer months, maybe it'll come down a little bit. Everybody says it... We fully expect it to come back in the fall, go back to college, don't go back to college. What is the data telling you at this point in time with an understanding that, you know, we're still iterating every day? >> Well, I think I mean, we're not epidemiologists, but at the same time, the science of it is a highly local response, very hyper local response to COVID-19 is what we've seen. Santa Clara, which is just a county, I mean, is different from San Francisco, right, sort of. So you beginning to see, like we saw in Brooklyn, it's very different, and Bronx, very different from Manhattan. So you're seeing a very, very local response to this disease, and I'm talking about US. You see the likes of Brazil, which we're worried about, has picked up quite a bit of cases now. I think the silver lining I would say is that China is up and running to a large degree, a large number of our user base there are back active, you can see the traffic patterns there. So two months after their last research cases, the business and economic activity is back and thriving. And so, you can kind of estimate from that, that this can be done where you can actually contain the rise of active cases and it will take masking of the entire community, masking and the healthy dose of increase in testing. One of our offices is in Prague, and Czech Republic has done an incredible job in trying to contain this and they've done essentially, masked everybody and as a result they're back thinking about opening offices, schools later this month. So I think that's a very, very local response, hyper local response, no one country and no one community is symmetrical with other ones and I think we have a unique situation where in United States you have a very, very highly connected world, highly connected economy and I think we have quite a problem on our hands on how to safeguard our economy while also safeguarding life. >> Yeah, so you can't just, you can't just take Norway and apply it or South Korea and apply it, every situation is different. And then I want to ask you about, you know, the economy in terms of, you know, how much can AI actually, you know, how can it work in this situation where you have, you know, for example, okay, so the Fed, yes, it started doing asset buys back in 2008 but still, very hard to predict, I mean, at this time of this interview you know, Stock Market up 900 points, very difficult to predict that but some event happens in the morning, somebody, you know, Powell says something positive and it goes crazy but just sort of even modeling out the V recovery, the W recovery, deep recession, the comeback. You have to have enough data, do you not? In order for AI to be reasonably accurate? How does it work? And how does at what pace can you iterate and improve on the models? >> So I think that's exactly where I would say, continuous modeling, instead of continuously learning continuous, that's where the vision of the world is headed towards, where data is coming, you build a model, and then you iterate, try it out and come back. That kind of rapid, continuous learning would probably be needed for all our models as opposed to the typical, I'm pushing a model to production once a year, or once every quarter. I think what we're beginning to see is the kind of where companies are beginning to kind of plan out. A lot of people lost their jobs in the last couple of months, right, sort of. And so up scaling and trying to kind of bring back these jobs back both into kind of, both from the manufacturing side, but also lost a lot of jobs in the transportation and the kind of the airlines slash hotel industries, right, sort of. So it's trying to now bring back the sense of confidence and will take a lot more kind of testing, a lot more masking, a lot more social empathy, I think well, some of the things that we are missing while we are socially distant, we know that we are so connected as a species, we need to kind of start having that empathy for we need to wear a mask, not for ourselves, but for our neighbors and people we may run into. And I think that kind of, the same kind of thinking has to kind of parade, before we can open up the economy in a big way. The data, I mean, we can do a lot of transfer learning, right, sort of there are new methods, like try to model it, similar to the 1918, where we had a second bump, or a lot of little bumps, and that's kind of where your W shaped pieces, but governments are trying very well in seeing stimulus dollars being pumped through banks. So some of the US case we're looking for banks is, which small medium business in especially, in unsecured lending, which business to lend to, (mumbles) there's so many applications that have come to banks across the world, it's not just in the US, and banks are caught up with the problem of which and what's growing the concern for this business to kind of, are they really accurate about the number of employees they are saying they have? Do then the next level problem or on forbearance and mortgage, that side of the things are coming up at some of these banks as well. So they're looking at which, what's one of the problems that one of our customers Wells Fargo, they have a question which branch to open, right, sort of that itself, it needs a different kind of modeling. So everything has become a very highly good segmented models, and so AI is absolutely not just a good to have, it has become a must have for most of our customers in how to go about their business. (mumbles) >> I want to talk a little bit about your business, you have been on a mission to democratize AI since the beginning, open source. Explain your business model, how you guys make money and then I want to help people understand basic theoretical comparisons and current affairs. >> Yeah, that's great. I think the last time we spoke, probably about at the Spark Summit. I think Dave and we were talking about Sparkling Water and H2O or open source platforms, which are premium platforms for democratizing machine learning and math at scale, and that's been a tremendous brand for us. Over the last couple of years, we have essentially built a platform called Driverless AI, which is a license software and that automates machine learning models, we took the best practices of all these data scientists, and combined them to essentially build recipes that allow people to build the best forecasting models, best fraud prevention models or the best recommendation engines, and so we started augmenting traditional data scientists with this automatic machine learning called AutoML, that essentially allows them to build models without necessarily having the same level of talent as these Greek Kaggle Grand Masters. And so that has democratized, allowed ordinary companies to start producing models of high caliber and high quality that would otherwise have been the pedigree of Google, Microsoft or Amazon or some of these top tier AI houses like Netflix and others. So what we've done is democratize not just the algorithms at the open source level. Now, we've made it easy for kind of rapid adoption of AI across every branch inside a company, a large organization, also across smaller organizations which don't have the access to the same kind of talent. Now, third level, you know, what we've brought to market, is ability to augment data sets, especially public and private data sets that you can, the alternative data sets that can increase the signal. And that's where we've started working on a new platform called Q, again, more license software, and I mean, to give you an idea there from business models endpoint, now majority of our software sales is coming from closed source software. And sort of so, we've made that transition, we still make our open source widely accessible, we continue to improve it, a large chunk of the teams are improving and participating in building the communities but I think from a business model standpoint as of last year, 51% of our revenues are now coming from closed source software and that change is continuing to grow. >> And this is the point I wanted to get to, so you know, the open source model was you know, Red Hat the one company that, you know, succeeded wildly and it was, put it out there open source, come up with a service, maintain the software, you got to buy the subscription okay, fine. And everybody thought that you know, you were going to do that, they thought that Databricks was going to do and that changed. But I want to take two examples, Hortonworks which kind of took the Red Hat model and Cloudera which does IP. And neither really lived up to the expectation, but now there seems to be sort of a new breed I mentioned, you guys, Databricks, there are others, that seem to be working. You with your license software model, Databricks with a managed service and so there's, it's becoming clear that there's got to be some level of IP that can be licensed in order to really thrive in the open source community to be able to fund the committers that you have to put forth to open source. I wonder if you could give me your thoughts on that narrative. >> So on Driverless AI, which is the closest platform I mentioned, we opened up the layers in open source as recipes. So for example, different companies build their zip codes differently, right, the domain specific recipes, we put about 150 of them in open source again, on top of our Driverless AI platform, and the idea there is that, open source is about freedom, right? It is not necessarily about, it's not a philosophy, it's not a business model, it allows freedom for rapid adoption of a platform and complete democratization and commodification of a space. And that allows a small company like ours to compete at the level of an SaaS or a Google or a Microsoft because you have the same level of voice as a very large company and you're focused on using code as a community building exercise as opposed to a business model, right? So that's kind of the heart of open source, is allowing that freedom for our end users and the customers to kind of innovate at the same level of that a Silicon Valley company or one of these large tech giants are building software. So it's really about making, it's a maker culture, as opposed to a consumer culture around software. Now, if you look at how the the Red Hat model, and the others who have tried to replicate that, the difficult part there was, if the product is very good, customers are self sufficient and if it becomes a standard, then customers know how to use it. If the product is crippled or difficult to use, then you put a lot of services and that's where you saw the classic Hadoop companies, get pulled into a lot of services, which is a reasonably difficult business to scale. So I think what we chose was, instead, a great product that builds a fantastic brand, that makes AI, even when other first or second.ai domain, and for us to see thousands of companies which are not AI and AI first, and even more companies adopting AI and talking about AI as a major way that was possible because of open source. If you had chosen close source and many of your peers did, they all vanished. So that's kind of how the open source is really about building the ecosystem and having the patience to build a company that takes 10, 20 years to build. And what we are expecting unfortunately, is a first and fast rise up to become unicorns. In that race, you're essentially sacrifice, building a long ecosystem play, and that's kind of what we chose to do, and that took a little longer. Now, if you think about the, how do you truly monetize open source, it takes a little longer and is much more difficult sales machine to scale, right, sort of. Our open source business actually is reasonably positive EBITDA business because it makes more money than we spend on it. But trying to teach sales teams, how to sell open source, that's a much, that's a rate limiting step. And that's why we chose and also explaining to the investors, how open source is being invested in as you go closer to the IPO markets, that's where we chose, let's go into license software model and scale that as a regular business. >> So I've said a few times, it's kind of like ironic that, this pandemic is as we're entering a new decade, you know, we've kind of we're exiting the era, I mean, the many, many decades of Moore's law being the source of innovation and now it's a combination of data, applying machine intelligence and being able to scale and with cloud. Well, my question is, what did we expect out of AI this decade if those are sort of the three, the cocktail of innovation, if you will, what should we expect? Is it really just about, I suggest, is it really about automating, you know, businesses, giving them more agility, flexibility, you know, etc. Or should we should we expect more from AI this decade? >> Well, I mean, if you think about the decade of 2010 2011, that was defined by software is eating the world, right? And now you can say software is the world, right? I mean, pretty much almost all conditions are digital. And AI is eating software, right? (mumbling) A lot of cloud transitions are happening and are now happening much faster rate but cloud and AI are kind of the leading, AI is essentially one of the biggest driver for cloud adoption for many of our customers. So in the enterprise world, you're seeing rebuilding of a lot of data, fast data driven applications that use AI, instead of rule based software, you're beginning to see patterned, mission AI based software, and you're seeing that in spades. And, of course, that is just the tip of the iceberg, AI has been with us for 100 years, and it's going to be ahead of us another hundred years, right, sort of. So as you see the discovery rate at which, it is really a fundamentally a math, math movement and in that math movement at the beginning of every century, it leads to 100 years of phenomenal discovery. So AI is essentially making discoveries faster, AI is producing, entertainment, AI is producing music, AI is producing choreographing, you're seeing AI in every walk of life, AI summarization of Zoom meetings, right, you beginning to see a lot of the AI enabled ETF peaking of stocks, right, sort of. You're beginning to see, we repriced 20,000 bonds every 15 seconds using H2O AI, corporate bonds. And so you and one of our customers is on the fastest growing stock, mostly AI is powering a lot of these insights in a fast changing world which is globally connected. No one of us is able to combine all the multiple dimensions that are changing and AI has that incredible opportunity to be a partner for every... (mumbling) For a hospital looking at how the second half will look like for physicians looking at what is the sentiment of... What is the surge to expect? To kind of what is the market demand looking at the sentiment of the customers. AI is the ultimate money ball in business and then I think it's just showing its depth at this point. >> Yeah, I mean, I think you're right on, I mean, basically AI is going to convert every software, every application, or those tools aren't going to have much use, Sri we got to go but thanks so much for coming to theCUBE and the great work you guys are doing. Really appreciate your insights. stay safe, and best of luck to you guys. >> Likewise, thank you so much. >> Welcome, and thank you for watching everybody, this is Dave Vellante for the CXO series on theCUBE. We'll see you next time. All right, we're clear. All right.

(upbeat music) >> Narrator: Live, from San Diego, California, it's theCUBE! Covering KubeCon, and CloudNativeCon. Brought to you by RedHat, the Cloud Native Computing Foundation, and its ecosystem partners. >> Welcome back, this is theCUBE's fourth year of covering KubeCon and CloudNativeCon. This is the North America show here in San Diego it's 2019, he is John Troyer, I am Stu Miniman, and happy to welcome to the program, first of all, I have Murli Thirumali, who is the co-founder and CEO of Portworx, and Murli, thank you so much for bringing one of your customers on the program, Satish Puranam, who is a Technical Specialist with Ford Motor Company. Gentlemen, thank you so much for joining us. >> Delighted to be here. >> All right, so Satish, we're going to start with you because, you know, the growth of this ecosystem has been phenomenal, there were End Users up on the mainstage, we've already had them, there's over, there's 129 now CNCF End User Participants there, but, you know, bring us in Ford, you know, we were getting ready for this, we're talking, there's so much change going in from, you know, of course, everybody talks about autonomous vehicles, and what there have, but, you know, technology has really embedded itself deeply into a company like Ford, so before we get into all the crew, just, bring us a little about into your world, what's happening, changing, and, you know, what your team does. >> Sure, in like uh, Ford generally has been in like a transformation journey for about the last two years now, that includes like, completely redoing our Data Centers, our Application Portfolio, as part of this monolithic journey, we started our journey with Cloud Foundry, we have been a huge favorite to Cloud Foundry shops for some time. And then, we also would like to start dabbling with like, Kubernetes and things, associated technologies primarily do for like, looking for like, data services, messaging services, lot of the stateful things, right? Cloud Native and like, Kubernetes, and I- Cloud Foundry, I am sorry, Did great wonders for us, for qualified graphs. So what do we do with like, stateful things? And that's what we started dabbling with Kubernetes and things like that. >> Yeah, Satish, if I could, I want to step back one second here, and say, you know, you do a transformation, consolidation, moving from monoliths to microservices, what was the business driver here, was it one day, some executive got up and said, you know, "hey this sounds really cool, go do it", or was there a specific driver in the business that now, your organization needs to respond to? >> I think the business drive is cost efficiency. Like, uh, there were, like, a lot of things that we would have not done, so there's a lot of technical debt we have to pay down, because of various fragmentation and various other things, so it's always about realizing business efficiencies, and most importantly, speed at which we deliver services to our customers internally, so that was the main driving force for our engaging in this transformation journey for like, about the last few years. >> Okay, Murli we'd love to have bring you to this conversation here. You obviously, agility is one of the things I hear most from customers, the driver of what new things. Infrastructure for the longest time, in many ways, it was like a boat anchor of what held us back. >> Murli: Yep. >> Especially you know, our friends in Networking and Storage, it is difficult to change and keep up with, with what's driving there, so bring us uh, bring us up to speed with Portworx and how you fit into Ford and more broadly. >> Yeah, just a quick introduction to Portworx, we've been around for about five years, now, right from the early days of containers and Kubernetes, and you know, we have quite a few customers now in Production, we have about 130 customers, 50 of the uh, the global 2k and so on, many, almost all those customers are in Production, deploying stat significant workloads. The interesting thing about Kubernetes in the last couple of years, especially, is that everybody recognizes it has won the war for orchestrating containers and applications, but the reality is, the customer still has to manage the whole stack, the stack of not just the app but the data itself underneath, and that's kind of the role of Portworx, Portworx is the platform for storage for Kubernetes, and we orchestrate all the underlying storage and the data applications, with that being said, I think one of the things that we've seen that Ford has kind of led the way in, and has been really amazing, is some of the many surprising things that people don't really know about Kubernetes, which has been happening now with customers like Ford for a while, one of them, for example, is just the use of Kubernetes in on-prem applications. Very few people really kind of, they think of Kubernetes as something that was born in the Cloud, and therefore, has kind of really only mushroomed in the Cloud, and you know, the, one of the key things about Kubernetes, and most of our customers are actually on-prem, and it to me is transforming the Data Center. The agility that Satish speaks about, is something that you don't just need because you are operating in the Cloud, you need that for all of your on-prem applications, too, and that's been one of the unique characteristics that we've seen from Ford. >> Yeah, and that's, I mean, you talked about your journey, Satish, you know, the pivotal folks really talk a lot about transformation and agility you know, no matter where your apps were sitting, I'm kind of curious in terms of the storage and the stateful- statefulness of the applications that your working with now, you know, what kind of a, if I looked at it, the diagram, what kind of a set-up would there be? So there's a Portworx layer underneath and beside Kubernetes that's managing some of the storage and some of the replication? Is it then, is the data sitting in a, you know, on a SAN somewhere, is it sitting in the Cloud, I mean, can you kind of describe what a typical application would look like? >> With your typical application, yes we draw storage, we've been drawing storage for the past several years from NetApp as being as the primary source of our data, and then we run on top of that, we run some kind of storage overlays, we dabble with quite a few technologies, including, uh, Rook, NetApp Trident, Uh, Loster, You know I'm like a, it was a journey A journey that we took us, to ultimately lead us to Portworx and we just didn't started with Portworx, but the toughest aspect has been the gravity that the stories bring along with it, and all the things that are, Cloud Native is great but Cloud Native has stayed somewhere and that has to be managed someplace, and we said "Hey, can we do that with Kubernetes?" Right? So, I think we have done a- I won't say an outstanding job but at least we've done a reasonably good job at actually at least wrapping our heads around it and we have quite a few workloads in production that are actually stateful, whether they are Base Systems, uh, there are also like Data Messaging Systems, many cards applications and all that stuff so that has been something that we have been working on for the past few years on our platforms at least. >> Yeah, well I wonder if you could expand a little bit on kind of the application suite you know, "What can we do? What can't we do?" Listen to the keynote this morning I definitely heard it was, if you look at a multi cluster environment, You know, you want to mirror and have the same things there. Well I can't just magically have all the data everywhere and data has gravity and the laws of physics do apply so I can't just automatically replicate terabytes from here to the Cloud or back so help us understand where we are. >> So, you know, one of the, uh, one of the things Satish told me yesterday which I loved was he saying, he said: "Stateful is almost easier than stateless now because of the fact that we have these extensions of Kubenetes." So, one of the things that's been very very impactful is that Kubernetes is now these extensions for managing you know, storage networking and so on, and in fact the way they do that is through an API that just an overlay, so we are an example of an overlay. And so think about it this way, if a customer about 60 percent of our customers are building a platform as their service, in many cases they don't even know what applications are going to be in there, so over our customer base we see the same alphabet soup over and over and over again. Guess what it is, Postgress, Cassandra's, all the databases Redis, right? You know, all of the messaging queues, right? Things like Kafta and uh, you know, Streaming Data, for example, Spark workloads. And so, one of the key things that is happening around with customers particularly on the enterprise side, like large enterprises, they are using all kinds of applications and they're all stateful. I mean they're very few enterprises that are not stateful and they're all running on some kind of a storage substrate that has virtualized the underlying storage. So we run on top of the underlying hardware, but then we're enabled to kind of work with all of the orchestration that Kubernetes provides but we're adding the orchestration of the Data infrastructure as well as the storage itself And I think that's one of the key things that's changed with Kubernetes in the last, I would say, two and a half years is, most people used to think of it as "in the cloud and stateless" but now it's "on-prem and stateful." >> So Satish, one of the things we've talked to customers is their journey of modernizing their applications, it's, there's things that you might build brand-new and are great here but, you know, I'm sure you have thousands of applications and-- >> Satish: Absolutely. >> You know, going from the old way to a brand new thing, there's lot of different ways to get there. Some of it you might need to just-- Where are you with the journey of getting things onto this platform layer that we're talking about? And what will that journey look like for Port? >> Net new apps, anything being new we're talking about writing and like Cloud Native, Twelve factor Apps, like, but anything new, I'm like, anything existing data services, messaging services, what we affectionately call as table stakes services, right? So, which are the Twelve Factor Apps rely on, we are targeting towards Kubernetes. The idea is, "are we there yet?" Probably "no" like We are getting there with along with our partners to put it on the platforms like Kubernetes, right? So, we are also doing a lot of automation orchestration on VMs itself. But the idea is heavy and heavier workloads are going to be lining on Kubernetes platforms, and there will be a lot of work in the upcoming years particularly 2020, where we will be concentrating more on those things and with the continuing growth would be on Twelve Factor, Net New, would be Twelve Factor, Net New, could be in Cloud Foundry, could be in Kubernetes. Time will tell, but uh, that's the guiding philosophy, so to speak, but uh, There's a lot that we have to learn in this journey right now. >> Well I was kind of curious about that Satish, we've talked about an alphabet soup, we've talked about a lot of different projects, and certainly here at KubeCon, the thing about the Cloud Native Computing Foundation is that not that they don't have opinions, but everybody has an opinon, there's lots of different components here, it's not one stack, it's a collection of things that could be put together in several different ways. So you've tried a bunch of different things with storage, I'm actually, I'm interested if there are, if there were kind of surprises or, you know, containerized activity is probably different than I/O activity and storage I/O is probably different than in a virtual machine, the storage itself has some different assumptions built into it, so like, do you have any advise for people? I'm interested in the storage case but also just in, you don't have to evaluate nerworking and security and compliance and a lot of different things. Like, how do you go about approaching this sort of evaluation in this trial; in this journey of when you have-- when you're facing an "alphabet soup" of options? >> I think uh, it all comes down to basic engineering, right? So, what I make, think about "what are your failure points?" I'm like, "could be servers failing, infrastructure, hardware failing" right? So, the basic tendance is that we try to introduce failure as early as possible, like, "what happens if you pull the wire?" and "what happens if the server failure, failure happens?" The question that always comes back is that "is there a way I can compose the same infrastructure so that I can spread it across a couple of failure domains?" I think that was the whole idea of when we started, is like, "can we decompose the problem such that we can actually take advantage of primitives that begged into Kebernetes?" The great thing with CSI, that we're just realizing, before that were all flex drivers, but, how do you actually organize storage in the back end that actually allows you to actually compose this thing on the front end using the Kubernetes primitives. I think that was the process we though. >> John: And CSI is a standard API, >> Correct. >> Yeah, storage API, yeah. >> Exactly. I mean that's what we are relying, we're hoping that it's going to help us with things like, uh, moving compute, uh, to the storage rather than moving storage to the compute. That's one of the evolving, thinking that we're working with. Portworx, we've been working with the community folks from work and a couple of other areas. It's, there's lot to be done here, like we're just in still early days I would say. >> Murli, want to make sure we get out there, Portworx had some updates for this week so what do you say to latest? >> Yeah, so, the updates actually relate to exactly to what Satish was talking about, you know, the idea of, so, container storage has kind of been on it's own journey right? In the early days that John remembers well, it was really providing storage per system, making that data available everywhere. It's then clearly moved to HA being having the High Availability say within the cluster and so on. So, but the data life cycle for the application that's been containerized extends well beyond that so we are making extensions to our own product that are kind of following that path. So, one of the things we launched a few months ago was disaster recovery, DR, which is very very specific to containers, so, container granular DR, so you can kind of you know, take a snapshot, not just of the data, but of the application state as well as the Kubernetes pods back and recover all three of them. At this KubeCon we're announcing two other things. One of them is backup, so our customers, as they make the journey through their app life cycle, inevitably they need to backup their data and we have, again, container granular backup, that will provide all of, by the way, on existing storage. We're not asking anybody to up change, there's underneath their hardware storage substructure. The last thing we're introducing is storage capacity management which is fully automated. You know one of the characteristics of Kubernetes is all of that is "get the person" "get the trouble to get out of the picture," right? The world is going to be automated. Kubernetes is one of the ways people are doing that. And what we have provided is the ability to auto-resize volumes, and auto-resize pods of storage and add more nodes automatically based on policy that is completely automated so that again, these applications, you know when the characteristics of containerized workloads, they aren't predictable; they go up and down and they grow very fast sometimes, and so all of that management, so autopilot, uh, you know, backup DR have now been added in addition to persistent in HA. >> Alright, so before I let you both go, uh, want to talk about 2020? >> So soon. >> Satish, I want to give you a wish. You talked about all the things you'd do the next couple of years, if you could get one thing more out if this ecosystem to make your lives easier for you and your team, you know? What would that be? >> I think standardization on more of these interfaces. Kerbenetes provides a great platform for everybody to interact equally. Uh, more things like CSI, CRI, stuff that's happening in the community. And more standardization will lead to actually, make my life and things and end prizes a lot more easier. Will like to see continue that happening, GPU space looks very interesting, um, so we'll see. That would be my wish at least. >> Alright so Murli, I'm not giving you a wish. You're going to tell me, what should we be looking for from Portworx in participation in, you know, in this community over the next year. >> I think one of the big changes that's happened, really, in the last couple of years that is really kind of achieving a hockey stick is that enterprises are recognizing that stateful apps are really, should be using Kubernetes and can use Kubernetes. So to me, what I predict is that I think, Kubernetes is going to move from not, from just managing applications, to actually managing infrastructure like storage. And so I, you know, my belief is that 2020 is the beginning of where Kubernetes becomes the control plane across the Data Center and Cloud. It's the new control plane. No, what Openstack was aspiring to be many years ago, and that it will be looking upwards to manage applications and downwards to manage infrastructure and, it's not just us who are doing that, folks like VMware with Project Pacific have kind of kind of indicated that that's the direction that we see. So I think it's roll is now much more than just an app orchestrator, it's really going to be the new control plane for infrastructure and apps in the enterprise and in the Cloud. >> Murli, Satish, thank you so much for sharing all the update. >> Thank you >> Pleasure to catch up with both of you >> Thanks. >> Northbound, Southbound, Multi Cloud, theCube is at all of these environments and all the shows. For John Trayer, I'm Stu Miniman as always, thank you for watching theCube.

>>live from Copenhagen, Denmark. It's the Q covering Nutanix dot next 2019. Brought to you by Nutanix >>Welcome back, everyone to the cubes Live coverage of Nutanix dot Next I'm your host Rebecca Knight alongside my co host Stew Minutemen. We have two guests for this segment we have. Mika will lose. She's the art director for Nutanix Thank you so much for coming on the show. >>Thank you for inviting me >>And we have Satish Ramachandran, Global head of design at Nutanix Thank you so much for coming on. So it's always so much fun to talk to really creative people, particularly in this technology world. I want to start the conversation by asking Michael first where you go for inspiration and who do you talk to? What he read? What kinds of things do you look at to inspire you to and then bring them back to your job here in Nutanix. So I strongly >>believe that inspiration come from everywhere. No matter where you go is an architecture or you go to the supermarket and you look on packaging or you read a book and you think about images or even just social media. And there is so much variety of different opinion and different cultures to get inspired from. Even from this conference, we took inspiration from Copenhagen, the city, and from Swiss design or from California and divide in the mid century. I put, like not in construction, but like architecture. Er, um, we created this really Sundwall the supreme the best day ever. And I was actually reading a book with my kids, the diary of a wimpy kid. And I was like, Okay, you know what? We can make something really fun out of it. We can take like a page from a diary and create Sabrina Best day, something like that. >>It was truly everywhere. >>It's really every. >>How about Yusa? Tish >>men? It's two parts, actually. I think one is the inspiration when it comes to the aesthetics of design. So to a large degree, I'm a huge fan off minimalism, everything from Japanese paintings, for example, where with two or three strokes, you have a stark on the water. The Bauhaus movement clean, elegant lines very minimal to the point, and even the Scandinavian architecture, for example, is quite minimalistic and very clean. So that is one angle on what we strive to do in terms off getting to minimal, clean, simple. But in the other portion of inspiration is actually comes from empathy because, you know, it's the you know, I care deeply about the human condition, even pre Nutanix sort of teenage angst that never left me right. And ah, so in a sense, is a lot of empathy. Toe what people are going through in terms of technology, how they're using it. How can we make their lives easier? How can we bring about some joys in their life and to a large degree, the secretary working? You know, I t, um, has bean sort of underserved design wise for many years on de. So there's a lot of inspiration that comes in the form of motivation in order to do something for people there. >>Well, yes, it's a teacher, I'm wondering, can help connect the dots with us. I think of minimalism and obviously ties to this simplicity Nutanix and remember in the early days, talking Nutanix to make something truly simple from a technology standpoint usually has a lot of work, and we've been talking to the executive team about, you know, in this multi cloud, highly disperse. Tear it even harder today. So how does some of those core design principles make their way into into Nutanix is world. >>You want me to talk about the process? You know, I >>think >>the process is quite straightforward. I mean, you start with understanding the space, understanding the experience that exists in the space. You don't start with the feature or the product. That's the first thing you start with the people. So you started with a very human centric manner on. Okay, What are they trying to do? What are they trying to achieve and how do you get them in the simplest possible manner to do that? So we have this thing that we use called intentional our design, which is one off our design principles. Very. How do you get someone who has an intention to fulfill their intention with the least amount of effort? And the effort in the middle is what we label less friction constantly. So we talk about trying to become friction less and so on. So the process for that is you start with the person what they're trying to get done, and >>from there you actually >>work all the Muslims in the organization. So design, basically at that point takes on the role of a facilitator by bringing in, you know, engineering product management design itself together and all in service off the user to create an experience, right? So it starts with, you know, formulating the requirements together with engineering and product management. It's address it, then converging on these things by creating prototypes than testing these things with users and so on and then figuring out really what is essential, what can be thrown out and how to keep it really simple. And that's how we build product, basically. >>So that's so. As you said, it starts with this point of empathy, and that is this collaborative process between the engineers and the artists and design team. How would you say that design is more part of the Nutanix philosophy, just rather than the simple, simple, easy, elegant products itself but the entire company? How would you say it's it's built into the philosophy? I actually think this is >>why Nutanix is so unique in our space because we don't just look at the technology we looking at a whole package of design and technology, the left brain and the right brain together. And it comes from our leadership because, dear, it is the great advocator for design. He's really believing in the importance of it, not just a pretty rap on something, but it's something that is meaningful and and really able to provide a full experience for our customers. >>Yeah, meet me how maybe I love to get you both of your commentary. There's a new AH advertising campaign that was launched. The video was in the keynote yesterday. >>It >>all together now it is very colorful, and it is very diverse and at the same time, even, you know, I'm a technology guy. I will often roll my eyes when I see a certain advertising, but to articulate to the world, it's like, Okay, how does my database and multi cloud and all these things play together? Well, way we anthropomorphized though those technology pieces into people on dhe. You've got photos that you can do there, so bring us inside a little bit as to how that you helped the messaging eso some, you know, pretty complex pieces underneath. >>Yes, we're very excited about this campaign. I have to tell you. We worked very hard to conceptualize it and bring it out to the world. And we were very excited to be able to share it here. That next the thinking behind it. Waas, you know I to world is complex and here in Nutanix, we really try to offer a simple way to remove this complexity. So what is a better way than just take those I t concept and business an application manners and personalize them and make them fun. And when you think about Public Cloud, what do you mean? What does it mean to you? How do you envision it when you think about a database? Do you think about the strongman that carrying the cylinder and you >>make it a >>campaign Maur You humanize it, you make it accessible to people and you make it fun And this is what we're trying to do We're trying to delight. Our customers were trying to empower them to be able to do their business in a better way, and that was our goals provide simplicity, choice and delights. >>And as you said, it's it's this ample anthropomorphizing of this. If you've a database where a person what would go with the database person look like it's the cloud Where Human? Yes, exactly. And it just I think they just >>make make it fun and you make it unique and you create something that is different in our scene. And nothing, That's what we're trying to do. >>How do you work together with the engineers? I mean, I know you said. You gather in a room and you are thinking about the end user. How does the customer experience this? But how do artists and engineers communicate? I mean, is that Is that ever a challenge or >>not? Really? No, not really. Actually, it's, Ah, it's a three legged stool. Basically, there's ah, and you know, if you put marketing in there as well for the awareness piece, which precludes anything that we you know the customer uses, it actually becomes a four legged stool. But in terms of building product, it's a three legged stool, which is product management, and they're trying to figure out what is the product market fit, and that's what they bring to the table. The engineer's coming and as we're dreaming up stuff, they're thinking, Is this stuff buildable or not? You know these guys dreaming way too much, right? And so it is a colonization. So and I think that's the crucible in which the best creativity actually comes out. It's not designing isolation where, you know, design dreams up something and the rest of the folks build it. It really isn't that so. We are, actually, in a sense, the way I see it, we have the glue and we formed the Crucible for the colonization. And and in that, you know, good things come out. >>So we hear you are in Denmark, which is design savvy, fashion forward, food obsessed and eyes cultivating that sense of well being in comfort and coziness. What kinds of things are you going to take with you from this conference itself? What are you seeing? What's interesting to you? And how are you gonna bring that back to Nutanix? >>Honestly, for me, I think it's just the warmth of the people in the community in here. They were so invasive and and and kind. And we got a chance to work with a lot of people when we were building this conference. And and to me it's all about the human connection and I think this is something that I will definitely carry with me when we go back to Nutanix. And we were trying to think about our next dock next conference. And you know how we can bring some of that too there as >>well? Yeah, it's to teach anything on dot next Copenhagen, and you know, you're from Berlin, so you're in Europe and get gets a different, you know, cultural input. I >>think they're still. I think >>there is still some stuff. I think around the accessibility mainly for me, like the hotel we're staying. And, you know, first thing I noticed was, you know, that's bringing on, you know, when you have to open the refrigerator, for example, or the closet door And it, I mean, that first thought was like, you know, they have already designed in the accessibility. And then I liberate that back to product, and I think you know how we doing on accessibility. And of course, you know, everything around you here is pretty inspiring in terms of architecture and so on and so forth. So that's a gimme, really. And you see that a lot of it in Germany so that it isn't as much new, but in terms of the conference, it's very heartening that will come this fire. You know, I don't know. Miami many years ago, which is my first conference, you know, we were like all of 600 people, and now we are 4500 here. So in a sense, it's very heartening. And people seem to embrace the, you know, the vision that we're putting foot. Yeah, you know, around convergence off many, many things. >>How deeply technical are both of you? Um, I understand. >>I understand the technology. I understand the struggle. I understand what we're trying to achieve is a company. It doesn't mean I can go and do a demo on stage, but I think it's important to understand the technology of the company that you work for in order to represent it truly and in order to convey the message that we're trying to tell because we are a storyteller. That's what we do. We take the message and the technology, and we bring it out to our customers. So it's important. >>I'm a dyed in the wool engineer s o. I was I mean, my cases where I was an engineer for a fleet to the kids. You know, you take running engineering teams, that kind of stuff. And then I stumbled upon design. So I have a very deep understanding off engineering and what it takes to build stuff. But I have another side of me which is generally around. Empathy, experiences, you know, human interaction, human behavior. What makes people take what frustrates them, those kinds of things. So for me that we design has beena synthesis off many off my interests, and that's why I fell in love with it and have stuck around. >>One of the biggest issues in Silicon Valley and in the technology industry at large is is the skills and the right people the talent gap? How much of an issue is that for the design teams within these technology companies? Because you are looking for so many different skills people who can grasp the technology but then also have this more creative spark Innis to them to how hard is it to find the right people? I think it's a little bit >>of a challenge, but I think we're very fortunate to have amazing teams that understand technology and design in the connection between them. So I know I feel very fortunate with the people I get to work with. Their very there are amazing. Yeah. >>I mean, it was hard in the beginning when we when Nutanix was 150 people or something on the brown. Nobody knew. So then it was very hard to find the right people and to also simplified the vision and to sell it. I still remember spending with every new hire. I would be the first guy they would talk to. And I spent two years in two hours on a whiteboard, talking of taking borders, a technology problem on translating it into an experiential problem. And speaking to really this is very hard to design for and that's where the challenge lies, right? But what a period of time we have successfully built a brand which is a Nutanix design brand. And we have done a ton of things that I'm actually very proud off establishing relationships with universities, even on the social media, having a website, having a proper blawg, various things. When Now we are recognized in the enterprise space as a place for designers to go and work. And there is a certain combination. I figured out where which makes for a good designer in the space. Because if you take people with too little off a technology background, then the ramp up is very high. S o. If you typically you find somebody who's got done some amount of technology than the prior company or in school. And there are people like that. There are plenty of them. And then they moved on to design. And that seems to be the right mix because they can understand the empathize both on the technology side and also on the design side of things. And that makes for the right combination. >>And it's not >>too bad to find people. >>And I think >>technology can be talked. But I think passion and carrying is that part of it is hard to find >>be innate skills. Yeah, exactly. Great. Well, Miguel and McHale and Satish thank you so much for coming on the Cuba and fun and enlightening a conversation. Thank you so >>much. It's great to be here. Thank you so much. >>Thank you, guys. >>I'm Rebecca Knight for stew Minutemen. Stay tuned for more of the cubes. Live coverage of Nutanix dot Next

(upbeat music) >> Woman Voiceover: From our studios in the heart of Silicon Valley, Palo Alto, California this is a CUBE Conversation. >> Hello and welcome to this special CUBE Conversation here in Palo Alto, California, CUBE Studios, I'm John Furrier, host of theCUBE, here with Sri Ambati. He's the founder and CEO of H20.ai. CUBE Alum, hot start up right in the action of all the machine learning, artificial intelligence, with democratization the role of data in the future, it's all happening with Cloud 2.0, DevOps 2.0, Sri, great to see you. Thanks for coming by. You're a neighbor, you're right down the street from us at our studio here. >> It's exciting to be at theCUBE Com. >> That's KubeCon, that's Kubernetes Con. CUBEcon, coming soon, not to be confused with KubeCon. Great to see you. So tell us about the company, what's going on, you guys are smoking hot, congratulations. You got the right formula here with AI. Explain what's going on. >> It started about seven years ago, and .ai was just a new fad that arrived that arrived in Silicon Valley. And today we have thousands of companies in AI, and we're very excited to be partners in making more companies become AI-first. And our vision here is to democratize AI, and we've made it simple with our open source, made it easy for people to start adapting data science and machine learning in different functions inside their large organizations. And apply that for different use cases across financial services, insurance, health care. We leapfrogged in 2016 and built our first closed source product, Driverless AI, we made it on GPUs using the latest hardware and software innovations. Open source AI has funded the rise of automatic machine learning, Which further reduces the need for extraordinary talent to fill the machine learning. No one has time today, and then we're trying to really bring that automatic machine learning at a very significant crunch time for AI, so people can consume AI better. >> You know, this is one of the things that I love about the current state of the market right now, the entrepreneur market as well as startups and growing companies that are going to go public. Is that there's a new breed of entrepreneurship going on around large scale, standing up infrastructure, shortening the time it takes to do something. Like provisioning. The old AIs, you got to be a PHD. And we're seeing this in data science, you don't have to be a python coder. This democratization is not just a tag line, actually the reality is of a business opportunity. Whoever can provide the infrastructure and the systems for people to do it. It is an opportunity, you guys are doing that. This is a real dynamic. This is a new way, a new kind of dynamic and an industry. >> The three real characteristics on ability to adopt AI, one is data is a team sport. Which means you've got to bring different dimensions within your organization to be able to take advantage of data and AI. And you've got to bring in your domain scientists, work closely with your data scientists, work closely with your data engineers, produce applications that can be deployed, and then get your design on top of it that can convince users or strategists to make those decisions that data is showing up So that takes a multi-dimensional workforce to work closely together. The real problem in adoption of AI today is not just technology, it's also culture. So we're kind of bringing those aspects together in formal products. One of our products, for example, Explainable AI. It's helping the data scientists tell a story that businesses can understand. Why is the model deciding I need to take this test in this direction? Why is this model giving this particular nurse a high credit score even though she doesn't have a high school graduation? That kind of figuring out those democratization goes all the way down. Why is the model deciding what it's deciding, and explaining and breaking that down into English. And building a trust is a huge aspect in AI right now. >> Well I want to get to the talent, and the time, and the trust equation on the next talk, but I want to get the hard news out there. You guys have some news, Driverless AI is one of your core things. Explain the news, what's the big news? >> The big news has been that... AI's a money ball for business, right? And money ball as it has been played out has been the experts were left out of the field, and algorithms taking over. And there is no participation between experts, the domain scientists, and the data scientists. And what we're bringing with the new product in Driverless AI, is an ability for companies to take our AI and become AI companies themselves. The real AI race is not between the Googles and the Amazons and the Microsofts and other AI companies, AI software companies. The real AI race is in the verticals and how can a company which is a bank, or an insurance giant, or a healthcare company take AI platforms and become, take the data and monetize the data and become AI companies themselves. >> Yeah, that's a really profound statement I would agree with 100% on that. I think we saw that early on in the big data world around Hadoop, well Hadoop kind of died by the wayside, but Dave Vellante and the WikiBon team have observed, and they actually predicted, that the most value was going to come from practitioners, not the vendors. 'Cause they're the ones who have the data. And you mentioned verticals, this is another interesting point I want to get more explanation from you on, is that apps are driven by data. Data needs domain-specific information. So you can't just say "I have data, therefore magic happens" it's really at the edge of the domain speak or the domain feature of the application. This is where the data is, so this kind of supports your idea that the AI's about the companies that are using it, not the suppliers of the technology. >> Our vision has always been how we make our customers satisfied. We focus on the customer, and through that we actually make customer one of the product managers inside the company. And the doors that open from working very closely with some of our leading customers is that we need to get them to participate and take AIs, algorithms, and platforms, that can tune automatically the algorithms, and have the right hyper parameter optimizations, the right features. And augment the right data sets that they have. There's a whole data lake around there, around data architecture today. Which data sets am I not using in my current problem I'm solving, that's a reasonable problem I'm looking at. That combination of these various pieces have been automated in Driverless AI. And the new version that we're now bringing to market is able to allow them to create their own recipes, bring their own transformers, and make an automatic fit for their particular race. So if you think about this as we built all the components of a race car, you're going to take it and apply it for that particular race to win. >> John: So that's the word driverless comes in. It's driverless in the sense of you don't really need a full operator, it kind of operates on its own. >> In some sense it's driverless. They're taking the data scientists, giving them a power tool. Historically, before automatic machine learning, driverless is in the umbrella of machine learning, they would fine tune, learning the nuances of the data, and the problem at hand, what they're optimizing for, and the right tweaks in the algorithm. So they have to understand how deep the streets are going to be, how many layers of deep learning they need, what variation of deep learning they should put, and in a natural language crossing, what context they need. Long term shot, memory, all these pieces they have to learn themselves. And there were only a few grand masters or big data scientists in the world who could come up with the right answer for different problems. >> So you're spreading the love of AI around. >> Simplifying that. >> You get the big brains to work on it, and democratization means people can participate and the machines also can learn. Both humans and machines. >> Between our open source and the very maker-centric culture, we've been able to attract some of the world's top data scientists, physicists, and compiler engineers. To bring in a form factor that businesses can use. One data scientist in a company like Franklin Templeton can operate at a level of ten or hundreds of them, and then bring the best in data science in a form factor that they can plug in and play. >> I was having a concert with Kent Libby, who works with me on our platform team. We have all this data with theCUBE, and we were just talking, we need to hire a data scientist and AI specialist. And you go out and look around, you've got Google, Amazon, all these big players spending between 3-4 million per machine learning engineer. And that might be someone under the age of 30 with no experience. So the talent bore is huge. The cost to just hire, we can't hire these people. >> It's a global war. There's talent shortage in China, there's talent shortage in India, there's talent shortage in Europe, and we have offices in Europe and India. There's a talent shortage in Toronto and Ottawa. So it's a global shortage of physicists and mathematicians and data scientists. So that's where our tools can help. And we see Driverless AI as, you can drive to New York or you can fly to New York. >> I was talking to my son the other day, he's taking computer science classes in night school. And it's like, well you know, the machine learning in AI is kind of like dog training. You have dog training, you train the dog to do some tricks, it does some tricks. Well, if you're a coder you want to train the machine. This is the machine training. This is data science, is what AI possibility is there. Machines have to be taught something. There's a base input, machines just aren't self-learning on their own. So as you look at the science of AI, this becomes the question on the talent gap. Can the talent gap be closed by machines? And you got the time, you want speed, low latency, and trust. All these things are hard to do. All three, balancing all three is extremely difficult. What's your thoughts on those three variables? >> So that's why we brought AI to help with AI. Driverless AI is a concept of bringing AI to simplify. It's an expert system to do AI better. So you can actually give to the hands of the new data scientists, so you can perform at the power of an advanced data scientist. We're not disempowering the data scientist, the part's still for a data scientist. When you start with a confusion matrix, false positives, false negatives, that's something a data scientist can understand. When you talk about feature engineering, that's something a data scientist can understand. And what Driverless AI is really doing is helping him do that rapidly, and automated on the latest hardware, that's where the time is coming into. GPUs, FPGAs, TPUs, different form of clouds. Cheaper, right. So faster, cheaper, easier, that's the democratization aspect. But it's really targeted at the data scientist to prevent experimental error. In science, the data science is a search for truth, but it's a lot of experiments to get to truth. If you can make the cost of experiments really simple, cheaper, and prevent over fitting. That's a common problem in our science. Prevent bias, accidental bias that you introduce because the data is biased, right. So trying to prevent the flaws in doing data science. Leakage, usually your signal leaks, and how do you prevent those common pieces. That's where Driverless AI is coming at it. But if you put that in a box, what that really unlocks is imagination. The real hard problems in the world are still the same. >> AI for creative people, for instance. They want infrastructure, they don't want to have to be an expert. They want that value. That's the consumerization. >> AI is really the co founder for someone who's highly imaginative and has courage, right. And you don't have to look for founders to look for courage and imagination. A lot of entrepreneurs in large companies, who are trying to bring change to their organizations. >> Yeah, we always say, the intellectual property game is changing from protocols, locked in, patented, to you could have a workflow innovation. Change one little tweak of a process with data and powerful AI, that's the new magic IP equation. It's in the workflow, it's in the application, it's new opportunities. Do you agree with that? >> Absolutely. The leapfrog from here is businesses will come up with new business processes. So we looked at business process optimization, and globalization's going to help there. But AI, as you rightfully said earlier, is training computers. Not just programming them, you're schooling them. A host of computers that can now, with data, think almost at the same level as a Go player. The world's leading Go player. They can think at the same level of an expert in that space. And if that's happening, now I can transform. My business can run 24 by 7 and the rate at which I can assemble machines and feed it data. Data creation becomes, making new data becomes, the real value that AI can- >> H20.ai announcing Driverless AI, part of their flagship product around recipes and democratizing AI. Congratulations. Final point, take a minute to explain to the folks just the product, how they buy it, what's it made of, what's the commitment, how do they engage with you guys? >> It's an annual license, a software license people can download on our website. Get a three week trial, try it on their own. >> Free trial? >> A free trial, our recipes are open-source. About a hundred recipes, built by grand masters have been made open source. And they can be plugged, and tried. Customers of course don't have to make their software open source. They can take this, make it theirs. And our vision here is to make every company an AI company. And that means that they have to embrace AI, learn it, tweak it, participate, some of the leading conservation companies are giving it back in the open source. But the real vision here is to build that community of AI practitioners inside large organizations. We are here, our teams are global, and we're here to support that transformation of some large customers. >> So my problem of hiring an AI person, you could help me solve that. >> Right today. >> Okay, so anyone who's watching, please get their stuff and come get an opening here. That's the goal. But that is the dream, we want AI in our system. >> I have watched you the last ten years, you've been an entrepreneur with a fierce passion, you want AI to be a partner so you can take your message to wider audience and build monetization around the data you have created. Businesses are the largest, after the big data warlords we have, and data privacy's going to come eventually, but I think businesses are the second largest owners of data they just don't know how to monetize it, unlock value from it, and AI will help. >> Well you know we love data, we want to be data-driven, we want to go faster. Love the driverless vision, Driverless AI, H20.ai. Here in theCUBE I'm John Furrier with breaking news here in Silicon Valley from hot startup H20.ai. Thanks for watching.

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

>>from around the globe. It's the Cube with digital coverage of workplace next made possible by Hewlett Packard Enterprise. >>Hello, everyone. We're here covering workplace next on the Cube For years, you know, we've talked about new ways to work, and it was great thought exercise. And then overnight the pandemic heightened the challenges of creating an effective work force. Most of the executives that we talked to in our survey say that productivity actually has improved since the work from Home Mandate was initiative. But, you know, we're talking not just about productivity, but the well being of our associates and managing the unknown. We're going to shift gears a little bit now. We've heard some interesting real world examples of how organizations are dealing with the rapid change in workplace, and we've heard about some lessons to take into the future. But now we're going to get more practical and look at some of the tools that are available to help you navigate. The changes that we've been discussing and with me to talk about these trends related to the future of work are are are Qadoura, who's the vice president of worldwide sales and go to market for Green Lake at HP Sadat Malik is the VP of I O t and Intelligent Edge at HP and Satish Yarra Valley is the global cloud and infrastructure practice Head at Whip Probe guys welcomes. Good to see you. Thanks for coming on. >>Thanks for having us. >>You're very welcome. Let me start with Sadat. You're coming from Austin, Texas here. So thank you. Stay crazy. As they say in Austin, for the uninitiated, maybe you could talk a little bit about h p E point. Next. It's a strategic component of H p. E. And maybe tell us a little bit about those services. >>Thank you so much for taking the time today. Appreciate everybody's participation here. So absolutely so point Next is HP Services on. This is the 23,000 strong organization globally spread out, and we have a very strong ecosystem of partners that be leveraged to deliver services to our customers. Um, our organization differentiates itself in the market by focusing on digital digital transformation journeys for our customers. For customers looking toe move to a different way off, engaging with its customers, transforming the way its employees work, figuring out a different way off producing the products that it sells to. His customers are changing the way it operationalize these things. For example, moving to the cloud going to a hybrid model, we help them achieve any of these four transformation outcomes. So point next job is toe point. What is next in this digital transformation journey and then partner with our customers to make that happen? So that's what we do. >>Thank you for that. I mean, obviously, you're gonna be seeing a lot of activity around workplace with shift from work from home, changes in the network changes in security. I mean the whole deal. What are some of your top takeaways that you can share with our audience? >>Yeah, they're >>so a lot has been happening in the workplace arena lately. So this is not new, right? This is not something that all of a sudden side happening when Kobe 19 hit, uh, the digital workplace was already transforming before over 19 happened. What over 19 has done is that it has massively accelerated the pace at which this change was happening. So, for example, right remote work was already there before over 19. But now everybody is working remotely so, in many ways, the solution that we have for remote work. They have been strained to appoint, never seen before. Networks that support these remote work environments have been pushed to their limits. Security was already there, right? So security was a critical piece off any off the thinking, any of the frameworks that we had. But now security is pivotal and central. Any discussion that we're having about the workplace environment data is being generated all across the all across the environment that we operated, right? So it's no longer being generated. One place being stored. Another. It's all over the place now. So what Kobe, 19 has done is that the transformation that was already underway in the digital workplace, it has taken that and accelerated it massive. The key take away for me is right that we have to make sure that when we're working with our customers, our clients, we don't just look at the technology aspect of things. We have to look at all the other aspect as well the people in the process aspect off this environment. It is critical that we don't assume that just because the technology is there to address these challenges that I just mentioned. Our people and our processes would be able to handle that as well. We need to bring everybody along. Everybody has different needs, and we need to be able to cater to those needs effectively. So that's my biggest take away. Make sure that the process and the people aspect of things was hand in glove with the technology that we were able to bring to bear here. >>Got it. Thank you. So, ah, let's go to San Francisco, bringing our war to the conversation. You're one of your areas of focus is is HP Green Lake. You guys were early on with the as a service model. Clearly, we've seen Mawr interest in cloud and cloud like models. I wonder if you could just start by sharing. What's Green Lake all about? Where does it fit into this whole workplace? Next, Uh, conversation that we're having? >>Yeah, absolutely. Um HP Green lake effectively is the cloud that comes to your data center to your Coehlo or to your edge, right? We saw with Public Cloud. The public cloud brought a ton of innovations, um, into the sort of hyper scale model. Now, with HP. What we've done is we've said, Look, customers need this level of innovation and this level of, you know, pay as you go economics the, you know, management layer the automation layer not just in a public cloud environment, but also in our customers data center or to the other potential edges or Coehlo scenarios. And what we've done is we've brought together Asada just mentioned the best of our point next services our software management layer as well as H. P. E s rich portfolio of hardware to come together to create that cloud experience. Um, of course, we can't do this without the rich ecosystem around us as well. And so everything from you know, some of our big S I partners like we bro, who also have the virtual desktop expertise or virtual desk that then come together to start helping us launch some of these new workloads supported cloud services such as D. D i eso for my perspective, v. D. I is the most important topic for a lot of our customers right now, especially in sectors like financial services, um, advanced engineering scenarios and health care where they need access to those, uh to their data centers in a very secure way and in a highly cost optimized way as well. >>Well, okay. Thank you. And then let's let's bring in, uh, petition talk a little bit about the ecosystem. I mean, we're pro. That's really kind of your wheelhouse. We've been talking a lot on the cube about moving from an industry of point products to platforms and now ecosystem innovation, Uh, are are mentioned VD I we saw that exploding eso teach. Maybe you could weigh in here and and share with us what you're seeing in the market and specifically around ecosystem. >>As we all know, the pandemic has redefined the way we collaborate to support this collaboration. We have set up huge campuses and office infrastructure In summary, our industry has centralized approach. Now, the very premise of the centralization bringing people together for work has changed. This evolving workspace dynamics have triggered the agency to reimagine the workspace strategy. CEO, CEO S and C H R ose are all coming together to redefine the business process and find new ways off engaging with customers and employees as organizations embrace work from home for the foreseeable future. Customer need to create secure by design workspaces for remote working environments. With the pro virtual disk platform, we can help create such seamless distal workspaces and enable customers to connect, collaborate and communicate with ease from anywhere securely. They're consistent user experience. Through this platform led approach, we are able to utter the market demands which are focused on business outcomes. >>Okay, and this is the specifics of this hard news that you're talking about Video on demand and Citrix coming together with your ecosystem. H p E were pro and again, the many partners that you work with is that correct? >>Well, actually, Dave, we see a strong playoff ecosystem partners coming together to achieve transformative business outcomes. As Arbor said earlier, HP and Wipro have long standing partnership, and today's announcement around HP Green Lake is an extension off this collaboration, where we provide leverage HP Green Leg Andre Pro, which elders platform to offer video as a service in a paper user model. Our aim is to enable customers fast track there. It is still works based transformation efforts by eliminating the need to support upfront capital investments and old provisioning costs while allowing customers to enjoy the benefit off compromise, control, security and compliance. Together, we have implemented our solution across various industry segments and deliver exceptional customer experiences by helping customer businesses in their workspace. Transformation journeys by defining their workspace strategy with an intelligent, platform led approach that enables responsiveness, scalability and resilience. It's known that Wipro is recognized as a global leader in the distal workspace and video I, with HP being a technology leader, enabling us with high level of program ability on integration capabilities. We see tremendous potential to jointly address the industry challenges as we move forward. >>Excellent. Uh, sad. I wanna come back to you. We talk a lot about the digital business, the mandate for digital business, especially with the pandemic. Let's talk about data. Earlier this year, HP announced the number of solutions that used data to help organizations work more productively safely. You know, the gamut talk about data and the importance of data and what you guys were doing there specifically, >>Yeah, that's a great question. So that is fundamental to everything that we're doing in the workplace arena, right? So from a technology perspective that provides us with the wherewithal to be able to make all the changes that we want to make happen for the people in the process side of things. So the journey that we've been on this past year is a very interesting one. Let me share with the audience a little bit of what's been going on on the ground with our customers. Um, what's what's been happening in the field? So when the when Kobe 19 hit right, a lot of our customers were subjected to these shutdown, which were very pervasive, and they had to stop their operations. In many cases, they had to send their employees home. So at that point, HB stepped in the point. Next organization stepped in and helped these customers set up remote work out options, which allowed them to keep their businesses going while they handle these shutdowns. Fast forward. Six months and the shutdown. We're starting to get lifted and our customers were coming back to us and saying to us that Hey, we would now like to get a least a portion off our workforce back to the normal place of work. But we're concerned that if we do that, it's gonna jeopardize their safety because off the infection concerned that were there. So what we did was that we built a cities or five solutions using various types of video analytics and data analysis analysis technologies that allowed these customers to make that move. So these five solutions, uh, let me walk, walk our customers and our clients and audience through those. The first two of these solutions are touchless entry and fever detection. So this is the access control off your premise, right? So to make sure that whoever is entering the building that's in a safe manner and any infection concerned, we stop it at the very get go once the employees inside the workplace, the next thing that we have is a set of two solutions. What one is social distance tracing and tracking, and the other one is workplace alerting. What these two solutions do is that they use video analytics and data technology is to figure out if there is a concern with employees adhering to the various guidelines that are in place on alerting the employees and the employers if there is any infringement happening which could risk overall environment. Finally, we realized right that irrespective off how much technology and process we put in place. Not everybody will be able to come into the normal place of work. So what we have done is that the first solution that we have is augmented reality and visual remote guidance. This solution uses a our technologies allow. People were on site to take advantage of the expertise that resides offsite to undertake complex task task, which could be as complex as overhauling a machine on ah factory floor using augmented reality where somebody off site who's an expert in that machine is helping somebody on site data has become central to a lot of the things that we do. But as I said, technology is one aspect of things. So ultimately the people process technology continuum has to come together to make these solutions real for our customers. >>Thank you, Arwa. We just have just about 30 seconds left and I wonder if you could close on. We're talking about cloud hybrid. Uh, everybody's talking about hybrid. We're talking about the hybrid workplace. What do you see for the for the future over the next 2345 years? >>Absolutely. And I think you're right, Dave. It is, ah, hybrid world. It's a multi cloud world. Ultimately, what our customers want is the choice and the flexibility to bring in the capabilities that drive the business outcomes that they need to support. And that has multiple dimensions, right? It's making sure that they are minimizing their egress costs, right. And many of our on Prem solutions do give them that flexibility. It is the paper use economics that we talked about. It is about our collective capability as an ecosystem to come together. You know, with Citrix and NVIDIA with R s I partner we pro and the rich heritage of HP es services as well as hardware to bring together these solutions that are fully managed on behalf of our customers so that they can focus their staff their i t capabilities on the products and services they need to deliver to their customers. >>Awesome. Guys, I wish we had more time. We got to go day volonte for the cube. Keep it right there. Lots of great more content coming your way. >>Yeah,

(upbeat music) >> Live, from Copenhagen, Denmark. It's theCUBE. Covering Nutanix.NEXT 2019. Brought to you by Nutanix. >> Welcome back everyone to theCUBE's live coverage of Nutanix.NEXT. We are in Copenhagen, Denmark. I'm your host, Rebecca Knight, hosting alongside Stu Miniman. We're joined by Fran Scott. She is a science and engineering presenter. Thanks so much for coming on the show. >> No worries at all. It's good to be here actually. >> So you are a well known face to UK audiences. You are a three times BAFTA nominated science and engineering presenter. Well-known. >> Give her a winner. (laughter) >> You're the Susan Lucci of science. You are the pyrotechnician and you lead the Christmas lectures at the Royal Institute. >> Yeah. I head up the demonstration team at the Royal Institution. We come up with all the science demonstrations, so the visual ways to show the science ideas. I head up that team. We build the demonstrations and we show science to people rather than just tell them about it. >> So mostly, you have a very cool job. (chuckles) >> I love my job. >> I want to hear how you got into this. What was it? What inspired you? >> Oh gosh, two very different questions. In terms of what inspired me, I was very lucky enough to be able to pursue what I love. And I came from a family where answers weren't given out willy-nilly. If you didn't know something, it wasn't a bad thing. It was like a, "Let's look it up. Let's look it up." I grew up in an atmosphere where you could be anything because you didn't have to know what you had to be. You could just have a play with it. I love being hands-on and making things, and I grew up on a farm, so I was quite practical. But I also loved science. Went to university, did neuroscience at university. I enjoyed the learning part but, where I was in terms of the science hierarchy, I found out that once you actually go into a lab, there's a lot of lab work and not much learning straight away, and it was the learning that I loved. And so my friends actually got me into science communication. They took me to the science museum and they were like, "Fran, you will love this." And I was like, "Will I?" And I was like, "You are so right." I got a job at the science museum in London by just approaching someone on that visit and being like, "How do I get a job here?" And they were like, "Well, you got to do this, this, this." I was like, "I can do that." I got the job there and I realized I loved science demonstrations and building stuff. Eventually I just combined that love of science and being practical together. And now I produce and write, build science props and science stage shows. And then it became a thing. (laughter) Hand it to me, I love it. >> So Fran, our audience is very much the technology community. Very supportive of STEM initiatives. Give us a little flavor as to some of the things you're working on. Where is there need for activities? >> I suppose the biggest example of that would be a show that I did a few years ago where there was a big push for new coders within the UK. And I was getting approached time and time again for visual ways to show computer coding. Or programming, as we used to call it back in the day. I didn't have an answer because then, I wasn't a coder. So I was like, "Well, I'll learn. And then I'll figure out a demonstration because this is what I do. So why don't I do it on coding?" And so yeah, I set about. I learnt code. And I came up with an explosions based coding show. Error 404. And we toured around the country with that. Google picked it up and it was a huge success just because it was something that people wanted to learn about. And people were stumped as to how to show coding visually. But because this is what we do day in and day out with different subjects, we could do it with coding just like we do it with physics. >> What do you think is the key? A lot of your audience is kids. >> Yes and family audiences. >> So what is the key to getting people excited about science? >> I think science itself is exciting if people are allowed to understand how brilliant it is. I think some of the trouble comes from when people take the step too big, and so you'd be like, "Hang on but, why is that cool? Why?" Because they don't under... Well they would understand if they were fed to them in a way that they get it. The way I say it is, anyone can understand anything as long as you make the steps to get there small enough. Sometimes the steps are too big for you to understand the amazingness of that thing that's happening. And if you don't understand that amazingness, of course you're going to lose interest. Because everyone around you is going, "Ah, this is awesome, this is awesome!" And you're like, "What? What's awesome?" I think it's up to us as adults and as educators to just try and not patronize the children, definitely not, but just give them those little steps so they can really see the beauty of what it is that we're in awed by. >> One of the things that is a huge issue in the technology industry is the dearth of women in particular, in the ranks of technology and then also in leadership roles. As a woman in science and also showing little girls everywhere all over the UK what it is to be a woman in science, that's a huge responsibility. How do you think of that, and how are you in particular trying to speak to them and say, "You can do this"? >> I've done a lot of research onto this because this was the reason I went into what I'm into. I worked a lot of the time behind the scenes just trying to get the science right. And then I realized there was no one like me doing science presenting. The girl was always the little bit of extra on the side and it was the man who was the knowledgeable one that was showing how to do the science. And the woman was like, "Oh, well that's amazing." And I was like, "Hang on. Let's try and flip this." And it just so happened that I didn't care if it was me. I just wanted a woman to do it. And it just happened that that was me. But now that I'm in that position, one, well I run a business as well. I run a business where we can train other new presenters to do it. It's that giving back. So yes, I train other presenters. I also make sure there's opportunity for other presenters. But I also try, and actually I work with a lot of TV shows, and work on their language. And work on the combination of like, "Okay, so you've got a man doing that, you got women doing this. Let's have a look at more diversity." And just trying to show the kids that there are people like them doing science. There's that classic phrase that, "You can't be what you can't see." So yes, it comes responsibility, but also there's a lot of fun. And if you can do the science, be intelligent, be fun, and just be normal and just enjoy your job, then people go, "Hang on," whether they're a boy or a girl, they go, "I want a bit of that," in terms of, "I want that as my job." And so by showing that, then I'm hopefully encouraging more people to do it. But it's about getting out and encouraging the next generation to do it as well. >> Fran, you're going to be moderating a panel in the keynote later this afternoon. Give our audience a little bit. What brought you to this event? What's going into it? And for those that don't get to see it live, what they're missing. >> I am one lucky woman. So the panel I'm moderating, it's all about great design and I am a stickler for great design. As a scientist, prop-builder, person that does engineering day in and day out, I love something when it's perfectly designed. If there is such a thing as a perfect design. So this panel that we've got, Tobias Manisfitz, Satish Ramachandran, and Peter Kreiner from Noma. And so they all come with their own different aspect of design. Satish works at Nutanix. Peter works at Noma, the restaurant here in Copenhagen. And Tobias, he designs the visual effects for things such as Game of Thrones and Call of Duty. And so yes, they each design things for... They're amazing at their level but in such a different way and for a different audience. I'm going to be questioning them on what is great design to them and what frictionless design means and just sort of picking their amazing brains. >> I love that fusion of technology and design as something they talked about in the keynote this morning. Think of Apple or Tesla, those two things coming together. I studied engineering and I feel like there was a missing piece of my education to really go into the design. Something I have an appreciation for, that I've seen in my career. But it's something special to bring those together. >> Yeah. I think care is brought in mostly because yes, one, I love design. But also I've worked a lot with LEGO. And so I was brought in to be the engineering judge on the UK version of LEGO Masters. Apparently, design in children's builds is the same as questioning the owner of NOMA restaurant. (chuckles) >> So what do you think? Obviously you're doing the panel tomorrow. What is in your mind the key to great design? Because as you said, you're a sucker for anything that is just beautiful and seamless and intuitive. And we all know what great design is when we hold it in our hands or look at it. But it is this very ineffable quality of something that... >> So the panel's later today actually. But in terms of great design, yes, we all know when we have great design. But the trouble comes in creating good design. I think the key, and it's always obvious when you say it out loud, but it's that hand in hand partnership with aesthetics and practicality. You can't have something that's just beautiful. But you can't have something that just works. You need to have it as a mixture of both. It's those engineers talking with the designers, the designers talking with the engineers. The both of them talking with the consumers. And from that, good design comes. But don't forget, good design means they're for different people as well. >> What are some of the most exciting things you're working on, because you are a professional pyrotechnician. We've never had someone like this on theCUBE before. This is amazing. This is a first time ever. >> I was strictly told no fire. >> Yes, thank you. We appreciate that. >> Well at the moment, as I said at the beginning, I'm lucky enough to head up the demo team at the Royal Institution. We are just heading into our Christmas lectures. Now if you don't know these Christmas lectures, they were the first science ever done to a juvenile audience. Back in 1825 was when they started. It's a tradition in the UK and so this year, we're just starting to come up with the demonstrations for them. And this year they presented by Hannah Fry, and so they're going to be on maths and algorithms and how that makes you lucky or does it make you lucky? We've been having some really fun meetings. I can't give away too much, but there definitely be some type of stunt involved. That's all I can say. But there's going to be a lot of building. I really need to get back, get my sore out, get stuff made. >> Excellent. And who is the scientist you most admire? >> Oh my word. >> Living or dead? >> Who is the scientist I most admire? (sighs) I do have... Oh gosh, this is... >> The wheels are churning. >> It's a cheesy one though, but Da Vinci. Just for his multi-pronged approach and the fact that he had so much going on in his brain that he couldn't even get everything down on paper. He'd half draw something and then something else would come to him. >> I had the opportunity of interviewing Walter Isaacson last year, and he loved... It was the, as we talked about, the science and the design and the merging of those. But reading that biography of him, what struck me is he never finished anything because it would never meet the perfection in his mind to get it done. I've seen that in creative people. They'll start things and then they'll move on to the next thing and there. Me as a engineering by training, it's like no, no. You need to finish work. Manufacturing from standpoint, work in progress is the worst thing you could have out there. >> He would be a rubbish entrepreneur. (chuckling) >> Right, but we're so lucky to have had his brain. >> Exactly. I think that's the thing. I think it gives us an insight into what the brain is capable of and what you can design without even knowing you're designing something. >> Well Fran, thank you so much for coming on theCUBE. This was so fun. >> Thanks for having me. >> I'm Rebecca Knight for Stu Miniman. Stay tuned for more of theCUBE's live coverage of .NEXT. (upbeat music)