>> Announcer: From the cube studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a CUBE Conversation. >> Hi, I'm Stu Miniman and welcome to a CUBE Conversation. I'm coming to you from our Boston area studio and looking forward, we're going to be digging into one of my favorite topics and also the community always loves when we have it. Talking about networking, of course. Happy to welcome you to the program. I have two first time guests. First of all, we have Mike Saur. He is a solutions architect of NetDevOps with CCI. And joining us a long time friend of the program. First time on the program, Omar Saltun, who is a leader, product management for Network Services Orchestrator with Cisco. Omar and Mike, thank you so much for joining us. >> Thanks, nice to be here. >> Thank you, sir. >> All right. So Mike, if you could just set up for us, CCI, Cisco partner, give us a little bit about the organization, what you specialize in, what you're known for. And tell us a bit about your role there. >> Sure. CCI systems is a trusted partner for typical mid market size service providers. That's primarily the focus and that's a lot of different areas of the business, cable access, CMTS, security, data center and now this next evolution of adding NetDevOps as that next step for trusted advisor. I've been in my role for about a year now at CCI with a strong passion for automation and finding the right fit tools to solve problems for our customers, whether that's a commercial product or a open source tool. So a lot of different problems out there and no one size fits all. So it's my passion to bring those types of solutions to CCIs customers. >> Wonderful. Mike, I'm hearing a lot of the themes that I'm very familiar with. I'm sure our audience is when we talk about Cisco, when we've gone to Cisco live, we've been in the DevNet zone. So having a lot of discussions about that NetDevOps piece, can you talk to us a little bit more, just the partnership with Cisco. I would love to hear how NetDevOps fits in with what you're doing and how that fits with Cisco too. >> Yeah, I've been working with Cisco on and off for the past 18 months to try to think outside the box. As we know, Network Services Orchestrator was primarily targeted at the large providers that have the investment resources, the programming staff, to be able to do that. So over the years, having various discussions with product management, Cisco and CCI have come together to partner to solve two of the big problems in our space for our customers. As far as the math problem of the investment that's needed to bring up Network Service Orchestrator, and then also the programming piece of that. So not a lot of the providers in the mid market space have that expertise. So CCI and Cisco are really pulling that all together with various trusted partners to bring that to life for them in a shorter timeframe, with more sets of controls, to bring them up to speed faster so that they can it with a martial arts type journey of starting small and integrating over different phases of the life cycle of automation. >> Great. Well, Omar, let's pull you into the discussion here. It tends to be in general from a product standpoint, a little bit easier to grow up market. We want to talk a bit about the mid market, so that Network Services Orchestrator, NSO. Help explain how that really can support the mid tier as Mike was saying. >> Sure, so we were a little crazy, we started at the top and starting to work our way down. So we're well established with tier one service providers, large enterprises, we have good markets penetration there. I think for us, it was a lot of growth opportunity down into the mid market, both on commercial and tier two, tier three service providers. I know that the challenge in NSO is awesome, but it's got a steep learning curve. So, these partnerships like the one here is perfect because it allows mid market customers to access the capability. But at the same time, they have someone to hold their hands. They have partners like CCI, that have both the technical expertise, as well as kind of understanding kind of what customer problems are, what operations and problem scaling look like in mid market, not just a tier one where the different markets, different requirements. >> Mike I would love to get your viewpoint as to what's happening inside your customers. So networking in general, obviously there's always new technologies that they need to integrate, but there's also the skill sets. NetDevOps, of course, helping pull people along to work closer with developers, coding more something we have to talk about. So the mid tier customer specifically, what challenges they face with bring us into some of those conversations, if you would. >> Right, so I preach a lot and talk about the vicious cycle of not automating. They don't have time 'cause they're too busy doing the day to day jobs. And I love to get into that vicious cycle and kind of bust that up and help to kind of think differently why they need to operate their networks differently. And they can take a lot of those tools and techniques from the software world and really help leverage them on their networks. There's just a skills gap right now with the mid market type folks. They're overworked, stressed. And with obviously the growth of IOT, more devices means more work. It's just a volume metric problem that certain automation tools can really make a difference in their world. And that's really what my passion is at, reducing human error, helping those businesses provide more uptime for their end customers and just driving a different way to operate networks in more efficiently in accurate way. >> And part of that... >> Please go ahead on that. >> And part of that is just not. You know those are the technical expertise, but there's also the how do you stitch things together? Any automation strategy is going to have more than one tool. And there's the idea of how do we stitch tools together? How do we build processes? How do we help up-skill customers? Those kinds of things. I mean, this is kind of the all the pieces that come together when you kind of mesh the technology and the apart for capabilities together. That's really what drives successful automation projects, and then get some of those problems solving and added value that we're talking about here. >> Yeah. I mean, Omar, when I think about scale and I think about automation, service fighters, you think would be some of the leading edge for some of that? Maybe just refresh our audience a bit as to how you help them along and how much, they used to kind of build a lot of their own toolings and that's challenging if you have to keep doing it itself. So why do they turn to Cisco for some of these solutions? >> I think two things, one, we build tools that survive scale, right? For NSO, we have customers managing hundreds of thousands of nodes at one time. So there's a scale on performance that comes from building SB class tooling. But the second piece is just understanding, you know, the operational environment service providers, have they have demanding requirements in terms of SLA scale, reg compliance, those kinds of things. And that's really what we've brought to the table is not just tools that have the power and the scale, but kind of understanding what the operational environment is for the typical tier one SP and making sure the tools mentioned to that. >> Michael... Please go ahead. >> Yeah, absolutely. And the idea of that businesses are changing fastly and keeping up with that speed of innovation is very difficult. And not to mention to, I mean, as a trusted partner for our customers, maybe the answer's not Cisco every time to be honest, maybe there's a different tool. So if we have a tool like NSO that could drive other vendors equipment, I think that makes customers feel safer, better, not vendor lock in. So the power that NSO brings is second to none, in my opinion. So I'm just all about flexibility and in solving problems for our customers. And to me, Network Services Orchestrator is that product. But like I said, there's a lot of integrations that need to be done and we need to break it down for these customers and get them to realize the value of it faster instead of the large deployments that you've seen in the tier one type of space. >> Yeah, Mike, you bring up a really good point. When I think traditionally about automation, we take a process or maybe we optimize a process and we automate it, but what companies need today is I need to react fast and I need to be able to make changes in the future if that's needed. So not fossilizing something, but being able to move forward. So it sounds like with NSO, some of your other things that you put together, you're helping customers not only do what they need today, but be ready for the future. Do I have that right? >> Yeah, absolutely. Like I said, it's just another progression of what CCI already is. That trusted advisor, we have the great opportunity that we talk to so many different providers of the same size, same business goals that we bring best in breed. And our talent that we have at CCI is just amazing and that's a passion that we're trying to get out there into the world that, Hey, we have horsepower and we're ready to help. We're about making lives better. So it's exciting. >> Yeah certainly in the mid market, one of the things we see is customers doing less building and more assembly. So in tier one, they have the time and resources to build stuff from scratch, to write services from scratch, those kinds of things. Mid-markets much more of a simply play, taking things off the shelf. No, maybe a little NSO, but it's also paired with a little bit of Ansible, a little bit of Python, and that's how they're going to handle their automation requirements, both, 'cause it's probably faster and probably in the long run, easier to maintain. >> Well, yeah. You bring up a great point, Omar. When I think traditionally that mid market and the channel partner often would be delivering prepackaged solutions. But today's solutions, you still need that a little bit of flexibility, that little bit of programming, they're not going to, throw a team of PhDs on it like some of the largest customers do. But they still need to be able to put things together and make them fit for what they need and ultimately their customers need. >> Yeah, I mean, every automation project it's still a snowflake. You take something or free VPN, right. Everyone does it, but everyone does it differently. There's no better, there's no worse. But if you're going to automate that you kind of start with an 80% solution, but then you need to line it up whether that's customer's infrastructure, their operations, their staff capabilities and those kinds of things. That's kind of getting over the finish line what CCI brings to the table in the mid market, sure. >> Yup. Mike, it's funny. I'm curious. CCI, does it have any relation with CCIE 'cause when we're talking about that skillsets that we need, obviously, you start, you think about Cisco certifications. How do you keep your team up on the latest technologies, making sure that they can be that trusted advisor that your customers need? >> Well, of course it's a combination of different things, classical learning, but I would say one of the big things is our collaboration capabilities. We have experts in many different areas and usually they have a secondary skill set and we collaborate. And a lot of times we make our own internal training that's more specific to our customers. So example, I really try to recommend to customers to move to EVPN technologies, but there's that learning curve that they don't know how to configure them. Next gen ethernet type of technologies for service providers. So by building an EVPN model and NSO, we're empowering them to leverage that sooner, faster with a smart tool like NSO. And that's really, some of the value that we have, we know what most of our customers use. The big guys tend to use layer three VPNs a lot of time. I would say just that a majority of our customers are very L two VPN vase or infrastructure services, and even offering them up to their own customers. So having a somewhat pre-packaged 80% as Omar had mentioned, and nothing's ever really the same all the time, but 80% of it probably is. And then we'll come in and then we can finish off that last 20% to make it come to life for that customer with a little bit of customization. So making it fit for their environment. >> Yeah, it's interesting. One of the biggest challenges out there for anyone is, okay, when do I have to revisit what I had? Is there a new technology? Is there a new way of doing things? So you just laid out like, you know, one way that customers, okay, this is the way I should be in my size thinking about VPN. Anything else? What, what kind of key things should people be hearing and they're saying up, if I have this problem, providers like CCI can help. >> Right. Just trying to increase the health of their network by having consistency checks. Over the years, networks have config wonder. It's very hard to keep that up even in the mid market networks. So the cleaner that your network is, the more uptime you're going to have, the easier it is for your network engineers and allows you to scale. Like I said, the time to businesses is just going rapidly. And being able to empower other teams like say knock or even sales engineering to build those L2VPNs for the customer. If you can build them faster by not escalating tickets to the core engineering team, you serve the customer faster and you freed up those network engineers to maybe be more proactive about building out the future network. Cause right now they're just stuck in that day to day grind. So config consistency, and like primary, like service builds L2, L3 VPN. Those are very popular. And one thing that I always like to challenge customers with is that a lot of times they're like, well, we can do it ourselves. And maybe some of these guys have a developer teams and typically they're more focused on the public facing website, internal apps. And I challenged like maybe you could... but what's your time worth to you? And the amount of man hours that were put into NSO, jumpstart you faster. And a lot of times I think you're going to gain more value in just getting that product that you can customize. 'Cause at the end of the day, it's a developer platform. So you bring it to life in your environment. >> Absolutely, there's so many things now that companies need to make that decision. Can they shift left? Can they push it to the platform? Are there solutions that just make things easier so that you can focus on really the things that are important to run your business and get the best utilization out of your people and the skillsets. Wonderful. Mike, Omar want to give you both, give us the final word takeaways you want people to have regarding kind of the opportunity that they can take advantage of, especially in the mid tier. Mike maybe we'll start with you. >> Yeah, thanks for having me on the show. I am just passionate about getting CCIS name out there. Not only for NetDevOps, but all the other practices that we have at CCI to be that trusted advisor and come talk to us. We have account teams that already, we have systems engineers that are ready. And I feel like one thing leads to another and it snowballs so reach out and I'd love to have a conversation with every single one of them, whether it's a small organization or a large organization, we're here to help. And that's super important to us. >> I think for us, we see automation start, tactically to science project. So ones trying to deal with the pain pointer or dealing with something here frustrated with which is, I think where most folks start. I think that the trick is to work with your peers, talk to your leadership and figure out how you go from science project to strategy and kind of map out the longer journey and be a little thoughtful as you pick tools and figuring out what you want to automate and make sure it has some value to. >> Mike Saur, Omar Sultan, thank you both for joining. Appreciate the update and especially on the CCI and Cisco partnership. >> Thanks too. >> Thank you. Have a great day. >> All right, I'm Stu Miniman and thank you for watching this CUBE conversation. (upbeat music)

(upbeat music) >> Live from Barcelona, Spain. It's theCUBE, covering Cisco live 2020 brought by Cisco, and its ecosystem partners. >> Hello and welcome back to theCUBEs live coverage, here in Barcelona, Spain for Cisco live 2020, I'm John Furrier my cohost Dave Vellante here at theCUBE. The big story is it's not about the infrastructure's it's about the applications. Of course, Cisco has been connecting businesses with routers and gear throughout the years and their history. Got a great guest here Omar Tawakol, who is the Vice President and General Manager of the Contact Center for Cisco, Omar, thanks to have you on. You're a serial entrepreneur, sold your second company. Now here at Cisco leading the charge, a lot of action Contact Center. Sounds like an old school thing. We all know what Contact Centers are, but a lot of action going on there. Tell us what's happening. >> There's a huge amount of energy and focus in the Contact Center. Now. First of all, thank you for having me and really brands are really investing in it. There's, you know, over 22% growth in this category, so a lot of attention is on bringing Contact Center to the cloud. Infusing it with the AI and just making it a lot easier to serve customers with very high, almost unbounded kind of expectations out of the brand. So we need to really help them technically, >> And it's an impact area too for customers because there's real results. We all know the little started out of Microsoft, it was the little tool that came up, the little paper clip and windows, and it became Chatbots. Now we've seen recommendation engines, AI bots have been great. This is accelerates the customer experience in purchasing and support. What's the next level look like? What does it, what's the next milestone? What's the next industry point? >> Well, you know, one of the ones that we're focusing on is this idea of turning your agents into super agents. When you kind of look at automation, there's two ways to go at automation. One is automate the human out, and the other is kind of the opposite. Take the human and make them more accurate, extend the range, allow them to answer questions faster. So that's what we're doing in the Contact Center. And the way we approach that is we say, there's a certain number of tasks, that really shouldn't, that are simple, that should never hit a human. And so if we can put kind of voice bots and Chatbots on the front end and make those really good interactions, you take off the simple stuff. What you're left with is, the human interactions are now going to be, a little bit more complicated. So now you instead use AI, to help listen along with a human and put up suggestions. So for instance, someone's calling in and they're saying, Hey, I'm traveling from California to Barcelona and I'm calling T-Mobile or AT&T and saying, you know, extend my data plan for there, the AI will listen and say, Hey, we looked at your data plan. It's already covered. You don't have to pay anything else in Spain. So that's going to make the customer happy. Typically agent would have to take 17% of the time searching and putting you on hold. The AI can completely cut that off. And so that makes the agent happier, the customer happier. So there's a lot of ground for improving the experience just by applying AI there. >> There's big spectrum in Contact Center experiences, ranging from a totally asynchronous email us and we'll get back to you, you hope, to one that is, you know, somewhat painful, >> Yes. >> with a synchronous experience in a phone call. Different people like different approaches. I personally like to solve my problem on the phone. So, where do you see Cisco being able to take, its customers and the consumers experiences? What do you see in the next five years that looking like? >> Yeah, so basically the three areas of attack. First off, Cisco acquired Voicea, they acquired MindMeld, they acquired a company, so over half a billion in acquisitions over the past 18 months precisely to bring AI to collaboration. But we also partner with Google. We announced the Google CCII partnership, because we wanted best of breed, and proprietary to attack one problem, get to customer solution faster, in the way that customer wants to interact. So if they want to interact kind of in an automated fashion, make that better, sometimes that's not going to work. And the last thing I want to hear is, Agent, right, So we want to do tech, something's not going to work. In early on say transferring you to human, take all the context of the interaction they had given to the human and then suggest to the human, Hey, we think you should tell them that feature for free get to a customer resolution faster. I see this as a five year journey. >> But that started it starting today. Actually that's some of that's happening today where you would have to sit there, agent, agent, they go right away, >> Right. >> Others who maybe don't use your products or they, you know, you go into that endless loop, so you're starting to see improvements but still a lot of upside. I'm sure you'd agree, which is good. That's good news for the marketplace. >> Absolutely. The next part of there is that the phone call finishes, use AI to wrap it up so they don't spend five minutes, trying to type up the wrap up and then coach them, to be able to identify what went well, what didn't, did they comply, so that you can compress the learning because you know the agent churn is high. Reduce the agent churn, get them to learn faster, keep them there longer. All these, of innovations impact, the economics of running a Contact Center. >> And that's the big one. The economics I want to get into that because the impact is, right in the moment, but there's also, impacting the accelerating the journey of the customer, but also providing contextually relevant interactions. You said super agents, the expert. How do you know when to deploy the right talent, at the right time? These are the challenges I'm talking about that impact to the customer journey and where some specific examples are economically impacted. >> Yeah, so talk about customer journey. We acquired a company called CloudCherry in October and I've already integrated the product in, and it's now Webex Experience Management. And the whole insight that we had there, was that a customer's journey doesn't just show up at the Contact Center. They interact with your brand before, hopefully a lot before they ever get to Contact Center in the Contact Center after the Contact Center. So what we needed to do is have the analytics that ties together kind of essentially listening across 17 different channels. So by the time you come to a customer representative, they now know what you've done in other areas. They understand your sentiment and other areas and they can take that into account and say, we see that you've traveled with us before. The other thing that's even more important than that is now you can give to the management team, the full understanding of the journey. So you can tell them, you know what, these two drivers of your experience, perhaps it's average hold time, or perhaps it's the technical expertise of the person on the phone really drive NPS. So if you invest in that a little, you're going to get a much higher NPS. The alternative is what I call kind of the highest paid executive in the room making intuitive decisions which they think are awesome, which typically are not so awesome, but if they actually had the data, >> Yeah. >> It would be a lot more powerful. >> So having that legacy. Having that corpus to tap into. Talk about developer. We're in the dev net zone. A lot of companies have been trying to build, their own homegrown integrations maybe because of a database issue or other stuff. How do you guys look at your customers, when they say I want to build on top of it? >> It's a really good question. We were at a customer innovation board, where all of our customers were together, telling us what they wanted. And we were telling them about the new, set of AI capabilities that are coming out next quarter and almost unanimously when we asked them would you prefer us to first roll out a UI that has an embedded in it and then afterwards give you some APIs or would you prefer just to get the API first and they unanimous said, just give us API first. >> Really. >> We might not even use your interface, for that and I was like, okay, I'm not going to to take it personally. (laugh loudly) >> Good requirements to get out, Right straight with the customer. >> Do you see any industries as really, leading the charge of I think about, I think about retail. I mean it was going to Amazon war room, and you think about Amazon, they basically say here's a finite set of choices. Pick one and you may be lucky, you may not. Okay, boom end of story. But you've got a relationship with that retailer. Do you see any particular industries, airlines or others really leaning into this and predicting doing well? >> Yeah, we've seen quite a few. Where people are really kind of leaning forward, so finance and insurance, cause they have a very high volume of interactions that they have with customers. So getting this right really impacts the NPS and all their economics. Certainly you've seen in retail some innovative examples. We've see some airlines looking at trying to kind of make the journey a little bit smoother. Surprisingly, I've seen a bunch in healthcare, trying to make the patient experience better. Yeah, it's not, I can't say that(mumbles) cutting edge, but they're really putting a lot of an investment, seeing what's happening with other brands, experiences saying, Hey, we should really revolutionize the patient experience too. So this is pretty across the board? >> Well the upside is enormous. I mean you build a relationship through a Contact Center. I mean that's loyalty for life if they're really good at it. >> Yeah, and that's why I like the approach that says, don't try to automate humans out of that, we want to speak to humans and for many, many, many years to come. The human experience in helping. >> Yeah. >> It's just going to be awesome. So instead of just focusing on getting rid of them, make them more effective. >> I want to get your thoughts on your vision around, the industry because if you think about Contact Center, I think telephony old days, the industry used to be Voice Over IP came from the PBXs in the unified communication space, integrated in, and then in comes the cloud. So what is the real game changer, because that kind of just seemed like telephony market trying to be cool the internet, and it just felt kind of clunky to me and then all of a sudden over the past few years, almost a complete resurgence of robust features, new things. What's your vision? Do you agree with that and what's happening? >> I agree. I think the biggest thing that's happening is the expectation on feature velocity, where before the cloud, all these big enterprises were calculating, okay I have to upgrade a certain version, and it's going to cost me a certain amount of money and time, and I have to coordinate with other, kind of partners that I'm involved with. Whereas when you come to the cloud, you just can move a lot faster cause you leave it up to a company like Cisco to take care of rolling out features in the middle of the night and you not even have to worry about it You don't have to pay for it and you enjoy the features. So I think that's really going to change the game in a significant way. The only thing that's changing, cause you mentioned voice is if you think about your kids, they're growing up and there was this two years ago, a child first uttered Alexa before they uttered the parent's name. (loughs loudly) So that is a generation gap. >> Yeah, and it's a full coming spool circle, voice in a whole new way. >> Voice is coming back in a new way. >> Yeah. >> And we're going to enable a different type of interaction because of that. >> Yeah, Of course, we were talking here on theCUBE and it's being converted into metadata. As you know, text transcription, machine learning, is fed by texts and voice. Working together is a new dynamic. What's your thoughts on that? >> Yeah, you have to be completely linked, so now it's not just a blob of audio. I have all the metadata. I have it transcribed. You have NLP to give you an understanding, of the intent of what's happening there. It's searchable, it's linkable. This is going to be a new world here, and of course, as you know, that's what we did a Voicea, so I'm very excited about that. >> I want to tee that up. Congratulations on your acquisition. If someone looks at Cisco and you're fresh to the scene here, you've been an entrepreneur, I'd be like, Cisco really held all these acquisitions. It's going to be hard for them to be competitive. How do you answer that? If someone says that to you and you see them on the street or competitor might say that if someone says if the Cisco, we give thought acquisitions, you guys have done it, you are sold to them. You mentioned the other ones, all those acquisitions coming together. What's that response to that? >> You know you're about to talk to Shree and Amy and what they did is they came to me and they said, I want you to focus on integrated value. So within three months we both integrated deeply into meetings and the Contact Center and we're working on one with Calling. The mentality here is two things, keep the talent, number one, number two, deeply integrate. So it doesn't become a theory about we acquired this company, you really need to show value. to the customer base and that mentality, has been very good for us. If people get energized about that because when you're acquired, you now have this ability to affect hundreds of millions of users on the Webex platform. The faster you integrate to do that, everybody benefits. >> Speed is the new competitive advantage. >> Yes. Omar Thanks for coming on. I know you have a tight schedule. We're going to bring you back in the studio in Palo Alto. >> Thank you for having >> Where we could dive on your business. Thanks for coming in. It's theCUBES coverage I'm John Furrier, Dave Vellante will be right back, after this short break. >> Thank you. Sorry, I got up to soon. (soft music)

>> Man: Live from San Francisco celebrating 10 years of high tech coverage, it's the Cube. (music) Covering VMworld 2019. (music) Brought to you by VMware and it's ecosystem partners. >> And welcome, indeed, here to the cube and our coverage of VMworld 2019. We are in the Moscone Center in San Francisco. They're open, they're back in business and so is VMware. And we're watching the folks stream out from this morning's keynote session, Pat Gelsinger hosting that session. And it was an impressive setup to say the least. Thousands packing that ballroom downstairs for a plethora of announcements, all from Pat Gelsinger. I'm John Walls, Justin Warren joins us. We haven't been together for a while, it's good to see you.- It's been a little while, yeah. >> How've you been? >> I've been well, I've been well. >> Yeah. >> Yeah. >> I'm surprised they brought us back together after the last time. >> I don't believe... let's not talk about that incident. >> I thought it went so well, we just end on a high note. But it is a pleasure to be with Justin, we'll be with him throughout the week, Monday, Tuesday, Wednesday, our coverage here. We're joined right now by two guests, Paul Savill, whose the SVP of Network and Technology Solutions at CenturyLink and Omar Sunna who is the Director of Digital Products at GE Health care. And gentlemen thanks for being with us, it's good to have you here on the Cube. >> Thank you John. >> First off, let's just, gimme, your both, your take just on VMWorld 2019. What you're looking for, what you're expecting, and kind of the early vibe that you have going on. Paul, why don't you take that first? >> Sure, one of the things I've really been impressed with is how VMware is expanding, the kind of open nature of it's relationships, it's developing it's ecosystem, really broadening it out, it's making a number of acquisitions to enable new capabilities. And we're really excited about that. CenturyLink and VMware have been partners for, I think, around 12, 15 years. As we've been building out our own cloud services and so it's a very exciting time to see all this technology coming together in the way that it is. >> I love with the way you put it too, acquisitions. Pat made a little comment about that, it's like, "I can't wait to find out who I'm "going to buy next." >> Yes. >> And they've been, certainly been in a full speed ahead modefor the past year, year and a half. Omar, you're take, early. >> Yeah, man, I think I look at it from a health care solutioning perspective and it's exciting to see this level of technology and kind of the building out of the ecosystem and what could it enable for health care consumers. Especially with the big focus around privacy and and data management. I think some of their, and security, some of their latest acquisitions could actually help grow that ecosystem and offer more options especially to the health care industry. >> All right, well now let's talk about your portfolio at work then, a little bit, at GE Healthcare. Obviously health systems, health care's a huge user you know, these days, well it's kind of simplifying it a bit, but just talk about what you're concerns are, what your attention is, and kind of the things that are keeping you up at night, these days, in terms of health care and what you're doing in the IT space. >> You know, I mean, I think the, you know when we look at our customer environment globally, you know, we tend to kind of summarize some of the key challenges for our customers around three pillars. Access, so being able to provide access to all the patients that need it, regardless of location. With aging population in a lot of developed countries, with also a lot of people having the means to receive more proactive health care, it is challenging the health systems to be able to provide adequate access to patients. Capacity, providing capacity when the resources, including the human capital resources, that health systems have. So how do you free up your specialists to make sure that they're able to provide the right level of patients who need it, patient care for the patients that need it. As well as clinical efficacy. How do we help with software applications, with technology, to help reduce the variation of care, and improve patient outcomes, regardless where the patient is receiving care, within the rural community or with advanced academic medical centers. So we try to kind of think of our solution technologies as helping our customers solve for access, capacity, and clinical efficacy. >> Yeah, so a lot of health care, it's kind of a retail setup in that there's lots of hospitals and other allied health professionals who have lots of different locations that they need to provide heath care for them and that technology needs to live where the patients are and where the doctors are. So it was interesting to see, in the key note, earlier this morning, talking about edge and different kinds of edge as well. We've got thin, medium, and thick edge, according to VMware. So how do you see that rise of edge computing effecting the way that you deal with health care. >> Yeah, I mean tremendous, actually, opportunity for us. And GE is working on capitalizing on the technology, on edge technology, to allow us to bring in AI application right to, where kind of within the customer network. And that is, that's helping us solve for a lot of concerns around private security as well as moving large data sets to the cloud to process, to be able to get benefit out of algorithm and additional applications. So that's actually an exciting area. And agree with you, I mean we're seeing more and more large distributed health care networks emorph, in the U.S. we've definitely seen huge merger and acquisition movement that we continue to see, and consolidation. And then we also see that globally. With regional delivery networks coming up and being able to have software applications live within this distributed network and provide information for the right clinician at the right time is a big initiative for us. And for us this makes a huge difference in the way our providers are able to deliver care for their patients. >> This seems like an ideal opportunity for the folks at CenturyLink to help you with that. >> Abso-- (nervous laughter) >> Yeah, that's right, I mean CenturyLink really, to that point, sees this landscape evolving rapidly. And we even have a phrase internally we use that, "The network is the data center." We believe that in the future, compute is going to be distributed so widely, in such a broad geography and dropped in places where it's most efficient to run it and where it's most efficient to connect it with network, that really, the data centers we think about it today, becomes this very widely distributed platform that is connected together with high performance networking solutions. And that's part of what we're working with GE Healthcare on. >> I'm old enough to remember when "The network is the computer" was the slogan that we're all following now, and it seems that's actually coming true now. Where we have this idea of it, it's not just cloud, and it's not just data centers, and it's not just edge, it's actually a combination of all of them. And you need to be able to deal with that technology wherever it needs to live. Which is, I think, is a positive change from what we were talking about a few years ago, where it seemed to be, we had to make one choice. Now the choice is you actually need a bit of everything. >> Right. >> Tell me about your decision, or at least in terms of on-prem, off-prem, and health care, I would assume, extremely sensitive, obviously, to security concerns and management and certain policies about who can access what, where, when and how, whatever. How are you going about making that decision in this new multi-cloud environment, this hybrid-cloud environment, when people are making migrations, you know, with their businesses, and they're going off-prem. But you, I would assume, have to be a lot more sensitive, or more sensitive to other factors than, perhaps, other businesses have to be. >> Yeah, we definitely do. There is, you know, with regulations, you know, and, for example in Europe, GDPR, there's in country regulations around where data resides. All of that kind of plays a factor in customer adoption of technologies and where they're comfortable. We've talked a lot of CIOs in the health care sector and a lot of them say, "Hey, listen we're on a journey, "we're used to hugging our servers, "we're used to controlling it, and technology has evolved. "But, in terms of our policies, ability to accept liability "of data breaches and what technology providers are willing "to sign up for. "All of that plays a roll in that journey." Like Justin had mentioned, it is actually a, in developing an ecosystem, where you have combination of on-prem and off-prem, is a lot of where health care health systems are investing their money. So we're seeing certain data that resides on-prem that is mission critical versus more historic data can go into cloud technology, cloud storage technology and others. But, there's no doubt that we're at an inflection point, we're seeing a lot more health systems sign up to cloud based SAS applications. Invest in private cloud hosting service, invest in also public cloud hosting services. And all of that actually will create, as a software provider, all that could actually help us create more opportunities and more solutioning for our customers. I love listening to some of the cloud computing power that would allow us to develop newer applications. So it's actually exciting, it's a journey with our customers, you know, we're choosing to kind of be alongside of our customers and help them. Doing a lot of education. And being able to have a relationship with CenturyLink, be able to see the advances and availability of resources that CenturyLink makes available for us as well as other partners that we have help us really make sure that we're able to build the right level of technology meeting the health care customer needs. >> So Paul, fill in the gaps a little bit about where CenturyLink is in trying to solve this, I wouldn't say dilemma, but it certainly is a puzzle of some sort, right, as decisions are made about what's going to be off loaded, what's not, how are we going to access, what do we allow. How do you see CenturyLink's role when you have a customer like Omar, like GE Healthcare, coming to you with their unique needs, and addressing those? >> Sure, well, as unique as GE Healthcare is in the health care industry, there are some common characteristics about how we are seeing enterprise customers look at these situations. And one of them is that placing compute on the premise itself, that, that is generally the most expensive real estate that an enterprise has when it has to go in the hospital, when it has to go at the retail store location. And a lot of enterprises today are doubling the amount of compute and storage that they're having at their premise locations every year because the volume is just growing so much. That's becoming a problem, because you don't want your, you don't want your hospital becoming a bigger and bigger data center, so to speak, right? And so the way that we're approaching the problem and working with this, is in VMware was actually, you know, expressing a very similar viewpoint about the edge and about how the thick edge and the thin edge, and the thin edge of the customer premise is where you want to have the lightest load, but you want to have the most critical applications that are sitting there, you want to have the information that you have to protect the most in a most guarded way that's most important for your operations there. But from there you can more efficiently run things from a distance backing out going all the way back to the public cloud core, if you connect it with high performance networking from end to end. And so what CenturyLink has been doing is putting together these solutions that make that balance of trade, so to speak, between the cost of compute, the cost of where you have to put it, to where it best can be housed, what kind of latency performance that it needs to have to meet it to the performance specification, all the way back to the public cloud design and how to tie it in to the public cloud. And that's where we've been building our competency and the solutions we've been putting together for customers. >> You mentioned the need for high performance networks in there so I've got to ask you about 5G. From what I know about 5G it looks like the kind of situation you have with health care, where you've got lots of mobile tablet devices, you've got lots of other actual equipment IoT devices in a health care situation. That seems like an ideal use case for 5G. Is that what hot 5G is actually for, is the hype real? >> Well, 5G is certainly going to transform the world in terms of it's ability to provide wireless high bandwidth connectivity and low latency connectivity to devices. But, edge compute is not about 5G. You can have edge compute without 5G. In fact, it's a bit of a myth that edge compute can't arrive until 5G comes, because edge compute is something that is available to do today. And, in fact, CenturyLink is deploying edge compute solutions with, by basically building fiber into enterprise locations and then housing compute at different areas of the network at the point that's most optimal for the solution. And there are a variety of wireless solutions that can be used in that campus environment other than 5G to connect wireless devices back securely and safely to that edge compute that sits there. >> But it seems like it still should be, or at least looks like it could be a game changer in what it's going to allow in terms of, I guess, advancing edge computing. >> Right? I mean, you're still going to provide new capabilities and new reach and new functionalities that don't currently exist. >> I take Paul's point, though, because there are other technologies like Wi-Fi 6, for example, which is, it's basically the same thing as 5G, it just uses a different radio communications mechanism. But, and I also take your point that you can do edge computing today, absolutely. You can put computing into retail situations and you can have, I mean we have tablet devices now. We have laptops. So we kind of have edge computing. We always have, it just now, now it has a name. >> Yes, that's correct. >> So, tell me before we let you go, Catalyst Award winner from CenturyLink and VMware, Paul, first off let's talk about how you assess that, what's the determination, the criteria, for that and then I'm going to let crow a little bit Omar, about receiving that award. But tell us about the Catalyst Award first. >> Yes, well we call it the Catalyst Award because, when you think about it, a catalyst is something that excites a chemical process. Technically that is the definition of catalyst. But catalyst, in the way we view it, is something that we wanted to recognize a person or a company, that we felt like was really driving innovation, that was really solving a problem and working, also collaboratively together with VMware and CenturyLink in solving some of these problems. So we looked at GE Healthcare and really felt like, in a place where certainly we have seen such great advances in health care administration and building to save people's lives. Oddly, medical errors is becoming an increasing amount of now the problems in terms of death rates. Because, while we have so many ways to solve problems, so many ways to address it, that portion of what's causing deaths is actually on the rise. And so GE Healthcare is taking the technology that they're deploying and helping to solve that problem, that's why we wanted to recognize Omar and the company today. >> An honor for you I would assume you're all pretty proud of that. >> Yeah, absolutely, and thank you, and, yeah, I mean it's was really fantastic to be recognized by our partners. And a great testimony to the team at GE Healthcare. And our team wakes up in the morning and our mission is to improve lives in the moment that matters. A lot of our technology is used in mission critical and the way we're able to deliver that to our customers relies heavily on our ability to leverage advances in technology and be able to improve our ability to deliver our different applications for our customers. So this, actually been fantastic, the relationship has been tremendous for us. Where we have hosted our solutions in CenturyLink, the level of support that we have received have really enabled us to deliver important application for our customers and meet their SLAs and meet their clinical use cases and the needs of software uptime. So that has been tremendous for us. >> Well congratulations. >> Thank you. >> Well then thanks for your time, both of you. And enjoy the show, enjoy San Francisco, we've got good weather this week. >> That's right, yeah. >> So get out and enjoy that, thank you Paul and Omar. Back with more on the Cube, you're watching our coverage here live in San Francisco in VMWorld 2019. (music)

>> Announcer: From San Mateo, California, it's theCUBE, covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Welcome back everybody, Jeff Frick here with theCUBE. We're at the crossroads, it's 101 and 92 in San Mateo, California. Lot of software companies have developed here. It's got a long history, at one point it was really kind of the all the software in Silicon Valley was based here versus chips in the south new media in the north. It's not quite the same anymore, that's really the roots of the area, you're probably stuck in traffic if your here, so look up, you'll see the SnapLogic sign, that's where we are, at their new headquarters. And we're excited to have practitioner, we love getting customers on, it's Omar Nawaz, he's the global head of digital transformation and a CISO, so not a small responsibility at Quantum. Great to see you. >> Well thank you for inviting me, I'm happy to be here. >> Absolutely. So you are one of these, could be the new unicorn, the head of digital transformation. So you were brought in for that role, you've been at the company a little over six months, less than a year. Why did they bring you in and where do you get started? >> Well, it's a very interesting role. Digital transformation is about change and we all know that that's hard, and that's why I specifically brought into the company, to help change the operating model and the business model for the company. So what I really do there is work with the leadership of the company and understand what their ambitions are. And then the exciting part starts, where my team and I actually help convert an ambition into reality. And so that we can create a measurable way to understand the reality we are creating for the ambition that we want to achieve is it really meaningful for us or not. >> And who do you report to? Who brought you in? >> So I actually report to the CFO of the company which >> CFO >> So you see the sort of different places where these roles fit in, but in our organization it made a lot of sense because as we're going through the transformation, it was important for us to sort of be close to the money, because it is investment required and you want to manage the cost as well, so that's where I'm at. >> And it's also very interesting that you're a CISO as well, Chief Information Security Officer, for those not following me on the acronym world. So security is a really important piece that is not an insignificant job, so how much of your time is transformation and how much of your time is CISO. >> I think most of my time is to transformation and it's part of when we look at security, we look at security as part of the transformation because as we evolve the company to a new model, it has ramification on how do we secure the new environment as well, so there's a split, I have more than one full time job, I guess you can say that. >> Welcome to Silicon Valley right? >> But yeah, I spend most of my time focused around digital transformation but security is a very important aspect of my role and we want to make sure the environment continues to be safe. >> So there's somebody out here watching this video, they're sitting in their office they just got the edict that they're now in charge of digital transformation at their company and they're pulling their hair out looking for CUBE interviews to help them out. So where do they go, how do they get started, what sort of resources should they be asking for, should they be leveraging, should they expect to give them some sort of success in this very very difficult role? >> So I think there's a lot of places where companies can start and I think of the things you have to understand is how digitally mature you as a company are. One of the key things in this industry is that we all see is that the speed and the rate of innovation is so tremendous and we see these waves of disruptive technology that comes in and there are companies that are adopting and embracing those technologies. And think about mobile or cloud or analytics or social, and those companies that adopt those technologies they can gain a certain level of proficiency and performance improvement, but the cycle is very very fast and now we are seeing yet another wave of technology innovation around IOT, API, artificial intelligence and so if you can quickly jump to that next round of technology and innovation then you can continue to build those efficiencies within the company and gain that competitive advantage or maintain that competitive advantage, and I think it's important for the companies to realize that they have to engage in this very very quickly and it's not a one time process either, it's never going to end, the transformation is never going to end, so you have to continually invest in it and where you start with it and where you go is to make sure that you understand where the company wants to go. >> Right. >> And how the technology can help you get there. That's sort of the hardest part of my job is to really convince the leadership and say this is where we will gain some significant benefit and so when I go to my CEO or CFO or the Board what I'm trying to help them understand is that by investing in technology A, B, C, whichever it is, this is what we achieve or this is sort of the picture, part of the puzzle we're trying to build. >> I love this concept, digital maturity, I've never heard anyone say that before, so it almost begs the question, is there some type of a checklist that you have to have made a minimum, either acknowledgement, I don't know if commitment is the right word, obviously you have to be 100 percent on cloud, but it does beg, is there some sort of, have you adopted some cloud, have you adopted some of this, some of that, some of this, to demonstrate A, that you're digitally mature or you're heading in that direction, and B, these are kind of necessary conditions to execute the digital transformation that I'm trying to put in place. >> Yeah, I don't have a specific measuring stick of where you measure your digital maturity but the things that you talked about, for example, if your organization is still dealing with sort of maintaining some of their own data centers and you're investing resources to that, you have not adopted cloud, mobile applications, you know your applications cannot be accessed remotely, then you're certainly not very digitally mature. Right. How much self service is available for your users internally or for your customers. Those are other signs of digital immaturity, another area to look at is, you know, you have a lot of data within the organization. How are you using that data? Is the data sitting in silos? Or is the data being integrated and now you can, you have analytics running on top of it. That's another measure of your maturity and as you look across the companies, you will see that there are companies who are sitting there in sort of that old traditional model of we're going to build these long term strategic plans and that's also a sign of accepting or adopting these technologies because they're hoping, they're waiting to really fully understand what the technology is going to be when they get there and they need to know all of those how and what it will look like when they get there and I think also to me that's also a sign of digital maturity of a company is do they understand what waves of disruption or technology is coming out. >> Right. So it's interesting, you said that you're biggest challenge is going to the Board and and the C suite and telling them how this is going to work. The other hand, they brought you in, not that long ago, with this very specific objective, so clearly you've got some great executive support. So how do you convince them and what are some of the things that you found just work, what are the right stories, what are the right examples, what are the right use cases, that even the digitally immature, finally are like ah now I get it. >> Yeah, so, I mean it helped that they were already thinking about it before they brought me in so that helps a lot, no doubt, I think the things that when I came in and I looked at the company, so there's many places where you can start, some of the areas you can think about is how do you improve the customer service, that's a very important aspect of how you become a better organization. So another area is process improvement and the third area is business model improvement, so I came in and I talked more about before we actually start looking at modifying or enhancing our business models, we need to get to a better, higher performance level within the organization and therefore I'm initially more focused on how do we improve our processes internally, right, and for us, based on our situation, and it varies for different companies, for us the first step in that was really to make sure that the people, systems, and the data are more interconnected. So even within that first step for me for the first phase for us was really to make sure that the people are connected, so do we have the right set of collaboration and communication tools, right, do we have the right set of analytics to sit on top of it, so we just finished that phase, we want to make sure that these are tangible, small steps, because you need to show some wins very very quickly so for us the first step was lets get the people connected. So we just did that, now the next step for us is to get our systems connected. So again, as I mentioned earlier, there is a lot of data that's sitting there, it has to be integrated. There's tremendous value that you can gain from that. So that's what we're getting into, this is our second phase of how do we connect the data together so this way we can start to get the next level of efficiency out of the company. >> So I am guessing after sitting here all day that the integration of your data, obviously we are at SnapLogic, is going to be easier than getting the people to change their processes and the connected people. What were some of the tricks to get people to adopt these new tools before we even start talking about the data? >> So I think there is, you have to show them the value obviously, if you talk about communication and collaboration tools I think the first thing is really about awareness. Right, there's a little bit of sort of top down, sort of mandate, or you may want to call sponsorship, that I think that that helps. >> Or stick >> Or stick, you know, so that helps. Because for some companies and for Quantum it was true that we did not have a corporate communication tool. There were multiple, right, so within the groups they were fine because they were able to communicate but between groups they were not able to, so we had to standardize on that, so I think that you kind of have to show these, there's always skepticism, because everything when people are used to certain things it seems to work for them right? >> I've always done it this way. >> Exactly right, so you have to show them new things and you have to create the awareness and then they start to see the value. It's not a one time thing, it's continuous effort, so we do lunch and learns, we do webinars, we do support sessions and things like this so this way people are more comfortable taking on the new technology. >> But it's so important right because your probability of success if you don't get the buy in from the participant is not very high, so the fact that you started there on the people before you really dove into the technology I think is pretty insightful and will probably increase your probability of success on the next phase tremendously, versus if you just integrated all the data and integrated all the apps and you still don't have people talking together, probably not going to be very successful. >> Exactly, because the data is in all these different business units and different groups and if they're not talking to each other, connecting the data has little or no value. So to me it's really about creating that connectivity so for us when you ask me, sort of, how do we start, so we start with connecting, connection is the first sort of phase of it and then the second is to empower people you know to create more self service and create more sort of autonomous units so that they can start to create value for themselves and for the company. So it's really about enabling the whole organization, sort of the ground swell type of approach, but you're going to first sort of bring the people to that sort of common place where it's easy for them to work, you bring the data along with it and then you standardize the environment or simplify it if you can and therefore it's easy for them to start taking on the services themselves. >> Right, so you finished the first phase and now the next phase is you're going to start integrating all the systems. >> Correct. >> So obviously, we're sitting here at SnapLogic, it's a big piece of what they do, so why did you decide to go with them and how are they helping you in this process? >> So for us, for this phase of digital transformation, you know there were two things that were really really important for us. One was really about how do we connect these systems together in a simple standardized way, so that was one criteria for us. And I believe SnapLogic does a great job and we're going to build it out at sort of the back core of our network. And then the second piece was really can we take this platform and make it available to our end users. So that they can create the connections or access the data that they want, right, and that's again where SnapLogic was able to demonstrate that this is very easy for them to use. So those were the two sort of very pivotal things for us as part of this phase of our digital transformation as to why we picked SnapLogic. >> Yeah it was funny 'cause you used the word self-service in your first phase so I think kind of this thing where your over and over and over it's so important to drive innovation in big companies is demarketerization demarketerization of the data, demarketerization of the tools and then let people find out things and then actually be able to execute. >> Exactly, because you know IT, there's a constant pressure on IT to cut costs, you know, so we cannot serve the whole company for all the things that needs to happen and the technology and the business is changing at such a rapid pace that unless we have experts who really understand that business unit function that well we are not the best people to build those things for them, they are the ones, but then you have a technology learning barrier or learning curve of do you need to put developers in there, so that's why to us this SnapLogic technology helps us that we believe that we can extend this ability to those users who really know their business, they can make the changes as they come, and the IT can help make sure that the right sort of infrastructure exists and the right sort of, level of connectivity exists. >> So I'm just curious, I know you're still early days in this project, but are there any Luddites that have kind of come around since you've been on this journey that suddenly just woke up and said oh okay now I get it now I see the value, now I kind of understand where we're trying to go, who maybe didn't think that way at the beginning. Or they all just know that they got to go. (laughs) >> No I think we are constantly learning along the way, I think that one of the key things that we learned just recently and SnapLogic is going to help us with that particular aspect of it is that we saw that there were a lot of systems that work fine, we don't use them, it's not a daily use type of thing, they get used quarterly, or annually, but we realized that if we can just bring more automation into those processes and we can tie it back to longer more historical data, then we can build more insights around it, so I think that when we show this to the users and especially the CFO now you all of a sudden sort of the lightbulbs go on and it's like oh this is great. Right, that I don't have to rely on only a small window of information, now I have a much broader window. >> Alright then, Omar thank you for spending a few minutes with us and sharing your story with us. I wish you nothing but success on this. >> Thank you very much. >> I'm sure it will be long and exciting with twists and turns and highs and lows. So good luck. >> We're looking forward to that. >> Alright, he's Omar, I'm Jeff Frick. We're at SnapLogic in San Mateo, California. Thanks for watching. (bright music)

>> Announcer: From San Mateo, California, it's theCUBE, covering SnapLogic Innovation Day 2018. Brought to you by SnapLogic. >> Welcome back everybody, Jeff Frick here with theCUBE. We're at the crossroads, it's 101 and 92 in San Mateo, California. Lot of software companies have developed here. It's got a long history, at one point it was really kind of the all the software in Silicon Valley was based here versus chips in the south new media in the north. It's not quite the same anymore, that's really the roots of the area, you're probably stuck in traffic if your here, so look up, you'll see the SnapLogic sign, that's where we are, at their new headquarters. And we're excited to have practitioner, we love getting customers on, it's Omar Nowaz, he's the global head of digital transformation and a CISO, so not a small responsibility at Quantum. Great to see you. >> Well thank you for inviting me, I'm happy to be here. >> Absolutely. So you are one of these, could be the new unicorn, the head of digital transformation. So you were brought in for that role, you've been at the company a little over six months, less than a year. Why did they bring you in and where do you get started? >> Well, it's a very interesting role. Digital transformation is about change and we all know that that's hard, and that's why I specifically brought into the company, to help change the operating model and the business model for the company. So what I really do there is work with the leadership of the company and understand what their ambitions are. And then the exciting part starts, where my team and I actually help convert an ambition into reality. And so that we can create a measurable way to understand the reality we are creating for the ambition that we want to achieve is it really meaningful for us or not. >> And who do you report to? Who brought you in? >> So I actually report to the CFO of the company which >> CFO >> So you see the sort of different places where these roles fit in, but in our organization it made a lot of sense because as we're going through the transformation, it was important for us to sort of be close to the money, because it is investment required and you want to manage the cost as well, so that's where I'm at. >> And it's also very interesting that you're a CISO as well, Chief Information Security Officer, for those not following me on the acronym world. So security is a really important piece that is not an insignificant job, so how much of your time is transformation and how much of your time is CISO. >> I think most of my time is to transformation and it's part of when we look at security, we look at security as part of the transformation because as we evolve the company to a new model, it has ramification on how do we secure the new environment as well, so there's a split, I have more than one full time job, I guess you can say that. >> Welcome to Silicon Valley right? >> But yeah, I spend most of my time focused around digital transformation but security is a very important aspect of my role and we want to make sure the environment continues to be safe. >> So there's somebody out here watching this video, they're sitting in their office they just got the edict that they're now in charge of digital transformation at their company and they're pulling their hair out looking for CUBE interviews to help them out. So where do they go, how do they get started, what sort of resources should they be asking for, should they be leveraging, should they expect to give them some sort of success in this very very difficult role? >> So I think there's a lot of places where companies can start and I think of the things you have to understand is how digitally mature you as a company are. One of the key things in this industry is that we all see is that the speed and the rate of innovation is so tremendous and we see these waves of disruptive technology that comes in and there are companies that are adopting and embracing those technologies. And think about mobile or cloud or analytics or social, and those companies that adopt those technologies they can gain a certain level of proficiency and performance improvement, but the cycle is very very fast and now we are seeing yet another wave of technology innovation around IOT, API, artificial intelligence and so if you can quickly jump to that next round of technology and innovation then you can continue to build those efficiencies within the company and gain that competitive advantage or maintain that competitive advantage, and I think it's important for the companies to realize that they have to engage in this very very quickly and it's not a one time process either, it's never going to end, the transformation is never going to end, so you have to continually invest in it and where you start with it and where you go is to make sure that you understand where the company wants to go. >> Right. >> And how the technology can help you get there. That's sort of the hardest part of my job is to really convince the leadership and say this is where we will gain some significant benefit and so when I go to my CEO or CFO or the Board what I'm trying to help them understand is that by investing in technology A, B, C, whichever it is, this is what we achieve or this is sort of the picture, part of the puzzle we're trying to build. >> I love this concept, digital maturity, I've never heard anyone say that before, so it almost begs the question, is there some type of a checklist that you have to have made a minimum, either acknowledgement, I don't know if commitment is the right word, obviously you have to be 100 percent on cloud, but it does beg, is there some sort of, have you adopted some cloud, have you adopted some of this, some of that, some of this, to demonstrate A, that you're digitally mature or you're heading in that direction, and B, these are kind of necessary conditions to execute the digital transformation that I'm trying to put in place. >> Yeah, I don't have a specific measuring stick of where you measure your digital maturity but the things that you talked about, for example, if your organization is still dealing with sort of maintaining some of their own data centers and you're investing resources to that, you have not adopted cloud, mobile applications, you know your applications cannot be accessed remotely, then you're certainly not very digitally mature. Right. How much self service is available for your users internally or for your customers. Those are other signs of digital immaturity, another area to look at is, you know, you have a lot of data within the organization. How are you using that data? Is the data sitting in silos? Or is the data being integrated and now you can, you have analytics running on top of it. That's another measure of your maturity and as you look across the companies, you will see that there are companies who are sitting there in sort of that old traditional model of we're going to build these long term strategic plans and that's also a sign of accepting or adopting these technologies because they're hoping, they're waiting to really fully understand what the technology is going to be when they get there and they need to know all of those how and what it will look like when they get there and I think also to me that's also a sign of digital maturity of a company is do they understand what waves of disruption or technology is coming out. >> Right. So it's interesting, you said that you're biggest challenge is going to the Board and and the C suite and telling them how this is going to work. The other hand, they brought you in, not that long ago, with this very specific objective, so clearly you've got some great executive support. So how do you convince them and what are some of the things that you found just work, what are the right stories, what are the right examples, what are the right use cases, that even the digitally immature, finally are like ah now I get it. >> Yeah, so, I mean it helped that they were already thinking about it before they brought me in so that helps a lot, no doubt, I think the things that when I came in and I looked at the company, so there's many places where you can start, some of the areas you can think about is how do you improve the customer service, that's a very important aspect of how you become a better organization. So another area is process improvement and the third area is business model improvement, so I came in and I talked more about before we actually start looking at modifying or enhancing our business models, we need to get to a better, higher performance level within the organization and therefore I'm initially more focused on how do we improve our processes internally, right, and for us, based on our situation, and it varies for different companies, for us the first step in that was really to make sure that the people, systems, and the data are more interconnected. So even within that first step for me for the first phase for us was really to make sure that the people are connected, so do we have the right set of collaboration and communication tools, right, do we have the right set of analytics to sit on top of it, so we just finished that phase, we want to make sure that these are tangible, small steps, because you need to show some wins very very quickly so for us the first step was lets get the people connected. So we just did that, now the next step for us is to get our systems connected. So again, as I mentioned earlier, there is a lot of data that's sitting there, it has to be integrated. There's tremendous value that you can gain from that. So that's what we're getting into, this is our second phase of how do we connect the data together so this way we can start to get the next level of efficiency out of the company. >> So I am guessing after sitting here all day that the integration of your data, obviously we are at SnapLogic, is going to be easier than getting the people to change their processes and the connected people. What were some of the tricks to get people to adopt these new tools before we even start talking about the data? >> So I think there is, you have to show them the value obviously, if you talk about communication and collaboration tools I think the first thing is really about awareness. Right, there's a little bit of sort of top down, sort of mandate, or you may want to call sponsorship, that I think that that helps. >> Or stick >> Or stick, you know, so that helps. Because for some companies and for Quantum it was true that we did not have a corporate communication tool. There were multiple, right, so within the groups they were fine because they were able to communicate but between groups they were not able to, so we had to standardize on that, so I think that you kind of have to show these, there's always skepticism, because everything when people are used to certain things it seems to work for them right? >> I've always done it this way. >> Exactly right, so you have to show them new things and you have to create the awareness and then they start to see the value. It's not a one time thing, it's continuous effort, so we do lunch and learns, we do webinars, we do support sessions and things like this so this way people are more comfortable taking on the new technology. >> But it's so important right because your probability of success if you don't get the buy in from the participant is not very high, so the fact that you started there on the people before you really dove into the technology I think is pretty insightful and will probably increase your probability of success on the next phase tremendously, versus if you just integrated all the data and integrated all the apps and you still don't have people talking together, probably not going to be very successful. >> Exactly, because the data is in all these different business units and different groups and if they're not talking to each other, connecting the data has little or no value. So to me it's really about creating that connectivity so for us when you ask me, sort of, how do we start, so we start with connecting, connection is the first sort of phase of it and then the second is to empower people you know to create more self service and create more sort of autonomous units so that they can start to create value for themselves and for the company. So it's really about enabling the whole organization, sort of the ground swell type of approach, but you're going to first sort of bring the people to that sort of common place where it's easy for them to work, you bring the data along with it and then you standardize the environment or simplify it if you can and therefore it's easy for them to start taking on the services themselves. >> Right, so you finished the first phase and now the next phase is you're going to start integrating all the systems. >> Correct. >> So obviously, we're sitting here at SnapLogic, it's a big piece of what they do, so why did you decide to go with them and how are they helping you in this process? >> So for us, for this phase of digital transformation, you know there were two things that were really really important for us. One was really about how do we connect these systems together in a simple standardized way, so that was one criteria for us. And I believe SnapLogic does a great job and we're going to build it out at sort of the back core of our network. And then the second piece was really can we take this platform and make it available to our end users. So that they can create the connections or access the data that they want, right, and that's again where SnapLogic was able to demonstrate that this is very easy for them to use. So those were the two sort of very pivotal things for us as part of this phase of our digital transformation as to why we picked SnapLogic. >> Yeah it was funny 'cause you used the word self-service in your first phase so I think kind of this thing where your over and over and over it's so important to drive innovation in big companies is demarketerization demarketerization of the data, demarketerization of the tools and then let people find out things and then actually be able to execute. >> Exactly, because you know IT, there's a constant pressure on IT to cut costs, you know, so we cannot serve the whole company for all the things that needs to happen and the technology and the business is changing at such a rapid pace that unless we have experts who really understand that business unit function that well we are not the best people to build those things for them, they are the ones, but then you have a technology learning barrier or learning curve of do you need to put developers in there, so that's why to us this SnapLogic technology helps us that we believe that we can extend this ability to those users who really know their business, they can make the changes as they come, and the IT can help make sure that the right sort of infrastructure exists and the right sort of, level of connectivity exists. >> So I'm just curious, I know you're still early days in this project, but are there any Luddites that have kind of come around since you've been on this journey that suddenly just woke up and said oh okay now I get it now I see the value, now I kind of understand where we're trying to go, who maybe didn't think that way at the beginning. Or they all just know that they got to go. (laughs) >> No I think we are constantly learning along the way, I think that one of the key things that we learned just recently and SnapLogic is going to help us with that particular aspect of it is that we saw that there were a lot of systems that work fine, we don't use them, it's not a daily use type of thing, they get used quarterly, or annually, but we realized that if we can just bring more automation into those processes and we can tie it back to longer more historical data, then we can build more insights around it, so I think that when we show this to the users and especially the CFO now you all of a sudden sort of the lightbulbs go on and it's like oh this is great. Right, that I don't have to rely on only a small window of information, now I have a much broader window. >> Alright then, Omar thank you for spending a few minutes with us and sharing your story with us. I wish you nothing but success on this. >> Thank you very much. >> I'm sure it will be long and exciting with twists and turns and highs and lows. So good luck. >> We're looking forward to that. >> Alright, he's Omar, I'm Jeff Frick. We're at SnapLogic in San Mateo, California. Thanks for watching. (bright music)

>> Announcer: From New York, it's The Cube! Covering Blockchain Week. Now here's John Furrier. >> Hello, and I'm John Furrier with The Cube. We're back here on the ground for coverage of Consensus 2018, part of Blockchain Week New York, and we've got some amazing action going on here. We got Omar Bham, who's with Crypt0, C-R-Y-P-zero. Also got a great podcast. Great to see you. Crypt0 News, you're doing a lot of great social. Love the hat, love the swag. >> Thank you so much. >> Lookin' good. >> Thank you so much. Yeah, this is a swag actually, a follower of mine actually sent me, so I get these random boxes of just shirts, but I love 'em because my entire closet is crypto shirts, and now Goodwill, because I donate all these crypto shirts. (laughs) >> That's awesome. >> Yeah, thanks. >> Well, great to have you on. >> A pleasure. >> You're a celebrity, media celebrity, but you're really an example of a rising new kind of stakeholder in the ecosystem and the community. You're producing content. You're producing with the community. It's a co-development model. You're building a network. >> Yeah, it's... >> Not audience, they're already there, but you've got a network. >> Yeah, it's that thing where you want to find that niche. >> You know? >> John: Yeah. >> And it's just we've been blessed, some of us, to find this space pretty early on and develop that presence before others perhaps could. It's just a blessing. >> So what's your take on all this place? I got to ask you, what's your thoughts? Massive crowd. What's the analysis? >> You know, I was here last year, and we were expecting, I think it was 2750 last year, this year 4000. Turns out to be 8000 people, and a big trending Twitter post today was do you think that you're getting work done? This is my Amin Gunsir. He's one of the big blockchain, he looks at the code very deeply in different blockchains. And so he said, do you feel like you're getting work done with that many people, or do you feel like you're not? And more people were actually getting work done. I think it was, like, 62% to 38%, the vote. (John chuckles) So even with the amount of people here, people are close, tight, and still getting work, you know, (mumbles). >> Well, one other thing, and this brings up a good point. I mean, when you're face to face at a physical event, you have engagement on a whole nother level. It's not digital. Not digital face to face. >> Yeah. >> And I was down in the cafeteria for the little cafe. It's supposed to be public, open, for when you buy your lunch. >> Yeah. >> It was like a conference room. I couldn't sit down. People having meetings. There is so much business being done, relationships being built. So this community really is kind of getting work done. >> Yeah. >> And a lot of it's relationship-based. >> Sure. Yes, absolutely. And, you know, it's a lot of it to do with old relationships blossoming into new relationships. It's that I trust somebody who I already trust. So a lot of these guys have been coming to conferences together for years. >> John: Right. >> And you get introduced to somebody, and then it just works that way. And that kind of a beautiful... >> John: Yeah. >> It's like a mesh network. It's not just coming here and trying to, you know, like, necessarily shill. It's like, oh, here's my friend who I trust. >> John: Yeah. >> We went to school together. And naturally automatically, maybe it's a human thing, we just connect to that person a little bit easier. >> Talk about the work you do. And you got a YouTube channel, you got a podcast, you do some Facebook. >> Yeah. >> What's the format of the show? What's your style? What are you looking for? What kind of content are you producing? Obviously it's very engaging, it's very popular. >> Yeah. >> What's your style? >> Well, originally my style was a belief that the economy was going to collapse, so I was a big investor in stocks, I was trading, and I was trying to save my 401(k). Believe it or not, this was a while back. And I was thinking, how do I grow my capital and preserve it? I was worried that we were going to have another collapse, like 2008 was the beginning of it. So I thought about the future, the singularity, and this one point where we look at Moore's law where computing prices get cut in half for chips every year and a half, was the original road map. Prices cut in half. And basically how do we connect that old world collapsing, perhaps, (John chuckles) into this new infrastructure? And cryptocurrency came at that point, where I had already had some bitcoin, and then Ethereum was coming out, and I realized Ethereum could very well provide that base protocol for the next internet of things, so... >> And the developer community uptake has been phenomenal for Ethereum. >> Yeah, it's incredible, yeah. >> So let's do a little show right now. Omar, what's going on? How's it going? (Omar laughs) What's the content like? What's the coolest thing you're seeing here? Share some stories from the show. What have you seen? >> Let me see. I did interviews with some huge people. So it's so cool just to run into, like, the creator of Lightcoin's right there giving out stickers for his cryptomagical friends. Creator of Monero talking about how he lost all his crypto in a boating accident to me yesterday. (John laughs) Talking to some big trader dudes. Hearing about some stuff I can't even talk about, like, because I promised, and we did a verbal NDA, and I honor those. But, I don't know, it's, everywhere you look, there's something to learn, and you'll be amazed. >> It's got everything into it. I mean, I love this wave, right, because one, technically it's some magical shit happening. >> Sure. >> And it's happening big time. Starting out is growing fast. Business side, radical disruption to business models. Community has been open source, kind of an extension to open source communities. So, and then you've got a glam factor, money. >> Um-hum. >> (laughs) Right, so, I mean, money, I mean... Well, what is it missing? >> You know, I had a friend actually tell me that he got kidnapped, he got kidnapped, tied up, and held at gunpoint for three hours for all his crypto, so he lost all his crypto. So mostly the people who are, like, way up there don't do all that flaunting and showy stuff. You look at the big developers aren't rolling up in the Lambos and Ferraris. Generally you want to be pretty humble and modest about what your earnings are. And so I think it's, maybe it's a sign of, like, that Floyd Mayweather phenomenon, let me show it off. >> John: Yeah. >> Yeah, let's flaunt it. But mostly, like, I think it's that, you know, when you work for somebody, you wear a suit. When you work for yourself, no offense. (laughs) >> Yeah. >> I think you look great. You go the jeans on. >> I'm not wearing a tie, so... >> Exactly. And then when you work for yourself, you can show up in pajamas. >> Yeah. >> So... >> Well, I got to agree with you that I love the mojo, and I think one of the things that's notable in this industry is the pioneers, the guys who are making the money on the front end, they're developers, too. >> Um-hum. >> They're not just, you know, guys rolling the financial Wall Street kind of thing. They're making money and they're paying it forward, right? There's a huge pay it forward culture here. >> Yes, absolutely. >> And I think that is, I think, the differentiator that no one sees, is that that ethos is self-governing. >> Um-hum. >> Yeah, I think there'll be a mainstream adoption pretty quickly. >> Um-hum. >> But still right now it's tight-knit. >> Um-hum. >> It's very cool, and it's a pay it forward culture. >> This is mainstream to me, man. Two years, seeing this space just blossom. But we're getting there. I think it's the early adopter phase. >> John: Yeah. >> Maybe a little bit of early adopter, early majority in the United States. It depends where you are in the world. In LA, everyone has at least heard of bitcoin... >> John: Yeah. >> ...or has some bitcoin where I live. It wasn't the case before when I was living in Miami and (mumbles). >> Well, Omar, I'm a big fan of your work. We showed you the clip or two. >> Oh, I'm a fan of yours. >> We're going to get that to you. >> I love what you're doing. Thank you so much for sharing it to me. >> Yeah. >> I have to have you on my own show, for sure. >> Yeah, what's the URLs? Give a plug, what's the URLs, YouTube channel, coordinates, how do people get in touch with you? >> You can go to youtube.com slash C-R-Y-P-T-zero, so it's basically crypto, but without a zero. You can go to Twitter, so you can follow me on... >> Without an O. >> Yeah? >> It's crypto without an O, or with an O? >> Not the letter O, just the letter, the number zero. >> The number zero, okay. >> So C-R-Y-P-T-zero. Then you go to Crypt0's News. Same way, I'm always Crypt0 with a zero at the end instead of a letter. So Crypt0's News, Instagram, Twitter. We're on SteamIt, Crypt0 everywhere. >> Well, let's do some code development together. You're now a Cube alumni. >> Yeah. >> Welcome to The Cube. >> Thank you so much for having me. We just met... >> Yeah, yeah. >> ...but I'm really excited to have met you. Super personality, man. >> Love the new producers. We love co-developing. We do it out in the open. We're in the open right now. We're on the floor here at Consensus 2018 bringing you all the coverage. Going to do 10 more interviews tomorrow. I did eight interviews last night. We interview anything that moves that's high-quality. Omar, thanks for coming on. It's The Cube. I'm John Furrier. Thanks for watching. >> Thanks, John. >> Announcer: Live from the campus of MIT in Cambridge, Massachusetts, it's The Cube! Covering the MIT Chief Data Officer and the Information Quality Symposium. Now here's your host Stu Miniman.

>>Hey everyone. Welcome back to the queue of Lisa Martin with Dave Valante and we're live in Vegas. This is snowflake summit, 22, their fourth annual event. A lot of people here, a lot of news, a lot to unpack so far, and this is only day, day one. We've got two guests here with us to talk about, uh, cyber security, a very important topic, please welcome Omar singer the head of cyber security strategy at snowflake and Julie Chilo VP of security at Guild education. Welcome. Thank >>You. Thank you >>For having all of >>Our favorite topics. Yeah. Oh >>One. It's not boring. >>You know this much and you have so much more to learn now. So here >>We go. Cybersecurity is, is not to say it's boring. Not boring is an understatement. Yeah. Omar, I wanna start with you so much news coming out today. Talk to us about what's new with cybersecurity. Workload is snowflakes. Flywheel of innovation just seems to be getting bigger and faster. >>Yeah. Yeah. Well, well, I'll tell you it's been a long road to get to where we are today. Um, my initial role at snowflake was to lead security engineering. So I've actually been using snowflake as the home for security data, basically from day one. And we saw that it worked, it worked really well. And we started hearing from customers that they were dealing with some of the same challenges that we faced as an internal security team. And we decided as snowflake that we wanna bring the benefits of the data cloud to cyber security teams at all of our customers. And that's what the workload is all about. >>Talk to us about the, the voice of the customer. Obviously we saw a lot of customer stories heard your customer. We're gonna be talking about Guild education in a minute, but in the voice of the customer, in terms of being influential, obviously you were an internal customer drinking that champagne like this tastes really good. This is better of the Flaco <laugh>, but how is the voice of the customer influential in terms of the, the cybersecurity workload, as we've seen the threat landscape change so much in the last two years alone? >>Sure, sure. And you know, security, it's a really hard problem. We like to think of it as a data problem. And when you start thinking about it, that way snowflake is re very relevant for it. But many security teams don't yet think about their challenge as a data challenge. And so they're struggling with a very fragmented data landscape. The facts are all over the place and they're not able to ask the kind of questions that they need to understand. Where are my risks? How are the bad guys gonna try to get into my network? And they can't reflect that to leadership to everybody that really cares about cyber security. This is a board level concern today without the unified data and without the analytics. Um, they really can't do any of that. And, and yeah, representing the customer is, is a big part of what I do. And we have great customers like, like Julie, who's been kind of with us on this journey. She's, she's a part of the movement. I mean, Julie, what, what has it been like, uh, for, for you? >>Oh, it's been, uh, it's been game changer for, for Guild for sure. When we first, uh, started, I didn't one, I didn't know this was a concept <laugh> so when I first started talking O me and, um, snowflake, uh, I had just heard through the grapevine that, that you could do, like, this was a thing you could use the data, you could get everything you needed in one place. And, um, it's been game changing for my team. Uh, we, we were in many different security tools. They were all isolated, siloed, and we're now able to move everything into one, uh, one area, uh, and get we're getting close to the one pane of glass, which I, um, I just heard was a mythical concept for >>Security for >>A long time. Yeah. For a long time. Um, so it's, uh, it's just been amazing and it's, uh, brought us closer to our data ops team. So I'm here this week, uh, with somebody from data ops, actually, that's awesome to help us out. >>So can you describe that further? I'm I'm, I'm, I'm amazed and skeptical the, the, the I'm imagining, you know, the Optiv chart that says eight, 8 million security tools on there, are you actually able, uh, describe how you're able to consolidate your tooling? >>So, one of, one of the biggest problem, one of the biggest problems we were facing initially was our SIM, um, the security incident and event management tool could not take anything from our DevSecOps tools. And so any security that we had in a developer pipeline was really isolated to that tool, and we could never get it into a SIM Sims just aren't meant they're not built to handle that they're built to handle, um, not, not really old school networks and, and data center traffic and everything I have is in the cloud. And so we were really, I, everything was isolated. So with snowflake, what we do is we, um, worked with our data ops team. We can move things from, um, like our, our scanning tools for, for the developer pipelines into snowflake. We can use then correlate different things such as, from like eight year ADP. Like if a, do you have somebody pushing code to production who's out on vacation, you can actually do that correlation with snowflake that was never available before. These are things we could never do before. And we're able to, um, just do correlations. You could not get in that you cannot get in a SIM. >>Why couldn't I just throw those into any old, you know, run of the mill cloud data warehouse? >>Well, you know, it's not just the scale, it's the complexity of the data. I think snowflake how we have the, the sche on read and then all of the kind of things that make snowflake really good for other departments turns out, works really well for security. And it's the ecosystem too. Nobody else has this ecosystem approach. You know, you heard on the keynote today that snowflake is the, this disrupting, um, the, the software application development, right? All, all that kind of focus. The tool consolidation doesn't need to mean that you only have one tool you can actually have best of breed, choose the tool you want. As long as the data's consolidated, you're not building more silos. And that's what our partners are doing. They're separating the application from the data. They're bringing the work to the data, and that's what you hear here. So Julie's team can still choose to use a variety of tools that get the job done, but all those tools are working off of the single source of truth. And that, that is unique to what snowflake >>Can enable. So we, we are Reiss. Uh, we should have asked you about Guild education, explain your, your, your organization. >>Oh, what does Guild do? Uh, so we're a late stage startup. Uh, we manage education as a benefit for, for large companies. So we, we house data from very large organizations with like their workforce and, and help students help, help their workforce go back to school. >>Okay. So unpacking some of the things you said, schema on Reed, but not necessarily no schema on, right. It's a little different, right. Because you're ingesting. Yeah. And then you're determining the scheme on read that's right. Right. Okay. So that makes it simple and fast for zoom, but you get data in and then you figure it out, bringing work to data. Can we just double click on that a little bit? Cuz I think when I think about that, we've heard terms like over the years bring compute to the data. That's what Hadoop was supposed to do. And it didn't, you know, it was like, everything was mm-hmm <affirmative> shoved. So what do you mean by that? How, how, what, what actually does that >>Mean? Yeah. So if you think about the traditional SAS solution, the vendor needed to invest in a data center and to have a data platform that would be scalable and robust because their service dependent on it and they couldn't trust that the customer would have that kind of data platform on the customer's side. What Snowflake's data cloud has done has democratized the data platform. So now you have startups to fortune 500 S the vendors, the customers, they're all uneven footing when it comes to the data platform. So now the vendors can say, bring your own snowflake. Why not? You know, and they can focus on building the best application to solve the real challenges that security teams have. But by the way, not only cybersecurity, we see this and for example, the, um, customer data space as well. So we're seeing more and more kind of SaaS industries seeing this approach and the applications are gonna come yeah. To the data platform of choice, uh, for the practitioner. >>Julie, can we talk about some of the outcomes that Guild education has achieved so far by working with this solution in terms of, we look at the threat landscape and how it's changed so much the last couple of years and how it's a matter of if, or sorry, when not, if I get hit with an attack, how, what are some of the key outcomes that a snowflake partnership and technology has enabled you to achieve? >>So the, the biggest one, again, it's around the Def sec ops program, um, where you see so many attacks these days happening in the code base. So you really have to be careful with your, your pipeline where the code's getting moved through, who has access, who can move code into production. Um, and these are so the, like if you're using GitHub or, um, like using a scanning tool called snake, they're, they're separate, like they're completely separate the only way that we can see who's moving code into production, or if there was a vulnerability or somebody turned off, the security tool is to move these logs, this data into snowflake, uh, and our engineering teams were already using snowflake. Uh, so that made it, that was an easy transition for us. I didn't have to go out and convince another team to support us somewhere else, but a great example where we were, we're seeing great, um, savings, not only in people time, but, but for security, um, we were having problems or the security or the <laugh>, the engineers were turning off our secure codes scanner. >>And we didn't find out until a little bit later. Uh, oh yeah. Yeah. So found out we, my team, we had a team, we spent about 160 hours going through a thousand pole requests manually. And I said, no, no more go find the go figure out where this data exists. We put it in a snowflake and we can create an automatic, uh, ping to the security team saying, Hey, they turned off the, the scanner, go check and see what, why did the scanner get turned off? So it's an immediate response from my team instead of finding out two months later. And this is just, isn't something you can do right now. That's you can't set it up. So, um, makes it so easy. Ping goes to slack. We can go to the, immediately to the engineering team and say, why did you >>Using using automation? >>Yeah. Did you, did you turn this off? Why did you turn it off? Get an exception in so one, it like helps with compliance, so we're not messing up our SOC two audit. Uh, and then two, from a security perspective, we are able to, to trust, but verify, um, which is a big part of the DevSecOps landscape, where they need code to move into production. They need a scan to run in under five minutes. My team can't be there to scan, you know, 10, like 10 times a day or a hundred times a day. So we have to automate all of that and then just get information as it comes in. >>Is it accurate to say that, um, you're not like shutting off your tools, you're just taking advantage of them and compressing the time to get value out of them or are you actually reducing the tool sets? >>No, we don't. Well, no, we, our goal wasn't to reduce the tool set. I mean, we did actually get rid of the SIM we were using. Uh, so we were partnering with one of, um, uh, snowflakes partners, um, >>Because yeah, but you still have a SIM, >>We still have it. It's just minimized what goes to the SIM, because most of what I care about, isn't actually going to a SIM. Yeah. It's all the other pieces that are in a cloud because we use all like, we're, we're a hundred percent in the cloud. I don't have servers, I don't have firewalls. We don't have routes routers or switches. So all the things I care about live in a cloud somewhere. And, and I want that information. And so a lot of times, um, especially when it comes to the engineering tools, they were already sending the information to snowflake or they're also interested. And so we're partnering like it's, we're doubling up on the use of the >>Data. Okay. And you couldn't get that outta your SIM. Maybe you're asking your SIM to do too much, or it just didn't deliver. >>No systems are built on search engines. You know, they don't, >>They, they can't do it. >>You kind of knew what you were looking for and you say, Hey, where did I see this? Where did I see that? Very different from data analytics and the kinds of question that security teams really want to ask. These are emergent properties. You need context, you need sequel, you need Python. That's how you ask the questions that security teams really want to ask the legacy Sims. They don't let you ask that kind of question. They weren't built with that in mind. And they're so expensive that by moving off of them, to this approach, you kind of pay for all these other solutions that, that then you can bring on. >>That seems to make the, what you just said. There was brilliant. It seems to make the customer conversation quite easy if they're saying, well, why should I replace my SIM? It's doing just fine. You just nailed it with, with what you said there. >>So, yeah. And we're, and we're seeing that happen extensively. And I'm excited that we have customers here at summit talking about their experience, moving off of a legacy SIM where the security team was off to the side, away from the rest of the company to a unified approach, the SIM and the other security solutions working on top of the snowflake and a collaboration between security and the data >>Team. So what does your security ecosystem look like? You've got SIM partners. Do you have identity access partners, endpoint partner. Absolutely. >>Describe that compliance automation ass. Yeah. We hear about companies really struggling to meet all the compliance requirements. Well, if all the data's already centralized, then I can kind of prove to my auditors and not just once a quarter, but once a day, I can make sure that all the environment is in compliance with whatever standard I have. So we see a lot of that cloud security is another big one because there's just 10 times more things happening in the cloud environment than in the data center. Everything is so heavily instrumented. And so we see cloud security solutions as significant as well. And the identity space, the list goes on and on. We do see the future being the entire security program uses connected applications with a single source of truth in the company's snowflake. And >>Would you say centralized, you, you it's logically centralized, right? I mean, it's virtually centralized, right? It's not, >>Well, that's >>Not shoved into one container, right? >>I mean, it's right. Well, that's the beauty of the data cloud, right? We, everybody that's on the data cloud is able to collaborate. And so whether it's in the same account or table or database, you know, that's really besides the point because all of the platform investments that snowflake is making on cross region, cross cloud collaboration means that once it's in snowflake, then it is unified and can be used together. But >>I think people misunderstand that sometimes. And BEWA made this point, uh, as the Christian about the global nature of, of snowflake and it's globally distributed, but it's logically a data cloud. >>Yeah. I like to call it one big database in the sky. You know, that's how I explain to security teams that are kind of new to the concept, but >>It's not, it's could be a lot of little databases, but it, but having the same framework, the same governance structure, the same security >>You're right. I think that's how it's achieved is what you're describing. You know, I think from the outcome, what the security team needs to know is that when there's some breach hitting the headline and they need to go to their leadership and say, I can assure you, we were not affected. They can be confident in that answer because they have access to the data, wherever it is in the world, they have access to ask you the questions they need to ask. >>And that confidence is critical. These days as that threat landscape just continues to change. Thank you both so much for joining us. Thank you. Talking about from a cyber security perspective, some of the things that are new, new at snowflake, what you guys are doing at Guild education and how you're really transforming the organization with the data cloud, we appreciate your insights. Thank you for having us. Thank you. Thanks you guys for our guests and Dave ante. I'm Lisa Martin. You're watching the queue live from Las Vegas on the show floor of snowflake summit 22. We'll be right back with our next guest.

>>Okay, okay, we're back, you're watching the cubes, continuous coverage of HBs Green Lake announcement. One of the things that we said on the Cuban. We first saw Green Lake was let's watch the pace at which H P E delivers new servants is what's that cadence like? Because that's a real signal as to the extent that the company's leading into the cloud and today we're covering that continued expansion. We're here with Tom Black, who was the general manager of HPC storage and Omar assad, who's the storage platform lead for cloud data services at Hewlett Packard Enterprise gentlemen welcome. It's good to see you. >>Thanks Dave. Thanks for having us today. Good to see you. >>Happy to be here. Dave. >>So obviously a lot has changed globally, but when you think of things like cyber threats, ransomware, uh, the acceleration of business transformation, uh, these are new things, a lot of it is unknown a lot of it was forced upon us tom what are you guys doing to address these trends? How are you helping customers? >>Sure, thanks for the question. So if you think back to what we launched in early May, kind of the initial cloud transformation of what was our traditional storage business. Um, we really focused on one key theme. Very customer and customer driven theme that the cloud operational model has one and that customers want that operational model, whether they're operating their workload in the cloud or whether they're operating that workload in their own facility or Nicolo kind of the same thing. So that was kind of our true north and that's what we launched out of the gate in May. But we did allude in May to the fact that we would have an ongoing series of new services coming out on the uh H B Green Lake edge to cloud platform. And just really excited today to be talking about somewhat that expansion looks like um we will continue uh through this month and through the quarters ahead to really add more and more services in that vein of focusing on bringing that true cloud services model to our customer. So we're really excited today to unveil kind of, we've entered the data protection as a service market with HP Green Lake. So this is really our expansion into a very top of mind topic and set of problems and solutions or headaches and aspirins, to quote an old friend um that Ceos faces, they think about how to manage data through its life cycle in their organization. >>When I talked to see IOS during the pandemic. Not that we're out yet, but really in the throes of it and asked them about things like business resilience that they said, you know, we really had to rethink our disaster recovery strategy. It was it was sort of geared toward a fire or a hurricane and we we just didn't even imagine this type of disaster if you will. So we really needed to rethink it. So when I, I see your disaster recovery as a service and capabilities like that. Is that the Xarelto acquisition? >>Yes. Dave thanks you. So we're super happy to have the Xarelto team now as part of our family. Um, just a brilliant team, a well respected technology, uh, kind of a blue chips at our customers and partners that really appreciate what zero has to offer. Um, as we looked at the data protection as a service market, one of the hardest problems is really in that disaster recovery space, I think Omar's gonna talk a little bit more about today. Um, but sort of really does bring the leading industry, what's called continuous data protection um, capability into our green lake platform. Um, we've just recently closed the acquisition and we're working on kind of integration plan as we speak now that we can actually talk to each other post close. Um, but you'll uh, you'll continue to see, you know, some really exciting milestones each and every quarter as we march forward with certain now as part of the family. >>So we all talk about how data is, is so important. We certainly learned during the pandemic that that if you weren't a digital business, you were out of business and a digital business is a data business. So things like backup data protection as a service become increasingly critical. I know you have some capabilities there maybe you could share with us. >>Absolutely. So you know, one of the things that we noticed was as we took the storage business through its transformation and we started can work you know, with the launch of the electron 90 and the six K platform. We really really brought the cloud operational model to our customers. So one of the things that you know, feedback that was coming loud and clear to us is that as we look at the storage portfolio where we look at file block and object, which are now being transformed into a cloud operational experience, data protection, disaster recovery coming back into business after a disaster snapshot management. All of those capabilities, we still have to rely on our partner technologies in order to do that now. It's not bad that we have great partners in the data protection world, but what we're really focused on is that cloud operational model and cloud operational experience and to and as tom mentioned through the data management life cycle. So as a result of that, we talked to a lot of our customers, we talked to a bunch of partners and one of the things that was coming back was that yes, there are many data protection backup offerings on the market. But that true as a service experience that is completely integrated to the services experience of the storage that the customers is experiencing that is not there. So what we looked at was especially to the largest ecosystem, which is the VM ware ecosystems. So we're launching data protection as a service or backup as a service for our VM ware customers offered from data services, cloud console as a SAAS portal. 100% SAs service, nothing to install. No media servers, no application servers, no catalog servers, no backup targets, no patching, no expansion, no capacity planning. None of that is needed. All that's needed is sign on click. Give your V center credentials and off you go, that's it. That is it three clicks and you're in business. So currently, you know, in our, in our analysis we offer five x faster recovery from any of the competitive offerings that there there there are 3.5 better de doop ratios. But for our customers is as simple as this. VM is protected as this many dollars per gig per month. That's it. No backup target, no media server, no catalogs are nothing nothing to manage total Turkey off of the portal. So that's the cadence of services that if you promise and this is one of the first ones when it comes to data management that is coming out into the open. >>So you may have just answered this question, but I want to pose it and get you maybe just summarize it because tom was talking earlier about the customer mandate for cloud in a cloud operational model. So I want you to explain to the audience how you're making that real >>actually can I start that one should be the test was monday morning. Getting ready for this chat with you Dave they got me on console and I'm not kidding three clicks, I got back up and running off the lab VM ware instance so I'll pass it off to you the real answer. But if I could do it three clicks >>as well as a convenience of this service, even tom can be your back, you might be able to do with this. Uh again, you know, a very important question the when you, when you look at the cloud operational model as you abstracts the hardware and and take the management model up into a SAS service, it gives our customers that access to that continuous delivery access that we have. We're going to continue to make the service medal better in the cloud model and automatically customers get the value of it without even reinstalling or going through a patch cycle or an upgrade cycle. But as we get into this cloud operational model, one of the things that was missing was uh if you if you if you if you start to talk about applications, how our application workloads going to be deployed, how are they going to be protected and how are they going to be expanded? So what we did was we, we expanded our info site offerings by merging them into the data services, cloud console and we're releasing a new service called app insects. It is going to be available to our customers at the end of the month. Uh It is, nothing has to change. They don't have to install any sort of agents or or host modifications, nothing like that. If their customers of electra nimble primary boxes and they're using info site and data services, cloud console, they will automatically get app insights. What Athens sites does is it really teases apart all that data that we have been collecting within foresight and now with the acquisition of HPV cloud physics, we're merging them together and relating the operational stacked top to bottom. So discovering all the way from your application usage, network usage, storage, use it. IOP usage VM values cross, collaborating them and presenting that to a customer from an app or an outcome perspective all in the data services, cloud console. So what this does for our customers is it really really transforms not only their operational experience but also buying experience. Because if you remember in one of the earlier releases of data services cloud console we released this application called, you know, intelligent intent based provisioning in which you just describe your workload and we go ahead and we provision that app insights and info site, feed that information directly into that and cloud physics generates and results and displays those analytics back to us to your partner of record and to the H. B. So we can all come together on a common data driven discussion point with our customers to continue to make their journey better >>tom where's all the boxes, traditional storage is changing. I've actually been waiting for this day for a long, long time. We've certainly seen glimpses of it from the cloud players, but they don't have, you know, super rich portfolio storage portfolio. They're growing now, but this is a really good strong example of a company with a large storage portfolio. That's, I mean I haven't heard the word three power once today. Right. And so what that says to me, that's an indication that you're thinking like a cloud player, can you maybe talk >>to that? Sure. Yeah, we're just tremendously excited about this transformation and really the reception we've got in the market from analysts, from partners, from customers because you're right, you haven't heard us talk about a box at all today. It's really about a block service, a file on the object service, a backup and recovery service, disaster recovery service. That that's that is the the language, if you will of the business problems of our customers not, do they need to pick this widget or that widget. And how many apps can I get here and there? And which did the h a cage protection scheme be that, is that, is our job to manage underneath are true North, which is the cloud operational model. And so that's going to be really how we we've set our course and how we will uh kind of deliver products solutions offers into the market underneath that umbrella, Ultimately, um getting our customers wherever their data is Dave to be able to interact at that service level instead of at that infrastructure box >>level, you've got my attention wherever the data. So that's the north star here is this is, you know, you're not done today obviously, but you've got a vision to bring that to the cloud across clouds on prem out to the edge. That's the abstraction layer that you're gonna build, your hiding all that complexity. That's correct. And that's cloud. The definition of cloud is changing. >>Yeah, >>it's no longer started, it's no longer a remote set of services. Somewhere up in the cloud. It's expanding on prem hybrid across clouds edge >>everywhere. You're exactly right. Dave it is, cloud is more about the experience and the outcome. It gives a customer than actually where the compute or storage is. We've chosen to take a very customer an agnostic position of whether it's, you know, data in your premise, data in your cloud. We're going to help you manage that data and deliver, you know, that data to workloads and analytics, uh, wherever the, wherever the compute needs to be, where the data needs to be. Again, technologies like Xarelto giving instability and move data across clouds from facilities and clouds back and forth. So it's a really exciting new day for HP. Green Lake were just so super happy to bring these technologies out and really continue to follow on the course of doing what we said, we would do >>the new mindset starts there, I guess it's obviously knew certainly new technologies, uh, you're talking about machine intelligence is a metadata challenge. Absolutely. Big time, you know, long term that North Star that we talked about and applying that machine intelligence, all the experience that you gather data that you're gathering is, I think ultimately how customers want you to solve this problem >>in the middle of info site data services, cloud console and the instrumentation that is already shipping on our appliances, both in edge appliances and the data center appliances were collecting more than a trillion data points over the period of a quarter. Right at the end of the day. So it's harnessing that at the back end to cross relate and then using the cloud physics accusation. What we're doing is we can now simulate these things on behalf of our customers into the future timeline. So at the end of the day, it's really about listening to the customer and what outcomes that they want to achieve with their data storage is there we provide excellent persistence layers where customers can store their data safely. But at the end of the day it's customers choice, They can store their data out of the edge in compute servers, commodity servers, X 86 servers, they can have their data in the data center which they are privately owned or their data can be in a service provider or it can be in a hyper secular. The infrastructure of the persistence layer is independent from the data services. Cloud console data services. Cloud console provides our customers with a SAS based industry leading metadata rich management experience, which then allows you to draw conclusions. So services like cloud physics services like uh enforce it, provide the analytics and richness of the metadata, backup and recovery service allows us to index our customers data and add a rich metadata to that and then combine that with xylitol, which is our disaster recovery as a service offering. Going to start over here. That gives the customer a very simple slider as to where they want their protection levels to be, they want their protection to be instant or they want their protection to be lazy eight hours window. But the thing is at the end of the day, it's about choice without managing the complexities of the hardware >>underneath because programmable completely right I come in, what I'm hearing is file object blocks of your multi protocol. I got a full stack so data data reduction, my snaps might replicate whatever whatever I need it in there as a service. I can I can access latency sensitive storage if I need to or I can push it out to cheaper stores. I could push it out to the cloud, presumably I could someday I air gap it uh and it's all done as infrastructure as code and then different protection levels where I see this going. It really gets exciting is you're now a data company and you're bringing ai machine intelligence and driving data products, data services for your customers who are going to monetize that at their end of the value >>chain. That's right. That's right. And safely insecurity. Keeping in mind that was their toes technology. We can give you, you know, small second recovery points to protect against ransomware. So all of that operational elegance, all those insights and intelligence to help you build a more agile, um you know, workloads centric organization, but then to do it safely and securely against ransomware, that's kind of the storm, if you will. That's brewing. And we're just really excited to be at the eye of it. >>I'm excited to. This is uh I've been waiting for this day for a long time and we're not talking about envy, Emmy and Atomic Rights and I love that stuff by the way and I'm sure it's all under the covers, but that's not what drives business value guys. Thanks so much for coming on the Cuban. David. >>Thanks for having us. It's been great. Thank you. >>All right. We're seeing a transformation all through the stack and keep it right there. This is Dave Volonte for the Cuban. Our coverage of HBs Green Lake announcements right back mm mhm

>>Welcome back to the cubes coverage of H P S. Green Lake announcement. We've been following Green Lake and the cadence of announcements making. Now we're gonna talk about ransomware, ransomware become a household term. But what people really don't understand is that virtually any bad actor can become a ransomware criminal by going on the dark web hiring a ransomware as a service sticking, putting a stick into a server and taking a piece of the action and that is a really insidious threat. Uh, the adversaries are extremely capable, so we're going to dig into that with Omar assad, who's the storage platform, lead cloud data services at H P E and Deepak verma vice president of product Zito, which is now an H P E company Gentlemen, welcome to the cube. Good to see you. Thank you. >>Thank you. Welcome. Pleasure to be here. So >>over you heard my little narrative upfront. How does the Xarelto acquisition fit into that discourse? >>Thank you. Dave first of all, we're extremely excited to welcome Sir toe into the HP family. Uh, the acquisition of Puerto expands the Green Lake offerings from H P E uh, into the data protection as a service and ransomware protection as a service capabilities and it at the same time accelerates the transformation that the HP storage businesses going through as it transforms itself into more of a cloud native business, which sort of follows on from the May 4th announcements that you helped us cover. Uh, this enables the HP sales teams to now expand the data protection perimeter and to start offering data protection as a service and ransomware as a service with the best in class technologies uh, from a protection site as well as from ransomware recovery side of the house. And so we're all the way down already trying to integrate uh, you know, the little offerings as part of the Green lake offerings and extending support through our services organization. And the more of these announcements are gonna roll out later in the month. >>And I think that's what you want to see from it as a service offering. You want to see a fast cadence of new services that are not a box by a box that are applying. No, it's services that you want to access. So let's, let's talk about before we get into the tech, can we talk about how you're helping customers deal with ransomware? Maybe some of the use cases that you're seeing. >>First of all, extremely excited to be part of the HP family now. Um, Quick history and that we've been around for about 11 years. We've had about 9000 plus customers and they all benefit from essentially the same technology that we invented 11 years ago. First and foremost, one of the use cases has been continuous data protection. So were built on the CdP platform, which means extremely low RTO S and R P O S for recovery. I'll give you example there um, United Airlines is an application that cost them $1 million dollars for every hour that they're down. They use traditional approaches. That would be a lot of loss with Zito, we have that down two seconds of loss in case and the application goes down. So that's kind of core and fundamental to our plaque. The second uh critical use case that for us has been simplicity. A lot of customers have said we make the difficult, simple. So DRS is a complex uh process. Um, give you an example there. Hcea Healthcare Consolidated four different disaster recovery platforms into a single platform in Puerto and saved about $10 million dollars a year. So it's making that operations of having disaster recovery process is much simpler. Um the third kind of critical use case for us as uh, the environment has evolved as the landscape has involved has been around hybrid cloud. So being able to take customers to the platforms that they want to go to that's critical for us And for our customers an example, there is Kingston technology's so Kingston tried some competitive products to move to Azure, it would take them about 24 hours to recover 30 VMS or so with zero technology. They will get about all their 1000 VMS up in Azure instantaneously. So these are three use cases that were foundational. Built. Built the company in the tech. >>Nice. Thank you. Thank you for that. So simple works well these days, especially with all this complexity we have to deal with. Can we get into the secret sauce a little bit. I mean CdP has been around forever. What do you guys do that? That's different. Maybe you can talk about that. Sure. >>Um it's cdp based, I think we've perfected the technology. It's less about being able to just copy the data. It's more about what you do when things go bump. We've made it simpler with driven economies of scale lower and being platform agnostic. We've really brought that up across to whatever platforms once upon a time it was moving from physical to virtual or even across different virtualization platforms and then being able to move across to whatever cloud platform customer may want or or back >>to cbP continuous data protection by the way for the audience that may not know that go ahead. And >>one of the additional points that I want to add to the box comment over here is the the basics of platform independence is what really drew uh hp technologists into the technology because you know, one of the things we have many, we have the high end platform with the H B electra nine Kv of the electro six kids the midrange platform. Then we have a bunch of file and object offerings on the side. What zero does it University universally applies to all those technologies and along with, you know, as you pair them up with our computer offerings to offer a full stack but now the stack is disaster recovery capable. Natively with the integration of certo, you know, one of the things that, you know, Deepak talked about about the as your migrations that a lot of the customers are talking about cloud is also coming up as a D our use case for a lot of our customers, customers, you know, you know, as we went through thousands of customers interviews one of the, one of the key things that came back was investing in a D our data center which is just waiting there for a disaster to happen. It's a very expensive insurance policy. So absurd. Oh, through its native capabilities allows customers to do is to just use public cloud as a D our target and and as a service, it just takes care of all the format conversions and recoveries and although that's completely automated inside the platform and and we feel that, you know, when you combine this either at the high end of data center storage offering or the middle age offering with this replication, D. R. And ransomware protection built into the same package, working under the same hood, it just simplifies and streamlines the customers deployment. >>Come here a couple of things. So first of all historically, if you wanted to recover to appoint within let's say, you know, 10 seconds, five seconds you have to pay up. Big time. Number one. Number two is you couldn't test your D. R. It was too risky. So people just had it in, they had a checkbox on compliance but they actually couldn't really test it because they were afraid they were going to lose data. So it sounds like you're solving both of those problems or >>or you know we remember the D. R. Test where it was a weekend. It was an event right? It was the event and at the end of july that the entire I. T. Organizing honey >>it's not gonna be home this weekend. Exactly what >>we've changed. That is a click of a button. You can D. R. Test today if you want to you can have disaster recovery still running. You can D. R. Test in Azure bring up your environment an isolated network bubble, make sure everything's running and bring it and bring it down. The interesting thing is the technology was invented back when our fear in the industry was losing a data center was losing power was catastrophic, natural disasters. But the technology has lent itself very well to the new threats which which are very much around ransomware as you mentioned because it's a type of disaster. Somebody's going after your data. Physical servers are still around but you still need to go back to a point in time and you need to do that very quickly. So the technology has really just found itself uh appealing to new challenges. >>If a customer asks you can I really eliminate cyber attacks, where should I put my my if I had 100 bucks to spend. Should I spend it on you know layers and defense should I spend it on recovery. Both, what would you tell them? >>I think it's a balanced answer. I think prevention is 100% impossible. Uh It's really I'd say spend it in in thirds. You want to spend a third of it and and prevention a third of it maybe in detection and then a third of it in uh recovery. So it's really that balancing act that means you can't leave the front door open but then have a lot of recovery techniques invested in. It has to be it has to be a balance and it's also not a matter of if it's a matter of when so we invest in all three areas. Hopefully two of them will work to your advantage. >>You dave you you should always protect your perimeter. I mean that that goes without saying but then as you invest in other aspects of the business, as Deepak mentioned, recovery needs to be fast and quick recovery whether from your recovering from a backup disaster. Are you covering from a data center disaster a corrupted file or from a ransomware attack. A couple of things that zero really stitches together like journal based recovery has been allowed for a while but making journal based recovery platform independent in a seamless fashion with the click of a button within five seconds go back to where your situation was. That gives you the peace of mind that even if the perimeter was breached, you're still protected, you know, five minutes into the problem And, and that's the peace of mind, which along with data protection as a service, disaster recovery as a service and now integrating this, you know, recovery from ransomware along with it in a very simple, easy to consume package is what drew us into the >>more you can do this you said on the use the cloud as a target. I could use the cloud as an air gap if I wanted to. It sounds like it's cloud Native, correct? Just wrap your stack in kubernetes and shove it in the cloud and have a host and say we're cloud to No, really I'm serious. So >>absolutely, we we looked at that approach and that that's where the challenge comes in, Right? So I give you the example of Kingston technology just doesn't scale, it's not fast enough. What we did was developed a platform for cloud Native. We consume cloud services where necessary in order to provide that scalability. So one example in Azure is being able to use scale set. So think about a scenario where you just declare a disaster, you've got 1000 VMS to move over, we can spin up the workers that need to do the work to get 1000 VMS spin them down. So you're up and running instantaneously and that involves using cloud Native uh tools and technologies, >>can we stay on that for a minute, So take take us through an example of what life was like would be like without zero trying to recover and what it's like with Puerto resources, complexity time maybe you could sort of paint a picture. Sure. >>Let me, I'll actually use an example from a customer 10 Kata. They uh develop defensive fabrics, especially fabric. So think about firefighters, think about our men and women abroad that need protective clothing that developed the fibers behave. They were hit by ransomware by crypto locker. That this was before zero. Unfortunately it took they took about a two week uh data loss. It took them weeks to recover that environment, bring it back up and the confidence was pretty low. They invested in, they looked at our technology, they invested in the technology and then they were hit with a different variant of crypto locker immediately. The the IT administrators and the ITS folks there were relieved right, they had a sense of confidence to say yes we can recover. And the second time around they had data loss of about 10 seconds, they could recover within a few minutes. So that's the before and after picture giving customers that confidence to say yep, a breach happened, we tried our best but now it's up to recovery and I can recover without having to dig tapes out from some vault and hopefully have a good copy of data sitting there and then try that over and over again and there's a tolerance right before a time before which business will not be able to sustain itself. So what we want to do is minimize that for businesses so that they can recover as quickly as possible with as little data loss as possible. >>Thank you for that. So, Omar, there's a bigger sort of cyber recovery agenda that you have as part of, of green lake, I'm sure. What, what should we expect, what's next? Where do you want to take this? >>So uh excellent question point in the future day. So one of the things that you helped us, uh you know, unveil uh in May was the data services. Cloud console. Data services. Cloud console was the first uh sort of delivery as we took the storage business as it is and start to transform into more of a cloud native business. We introduced electra uh which is the cloud native hardware with the customers buy for persistent storage within their data center. But then data services, cloud console truly cemented that cloud operational model. Uh We separated the management from, from the devices itself and sort of lifted it up as a sas service into the public, public cloud. So now what you're gonna see is, you know, more and more data and data management services come up on the data services. Cloud console and and zero is going to be one of the first ones. Cloud physics was another one that we we talked about, but zero is the is the true data management service that is going to come up on data services, cloud console as part of the Green Lake services agenda that that HP has in the customer's environ and then you're gonna see compliance as a service. You're going to see data protection as a service. You're gonna see disaster recovery as a service. But the beautiful thing about it is, is choice with simplicity as these services get loaded up on data services, clown console. All our customers instantly get it. There's nothing to install, there's nothing to troubleshoot uh, there's nothing to size. All those capabilities are available on the console, customers go in and just start consuming Xarelto capabilities from a management control plane, Disaster recovery control plan are going to be available on the data services, cloud console, automatically detecting electro systems, rian Bear systems, container based systems, whichever our customers have deployed and from there is just a flip of a button. Another way to look at it is it sort of gives you that slider that you have data protection or back up on one side, you've got disaster recovery on one side, you've got ransomware protection on on the extreme right side, you can just move a slider across and choose the service level that you want without worrying about best practices, installation, application integration. All of that just takes control from the data services, cloud concepts. >>Great, great summary because historically you would have to build that right now. You can buy it as a service. You can programmatically, you know, deploy it and that's a game changer. Have to throw it over the fence to some folks. That's okay. Now, you know, make it make it work and then they change the code and you come back a lot of finger pointing. It's now it's your responsibility. >>Absolutely. Absolutely. We're excited to provide Zito continue provides the desert of customers but also integrate with the Green Green Lake platform and let the rest of Green Lake customers experience some of the sort of technology and really make that available as a service. >>That's great. This is a huge challenge for customers. I mean they do, I pay their ransom. Do not pay the ransom. If I pay the ransom the FBI is going to come after me. But if I don't pay the ransom, I'm not gonna get the crypto key. So solutions like this are critical. You certainly see the president pushing for that. The United States government said, hey, we got to do a better job. Good job guys, Thanks for for sharing your story in the cube and congratulations. Thank >>you. Thank you David. >>All right. And thank you for watching everybody. Uh this is the, I want to tell you that everything that you're seeing today as part of the Green Lake announcement is going to be available on demand as part of the HP discover more. So you got to check that out. Thank you. You're watching the cube. >>Mhm mm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave a lot and you're watching the cube. We're here with Omar assad is the vice president, GM of H P S H C I and primary storage and data management business. And Sandeep Singh was the vice president of marketing for HP storage division. Welcome gents. Great to see you. >>Great to be here. Dave, >>it's a pleasure to be here today. >>Hey, so uh, last month you guys, you made a big announcement and and now you're, you know, shining the spotlight on that here at discover Cindy. Maybe you can give us a quick recap, what do we need to know? >>Yeah, Dave. We announced that we're expanding HB Green Lake by transforming HB storage to a cloud native software defined data services business. We unveiled a new vision for data that accelerates data dream of transformation for our customers. Uh and it introduced a and we introduced the data services platform that consists of two game changing innovations are first announcement was data services cloud console. It's a SAS based console that delivers the cut operational agility and it's designed to unify data operations through a suite of cloud data services. Our second announcement is H P E electra. It's cloud native data infrastructure to power your data edge to cloud. And it's managed natively with data services cloud console to bring that cloud operational model to our customers wherever their data lives. Together with the data services >>platform. >>Hp Green Green Lake brings that cloud experience to our customers data across edge and on premises environment and lays the foundation for our customers to shift from managing storage to managing data. >>Well, I think it lays the foundation for the next decade. You know, when we entered this past decade, we we we we keep we use terms like software led that that sort of morphed into. So the software defined data center containers with kubernetes, let's zoom out for a minute. If we can homer, maybe you could describe the problems that you're trying to address with this announcement. >>Thanks dave. It's always a pleasure talking to you on these topics. So in my role as general manager for primary storage, I speak with the hundreds of customers across the board and I consistently hear that data is at the heart of what our customers are doing and they're looking for a data driven transformative approach to their business. But as they engage on these things, there are two challenges that they consistently faced. The first one is that managing storage at scale Is rife with complexity. So while storage has gotten faster in the last 20 years, managing a single array or maybe two or three arrays has gotten simpler over time. But managing storage at scale when you deploy fleet, so storage as customers continue to gather, store and life cycle of that data. This process is extremely frustrating for customers. Still I. T. Administrators are firefighting, they're unable to innovate for their business because now data spans all the way from edge to corridor cloud. And then with the advent of public cloud there's another dimension of multi cloud that has been added to their data sprawl. And then secondly what what we what we consistently hear is that idea administrators need to shift from managing storage to managing data. What this basically means is that I. T. Has a desire to mobilize, protect and provision data seamlessly across its lifecycle and across the locations that it is stored at. This ensures that I. D. Leaders uh and also people within the organization understand the context of the data that they store and they operate upon. Yet data management is an extremely big challenge and it is a web of fragmented data silos across processes across infrastructure all the way from test and dev to administration uh to production uh to back up to lifecycle data advantage. Uh And so up till now data management was tied up with storage management and this needs to change for our customers especially with the diversity of the application workloads as they're growing and as customers are expanding their footprint across a multi cloud environment, >>just had to almost um response there. We recently conducted a survey that was actually done by E. S. She. Um and that was a survey of IT. decision makers. And it's interesting what it showcased, 93% of the respondents indicated that storage and data management complexity is impeding their digital transformation. 95% of the respondents indicated that solving storage and data management complexity is a top 10 business initiative for them And 94% want to bring the cloud experience on premises. >>You know, I'll chime in. I think as you guys move to the sort of software world and container world affinity to developers homer. You talked about, you know, things like data protection and we talk about security being bolted on all the time. Now. It's designed in it's it's done at sort of the point of creation, not as an afterthought and that's a big change that we see coming. Uh Let's talk about, you know what also needs to change as customers make the move from this idea of managing storage to to managing data or maybe you can take that one. >>That's a that's a very interesting problem. Right. What are the things that have to be true in order for us to move into this new data management model? So, dave one of the things that the public cloud got right is the cloud operational model which sets the standard for agility and a fast pace for our customers in a classic I. T. On prime model. If you ever wanted to stand up an application or if you were thinking about standing up a particular workload, uh you're going to file a series of I. T. Tickets uh And then you are at the mercy of whatever complex processes exist within organization and and depending on what the level of approvals are within a particular organization, standing up a workload can take days, weeks or even months in certain cases. So what cloud did was a rock that level of simplicity for someone that wanted to instead she ate an app. This means that the provision of underlying infrastructure that makes that workload possible needs to be reduced to minutes from days and weeks. But so what we are intending to do over here is to bring the best of both worlds together so that the cloud experience can be experienced everywhere with ease and simplicity and the customers don't need to change their operating model. So it's blending the two together. And that's what we are trying to usher in into this new era where we start to differentiate between data management and storage management as two independent. Yes, >>Great. Thank you for that. Omer. So deep. I wonder if you could share with the audience, you know, the vision that you guys unveiled, What does it look like? How are you making it actually substantive and and real? >>Yeah. David, That's also great question. Um across the board it's time to reimagine data management. Everything that homer shared. Those challenges are leading to customers needing to break down the silos and complexity that plagues these distributed data environments. And our vision is to deliver a new data experience that helps customers unleash the power of data. We call this vision unified data obs Unified Data Ops integrates data centric policies to streamline data management cloud native control to bring the cloud operational model to where customers data labs and a I driven insights to make the infrastructure invisible. It delivers a new data experience to simplify and bring that agility of cloud to data infrastructure. Streamline data management and help customers innovate faster than ever before. We're making the promise of unified Data Ops Real by transforming H P E storage to a cloud native software defined data services business and introducing a data services platform that expands Hve Green Lake. >>I mean, you know, you talk about the complexity, I see, I look at it as you kind of almost embracing the complexity saying, look, it's gonna keep getting more complex as the cloud expands to the edge on prem Cross cloud, it gets more complex underneath. What you're doing is you're almost embracing that complexity, putting a layer over it and hiding that complexity from from the end customer that and so they can spend their time doing other things over. I wonder if you can maybe talk a little bit more about the data services console, is it sort of another, you know, software layer to manage infrastructure? What exactly is it? >>It's a lot more than that dave and you're you're 100% right. It's basically we're attempting in this release to attack that complexity. Head on. So simply put data services. Cloud console is a SAS based console that delivers cloud operational model and cloud operational agility uh to our customers, it unifies data operations through a series of cloud data services that are delivered on top of this console to our customers in a continuous innovation stream. Uh And what we have done is going back to the point that I made earlier separating storage and data management and putting the strong suites of each of those together into the SAS delivered console for our customers. So what we have done is we have separated data and infrastructure management away from physical hardware to provide a comprehensive and a unified approach to managing data and infrastructure wherever it lives from a customer's perspective, it could be at the edge, it could be in a coal. Oh, it could be in their data center or it could be a bunch of data services that are deployed within the public cloud. So now our customers with data services, cloud console can manage the entire life cycle of their data from all the way from deployment, upgrading and optimizing it uh from a single console from anywhere in the world. Uh This console is designed to streamline data management with cloud data services that enable access to data, It allows for policy-based data protection, it allows for an organizational wide search on top of your storage assets. And we deliver basically a 360° visibility to all your data from a single console that the customer can experience from anywhere. So, so if you look at the journey, the way we're deciding to deliver this. So the first in its first incarnation, uh data services, cloud console gives you infrastructure and cloud data services to start to do data management along with that. But this is that foundation that we are placing in front of our customers, the SAS console through which we get touch our customers on a daily basis. And now as our customers get access to the SAAS platform on the back end, we will continue to roll in additional services throughout the years on a true SAS based innovation base for our customers. And and these services can will be will be ranging all the way from data protection to multiple out data management, all the way to visibility all the way to understanding the context of your data as it's stored across your enterprise. And in addition to that, we're offering a consistent, revised, unified API which allows for our customers to build automation against their storage infrastructure without ever worrying about that. As infrastructure changes. Uh the A P I proof points are going to break for them. That is never going to happen because they are going to be programming to a single SAS based aPI interface from now on. >>Right. And that brings in this idea of infrastructures coding because you talk about as a service to talk about Green Lake and and my question is always okay. Tell me what's behind that. And if and if and if and if you're talking about boxes and and widgets, that's a it's a problem. And you're not you're talking about services and A P. I. S and microservices and that's really the future model. And infrastructure is code and ultimately data as code is really part of that. So, All right. So you guys, I know some of your branding folks, you guys give deep thought uh, to this. So the second part of the announcement is the new product brands and deep maybe you can talk about that a little bit. >>Sure. Ultimately delivering the cloud operational model requires cognitive data infrastructure and that has been engineered to be natively managed from the cloud. And that's why we have also introduced H. P. E. Electra. Omar. Can you perhaps described HB electro even more? >>Absolutely. Thank you. Sandy. Uh, so with with HB Electoral we're launching a new brand of cloud native hardware infrastructure to power our customers data all the way from edge to the core to the cloud. The releases are smaller models for the edge then at the same time having models for the data center and then expanding those services into the public cloud as well. Right. All these hardware devices, Electoral hardware devices are cloud native. Empowered by our Data services. Cloud Council. We're announcing two models with this launch H. P. E. Electra 9000. Uh, this is for our mission critical workloads. It has its history and bases in H P E primera. It comes with 100% availability guarantee. Uh It's the first of its type in the industry. It comes with standard support contract, No special verb is required. And then we're also launching HB electoral 6000. Uh These are based in our history of uh nimble storage systems. Uh These these are for business critical applications, especially for that mid range of the storage market, optimizing price, performance and efficiency. Both of these systems are full envy, any storage powered by our timeless capabilities with data in place upgrades. And then they both deliver a unified infrastructure and data management experience through the data services, cloud console. Uh and and and at the back end, unified ai Ops experience with H P E info site is seamlessly blended in along with the offering for our customers. >>So this is what I was talking about before. It's sort of not your grandfather's storage business anymore. Is this is this is this is something that is part of that, that unified vision, that layer that I talked about. The AP is the program ability. So you're you're reaching into new territory here. Maybe you can give us an example of how the customers experience what that looks like. >>Excellent, loved her Dave. So essentially what we're doing is we're changing the storage experience to a true cloud operational model for our customers. These recent announcements that we just went through along with, indeed they expand the cloud experience that our customers get with storage as a service with HPD Green Lake. So a couple of examples to make this real. So the first of all is simplified deployment. Uh, so I t no longer has to go through complex startup and deployment processes. Now, all you need to do is these systems shipped and delivered to the customer's data center. Operational staff just need to rack and stack and then leave, connect the power cable, connect the network cable. And the job is done from that point onwards, data services console takes over where you can onboard these systems, you can provision these systems if you have a pre existing organization wide security as well as standard profile setup in data services console, we can automatically apply those on your behalf and bring these systems online. From a customer's perspective, they can be anywhere in the world to onboard these systems, they could be driving in a car, they could be sitting on a beach uh And and you know, these systems are automatically on boarded through this cloud operational model which is delivered through the SAAS application for our customers. Another big example. All that I'd like to shed light on is intent based provisioning. Uh So Dave typically provisioning a workload within a data center is an extremely spreadsheet driven trial and error kind of a task. Which system do I land it on? Uh Is my existing sl is going to be affected which systems that loaded, which systems are loaded enough that I put this additional workload on it and the performance doesn't take. All of these decisions are trial and error on a constant basis with cloud data services console along with the electron new systems that are constantly in a loop back information feeding uh Typical analytics to the console. All you need to do is to describe the type of the workload and the intent of the workload in terms of block size S. L. A. That you would like to experience at that point. Data services console consults with intra site at the back end. We run through thousands of data points that are constantly being given to us by your fleet and we come back with a few recommendations. You can accept the recommendation and at that time we go ahead and fully deploy this workload on your behalf or you can specify a particular system and then we will try to enforce the S. L. A. On that system. So it completely eliminates the guesswork and the planning that you have to do in this regard. Uh And last but not the least. Uh you know, one of the most important things is, you know, upgrades has been a huge problem for our customers. Uh And typically oftentimes when you're not in this constant, you know, loop back communication with your customers. It often is a big challenge to identify which release or which bug fix or which update goes on to which particular machine. All of that has been completely taken away from our customers and fully automated. Uh we run thousands of signatures across are installed base. We identify which upgrades need to be curated for which machines in a fleet for a particular customer. And then if it applies to that customer we presented, and if the customer accepts it, we automatically go ahead and upgrade the system and and and last, but not the least from a global management perspective. Now, a customer has an independent data view of their data estate, independent from a storage estate. And data services. Council can blend the two to give a consistent view or you can just look at the fleet view or the data view. >>It's kind of the Holy Grail. I mean I've been in this business a long time and I think I t. People have dreamt about you know this kind of capability for for a long long time. I wonder if we could sort of stay on the customers for a moment here and and talk about what's enabled. Now everybody's talking digital transformation that I joke about the joke. Not funny. The force marched to digital with Covid uh and we really wasn't planned for but the customers really want to drive now that digital transfer some of them are on the back burner and now they're moving to the front burner. What are the outcomes that are that are enabled here? Omar. >>Excellent. So so on on a typical basis for a traditional I. T. Customer, this cloud operational model means that you know information technology staff can move a lot faster and they can be a lot more productive on the things that are directly relevant to their business. They can get up to 99% of the savings back to spend more time on strategic projects or best of all spend time with their families rather than managing and upgrading infrastructure and fleets of infrastructure. Right. For line of business owners, the new experience means that their data infrastructure can be presented can be provision where the self service on demand type of capability. Uh They necessarily don't have to be in the data center to be able to make those decisions. Capacity management, performance management, all of that is died in and presented to them wherever they are easy to consume SAS based models and especially for data innovators, whether it's D B A s, uh whether it's data analysts, they can start to consume infrastructure and ultimately data as a code to speed up their app development because again, the context that we're bringing forward is the context of data decoupling it from. Actually, storage management, storage management and data management are now two separate domains that can be presented through a single console to tie the end to end picture for a customer. But at the end of the day, what we have felt is that customers really really want to rely and move forward with the data management and leave infrastructure management to machine oriented task, which we have completely automated on their behalf. >>So I'm sure you've heard you got the memo about, you know, H H P going all in on as a service. Uh it's clear that the companies all in. How does this announcement fit in to that overall mission, Sandeep >>Dave. We believe the future is edge to cloud and our mission is to be the edge to cloud platform as a service company and as as HB transforms HP Green Lake is our unified cloud platform. Hp Green Link is how we deliver cloud services and agile cloud experiences to customers, applications and data across the edge to cloud. With the storage announcement that we made recently, we announced that we're expanding HB Green Lake with as a service transformation of the HPV storage business to a cloud native software defined data services business. And this expands storage as a service delivering full cloud experience to our customers data across edge and on prem environment across the board were committed to being a strategic partner for every one of our customers and helping them accelerate their digital transformation. >>Yeah, that's where the puck is going guys. Hey as always great conversation with with our friends from HP storage. Thanks so much for the collaboration and congratulations on the announcements and I know you're not done yet. >>Thanks. Dave. Thanks. Dave. All right. Dave. It's a pleasure to be here. >>You're very welcome. And thank you for being with us for hp. You discovered 2021. You're watching the cube, the leader digital check coverage. Keep it right there, but right back. >>Mhm. Mhm.

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cube. We're here with Omar assad is the vice president GM of H P S H C I and primary storage and data management business. And Sandeep Singh was the vice president of marketing for HP storage division. Welcome gents. Great to see you. >>Great to be here. Dave, >>It's a pleasure to be here today. >>Hey, so uh, last month you guys, you made a big announcement and and now you're, you know, shining the spotlight on that here at discover Cindy. Maybe you can give us a quick recap, what do we need to know? >>Yeah, Dave. We announced that we're expanding HB Green Lake by transforming HB storage to a cloud native software defined data services business. We unveiled a new vision for data that accelerates data, dream of transformation for our customers. Uh and it introduced a and we introduced the data services platform that consists of two game changing innovations are first announcement was Data services cloud console. It's a SAS based console that delivers the cut operational agility and it's designed to unify data operations through a suite of cloud data services. Our 2nd announcement is HPE. Electra. It's cloud native data infrastructure to power your data edge to cloud. And it's managed natively with data services cloud console to bring that cloud operational model to our customers wherever their data lives together with the data services platform. Hp Green Green Lake brings that cloud experience to our customers data across edge and on premises environment and lays the foundation for our customers to shift from managing storage to managing data. >>Well, I think it lays the foundation for the next decade. You know, when we entered this past decade, we we were Ricky bobby's terms like software led that that sort of morphed into. So the software defined data center containers with kubernetes, Let's zoom out for a minute. If we can homer maybe you could describe the problems that you're trying to address with this announcement. >>Thanks dave. It's always a pleasure talking to you on these topics. So in my role as general manager for primary storage, I speak with the hundreds of customers across the board and I consistently hear that data is at the heart of what our customers are doing and they're looking for a data driven transformative approach to their business. But as they engage on these things, there are two challenges that they consistently faced. The first one is that managing storage at scale Is rife with complexity. So while storage has gotten faster in the last 20 years, managing a single array or maybe two or three arrays has gotten simpler over time. But managing storage at scale when you deploy fleet. So storage as customers continue to gather, store and lifecycle that data. This process is extremely frustrating for customers. Still I. T. Administrators are firefighting, they're unable to innovate for their business because now data spans all the way from edge to corridor cloud. And then with the advent of public cloud there's another dimension of multi cloud that has been added to their data sprawl. And then secondly what what we what we consistently hear is that idea administrators need to shift from managing storage to managing data. What this basically means is that I. D. Has a desire to mobilize, protect and provision data seamlessly across its lifecycle and across the locations that it is stored at. Uh This ensures that I. D. Leaders uh and also people within the organization understand the context of the data that they store and they operate upon. Yet data management is an extremely big challenge and it is a web of fragmented data silos across processes across infrastructure all the way from test and dev to administration uh to production uh to back up to lifecycle data management. Uh And so up till now data management was tied up with storage management and this needs to change for our customers especially with the diversity of the application workloads as they're growing and as customers are expanding their footprint across a multi cloud environment >>just to add to almost uh response there. We recently conducted a survey that was actually done by E. S. She. Um and that was a survey of IT. decision makers. And it's interesting what it showcased, 93% of the respondents indicated that storage and data management complexity is impeding their digital transformation. 95% of the respondents indicated that solving storage and data management complexity is a top 10 business initiative for them and 94% want to bring the cloud experience on premises, >>you know, al china. And I think as you guys move to the sort of software world and container world affinity to developers homer, you talked about, you know, things like data protection and we talk about security being bolted on all the time. Now. It's designed in it's it's done at sort of the point of creation, not as an afterthought. And that's a big change that we see coming. Uh But let's talk about, you know, what also needs to change as customers make the move from this idea of managing storage to to managing data or maybe you can take that one. >>That's a that's a that's a very interesting problem. Right. What are the things that have to be true in order for us to move into this new data management model? So, dave one of the things that the public cloud got right is the cloud operational model uh which sets the standard for agility and a fast pace for our customers in a classic I. T. On prime model, if you ever wanted to stand up an application or if you were thinking about standing up a particular workload, uh you're going to file a series of I. T. Tickets and then you're at the mercy of whatever complex processes exist within organization and and depending on what the level of approvals are within a particular organization, standing up a workload can take days, weeks or even months in certain cases. So what cloud did was they brought that level of simplicity for someone that wanted to instead she ate an app. This means that the provisioning of underlying infrastructure that makes that workload possible needs to be reduced to minutes from days and weeks. But so what we are intending to do over here is to bring the best of both worlds together so that the cloud experience can be experienced everywhere with ease and simplicity and the customers don't need to change their operating model. So it's blending the two together. And that's what we are trying to usher in into this new era where we start to differentiate between data management and storage management as two independent things. >>Great, thank you for that. Omer sometimes I wonder if you could share with the audience, you know, the vision that you guys unveiled, What does it look like? How are you making it actually substantive and and real? >>Yeah. Dave. That's also great question. Um across the board it's time to reimagine data management. Everything that homer shared. Those challenges are leading to customers needing to break down the silos and complexity that plagues these distributed data environments. And our vision is to deliver a new data experience that helps customers unleash the power of data. We call this vision unified data jobs, Unified Data Ops integrates data centric policies to streamline data management, cloud native control to bring the cloud operational model to where customers data labs and a I driven insights to make the infrastructure invisible. It delivers a new data experience to simplify and bring that agility of cloud to data infrastructure. Streamline data management and help customers innovate faster than ever before. We're making the promise of Unified Data Ops Real by transforming Hve storage to a cloud native software defined data services business and introducing a data services platform that expands Hve Green Lake. >>I mean, you know, you talk about the complexity, I see, I look at it as you kind of almost embracing the complexity saying, look, it's gonna keep getting more complex as the cloud expands to the edge on prem Cross cloud, it gets more complex underneath. What you're doing is you're almost embracing that complexity and putting a layer over it and hiding that complexity from from the end customer that and so they can spend their time doing other things over. I wonder if you can maybe talk a little bit more about the data services console, Is it sort of another software layer to manage infrastructure? What exactly is it? >>It's a lot more than that, Dave and you're you're 100% right. It's basically we're attempting in this release to attack that complexity head on. So simply put data services. Cloud console is a SAS based console that delivers cloud operational model and cloud operational agility uh to our customers. It unifies data operations through a series of cloud data services that are delivered on top of this console to our customers in a continuous innovation stream. Uh And what we have done is going back to the point that I made earlier separating storage and data management and putting the strong suites of each of those together into the SAS delivered console for our customers. So what we have done is we have separated data and infrastructure management away from physical hardware to provide a comprehensive and a unified approach to managing data and infrastructure wherever it lives. From a customer's perspective, it could be at the edge, it could be in a coal. Oh, it could be in their data center or it could be a bunch of data services that are deployed within the public cloud. So now our customers with data services. Cloud console can manage the entire life cycle of their data from all the way from deployment, upgrading and optimizing it uh from a single console from anywhere in the world. Uh This console is designed to streamline data management with cloud data services that enable access to data. It allows for policy-based data protection, it allows for an organizational wide search on top of your storage assets. And we deliver basically a 360° visibility to all your data from a single console that the customer can experience from anywhere. So, so if you look at the journey the way we're deciding to deliver this. So the first, in its first incarnation, uh Data services, Cloud console gives you infrastructure and cloud data services to start to do data management along with that. But this is that foundation that we are placing in front of our customers, the SAS console, through which we get touch our customers on a daily basis. And now as our customers get access to the SAAS platform on the back end, we will continue to roll in additional services throughout the years on a true SAS based innovation base for our customers. And and these services can will be will be ranging all the way from data protection to multiple out data management, all the way to visibility all the way to understanding the context of your data as it's stored across your enterprise. And in addition to that, we're offering a consistent revised unified Api which allows for our customers to build automation against their storage infrastructure. Without ever worrying about that. As infrastructure changes, uh, the A. P I proof points are going to break for them. That is never going to happen because they are going to be programming to a single SAS based aPI interface from now on. >>Right. And that brings in this idea of infrastructure as code because you talk about as a service to talk about Green Lake and and my question is always okay. Tell me what's behind that. And if and if and if and if you're talking about boxes and and widgets, that's a it's a problem. And you're not, you're talking about services and A P. I. S and microservices and that's really the future model and infrastructure is code and ultimately data as code is really part of that. So, All right. So you guys, I know some of your branding folks, you guys give deep thought to this. So the second part of the announcement is the new product brands and deep maybe you can talk about that a little bit. >>Sure. Ultimately delivering the cloud operational model requires cognitive data infrastructure and that has been engineered to be natively managed from the cloud. And that's why we have also introduced H. P. E. Electra. Omar, Can you perhaps described HB electro even more. >>Absolutely. Thank you. Sandy. Uh, so with with HB Electoral we're launching a new brand of cloud native hardware infrastructure to power our customers data all the way from edge to the core to the cloud. The releases are smaller models for the edge then at the same time having models for the data center and then expanding those services into the public cloud as well. Right. All these hardware devices, Electoral hardware devices are cloud native and powered by our data services. Cloud Council, we're announcing two models with this launch H. P. E Electoral 9000. Uh, this is for our mission critical workloads. It has its history and bases in H P E. Primera. It comes with 100% availability guarantee. Uh It's the first of its type in the industry. It comes with standard support contract, no special verb is required. And then we're also launching HB Electoral 6000. Uh These are based in our history of uh nimble storage systems. Uh These these are for business critical applications, especially for that mid range of the storage market, optimizing price, performance and efficiency. Both of these systems are full envy any storage powered by our timeless capabilities with data in place upgrades. And then they both deliver a unified infrastructure and data management experience through the data services, cloud console. Uh And and and at the back end unified Ai Ops experience with H P. E. Info site is seamlessly blended in along with the offering for our >>customers. So this is what I was talking about before. It's sort of not your grandfather's storage business anymore. This is this is this is something that is part of that, that unified vision, that layer that I talked about, the A. P. I. Is the program ability. So you're you're reaching into new territory here. Maybe you can give us an example of how the customers experience what that looks like. >>Excellent. Love to Dave. So essentially what we're doing is we're changing the storage experience to a true cloud operational model for our customers. These recent announcements that we just went through along with, indeed they expand the cloud experience that our customers get with storage as a service with HP Green Lake. So a couple of examples to make this real. So the first of all is simplified deployment. Uh So I t no longer has to go through complex startup and deployment processes. Now all you need to do is these systems shipped and delivered to the customer's data center. Operational staff just need to rack and stack and then leave connect the power cable, connect the network cable. And the job is done. From that point onwards, data services console takes over where you can onboard these systems, you can provision these systems if you have a pre existing organization wide security as well as standard profile setup in data services console, we can automatically apply those on your behalf and bring these systems online. From a customer's perspective, they can be anywhere in the world to onboard these systems, they could be driving in a car, they could be sitting on a beach. Uh And and you know, these systems are automatically on boarded through this cloud operational model which is delivered through the SAAS application for our customers. Another big example. All that I'd like to shed light on is intent based provisioning. Uh So Dave typically provisioning a workload within a data center is an extremely spreadsheet driven trial and error kind of a task. Which system do I land it on? Uh Is my existing sl is going to be affected which systems that loaded which systems are loaded enough that I put this additional workload on it and the performance doesn't take. All of these decisions are trial and error on a constant basis with cloud Data services console along with the electron new systems that are constantly in a loop back information feeding uh Typical analytics to the console. All you need to do is to describe the type of the workload and the intent of the workload in terms of block size S. L. A. That you would like to experience at that point. Data services console consults with intra site at the back end. We run through thousands of data points that are constantly being given to us by your fleet and we come back with a few recommendations. You can accept the recommendation and at that time we go ahead and fully deploy this workload on your behalf or you can specify a particular system and then people try to enforce the S. L. A. On that system. So it completely eliminates the guesswork and the planning that you have to do in this regard. Uh And last but not the least. Uh You know, one of the most important things is, you know, upgrades has been a huge problem for our customers. Uh And typically oftentimes when you're not in this constant, you know, loop back communication with your customers. It often is a big challenge to identify which release or which bug fix or which update goes on to which particular machine, all of that has been completely taken away from our customers and fully automated. Uh We run thousands of signatures across are installed base. We identify which upgrades need to be curated for which machines in a fleet for a particular customer. And then if it applies to that customer we presented, and if the customer accepts it, we automatically go ahead and upgrade the system and and and last, but not the least from a global management perspective. Now, a customer has an independent data view of their data estate, independent from a storage estate and data services. Council can blend the two to give a consistent view or you can just look at the fleet view or the data view. >>It's kind of the holy Grail. I mean I've been in this business a long time and I think I. T. People have dreamt about you know this kind of capability for for a long long time. I wonder if we could sort of stay on the customers for a moment here and and talk about what's enabled. Now. Everybody's talking digital transformation. I joke about the joke. Not funny. The force marched to digital with Covid. Uh and we really wasn't planned for but the customers really want to drive now that digital transfer some of them are on the back burner and now they're moving to the front burner. What are the outcomes that are that are enabled here? Omar. >>Excellent. So so on on a typical basis for a traditional I. T. Customer this cloud operational model means that you know information technology staff can move a lot faster and they can be a lot more productive on the things that are directly relevant to their business. They can get up to 99% of the savings back to spend more time on strategic projects or best of all spend time with their families rather than managing and upgrading infrastructure and fleets of infrastructure. Right for line of business owners, the new experience means that their data infrastructure can be presented can be provision where the self service on demand type of capability. Uh They necessarily don't have to be in the data center to be able to make those decisions. Capacity management, performance management, all of that is died in and presented to them wherever they are easy to consume. SaS based models and especially for data innovators, whether it's D B A s, whether it's data analysts, they can start to consume infrastructure and ultimately data as a code to speed up their app development because again, the context that we're bringing forward is the context of data decoupling it from. Actually, storage management, storage management and data management are now two separate domains that can be presented through a single console to tie the end to end picture for a customer. But at the end of the day, what we have felt is that customers really, really want to rely and move forward with the data management and leave infrastructure management to machine oriented task, which we have completely automated on their behalf. >>So I'm sure you've heard you got the memo about, you know, H H p going all in on as a service. Uh it is clear that the companies all in. How does this announcement fit in to that overall mission? Cindy >>dave We believe the future is edge to cloud and our mission is to be the edge to cloud platform as a service company and as as HB transforms HP Green Lake is our unified cloud platform. Hp Green Link is how we deliver cloud services and agile cloud experiences to customers applications and data across the edge to cloud. With the storage announcement that we made recently, we announced that we're expanding HB Green Lake with as a service transformation of the HPV storage business to a cloud native software defined data services business. And this expands storage as a service, delivering full cloud experience to our customers data across edge and on prem environment across the board were committed to being a strategic partner for every one of our customers and helping them accelerate their digital transformation. >>Yeah, that's where the puck is going guys. Hey as always great conversation with with our friends from HP storage. Thanks so much for the collaboration and congratulations on the announcements and and I know you're not done yet. >>Thanks. Dave. Thanks. Dave. >>Thanks. Dave. It's a pleasure to be here. >>You're very welcome. And thank you for being with us for hp. You discovered 2021 you're watching the cube, the leader digital check coverage. Keep it right there, but right back. >>Yeah. Yeah.

(upbeat music) >> Hello everyone, and welcome to The CUBE where we're covering the recent news from Hewlett Packard enterprise, making moves and storage. And with me are Omar Assad, vice president and general manager for Primary Storage, HCI and data management at HPE. And Sandeep Singh, who's the vice president of Storage Marketing at Hewlett Packard Enterprise. Gentlemen, welcome back to the CUBE Great to see you both. >> David, it's pleasure to be here. >> Always a pleasure talking to you David, thank you so much. >> Oh, it's my pleasure. Hey, so we just watched HPE make a big announcement and I wonder Sandeep if you could give us a quick recap. >> Yeah, of course, Dave. In the world of enterprise storage, there hasn't been a moment like this in decades upon at which everything is changing for data and infrastructure. And it's really coming at the nexus of data cloud and AI that's opening up the opportunity for customers across industries to accelerate their data-driven transformation. Building on that, we just unveiled a new vision for data that accelerates the data driving transformation for customers edge to cloud. And to pay that off, we introduce a new data services platform that consists of two game-changing innovations. First it's a data services cloud console which is a SAS based console that delivers cloud operational agility for customers. And it's designed to unify data operations through a suite of cloud services. Then our second announcement is HPE Electra. HB Electra is a cloud native data infrastructure portfolio to power your data edge to cloud. It's managed natively with data services cloud console and it brings that cloud operational model to customers wherever their data lives. These innovations are really combined with our industry leading AI ops platform which is HPE in foresight, and combine these innovations radically simplify and bring that cloud operational model to customers or data and infrastructure management. And it gives the opportunity for streamlining data management across the life cycle. These innovations are making it possible for organizations across the industries to unleash the power of data. >> That's kind of cool, I mean, a lot of the stuff we've been talking about for all these years is sort of this unified layer across all clouds on prem, AI injected in, I could tell you're excited and it sounds like you you can't wait to get these offerings in the hands of customers. But I wonder if we get back up a little a minute. Omer, maybe you could describe the problem statement that you're addressing with this announcement. What are customers really, what are their pain points? >> Excellent question, Dave. So in my role, as the general manager for data management and storage here at HPE, I get the wonderful opportunity to talk to hundreds of customers in a year. And as time has progressed, as the amount of data under organizations management has continued to increase. What I have noticed is that recently there are three main themes that are continuously emerging and are now bubbling at the top. The first one is storage infrastructure management itself is extremely complex for customers. While there have been lots of leaps and down progress in managing a single array or managing two arrays with a lot of simplification of the UI and maybe some modern UI are present. But as the problem starts to get at scale, as customers acquire more, and more assets to store and manage their data on premise, the management at scale is extremely complex. Yes, storage has gotten faster. Yes, flash has had a profound effect on performance availability and latency access to the data but infrastructure management and storage management as a whole has become a pain for customers and it's a constant theme as storage lifecycle management comes up, storage refresh has come up and deploying and managing storage infrastructure at scale comes up. So that's one of the main problems that I've been seeing as I talk to customers. Now, secondly, a lot of customers are now talking about two different elements. One is storage and storage deployment and life cycle management. And the second is the management of data that is stored on those storage devices. As the amount of data grows the silos continue to grow, a single view of life cycle management of data customers don't get to see it. And lastly, one of the biggest things that we see is a lot of customers are now asking, how can I extract a value from this data under my management because they can't seem to parse through the silos. So there is an incredible amount of productivity lost when it comes to data management as a whole, which is just fragmented into silos and then from a storage management. And when you put these two together and especially add two more elements to it which is hybrid management of data or a multi-cloud management of data, the silos and the sprawl just continues and there is nothing that is stitching together this thing at scale. So these are the three main themes that constantly appear in these discussions. Although in spite of these, a lot of modern enhancements in storage. >> Well, I wonder if I could comment guys. Is I've been following this industry for a number of years and you're absolutely right Omer. I mean, if you look at the amount of money and time and energy that's spent into or put into the data architectures, people are frustrated, they're not getting enough out of it. And I'd note that, the prevailing way in which we've attacked complexity historically is you build a better box. And well, that system was maybe easier to manage than the predecessor systems. All it did is create another silo and then the cloud, despite its inherent simplicity, that was another disconnected siloed. So then we threw siloed management solutions at the problem, and we're left with this collection of point solutions with data sort of trapped inside. So I wonder if you could give us your thoughts on that and do you agree? What data do you have around this problem statement? >> Yeah, Dave that's a great point. And actually ESG just recently conducted a survey of over 250 IT decision makers. And that actually brings one of the perfect validations of the problems that Omer, and you just articulated. What it showed is that 93% of the respondents indicated that storage and data management, that complexity is impeding their digital transformation. On average, the organizations have over 23 different data management tools which just typifies and is a perfect showcase of the fragmentation and the complexity that exists in that data management. And 95% of the respondents indicated that solving storage and data management, that complexity is a top 10 business initiative for them. And actually top five for 67% of the respondents. So it's a great validation across the board. >> Well, it's fresh in their minds too, because pre pandemic there was probably a mixed picture, right? It was probably well there's complacency or we're not moving fast enough, we have other priorities, but they were forced into this. Now they know what the real problem is. It's front and center. I liked that you're putting out there in your announcement, this sort of future state that you're envisioning for customers. And I wonder if we could sort of summarize that and share with our listeners that vision that you unveiled, what does it look like and how are you making it real? >> Yeah, overall, we feel very strongly that it's time for our customers to reimagine data management. And our vision is that customers need to break down the silos and complexity that plagues the distributed data environments. And they need to experience a new data experience across the board. That's going to help them accelerate their data-driven transformation. And we call this vision unified data ops. Unified data ops integrates data centric policies across the board to streamline data management, cloud native control and operations, to bring that agility of cloud and the operational model to wherever data lives. And AI driven insights and intelligence to make the infrastructure invisible. It delivers a whole new experience to customers to radically simplify and bring the agility of talent to data and data infrastructure. Streamlined data management, and really help customers innovate faster than ever before. And we're making the promise of unified data ops real by transforming the entire HPE storage business to a cloud native software defined data services. And that's through introducing a data services platform that expands HPE GreenLake. >> I mean, the key word I take away there Sandeep is invisible. I mean, as a customer I want you to abstract that complexity away that underlying infrastructure complexity is. I just don't want to see it anymore over. Omer, I wonder if we could start with the first part of the announcement. Maybe you can help us unpack data services, cloud console. I mean, people are immediately going to think it's just another software product to manage infrastructure. But to really innovate, I'm hoping that it's more than that. >> Absolutely, David, it's a lot more than that. What did we have done fundamentally at the root of the problem is we have taken the data and infrastructure control away from the hardware and through that, we provided a unified approach to manage the data wherever it lives. It's a full blown SAS console, which our customers get onto. And from there they can deploy appliances, manage appliances, lifecycle appliances and then they're not only stop at that, but then go ahead and start to get context around their data. But all of that is available through a SAS platform, a SAS console. 'Cause as every customer onboard themselves and their equipment and their storage infrastructure onto this console, then they can go ahead and define role-based access for different parts of their organization. They can also apply role-based access to HPE GreenLake management personnel, so they can come in and do and perform all the operations for the customers. We at the same console, by just being another access control methodology in that. And then in addition to that, data mobility is extremely important to our customers. How do you make data available in different hyperscaler clouds? If the customer's digital transformation requires that. So again, from that single cloud console, from that single data console, which we are naming here as data services console, customers are able to curate the data, maneuver the data, pre-position the data into different hyperscalers. But the beautiful thing is that the entire view of the storage infrastructure, the data with its that is stored on top of that access control methodologies and management framework is operational from a single SAS console which the customer can decide to give access to whichever management entity or authority comes into help them. And then what this leads us into is then combining these things into a northbound API. So anybody that wants to streamline operational manageability can then use these APIs to program against a single API which will then control the entire infrastructure on behalf of the customer. So if somebody, they, what this is, is it is bringing that cloud operational model that was so desired by each one of our customers into their data centers. And this is what I call an in-place transformation of a management experience for our customer by making them seamlessly available on a cloud operational model for their infrastructure. >> Yeah, and you've turned that into essentially an API with a lot of automation, that's great. So, okay. So that's kind of how you're trying to change the game here. You're charting new territory. You've talked to hundreds and hundreds of customers every year. I wonder if you could paint a picture from the customer perspective. How does their experience actually change? >> Wonderful, Dave. This allows me to break it down into bits and bites further for you. And I love that, right? So the way you look at it is, recently, the storage management from an, as we talked about earlier from an array perspective or maybe two arrays perspective has been simplified. I mean, it's a solved problem. But when you start to imagine deploying hundreds of arrays and these are large customers, they have massive amounts of data assets, storage management hasn't scaled along as the infrastructure scales. But if you look at the consumer world, you can have hundreds of devices, but the ownership model is completely set. So the inspiration for solving this problem for us actually lied, was inspired from consumerization of IT. And that's a big trend over here. So now we're changing the customer's ownership model, the customer's deployment model and the customer's data management model into a true cloud first model. So let me give some of the examples of that, right? So first of all, let's talk about deployment. So previously deployment has been a massive challenge for our customers. What does deployment in this new data services console world looks like? Devices show up, you rack them up and then you plug in the power cable, you plug in the network cable, and then you walk out of the data center. Data center administrator or the storage administrator, they will be on their iPad, on their data services console or iPhone or whatever the device of their choices, and from that console, from that point on, the device will be registered, onboarded. Its initial state will be given to it from the cloud. And if the customer has some predefined states for their previous deployment model already saved with the data console, they don't even need to do that. We'll just take that and apply that state and induct the device into the fleet. That's just one example. It's extremely simple. Plug in the power cable, plug in the network cable and the data center operational manager just walks out. After that you could be on the beach, you could be at your home, you could be driving in a car and this don't, I advise people not to fiddle with their I-phones when they're driving in a car, but still you could do it if you want to. So that's just one part from a deployment methodology perspective. Now, the second thing that Sandeep and I often bounce ideas bond is is it is provisioning of a workload. It's like a science these days. And is this array going to be able to absorb my workload? Is the latency going to go South? Does this workload latency profile match this particular piece of device in my data center? All of this is extremely manual. And it literally takes, I mean, if you talk to any of the customers or even analysts, deploying a workload is a massive challenge. It's a guesswork that you have to model and basically see how it works out. I think based on HPE info site, we're collecting hundreds and millions of data points from all these devices. So now to harness that and present that back to a customer in a very simple manner so that we can model on their behalf to the data services console, which is now workload of it. you just describe your workload. Hey, I'm going to need these many IOPS. And by the way, this happens to be my application. And that's it. On the backend, because we're managing your infrastructure, the cloud console understands your entire fleet. We are seeing the statistics and the telemetric coming off of your systems. And because now you've described the workload for us we can do that matching for you. And what intent based provisioning does is, describe your workloads in two or three clicks or maybe two or three API construct formats and we'll do the provisioning, the deployment and bringing it up for you on your behalf on the right pieces of infrastructure that matched it. And if you don't like our choices, you can manually change it as well. But from a provisioning perspective, a thing that took days can now come down to a couple of minutes of the description. And lastly then, global data management, distributed infrastructure from edge to cloud, invisible upgrades, only upgrading the right amount of infrastructure that needs the upgrade. All of that just comes rolling along with it, right? So those are some of the things that this data services console as a SAS management and scale allows you to do. >> And actually, if I can just jump in and add a little bit. What Omer described, especially with intent based provisioning, that's really bringing a paradigm shift to provisioning. It's shifting it from a long centric to app centric provisioning. And when you combine it with identity management and role-based access, what it means is that you're enabling self-service on demand provisioning of the underlying data infrastructure to accelerate the app workload deployment. And you're eliminating guesswork and providing the ability to be able to optimize service level objectives. >> Yeah, it sounds like you've really nailed in an elegant way that provisioning challenge. I've been saying for years if your primary expertise is deploying logical unit numbers you better find some other skills because the day is coming that that's just going to get automated away. So that's cool. There's another issue that I'm sure you've thought about, but I wonder if you could address. I mean, you've got the definition of cloud is changing, the cloud is expanding to on prem expand. The cloud is going out to the edge, it's going across clouds. And so security becomes a big issue that threat surface is expanding. The operating model is changing. So how are you thinking about addressing those security concerns? >> Excellent question, Dave. So most of the organizations that we've talked to... In today's modern world, almost every customer that I've talked to has deployed either some sort of a cloud console where they're either one of the customers for the hyperscalers or buy in for SAS based applications are pervasive across the customer base. And as you know, we were the first ones to introduce the automatic telemeter management through HPE info site. That's one of the largest storage SAS services in production today that we operate on behalf of our customers, which has, Dave, about 85% connectivity rate. So from that perspective, keeping customers data secure, keeping customers telemetry information secure, we're no stranger to that. Again, we follow all security protocols that any cloud operational SAS service would do so. Reverse tunneling, the firewall compliancy security audit logs that are published to our customers and published to customers chief information security officers. So all of those, what I call crossing the T's and dotted the I's, we do that with security expert and security policies for which each of our customers has a different set of rules. And we have a property engagement model that we go through that particular audit process for our customers. Then secondly, Dave, the data services cloud console is actually built on a fundamental cloud deployment technology that is not, sort of new. Aruba central, which is an Aruba management console which is also an HPE company it's been deployed, it's managing millions of access points in a SAS framework for our customers. So the fundamental building blocks of the data storage console from a basic enablement perspective come from the Aruba central console. And what we've taken is we've taken those generic cloud-based SAS services and then built data and storage centric SAS services on top of that and made them available to our customers. >> Yeah, I really like the Aruba. You picked that up several years ago . And it's same thing with, with info site, the way that you bring it to other parts of the portfolio. Those are really good signs to watch of successful acquisitions. All right, there's a lot here. I want to talk about the second part of the announcement. I know your branding team, you guys are serious about branding. That new product brand, maybe you could talk about that. >> So again, so delivering the cloud operational model is just the first piece, right? And now the second part of the announcement is delivering the cloud native hardware infrastructure which is extremely performance to go along with this cloud operational model. So what we have done Dave, in this announcement is we've announced HPE Electra. This is our new brand for our cloud native infrastructure to power your data and its appliances from core to the edge, to the cloud. And what it does is it takes the cloud operational model and this hardware is powered by that. It's completely wrapped around that. And so HPE Electra is available in two models right now, the HB electron 9,000, which is available for mission critical workloads, for those high intensity workloads with a hundred percent availability guarantee where no failure is ever an option. And then it's also available as HPE Electra 6,000, which is available for general purpose, business critical workloads, generally trying to address that mid range of the storage market. And both of these systems are full 100% NBME front and back. And they're powered by the same unified cloud management operational experience that the data cloud console provides. And what it does is it allows our customers to simplify the deployment model. It simplifies their management model and really, really allows them to focus on the context, the data and the app diversity, whereas data mobility, data connectivity, data management in a multi-cloud world is then completely obstructed from them. >> [Sandeep And Dave-- >> Go ahead, please. >> Just to jump in. HPE Electra combined with data services cloud console is delivering a cloud experience that makes deploying and scaling the application workloads as simple as flipping a switch. >> It really does. It really does. And I'm very comfortable in saying this, like HPE in foresight, we were the first in the industry to bring AI based elementary and support enabled metrics to work. And then here with data services console and the hardware that goes with it, we're just completely transforming the storage ownership and a storage management model. And for our customers, it's a seamless, non-disruptive upgrade with fully data in place upgrade. And they transform to a cloud operational model where they can manage their infrastructure better where they are through a complete consumer grade SAS console, is again the first of its kind, when you look at storage management and storage management at scale. >> And I like how you're emphasizing that management layer, but underneath you've got all the modern hardware technologies too which is important, because it's a performance it's got to be, a good price performance. So now can we bring this back again to the customers? What are the outcomes that this is going to enable for them? >> So I think Dave, the first and the foremost thing is as they scale their storage infrastructures, they don't have to think. It's really as simple as yeah, just send it to the data center, plug in the power cable, plug in the network cable and up it comes. And from that point onwards, the life cycle and the device management aspect are completely abstracted by the data services console. All they have to focus is I just have new capacity available to me and when I have an application, the system will figure it out for me where they need to deploy. So no more needing the guesswork, the Excel sheets of capacity management, the charge back models, none of that stuff is needed. And for customers that are looking to transform their applications, customers looking to refactor their applications into a hyperscaler model, or maybe transform from VM to containers, all they need to think about and focus is on that. The data will just follow these workloads from that perspective. >> And David, just to almost response here. As I speak with customers, one of the things I'm hearing from IT is that line of business really wants IT to deliver that agility of cloud. Yet IT also has to deliver all of the enterprise reliability, availability, all of the data services. And what's fantastic here is that through this cloud operational model, IT can deliver that agility, that line of business owners are looking for. At the same time they're been under pressure to do a lot more with less. And through this agility, IT is able to get time back, be able to focus more on the strategic projects, at the same time, be able to get time back to spend more time with our families. That's incredibly important. >> Well, I love the sort of mindset shift I'm seeing from HPE. We're not talking about how much the box weighs, we're talking about the customer experience. And I wonder, you know, that kind of leads me, Sandeep to how this kind of fits in to this new. Really to me, I'm seeing the transformation before our eyes but how does it fit into HPE's overall mission? >> Well Dave, our mission overall is to be the edge to cloud platform as a service company with HPE GreenLake, being the key to delivering that cloud experience. And as Omer put it, be able to deliver that cloud experience wherever the customer data lives. And today we're advancing HPE GreenLake as a service transformation of the HPE storage business to a software defined cloud data services business overall. And for our customers, this translates to our operational and ownership experience that unleashes their agility, their data and their innovation. So we're super excited. >> Guys, I can tell you're excited. Thanks so much for coming to the CUBE and summarizing the announcements, congratulations and best of luck to both of you and to HPE and your customers. >> Thank you, Dave. It was a pleasure. >> Thanks, Dave. (upbeat music)

>>Edge computing is predict, projected to be a multi-trillion dollar business. You know, it's hard to really pinpoint the size of this market. Let alone fathom the potential of bringing software, compute, storage, AI, and automation to the edge and connecting all that to clouds and on-prem systems. But what, you know, what is the edge? Is it factories? Is it oil rigs, airplanes, windmills, shipping containers, buildings, homes, race cars. Well, yes and so much more. And what about the data for decades? We've talked about the data explosion. I mean, it's mind boggling, but guess what, we're gonna look back in 10 years and laugh. What we thought was a lot of data in 2020, perhaps the best way to think about edge is not as a place, but when is the most logical opportunity to process the data and maybe it's the first opportunity to do so where it can be decrypted and analyzed at very low latencies that that defines the edge. And so by locating compute as close as possible to the sources of data, to reduce latency and maximize your ability to get insights and return them to users quickly, maybe that's where the value lies. Hello everyone. And welcome to this cube conversation. My name is Dave Vellante and with me to noodle on these topics is Omar Assad, VP, and GM of primary storage and data management services at HPE. Hello, Omer. Welcome to the program. >>Hey Steve. Thank you so much. Pleasure to be here. >>Yeah. Great to see you again. So how do you see the edge in the broader market shaping up? >>Uh, David? I think that's a super important, important question. I think your ideas are quite aligned with how we think about it. Uh, I personally think, you know, as enterprises are accelerating their sort of digitization and asset collection and data collection, uh, they're typically, especially in a distributed enterprise, they're trying to get to their customers. They're trying to minimize the latency to their customers. So especially if you look across industries manufacturing, which is distributed factories all over the place, they are going through a lot of factory transformations where they're digitizing their factories. That means a lot more data is being now being generated within their factories. A lot of robot automation is going on that requires a lot of compute power to go out to those particular factories, which is going to generate their data out there. We've got insurance companies, banks that are creating and interviewing and gathering more customers out at the edge for that. >>They need a lot more distributed processing out at the edge. What this is requiring is what we've seen is across analysts. A common consensus is that more than 50% of an enterprise is data, especially if they operate globally around the world is going to be generated out at the edge. What does that mean? More data is new data is generated at the edge, but needs to be stored. It needs to be processed data. What is not required needs to be thrown away or classified as not important. And then it needs to be moved for Dr. Purposes either to a central data center or just to another site. So overall in order to give the best possible experience for manufacturing, retail, uh, you know, especially in distributed enterprises, people are generating more and more data centric assets out at the edge. And that's what we see in the industry. >>Yeah. We're definitely aligned on that. There's some great points. And so now, okay. You think about all this diversity, what's the right architecture for these deploying multi-site deployments, robo edge. How do you look at that? >>Oh, excellent question. So now it's sort of, you know, obviously you want every customer that we talk to wants SimpliVity, uh, in, in, and, and, and, and no pun intended because SimpliVity is reasoned with a simplistic edge centric architecture, right? So because let's, let's take a few examples. You've got large global retailers, uh, they have hundreds of global retail stores around the world that is generating data that is producing data. Then you've got insurance companies, then you've got banks. So when you look at a distributed enterprise, how do you deploy in a very simple and easy to deploy manner, easy to lifecycle, easy to mobilize and easy to lifecycle equipment out at the edge. What are some of the challenges that these customers deal with these customers? You don't want to send a lot of ID staff out there because that adds costs. You don't want to have islands of data and islands of storage and promote sites, because that adds a lot of States outside of the data center that needs to be protected. >>And then last but not the least, how do you push lifecycle based applications, new applications out at the edge in a very simple to deploy better. And how do you protect all this data at the edge? So the right architecture in my opinion, needs to be extremely simple to deploy. So storage, compute and networking, uh, out towards the edge in a hyperconverged environment. So that's, we agree upon that. It's a very simple to deploy model, but then comes, how do you deploy applications on top of that? How do you manage these applications on top of that? How do you back up these applications back towards the data center, all of this keeping in mind that it has to be as zero touch as possible. We at HBS believe that it needs to be extremely simple. Just give me two cables, a network cable, a power cable, tied it up, connected to the network, push it state from the data center and back up at state from the ed back into the data center. Extremely simple. >>It's gotta be simple because you've got so many challenges. You've got physics that you have to deal your latency to deal with. You got RPO and RTO. What happens if something goes wrong, you've gotta be able to recover quickly. So, so that's great. Thank you for that. Now you guys have hard news. W what is new from HPE in this space >>From a, from a, from a, from a deployment perspective, you know, HPE SimpliVity is just gaining like it's exploding, like crazy, especially as distributed enterprises adopt it as it's standardized edge architecture, right? It's an HCI box has got stories, computer networking, all in one. But now what we have done is not only you can deploy applications all from your standard V-Center interface, from a data center, what have you have now added is the ability to backup to the cloud, right? From the edge. You can also back up all the way back to your core data center. All of the backup policies are fully automated and implemented in the, in the distributed file system. That is the heart and soul of, of the SimpliVity installation. In addition to that, the customers now do not have to buy any third-party software into backup is fully integrated in the architecture and it's van efficient. >>In addition to that, now you can backup straight to the client. You can backup to a central, uh, high-end backup repository, which is in your data center. And last but not least, we have a lot of customers that are pushing the limit in their application transformation. So not only do we previously were, were one-on-one them leaving VMware deployments out at the edge sites. Now revolver also added both stateful and stateless container orchestration, as well as data protection capabilities for containerized applications out at the edge. So we have a lot, we have a lot of customers that are now deploying containers, rapid manufacturing containers to process data out at remote sites. And that allows us to not only protect those stateful applications, but back them up, back into the central data center. >>I saw in that chart, it was a light on no egress fees. That's a pain point for a lot of CEOs that I talked to. They grit their teeth at those entities. So, so you can't comment on that or >>Excellent, excellent question. I'm so glad you brought that up and sort of at that point, uh, uh, pick that up. So, uh, along with SimpliVity, you know, we have the whole green Lake as a service offering as well. Right? So what that means, Dave, is that we can literally provide our customers edge as a service. And when you compliment that with, with Aruba wired wireless infrastructure, that goes at the edge, the hyperconverged infrastructure, as part of SimpliVity, that goes at the edge, you know, one of the things that was missing with cloud backups is the every time you backup to the cloud, which is a great thing, by the way, anytime you restore from the cloud, there is that breastfeed, right? So as a result of that, as part of the GreenLake offering, we have cloud backup service natively now offered as part of HPE, which is included in your HPE SimpliVity edge as a service offering. So now not only can you backup into the cloud from your edge sites, but you can also restore back without any egress fees from HBS data protection service. Either you can restore it back onto your data center, you can restore it back towards the edge site and because the infrastructure is so easy to deploy centrally lifecycle manage, it's very mobile. So if you want to deploy and recover to a different site, you could also do that. >>Nice. Hey, uh, can you, Omar, can you double click a little bit on some of the use cases that customers are choosing SimpliVity for, particularly at the edge, and maybe talk about why they're choosing HPE? >>What are the major use cases that we see? Dave is obviously, uh, easy to deploy and easy to manage in a standardized form factor, right? A lot of these customers, like for example, we have large retailer across the us with hundreds of stores across us. Right now you cannot send service staff to each of these stores. These data centers are their data center is essentially just a closet for these guys, right? So now how do you have a standardized deployment? So standardized deployment from the data center, which you can literally push out and you can connect a network cable and a power cable, and you're up and running, and then automated backup elimination of backup and state and BR from the edge sites and into the data center. So that's one of the big use cases to rapidly deploy new stores, bring them up in a standardized configuration, both from a hardware and a software perspective, and the ability to backup and recover that instantly. >>That's one large use case. The second use case that we see actually refers to a comment that you made in your opener. Dave was where a lot of these customers are generating a lot of the data at the edge. This is robotics automation that is going to up in manufacturing sites. These is racing teams that are out at the edge of doing post-processing of their cars data. Uh, at the same time, there is disaster recovery use cases where you have, uh, you know, campsites and local, uh, you know, uh, agencies that go out there for humanity's benefit. And they move from one site to the other. It's a very, very mobile architecture that they need. So those, those are just a few cases where we were deployed. There was a lot of data collection, and there's a lot of mobility involved in these environments. So you need to be quick to set up quick, to up quick, to recover, and essentially you're up to your next, next move. >>You seem pretty pumped up about this, uh, this new innovation and why not. >>It is, it is, uh, you know, especially because, you know, it is, it has been taught through with edge in mind and edge has to be mobile. It has to be simple. And especially as, you know, we have lived through this pandemic, which, which I hope we see the tail end of it in at least 2021, or at least 2022. They, you know, one of the most common use cases that we saw, and this was an accidental discovery. A lot of the retail sites could not go out to service their stores because, you know, mobility is limited in these, in these strange times that we live in. So from a central center, you're able to deploy applications, you're able to recover applications. And, and a lot of our customers said, Hey, I don't have enough space in my data center to back up. Do you have another option? So then we rolled out this update release to SimpliVity verse from the edge site. You can now directly back up to our backup service, which is offered on a consumption basis to the customers, and they can recover that anywhere they want. >>Fantastic Omer, thanks so much for coming on the program today. >>It's a pleasure, Dave. Thank you. >>All right. Awesome to see you. Now, let's hear from red bull racing and HPE customer, that's actually using SimpliVity at the edge. Countdown really begins when the checkered flag drops on a Sunday. It's always about this race to manufacture >>The next designs to make it more adapt to the next circuit to run those. Of course, if we can't manufacture the next component in time, all that will be wasted. >>Okay. We're back with Matt kudu, who is the CIO of red bull racing? Matt, it's good to see you again. >>Great to say, >>Hey, we're going to dig into a real-world example of using data at the edge and in near real time to gain insights that really lead to competitive advantage. But, but first Matt, tell us a little bit about red bull racing and your role there. >>Sure. So I'm the CIO at red bull racing and that red bull race. And we're based in Milton Keynes in the UK. And the main job job for us is to design a race car, to manufacture the race car, and then to race it around the world. So as CIO, we need to develop the ITT group needs to develop the applications is the design, manufacturing racing. We also need to supply all the underlying infrastructure and also manage security. So it's really interesting environment. That's all about speed. So this season we have 23 races and we need to tear the car apart and rebuild it to a unique configuration for every individual race. And we're also designing and making components targeted for races. So 20 a movable deadlines, um, this big evolving prototype to manage with our car. Um, but we're also improving all of our tools and methods and software that we use to design and make and race the car. >>So we have a big can do attitude of the company around continuous improvement. And the expectations are that we continuously make the car faster. That we're, that we're winning races, that we improve our methods in the factory and our tools. And, um, so for, I take it's really unique and that we can be part of that journey and provide a better service. It's also a big challenge to provide that service and to give the business the agility, agility, and needs. So my job is, is really to make sure we have the right staff, the right partners, the right technical platforms. So we can live up to expectations >>That tear down and rebuild for 23 races. Is that because each track has its own unique signature that you have to tune to, or are there other factors involved there? >>Yeah, exactly. Every track has a different shape. Some have lots of strengths. Some have lots of curves and lots are in between. Um, the track surface is very different and the impact that has some tires, um, the temperature and the climate is very different. Some are hilly, some, a big curves that affect the dynamics of the power. So all that in order to win, you need to micromanage everything and optimize it for any given race track. >>Talk about some of the key drivers in your business and some of the key apps that give you a competitive advantage to help you win races. >>Yeah. So in our business, everything is all about speed. So the car obviously needs to be fast, but also all of our business operations needed to be fast. We need to be able to design a car and it's all done in the virtual world, but the, the virtual simulations and designs need to correlate to what happens in the real world. So all of that requires a lot of expertise to develop the simulation is the algorithms and have all the underlying infrastructure that runs it quickly and reliably. Um, in manufacturing, um, we have cost caps and financial controls by regulation. We need to be super efficient and control material and resources. So ERP and MES systems are running and helping us do that. And at the race track itself in speed, we have hundreds of decisions to make on a Friday and Saturday as we're fine tuning the final configuration of the car. And here again, we rely on simulations and analytics to help do that. And then during the race, we have split seconds, literally seconds to alter our race strategy if an event happens. So if there's an accident, um, and the safety car comes out, or the weather changes, we revise our tactics and we're running Monte Carlo for example. And he is an experienced engineers with simulations to make a data-driven decision and hopefully a better one and faster than our competitors, all of that needs it. Um, so work at a very high level. >>It's interesting. I mean, as a lay person, historically we know when I think about technology and car racing, of course, I think about the mechanical aspects of a self-propelled vehicle, the electronics and the light, but not necessarily the data, but the data's always been there. Hasn't it? I mean, maybe in the form of like tribal knowledge, if somebody who knows the track and where the Hills are and experience and gut feel, but today you're digitizing it and you're, you're processing it and close to real time. >>It's amazing. I think exactly right. Yeah. The car's instrumented with sensors, we post-process at Virgin, um, video, um, image analysis, and we're looking at our car, our competitor's car. So there's a huge amount of, um, very complicated models that we're using to optimize our performance and to continuously improve our car. Yeah. The data and the applications that can leverage it are really key. Um, and that's a critical success factor for us. >>So let's talk about your data center at the track, if you will. I mean, if I can call it that paint a picture for us, what does that look like? >>So we have to send, um, a lot of equipment to the track at the edge. Um, and even though we have really a great wide area network linked back to the factory and there's cloud resources, a lot of the trucks are very old. You don't have hardened infrastructure, don't have ducks that protect cabling, for example, and you could lose connectivity to remote locations. So the applications we need to operate the car and to make really critical decisions, all that needs to be at the edge where the car operates. So historically we had three racks of equipment, like a safe infrastructure, um, and it was really hard to manage, um, to make changes. It was too flexible. Um, there were multiple panes of glass, um, and, um, and it was too slow. It didn't run her applications quickly. Um, it was also too heavy and took up too much space when you're cramped into a garage with lots of environmental constraints. >>So we, um, we'd, we'd introduced hyperconvergence into the factory and seen a lot of great benefits. And when we came time to refresh our infrastructure at the track, we stepped back and said, there's a lot smarter way of operating. We can get rid of all the slow and flexible, expensive legacy and introduce hyperconvergence. And we saw really excellent benefits for doing that. Um, we saw a three X speed up for a lot of our applications. So I'm here where we're post-processing data, and we have to make decisions about race strategy. Time is of the essence in a three X reduction in processing time really matters. Um, we also, um, were able to go from three racks of equipment down to two racks of equipment and the storage efficiency of the HPE SimpliVity platform with 20 to one ratios allowed us to eliminate a rack. And that actually saved a hundred thousand dollars a year in freight costs by shipping less equipment, um, things like backup, um, mistakes happen. >>Sometimes the user makes a mistake. So for example, a race engineer could load the wrong data map into one of our simulations. And we could restore that VDI through SimpliVity backup at 90 seconds. And this makes sure it enables engineers to focus on the car to make better decisions without having downtime. And we sent them to, I take guys to every race they're managing 60 users, a really diverse environment, juggling a lot of balls and having a simple management platform like HPE SimpliVity gives us, allows them to be very effective and to work quickly. So all of those benefits were a huge step forward relative to the legacy infrastructure that we used to run at the edge. >>Yeah. So you had the nice Petri dish and the factory. So it sounds like your, your goals, obviously your number one KPI is speed to help shave seconds time, but also costs just the simplicity of setting up the infrastructure. >>Yeah. It's speed. Speed, speed. So we want applications absolutely fly, you know, get to actionable results quicker, um, get answers from our simulations quicker. The other area that speed's really critical is, um, our applications are also evolving prototypes, and we're always, the models are getting bigger. The simulations are getting bigger and they need more and more resource and being able to spin up resource and provision things without being a bottleneck is a big challenge in SimpliVity. It gives us the means of doing that. >>So did you consider any other options or was it because you had the factory knowledge? It was HCI was, you know, very clearly the option. What did you look at? >>Yeah, so, um, we have over five years of experience in the factory and we eliminated all of our legacy, um, um, infrastructure five years ago. And the benefits I've described, um, at the track, we saw that in the factory, um, at the track we have a three-year operational life cycle for our equipment. When into 2017 was the last year we had legacy as we were building for 2018. It was obvious that hyper-converged was the right technology to introduce. And we'd had years of experience in the factory already. And the benefits that we see with hyper-converged actually mattered even more at the edge because our operations are so much more pressurized time has even more of the essence. And so speeding everything up at the really pointy end of our business was really critical. It was an obvious choice. >>Why, why SimpliVity? What why'd you choose HPE SimpliVity? >>Yeah. So when we first heard about hyperconverged way back in the, in the factory, um, we had, um, a legacy infrastructure, overly complicated, too slow, too inflexible, too expensive. And we stepped back and said, there has to be a smarter way of operating. We went out and challenged our technology partners. We learned about hyperconvergence within enough, the hype, um, was real or not. So we underwent some PLCs and benchmarking and, and the, the PLCs were really impressive. And, and all these, you know, speed and agility benefits, we saw an HP for our use cases was the clear winner in the benchmarks. So based on that, we made an initial investment in the factory. Uh, we moved about 150 VMs in the 150 VDI into it. Um, and then as, as we've seen all the benefits we've successfully invested, and we now have, um, an estate to the factory of about 800 VMs and about 400 VDI. So it's been a great platform and it's allowed us to really push boundaries and, and give the business, um, the service that expects. >>So w was that with the time in which you were able to go from data to insight to recommendation or, or edict, uh, was that compressed, you kind of indicated that, but >>So we, we all telemetry from the car and we post-process it, and that reprocessing time really it's very time consuming. And, um, you know, we went from nine, eight minutes for some of the simulations down to just two minutes. So we saw big, big reductions in time and all, ultimately that meant an engineer could understand what the car was during a practice session, recommend a tweak to the configuration or setup of it, and just get more actionable insight quicker. And it ultimately helps get a better car quicker. >>Such a great example. How are you guys feeling about the season, Matt? What's the team's sentiment? >>Yeah, I think we're optimistic. Um, we w we, um, uh, we have a new driver >>Lineup. Uh, we have, um, max for stopping his carries on with the team and Sergio joins the team. So we're really excited about this year and, uh, we want to go and win races. Great, Matt, good luck this season and going forward and thanks so much for coming back in the cube. Really appreciate it. And it's my pleasure. Great talking to you again. Okay. Now we're going to bring back Omer for quick summary. So keep it real >>Without having solutions from HB, we can't drive those five senses, CFD aerodynamics that would undermine the simulations being software defined. We can bring new apps into play. If we can bring new them's storage, networking, all of that can be highly advises is a hugely beneficial partnership for us. We're able to be at the cutting edge of technology in a highly stressed environment. That is no bigger challenge than the formula. >>Okay. We're back with Omar. Hey, what did you think about that interview with Matt? >>Great. Uh, I have to tell you I'm a big formula one fan, and they are one of my favorite customers. Uh, so, you know, obviously, uh, one of the biggest use cases as you saw for red bull racing is Trackside deployments. There are now 22 races in a season. These guys are jumping from one city to the next, they've got to pack up, move to the next city, set up, set up the infrastructure very, very quickly and average formula. One car is running the thousand plus sensors on that is generating a ton of data on track side that needs to be collected very quickly. It needs to be processed very quickly, and then sometimes believe it or not, snapshots of this data needs to be sent to the red bull back factory back at the data center. What does this all need? It needs reliability. >>It needs compute power in a very short form factor. And it needs agility quick to set up quick, to go quick, to recover. And then in post processing, they need to have CPU density so they can pack more VMs out at the edge to be able to do that processing now. And we accomplished that for, for the red bull racing guys in basically two are you have two SimpliVity nodes that are running track side and moving with them from one, one race to the next race, to the next race. And every time those SimpliVity nodes connect up to the data center collector to a satellite, they're backing up back to their data center. They're sending snapshots of data back to the data center, essentially making their job a whole lot easier, where they can focus on racing and not on troubleshooting virtual machines, >>Red bull racing and HPE SimpliVity. Great example. It's agile, it's it's cost efficient, and it shows a real impact. Thank you very much. I really appreciate those summary comments. Thank you, Dave. Really appreciate it. All right. And thank you for watching. This is Dave Volante. >>You.

(mellow music) >> Okay, we're back with Matt Cadieux who is the CIO Red Bull Racing. Matt, it's good to see you again. >> Yeah, great to see you, Dave. >> Hey, we're going to dig into a real world example of using data at the edge and in near real-time to gain insights that really lead to competitive advantage. But first Matt, tell us a little bit about Red Bull Racing and your role there. >> Sure, so I'm the CIO at Red Bull Racing. And at Red Bull Racing we're based in Milton Keynes in the UK. And the main job for us is to design a race car, to manufacture the race car, and then to race it around the world. So as CIO, we need to develop, the IT team needs to develop the applications used for the design, manufacturing, and racing. We also need to supply all the underlying infrastructure, and also manage security. So it's a really interesting environment that's all about speed. So this season we have 23 races, and we need to tear the car apart, and rebuild it to a unique configuration for every individual race. And we're also designing and making components targeted for races. So 23 immovable deadlines, this big evolving prototype to manage with our car. But we're also improving all of our tools and methods and software that we use to design and make and race the car. So we have a big can-do attitude in the company, around continuous improvement. And the expectations are that we continue to make the car faster, that we're winning races, that we improve our methods in the factory and our tools. And so for IT it's really unique and that we can be part of that journey and provide a better service. It's also a big challenge to provide that service and to give the business the agility it needs. So my job is really to make sure we have the right staff, the right partners, the right technical platforms, so we can live up to expectations. >> And Matt that tear down and rebuild for 23 races. Is that because each track has its own unique signature that you have to tune to or are there other factors involved there? >> Yeah, exactly. Every track has a different shape. Some have lots of straight, some have lots of curves and lots are in between. The track's surface is very different and the impact that has on tires, the temperature and the climate is very different. Some are hilly, some are big curves that affect the dynamics of the car. So all that in order to win, you need to micromanage everything and optimize it for any given race track. >> And, you know, COVID has, of course, been brutal for sports. What's the status of your season? >> So this season we knew that COVID was here and we're doing 23 races knowing we have COVID to manage. And as a premium sporting team we've formed bubbles, we've put health and safety and social distancing into our environment. And we're able to operate by doing things in a safe manner. We have some special exhibitions in the UK. So for example, when people return from overseas that they do not have to quarantine for two weeks but they get tested multiple times a week and we know they're safe. So we're racing, we're dealing with all the hassle that COVID gives us. And we are really hoping for a return to normality sooner instead of later where we can get fans back at the track and really go racing and have the spectacle where everyone enjoys it. >> Yeah, that's awesome. So important for the fans but also all the employees around that ecosystem. Talk about some of the key drivers in your business and some of the key apps that give you competitive advantage to help you win races. >> Yeah, so in our business everything is all about speed. So the car obviously needs to be fast but also all of our business operations need to be fast. We need to be able to design our car and it's all done in the virtual world but the virtual simulations and designs need to correlate to what happens in the real world. So all of that requires a lot of expertise to develop the simulations, the algorithms, and have all the underlying infrastructure that runs it quickly and reliably. In manufacturing, we have cost caps and financial controls by regulation. We need to be super efficient and control material and resources. So ERP and MES systems are running, helping us do that. And at the race track itself in speed, we have hundreds of decisions to make on a Friday and Saturday as we're fine tuning the final configuration of the car. And here again, we rely on simulations and analytics to help do that. And then during the race, we have split seconds, literally seconds to alter our race strategy if an event happens. So if there's an accident and the safety car comes out or the weather changes, we revise our tactics. And we're running Monte Carlo for example. And using experienced engineers with simulations to make a data-driven decision and hopefully a better one and faster than our competitors. All of that needs IT to work at a very high level. >> You know it's interesting, I mean, as a lay person, historically when I think about technology and car racing, of course, I think about the mechanical aspects of a self-propelled vehicle, the electronics and the like, but not necessarily the data. But the data's always been there, hasn't it? I mean, maybe in the form of like tribal knowledge, if it's somebody who knows the track and where the hills are and experience and gut feel. But today you're digitizing it and you're processing it in close to real-time. It's amazing. >> Yeah, exactly right. Yeah, the car is instrumented with sensors, we post-process, we're doing video, image analysis and we're looking at our car, our competitor's car. So there's a huge amount of very complicated models that we're using to optimize our performance and to continuously improve our car. Yeah, the data and the applications that leverage it are really key. And that's a critical success factor for us. >> So let's talk about your data center at the track, if you will, I mean, if I can call it that. Paint a picture for us. >> Sure. What does that look like? >> So we have to send a lot of equipment to the track, at the edge. And even though we have really a great lateral network link back to the factory and there's cloud resources, a lot of the tracks are very old. You don't have hardened infrastructure, you don't have docks that protect cabling, for example, and you can lose connectivity to remote locations. So the applications we need to operate the car and to make really critical decisions, all that needs to be at the edge where the car operates. So historically we had three racks of equipment, legacy infrastructure and it was really hard to manage, to make changes, it was too inflexible. There were multiple panes of glass, and it was too slow. It didn't run our applications quickly. It was also too heavy and took up too much space when you're cramped into a garage with lots of environmental constraints. So we'd introduced hyper-convergence into the factory and seen a lot of great benefits. And when we came time to refresh our infrastructure at the track, we stepped back and said there's a lot smarter way of operating. We can get rid of all this slow and inflexible expensive legacy and introduce hyper-convergence. And we saw really excellent benefits for doing that. We saw a three X speed up for a lot of our applications. So here where we're post-processing data, and we have to make decisions about race strategy, time is of the essence and a three X reduction in processing time really matters. We also were able to go from three racks of equipment down to two racks of equipment and the storage efficiency of the HPE SimpliVity platform with 20 to one ratios allowed us to eliminate a rack. And that actually saved a $100,000 a year in freight costs by shipping less equipment. Things like backup, mistakes happen. Sometimes a user makes a mistake. So for example a race engineer could load the wrong data map into one of our simulations. And we could restore that DDI through SimpliVity backup in 90 seconds. And this makes sure, enables engineers to focus on the car, to make better decisions without having downtime. And we send two IT guys to every race. They're managing 60 users, a really diverse environment, juggling a lot of balls and having a simple management platform like HP SimpliVity gives us, allows them to be very effective and to work quickly. So all of those benefits were a huge step forward relative to the legacy infrastructure that we used to run at the edge. >> Yes, so you had the nice Petri dish in the factory, so it sounds like your goals obviously, number one KPI is speed to help shave seconds off the time, but also cost. >> That's right. Just the simplicity of setting up the infrastructure is key. >> Yeah, that's exactly right. >> It's speed, speed, speed. So we want applications that absolutely fly, you know gets actionable results quicker, get answers from our simulations quicker. The other area that speed's really critical is our applications are also evolving prototypes and we're always, the models are getting bigger, the simulations are getting bigger, and they need more and more resource. And being able to spin up resource and provision things without being a bottleneck is a big challenge. And SimpliVity gives us the means of doing that. >> So did you consider any other options or was it because you had the factory knowledge, HCI was, you know, very clearly the option? What did you look at? >> Yeah, so we have over five years of experience in the factory and we eliminated all of our legacy infrastructure five years ago. And the benefits I've described at the track we saw that in the factory. At the track, we have a three-year operational life cycle for our equipment. 2017 was the last year we had legacy. As we were building for 2018, it was obvious that hyper-converged was the right technology to introduce. And we'd had years of experience in the factory already. And the benefits that we see with hyper-converged actually mattered even more at the edge because our operations are so much more pressurized. Time is even more of the essence. And so speeding everything up at the really pointy end of our business was really critical. It was an obvious choice. >> So why SimpliVity? Why do you choose HPE SimpliVity? >> Yeah, so when we first heard about hyper-converged, way back in the factory. We had a legacy infrastructure, overly complicated, too slow, too inflexible, too expensive. And we stepped back and said there has to be a smarter way of operating. We went out and challenged our technology partners. We learned about hyper-convergence. We didn't know if the hype was real or not. So we underwent some PLCs and benchmarking and the PLCs were really impressive. And all these, you know, speed and agility benefits we saw and HPE for our use cases was the clear winner in the benchmarks. So based on that we made an initial investment in the factory. We moved about 150 VMs and 150 VDIs into it. And then as we've seen all the benefits we've successfully invested, and we now have an estate in the factory of about 800 VMs and about 400 VDIs. So it's been a great platform and it's allowed us to really push boundaries and give the business the service it expects. >> Well that's a fun story. So just coming back to the metrics for a minute. So you're running Monte Carlo simulations in real-time and sort of near real-time. >> Yeah. And so essentially that's, if I understand it, that's what-ifs and it's the probability of the outcome. And then somebody's got to make, >> Exactly. then a human's got to say, okay, do this, right. And so was that, >> Yeah. with the time in which you were able to go from data to insight to recommendation or edict was that compressed? You kind of indicated that, but. >> Yeah, that was accelerated. And so in that use case, what we're trying to do is predict the future and you're saying well, and before any event happens, you're doing what-ifs. Then if it were to happen, what would you probabilistically do? So, you know, so that simulation we've been running for a while but it gets better and better as we get more knowledge. And so that we were able to accelerate that with SimpliVity. But there's other use cases too. So we offload telemetry from the car and we post-process it. And that reprocessing time really is very time consuming. And, you know, we went from nine, eight minutes for some of the simulations down to just two minutes. So we saw big, big reductions in time. And ultimately that meant an engineer could understand what the car was doing in a practice session, recommend a tweak to the configuration or setup of it, and just get more actionable insight quicker. And it ultimately helps get a better car quicker. >> Such a great example. How are you guys feeling about the season, Matt? What's the team's, the sentiment? >> Yeah, I think we're optimistic. We with thinking our simulations that we have a great car. We have a new driver lineup. We have Max Verstappen who carries on with the team and Sergio Perez joins the team. So we're really excited about this year and we want to go and win races. And I think with COVID people are just itching also to get back to a little degree of normality, and, you know, and going racing again, even though there's no fans, it gets us into a degree of normality. >> That's great, Matt, good luck this season and going forward and thanks so much for coming back in theCUBE. Really appreciate it. >> It's my pleasure. Great talking to you again. >> Okay, now we're going to bring back Omar for a quick summary. So keep it right there. (mellow music)

>>from around the globe. It's the Q. With digital coverage >>of exa scale day made possible by Hewlett Packard Enterprise. We're back at the celebration of Exa Scale Day. This is Dave Volant, and I'm pleased to welcome to great guests Brian Dance Berries Here. Here's what The ISS Program Science office at the Johnson Space Center. And Dr Mark Fernandez is back. He's the Americas HPC technology officer at Hewlett Packard Enterprise. Gentlemen, welcome. >>Thank you. Yeah, >>well, thanks for coming on. And, Mark, Good to see you again. And, Brian, I wonder if we could start with you and talk a little bit about your role. A T. I s s program Science office as a scientist. What's happening these days? What are you working on? >>Well, it's been my privilege the last few years to be working in the, uh, research integration area of of the space station office. And that's where we're looking at all of the different sponsors NASA, the other international partners, all the sponsors within NASA, and, uh, prioritizing what research gets to go up to station. What research gets conducted in that regard. And to give you a feel for the magnitude of the task, but we're coming up now on November 2nd for the 20th anniversary of continuous human presence on station. So we've been a space faring society now for coming up on 20 years, and I would like to point out because, you know, as an old guy myself, it impresses me. That's, you know, that's 25% of the US population. Everybody under the age of 20 has never had a moment when they were alive and we didn't have people living and working in space. So Okay, I got off on a tangent there. We'll move on in that 20 years we've done 3000 experiments on station and the station has really made ah, miraculously sort of evolution from, ah, basic platform, what is now really fully functioning national lab up there with, um, commercially run research facilities all the time. I think you can think of it as the world's largest satellite bus. We have, you know, four or five instruments looking down, measuring all kinds of things in the atmosphere during Earth observation data, looking out, doing astrophysics, research, measuring cosmic rays, X ray observatory, all kinds of things, plus inside the station you've got racks and racks of experiments going on typically scores, you know, if not more than 50 experiments going on at any one time. So, you know, the topic of this event is really important. Doesn't NASA, you know, data transmission Up and down, all of the cameras going on on on station the experiments. Um, you know, one of one of those astrophysics observatory's you know, it has collected over 15 billion um uh, impact data of cosmic rays. And so the massive amounts of data that that needs to be collected and transferred for all of these experiments to go on really hits to the core. And I'm glad I'm able toe be here and and speak with you today on this. This topic. >>Well, thank you for that, Bryan. A baby boomer, right? Grew up with the national pride of the moon landing. And of course, we've we've seen we saw the space shuttle. We've seen international collaboration, and it's just always been something, you know, part of our lives. So thank you for the great work that you guys were doing their mark. You and I had a great discussion about exa scale and kind of what it means for society and some of the innovations that we could maybe expect over the coming years. Now I wonder if you could talk about some of the collaboration between what you guys were doing and Brian's team. >>Uh, yeah, so yes, indeed. Thank you for having me early. Appreciate it. That was a great introduction. Brian, Uh, I'm the principal investigator on Space Born computer, too. And as the two implies, where there was one before it. And so we worked with Bryant and his team extensively over the past few years again high performance computing on board the International Space Station. Brian mentioned the thousands of experiments that have been done to date and that there are currently 50 orm or going on at any one time. And those experiments collect data. And up until recently, you've had to transmit that data down to Earth for processing. And that's a significant amount of bandwidth. Yeah, so with baseball and computer to we're inviting hello developers and others to take advantage of that onboard computational capability you mentioned exa scale. We plan to get the extra scale next year. We're currently in the era that's called PETA scale on. We've been in the past scale era since 2000 and seven, so it's taken us a while to make it that next lead. Well, 10 years after Earth had a PETA scale system in 2017 were able to put ah teraflop system on the International space station to prove that we could do a trillion calculations a second in space. That's where the data is originating. That's where it might be best to process it. So we want to be able to take those capabilities with us. And with H. P. E. Acting as a wonderful partner with Brian and NASA and the space station, we think we're able to do that for many of these experiments. >>It's mind boggling you were talking about. I was talking about the moon landing earlier and the limited power of computing power. Now we've got, you know, water, cool supercomputers in space. I'm interested. I'd love to explore this notion of private industry developing space capable computers. I think it's an interesting model where you have computer companies can repurpose technology that they're selling obviously greater scale for space exploration and apply that supercomputing technology instead of having government fund, proprietary purpose built systems that air. Essentially, you use case, if you will. So, Brian, what are the benefits of that model? The perhaps you wouldn't achieve with governments or maybe contractors, you know, kind of building these proprietary systems. >>Well, first of all, you know, any any tool, your using any, any new technology that has, you know, multiple users is going to mature quicker. You're gonna have, you know, greater features, greater capabilities, you know, not even talking about computers. Anything you're doing. So moving from, you know, governor government is a single, um, you know, user to off the shelf type products gives you that opportunity to have things that have been proven, have the technology is fully matured. Now, what had to happen is we had to mature the space station so that we had a platform where we could test these things and make sure they're gonna work in the high radiation environments, you know, And they're gonna be reliable, because first, you've got to make sure that that safety and reliability or taken care of so that that's that's why in the space program you're gonna you're gonna be behind the times in terms of the computing power of the equipment up there because, first of all and foremost, you needed to make sure that it was reliable and say, Now, my undergraduate degree was in aerospace engineering and what we care about is aerospace engineers is how heavy is it, how big and bulky is it because you know it z expensive? You know, every pound I once visited Gulfstream Aerospace, and they would pay their employees $1000 that they could come up with a way saving £1 in building that aircraft. That means you have more capacity for flying. It's on the orders of magnitude. More important to do that when you're taking payloads to space. So you know, particularly with space born computer, the opportunity there to use software and and check the reliability that way, Uh, without having to make the computer, you know, radiation resistance, if you will, with heavy, you know, bulky, um, packaging to protect it from that radiation is a really important thing, and it's gonna be a huge advantage moving forward as we go to the moon and on to Mars. >>Yeah, that's interesting. I mean, your point about cots commercial off the shelf technology. I mean, that's something that obviously governments have wanted to leverage for a long, long time for many, many decades. But but But Mark the issue was always the is. Brian was just saying the very stringent and difficult requirements of space. Well, you're obviously with space Born one. You got to the point where you had visibility of the economics made sense. It made commercial sense for companies like Hewlett Packard Enterprise. And now we've sort of closed that gap to the point where you're sort of now on that innovation curve. What if you could talk about that a little bit? >>Yeah, absolutely. Brian has some excellent points, you know, he said, anything we do today and requires computers, and that's absolutely correct. So I tell people that when you go to the moon and when you go to the Mars, you probably want to go with the iPhone 10 or 11 and not a flip phone. So before space born was sent up, you went with 2000 early two thousands computing technology there which, like you said many of the people born today weren't even around when the space station began and has been occupied so they don't even know how to program or use that type of computing. Power was based on one. We sent the exact same products that we were shipping to customers today, so they are current state of the art, and we had a mandate. Don't touch the hardware, have all the protection that you can via software. So that's what we've done. We've got several philosophical ways to do that. We've implemented those in software. They've been successful improving in the space for one, and now it's space born to. We're going to begin the experiments so that the rest of the community so that the rest of the community can figure out that it is economically viable, and it will accelerate their research and progress in space. I'm most excited about that. Every venture into space as Brian mentioned will require some computational capability, and HP has figured out that the economics air there we need to bring the customers through space ball into in order for them to learn that we are reliable but current state of the art, and that we could benefit them and all of humanity. >>Guys, I wanna ask you kind of a two part question. And, Brian, I'll start with you and it z somewhat philosophical. Uh, I mean, my understanding was and I want to say this was probably around the time of the Bush administration w two on and maybe certainly before that, but as technology progress, there was a debate about all right, Should we put our resource is on moon because of the proximity to Earth? Or should we, you know, go where no man has gone before and or woman and get to Mars? Where What's the thinking today, Brian? On that? That balance between Moon and Mars? >>Well, you know, our plans today are are to get back to the moon by 2024. That's the Artemus program. Uh, it's exciting. It makes sense from, you know, an engineering standpoint. You take, you know, you take baby steps as you continue to move forward. And so you have that opportunity, um, to to learn while you're still, you know, relatively close to home. You can get there in days, not months. If you're going to Mars, for example, toe have everything line up properly. You're looking at a multi year mission you know, it may take you nine months to get there. Then you have to wait for the Earth and Mars to get back in the right position to come back on that same kind of trajectory. So you have toe be there for more than a year before you can turn around and come back. So, you know, he was talking about the computing power. You know, right now that the beautiful thing about the space station is, it's right there. It's it's orbiting above us. It's only 250 miles away. Uh, so you can test out all of these technologies. You can rely on the ground to keep track of systems. There's not that much of a delay in terms of telemetry coming back. But as you get to the moon and then definitely is, you get get out to Mars. You know, there are enough minutes delay out there that you've got to take the computing power with you. You've got to take everything you need to be able to make those decisions you need to make because there's not time to, um, you know, get that information back on the ground, get back get it back to Earth, have people analyze the situation and then tell you what the next step is to do. That may be too late. So you've got to think the computing power with you. >>So extra scale bring some new possibilities. Both both for, you know, the moon and Mars. I know Space Born one did some simulations relative. Tomorrow we'll talk about that. But But, Brian, what are the things that you hope to get out of excess scale computing that maybe you couldn't do with previous generations? >>Well, you know, you know, market on a key point. You know, bandwidth up and down is, of course, always a limitation. In the more computing data analysis you can do on site, the more efficient you could be with parsing out that that bandwidth and to give you ah, feel for just that kind of think about those those observatory's earth observing and an astronomical I was talking about collecting data. Think about the hours of video that are being recorded daily as the astronauts work on various things to document what they're doing. They many of the biological experiments, one of the key key pieces of data that's coming back. Is that video of the the microbes growing or the plants growing or whatever fluid physics experiments going on? We do a lot of colloids research, which is suspended particles inside ah liquid. And that, of course, high speed video. Is he Thio doing that kind of research? Right now? We've got something called the I s s experience going on in there, which is basically recording and will eventually put out a syriza of basically a movie on virtual reality recording. That kind of data is so huge when you have a 360 degree camera up there recording all of that data, great virtual reality, they There's still a lot of times bringing that back on higher hard drives when the space six vehicles come back to the Earth. That's a lot of data going on. We recorded videos all the time, tremendous amount of bandwidth going on. And as you get to the moon and as you get further out, you can a man imagine how much more limiting that bandwidth it. >>Yeah, We used to joke in the old mainframe days that the fastest way to get data from point a to Point B was called C Tam, the Chevy truck access method. Just load >>up a >>truck, whatever it was, tapes or hard drive. So eso and mark, of course space born to was coming on. Spaceport one really was a pilot, but it proved that the commercial computers could actually work for long durations in space, and the economics were feasible. Thinking about, you know, future missions and space born to What are you hoping to accomplish? >>I'm hoping to bring. I'm hoping to bring that success from space born one to the rest of the community with space born to so that they can realize they can do. They're processing at the edge. The purpose of exploration is insight, not data collection. So all of these experiments begin with data collection. Whether that's videos or samples are mold growing, etcetera, collecting that data, we must process it to turn it into information and insight. And the faster we can do that, the faster we get. Our results and the better things are. I often talk Thio College in high school and sometimes grammar school students about this need to process at the edge and how the communication issues can prevent you from doing that. For example, many of us remember the communications with the moon. The moon is about 250,000 miles away, if I remember correctly, and the speed of light is 186,000 miles a second. So even if the speed of light it takes more than a second for the communications to get to the moon and back. So I can remember being stressed out when Houston will to make a statement. And we were wondering if the astronauts could answer Well, they answered as soon as possible. But that 1 to 2 second delay that was natural was what drove us crazy, which made us nervous. We were worried about them in the success of the mission. So Mars is millions of miles away. So flip it around. If you're a Mars explorer and you look out the window and there's a big red cloud coming at you that looks like a tornado and you might want to do some Mars dust storm modeling right then and there to figure out what's the safest thing to do. You don't have the time literally get that back to earth have been processing and get you the answer back. You've got to take those computational capabilities with you. And we're hoping that of these 52 thousands of experiments that are on board, the SS can show that in order to better accomplish their missions on the moon. And Omar, >>I'm so glad you brought that up because I was gonna ask you guys in the commercial world everybody talks about real time. Of course, we talk about the real time edge and AI influencing and and the time value of data I was gonna ask, you know, the real time, Nous, How do you handle that? I think Mark, you just answered that. But at the same time, people will say, you know, the commercial would like, for instance, in advertising. You know, the joke the best. It's not kind of a joke, but the best minds of our generation tryingto get people to click on ads. And it's somewhat true, unfortunately, but at any rate, the value of data diminishes over time. I would imagine in space exploration where where you're dealing and things like light years, that actually there's quite a bit of value in the historical data. But, Mark, you just You just gave a great example of where you need real time, compute capabilities on the ground. But but But, Brian, I wonder if I could ask you the value of this historic historical data, as you just described collecting so much data. Are you? Do you see that the value of that data actually persists over time, you could go back with better modeling and better a i and computing and actually learn from all that data. What are your thoughts on that, Brian? >>Definitely. I think the answer is yes to that. And, you know, as part of the evolution from from basically a platform to a station, we're also learning to make use of the experiments in the data that we have there. NASA has set up. Um, you know, unopened data access sites for some of our physical science experiments that taking place there and and gene lab for looking at some of the biological genomic experiments that have gone on. And I've seen papers already beginning to be generated not from the original experimenters and principal investigators, but from that data set that has been collected. And, you know, when you're sending something up to space and it to the space station and volume for cargo is so limited, you want to get the most you can out of that. So you you want to be is efficient as possible. And one of the ways you do that is you collect. You take these earth observing, uh, instruments. Then you take that data. And, sure, the principal investigators air using it for the key thing that they designed it for. But if that data is available, others will come along and make use of it in different ways. >>Yeah, So I wanna remind the audience and these these these air supercomputers, the space born computers, they're they're solar powered, obviously, and and they're mounted overhead, right? Is that is that correct? >>Yeah. Yes. Space borne computer was mounted in the overhead. I jokingly say that as soon as someone could figure out how to get a data center in orbit, they will have a 50 per cent denser data station that we could have down here instead of two robes side by side. You can also have one overhead on. The power is free. If you can drive it off a solar, and the cooling is free because it's pretty cold out there in space, so it's gonna be very efficient. Uh, space borne computer is the most energy efficient computer in existence. Uh, free electricity and free cooling. And now we're offering free cycles through all the experimenters on goal >>Eso Space born one exceeded its mission timeframe. You were able to run as it was mentioned before some simulations for future Mars missions. And, um and you talked a little bit about what you want to get out of, uh, space born to. I mean, are there other, like, wish list items, bucket bucket list items that people are talking about? >>Yeah, two of them. And these air kind of hypothetical. And Brian kind of alluded to them. Uh, one is having the data on board. So an example that halo developers talk to us about is Hey, I'm on Mars and I see this mold growing on my potatoes. That's not good. So let me let me sample that mold, do a gene sequencing, and then I've got stored all the historical data on space borne computer of all the bad molds out there and let me do a comparison right then and there before I have dinner with my fried potato. So that's that's one. That's very interesting. A second one closely related to it is we have offered up the storage on space borne computer to for all of your raw data that we process. So, Mr Scientist, if if you need the raw data and you need it now, of course, you can have it sent down. But if you don't let us just hold it there as long as they have space. And when we returned to Earth like you mentioned, Patrick will ship that solid state disk back to them so they could have a new person, but again, reserving that network bandwidth, uh, keeping all that raw data available for the entire duration of the mission so that it may have value later on. >>Great. Thank you for that. I want to end on just sort of talking about come back to the collaboration between I S s National Labs and Hewlett Packard Enterprise, and you've got your inviting project ideas using space Bourne to during the upcoming mission. Maybe you could talk about what that's about, and we have A We have a graphic we're gonna put up on DSM information that you can you can access. But please, mark share with us what you're planning there. >>So again, the collaboration has been outstanding. There. There's been a mention off How much savings is, uh, if you can reduce the weight by a pound. Well, our partners ice s national lab and NASA have taken on that cost of delivering baseball in computer to the international space station as part of their collaboration and powering and cooling us and giving us the technical support in return on our side, we're offering up space borne computer to for all the onboard experiments and all those that think they might be wanting doing experiments on space born on the S s in the future to take advantage of that. So we're very, very excited about that. >>Yeah, and you could go toe just email space born at hp dot com on just float some ideas. I'm sure at some point there'll be a website so you can email them or you can email me david dot volonte at at silicon angle dot com and I'll shoot you that that email one or that website once we get it. But, Brian, I wanna end with you. You've been so gracious with your time. Uh, yeah. Give us your final thoughts on on exa scale. Maybe how you're celebrating exa scale day? I was joking with Mark. Maybe we got a special exa scale drink for 10. 18 but, uh, what's your final thoughts, Brian? >>Uh, I'm going to digress just a little bit. I think I think I have a unique perspective to celebrate eggs a scale day because as an undergraduate student, I was interning at Langley Research Center in the wind tunnels and the wind tunnel. I was then, um, they they were very excited that they had a new state of the art giant room size computer to take that data we way worked on unsteady, um, aerodynamic forces. So you need a lot of computation, and you need to be ableto take data at a high bandwidth. To be able to do that, they'd always, you know, run their their wind tunnel for four or five hours. Almost the whole shift. Like that data and maybe a week later, been ableto look at the data to decide if they got what they were looking for? Well, at the time in the in the early eighties, this is definitely the before times that I got there. They had they had that computer in place. Yes, it was a punchcard computer. It was the one time in my life I got to put my hands on the punch cards and was told not to drop them there. Any trouble if I did that. But I was able thio immediately after, uh, actually, during their run, take that data, reduce it down, grabbed my colored pencils and graph paper and graph out coefficient lift coefficient of drag. Other things that they were measuring. Take it back to them. And they were so excited to have data two hours after they had taken it analyzed and looked at it just pickled them. Think that they could make decisions now on what they wanted to do for their next run. Well, we've come a long way since then. You know, extra scale day really, really emphasizes that point, you know? So it really brings it home to me. Yeah. >>Please, no, please carry on. >>Well, I was just gonna say, you know, you talked about the opportunities that that space borne computer provides and and Mark mentioned our colleagues at the I S s national lab. You know, um, the space station has been declared a national laboratory, and so about half of the, uh, capabilities we have for doing research is a portion to the national lab so that commercial entities so that HP can can do these sorts of projects and universities can access station and and other government agencies. And then NASA can focus in on those things we want to do purely to push our exploration programs. So the opportunities to take advantage of that are there marks opening up the door for a lot of opportunities. But others can just Google S s national laboratory and find some information on how to get in the way. Mark did originally using s national lab to maybe get a good experiment up there. >>Well, it's just astounding to see the progress that this industry is made when you go back and look, you know, the early days of supercomputing to imagine that they actually can be space born is just tremendous. Not only the impacts that it can have on Space six exploration, but also society in general. Mark Wayne talked about that. Guys, thanks so much for coming on the Cube and celebrating Exa scale day and helping expand the community. Great work. And, uh, thank you very much for all that you guys dio >>Thank you very much for having me on and everybody out there. Let's get the XO scale as quick as we can. Appreciate everything you all are >>doing. Let's do it. >>I've got a I've got a similar story. Humanity saw the first trillion calculations per second. Like I said in 1997. And it was over 100 racks of computer equipment. Well, space borne one is less than fourth of Iraq in only 20 years. So I'm gonna be celebrating exa scale day in anticipation off exa scale computers on earth and soon following within the national lab that exists in 20 plus years And being on Mars. >>That's awesome. That mark. Thank you for that. And and thank you for watching everybody. We're celebrating Exa scale day with the community. The supercomputing community on the Cube Right back