(upbeat music) >> TheCUBE presents UiPath Forward 5. Brought to you by UiPath. >> Hello and welcome back to TheCUBE's coverage of UiPath Forward 5. We're here in Las Vegas at the Venetian Convention Center. This is day two. We're wrapping up Dave Nicholson and Dave Vellante. This is the fourth time theCUBE has been at UiPath Forward. And we've seen the transformation of the company from, essentially, what was a really interesting and easy to adopt point product to now one through acquisitions, IPO, has made a number of enhancements to its platform. David Cardenas is here. Deputy Director of Operations for County of Los Angeles, the Department of Public Health. David, good to see you. Thanks for coming on theCUBE. >> Thanks for having me on guys. Appreciate it. >> So what is your role? What does it have to do with automation? >> So I had been, actually started off in the IT space within the public health. Had served as a CIO previously, but now been moving into broader operations. And I basically manage all of the back office operations for the department, HR, IT, finance, all that. >> So you've had a wild ride in the last couple of years. >> Yeah, I think, like I've been talking earlier, it's just been, the last two years have just been horrendous. It's been a really difficult experience for us. >> Yeah, and I mean, the scars are there, and maybe permanently. But it also had major effects on organizations, on operations that, again, seem to be permanent. How would you describe the situation in your organization? >> So I think it, the urgency that came along with the pandemic response, kind of required us to look at things, you know, differently. We had to be, realize we had to be a lot more nimble than when we were and try to figure out how to enhance our operations. But really look at the core of what we're doing and figure out how it is to be more efficient. So I think we've kind of seen it as an opportunity to really examine ourselves a little bit more deeply and see what things we need to do to kind of, to fix our operations and get things on a better path. >> You know, I think a lot of organizations we talked to say that. But I want to understand how you handle this is, you didn't have time to sit back in the middle of the pandemic. >> Yeah. >> And then as you exit, what I call the isolation economy, people are so burned out, you know? So how do you deal with that organizational trauma? Say, okay now, let's sit back and think about this. Do people, are they eager to do so? Do they have the appetite for it? What's that dynamic like? >> So I think certainly there's a level of exhaustion inside the organization. I can't say that there isn't because it's just been, you know, two years of 24/7/365 kind of work. And that's tough on any organization. But I think what we realize is that there's, you know, we need to move into action quickly 'cause we don't know what's going to come next, right? And we're expecting that this is just a sign of what's to come and that we're just at the start of that stage of, we're just going to see a lot more outbreaks, we're going to see a lot more conditions kind of hitting us. And if we're not prepared for that, we're not going to be able to respond for the, and preserve the health and safety of our citizens, right? So I think we're taking a very active, like, look at these opportunities and see what we've done and say how do we now make the changes that we made in response to the pandemic permanent so that the next time this comes at us, we won't have to be struggling the way that we were to try to figure things out because we'll have such a better foundation in place to be able to move things forward. >> I mean, I've never served in the military, but I imagine that when you're in the military, you're always prepared for some kind of, you know, in your world, code red, right? >> Yeah. >> So it's like this code red culture. And that seems to have carried through, right? People are, you know, constantly aware that, wow. We got caught off guard and we don't want that to happen again. Because that was a big part of the trauma was just the unknown- >> Right. >> and the lack of preparedness. So thinking about technology and its role in helping you to prepare for that type of uncertainty. Can you describe how you're applying technology to prepare for the next unknown? >> So I think, so that first part of what you said, I think the difficulty we've always had in the public health side is that there's the, generally the approach to healthcare is very reactionary, right? Your first interface with the healthcare system is, "I'm going to go see my doctor; I'm going to go to the hospital." The work that we do in public health is to try to do everything we can to keep you out of that, right? So it's broad-based messaging, social media now is going to put us out there. But also, to be able to surveil disease in a different way. And so the holy grail for us in healthcare has always been, at least on the public health side, has been to try to see how can we tap in more actively that when you go see the doctor or when you go to the hospital, how can I get access to that information very, very quickly so that I know, and can see, and surveil my entire county in my jurisdiction and know, oh, there's an outbreak of disease happening in this section of the county. We're 10 million people with, you know, hundreds of square miles inside of LA. There are places where we can see very, you know, specific targets that we know we have to hit. But the data's a little stale and we find out several months after. We need to figure out a way to do that more actively. Technology's going to be our path to be able to capture that information more actively and come up on something a little bit, so we can track things faster and be able to respond more quickly. So that's our focus for all our technology implementations, automation like UiPath has offered us and other things, is around how to gather that information more quickly and put that into action so we can do quick interventions. >> People have notoriously short memories. Please tell me (chuckles) any of the friction that you may have experienced in years past before the pandemic. That those friction points where people are thinking, "Eh, what are the odds?" >> Yeah. "Eh, I've got finite budget, I think I'm going to spend it on this thing over here." Do you, are you able to still ride sort of the wave of mind share at this point when putting programs together for the future? >> So whatever friction was there during the pandemic wiped away. I mean, we had amazing collaboration with the medical provider community, our hospital partners. The healthcare system in LA was working very closely with us to make sure that we were responding. And there is that wave that we are trying to make sure that we use this as an opportunity to kind of ride it so that we can implement all the things that we want. 'Cause we don't know how long that's going to last us. The last time that I saw anything this large was after the anthrax attacks and the bioterrorism attacks that we had after 9/11. >> How interesting. >> Public health was really in lens at that point. And we had a huge infusion of funding, a lot of support from stakeholders, both politically and within the healthcare system. And we were able to make some large steps in movement at that point. This feels the same but in a larger scale because now it touched every part of the infrastructure. And we saw how society really had to react to what was going on in a different way than anyone has ever prepared for. And so now is we think is a time where we know that people are making more investments. And our success is going to be their success in the longterm. >> And you have to know that expectations are now set- >> Extremely high. >> at a completely different level, right? >> Yes, absolutely. >> There is no, "Oh, we don't have enough PPE." >> Correct. >> Right? >> David: Correct. >> The the expectation level is, hey, you should have learned from all of- >> We should have it; we can deliver it, We'll have it at the ready when we need to provide it. Yes, absolutely. >> Okay, so I sort of mentioned, we're, David cubed on theCUBE (all laughing). So three Daves. You spoke today at the conference? >> Actually I'm speaking later actually in the session in an hour or so. >> Oh Okay. My understanding is that you've got this concept of putting humans at the center of the automation. What does that mean? Why is that important? Help us understand that. >> So I think what we found in the crisis is that the high demand for information was something we hadn't seen before, right? We're one of the largest media markets in the United States. And what we really had trouble with is trying to figure out how to serve the residents, to provide them the information that we needed to provide to them. And so what we had traditionally done is press releases, you know, just general marketing campaigns, billboards, trying to send our message out. And when you're talking about a pandemic where on a daily basis, hour-by-hour people wanted to know what was going on in their local communities. Like, we had to change the way that we focused on. So we started thinking about, what is the information that the residents of our county need? And how can we set up an infrastructure to sustain the feeding of that? Because if we can provide more information, people will make their own personal decisions around their personal risk, their personal safety measures they need to take, and do so more actively. More so than, you know, one of us going on camera to say, "This is what you should do." They can look for themselves and look at the data that's in front of them and be able to make those choices for themselves, right? And so we needed to make sure that everything that we were doing wasn't built around feeding it to our political stakeholders, which are important stakeholders. We needed to make sure that they're aware and are messaging out, and our leadership are aware. But it's what could we give the public to be able to make them have access to information that we were collecting on an every single day basis to be able to make the decisions for their lives. And so the automation was key to that. We were at the beginning of the pandemic just had tons and tons of resources that we were throwing at the problem that was, our systems were slow, we didn't have good ability to move data back and forth between our systems, and we needed a stop-gap solution to really fill that need and be able to make the data cycles to meet the data cycles. We had basically every day had to deliver reports and analytics and dashboards by like 10 o'clock in the morning because we knew that the 12 an hour and the five-hour news cycles were going to hit and the press were going to then take those and message out. And the public started to kind of come in at that same time and look at 10 and 11 o'clock and 12 o'clock. >> Yeah. >> We could see it from how many hits were hitting our website, looking for that information. So when we failed and had a cycle where that data cycle didn't work and we couldn't deliver, the public would let us know, the press would let us know, the stakeholders would let us know. We had never experienced anything like that before, right. Where people had like this voracious appetite for the information. So we needed to have a very bulletproof process to make sure that every single 24 hours we were delivering that data, making it available at the ready. >> Software robots enabled that. >> Exactly. >> Okay. And so how were you able to implement that so quickly within such a traumatic environment? >> So I think, I guess necessity is always the mother of invention. It kind of drove us to go real quickly to look at what we had. We had data entry operations set up where we had dozens and dozens of people whose sole job in life on a 24-hour cycle was to receive medical reports that we we're getting, interview data that's coming from our case interviews, hospitalization data that was coming in through all these different channels. And it was all coming in in various forms. And they were entering that into our systems of record. And that's what we were using, extracts from that system of record, what was using to generate the data analyses in our systems and our dashboards. And so we couldn't rely on those after a while because the data was coming in at such high volume. There wasn't enough data entry staff to be able to fit the need, right? And so we needed to replace those humans and take them out of that data entry cycle, pop in the bots. And so what we started to look at is, let's pick off the, where it is that that data entry cycle starts and see what we could do to kind of replace that cycle. And we started off with a very discreet workload that was focused on some of our case interview data that was being turned into PDFs that somebody was using to enter into our systems. And we said, "Well before you do that," since we can't import into the systems 'cause it wasn't working, the import utilities weren't working. We got 'em into simple Excel spreadsheets, mapped those to the fields in our systems and let the bots do that over and over again. And we just started off with that one-use case and just tuned it and went cycle after cycle. The bots just got better and better to the point where we had almost like 95% success rates on each submission of data transactions that we did every day. >> Okay, and you applied that automation, I don't know, how many bots was it roughly? >> We're now at like 30; we started with about five. >> Okay, oh, interesting. So you started with five and you applied 'em to this specific use case to handle the velocity and volume of data- >> Correct. >> that was coming in. But that's obviously dynamic and it's changed. >> Absolutely. >> I presume it's shifted to other areas now. So how did you take what you learned there and then apply it to other use cases in other parts of the organization? >> So, fortunately for us, the process that was being used to capture the information to generate the dashboards and the analyses for the case interview data, which is what we started with- >> Yeah. >> Was essentially being used the same for the hospitalization data that we were getting and for tracking deaths as they were coming in as well. And so the bots essentially were just, we just took one process, take the same bots, copy them over essentially, and had them follow the very same process. We didn't try to introduce any different workflow than what was being done for the first one so we could replicate quickly. So I think it was lucky for us a lot- >> Dave V.: I was going to say, was that luck or by design? >> It was the same people doing the same analyses, right? So in the end they were thinking about how to be efficient themselves. So they kind of had coalesced around a similar process. And so it was kind of like fortunate, but it was by design in terms of how they- >> Dave V.: It was logical to them. >> Logical to them to make it. >> Interesting. >> So for us to be able to insert the bots became pretty easy on the front end. It's just now as we're trying to now expand to other areas that were now encountering like unique processes that we just can't replicate that quickly. We're having to like now dig into. >> So how are you handling that? First of all, how are you determining which processes? Is it sort of process driven? Is it data driven? How do you determine that? >> So obviously right now the focus still is COVID. So the the priorities scale that we've set internally for analyzing those opportunities really is centered around, you know, which things are really going to help our pandemic response, right? We're expecting another surge that's going to happen probably in the next couple of weeks. That'll probably take us through December. Hopefully, at that point, things start to calm down. But that means high-data volume again; these same process. So we're looking at optimizing the processes that we have, what can we do to make those cycles better, faster, you know, what else can we add? The data teams haven't stopped to try to figure out how else can they turn out new data reports, new data analysis, to give us a different perspective on the new variants and the new different outbreaks and hotspots that are popping up. And so we also have to kind of keep up with where they're going on these data dashboards. So they're adding more data into these reports so we know we have to optimize that. And then there's these kind of tangential work. So for example, COVID brought about, unfortunately, a lot of domestic violence reports. And so we have a lot of domestic violence agencies that we work with and that we have interactions with and to monitor their work, we have certain processes. So that's kind of like COVID-adjacent. But it's because it's such a very critical task, we're looking at how we can kind of help in those processes and areas. Same thing in like in our substance abuse area. We have substance use disorder treatment services that we provide. And we're delivering those at a higher rate because COVID kind of created more of a crisis than we would've liked. And so that's how we're prioritizing. It's really about what is the social need, what does the community need, and how can we put the technology work in those areas? >> So how do you envision the future of automation in your organization and the future of your organization? What does that look like? Paint a picture for us. >> So I'm hoping that it really does, you know, so we're going to take everything that's COVID related in the disease control areas, both in terms of our laboratory operations, in terms of our clinic operations, the way we respond, vaccination campaigns, things of that nature. And we're going to look at it to see what can efficiencies can we do there because it's a natural outgrowth of everything we've done on COVID up to this point. So, you know, it's almost like it's as simple as you're just replicating it with another disease. The disease might have different characteristics, but the work process that we follow is very similar. It's not like we're going to change everything and do something completely different for a respiratory condition as we would for some other type of foodborne condition or something else that might happen. So we certainly see very easy opportunities to just to grow out what we've already done in terms of the processes is to do that. So that's wave one, is really focus on that grow out. The second piece I think is to look at these kind of other general kind of community-based type of operations and see what operations we can do there to kind of implement some improvements there. And then I'm certainly in my new role of, in Deputy Director of Operation, I'm a CIO before. Now that I'm in this operations role, I have access to the full administrative apparatus for the department. And believe me, there's enough to keep me busy there. (Dave V. Laughing) And so that's going to be kind of my third prong is to kind of look at the implement there. >> Awesome. Go ahead, Dave. >> Yeah, so, this is going to be taking a step back, kind of a higher level view. If we could direct the same level of rigor and attention towards some other thing that we've directed towards COVID, if you could snap your fingers and make that happen, what would that thing be in the arena of public health in LA County in particular, or if you want California, United States. What is something that you feel maybe needs more attention that it's getting right now? >> So I think I touched on it a little bit earlier, but I think it's the thing we've been always been trying to get to is how to really become just very intentional about how we share data more actively, right? I don't have to know everything about you, but there are certain things I care about when you go to the doctor for that doctor and that physician to tell me. Our physicians, our healthcare system as you know, is always under a lot of pressure. Doctors don't have the time to sit down and write a form out for me and tell me everything that's going on. During COVID they did because they were, they cared about their patients so much and knew, I need to know what's going on at every single moment. And if I don't tell you what's going on in my office, you'll never know and can't tell us what's going on in the community. So they had a vested interest in telling us. But on a normal day-to-day, they don't have the time for that. I got to replace that. We got to make sure that when we get to, not me only, but everyone in this public health community has to be focused and working with our healthcare partners to automate the dissemination and the distribution of information so that I have the information at my fingers, that I can then tell you, "Here's what's going on in your local community," down to your neighborhood, down to your zip code, your census tracked, down to your neighbors' homes. We'll be able to tell you, "This is your risk. Here are the things that are going on. This is what you have to watch out for." And the more that we can be more that focused and laser-focused on meeting that goal, we will be able to do our job more effectively. >> And you can do that while preserving people's privacy. >> Privacy, absolutely. >> Yeah, absolutely. But if people are informed then they can make their own decisions. >> Correct. >> And they're not frustrated at the systems. David, we got to wrap. >> Sure. >> But maybe you can help us. What's your impression of the, first of all, is this your first Forward? You've been to others? >> This is my first time. >> Okay. >> My first time. >> What's your sort of takeaway when you go back to the office or home and people say, "Hey, how was the show? What, what'd you learn?" What are you going to say? >> Well, from just seeing all the partners here and kind of seeing all the different events I've been able to go to and the sessions there's, you don't know many times I've gone to and say, "We've got to be doing that." And so there's certainly these opportunities for, you know, more AI, more automation opportunities that we have not, we just haven't even touched on really. I think that we really need to do that. I have to be able to, as a public institution at some point our budgets get capped. We only have so much that we're going to receive. Even riding this wave, there's only so much we're going to be able to get. So we have to be very efficient and use our resources more. There's a lot more that we can do with AI, a lot more with the tools that we saw, some of the work product that are coming out at this conference that we think we can directly apply to kind of take the humans out of that, their traditional roles, get them doing higher level work so I can get the most out of them and have this other more mundane type of work, just have the systems just do it. I don't need anybody doing that necessarily, that work. I need to be able to leverage them for other higher level capabilities. >> Well thank you for that. Thanks for coming on theCUBE and really appreciate. Dave- >> It's been great talking to you guys, thank you. >> Dave, you know, I love software shows because the business impact is so enormous and I especially love cool software shows. You know, this first of all, the venue. 3,500 people here. Very cool venue. I like the fact that it's not like booth in your face, booth competition. I mean I love VMware, VMworld, VMware Explore. But it's like, "My booth is bigger than your booth." This is really nice and clean, and it's all about the experience. >> A lot of steak, not as much sizzle. >> Yeah, definitely. >> A lot of steak. >> And the customer content at the UiPath events is always outstanding. But we are entering a new era for UiPath, and we're talking. We heard a lot about the Enterprise platform. You know, the big thing is this company's been in this quarterly shock-lock since last April when it went public. And it hasn't all been pretty. And so new co-CEO comes in, they've got, you know, resetting priorities around financials, go to market, they've got to have profitable growth. So watching that that closely. But also product innovation so the co-CEOs will be able to split that up, split their duties up. Daniel Dines the product visionary, product guru. Rob Enslin, you know- making the operations work. >> Operations execution business, yeah. >> We heard that Carl Eschenbach did the introduction. Carl's a major operator, wanted that DNA into the company. 'Cause they got to keep product innovation. And I want to, I want to see R&D spending, stay relatively high. >> Product innovation, but under the heading of platform. And that's the key thing is just not being that tool set. The positioning has been, I think, accurate that, you know, over history, we started with these RPA tools and now we've moved into business process automation and now we're moving into new frontiers where, where truly, AI and ML are being leveraged. I love the re-infer story about going in and using natural national (chuckles) national, natural language processing. I can't even say it, to go through messaging. That's sort of a next-level of intelligence to be able to automate things that couldn't be automated before. So that whole platform story is key. And they seem to have made a pretty good case for their journey into platform as far as I'm concerned. >> Well, yeah, to me again. So it's always about the customers, want to come to an event like this, you listen to what they say in the keynotes and then you listen to what the customers say. And there's a very strong alignment in the UiPath community between, you know, the marketing and the actual implementation. You know, marketing's always going to be ahead. But, we saw this a couple of years ago with platform. And now we're seeing it, you know, throughout the customer base, 10,000+ customers. I think this company could have, you know, easily double, tripled, maybe even 10x that. All right, we got to wrap. Dave Nicholson, thank you. Two weeks in a row. Good job. And let's see. Check out siliconangle.com for all the news. Check out thecube.net; wikibon.com has the research. We'll be on the road as usual. theCUBE, you can follow us. UiPath Forward 5, Dave Vellante for Dave Nicholson. We're out and we'll see you next time. Thanks for watching. (gentle music)

(upbeat music) >> theCUBE presents UiPath FORWARD5 brought to you by UiPath. >> Welcome back to Las Vegas, everybody you're watching theCUBE's coverage of UiPath FORWARD5. We're here at the Venetian Convention Center Dave Vellante with Dave Nicholson this morning. Dave, we heard these boomers, these thunder boomers. We thought it was the sound system. (Dave laughing) >> Thought it was something fake. >> But it was actually some crazy weather out here in Vegas. It's rare to see that kind of nuttiness out here. John Morrison is the director of Product and Technology at T-Mobile and Naga Chakravarthy is the Chief Digital Officer at iOpex. Guys, welcome. >> Thanks for having us. >> Next, so John, (commentator booming) so okay, we're serving automation. I don't know if you guys can hear that S0 let's just give him a second here. >> (Commentator) Three different tracks >> I think it's pretty loud. Probably coming through. Usually we don't get that. >> It's live. >> But, it is live. So John, we, we've interviewed a lot of customers that have automation in their title. Your title's, Director of product and technology. Obviously you're here 'cause you have an affinity to automation. But talk about your role and how automation fits into it. >> Sure. Well, I'm the director of product and technology and I oversee what we call the communication, collaboration and productivity applications and services for T-Mobile. Reason I'm here is we took over the automation program and automation is falling within to our productivity portfolio. So I'm here to learn about, from these experts and all these leaders within the UiPath and from our vendors as well. >> Okay. Now tell us about iOpex. So kind of an interesting name. Where'd that come from? I think cloud. When I think opex, but, get rid of my cap. Where's the name come from and what do you guys do? >> Actually we thought hard about what to name about 13 years back. You know, I think all of us, the whole team comes from a service background and then I think we believe that you need to have people and as a lot of operational activities were increasing, you know the dependency on people was also increasing. And we thought that there has to be an angle for us to be very unique in the market. So we thought, you know, I would say iOpex is currently at 3.0 and if you look at what 1.0 was, it's all about driving innovation in operation excellence, right? And the medium was technology. And today, if you ask me from operation excellence that is the base, we are actually looking at how do you drive innovation in operating experiences. That's where automation and all these things becomes very native to us. >> So the market just went right, right to you guys you were ahead of the game. And then, wow, now, >> I have to brag that we fortunately named it Opex, which can be interchangeably used for operation excellence or operating experience. >> Got it. >> So, so John, where did, where did it start? What was the catalyst for your automation journey? How did, was it the, was it the, the merger? Take us through that. >> Sure. So I look at our automation journey, like a crawl, walk, run journey for sure. It started with the partnership of UiPath and iOpex. We had an innovation lab. They came, they set up a proof of concept. Proof of concept was successful. I was then asked to build out an automation program for the T-mobile enterprise. Not having any experience within automation as we had discussed before usually you have automation within the title. We leaned heavily on our partners iOpex being main critical partner in that evolution. And so iOpex came in and helped us build that center of excellence and really helped us put that support team together so that we could be successful as we moved forward. Now, when we had both of those in place, we were able to go to the businesses and find opportunities and showcase what automation was all about. The problem is we were so green is that, you know, we'd go and we'd look at an opportunity, but that opportunity we'd deliver and then our pipeline would be empty and we'd have to go look for other opportunities. So we really had to present and get that executive sponsorship of automation for the enterprise. And I'm going to do a few shoutouts here. Giao Duong, John Lowe and our CIO Brian King, were critical in giving us what we needed to be successful. They gave us the expertise, the funds to do what we needed to, to build out this program. We utilized iOpex, UiPath to really get that expertise in place. And today, our pipeline, we have about 300,000 manual hours of labor savings that we'll deploy by the end of the year. That's a huge success. And that's where we're at right now. The run part of it is going to be, I'll wait. >> Wait. No, it's okay. So you went, you went from hunting to fishing in a barrel? >> Absolutely. Absolutely. So the, our next is focused on citizen development, building out that citizen development program, where we will be partnering with UiPath and iOpex to get that in place. And once we have that in place I feel like we're going to be ready to run and we'll see that program just kick off. But like I said before, 300,000 hours of savings in the first year of that program. That's incredible. And we're a large company and we'll, I mean we're just starting so it's going to be fun. >> So many questions. So Naga, is the COE where people typically start or is it sometimes a grassroot effort and then the COE comes later? How do you typically recommend approaching it? >> I think the fact that we started very small there was a clear mandate that we have to take a very strategic approach while we are solving a tactical problem to show that automation is the future and you need to solve using automation, right? And we not only looked at it just from a task automation standpoint, we were starting to look at it from a process, entire end to end process automation. And when we started looking at it, though we were tactically automating it, COE naturally fell in place. So, which means you need to evangelize this across multiple departments. So when you have to have, when you have to have evangelize across multiple departments, what is very important is you need to have the pod leaders identified let's say if you have to go to different departments it is somebody from John's team who's very capable of navigating through different departments' problem statements and how when you, when you navigate it you can rightly evangelize what is the benefit. And when it comes to benefit, right? You need to look at it from both the angles of operation excellence and what is it going to do from a growth standpoint of solving a future problem. So somebody internally within T-Mobile we were able to use very nice, you know John's team, you know, the COE naturally fell in place. All of them were at some point in time doing automation. And slowly it was a path that they took to evangelize and we were able to piggyback and scale it bigger. >> So in the world we're in, whether you're talking about cloud services that are created by hyper scale cloud providers or automation platforms from UiPath, between those shiny toys and what we want to accomplish with them in the world of business and everything else there are organizations like iOpex and you and John are working together to figure out which projects need to be done in a strategic, from a strategic viewpoint but you're also addressing them tactically. I'm curious, >> Yeah. >> How does that business model from an iOpex perspective work do you have people embedded at T-Mobile that are working with John and his folks to identify the next things to automate? Is it a, is it, where is the push and where is the pull coming from in terms of, okay now what do we do next? Because look, let's be frank, in the, from a business perspective, iOpex wants to do as much as it can a value for T-mobile because that's what, that's the business they're in. But, so tell me about that push pull between the two of you. Does that make sense? Yeah, So I'll say real fast that, yeah iOpex is actually part of the T-mobile team. They are embedded. >> Nicholson: Okay. >> We work with them daily. >> Nicholson: Okay. >> Right. They had the expertise they're passing along the expertise to our full-time employees. And so it's like we're all one team. So that should answer that one for sure there. >> Absolutely. Let me add one more point to it. See if, you know, I think with respect to T-Mobile I would say it's a little bit of a special case for us. Why I say that is, when we started the whole conversation of we need to drive automation with you there was a natural way to get embedded, you know as part of their team. Normally what happens is a team, a COE team works and say I will do the discovery and you guys can come and do the solution design. That was not the case, right? I think it was such a strategic investment that T-Mobile made on us, right? We were part of the discovery team. So, which means that we were able to take all the best practices that we learned from outside and openness to accept and start looking at it what's in it for us for the larger good that made us to get to what we call it as building a solution factory for T-Mobile. >> Vellante: I got a lot of questions. >> John: Yeah. >> John, you mentioned your CIO and a couple of other constituents. >> Yes. >> What part of the organization were they from? They helped you with funding, >> Yep. >> And maybe sort of gave you a catalyst. How did this all get funded? If I, if you could, Cause a lot of people ask me well how do I fund this thing? Does it fund itself? Do I do, is it an IT driven initiative line of business? >> So those executives were from the IT team. >> Vellante: Okay. For sure. But a lot of our programs start from grassroots ground up and you know a lot of vendors say, hey, you need it from the top down. This was a perfect example of getting it from the top down. We were working it, it was fine, but it wouldn't have taken off if we didn't have, you know, Brian King and John Lowe providing us that executive sponsorship, going to their peers and telling them about the program and giving us the opportunity to showcase what automation can do. >> How do you choose, I got so many questions I'm going to go rapid fire. How do you choose your automation priorities? Is it process driven? Is it data led? What's the right approach? >> I think it's a combination, right? One fundamentally guiding principle that we always look at is let it not be a task automation, right? Task automation solves a particular problem, but maybe you know, if you start looking at it from a bigger, you need to start looking at it from process angle. And when it comes to process, right? There are a lot of things that gets executed in the systems of record, in the form of workflow. And there's a lot of things that gets executed outside the systems of record, which is in people's mind. That's when data comes in, right? So let's say you use process mining tool of UiPath, you will get to know that there is a bottleneck in a particular process because it's cluttered somewhere. But you also have to look at why is this clutter happening, and you need to start collecting data. So a combination of a data science as well as a process science blends together. And that's when you'll start deciding, hey this is repetitive in nature, this is going to scale, this is an optimization problem. And then you build a scorecard and that scorecard naturally drives the, you know decision making process. Hey, it's going to drive operation excellence problem for me or is it going to be a true business benefit of driving growth? >> So I was going to ask you how you visualize it. You visualize it through, I guess, understanding of the organization, anecdotal comments, research digging, peeling the onion, and then you do some kind of scorecard like approach and say, okay these are the high, high opportunity areas. Okay. So combination. Got it. How about change management? Because Dave, you and I were talking about this before, big organizations that I know they have IT, they got an application portfolio. That application portfolio the applications have dependencies on each other. And then they have a process portfolio that is also related. So any change in process ripples through the applications. Any change in application affects other applications and affects processes. So how do you handle change management? >> So we actually have a change management team and we make sure that before we go forward with anything it's communicated what changes would be in place. And this change management team also does communications broadly for any of our applications, not just automation. So they partner close with iOpex, with our development teams on opportunities that are going out. You want to add anything? >> Yeah. So when it comes to change management, right? Well, John is front-ending all the changes relating to apps and stuff like that by having a steering committee, what really is the proactive thing that we end up doing is right when a bot goes live, there is a life support that we provide for the entire bot that's gone live. And the fundamentally core principle for that entire support to work good is you start looking at what's the benefit that the bot is giving more than that when a bot fails. Right? Why is the bot failing? Is it because the systems of records on which the bot is running? Is it that is failing? Or the inputs that is coming to the systems of record the data format, is it changing or the bot logic is failed? And once we set up a constant monitoring about that we were able to throw insights into the change management team saying that the bot failed because of various reasons. And that kind of compliments the whole change management process. And we get earlier notifications saying, hey there's going to be changes. So which means we go proactively look at, hey, okay fair enough, this systems of records, this data is going to change. Can we test this out in staging before you hit the production? So that way the change becomes a smoother process. >> And how quickly can you diagnose that? Is it hours, minutes, days, weeks, months? >> So, >> Vellante: Depends. >> It's a very subjective question. Right. If we know the pattern early then the SWAT team quickly gets into it and figure out how we could stop something, you know, stop the bot from failing. The moment the bot fails, you know, you need to basically look at how the business is going to going to get affected. But we try to do as much as we could. >> So Naga, I'm going to put you on the spot here. >> Please. >> As a partner of UiPath, this question of platform versus product. In order to scale and survive and thrive into the future UiPath needs to be able to demonstrate that it's more than a tool set, but instead a platform. What's your view on that in general? What differentiates a platform from a product? Does it matter to your organization whether UiPath moves in the direction of platform or not? >> I think, it is, it's undoubtedly platform, right? And a platform in my mind will constantly evolve. And once you think about it as a platform you will end up having a lot of plug and place. If you look at the way UiPath is evolving it is evolving as a platform. It used to be attended bot and unattended bot and plugged with Orchestrator. And if you look at it, the problem of solving the up chain and the down chain naturally came in process mining, task capture, made it up chain, a platform that solves the up chain. And then it slowly evolved into, hey I'm actually doing business process automation. Why could I not do test automation with the same skillset? So a platform will try to look at what is that, you know I've got in myself and how can I reuse across the enterprise? I think that is deeply embedded in the UiPath culture. And that's the kind of platform that, you know anybody like a system integrator like us, we do not have to multi-skill people. You just have to skill in one and you can interchange. That I would say is a good approach. >> So John, what's the future look like? What's the organization's appetite for automation? You know, is there an all you could eat kind of enterprise license approach? >> John: Yeah, so we are enterprise license. >> You are? Okay. >> So, and iOpex helped us move to the cloud so we can move quickly. That was definitely a benefit. The future of it, I would say citizen development is going to be key. Like I want citizen development within every business organization. I want them to be able to discover, deploy, you know, and and just use us, the center of excellence as support as needed. The appetite's there. Every group has automation within their goals or KPIs right? So it's there. We just need to be able to get in front of 'em. It's a large company. So I'm, '23 is going to be huge for us. >> Another fantastic story. I love that UiPath brings the customers to theCUBE. So thank you guys for telling your story. Congratulations on all your success. Good luck in the future. >> Yeah. Thank you. >> All right. Okay. Thank you for watching. This is Dave Vellante for Dave Nicholson UiPath FORWARD5. The bots are running around Dave. We're going to have to get one of the bots to come up here and show people a lot of fun at FORWARD. We're here in Vegas, right back, right after this short break.

>>The Cube presents UI Path Forward. Five. Brought to you by UI Path. >>Welcome back to The Cube's coverage of UI Path Forward. Five from Las Vegas. We're inside. The formerly was The Sands, now it's the Venetian Convention Center. Dave Nicholson. David, Deb. I've never seen it set up like this before. UI Path's. Very cool company. So of course the setup has to be cool, not like tons of concrete. James Furlong is here, the Vice President of Supply Chain Management and projects at Puma. And Derek Weimer is the CEO of Robo, who's an implementation partner, expert at Intelligent Automation. Folks, welcome to the Cube. Good to see you. Great to have you on. >>Thank you. It's a pleasure. >>So what's happening at Puma these days? I love your sneakers, but you guys probably do more than that, but let's tell us about, give us the update on Puma. >>Yeah, absolutely. Puma's one of the world's leading sports, sports brands. So we encompass all things sports. We do footwear, we do apparel, we do accessories. Cobra, Puma golf is underneath our umbrella as well. So we get the added benefit of having that category as well. And yeah, trade, trade all over the world and it's an exciting, exciting brand to be with. >>And di Robo Atlanta based really specialists in intelligent automation. That's pretty much all you do, is that right? >>Yeah, we are a pure play intelligence automation professional services firm. That's all we do. We're the world's largest firm that focuses only on automation headquarter in Germany, but with a large presence here in Americas. >>So we hear from a lot of customers. We've heard from like with the journey it started, you know, mid last decade, Puma James is just getting started. We April you mentioned. So take us through that. What was the catalyst as you're exiting the, the pandemic, the isolation economy we call it? Yeah. What was the catalyst tell, take us through the sort of business case for automation. >>Sure, absolutely. So Puma, our mission is forever faster. It's, it's our mantra and something we live and breathe. So naturally we have an intense focus on innovation and, and automation. So with that mindset, the way this all kicked off is that I had the opportunity to go into some of our distribution facility and I was unbelievably impressed with the automation that I saw there. So how automation augmented the employee workforce. And it was just very impressive to see that some of our state of the art technology and automation at the same time. Then I went back to the office with that excitement and that passion and I saw that we had the opportunity to take that to our employee base as well. We sort of lacked that same intense focus on how do we take automation and technology like I saw at the distribution facilities and bring it to our employees because picture a large workforce of talented, dedicated employees and they just couldn't keep up with the explosive growth who's seen explosive growth over the last couple of years and they just couldn't keep up with it. So I said that that's it. We need to, to take that same passion and innovation and enter in hyper hyper automation. So we went to the leadership team and no surprise they were all in. We went with them with the idea of bringing hyper automation, starting with RPA to, to our office employees. And they were in, they support innovation and they said, Great, what do you need? Really? Go for it. >>The first question wasn't how much, >>Actually the first question I will say that the funny part is, is they said, Well I like this, it sounds too good to be true. And because it, it really does. If you're new to it like we were and I'm pitching all the benefits that RPA could bring, it does sound too good to me. True. So they said, All right, you know, we trust you and, and go for it. What do you need? Resources, just let us know. So sure enough, I had a proof of concept, I had an idea, but now what? I didn't know where to go from there. So that's where we did some intensive research into software suppliers, but also implementation partners because now we knew what we wanted to do. We had excitement, we had leadership buy-in now, now what do I do? So this is when we entered our partnership to figure out, okay, help Puma on this journey. >>How'd you guys find each other? You know, >>Just intensive research and spoke with a lot of people here. Is there a lot of great organizations? But at the end of the day, they really supported everything that Houma stood for, what we're looking to do and had a lot of trust in the beginning and Dirk and his team and how he could help us on this journey. Yeah. >>Now James, your, your job title system for supply chain management. It is, but I understand that you have had a variety of roles within the organization. Now if we're talking about another domain, artificial intelligence, machine learning. Yeah. There's always this concept of domain expertise. Yeah. And how when you're trying to automate things in that realm, domain expertise is critical. Yeah. You have domain expertise outside of your job title. Yeah. So has that helped you with this journey looking at automation, being able to, being able to have insight into those other organizations? >>Yeah, absolutely. And I think when we were pitching it to the leadership team in the beginning, that enabled me to look at each one sitting at the table and saying, alright, and on the sales, on a commercial side, I was a head of sales for one of the trade channels. I could speak directly to him in the benefits it could have with not with tribal knowledge and with an expertise. So it wasn't something that, it was just, oh, that's supply chain. I could sit, you know, with the, our CFO and talk to him about the, the benefits for his group merchandising and legal so on. I was really able to kind of speak to each one of them and how it would support, because I had that knowledge from being blessed of 15 years experience at, at Puma. So yeah, I was able to take all of that and figure out how do I make sure not just supply chain benefits from rpa, but how does the whole organization benefit from not only RPA but the hyper automation strategy. >>So what's an engagement look like? You start, I presume you, you gotta do some type of assessment and, and you know, of some upfront planning work. Yeah. What does that look like? How, what's the starting point? Take us through that >>Journey. Yeah, so exactly. So the, the key when you're trying to get value from Intel automation is finding the right opportunities, right? And you can automate a lot of things, but which are the things that are gonna drive the most value and, and the value that actually matters to the company, right? So where are you trying to get to from a strategic level, your objectives and how do you actually use automation to help you get to there? So the first thing is, what are the opportunities gonna help you do that? And then once you identify, what we recommend is start with something that's gonna be, you know, accessible, small, You're gonna get a quick win. Cuz then the important thing is once you get that out there, you build the momentum and excitement in the organization that then leads to more and more. And then you build a proper pipeline and you and you get that the, the engagement. >>So what was that discovery like? Was it you fly up there and do a, a chalk talk? Or did you already know James, like where you wanted to focus? >>Yeah, I knew I had a solid proof of concept with the disruptions in supply chain we couldn't keep up with, with all the changes and supply. So right away I knew that I have a very substantial impact on the organization and it would be a solid proof of concept. It was something that not only would supply chain steal, but our customers would feel that we would be servicing them better. Our sales team, the commercial team, marketing impacted everybody. But at the same time it was tangible. I saw two people that just physically couldn't get their, their work done despite how talented and hardworking they were. So I, I was in on that proof of concept and then I just took that idea with some strong advice from Dirk and and his team on, okay, well how do I take that? But then also use that to evangelize through the organization. What are some pitfalls to avoid? Because as a proof of concept, they just told me it's too good to be true. I believe in it. So it was so important to me that it >>Was successful. >>It get your neck out. Oh, I sure was. Which is a little scary, but I had confidence that we would >>Do it. But your poc you had to have a systems view. Yes. Right? Cuz you were trying to, I think you, I'm inferring that you had two people working really hard, but they couldn't get their job done. Yeah, for sure. They were just sitting on their hands. Right. Waiting. Okay. So you kind of knew where the bottlenecks were. Yes. And that's what you attacked and or you helped James and her the team think through that or, >>Yeah, exactly. So, so a couple points you were asking about her domain model of knowledge earlier, and I think that's really key to the puma's success with it, is that they've come at it from a business point of view, what matters to the business. And at the point, you know, supply chain challenges, how do we use automation to address that? And then, you know, and then it's gonna, it's actually gonna, you know, pick opportunities that are gonna matter to the business. Yeah, >>Yeah. At the same time, we, we knew this could be a scary thing, right? If it's not done right, you know, automation definitely can, can take a, a wrong path. So what we relied on them for is tell us how to make this successful. We wanted structure, we wanted oversight, we wanted to balance that with speed and really, you know, developing our pipeline, but at the same time, tell us how to do this right? How do we set up a center, our first ever center of excellence? They help us set that up. Our steerco, our process definition documents are like, they really helped us add that structure to how to make this successful, sustainable and make sure that we were standing things up the right way versus launching into a strong proof, proof of concept. But then it's not gonna be scalable if we didn't really take their strong advice on how to make this something, you know, that had the right oversight, the right investment. So that was, that was key as >>Well for us. So when you looked at the POC and James was saying there were potential pitfalls, what were those pitfalls? Like what did you tell Puma, Hey, watch out for this, watch out for that. What was sort of the best advice there? >>Yeah, so I think one is understanding complexity, right? So a lot of opportunities sound good, but you want to make sure that it's, it's feasible with the right tool set. And also that you're not bit off too much in the beginning is really important. And so some of that is that bringing that expertise to say, Okay, yeah, look, that does something, a good process. You're gonna get value out. It's not gonna be overly complicated. It's a good place to start. And then also, I guess the thing too to mention is it's more than just a technology project. And that's the thing that we also really focus on is it's actually as much about the change management, it's much about, you know, what is the right story, the business case around it, the technology actually in a way is the easy part and it's all the stuff around it that really makes the POC effective, >>Obviously the process. Yeah. Been the people I presume getting to adopt, >>Right? And I think, again, with our, our brand mantra forever faster, we, we get that support that the buy-in from the top is is there from, from the beginning. So that's a benefit that some companies don't, they don't have, right? They have a little resistance maybe from the top. We're trying to get everyone's buy in it. And we had that. So we had, you know, the buy-in the engagement, we were ready to go. So now we just needed someone to kind of help us. >>One more if I may. Yeah, yeah. Gabe, six months in. Yes. That's the business impact that, can >>You tell you? That was tremendous. Yeah. >>Really already six months. Wow. >>Yeah, >>Absolutely. Cfo, CFO's dream. Yeah. >>And again, and, and we had a CFO change mid, mid project. So the new CFO comes in, not new to Puma, the same thing. Super, super smart guy. And I had to sit and again pitch, you know, pitch what it is and the support that I needed by way of investment. And he saw the results and he was all in, you know, what do you need, what's next? And instantly was challenging his departments, Why don't he got competitive, right? We're a competitive bunch, so why don't you know, you should have more in the pipeline. And he was, he was bought in. So there was that fear of a new CFO coming in and how do you show value? Because some of it is, it's very easy to show right away, You know, we were able to refocus those two full-time employees on, on higher value chain activity and you know, they're doing a tremendous job and they're, you know, they have the, the bot and the automation supporting them. So he saw that right away. And we can show him that. But he also understands, as does the whole leadership team, the concept of downstream impacts that you can't necessarily, you know, touch and, and put on paper. So he sees some, but then he also recognizes all the other upstream and downstream impacts that it's had and he's all in and supports whatever, whatever we need. >>Yeah. New CFOs like George Seaford taking over for bill walls. >>Yeah, exactly. Exactly. We >>Have, we have to keep showing results and it has to be sustainable. So that's, again, we'll rely on our partnership to say, okay, this is the beginning, you know, what's next? Keep us, you know, honest on oversight and, and any pitfalls that we should avoid because he's excited. But at the same time, we need to make sure that we sustain those results and, and show what's next. Now they all gotta taste to the apple and they're very eager to see what's next in, in, in this hyper automation journey. >>Well, Dirk, you've partnered on this journey, this specific journey with, with, with Puma. But from your perspective in the broader marketplace, what would be the perfect low hanging fruit opportunity that you would like to have somebody call you and say, Hey, we've got, we've got this perspective engagement with a client. What would be the, what would be the like, Oh yeah, that's easy, that's huge roi really quickly, What does that look like? >>Yeah, I think there's, there's a few areas, right? You know, one task automation RPA is a, is a really good entry point, right? Because it's, it's, it's not overly complex. It doesn't involve a lot of complicated technologies. And I'd say the, the usual starting areas, you know, you, you finance back office, you know, shared service, invoice processing, you know, payables is a very good opportunity area. HR is also an area I would look at, you know, in new, new employee onboarding process or you know, payroll, et cetera. And then supply chain is actually becoming more and more, more common, right? So those would be I guess, top three areas I would mention. And >>Then, and then kind of follow onto that, what's the tip of this sphere? What's the sort of emerging market Yeah. >>For >>This kind of technology? >>I think there's two things. One, it's taking a holistic into end view and leveraging multiple, you know, technology, you know, beyond just rpa, right? You know, intelligent document processing, iml, you know, bringing all this to bear to actually do a true digital transformation. That's, that's number one. And then I'd say the second is going from focusing on cost and efficiency to actually getting into the front office and how do you, how do you actually increase revenue? How do you increase margin? How do you actually, you know, help with that, that top line growth. I think that's really, and that's where you're leveraging technologies, you know, like the, the AI as an example to really help you understand how do you optimize. >>So James, that's, that becomes then an enterprise wide initiative. Yeah. That's, that's, is that your vision? Maybe maybe lay that out for >>Us a bit. Yeah, ab absolutely. The, the vision is now that we've seen what, what it can do, how do we take it from being managed by just, you know, supply chain and this proof of concept cuz I manage projects, but now it's bigger than just a supply chain project. And how do we sort of evangelize that through the whole organization And you know, they mentioned on main stage this, the creation of new jobs and, and roles and how a, a company might set out their strategic directive now is, is changing and evolving. So you know that that's our idea now and that what we'll need support next is how should we structure now for success. And so that it's across the whole enterprise. But that's, that's the vision for >>Sure. What worries you do, you worried about it like taking off and getting outta control and not being governed and so you have to be a little bit careful there. >>Yeah, for sure. That was really important to us. And we actually got to leverage a lot of heavy lifting that Puma Global had done at the same time that we were coming up and, and thinking of the idea of rpa. They were having the same thoughts and they did a lot of heavy lifting again, about not only the software providers but also what does the structure look like, the oversight, a center of excellence globally. So we were able to really leverage a lot of best practices and SOPs that they had set out and we were able to kind of leverage those, bring those to Puma North America so that we didn't face that fear cuz that would be a limiting factor for us. So because we were so disciplined and we could leverage the work that they had done, that fear wasn't, wasn't there. Now we have to stay, you know, on top of it. And as people get excited, how do you kind of mirror the excitement and with it at the same time that the oversight and not getting, you know, too, too big, too fast. So that's the balance that we'll, we'll work through now. It's a good problem to have. >>Well, exactly. It is super exciting. Great story. Congratulations on, on the success and good luck. Thank you. Yeah, you very much for coming to the, Yeah. Thank you. Thank you. All right. And thank you for watching. Keep it right there. Dave Nicholson Andante right back, the cube live from Las Vegas UI path forward. Five.

>> Announcer: theCUBE presents HPE Discover 2022, brought to you by HPE. >> We're back at the formerly the Sands Convention Center, it's called the Venetian Convention Center now, Dave Vellante and John Furrier here covering day three, HPE Discover 2022, it's hot outside, it's cool in here, and we're going to heat it up with Rashmi Kumar, who's the Senior Vice President and CIO of Hewlett Packard Enterprise, great to see you face to face, it's been a while. >> Same here, last couple of years, we were all virtual. >> Yeah, that's right. So we've talked before about sort of your internal as-a-service transformation, you know, we do call it dog fooding, everybody likes to course correct and say, no, no, it's drinking your own champagne, is it really that pretty? >> It is, and the way I put it is, no pressure to my product teams, it's being customer zero. >> Right, take us through the acceleration on how everything's been going with you guys, obviously, the pandemic was an impact to certainly the CIO role and your team but now you've got GreenLake coming in and Antonio's big statement before the pandemic, by 2022 everything will be as a service and then everything went remote, VPNs and all this new stuff, how's it going? >> Yeah, so from business perspective, that's a great point to start that, right? Antonio promised in 2019 that HPE will be Everything-as-a-Service company and he had no view of what's going to happen with COVID. But guess what? So many businesses became digital and as-a-service during those two years, right? And now we came back this year, it was so exciting to be part of Discover when now we are Everything-as-a-Service. So great from business perspective but, when I look at our own transformation, behind the scene, what IT has been busy with and we haven't caught a breadth because of pandemic, we have taken care of all that change, but at the same time have driven our transformation to make HPE, edge to cloud platform as a service company. >> You know, I saw a survey, I referenced it earlier today, it was a survey, I think it was been by Couchbase, it was a CIO survey, so they asked, who was responsible at your organization for the digital transformation? And overwhelming, like 75% said, CIO, which surprised me 'cause, you know, in line with the business and so forth but in fact I thought, well, maybe, because of the forced march to digital that's what was top of their mind, so who is responsible for, and I know it's not just one person, for the digital transformation? Describe that dynamic. >> Yeah, so definitely it's not one person, but you do need that whole accountable, responsible, informed, right, in the context of digital transformation. And you call them CIO, you call them CDIO or CDO and whatnot but, end of the day, technology is becoming an imperative for a business to be successful and COVID alone has accelerated it, I'm repeating this maybe millions time if you Google it but, CIOs are best positioned because they connect the dots across organization. In my organization at HPE, we embarked upon this large transformation where we were consolidating 10 different ERPs, multiple master data system into one and it wasn't about doing digital which is e-commerce website or one technology, it was creating that digital foundation for the company then to transform that entire organization to be a physical product company to a digital product company. And we needed that foundation for us to get that code to cash experience, not only in our traditional business, but in our as-a-service company. >> So maybe that wasn't confirmation bias, I want to ask you about, we've been talking a lot about sustainability and I've made the comment that, if you go back, you know, 10, 12 years and you were CIO IT at that time, CIO really didn't care about the energy bill, that was paid for by facilities, they really didn't talk to each other much and that's completely changed, why has it changed? How should a CIO, how do your your peers think about energy costs today? >> Yeah, so, at some point look, ESG is the biggest agenda for companies, regulators, even kind of the watchers of ISS and Glass Lewis type thing and boards are becoming aware of it. If you look at 2-4% of greenhouse emission comes from infrastructure, specifically technology infrastructure, as part of this transformation within HPE, I also did what I call private cloud transformation. Remember, it's not data center transformation, it's private cloud transformation. And if you can take your traditional workload and cloudify it which runs on a GreenLake type platform, it's currently 30% more efficient than traditional way of handling the workload and the infrastructure but, we recently published our green living progress report and we talk about efficiency, by 2020 if you have achieved three times, the plan is to get to 30 times by 2050 where, infrastructure will not contribute to energy bill in turn the greenhouse emission as well. I think CIOs are responsible multifold on the sustainability piece. One is how they run their data center, make it efficient with GreenLake type implementations, demand from your hyperscaler to provide that, what Fidelma just launched, sustainability scorecard of the infrastructure, second piece is, we are the data gods in the company, right? We have access to all kinds of data, provide that to the product teams and have them, if we cannot measure, we cannot improve. So if you work with your product team, work with your BU leader, provide them data around greenhouse gas and how they're impacting a mission through their products and how can they make it better going forward, and that can be done through technology, right? All the measurements come from technology. So what technology we need to provide to our manufacturing lines so that they can monitor and improve on the sustainability front as well. >> You mentioned data, I wanted to bring that up 'cause I was going to bring that up in another top track here, data as an asset now is at play, so I get the data on the sustainability, feed that in, but as companies go to the cloud operating model, they go, hey, I got the hyperscalers, you call microscale, Amazon for instance, and you got on-premises data center, which is a large edge and you got the edge, the data control plane, and then the control plane and the data plane are always seem to be like the battle ground, I want to control the data plane, will customers own the data plane or will the infrastructure providers control that data plane? And how do you see that? Because we want to power the machine learning, so data plane control plane, it seems to be like the new middleware, what's your view on that? How do you look at that holistically? >> Yeah, so I'll start based on the hyperscaler conversation, right? And I had this conversation with one of the very big ones recently, or even our partner, SAP, when they talk about RISE, data center and how I host my application infrastructure, that's the lowest common denominator of our job. When I talk about CIOs being responsible for digital transformation, that means how do I make my business process more innovative? How do I make my data more accessible, right? So, if you look at data as an asset for the company, it's again, they're responsible, accountable. As CIO, I'm responsible to have it managed, have it on a technology platform, which makes it accessible by it and our business leader accountable to define the right metrics, right kind of KPIs, drive outcome from that data. IT organization, we are also too busy driving a lot of activities and today's world is going to bad business outcome. So with the data that I'm collecting, how do I enable my business leader to be able to drive business outcome through the use of the data? That's extremely important, and at HPE, we have achieved it, there are two ways, right? Now I have one single ERP, so all the data that I need for what I call operational reporting, get hindsight and insight is available at one place and they can drive their day to day business with that, but longer term, what's going to happen based on what happened, which I call insight to foresight comes from a integrated data platform, which I have control of, and you know, we are fragmenting it because companies now have Databox, Snowflake, AWS data analytics tool, Azure data analytics tool, I call it data torture. CIOs should get control of common set of data and enable their businesses to define better measurements and KPIs to be able to drive the data. >> So data's a crown jewel then, it's crown jewel not-- >> Can we double-click on that because, okay, so you take your ERP system, the consumers of data in the ERP system, they have the context that we've kind of operationalized those systems. We haven't operationalized our analytics systems in the same way, which is kind of a weird dynamic, and so you, right, I think correctly noted Rashmi that, we are creating all these stove pipes. Now, think I heard from you, you're gaining control of those stove pipes, but then how do you put data back in the hands of those line of business users without having to go through a hyper specialized analytics team? And that's a real challenge I think for data. >> It is challenge and I'll tell you, it's messy even in my world but, I have dealt with data long enough, the value lies in how do I take control of all stove pipes, bring it all together, but don't make it a data lake which is built out of multiple puddles, that data lake promise hasn't delivered, right? So the value lies in the conformed layer which then it's easier for businesses to access and run their analytics from, because they need a playground because all the answers they don't have, on the operation side, as you mentioned, we got it, right? It'll happen, but on the fore site side and deeper insight side based on driving the key metrics, two challenges; understanding what's the key metrics in KPI, but the second is, how to drive visibility and understanding of it. So we need to get technology out of the conversation, bring in understanding of the data into the conversation and we need to drive towards that path. >> As a business, you know, line of business person putting that hat on, I would love to have this conversation with my CIO because I would say, I just want self-service infrastructure and I want to have access to the data that I need, I know what metrics I need to run my business so now I want the technology to be just a technical detail, you take care of that and then somebody in the organization, probably not the line of business person wants to make sure that that data is governed and secure. So there's somebody else and that maybe is your responsibility, so how do you handle that real problem? So I think you're well on the track with GreenLake for self-serve infrastructure, right, how do you handle the sort of automated governance piece of it, make that computational? Yeah, so one thing is technology is important because that's bringing all the data together at one place with single version of truth. And then, that's why I say my sons are data scientist, by the way, I tell them that the magic happens at the intersection of technology knowledge, data knowledge, and business knowledge, and that's where the talent, which is very hard to find who can connect dots across these three kind of circles and focus on that middle where the value lies and pushing businesses to, because, you know, business is messy, I've worked on pharma companies, utilities, now technology, order does not mean revenue, right? There's a lot more that happen and pricing or chargeback, rebates, all that things, if somebody can kind of make sense out of it through incremental innovation, it's not like a big bang I know it all, but finding those areas and applying what you said, I call it the G word, governance, to make sure your source is right and then creating that conform layer then makes into the dashboard the right information about those types of metrics is extreme. >> And then bringing that to the ecosystem, now I just made it 10 times more complicated. >> Yeah, this is a great conversation, we on theCUBE interview one time we're talking about the old software days where shrink-wrap software be on the shelf, you wouldn't know if was successful until you looked at the sales data, well after the fact, now everything's instrumented, SaaS companies, you know exactly what the adoption is, either people like it or they don't, the data doesn't lie. So now companies are realizing, okay, I got data, I can instrument everything, your customers are now saying, I can get to the value fast now. So knowing what that value is is what everyone's talking about. How do you see that changing the data equation? >> Yeah, that's so true even for our business, right? If you talk to Fidelma today, who is our CTO, she's bringing together the platform and multiple platforms that we had so far to go to as-a-service business, right? Infosite, Aruba Central, GLCP, or now we call it it's all HPE GreenLake, but now this gives us the opportunity to really be a alongside customer. It's no more, I sold a box, I'll come back to you three years later for a refresh, now we are in touch with our customer real time through Telemetry data that's coming from our products and really understanding how our customers are reacting with that, right? And that's where we instantiated what we call is a federated data lake where, marketing, product, sales, all teams can come together and look at what's going on. Customer360, right? Data is locked in Salesforce from opportunity, leads, codes perspective, and then real time orders are locked in S4. The challenge is, how do we bring both together so that our sales people have on their fingertip whats the install base look like, how much business that we did and the traditional side and the GreenLake side and what are the opportunities here to support our customers? >> Real quick, I know we don't have a lot of time left, but I want to touch on machine learning, which basically feeds AI, machine learning, AI go together, it's only as good as the data you can provide to it. So to your point about exposing the data while having the stove pipes for compliance and governance, how do you architect that properly? You mentioned federated data lake and earlier you said the data lake promise hasn't come back, is it data meshes? What is the architecture to have as much available data to be addressed by applications while preserving the protection? >> Yeah, so, machine learning and AI, I will also add chatbots and conversational AI, right? Because that becomes the front end of it. And that's kind of the automation process promise in the data space, right? So, the point is that, if we talk about federated data lake around one capability which I'm talking about GreenLake consumption, right? So one piece is around, how do I get data cleanly? How do I relate it across various products? How do I create metrics out of it? But how do I make it more accessible for our users? And that's where the conversational AI and chatbot comes in. And then the opportunity comes in is around not only real time, but analytics, I believe Salesforce had a pitch called customer insight few years ago, where they said, we have so many of you on our platform, now I can combine all the data that I can access and want to give you a view of how every company is interacting with their customer and how you can improve it, that's where we want to go. And I completely agree, it ends up being clean data, governed data, secure data, but having that understanding of what we want to project out and how do I make it accessible for our users very seamlessly. >> Last question, what's your number one challenge right now in this post isolation world? >> Talent, we haven't talked about that, right? >> Got to get that out there. >> All these promises, right, the entire end to end foundational transformation, as-a-service transformation, talking about the promise of data analytics, we talked about governance and security, all that is possible because of the talent we have or we will have, and our ability to attract and retain them. So as CIO, I personally spend a lot of time, CEO, John Schultz, Antonio, very, very focused on creating that employee experience and what we call everything is edge for us, so edge to office initiative where we are giving them hybrid work capabilities, people are very passionate about purpose, so sustainability, quality, all these are big deal for them, making sure that senior leadership is focused on the right thing, so, hybrid working capability, hiring the right set of people with the right skill set and keeping them excited about the work we are doing, having a purpose, and being honest about it means I haven't seen a more authentic leader than Antonio, who opens up his keynote for this type of convention, with the purpose that he's very passionate about in current environment. >> Awesome, Rashmi, always great to have you on, wonderful to have you face to face, such a clear thinker in bringing your experience to our audience, really appreciate it. >> Thank you, I'm a big consumer of CUBE and look forward to having-- >> All right, and keep it right there, John and I will be back to wrap up with Norm Follett, from HPE discover 2022, you're watching theCUBE. 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>>The cube presents HPE discover 2022 brought to you by HPE. >>Hello, everybody. Welcome to day three of the Cube's coverage of HPE discover 2022 we're live from Las Vegas and the Venetian convention center. This is I, I counted him up. I think this is the 14th HP HP slash HPE. Discover that we've done really excited to welcome in Alexia Clements. She's the vice president of go to market for HPE GreenLake cloud services. That's all the rage everybody's talking about. Green, all the wood behind the arrow, as the saying goes, welcome to the queue. Good to see >>You. Thank you so much for having me thrilled to be here. >>You walk up Janet Jackson last night, >>Epic. Wow. She killed it. She was awesome. >>I thought the band was super tight, but the other thing was the place was >>Packed. It was >>Nice. You know, what happens is a lot of time they put the band in the getaway day, you know, and nobody stays, but wow, the, the hall was jammed. >>It was great. It was, you could feel the momentum and the excitement. And it was just a great way to, to kind of end the, the HP discover. So it was great. >>Yeah. I mean, I, I mentioned that we've been to a lot of HP slash HPE discovers and, and this one was different in the sense that I think first of all, 8,000 people, yep. People are excited to get back together, but I think, you know, HPE has a spring in its step and the customers are kind of interested. It's much more focused than some of the past HPE discoverers, which was kind of hard to get my hands around. Sometimes the business was sort of an Antonio's pulled that together. So what's changed since the last time we were face to face. >>We're transforming and hope you all saw that on the, on the floor here. So, um, we're absolutely trans going through a transformation and, you know, I, I think we're, you know, we're shifting to an edge to cloud platform company. And with that, it's, it's how we approach our customers differently and our partners and, you know, we're hoping that, uh, we showed this week and that, that we're different and we're transforming. >>So how do you spend your time Mo mostly in front of customers having conversations about what, what their needs are and aligning is that right? >>Yeah. So, um, I, I lead the, the go to market for GreenLake. So that's everything around how we're driving our as a service go to market strategy, how we're driving programs, enablement, how we're really in the end, how we're executing on that as a service strategy from a sales perspective. >>So what do you hear? Of course, a lot of that involves partners. Yep. Right. I mean, that's kind of the route to market. Absolutely. The HPE prefers for obvious reasons, although others don't necessarily share that, but, but, so what are you hearing from the partner ecosystem and the customers that their biggest challenges are now that we're entering the let's call it the post isolation economy? <laugh> >>Yeah. I mean, the reality is, is digital transformations are hard and I think some customers, um, who haven't necessarily moved forward on it or, you know, maybe they move forward and they're realizing, Hey, I'm stuck and I'm not, I'm not getting to where I wanna be and really, you know, driving that end state. So, I mean, I, I would just say overall, I think things are like, customers are, are struggling if they didn't, you know, they're falling behind a little bit. And I think through the conversations that we're having and through HP green, like it gives customers choice. And so really, um, I mean, what, you know, I spend my time with, and, and when we're talking to customers and partners, it's about helping customers on that digital transformation journey and understanding what are they trying to drive? What business outcomes are they trying to drive and how we can help them get there. So >>I, I often call it the force March to digital yep. With the pandemic. Um, and, and I, I was looking at a survey recently, I think it was put on by couch base. And it was probably on a thousand respondents and it was a CIO survey and they asked who's, who's responsible for the digital transformation at the organization and overwhelmingly it was the it organization. And I said, uhoh, that's the problem now. But it made sense to me because when the economy shut down, everybody went to it and said help, right. Make this work somehow. Right. But, but what, that doesn't seem to me to be the right prescription for a successful digital transformation. Do you agree with that? And what do you see as a successful template for DX? >>Well, I think what, what we see is that really the lines of business are desperate to move fast and they're really looking for their it partners to help them in that journey and, and, and drive, you know, whether it be, you know, drive them, you know, drive orders, drive, you know, they need it to help them in that journey. And so really it's gotta be a partnership between the two organizations. And what we're trying to do with HP GreenLake is kind of abstract that almost. So, Hey, we're gonna give it to you in an, as a service and you're gonna get all of these components. And all you have to think about is where do I need to grow and what are the outcomes that I'm looking for? So that's what it's gotta be. There's gotta be tight alignment, I think between the lines of business and it, and sometimes those two don't know how to talk to each other. >>Mm-hmm <affirmative> so that's another way of, of really trying to speak to the business leaders and say, what are you trying to do? Where do you need to go? And what do you need to get? And, and a lot of times they don't even know what they need to get there. So that's where we need to have those different conversations with our customers to, and that's where we look for our partners to help us in that. So really having those different conversations to progress, um, what, you know, what customers are really looking to, to drive, >>How, how does GreenLake specifically accelerate that transformation? Where does it fit? Maybe you can kind of take us through, you know, a, a generic example of how that works. >>Yeah. I mean, a great example is, you know, especially with the pandemic is desktop, Hey, you now need to, you know, everybody's working from different locations. So, you know, desktop as a service VDI as a service, and, you know, you're putting it in a, you know, per whatever, you know, per you can, whatever variable pricing you want, but think about it, you have that one pay as you go. And so the it organization, all they have to think about is that's my, you know, per, per unit price there. So that's a great example of how we saw, like, especially during the pandemic, that was something that was, you know, a huge area of focus organizations. What's >>The spectrum that you see in terms of, you know, the maturity model, if you will, a digital transformation. I mean, if you weren't in a digital business during the pandemic, you were pretty much out of business. Yeah. And with very few exceptions. Um, and so, okay. So on the one end, you have folks that sort of were forced into it. You, my forced March scenario, others were actually moving quite a bit along before the pandemic, others were kind of given at lip service and maybe doing a few projects. What do you see as that spectrum? >>I think if you're not transforming, you're falling behind. And so everybody needs to be, you know, looking to the future and understanding, you know, really trying to get aggressive on that. And that's what we're seeing. We're seeing companies who, you know, aren't moving fast on that or falling behind. >>Do you see a bifurcation? I'm sure you do those that say, yeah, I want as a service and others that say, look, I I'm really well capitalized. I'm gonna gimme the, gimme the CapEx. I'm gonna put it in and run it myself. And is there a relationship between that approach and their digital transformation maturity, or is it kind of just really their preference? >>I, I mean, for us, we're meeting customers where they're at on their journey and their multi-cloud journey. So some, and, and what I'm seeing is that every customer today has multiple clouds, whether that be their, you know, their kind of, MultiGen it, the, the legacy stuff that they've gotta deal with. They've got stuff in public clouds, and they're trying to really transform and figure out how do I work all of that in like, how do I move forward with that new operating model? And so what I'm seeing is, you know, we're gonna meet customers where they're at on their journey. So some are gonna continue to go down that path in a, how they've always purchased their it. And others are really, you know, more often than not, we're seeing, they want that as a service cloudlike to have all the benefits of cloud, but yet still have it on their prem or in a colo or, you know, at the edge. So I do see some of those customers who are thinking differently, right. That, and they're the ones that are more apt to be a little bit more aggressive on their digital transformation. They're, they're open to the possibility if that makes sense. No, >>It does. It makes total sense. I, I, I think, you know, on the one hand they're a lot of customers are trying to build their own cloud. Yep. Um, so you mention multicloud, I'm not gonna go to Amazon to help me with my multicloud strategy. That's not, that's not gonna be my preferr. Yeah. I might talk to Microsoft about it a little bit. Google's got Antos and that's kind of interesting, but you know, Google's not enterprise, they got good data, but so, but there are other choices out there. Why HPE for my cloud hybrid multi-cloud strategy, give us the >>Sticker. It's, it's the best of both worlds for customers. So it enables them to have the security. It enables them to grow, to, to be in their data centers or in colos at the edge. It allows them to not over provision. It allows them to pay as they go and pay as they grow there's. Um, and then it also really is that ease factor. So it it's that thinking about it as I have, I already, I know what my pricing is. I know what that predictability is from a pricing perspective and what my costs are gonna be. So all of those things really re that all those messages resonate with customers, >>Right? L thanks so much for coming on. We got the trains are backing up super tight schedule today. This is wall to wall coverage of HPE. Discover. Thank you. Thank >>You so much for having me appreciate it. >>You're SU very welcome. All right. Keep it right there. Dave ante is here. John furrier, HPE discover 2022 from Las Vegas. We're live. We'll be right back.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hi everybody. Welcome back to the Cube's coverage of HPE. Discover 2022 from the Venetian convention center, formerly the sand convention center in Las Vegas, Dave ante, with John furrier. We're here with Brad parks. Who's the chief product officer at morphia data and Brian Thompson. Who's the vice president of GreenLake cloud product management at Hewlett Packard enterprise gentlemen. Great to see you first time on the queue first time. Wow. I just assumed we've known each other for, so >>We've been around a long time now. I'm happy to be here and thanks for, thanks for making the >>Time. Yeah, you've put a lot of people on the queue, but Morpheus data, when we, you know, we first met, I mean, with your new role here several years ago, tell, give us the update what's Morpheus do, why are you, so why does people, why do people need Morpheus? Think >>People need Morpheus, cuz it is messy, right? Technology promise, you know, simple, better, faster, but it's only gotten more complex, more heterogeneous over the last decade. We are a unified orchestration and automation platform that makes kind of the, the messy labyrinth that is enterprise. It kind of simpler to navigate primary use case. Self-service for developers who wanna push a button, get a database and an abstract deployed into their on-prem or their public cloud without having to wait on it. >>So you've, you've, you've been through the hyper-converged world. You've seen all that hardware come together. The VMware Nutanix of the world's kind of hardware. Now you got this software abstraction where you got operations, you've got AI, you got all kinds of ops AI ops dev ops data ops ops machine, >>You >>Know, they're all there. And so you got developer environments, you got operating environments. It's just getting more complicated at scale. Yep. This is a huge challenge. You guys are tackling this and then by the way, throw in automation in there too. Right? So, so all that's kind of coming together. How does self-service work put all that complication? >>Well, so I was just talking about Robert Christiansen. I know he's probably think he's been on the Q he's on S team and the ven diagram that we see in hundreds of enterprises we talk to is there's a need for central platform engineering at an enterprise to enable developers, to hit a button, get their database, run an I API line, you know, get their app stack deployed. They also wanna do the same thing with Kubernetes, right? Micro clusters deployed, you know, at a service, same thing with Terraform and Ansible. And they're just there aren't enough skilled operators who have moved up that stack. So you have to automate and canonize that knowledge and, and make it easy. >>Brian, one of the sort of pillars of GreenLake is, and as a service is data and we see a change in the way data is data platforms are being architected, data organizations. And one of the things that is a critical principle of sort of what we see as the new data era is self-service infrastructure where the operation of the technical details are an operational detail, not the be all end, all, you have to go beg and get data out. Okay. So you guys are building out, I think, consistent with that principle self-service infrastructure. That's right. So where does Morpheus fit in, in terms of that objective, what's your relationship like and, and help us understand >>That. Yeah. Within GreenLake, specifically think of this as a broad portfolio of different as a service offerings. Part of that key is meeting customers where they are and where they want to be. So we have that array of things which are fully self-service if you will, but serving an it admin type of persona. So it's where as a enterprise, I still have those resources. I want that granular of control all the way through, how do we deliver some of our more advanced cloud services, really trying to serve the end user to your point, how do I empower application owners, developers to, to bring in and, and work with those services? This is key in, in some of those cloud services, we're delivering more of VSC is a key component that we work as we bring to again, provide those interfaces. How do I provide everything from API CLI through a gooey experience that can span across multiple form factors, bring together that more of a homogenous experience? >>What, what options are out there to solve this problem today? I mean, what are the best practices? Is it do it yourself? Is it, you know, a little bit of VMware here, a little bit of, you know, other tooling there, what, what do you see out there in the marketplace? >>I'll give kinda my perspective kind of yeah. Outside the, the tools that we see when we walk into an enterprise, you've got a company that's got a lot of VMware, maybe a little Nutanix, we've got some AWS, they wanna use OpenShift for their clusters. They got Terraform Ansible, and they got service now. And there's a, there's a poor it ops team in the middle, trying to wire all that together. And each of those domains have tried to go up this hill, right. VMware's done with vRealize automation, you know? Yeah. OpenShift will say no where the way, and you use cube vert to >>Do your virtual service now will say the same thing. Right? >>So our goal is, you know, we started in the middle right. Middle out, right. We started unifying that for self-service for developers and finance teams. And we're we're agnostic. We don't have a dog in the fight, right. We don't have a hypervisor business, a hardware business, an ITSM business. We're all about bringing the pieces together. But that said, we work with partners like HP, you have a footprint of thousands of customers who are solving that same problem and need to need to move up stack. So it's been a good win-win. So >>You're not trying to be the cloud operating system per se. I mean, right. The way, the way a VMware wants to be, or you could even argue, well, I guess open, you >>Got, you got the hyperscalers coming down, you got VMware moving up. But again, they all at the end of the day are trying to control their cash cow, right. Their hardcore business. We wanna make them all transparent. So >>Your bet is it's gonna be all of the above. Yeah. That's not gonna change. Right. That's the complexity is, is that right? Or do you think they're gonna consolidate? >>No, I think there's definitely something to that. I also think there's enough. Disparate. Technology's not gonna be one size fits all or one to rule them all. In fact, I think that's part of the examples in the past, like private cloud is we announced yesterday private cloud for enterprise. It's not a new term. People are doing that for quite a while now, but they are typically fairly brittle hand rolled disparate technologies, some poor it team trying to hold it together. So where we can provide that kind of life cycle management in a cloud operating model, remove that complexity and provide that stability. And in that experience across what will be interchangeable parts at times, I think that's really that direction in, >>Yeah. You guys talk about this whole starting in the middle. I like that because there's a skills gap as well. Right. Not only is there for a challenge on it that transforms, there's not enough. People actually know how to manage a Kubernetes cluster spin one up. Yeah. So there's been a rise of managed services. We're seeing come outta the woodwork almost in all areas where it's complex. Yeah. How does that fit into the makeup of as customers, engineer or rearchitect or, or just evolve to edge on premises and public cloud? Yeah. In a cloud operating way, because if I got managed service, do they just plug in, I mean, new orchestrating services, managed services all the above, take us through this dynamic because we're seeing more and more customers saying, just gimme the service. Yeah. >>I, I know manage perspective. This, this kinda goes back to that portfolio of meeting customers where they are. There are some that, that have that expertise in house they're opinionated. They just want a different consumption model. But on the other side of that, it's difficult to attract and retain that type of talent. And if I have limited resources, am I gonna focus on the care and feeding of that underlying infrastructure? Or am I gonna try to up level and focus on things more strategic to the business? So that's where we've certainly been focusing. And I think this type of management capability is what feeds into that. Right? >>Talk about the trust aspect, because if I'm gonna go manage service, it better work. I need to trust it. It's not a zero trust environment. It's actually a trust and verified, but you're seeing the software supply chain is a big discussion point. Developers don't wanna have to get back off their CDC pipeline to go in and manage stuff. So a managed service has to be verified. Yeah. There's a huge trust factor in there. How does what's the status of this now? Is it real? >>I think one of the, one of the pieces we see in terms of trust organizationally, I mean, people in process is always harder than the tech usually. And, and a lot of the trust is just internal. You get, you know, developers don't trust the ops team, right? Security doesn't trust anybody, you know, finance doesn't trust, you know, who's billing them. Part of what we do as a stack is we give each of those stakeholder groups, the ability to get their core needs met without getting each other's way. And from a delivery perspective where we partner with HPE is we are, you know, we're a platform framework, we're a technology provider we're inside, you know, products like the private cloud. We work their GMs team, the manage services team. If they wanna take on more of that operational concern, right. They use us or if the customer wants to manage it themselves. So we we're all about enabling them at the end of the day. And, and HP brings >>And how hard bread is it to unify? UN unification is a great word. I love let's unify everybody. Right. So how, how hard is that? Can you scope that problem statement for us? What does that mean? >>I'll separate it from a technology perspective and then the people process. So a lot of the traditional people that have played in that space that do it yourself, you mention right. Scripting it all together is hard, right? And if you change from cloud a to cloud B, you're set back six months, like why we exist is we wanna very quickly pull the pieces together. We can usually get a POC up and running in about two hours, right? That's a, self-service VMware private cloud, right? That doesn't mean you've solved the organizational inertia. You know, that's, that takes time, weeks, months. And that's where people are like Accenture GreenLake, other SI other channel partners bring that together to, to help make that change happen. >>How mature is the platform? Where are you in terms of determining product market fit? Are you, are you scaling at this point? >>Well, the, the great part about our origin story, right? We got our start as an internal tool set inside a two and a half billion dollar private equity firm that was transforming it at dozens of companies. So we were built for the use case product market fit happened, cuz a bunch of guys needed to get their jobs done. So we've been an outbound since 2015, right? We were top of the stack ranking, you know, all the MQs, all the quadrants, all the analysis. So we think we're their product market fit. The nice thing is customers have actually moved to where we are. Right? Five years ago, cloud management meant cleaning up the lift and shift mess. Now it's automation platform engineering. So it it's a fun time. >>It's it's operational. Yeah. It's they're operationalizing it. >>What's your go to market model. Maybe you could double click on those through >>Partners. So honestly through HP is a big one. We're small, right? We want to be the best unified platform we can be. Our go to market is via technology partners like HPE, right? The other systems integrators, other channel partners globally. So, so yeah. It's >>So then you've got kind of a tiger team overly. Yep. Salesforce is that, that >>Yeah, we've got teams globally. So we've got about 700,000 workloads under management around the world. About 70% of those are OnPrem VMware Nutanix. The rest are up in the public cloud. So we work with partners, solution providers, services, engines to, to help deliver that to >>Customers. What do you make of the 61 billion acquisition of VMware from Broadcom? >>We're, you know, I think your analysis was spot on. It is gonna be a, a war of, you know, what is the, the most profitable to that new Broadcom business and things like vRealize automation, some of these fringe products that are core at a customer use cases, but may not be driving a lot of bottom revenue for VMware, I think are gonna be gonna be on the bubble. And we've seen more interest in the last few weeks from people who just want to hedge their bets. Right. They want to be able to switch from hypervisor a to hypervisor B or cloud a to cloud B without being locked into anyone's stack. And that is, that is why we exist. Mm. >>You wanna comment on that? >>I mean, it's, you know, for HP and from a GreenLake and even just historically, right. It's about customer choice. Mm. We have a strong relationship with VMware. Sure. We have, I don't know how many bajillions of servers out there running VMware that we, we support with. So, you know, it's, it's, it's all just looking at that ecosystem and helping deliver those customer solutions and outcomes is our focus. Yeah. >>Thank >>You. Brian. Talk about the GreenLake success with partners. We're seeing ecosystem is a big part of that and we know the formula for ecosystems create value. What is the pitch that green lakes making to the marketplace right now to attract more folks to build and or integrate into the >>Platform? Yeah. I mean, GreenLake started with a, a vehicle of how do I start to deliver an OPEX model, a consumption model for traditional infrastructure that we've been providing more and more as the services and solutions really have emerged and evolved. It's gone from, how do I just give you kit and a consumption model for it to now looking at embedded solutions with third party ISV software building or wrapping those services around it, really delivering outcomes and solutions you're seeing. And hopefully you'll solve just from announcement more and more of that, where we have kind of turnkey solutions with key partners, how do we bring a marketplace ecosystem together? How do we help enable those kind of full solutions? Because we're not gonna build it all ourselves, right. We wanna make sure that we can deliver those outcomes. >>So marketing is often and should be ahead of the actual product, early days of GreenLake. It was really a, you know, financial model. Sure. Right. Where do, where do you see GreenLake today? How far is it matured? We saw some of the, the announcements yesterday. We saw some demos. Where are we at? >>Yeah. So this actually, I think really the exciting part is you might have heard Antonio refer to as that journey to one each of our different businesses within green or within HPE, they've all been building these cloud services in GreenLake enabled services. But as you saw Alma share the path to the HPE GreenLake cloud platform that really is bringing these services together into a functional platform, right? Common identity, common telemetry services, bringing these together as now, integrable interoperable services. Like you're starting to see that come together and you can really see the Chrome trail of, of where we're going with a very powerful hybrid cloud experience, right? Spanning private public on-prem colo and a, and a full solution set within there. So it that's, that's the exciting part >>For me and Brad Morpheus will be a capability inside of GreenLake that a customer can consume. Do you have to write to GreenLake APIs to enable that? Or is it, is it more just certify that you work inside a GreenLake? What has to get done? I'll say a lot >>Of what they've done is actually written into, into our APIs. Like we've normalized hybrid it. We have a, a database model of every load balance or a cloud endpoint automation tool. So we are, we're all about making it easier to consume it. And the vision that Alma and HP has around GreenLake fits very well with why we exist. So they're able to extract metering data from our, you know, from our API, we know who provisioned what, where how much they spent. So we're a good repository and platform partner for them to, to build on. It's >>Great for that console that you guys have. Yeah. >>You got the, you got the open APIs, you publish those, you guys take advantage of 'em and then sure. Boom. Then you can consume. Got it. All right, guys. Hey, great to see you again, red. Thanks for, for >>Coming on. Thanks. Thanks for having us on >>Our pleasure. Great stuff. Congratulations. Okay. Keep it right there. This is Dave Valante for John furrier. Are you watching the cubes coverage of HPE discover 2022 from Las Vegas? We'll be right back.

>> TheCUBE presents HPE Discover 2022 brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022. We're here at the Venetian convention center in Las Vegas Dave Vellante for John Furrier. Cam Amirs here is the director of technical alliances at Cribl'. Cam, good to see you. >> Good to see you too. >> Cribl'. Cool name. Tell us about it. >> So let's see. Cribl' has been around now for about five years selling products for the last two years. Fantastic company, lots of growth, started there 2020 and we're roughly 400 employees now. >> And what do you do? Tell us more. >> Yeah, sure. So I run the technical alliances team and what we do is we basically look to build integrations into platforms such as HPE GreenLake and Ezmeral. And we also work with a lot of other companies to help get data from various sources into their destinations or, you know other enrichments of data in that data pipeline. >> You know, you guys have been on theCUBE. Clint's been on many times, Ed Bailey was on our startup showcase. You guys are successful in this overfunded observability space. So, so you guys have a unique approach. Tell us about why you guys are successful in the product and some of the things you've been doing there. >> Yeah, absolutely. So our product is very complimentary to a lot of the technologies that already exist. And I used to joke around that everyone has these like pretty dashboards and reports but they completely glaze over the fact that it's not easy to get the data from those sources to their destinations. So for us, it's this capability with Cribl' Stream to get that data easily and repeatably into these destinations. >> Yeah. You know, Cam, you and I are both at the Snowflake Summit to John's point. They were like a dozen observability companies there. >> Oh yeah. >> And really beginning to be a crowded space. So explain what value you bring to that ecosystem. >> Yeah, sure. So the ecosystem that we see there is there are a lot of people that are kind of sticking to like effectively getting data and showing you dashboards reports about monitoring and things of that sort. For us, the value is how can we help customers kind of accelerate their adoption of these platforms, how to go from like your legacy SIM or your legacy monitoring solution to like the next-gen observability platform or next-gen security platform >> and what you do really well is the integration and bringing those other toolings to, to do that? >> Correct, correct. And we make it repeatable. >> How'd you end up here? >> HP? So we actually had a customer that actually deployed our software on the HPS world platform. And it was kind of a light bulb moment that, okay this is actually a different approach than going to your traditional, you know, AWS, Google, et cetera. So we decided to kind of hunt this down and figure out how we could be a bigger player in this space. >> You saw the data fabric announcement? I'm not crazy about the term, data fabric is an old NetApp term, and then Gartner kind of twisted it. I like data mesh, but anyway, it doesn't matter. We kind of know what it is, but but when you see an announcement like that how do you look at it? You know, what does it mean to to Cribl' and your customers? >> Yeah. So what we've seen is that, so we work with the data fabric team and we're able to kind of route our data to their, as a data lake, so we can actually route the data from, again all these very sources into this data lake and then have it available for whatever customers want to do with it. So one of the big things that I know Clint talks about is we give customers this, we sell choice. So we give them the ability to choose where they want to send their data, whether that's, you know HP's data lake and data fabric or some other object store or some other destination. They have that choice to do so. >> So you're saying that you can stream with any destination the customer wants? What are some examples? What are the popular destinations? >> Yeah so a lot of the popular destinations are your typical object stores. So any of your cloud object stores, whether it be AWS three, Google cloud storage or Azure blob storage. >> Okay. And so, and you can pull data from any source? >> Laughter: I'd be very careful, but absolutely. What we've seen is that a lot of people like to kind of look at traditional data sources like Syslog and they want to get it to us, a next-gen SIM, but to do so it needs to be converted to like a web hook or some sort of API call. And so, or vice versa, they have this brand new Zscaler for example, and they want to get that data into their SIM but there's no way to do it 'cause a SIM only accepts it as a Syslog event. So what we can do is we actually transform the data and make it so that it lands into that SIM in the format that it needs to be and easily make that a repeatable process >> So, okay. So wait, so not as a Syslog event but in whatever format the destination requires? >> Correct, correct. >> Okay. What are the limits on that? I mean, is this- >> Yeah. So what we've seen is that customers will be able to take, for example they'll take this Syslog event, it's unstructured data but they need to put it into say common information model for Splunk or Elastic common schema for Elastic search or just JSON format for Elastic. And so what we can do is we can actually convert those events so that they land in that transformed state, but we can also route a copy of that event in unharmed fashion, to like an S3 bucket for object store for that long term compliance user >> You can route it to any, basically any object store. Is that right? Is that always the sort of target? >> Correct, correct. >> So on the message here at HPE, first of all I'll get to the marketplace point in a second, but it's cloud to edge is kind of their theme. So data streaming sounds expensive. I mean, you know so how do you guys deal with the streaming egress issue? What does that mean to customers? You guys claim that you can save money on that piece. It's a hotly contested discussion point. >> Laughter: So one of the things that we actually just announced in our 350 release yesterday is the capability of getting data from Windows events, or from Windows hosts, I'm sorry. So a product that we also have is called Cribl' Edge. So our capability of being able to collect data from the edge and then transit it out to whether it be an on-prem, or self-hosted deployment of Cribl', or or maybe some sort of other destination object store. What we do is we actually take the data in in transit and reduce the volume of events. So we can do things like remove white space or remove events that are not really needed and compress or optimize that data so that the egress cost to your point are actually lowered. >> And your data reduction approach is, is compression? It's a compression algorithm? >> So it is a combination, yeah, so it's a combination. So there's some people what they'll do is they'll aggregate the events. So sometimes for example, VPC flow logs are very chatty and you don't need to have all those events. So instead you convert those to metrics. So suddenly you reduced those events from, you know high volume events to metrics that are so small and you still get the same value 'cause you still see the trends and everything. And if later on down the road, you need to reinvestigate those events, you can rehydrate that data with Cribl' replay >> And you'll do the streaming in real time, is that right? >> Yeah. >> So Kafka, is that what you would use? Or other tooling? >> Laughter: So we are complimentary to a Kafka deployment. Customer's already deployed and they've invested in Kafka, We can read off of Kafka and feed back into Kafka. >> If not, you can use your tooling? >> If not, we can be replacing that. >> Okay talk about your observations in the multi-cloud hybrid world because hybrid obviously everyone knows it's a steady state now. On public cloud, on premise edge all one thing, cloud operations, DevOps, data as code all the things we talk about. What's the customer view? You guys have a unique position. What's going on in the customer base? How are they looking at hybrid and specifically multi-cloud, is it stitching together multiple hybrids? Or how do you guys work across those landscapes? >> So what we've seen is a lot of customers are in multiple clouds. That's, you know, that's going to happen. But what we've seen is that if they want to egress data from say one cloud to another the way that we've architected our solution is that we have these worker nodes that reside within these hybrid, these other cloud event these other clouds, I should say so that transmitting data, first egress costs are lowered, but being able to have this kind of, easy way to collect the data and also stitch it back together, join it back together, to a single place or single location is one option that we offer customers. Another solution that we've kind of announced recently is Search. So not having to move the data from all these disparate data sources and data lakes and actually just search the data in place. That's another capability that we think is kind of popular in this hybrid approach. >> And talk about now your relationship with HPE you guys obviously had customers that drove you to Greenlake, obviously what's your experience with them and also talk about the marketplace presence. Is that new? How long has that been going on? Have you seen any results? >> Yeah, so we've actually just started our, our journey into this HPE world. So the first thing was obviously the customer's bringing us into this ecosystem and now our capabilities of, I guess getting ready to be on the marketplace. So having a presence on the marketplace has been huge giving us kind of access to just people that don't even know who we are, being that we're, you know a five year old company. So it's really good to have that exposure. >> So you're going to get customers out of this? >> That's the idea. [Laughter] >> Bring in new market, that's the idea of their GreenLake is that partners fill in. What's your impression so far of GreenLake? Because there seems to be great momentum around HP and opening up their channel their sales force, their customer base. >> Yeah. So it's been very beneficial for us, again being a smaller company and we are a channel first company so that obviously helps, you know bring out the word with other channel partners. But HP has been very, you know open arm kind of getting us into the system into the ecosystem and obviously talking, or giving the good word about Cribl' to their customers. >> So, so you'll be monetizing on GreenLake, right? That's the, the goal. >> That's the goal. >> What do you have to do to get into a position? Obviously, you got a relationship you're in the marketplace. Do you have to, you know, write to their API's or do you just have to, is that a checkbox? Describe what you have to do to monetize. >> Sure. So we have to first get validated on the platform. So the validation process validates that we can work on the Ezmeral GreenLake platform. Once that's been completed, then the idea is to have our logo show up on the marketplace. So customers say, Hey, look, I need to have a way to get transit data or do stuff with data specifically around logs, metrics, and traces into my logging solution or my SIM. And then what we do with them on the back end is we'll see this transaction occur right to their API to basically say who this customer is. 'Cause again, the idea is to have almost a zero touch kind of involvement, but we will actually have that information given to us. And then we can actually monetize on top of it. >> And the visualization component will come from the observability vendor. Is that right? Or is that somewhat, do you guys do some of that? >> So the visualization is right now we're basically just the glue that gets the data to the visualization engine. As we kind of grow and progress our search product that's what will probably have more of a visualization component. >> Do you think your customers are going to predominantly use an observability platform for that visualization? I mean, obviously you're going to get there. Are they going to use Grafana? Or some other tool? >> Or yeah, I think a lot of customers, obviously, depending on what data and what they're trying to accomplish they will have that choice now to choose, you know Grafana for their metrics, logs, et cetera or some sort of security product for their security events but same data, two different kind of use cases. And we can help enable that. >> Cam, I want to ask you a question. You mentioned you were at Splunk and Clint, the CEO and co-founder, was at Splunk too. That brings up the question I want to get your perspective on, we're seeing a modern network here with HPE, with Aruba, obviously clouds kind of going next level you got on premises, edge, all one thing, distributed computing basically, cyber security, a data problem that's solved a lot by you guys and people in this business, making sure data available machine learnings are growing and powering AI like you read about. What's changed in this business? Because you know, Splunking logs is kind of old hat you know, and now you got observability. Unification is a big topic. What's changed now? What's different about the market today around data and these platforms and, and tools? What's your perspective on that? >> I think one of the biggest things is people have seen the amount of volume of data that's coming in. When I was at Splunk, when we hit like a one terabyte deal that was a big deal. Now it's kind of standard. You're going to do a terabyte of data per day. So one of the big things I've seen is just the explosion of data growth, but getting value out of that data is very difficult. And that's kind of why we exist because getting all that volume of data is one thing. But being able to actually assert value from it, that's- >> And that's the streaming core product? That's the whole? >> Correct. >> Get data to where it needs to be for whatever application needs whether it's cyber or something else. >> Correct, correct. >> What's the customer uptake? What's the customer base like for you guys now? How many, how many customers you guys have? What are they doing with the data? What are some of the common things you're seeing? >> Yeah. I mean, it's, it's the basic blocking and tackling, we've significantly grown our customer base and they all have the same problem. They come to us and say, look, I just need to get data from here to there. And literally the routing use case is our biggest use case because it's simple and you take someone that's a an expensive engineer and operations engineer instead of having them going and doing the plumbing of data of just getting logs from one source to another, we come in and actually make that a repeatable process and make that easy. And so that's kind of just our very basic value add right from the get go. >> You can automate that, automate that, make it repeatable. Say what's in the name? Where'd the name come from? >> So Cribl', if you look it up, it's actually kind of an old shiv to get to siphon dirt from gold, right? So basically you just, that's kind of what we do. We filter out all the dirt and leave you the gold bits so you can get value. >> It's kind of what we do on theCUBE. >> It's kind of the gold nuggets. Get all these highlights, hitting Twitter, the golden, the gold nuggets. Great to have you on. >> Cam, thanks for, for coming on, explaining that sort of you guys are filling that gap between, Hey all the observability claims, which are all wonderful but then you got to get there. They got to have a route to get there. That's what got to do. Cribl' rhymes with tribble. Dave Vellante for John Furrier covering HPE Discover 2022. You're watching theCUBE. We'll be right back.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Venetian convention center. You're watching the Cube's coverage of HPE discover 2022. The first discover live discover in three years, 2019 was the last one. The cube we were just talking about. This has been at H HP discover. Now HPE since 2011, my co-host John furrier. We're pleased to welcome Phil Maru. Who's the executive vice president and general manager of HPE Aruba. And he's joined by David Hughes, the chief product and technology officer at HPE Aruba gentleman. Welcome to the cube. Good to see you. Thank you. Thank >>You. >>Okay, so you guys talk a lot, Phil, about the intelligent edge. Yep. Okay. What do you, what do you mean by that? >>Yeah, so we, well, we're kind of focused on, is providing technology to customers that sits out at the edge and typically the edge would be, uh, any location out of the data center or out of the cloud. So for the most part, our customers would deploy our technology either in their office premises or maybe retail premises shops, uh, maybe deploying out of the home where their employees are on a factory floor. And we're really talking about technology to connect both people and devices back to, um, systems and technology throughout an organization. So, but >>I, I, you know, sometimes I call it the near edge and the far edge yeah. Near, near edge. Maybe as we saw home Depot up on the stage yesterday far, Edge's like space. Right. You're including all of that. Right. That's >>Edge. >>Yeah. And actually we, we, we, you know, we've got a broad range of technology that actually works within the data center as well. So, you know, what we are focused on is providing, uh, network technology, software and services. And, you know, for the most part, our heritage is at the edge, but it's more pervasive than that. So >>If you have the edge, you got connectivity and power, that's an edge. How much, um, is the physical world being connected now you're seeing robotics automation. Yeah. Ex and with machine learning specifically in compute, really driving a new acceleration at the edge. What you, how do you guys view that? What's your reaction? Yeah. >>I think, look, it, I think as connectivity is improving and that's both in terms of wifi connectivity, so, you know, wifi technology continues to, uh, advance and also you've got this new kind of private 5g area, just generally connectivity is becoming more pervasive and that's helping some industries that haven't previously embraced it. And I think industrial is, is one of the big ones. So, you know, historically it was difficult for kind of car manufacturers to really enable a factory floor. But now the connectivity is connectivity is better. That gives them the opportunity to be able to really change how they do things. So >>David, if you do take an outside in view, mm-hmm <affirmative>, uh, and, and, and when you talk to customers, what are they telling you and how is that informing your product strategy? >>Yeah, well, you >>Know, I think there's, there's several themes we hear. One is, you know, it's really important, better work from anywhere they wanna enable their employees, um, to get the same experience, whether they're at home or on the road or in their branch office or at headquarters. Um, you know, people are also concerned that as they deploy, deploy all of this IOT and pursuit of digital transformation, they don't want those devices to be a weak point where someone breaks into one device and moves naturally, um, across the network. So they want to have this great experience for their customers and their users, but they wanna make sure that they're not compromising security, um, in any way. And so it's about getting that balance between ease of use and, and security. That's one of the primary things we hear, >>You know, Dave, one of the things we talked about many, many years ago was when hybrid and was starting to come out multi-cloud was on the, on the table early on. Uh, we were, we were saying, Hey, the data center is just a big edge, right? I mean, if you have cloud operations and you see what's going on with GreenLake here now, the momentum hybrid cloud is cloud operations, right? An edge off data centers to a big edge on premises. And you got the edge as you have cloud operations, like say GreenLake, plugging in partners and diverse environments. You're connecting, not just branch offices that are per perimeter based. You have no perimeter and you have now other companies connecting mm-hmm <affirmative> so you got data and you got network. How do you guys see that transition as GreenLake has a very big ecosystem part of it, partners and whatnot. >>Yeah. So, you know, I think for us, um, the ecosystem of partners that we have is critical in terms of delivering what our customers need. And, you know, I think one of the really important areas is around verticals. So, um, you know, when you think about different verticals, they have similar problems, but you need to tailor the solutions. Um, to each of those, you know, we are talking a bit about devices and people. When you look at say a healthcare environment, there can be 30 devices there for each patient. And, um, so there's connecting all those devices securely, but we have partners that will help pull all of that together that may be focused on, um, you know, medical environment that may focused on stadiums. They may be focused on industrial. Um, so having partners that understand those verticals and working closely with them to deliver solutions is important in our go to market. >>So another kind of product question and related to what you just said, David, I got connectivity, speed, reliability, cost security, or maybe a missing something. But you, you said earlier, you gonna gotta balance those. How do you do that? And do you do that for the specific use cases? Like for instance, you just mentioned stadiums and 81 and how do you balance those and, and do you tailor those for the use cases? >>Yeah, well, I think it depends on the customer and different people have different views about where they need to be. So some people are, are so afraid about security. They wanna be air gapped and completely separate than the internet. That would be one extreme mm-hmm <affirmative> other people, you know, look at it and see what's happening with COVID with everyone working from home with people being able to work from Starbucks or the airport. And they're beginning to think, well, why is the branch that much different? And so what I think we are seeing is, you know, a reevaluation of how people connect to, um, the apps they're using and, uh, you know, you, you, you've probably for sure heard people talking about zero trust, talking about micro segmentation. You know, I think what we we see is that people wanna be able to build a network in a way where rather than any device being able to talk to any device or any person, which is where the internet started, we wanna build to build networks where people or devices can only talk to the destinations that are necessary for them to do their job. >>And so a lot of the technology that we are building into the network is really about making security intrinsic by limiting what can talk to what that's >>Actually micro, micro segmentations, zero trust, um, these all point to a modern, the modern network, as you say, Antonio Neri was just on the cube, talking about programmability, substrate, the words like that come to mind, what is the modern network look like? I mean, you have to be agile. You have to be programmable. You have to have security. Can you describe in your words, what does the modern network these days need to look like? How should customers think about architecting them? What are some of the table stakes and what are some of the differentiators that customers need to do to have a modern network? >>Yeah, well, you covered off a coup a few quarter, one there with clarity and so on. So let me pick one that you didn't mention. And, and I, you know, I think we are seeing, you know, a lot of interest around network as a service. And, you know, when we think about network as a service, we think about it broadly, um, you know, for consumers, we're getting more and more used to buying things as a service versus buying a thing. When you, when you get Alexa, you care about how well she answers your questions, you don't care about what CPU is or how much Ram Alexa has. And likewise with networking, people are caring about the outcomes of keeping their employees connected, keeping their, their devices and systems running. And so what for us, what NASA is all about is that shift of thinking about a network as being a collection of devices that get managed to being a framework for connectivity and running it from the point of view of those outcomes. >>And so whether, you know, it's about CapEx versus OPEX or about do it yourself, managing the network yourself versus outsourcing that, um, or it's about the, you know, Greenfield versus brownfield, each of our customers has got a different starting point, but they're all getting heading towards this destination of being able to treat their network as a service. And so that is, you know, a key area of innovation for us and whether it's big customers like home Depot that you heard about yesterday, um, where we kind of manage everything for them on a, as on a store basis, um, for connectivity, um, or, you know, the recent, um, skew based nest that we launched, which is a really scalable foundation for our partners to build nest offerings around. Um, we see this as a key part of network modernization. Yeah. >>And one of the things, again, that's great stuff. Uh, infrastructure is code, which was really kind of pioneer the DevOps movement in cloud kind of as platform level. And you got data ops now and AI at the top of the stack, we were always wondering when network as code was gonna come, uh, and where you actually have it, where it's programmable. I mean, we all know what policies do do. They're good. That's all great network as code. >>Yeah. >>And that's the concept that's like DevOps, it's like, make it work just seamlessly, just be always on. And >>Yeah. And smart, you know, people are always looking for the, for the easy button. Um, and so they want, they want things to operate easily. They want it to be easy to manage. And, you know, I actually think there's a little bit of a, um, a conflict between networkers code and the easy button, right? So it depends on the class of customers. Some customers like financials, for instance, have a huge software development organizations that are extremely capable that could, that can go with program ability that want things as code. But the majority of the, of, of the verticals that we deal with, um, don't have those big captive software organizations. And so they're really looking for automation and simplicity and they wanna outsource that problem. So in Aruba central, we have invested a lot to make it really easy for our customers to, um, get what they need, you know, is that movement of zero code. It's more like zero code. They want, they want something packaged now >>The headless networks. Yeah. Low code, no code >>Kind of thing. Yeah, that's right. And, you know, obviously for people that have the sophistication that want to, um, do the most advanced things, we have APIs. And so we support that kind of programmable way of doing things. But I'd say that that's that's, those are more specialized customers. So >>Phil, yeah. Uh, is that the strategy? I mean, David listed off a number of, of factors here is that Aruba's strategy to modernize networks to actually create the easy button through network as a service is as simple as dial tone. Is that how we >>Should think? I mean, the way I think about the strategy is I think about it as a triangle, really, along the bottom, we've got the products and services that we offer and we continue to add more products and services. We either buy companies such as silver peak a couple of years ago, or we build, uh, additional products and by, and by the way, that's in response to customers who are frustrated with some other suppliers and wanna move on mass over to, uh, companies like ourselves. So at the bottom layer of the product and services, and then the other side of the triangle one would be NAS, which we talked about, which is kind of move to buying network and as a service. And then the other side of the triangle is the platform, which for us is river central, which is part of HP GreenLake. And that's really all about, you know, kind of making it easy for customers to manage networks and Aruba central right now has got about 120,000 live customers on it. It connects to about 2 million devices and it's collecting a lot of data as well. So we anonymously collect data from all of our customers. We've got one and a half billion data points in the platform. And what we do is we let that data kind of look for anomalies and spot problems on the network before they happen for customers. >>So Aruba central predated, uh, uh, GreenLake GreenLake. Yeah. And, and so did you write to GreenLake through GreenLake APIs? How, what was the engineering work to accomplish that? >>Yeah, so really, um, Aruba central is kind of the Genesis of the GreenLake platform. So we took Aruba central and made it more generic okay. To build the GreenLake cloud platform. And you know, what we've done very recently is bring, bring Aruba into that unified infrastructure, along with storage and compute. So the same sign-on applies across all of HP's, um, products, the same way of managing licenses, managing devices. And so it provides us, uh, great foundation going forwards to, um, solve more comprehensively. Our customers automation requires. >>So, so just a quick follow. So Aruba actually was the main spring of GreenLake from the standpoint of okay. Sing, like you said, single sign on a platform that could evolve and become more, more generic. Yes. So, okay. So that was a nice little, um, bonus of the acquisition, you know, it's now the whole company >><laugh> Aruba taking over. >>Yeah. There's been a lot of work to, to, uh, you know, make it generic and, and widely applicable. Right. Yeah. Um, so, but >>You were purpose >>Built for yeah. Well it's foundational. Yes. So foundational for GreenLake, they built on top of it. Yeah. So you mentioned the data points, billions of data points. So I gotta ask you, cuz we're seeing this, um, copy more and more with machine learning, driving a lot of acceleration, cuz you can do simulations with machine learning and compute. We had Neil McDonal done earlier. He's a compute guy, you got networking. So with all this, um, these services and devices being put on and off the network humans, can't actually figure this out. You can discover what's on the network. How are you guys viewing the discovery and monitoring because there's no perimeter okay. On the network anymore. So I want to know what's out there. Um, how do you get through it? How does machine learning and AI play into this? >>Yeah. I mean, what we are trying to do is obviously flag trends for customers and say, Hey look, you know, we can either see something happening with your network. So there's a particular issue over here and we need to, I dunno, free up more capacity to solve that. Or we're looking at how their network is running and then comparing that with anonymized data from all of our other customers as well. So we're just helping find those problems. But yeah, you're right. I mean, I think it is becoming more of an issue for organizations, you know, how do you manage the network, >>But you see machine learning and AI playing a big part. >>Yeah, yeah. Yeah. I think, uh, AI massively and, and other technology advances as well that we make. So recently we, uh, also announced the availability of location awareness within our access points. And that might sound like a simple thing. But when network, when companies build out their networks, they often lose or they potentially could lose the records as to, well, where were the access points that we laid out and actually where are they not within, you know, 20 feet, but where actually are they? So we introduced kind of location, finding technology as well into our, uh, access points to make it easy for >>Customers. So Aruba one of the best, if not the best acquisition. I think that HP E has made, um, it's made by three par was, you know, good. It saved the storage business. Okay. That was more of a defensive play. Uh, but to see Aruba, it's a growth business. You guys report on it every quarter. Yeah. It's obviously a key ingredient to enable uh, uh, GreenLake and, and a that's another example, nimble was similar. We're much smaller sort of more narrow, but taking the AI ops piece and bringing it over. So it's, it was great to see HPE executing on some of its M and a as opposed to just leaving them alone and not really leveraging 'em. So guys, yeah. Congratulations really appreciate you guys coming on and explaining that. Congratulations on all the, all the great work and thanks for coming on the cube. Okay. >>Thank you guys. Yeah. Thanks for having us. >>All right, John, and I'll be back right after this short break. You're watching the cube, the leader in enterprise tech coverage from HPE Las Vegas, 2022. We'll be right back.

>>Welcome back to the cubes coverage of Veeam on 2022 at the RS. Nice to be at the aria. My co-host Dave Nicholson here. We spend a lot of time at the Venetian convention center, formerly the sand. So it's nice to have a more intimate venue. I really like it here. George Burg is joining us. He's the vice president of data protection at vast data, a company that some of you may not know about. George. >>Welcome a pleasure. Thank you so much for having me. >>So VAs is smoking hot, raised a ton of dough. You've got great founders, hard charging, interesting tech. We've covered a little bit on the Wikibon research side, but give us the overview of the company. Yeah, >>If I could please. So we're here at the, you know, the Veeam show and, you know, the theme is modern data protection, and I don't think there's any company that epitomizes modern data protection more than vast data. The fact that we're able to do an all flash system at exabyte scale, but the economics of cloud object based deep, cheap, and deep archive type solutions and an extremely resilient platform is really game changing for the marketplace. So, and quite frankly, a marketplace from a data protection target space that I think is, is ripe for change and in need of change based on the things that are going on in the marketplace today. >>Yeah. So a lot of what you said is gonna be surprising to people, wait a minute, you're talking about data protection and all flash sure. I thought you'd use cheap and deep disc or, you know, even tape for that or, you know, spin it up in the cloud in a, in a deep archive or a glacier. Explain your approach in, in architecture. Yeah. At a >>High level. Yeah. So great question. We get that question every day and got it in the booth yesterday, probably about 40 or 50 times. How could it be all flash that at an economic point that is the fitting that of, you know, data protection. Yeah. >>What is this Ferrari minivan of which you speak? >>Yeah, yeah, yeah. The minivan that goes 180 miles an hour, right. That, you know, it's, it's really all about the architecture, right? The component tree is, is somewhat similar to what you'll see in other devices. However, it's how we're leveraging them in the architecture and design, you know, from our founders years ago and building a solution that just not, was not available in the marketplace. So yeah, sure. We're using, you know, all flash QLC drives, but the technology, you know, the advanced next generation algorithms or erasure coding or rage striping allows us to be extremely efficient. We also have some technologies around what we call similarity, some advanced data reduction. So you need less, less capacity if you will, with a vast system. So that obviously help obviously helps us out tremendously with their economics. But the other thing is I could sell a customer exactly what they need. If you think about the legacy data protection market purpose built back of appliances, for example, you know, ALA, Adele, Aita, and HP, you know, they're selling systems that are somewhat rigid. There's always a controller in a capacity. It's tied to a model number right. Soon as you need more performance, you buy another, as soon as you need more capacity, you buy another, it's really not modular in any way. It's great >>Model. If you want to just keep, keep billing the >>Customer. Yeah. If, if that, if yeah. And, and I, I think, I think at this point, the purpose, you know, Dave, the purpose built backup appliance market is, is hungry for a change. Right. You know, there's, there's not anyone that has one. It doesn't exist. I'm not just talking about having two because of replication. I'm it's because of organic growth. Ransomware needs to have a second unit, a second copy. And just, and just scalability. Well, you >>Guys saw that fatigue with that model of, oh, you need more buy more, >>Right? Oh, without a doubt, you said we're gonna attack that. Yeah. Yeah. Sorry. No, no, no. That's great. Without a doubt. So, so we can configure a solution exactly. To the need. Cause let's face it. Every single data center, every single vertical market, it's a work of art. You know, everyone's retention policies are different. Everyone's compliance needs are different. There might be some things that are self mandated or government mandated and they're all gonna be somewhat different. Right? The fact of the matter is the way that our, our architecture works, disaggregated shared everything. Architecture is different because when we go back to those model numbers and there's more rigid purpose built back of appliances, or, or maybe a raise designed specifically for data protection, they don't offer that flexibility. And, you know, I, I, I think our, our, our, our entry point is sized to exactly what the need is. Our ease of scalability. You need more performance. We just add another compute, another compute box, what we call our C box. If you need more capacity, we just add another data box, a D box, you know, where the data resides. And, you know, I, you know, especially here at Veeam, I think customers are really clamoring for that next generation solution. They love the idea that there's a low point of entry, but they also love the idea that, that it's easy to scale on demand, you know, as, as needed and as needed basis. >>So just, I wanna be just, I want to go down another layer on that architecturally. Cause I think it's important for people to understand. Sure, exactly what you're saying. When you're talking about scaling, there's this concept of the, of the sort of devil's triangle, the tyranny of this combination of memory, CPU and storage. Sure. And if you're too rigid, like in an appliance, you end up paying for things you don't need. Correct. When all I need is a little more capacity. Correct. All I need is a little more horsepower. Well, you wanna horsepower? No, you gotta buy a bunch of capacity. Exactly. Oh, need capacity. No, no. You need to buy expensive CPUs and suck a bunch of power. All I need is capacity. So what, so go through that, just a little more detail in terms of sure. How you cobble these systems together. Sure. My, the way my brain works, it's always about Legos. So feel free to use Legos. >>Yeah. We, so, so with our disaggregated solution, right. We've separated basically hardware from software. Right. So, so, so that's a good thing, right? From an economic standpoint, but also a design and architecture standpoint, but also an underlining underpinning of that solution is we've also separated the capacity from the performance. And as you just mentioned, those are typically relatively speaking for every other solution on the planet. Those are tied together. Right? Right. So we've disaggregated that as well within our architecture. So we, we again have basically three tier, tier's not the right word, three components that build out a vast cluster. And again, we don't sell like a solution designed by a model number. And that's typically our C boxes connected via NVMe over fabric to a D box C is all the performance D is all the capacity because they're modular. You can end up like our, our baseline product would start out as a one by one, one C box one D box, right? >>Connected again, via different, different size and Vme fabrics. And that could scale to hundreds. When we do have customers with dozens of C boxes, meeting high performance requirements, keep in mind when, when vast data came to market, our founders brought it to the market for high performance computing machine learning, AI data protection was an afterthought, but those found, you know, foundational things that we're able to build in that modularity with performance at scale, it behooves itself, it's perfect fit for data protection. So we see in clients today, just yesterday, two clients standing next to each other in the same market in the same vertical. I have a 30 day retention. I have a 90 day retention. I have to keep one year worth of full backups. I have to keep seven years worth of full backups. We can accommodate both and size it to exactly what the need is. >>Now, the moment that they need one more terabyte, we license into 100 terabyte increments so they can actually buy it in a sense, almost in arrears, we don't turn it off. We don't, there's not a hard cat. They have access to that capacity within the solution that they provide and they can have access immediate access. And without going through, let's face it. A lot of the other companies that we're both thinking of that have those traditional again, purpose-built solutions or arrays. They want you to buy everything up front in advance, signing license agreements. We're the exact opposite. We want you to buy for the need as, and as needed basis. And also because the fact that we're, multi-protocol multi-use case, you see people doing many things within even a single vast cluster. >>I, I wanna come back to the architecture if I, I can and just understand it better. And I said, David, Flo's written a lot about this on our site, but I've had three key meetings in my life with Mosia and I, and I you've obviously know the first week you showed up in my offices at IDC in the late 1980s said, tell me everything, you know about the IBM mainframe IO subsystem. I'm like, oh, this is gonna be a short meeting. And then they came back a year later and showed us symmetric. I was like, wow, that's pretty impressive. The second one was, I gave a speech at 43 south of 42 south. He came up and gave me a big hug. I'm like, wow. He knows me. And the third one, he was in my offices at, in Mabo several years ago. And we were arguing about the flash versus spinning disc. And he's like, I can outperform an all flash array because we've tuned our algorithms for spinning disc. Everybody else is missing that. You're basically saying the opposite. Correct. We've turned tuned our algorithms to, for QC David Flos says Dave, there's a lot of ways to skin a cat in this technology industry. So I wanted to make sure I got that right. Basically you're skinning the cat with different >>Approach. Yeah. We've also changed really the approach of backup. I mean, the, the term backup is really legacy. I mean, that's 10, 12 years of our recovery. The, the story today is really about, about restore resiliency and recovery. So when you think about those legacy solutions, right, they were built to ingest fast, right? We wanna move the data off our primary systems, our, our primary applications and we needed to fit within a backup window. Restore was an afterthought. Restore was, I might occasionally need to restore something. Something got lost, something got re corrupted. I have to restore something today with the, you know, let's face it, the digital pandemic of, of, of cyber threats and, and ransomware it's about sometimes restoring everything. So if you look at a legacy system, they ingest, I'm sorry. They, they, they write very fast. They, they, they can bring the data in very quickly, but their restore time is typically about 20 to 25%. >>So their reading at only 20, 25% of their right speed, you know, is their rate speed. We flip the script on that. We actually read eight times faster than we write. So I could size again to the performance that you need. If you need 40 terabytes, an hour 50 terabytes an hour, we can do that. But those systems that write at 40 terabytes an hour are restoring at only eight. We're writing at a similarly size system, which actually comes out about 51 terabytes an hour 54 terabytes. We're restoring at 432 terabytes an hour. So we've broken the mold of data protection targets. We're no longer the bottleneck. We're no longer part of your recovery plan going to be the issue right now, you gotta start thinking about network connectivity. Do I have, you know, you know, with the, with our Veeam partners, do we have the right data movers, whether virtual or physical, where am I gonna put the data? >>We've really helped customer aided customers to rethinking their whole Dr. Plan, cuz let's face it. When, when ransomware occurs, you might not be able to get in the building, your phones don't work. Who do you call right? By the time you get that all figured out and you get to the point where you're start, you want to start recovering data. If I could recover 50 times faster than a purpose built backup appliance. Right? Think about it. Is it one day or is it 50 days? Am I gonna be back online? Is it one hour? Is it 50 hours? How many millions of dollars, tens of thousands of dollars were like, will that cost us? And that's why our architecture though our thought process and how the system was designed lends itself. So well for the requirements of today, data protection, not backup it's about data protection. >>Can you give us a sense as to how much of your business momentum is from data protection? >>Yeah, sure. So I joined VAs as we were talking chatting before I come on about six months ago. And it's funny, we had a lot of vast customers on their own because they wanted to leverage the platform and they saw the power of VAs. They started doing that. And then as our founders, you know, decided to lean in heavily into this marketplace with investments, not just in people, but also in technology and research and development, and also partnering with the likes of, of Veeam. We, we don't have a data mover, right. We, we require a data mover to bring us the data we've leaned in tremendously. Last quarter was really our, probably our first quarter where we had a lot of marketing and momentum around data protection. We sold five X last quarter than we did all of last year. So right now the momentum's great pipeline looks phenomenal and you know, we're gonna continue to lean in here. >>Describe the relationship with Veeam, like kind of, sort of started recently. It sounds like as customer demand. Yeah. But what's that like, what are you guys doing in terms of engineering integration go to market? >>Yeah. So, so we've gone through all the traditional, you know, verifications and certifications and, and, and I'm proud to say that we kind of blew the, the, the roof off the requirements of a Veeam environ. Remember Veeam was very innovative. 10, 12 years ago, they were putting flash in servers because they, they, they want a high performing environment, a feature such as instant recovery. We've now enabled. When I talked about all those things about re about restore. We had customers yesterday come to us that have tens of thousands of VMs. Imagine that I can spin them up instantaneously and run Veeam's instant recovery solution. While then in the background, restoring those items that is powerful and you need a very fast high performance system to enable that instant. Recovery's not new. It's been in the market for very long, but you can ask nine outta 10 customers walk in the floor. >>They're not able to leverage that today in the systems that they have, or it's over architected and very expensive and somewhat cost prohibitive. So our relationship with Veeam is really skyrocketing actually, as part of that, that success and our, our last quarter, we did seven figure deals here in the United States. We've done deals in Australia. We were chatting. I, I, I happened to be in Dubai and we did a deal there with the government there. So, you know, there's no, there's no specific vertical market. They're all different. You know, it's, it's really driven by, you know, they have a great, you know, cyber resilient message. I mean, you get seen by the last couple of days today and they just want that power that vast. Now there are other systems in the marketplace today that leverage all flash, but they don't have the economic solution that we have. >>No, your, your design anticipated the era that we're we're in right now from it, it anticipated the ability to scale in, to scale, you know, in >>A variety. Well, listen, anticipation of course, co coincidental architecture. It's a fantastic fit either way, either way. I mean, it's a fantastic fit for today. And that's the conversations that we're having with, with all the customers here, it's really all about resiliency. And they know, I mean, one of the sessions, I think it was mentioned 82 or 84% of, of all clients interviewed don't believe that they can do a restore after a cyber attack or it'll cost them millions of dollars. So that there's a tremendous amount of risk there. So time is, is, is ultimately equals dollars. So we see a, a big uptick there, but we're, we're actually continuing our validation work and testing with Veeam. They've been very receptive, very receptive globally. Veeam's channel has also been very receptive globally because you know, their customers are, you know, hungry for innovation as well. And I really strongly believe ASBO brings that >>George, we gotta go, but thank you. Congratulations. Pleasure on the momentum. Say hi to Jeff for us. >>We'll we'll do so, you know, and we'll, can I leave you with one last thought? Yeah, >>Please do give us your final thought. >>If I could, in closing, I think it's pretty important when, when customers are, are evaluating vast, if I could give them three data points, 100% of customers that Triva test vast POC, vast BVAs 100% Gartner peer insights recently did a survey. You know, they, they do it with our, you know, blind survey, dozens of vast customers and never happened before where 100% of the respondents said, yes, I would recommend VA and I will buy VAs again. It was more >>Than two respondents. >>It was more, it was dozens. They won't do it. If it's not dozens, it's dozens. It's not dozen this >>Check >>In and last but not. And, and last but not least our customers are, are speaking with their wallet. And the fact of the matter is for every customer that spends a dollar with vast within a year, they spend three more. So, I mean, if there's no better endorsement, if you have a customer base, a client base that are coming back and looking for more use cases, not just data protection, but again, high performance computing machine learning AI for a company like VA data. >>Awesome. And a lot of investment in engineering, more investment in engineering than marketing. How do I know? Because your capacity nodes, aren't the C nodes. They're the D nodes somehow. So the engineers obviously won that naming. >>They'll always win that one and we, and we, and we let them, we need them. Thank you. So that awesome product >>Sales, it's the golden rule. All right. Thank you, George. Keep it right there. VEON 20, 22, you're watching the cube, Uber, Uber right back.