(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 HPE discover 2022 brought to you by HPE. >>Welcome back to the Cube's coverage. We're wrapping up day two, John furrier and Dave ante. We got some friends and colleagues, longtime friends, Crawford Del Pret is the president of IDC. Matt Eastwood is the senior vice president of infrastructure and cloud guys. Thanks for coming on spending time. Great to you guys. >>That's fun to do it. Awesome. >>Cravin I want to ask you, I, I think this correct me if I'm wrong, but this was your first physical directions as, as president. Is that true or did you do one in 2019? >>Uh, no, we did one in 20. We did, we did one in 20. I was president at the time and then, and then everything started, >>Well, how was directions this year? You must have been stoked to get back together. Yeah, >>It was great. I mean, it was actually pretty emotional, you know, it's, it's a community, right? I mean, we have a lot of customers that have been coming to that event for a long, long time and to stand up on the stage and look out and see people, you know, getting a little bit emotional and a lot of hugs and a lot of bringing people together. And this year in Boston, we were the first event really of any size that kind of came back. And when I kind of didn't see that coming in terms of how people, how ready people were to be together. Cause >>When did you did it April >>In Boston? Yeah, we did it March in March. Yeah, it was, it was, it was, it was a game day decision. I mean, we were, we had negotiated it, we were going back and forth and then I kind of made the call at the last minute, say, let's go and do it. And in Santa Clara, I felt like we were kind of opening up the crypt at the convention center. I mean, all the production people said, you know what? You guys were really the first event to be back. And attendance was really strong. You know, we, we, we got over a thousand. It was, it was really good. >>Good. It's always a fun when I was there. It was, it's a big deal. You guys prepare for it. Yeah. Some new faces up on the stage. Yeah. So, so Matt, um, you've been doing the circuit. I take it like, like all top analysts, super busy. Right. This is kind of end of the spring. I mean, I know it's summer, right. That's right. But, um, how do you look at, at discover relative some, some of the other events you've been at? >>So I think if you go back to what Crawford was just talking about our event in March, I mean, March was sort of the, the reopening and there was, I think people just felt so happy to be, to be back out there. You still get a little bit at, at these events. I mean, cuz for each, each company it's their first time back at it, but I think we're starting to get down what these events are gonna feel like going forward. Um, and it, I mean, there's good energy here. There's been a good attendance. I think the, the interest in getting back live and having face to face meetings is clearly strong. >>Yeah. I mean, this definitely shows that hybrids, the steady state, both events cloud. Yeah. Virtualization remotes. So what are you guys seeing with that hybrid mode? Just from a workforce, certainly people excited to get back together, but it's gonna continue. You're starting to see that digital piece. How is that impacting some of the, some of the customers you're tracking, who's winning and who's losing, coming out of the pandemic. What's the big picture look like? >>Yeah. I mean, if you, if you take a look at hybrid work, um, people are testing many, many, many different models. And I think as we move from a pandemic to an em, we're gonna have just waves and waves and waves of people needing that flexibility for a lot of different reasons, whether they have, uh, you know, preexisting conditions, whether they're just not comfortable, whether they have people who can't be vaccinated at home. So I think we're gonna be in this hybrid work for a long, long time. I do think though that we are gonna transition back into some kind of a normal, um, and I, and I think the big difference is that I think leaders back in the day, a long time ago, when people weren't coming into work, it was kind of like, oh, I know nothing's going on there. People aren't getting worked. And I think we're over that stage. Yeah. I think we're now into a stage where we know people can be productive. We know people can effectively work from home and now we're into the reason to be in the office. And the reason to be in the office is that collaboration, it's that mentoring it's that, you know, think about your 25 year old self. Do you wanna be staring at a windshield all day long and not kind of building those relationships? People want face to face, it's difficult. They want face >>To face and I would, and you guys had a great culture and it's a young culture. How are you handling it as an executive in terms of, is there a policy for hybrid or >>Yeah, so, so, so at IDC, what we did is we're in a pilot period and we've kind of said that the summertime is gonna be a pilot period and we've asked people, we're actually serving shocker, we're >>Serving, >>But we're, but we're, but, but we're actually asking people to work with their manager on what works for them. And then we'll come up with, you know, whether you are in, out of the office worker, which will be less than two days a hybrid worker, which will be three days or, uh, in, in the office, which is more than three days a week. And you know, we all know there's, there's, there's limitation, there's, there's, there's variability in that, but that's kind of what we're shooting for. And we'd like to be able to have that in place in the fall. >>Are you pretty much there? >>Yeah, I am. I, I am there three days a week. I I, Mondays and Fridays, unless, >>Because you got the CEO radius, right? Yeah. >><laugh>, <laugh> >>The same way I'm in the office, the smaller, smaller office. But so, uh, let's talk a little bit about the, the numbers we were chatting earlier, trying to squint through you guys are, you know, obviously the gold standard for what the market does, what happened in, you know, during the pandemic, what happened in 2021 and what do you expect to happen in, in 2022 in terms of it spending growth? >>Yeah. So this is, this is a crazy time, right? We've never seen this. You and I have a long history of, uh, of tracking this. So we saw in, in, in, in 2020, the market decelerated dramatically, um, the GDP went down to a negative like it always does in these cases, it was, you know, probably negative six in that, in that, in that kind of range for the first time, since I've been tracking it, which goes back over 30 years, tech didn't go negative tech went to about just under 3%. And then as we went to 2021, we saw, you know, everything kind of snap back, we saw tech go up to about 11% growth. And then of course we saw, you know, GDP come back to about a 4%, you know, ki kind of range growth. Now what's I think the story there is that companies and you saw this anecdotally everywhere companies leaned into tech, uh, company. >>You know, I think, you know, Matt, you have a great statistic that, you know, 80% of companies used COVID as their point to pivot into digital transformation, right. And to invest in a different way. And so what we saw now is that tech is now where I think companies need to focus. They need to invest in tech. They need to make people more productive with tech and it played out in the numbers now. So this year what's fascinating is we're looking at two Fastly different markets. We've got gasoline at $7 a gallon. We've got that affecting food prices. Uh, interesting fun fact recently it now costs over $1,000 to fill an 18 Wheeler. All right. Based on, I mean this just kind of can't continue. So you think about it, don't put the boat >>In the wall. Yeah. Yeah. >>Good, good, good, good luck. It's good. Yeah, exactly. <laugh> so a family has kind of this bag of money, right? And that bag of money goes up by maybe three, 4% every year, depending upon earnings. So that is sort of sloshing around. So if food and fuel and rent is taking up more gadgets and consumer tech are not, you know, you're gonna use that iPhone a little longer. You're gonna use that Android phone a little longer. You're gonna use that TV a little longer. So consumer tech is getting crushed, you know, really it's very, very, and you saw it immediately and ad spending, you've seen it in meta. You've seen it in Facebook. Consumer tech is doing very, very it's tough enterprise tech. We haven't been in the office for two and a half years. We haven't upgraded whether that be campus wifi, whether that be, uh, servers, whether that be, uh, commercial PCs, as much as we would have. So enterprise tech, we're seeing double digit order rates. We're seeing strong, strong demand. Um, we have combined that with a component shortage and you're seeing some enterprise companies with a quarter of backlog. I mean, that's, you know, really unheard at higher >>Prices, which >>Also, and therefore that drives that >>Drives. It shouldn't be that way. If there's a shortage of chips, it shouldn't be that way, >>But it is, but it is, but it is. And then you look at software and we saw this, you know, we've seen this in previous cycles, but we really saw it in the COVID downturn where, uh, in software, the stickiness of SaaS means that you just, you're not gonna take that stuff out. So the, the second half of last year we saw double digit rates in software surprise. We're seeing high single digit revenue growth in software now, so that we think is gonna sustain, which means that overall it demand. We expect to be between five and 6% this year. Okay, fine. We have a war going on. We have, you know, potentially, uh, a recession. We think if we do, it'll be with a lower case, R maybe you see a banded down to maybe 4% growth, but it's gonna grow this. >>Is it, is it both the structural change of the disruption of COVID plus the digital transformation yeah. Together? Or is it, >>I, I think you make a great point. Um, I, I, I think that we are entering a new era for tech. I think that, you know, Andrew's famous wall street journal oped 10 years ago, software is even world was absolutely correct. And now we're finding that software is, is eing into every nook and cranny people have to invest. They, they know disruptors are coming around every single corner. And if I'm not leaning into digital transformation, I'm dead. So >>The number of players in tech is, is growing, >>Cuz there's well, the number of players in tech number >>Industry's coming >>In. Yeah. The industry's coming in. So I think the interesting dynamic you're gonna see there is now we have high interest rates. Yeah. Which means that the price of funding these companies and buying them and putting data on is gonna get higher and higher, which means that I think you could, you could see another wave of consolidation. Mm-hmm <affirmative> because tech large install based tech companies are saying, oh, you know what? I like that now >>4 0 9 S are being reset too. That's another point. >>Yeah. I mean, so if you think about this, this transformation, right. So it's all about apps, absent data and differentiating and absent data. What the, the big winner the last couple years was cloud. And I would just say that if this is the first potential recession that we're talking about, where the cloud service providers. So I think a cloud as an operating model, not necessarily a destination, but for these cloud service providers, they've actually never experienced a slowdown. So how, and, and if you think about the numbers, 30% of, of the typical it budget is now quote, unquote cloud and 30% of all expenditures are it related. So there's a lot of exposure there. And I think you're gonna see a lot of, a lot of focus on how we can rationalize some of those investments. >>Well, that's a great point. I want to just double click on that. So yeah, the cloud did well during the pandemic. We saw that with SAS, have you guys tracked like the Tams of what got pulled forward? So the bit, a big discussion about something that pulled forward because of the pandemic, um, like zoom, for instance, obviously everyone's using zoom. Yeah, yeah, yeah. Was there fake Tams? There was one, uh, couple analysts who were pointing out that some companies were hot during the pandemic will go away that that Tam doesn't really exist, but there's some that got pulled forward early. That's where the growth is. So is there a, is there a line between the, I call fake Tam or pulled forward TA that was only for the pandemic situationally, um, devices might be like virtual event, virtual event. Software was one, I know Hoppin got laid a lot of layoffs. And so that was kind of gone coming, coming and going. And you got SAS which got pulled forward. Yep. And it's not going away, but it's >>Sustaining. Yeah. Yeah. But it's, but, but it's sustaining, um, you know, I definitely think there was a, there was a lot of spending that absolutely got pulled forward. And I think it's really about CEO's ability to control expectations and to kind of message what it, what it looks like. Um, you know, I think I look, I, I, I think virtual event platforms probably have a role. I think you can, you can definitely, you know, raise your margins in the event, business, significantly using those platforms. There's a role for them. But if you were out there thinking that this thing was gonna continue, then you know, that that was unrealistic, you know, Dave, to, to your point on devices, I'm not necessarily, you know. Sure. I think, I think we definitely got ahead of our expectations and things like consumer PCs, those things will go back to historical growth >>Rates. Yeah. I mean, you got the install base is pretty young right now, but I think the one way to look at it too, is there was some technical debt brought in because people didn't necessarily expect that we'd be moving to a permanent hybrid state two years ago. So now we have to actually invest on both. We have to make, create a little bit more permanency around the hybrid world. And then also like Crawford's talking about the permanency of, of having an office and having people work in, in multiple modes. Yeah. It actually requires investment in both the office. And >>Also, so you're saying operationally, you gotta run the company and do the digital transformation to level up the hybrid. >>Yeah. Yeah. Just the way people work. Right. So, so, you know, you basically have to, I mean, even for like us internally, Crawford was saying, we're experimenting with what works for us. My team before the pandemic was like one third virtual. Now it's two third virtual, which means that all of our internal meetings are gonna be on, on teams or zoom. Right. Yeah. They're not gonna necessarily be, Hey, just coming to the office today, cuz two thirds of people aren't in the Boston area. >>Right. Matt, you said if you see cloud as an operating model, not necessarily a place. I remember when you were out, I was in the, on the, on the, on the zoom when, when first met Adam Celski yeah. Um, he said, you were asking him about, you know, the, the on-prem guys and he's like, nah, it's not cloud. And he kind of was very dismissive of it. Yeah. Yeah. I wanna get your take on, you know, what we're seeing with as Azure service GreenLake, apex, Cisco's got their version. IBM. Fewer is doing it. Is that cloud. >>I think if it's, I, I don't think all of it is by default. I think it is. If I actually think what HPE is doing is cloud, because it's really about how you present the services and how you allow customers to engage with the platform. So they're actually creating a cloud model. I think a lot of people get lost in the transition from, you know, CapEx to OPEX and the financing element of this. But the reality is what HPE is doing and they're sort of setting the standard. I think for the industry here is actually setting up what I would consider a cloud model. >>Well, in the early days of, of GreenLake, for sure it was more of a financial, you >>Know, it was kind of bespoke, right. But now you've got 70 services. And so you can, you can build that out. But >>You know, we were talking to Keith Townsend right after the keynote and we were sort of UN unpacking it a little bit. And I, I asked the question, you know, if you, if you had to pin this in terms of AWS's maturity, where are we? And the consensus was 2014 console filling, is that fair or unfair? >>Oh, that's a good question. I mean, um, I think it's, well, clouds come a long way, right? So it'd be, I, I, I think 20, fourteen's probably a little bit too far back because >>You have more modern tools I Kubernetes is. Yeah. >>And, but you also have, I would say the market still getting to a point of, of, of readiness and in terms of buying this way. So if you think about the HP's kind of strategy around edge, the core platform as a, as a service, you know, we're all big believers in edge and the apps follow the data and the data's being created in new locations and you gotta put the infrastructure there. And for an end user, there's a lot of risk there because they don't know how to actually plan for capacity at the edge. So they're gonna look to offload that, but this is a long term play to actually, uh, build out and deploy at the edge. It's not gonna happen tomorrow. It's a five, 10 year play. >>Yeah. I mean, I like the operating model. I'd agree with you, Matt, that if it's, if it's cloud operations, DevSecOps and all that, all that jazz it's cloud it's cloud operating and, and, and public cloud is a public cloud hyperscaler on premise. And the storage folks were presented. That's a single pane of glass. That's old school concepts, but cloud based. Yep. Shipping hardwares, auto figures. Yeah. That's the kind of consumption they're going for now. I like it. Then I, then they got the partner led thing is the partner piece. How do you guys see that? Because if I'm a partner, there's two things, wait a minute, am I at bottleneck to the direct self-service? Or is that an enabler to get more cash, to make more money? If I'm a partner. Cause you see what Essentia's doing with what they do with Amazon and Deloitte and et C. Yeah. You know, it's interesting, right? Like they've a channel partner, I'm making more cash. >>Yeah. I mean, well, and those channel partners are all in transition too. They're trying to yeah. Right. Figure out. Right, right. Are they, you know, what are their managed services gonna look like? You know, what kind of applications are they gonna stand up? They're they're not gonna just be >>Reselling, bought a big house in a boat. The box is not selling. I wanna ask you guys about growth because you know, the big three cloud, big four growing pick a number, I dunno, 30, 35% revenue big. And like you said, it's 30% of the business now. I think Dell's growing double digits. I don't know how much of that is sustainable. A lot of that is PCs, but still strong growth. Yep. I think Cisco has promised 9% >>In, in that. Right, right. >>About that. Something like that. I think IBM Arvin is at 6%. Yep. And I think HPE has said, Hey, we're gonna do three to 4%. Right. Which is so really sort of lagging and which I think a lot of people in wall street is like, okay, well that's not necessarily so compelling. Right. What does HPE have to do to double that growth? Or even triple that growth. >>Yeah. So they're gonna need, so, so obviously you're right. I mean, being able to show growth is Tanem out to this company getting, you know, more attention, more heat from, from investors. I think that they're rightly pointing to the triple digit growth that they've seen on green lake. I think if you look at the trailing, you know, 12 month bookings, you got over, you know, 7 billion, which means that in a year, you're gonna have a significant portion of the company is as a service. And you're gonna see that revenue that's rat being, you know, recognized over a series of months. So I think that this is sort of the classic SAS trough that we've seen applied to an infrastructure company where you're basically have to kind of be in the desert for a long time. But if they can, I think the most important number for HPE right now is that GreenLake booking snow. >>And if you look at that number and you see that number, you know, rapidly come down, which it hasn't, I mean off a very large number, you're still in triple digits. They will ultimately start to show revenue growth, um, in the business. And I think the one thing people are missing about HPE is there aren't, there are a lot of companies that want to build a platform, but they're small and nobody cares. And nobody let's say they throw a party and nobody comes. HP has such a significant installed base that if they do build a platform, they can attract partners to that platform. What I mean by that is partners that deliver services on GreenLake that they're not delivering. They have the girth to really start to change an industry and change the way stuff is being built. And that's the be they're making. And frankly, they are showing progress in that direction. >>So I buy that. But the one thing that concerns me is they kind of hide the ball on services. Right. And I, and I worry about that is like, is this a services kind of just, you know, same wine, new bottle or, >>Or, yeah. So, so I, I, I would argue that it's not about hiding the ball. It's about eliminating confusion of the marketplace. This is the company that bought EDS only to spin it off <laugh>. Okay. And so you don't wanna have a situation where you're getting back into services. >>Yeah. They're the only one >>They're product, not the only ones who does, I mean, look at the way IBM used to count and still >>I get it. I get it. But I think it's, it's really about clarity of mission. Well, I point next they are in the Ts business, absolutely. Point of it. It's important prop >>Drive for them at the top. Right. The global 50 say there's still a lot of uniqueness in what they want to buy. So there's definitely a lot of bespoke kind of delivery. That's still happening there. The real promise here is when you get into the global 2000 and yeah. And can start them to getting them to consume very standardized offers. And then the margins are, are healthy >>And they got they're what? Below 30, 33, 30 3%. I think 34% last quarter gross margin. Yeah. That that's solid. Just compare that with Dell is, I don't know. They're happy with 20, 21% of correct. You get that, which is, you know, I I'll come back. Go ahead. I want, I wanna ask >>Guys. No, I wanna, I wanna just, he said one thing I like, which was, I think he nailed it. They have such, um, big install base. They have a great channel. They know how to use it. Right. That's a real asset. Yeah. And Microsoft, I remember when their stock was trading at 26 when Baltimore was CEO. Yep. What they did with no, they had office and windows, so a little bit different. Yep. But similar strategy, leverage our install base, bring something up to them. That's what you're kind of connecting the >>Absolutely. You have this velocity, uh, machine with a significant girth that you can now move to a new model. They move that to a new model. To Matt's point. They lead the industry, they change the way large swath the customers buy and you will see it in steady revenue growth over time. Okay. So I just in that, well, >>So your point is the focus and there the right it's the right focus. And I would agree what's >>What's the other move. What's their other move, >>The problem. Triple digit booking growth off a number that gets bigger >>Inspired. Okay. >>Whats what's the scoreboard. Okay. Now they're go at the growth. That's the scoreboard. What are the signals? Are you looking at on the scoreboard Crawford and Matt in terms of success? What are the benchmarks? Is it ecosystem growth, number of services, triple growth. Yeah. What's the, what are some of the metrics that you guys are gonna be watching and we should be watching? >>Yeah. I mean, I dunno if >>You wanna jump in, I mean, I think ecosystem's really critical. Yeah. You want to, you want to have well and, and you need to sell both ways like HPE needs to be selling their technology on other cloud providers and vice versa. You need to have the VMs of the world on, you know, offering services on your platform and, and kind of capturing some, some motion off that. I think that's pretty critical. The channel definitely. I mean, you have to help and what you're gonna see happen there is there will be channel partners that succeed in transforming and succeeding and there'll be a lot that go away and that some, some of that's, uh, generational there'll be people that just kind of age outta the system and, and just go home. >>Yeah. Yeah. So I would argue it's, it's, it's, it's gonna be, uh, bookings growth rate. It's gonna be retention rate of the, of, of, of the customers, uh, that they have. And then it's gonna be that, that, um, you know, ultimately you're gonna see revenue, um, growth, and which is that revenue growth is gonna have to be correlated to the booking's growth for green lake cross. >>What's the Achilles heel on, on HPE. If you had to do the SWAT, what's the, what's the w for HPE that they really need to pay >>Attention to. I mean, they, they need to continue their relentless focus on cost, particularly in the, in the core compute, you know, segment they need to be, they need to be able to be as cost effective as possible while the higher profit dollars associated with GreenLake and other services come in and then increase the overall operating margin and gross margin >>Picture for the, I mean, I think the biggest thing is they just have, they have to continue the motion that they've been on. Right. And they've been consistent about that. Mm-hmm, <affirmative> what you see where others have, have kind of slipped up is when you go to, to customers and you present the, the OPEX as a service and the traditional CapEx side by side, and the customers put in this position of trying to detangle what's in that OPEX service, you don't wanna do that obviously. And, and HP has not done that, but we've seen others kind of slip up. And, but >>A lot of companies still wanna buy CapEx. Right. Absolutely liquid. And, and I think, >>But you shouldn't do a, you shouldn't do that bake off by putting those two offers out. You should basically ascertain what they want to do. >>What's kind of what Dell does. Right. Hey, how, what do you want? We got this, we got >>This on one hand, we got this, the, we got that, right. Uh, the two hand sales rep, no, this CapEx. Thing's interesting. And if you're Amazon and Azure and, and GCP, what are they thinking right now? Cause remember what, four years ago outpost was launched, which essentially hardware. Yeah. This is cloud operating model. Yep. Yeah. They're essentially bringing outpost. This is what they got basically is Amazon and Azure, like, is this ABL on the radar for them? How would you, what, what are they thinking in your mind if we're on, if we're in their office, in their brain trust, are they laughing? Are they like saying, oh, they're scared. Is this real threat >>Opportunity? I, I, I mean, I wouldn't say they're laughing at all. I, I would say they're probably discounting a little bit and saying, okay, fine. You know, that's a strategy that a traditional hardware company is moving to. But I think if you look underneath the covers, you know, two years ago it was, you know, pretty basic stuff they were offering. But now when you start getting into some, you know, HPC is a service, you start getting into data fabric, you start getting into some of the more, um, sophisticated services that they're offering. And, and I think what's interesting about HP. What my, my take is that they're not gonna go after the 250 services the Amazon's offering, they're gonna basically have a portfolio of services that really focus on the core use cases of their infrastructure set. And, and I think one of the danger things, one, one of the, one of the red flags would be, if they start going way up the stack and wanting to offer the entire application stack, that would be like a big flashing warning sign, cuz it's not their sweet spot. It's not, not what they have. >>So machine learning, machine learning and quantum, okay. One you can argue might be up the stack machine learning quantum should be in their wheelhouse. >>I would argue machine learning is not up the stack because what they would focus on is inference. They'd focus on learning. If they came out and said, machine learning all the way up to the, you know, what a, what, what a drug discovery company needs to do. >>So they're bringing it down. >>Yeah. Yeah. Well, no, I think they're focusing on that middle layer, right? That, that, that data layer. And I think that helping companies manage their data make more sense outta their data structure, their data that's core to what they wanna do. >>I, I feel as though what they're doing now is table stakes. Honestly, I do. I do feel like, okay, Hey finally, you know, I say the same thing about apex, you >>Know, we finally got, >>It's like, okay guys, the >>Party. Great. Welcome to the, >>But the one thing I would just say about, about AWS and the other big clouds is whether they might be a little dismissive of what's truly gonna happen at the edge. I think the traditional OEMs that are transforming are really betting on that edge, being a huge play and a huge differentiator for them where the public cloud obviously have their own bets there. But I think they were pretty dismissive initially about how big that went. >>I don't, and I don't think anybody's really figured out the edge yet. >>Well, that's an, it's a battleground. That's what he's saying. I think you're >>Saying, but on the ecosystem, I wanna say up the stack, I think it's the ecosystem. That's gotta fill that out. You gotta see more governance tools and catalogs and AI tools and, and >>It immediately goes more, it goes more vertical when you go edge, you're gonna have different conversations and >>They're >>Lacking. Yeah. And they, but they're in there though. They're in the verticals. HP's in the, yeah, >>For sure. But they gotta build out an ego. Like you walk around here, the data, the number of data companies here. I mean, Starburst is here. I'm actually impressed that Starburst is here. Cause I think they're a forward thinking company. I wanna see that times a hundred. Right. I mean, that's >>You see HP's in all the verticals. That's I think the point here, >>So they should be able to attract that ecosystem and build that, that flywheel that's the, that's the hallmark of a cloud that marketplace. >>Yeah, it is. But I think there's a, again, I go back to, they really gotta stay focused on that infrastructure and data management. Yeah. >>But they'll be focused on that, but, but their ecosystem, >>Their ecosystem will then take it up from there. And I think that's the next stage >>And that ecosystem's gotta include OT players and communications technologies players as well. Right. Because that stuff gets kind of sucked up in that, in that edge play. Do >>You feel like HPE has a, has a leg up on that or like a little, a little bit of a lead or is it pretty much, you know, even raced right now? >>I think they've, I think the big infrastructure companies have all had OEM businesses and they've all played there. It's it's, it's also helping those OT players actually convert their own needs into more of a software play and, and not so much of >>Physical. You've been, you've been following and you guys both have been following HP and HPE for years. They've been on the edge for a long time. I've been focused on this edge. Yeah. Now they might not have the product traction that's right. Or they might not develop as fast, but industrial OT and IOT they've been talking about it, focused on it. I think Amazon was mostly like, okay, we gotta get to the edge and like the enterprise. And, and I think HP's got a leg up in my opinion on that. Well, I question is can they execute? >>Yeah. I mean, PTC was here years ago on stage talking >>About, but I mean, you think about, if you think about the edge, right. I mean, I would argue one of the best acquisitions this company ever did was Aruba. Right. I mean, it basically changed the whole conversation of the edge changed the whole conversation. >>If >>Became GreenLake, it was GreenLake. >>Well, it became a big department. They gave a big, but, but, but I mean, you know, I mean they, they, they went after going selling edge line servers and frankly it's very difficult to gain traction there. Yeah. Aruba, huge area. And I think the March announcement was when they brought Aruba management into. Yeah. Yeah. >>Totally. >>Last question. Love >>That. >>What are you guys saying about the, the Broadcom VMware acquisition? What's the, what are the implications for the ecosystem for companies like HPE and just generally for the it business? >>Yeah. So >>You start. Yeah, sure. I'll start, I'll start there. So look, you know, we've, you know, spent some time, uh, going through it spent some time, you know, speaking, uh, to the, to the, to the folks involved and, and, and I gotta tell you, I think this is a really interesting moment for Broadcom. This is Broadcom's opportunity to basically build a different kind of a conversation with developers to, uh, try to invest in. I mean, just for perspective, right? These numbers may not be exact. And I know a dollar is not a dollar, but in 2001, anybody, remember what HP paid for? Compact >>8,000,000,020, >>So 25 billion, 25 billion. Wow. VMware just got sold for 61 billion. Wow. Okay. Unbill dollars. Okay. That gives you a perspective. No, again, I know a dollar is not a dollar 2000. >>It's still big numbers, >>2022. So having said that, if you just did it to, to, to basically build your DCF model and say, okay, over this amount of time, I'll pay you this. And I'll take the money out of this period of time, which is what people have criticized them for. I think that's a little shortsighted. I, yeah, I think this is Broadcom's opportunity to invest in that product and really try to figure out how to get a seat at the table in software and pivot their company to enterprise software in a different way. They have to prove that they're willing to do that. And then frankly, that they can develop the skills to do that over time. But I do believe this is a, a different, this is a pivot point. This is not >>CA this is not CA >>It's not CA >>In my, in my mind, it can't be CA they would, they would destroy too much. Now you and I, Dave had some, had some conversations on Twitter. I, I don't think it's the step up to them sort of thinking differently about semiconductor, dying, doing some custom semi I, I don't think that's. Yeah. I agree with that. Yeah. I think I, I think this is really about, I got two aspiration for them pivoting the company. They could >>Justify the >>Price to the, getting a seat at the adults table in software is, >>Well, if, if Broadcom has been squeezing their supplies, we all hear the scutle butt. Yeah. If they're squeezing, they can use VMware to justify the prices. Yeah. Maybe use that hostage. And that installed base. That's kind of Mike conspiracy. >>I think they've told us what they're gonna do. >><laugh> I do. >>Maybe it's not like C what's your conspiracy theory like Symantec, but what >>Do you think? Well, I mean, there's still, I mean, so VMware there's really nobody that can do all the things that VMware does say. So really impossible for an enterprise to just rip 'em out. But obviously you can, you can sour people's taste and you can very much influence the direction they head in with the collection of, of providers. One thing, interesting thing here is, was the 37% of VMware's revenues sold through Dell. So there's, there's lots of dependencies. It's not, it's not as simple as I think John, you you're right. You can't just pull the CA playbook out and rerun it here. This is a lot more complex. Yeah. It's a lot more volume of, of, of distribution, but a fair amount of VMware's install >>Base Dell's influence is still there basically >>Is in the mid-market. It's not, it's not something that they're gonna touch directly. >>You think about what VMware did. I mean, they kept adding new businesses, buying new businesses. I mean, is security business gonna stay >>Networking security, I think are interesting. >>Same >>Customers >>Over and over. Haven't done anything. VMware has the same customers. What new >>Customers. So imagine simplifying VMware. Right, right. Becomes a different equation. It's really interesting. And to your point, yeah. I mean, I think Broadcom is, I mean, Tom Crouse knows how to run a business. >>Yeah. He knows how to run a business. He's gonna, I, I think it's gonna be, you know, it's gonna be an efficient business. It's gonna be a well run business, but I think it's a pivot point for >>Broadcom. It's amazing to me, Broadcom sells to HPE. They sell it to Dell and they've got a market cap. That's 10 X, you know? Yes. Yeah. All we gotta go guys. Awesome. Great conversation guys. >>A lot. Thanks for having us on. >>Okay. Listen, uh, day two is a, is a wrap. We'll be here tomorrow, all day. Dave ante, John furrier, Lisa Martin, Lisa. Hope you're feeling okay. We'll see you tomorrow. Thanks for watching the cube, your leader in enterprise tech, live coverage.

(upbeat music) >> Hello, welcome back to theCUBE's coverage of AWS re:Invent 2021. We're here in the studios in Palo Alto, California. Two great guests Linda Tong, general manager of Cisco AppDynamics and Garrick Linn, architect of operations at Match.com. Thanks for joining us. We're talking about AppDynamics, Match.com and customer experience. Mainly around cloud migration. So Linda, great to see you and Garrick, thanks for coming on theCUBE. >> Great to see you again. Thank you for having us. >> Same here. >> Linda, you're a CUBE alumni. we've talked about cloud migration application performance, modern application development, all powered by the Cloud, right? So this is really key and people are relying on the cloud and cloud scale and data to drive the digital transformation, the digital services and applications right now. How has the pandemic affected your customers and their expectations for digital experiences? >> Oh boy, I mean the pandemic has been, it has been rough for our customers, you know, and part of that is what Garrick's going to tell you a little bit more about today, but folks are seeing this increase in expectancy of accelerated speed and delivering innovation, building great applications and iterating on them quickly. And frankly, their customers' demands we're engaging with them through digital services. And that has led to this massive increase in, one, the types of technologies that they're consuming to build and deliver these applications. And two the complexity upon how they actually wrap their arms around it and understand what's going on and deliver these great experiences. And so it's been a rough road for our customers and what we find with AppDynamics and Cisco is our ability to partner with our customers to help them wrap their arms around that complexity. >> John: Garrick, I'd love to get your commentary on this because I'll say, Match.com has been at large-scale for many, many years, and now the pandemic comes in now a new user experience, more accelerated, more action, more things are happening, right? So this is truly the hybrid world coming together. I mean, it is kind of the same game, but kind of new patterns are emerging. What have you seen in the pandemic around the expectations and the services and you guys are providing in the digital experiences? >> Yeah, sure. So as you mentioned, Match has been around for quite some time. We've been here for over 25 years. We have an interesting mix, heterogeneous, technology, some old stuff, some new stuff. A lot of the mentality that we try to bring is to innovate. The pandemic was, it brought a lot of uncertainty. We weren't really sure how people were going to react. Was it going to be everybody kind of hunkers down on dating definitely is something that requires human interaction in multiple levels. And it turned out that people were still very much interested in getting to a place where they can find human connections and you know Match as a premium product tries to make that delightful. And so we had our hands full, especially at the beginning, things like, by checking the video features, how does that work? What are the expectations? Is that going to creep people out? If we try to offer that, are they going to use it? How are they going to date? How are they going to talk? How can we make sure that they're safe? All these kinds of things went into it. And so when we have been using AppDynamics for you know, years now, well before the pandemic, and we use that in order to get a gauge, not just on the type of traffic and load, but also, "Hey, you've got these new features, "how do they fit into this huge complex environment?" And so some of those timelines that maybe were a little bit more relaxed were very much accelerated, And like a lot of companies, we had to figure out how to deliver on that. >> John: Yeah, Linda, I want to get your thoughts. We've talked about in the past, AppDynamics has been a leader in really accelerating the value for customers. Now with the pandemic, you mentioned these new experiences are being pulled in from the physical world, right? So you have things that were happening on digital in the application space. Now you have more experiences coming in because there's no places to meet face to face. Now it's coming together, but people have been seeing the value. Well, if I can't meet in person Match.com are going to do some things, new things, online chat, whatever. This dynamic of old way, new way is changing and cloud is powering that. What are you seeing in terms of your customers' journeys around what was once pre-pandemic and now post-pandemic? >> Well, a big part of that is more and more of these experiences rely on digital services and these amazing sort of ways to connect with each other and in a very digital space, expectations of customers have changed. So not only do you experience applications and you want it to be simple, easy to use, delightful, and it delivers on the needs that you want. But on top of that, you expect it to be performant. You expect it to be secure. You expect there to be frankly, no hiccups whatsoever, because now this is your way to connect with others. This is your way to find dates or go on dates. And the last thing you want, is watching your screen pixelate, as you're trying to have an important conversation. And these kinds of experiences and these challenges as people build more and more of these digital services to build these connections, frankly, require a lot more of folks like Garrick and his team. They now have to deliver amazing experiences with perfect performance, no security risks, no bumps in the night. And that's really tough, right? Expectations have gone through the roof. >> John: Yeah, the whole story on that one point, just to kind of add live in this was that that whole concept of moving fast used to take months, right? I mean, weeks, months, now it's days and hours. So months to weeks, days and hours but Garrick, this is the challenge. This is the opportunity with the cloud. Can you just take us through your cloud journey and your goals and some of the impacts that has had on your transition to the cloud? What does that look like? >> Yeah, so we've had our on-prem data centers for quite some time, and we started putting our toe in, I guess, although it was a kind of intense at the beginning, just trying to get people on board and to say, "Hey, this is possible." We started out with a fairly small SWAT team then managed within a couple of months, working closely with our developers. We have a lot of smart people, you know, with background or overall, just security folks over devs to just demonstrate that we could do it. So we managed to take something like 80% of our front end traffic for most of the day, just kind of spinning that up, learning lessons from that, knowing what we didn't know. AppDynamics, if we didn't have that would have been almost impossible to get a read if for no other reason, then just one little tidbit. We used to have a data center in Virginia. And so physics being what it is, you know, there's just been a flight that we have to contend with. And for a couple, few years, we hadn't had the 30 millisecond or so round trip latency on there. So all of a sudden we're going back to the cloud that reintroduced this latency. So what does that mean? Will you be asked to sort of glide by and absorb it? How do we track it? How can we figure out what the Delta is between, you know, here's how we've done things on-prem. Here's how it looks out here. If you are the cross, you know, calls and, you know, AppDynamics was what we used to be able to get a read and say, "Hey, look, it isn't as good as we know we can make it, but it's something, it's a starting point. Here's why, we can show you the graphs. We can show you the data. Let's do this thing." So we then pulled back and we have focused this year on actually our affinity apps, which is a collection of applications that are also going to be okay just in, and so we've been asked to get those completely migrated over. We're going to be running in hybrid mode for a while. We're going to need to be able to compare apples to apples, apples to orangutans, all that. And this is one of the main things for you, we describe. >> {John] If I can just follow up on that just real quick, because I think this is a good point. You got the data points, you double down on that. You're looking at real data, and then you look at success and you double down, that's the playbook. So, and the other thing is that you guys actually have a real operation that's running full throttled, right? (John laughs) So, yeah, so I can see that nice balance. What does the future look like beyond that? Because when you got a business that's scaling, it's running, it's like changing the airplane engine out at 30,000 feet. You got to continue to push the envelope. >> Yup, so, and no, exactly right. Again, we're a premium product. And so we've got to back that up. And that means, maintaining high availability. And so over the next few years, we're going to be looking at what have we already do? What can we move in piecemeal kind of way where it makes sense? What are the things that we can rethink? We're also using AppDynamics as part of our containerization initiative. You know, we've got lots of virtual infrastructure, but what is it, again, what does it look like on-prem, in a container, go down the list of different things that might be different. And then to be able to compare that to what it looks like, in the cloud. So it's going to be a while yet, but like a lot of companies, when we got into this, we didn't think it was going to be done in six months. Even if we have to deliver those features at a much faster rate, we know that the long haul, we got to make smart decisions and plan the capacity, and, you know, get there. (chuckles) >> John: That's a real pragmatic approach. Linda, you and I both are sports fans. We've talked in the past about sports, and the old adage, what inning are we in growth? It's to use that baseball metaphor. I would say it's a double header, game one won by the cloud, game two is happening now. And the trend is this end-to-end mature, operationally focused customer base. And IT, where IT has shifted to the cloud right now. And they're having this new view of what modern is. End-to-end, understanding different stacks relative to applications. It's not as simple as it was before, but it's relevant. Can you share your views on how that's playing out because, or do you agree with that? And do you see that as an important part of the customer? >> Yeah, I mean, I think it's, that complexity that the IT organizations are seeing now, as they fully adopt the cloud for all their new applications and start to migrate some of their existing applications over. That world is only increasing in complexity. The way that you can virtualize your applications, break them out into millions of services, the dependencies you have on third party applications or SaaS services. These things only add that many more data points that you now have to cover and think about and make sure that those things deliver upon their SLAs, right? And wrapping your arms around that requires a partner to help you separate signal from noise. Because now you're going into a world without simplicity that you just mentioned has gotten to some point where it's beyond what you can actually sort of keep in your mind. Beyond what you can just look at data and sift through and understand, you really need tools and systems that come together, and understand that data for you and start to represent your business to you in a new way and abstract away those layers of complexity. While you do that, because I think, as you talk about those innings, that first inning, second inning, or rather first game, second game in the series, it's not a full migration to the cloud, right? There are going to be some applications that stay on-prem that stay in their traditional environments and may never move. And then some of them are going to go hybrid. Some will keep parts of the applications on-prem, and they're going to start to modularize components of it. And so it's not going to be sort of a mass scale migration. And then we're all in the promised land. And we deal with the cloud complexity. It's going to be ever increasing complexity. As we now introduce so many variants of applications, so many variants of technology, and what people are going to need is someone who can help them cover that entire estate and understand it at scale. >> John: Yeah, I mean, I think it's the enterprise conversion, if you will of cloud operations on-premises because of the reasons. And now you've got the edge. Garrick, this is the whole kind of end-to-end stack conversation view. And by the way, there isn't one tech stack to rule them all because you have different use cases. You might have an application that needs a financial gateway or have other capabilities. So integration's huge. This only increases the point Linda was making about complexity behind the scenes. How does AppDynamics help you with this for Match.com? >> So we have quite a bit of infrastructure, you know, a lot of it is shared, well, most of all, maintaining, sandboxes for user data and that sort of thing. And so now the navigating that space is always interesting. So for instance, one of the new things that we have coming out is Star.com It's out there right now. It's a dating site that's geared towards single parents. It does share some of the infrastructure, but we're realizing what that means, how is that different, how our registration flow is different, how our subscription flow is different. Where are the things that DevOps are actively trying to improve on and rethink? That's one of the things that we try to focus on when we're trying to kind of pick out, like, is this a good candidate to move over to the cloud sooner or later? Is this a good candidate for something that needs to be maybe bake a little bit more? And having established those baselines with the shared infrastructure, and having a pretty good understanding of how they react, how they work really helps us, you know, tee up these new initiatives and in front of those needs in a more efficient way. So yeah, absolutely. >> John: What's some of the activity you guys seen? And what's the peak activity on Match.com these days? >> Yeah, so dating apps in general, but not so particular we use a nested or breast fractal peak, and it's a pattern that, from what they told me back in the old days, took a little while to realize was a thing. And not just like, oh we changed something and then did this and produced that. So every evening is our peak basically. So with taking time zones into account, obviously, in the United States from about five to 10 o'clock at night or so, we get this, growing, burst of traffic. So that can be anywhere from 23% sometimes. It kind of varies. Then we have a weekly peak where every, you know, Sunday and Monday we expect a higher amount of traffic than we would other days. And it kind of makes sense from an Archer psychology kind of standpoint where, you know, you're coming off of dates, you're trying to set dates up. That's where a lot of that activity is. And then we have a yearly peak, which goes from around Christmas to President's day. Believe it or not, it's President's day, it's not Valentine's day. And so the sort of thing where when we're trying to plan for capacity and we do a lot of, what cost squeeze tests, were not quite as I guess, engineering, but hey, what does it look like if we go down in capacity by 50%, what happens? where are the weak points? A January, Monday night is very different from a May, Thursday in June (chuckles). So we have to predict, we can anticipate some of that, but we don't know for sure, a lot can change in a year. So when we're preparing for a yearly peak, we really have to pay attention. We have to prep. We have to plan for that and work with that to figure out how we can get through it and maintain that level of service. >> That's awesome, and AppDynamics to help you to do that. I'd love to get a bot to give me the optimal dating times, to share with my single friends. Great stuff. Linda, thank you for coming. Great to see you. Congratulations on a great case study. Great story. How large-scale applications and are working in the modern cloud. So congratulations on your success. Thanks for coming on theCUBE. Appreciate it. >> Awesome, thank you, so good to be here. >> Okay, CUBE coverage of re:Invent 2021. I'm John Furrier with theCUBE. Thanks for watching. (upbeat music)

>>Yeah, yeah. >>Hello and welcome back. I hope you're ready for our next session. Become the analyst of the future. We'll hear the customer's perspective about their increasingly strategic role and the potential career growth that comes with it. Joining us today are Nate Weaver, director of product marketing at Thought Spot. Yasmin Natasa, senior director of national sales strategy and insights over at Comcast and Steve Would Ledge VP of customer and partner initiatives. Oughta Terex. We're so happy to have you all here today. I'll hand things over to meet to kick things off. >>Yeah, thanks, Paula. I'd like to start with a personal story that might resonate with our audience, says an analyst. Early in my career, I was the intermediary between the business and what we called I t right. Basically database administrators. I was responsible for understanding business logic gathering requirements, Ringling data building dashboards for executives and, in my case, 100 plus sales reps. Every request that came through the business intelligence team. We owned everything, right? Indexing databases for speed, S s. I s packages for data transfer maintaining Department of Data Lakes all out cubes, etcetera. We were busy. Now we were constantly building or updating something. The worst part is an analyst, If you ask the business, every request took too long. It was slow. Well, from an analyst perspective, it was slow because it's a complex process with many moving parts. So as an analyst fresh out of grad school often felt overeducated, sometimes underappreciated, like a report writer, we were constantly overwhelmed by never ending ad hoc request, even though we had hundreds of reports and robust dashboards that would answer 90% of the questions. If the end user had an analytical foundation like I did right, if they knew where to look and how to navigate dimensions and hierarchies, etcetera. So anyway, point is, we had to build everything through this complex and slow, um, process. So for the first decade of my career, I had this gut feeling there had to be a better way, and today we're going to talk about how thought SWAT and all tricks are empowering the analysts of the future by reimagining the entire data pipeline. This paradigm shift allows businesses and data teams thio, connect, transform, model and, most importantly, automate what used to be this terribly complex data analysis process. With that, I'd like to hand it over to Steve to describe the all tricks analytic process automation platform and how they help analysts create more robust data sets that enable non technical end users toe ask and answer their own questions, but also more sophisticated business questions. Using Search and AI Analytics in Thoughts Fire Steve over to you. >>Thanks for that really relevant example. Nate and Hi, everyone. I'm Steve. Will it have been in the market for about 20 years, and then Data Analytics and I can completely I can completely appreciate what they was talking about. And what I think is unique about all tricks is how we not only bring people to the data for a self service environment, but I think what's often missed in analytics is the automation and figure out. What is the business process that needs to be repeated and connecting the dots between the date of the process and the people To speed up those insights, uh, to not only give people to self service, access to information, to do data prep and blending, but more advanced analytics, and then driving that into the business in terms of outcomes. And I'll show you what that looks like when you talk about the analytic process automation platform on the next slide. What we've done is we've created this end to end workflow where data is on the left, outcomes around the right and within the ultras environment, we unify data prep and blend analytics, data science and process automation. In this continuous process, so is analysis or an end user. I can go ahead and grab whatever data is made available to me by i t. You have got 80 plus different inputs and a p i s that we connect to. You have this drag and drop environment where you conjoined the data together, apply filters, do some descriptive analytics, even do things like grab text documents and do sentiments analysis through that with text, mining and natural language processing. As people get more used to the platform and want to do more advanced analytics and process automation, we also have things like assisted machine learning and predictive analytics out of the box directly within it as well and typically within organizations. These would be different departments and different tools doing this and we try to bring all this together in one system. So there's 260 different automation building blocks again and drag a drop environment. And then those outcomes could be published into a place where thoughts about visualizes that makes it accessible to the business users to do additional search based B I and analytics directly from their browser. And it's not just the insights that you would get from thought spot, but a lot of automation is also driving unattended, unattended or automated actions within operational systems. If you take an example of one of our customers that's in the telecommunications world, they drive customer insights around likeliness to turn or next best offers, and they deliver that within a salesforce applications. So when you walk into a retail store for your cell phone provider, they will know more about you in terms of what services you might be interested in. And if you're not happy at the time and things like that. So it's about how do we connect all those components within the business process? And what this looks like is on this screen and I won't go through in detail, but it's ah, dragon drop environment, where everything from the input data, whether it's cloud on Prem or even a local file that you might have for a spreadsheet. Uh, I t wants to have this environment where it's governed, and there's sort of components that you're allowed to have access to so that you could do that data crept and blending and not just data within your organization, but also then being able to blend in third party demographic data or firm a graphic information from different third party data providers that we have joined that data together and then do more advanced analytics on it. So you could have a predictive score or something like that being applied and blending that with other information about your customer and then sharing those insights through thought spots and more and more users throughout the organization. And bring that to life. In addition to you, as we know, is gonna talk about her experience of Comcast. Given the world that we're in right now, uh, hospital care and the ability to have enough staff and and take care of all of our people is a really important thing. So one of our customers, a large healthcare network in the South was using all tricks to give not only analyst with the organization, but even nurses were being trained on how to use all tricks and do things like improve observation. Wait time eso that when you come in, the nurse was actually using all tricks to look at the different time stamps out of ethic and create a process for the understands. What are all the causes for weight in three observation room and identify outliers of people that are trying to come in for a certain type of care that may wait much longer than on average. And they're actually able to reduce their wait time by 22%. And the outliers were reduced by about 50% because they did a better job of staffing. And overall staffing is a big issue if you can imagine trying to have a predictive idea of how many staff you need in the different medical facilities around the network, they were bringing in data around the attrition of healthcare workers, the volume of patient load, the scheduled holidays that people have and being able to predict 4 to 6 months out. What are the staff that they need to prepare toe have on on site and ready so they could take care of the patients as they're coming in. In this case, they used in our module within all tricks to do that, planning to give HR and finance a view of what's required, and they could do a drop, a drop down by department and understand between physicians, nurses and different facilities. What is the predicted need in terms of staffing within that organization? So you go to the next slide done, you know, aside from technology, the number one thing for the analysts of the future is being able to focus on higher value business initiatives. So it's not just giving those analysts the ability to do this self service dragon drop data prep and blend and analytics, but also what are the the common problems that we've solved as a community? We have 150,000 people in the alter its community. We've been in business for over 23 years, so you could go toe this gallery and not only get things like the thought spot tools that we have to connect so you can do direct query through T Q l and pushed it into thought spot in Falcon memory and other things. But look at things like the example here is the healthcare District, where we have some of our third party partners that have built out templates and solutions around predictive staffing and tracking the complicating conditions around Cove. It as an example on different KPs that you might have in healthcare, environment and retail, you know, over 150 different solution templates, tens of thousands of different posts across different industries, custom return and other problems that we can solve, and bringing that to the community that help up level, that collective knowledge, that we have this business analyst to solve business problems and not just move data, and then finally, you know, as part of that community, part of my role in all tricks is not only working with partners like thought spot, but I also share our C suite advisory board, which we just happen to have this morning, as a matter of fact, and the number one thing we heard and discussed at that customer advisory board is a round up Skilling, particularly in this virtual world where you can't do in classroom learning how do we game if I and give additional skills to our staff so that they can digitize and automate more and more analytic processes in their organization? I won't go through all this, but we do have learning paths for both beginners. A swell as advanced people that want to get more into the data science world. And we've also given back to our community. There's an initiative called Adapt where we've essentially donated 125 hours of free training free access to our products. Within the first two weeks, we've had over 9000 people participate in that get certified across 100 different companies and then get jobs in this new world where they've got additional skills now around analytics. So I encourage you to check that out, learn what all tricks could do for you in up Skilling your journey becoming that analysts of the future And thanks for having me today thoughts fun looking forward to the rest of conversation with the Azmin. >>Yeah, thanks. I'm gonna jump in real quick here because you just mentioned something that again as an analyst, is incredibly important. That's, you know, empowering Mia's an analyst to answer those more sophisticated business questions. There's a few things that you touched on that would be my personal top three. Right? Is an analyst. You talked about data cleansing because everyone has data quality problems enhancing the data sets. I came from a supply chain analytics background. So things like using Dun and Bradstreet in your examples at risk profiles to my supplier data and, of course, predictive analytics, like creating a forecast to estimate future demand. These are things that I think is an analyst. I could truly provide additional value. I'd like to show you a quick example, if I may, of the type of ad hoc request that I would often get from the business. And it's fairly complex, but with a combination of all tricks and thought spots very easy to answer. Crest. The request would look something like this. I'd like to see my spend this year versus last year to date. Uh, maybe look at that monthly for Onley, my area of responsibility. But I only want to focus on my top five suppliers from this year, right? And that's like an end statement. I saw that in one of your slides and so in thoughts about that's answering or asking a simple question, you're getting the answer in maybe 30 seconds. And that's because behind the scenes, the last part is answering those complexities for you. And if I were to have to write this out in sequel is an analyst, it could take me upwards, maybe oven our because I've got to get into the right environment in the database and think about the filters and the time stamps, and there's a lot going on. So again, thoughts about removes that curiosity tax, which when becoming the analysts of the future again, if I don't have to focus on the small details that allows me to focus on higher value business initiatives, right. And I want to empower the business users to ask and answer their own questions. That does come with up Skilling, the business users as well, by improving data fluency through education and to expand on this idea. I wanna invite Yasmin from Comcast to kind of tell her personal story. A zit relates to analysts of the future inside Comcast. >>Well, thank you for having me. It's such a pleasure. And Steve, thank you so much for starting and setting the groundwork for this amazing conversation. You hit the nail on the head. I mean, data is a Trojan horse off analytics, and our ability to generate that inside is eyes busy is anchored on how well we can understand the data on get the data clean It and tools, like all tricks, are definitely at the forefront off ability to accelerate the I'll speak to incite, which is what hot spot brings to the table. Eso My story with Thought spot started about a year and a half ago as I'm part of the Sales Analytics team that Comcast all group is officially named, uh, compensation strategy and insight. We are part of the Consumer Service, uh, Consumer Service expected Consumer Service group in the cell of Residential Sales Organization, and we were created to provide insight to the Comcast sells channel leaders Thio make sure that they have database insight to drive sales performance, increased revenue. We When we started the function, we were really doing a lot of data wrangling, right? It wasn't just a self performance. It waas understanding who are customers were pulling a data on productivity. Uh, so we were going into HR systems are really going doing the E T l process, but manually sometimes. And we took a pause at one point because we realized that we're spending a good 70% of our time just doing that and maybe 5% of our time storytelling. Now our strength was the storytelling. And so you see how that balance wasn't really there. And eso Jim, my leader pause. It pulls the challenge of Is there a better way of doing this on DSO? We scan the industry, and that's how we came across that spot. And the first time I saw the tool, I fell in love. There's not a way for me to describe it. I fell in love because I love the I love the the innovation that it brought in terms of removing the middleman off, having to create all these layers between the data and me. I want to touch the data. I want to feel it, and I want to ask questions directly to it, and that's what that's what does for us. So when we launched when we launch thoughts about for our team, we immediately saw the difference in our ability to provide our stakeholders with better answers faster. And the combination of the two makes us actually quite dangerous right on. But it has been It has been a great great journey altogether are inter plantation was done on the cloud because at the time, uh, the the we had access to AWS account and I love to be at the edge of technology, So I figured it would be a good excuse for me to learn more about cloud technology on its been things. Video has been a great journey. Um, my, my background, uh, into analytics comes from science. And so, for me, uh, you know, we are really just stretching the surface off. What is possible in terms off the how well remind data to answer business questions on Do you know, tools like thought spot in combination with technologies. Like all trades, eyes really are really the way to go about it. And the up skilling, um the up skilling off the analysts that comes with it is really, really, really exciting because people who love data want to be able to, um want to be efficient about how they spend time with data. Andi and that's what? That's what I spend a lot of my Korea I'd Comcast and before Comcast doing so It gives me a lot of ah, a lot of pleasure to, um to bring that to my organization and to walk with colleagues outside off. We didn't Comcast to do so The way we the way we use stops, that's what we did not seem is varies. One of the things that I'm really excited about is integrating it with all the tools that we have in our analytics portfolio, and and I think about it as the over the top strategy. Right. Uh, group, like many other groups, wouldn't Comcast and with our organizations also used to be I tools. And it is not, um, you choose on a mutually exclusive strategies, right? Eso In our world, we build decision making, uh, decision making tools from the analysis that we generate. When we have the read out with the cells channel leaders, we we talk about the insight, and invariably there's some components off those insight that they want to see on a regular basis. That becomes a reporting activity. We're not in a reporting team. We partner with reporting team for them to think that input and and and put it on and create a regular cadence for it. Uh, the over the top strategy for me is, um, are working with the reporting team to then embed the link to talk spot within the report so that the questions that can be answered by the reports left dashboard are answered within the dashboard. But we make sure that we replicate the data source that feeds that report into thought spot so that the additional questions can then be insert in that spot. It and it works really well because it creates a great collaboration with our partners on the on the reporting side of the house on it also helps of our end the end users do the cell service in along the analytic spectrum, right? You go to the report when you can, when all you need is dropped down the filters and when the questions become more sophisticated, you still have a platform in the place to go to ask the questions directly and do things that are a bit funk here, like, you know, use for like you because you don't know what you're looking for. But you know that there's there's something there to find. >>Yeah, so yeah, I mean, a quick question. Our think would be on this year's analytics meet Cloud open for everyone and your experience. What does that mean to you? Including in the context of the thought spot community inside Comcast? >>Oh yes, it's the Comcast community. The passport commedia Comcast is very vibrant. My peers are actually our colleagues, who I have in my analytics village prior to us getting on board with hot spot and has been a great experience for us. So have thoughts, but as an additional kind of topic Thio to connect on. So my team was the second at Comcast to implement that spot. The first waas, the product team led by Skylar, and he did his instance on Prem. Um, he the way that he brings his data is, is through a sequel server. When I came what, as I mentioned earlier, I went on the cloud because, as I mentioned earlier, I like to be on the edge of technology and at the time thought spot was moving towards towards the cloud. So I wanted to be part of that wave. There's Ah, mobile team has a new instance that is on the cloud thing. The of the compliance team uses all tricks, right? And the S O that that community to me is really how the intellectual capital that we're building, uh, using thought spot is really, really growing on by what happens to me. And the power of being on the cloud is that if we are all using the same tool, right and we are all kind of bringing our data together, um, we are collaborating in ways that make the answer to the business questions that the C suite is asking much better, much richer. They don't always come to us at the same time, right? Each function has his own analytics group, Andi. Sometimes if we are not careful, we're working silo. But the community allows us to know about what each other are working on. And the fact that we're using the same tool creates a common language that translates into opportunities for collaboration, which will translate into, as I mentioned earlier, richer better on what comprehensive answers to the business. So analyst Nick the cloud means better, better business and better business answers and and better experiences for customers at the end of the day, so I'm all for it. >>That's great. Yeah. Comcast is obviously a very large enterprise. Lots of data sources, lots of data movement. It's cool to hear that you have a bit of a hybrid architecture, er thought spot both on premise. Stand in the cloud and you did bring up one other thing that I think is an important question for Steve. Most people may just think of all tricks as an E T l tool, but I know customers like Comcast use it for way more than just that. Can you expand upon the differences between what people think of a detail tool and what all tricks is today? >>Yeah, I think of E. T L tools as sort of production class source to target mapping with transformations and data pipelines that air typically built by I t. To service, you know, major areas within the business, and that's super valuable. One doesn't go away, and in all tricks can provide some of that. But really, it's about the end user empowerment. So going back to some of guys means examples where you know there may be some new information that you receive from a third party or even a spreadsheet that you develop something on. You wanna start to play around that information so you can think of all the tricks as a data lab or data science workbench, in fact, that you know, we're in the Gartner Magic Quadrant for data science and machine learning platforms. Because a lot of that innovation is gonna happen at the individual level we're trying to solve. And over time, you might want to take that learning and then have I t production eyes it within another system. But you know, there's this trade off between the agility that end users need and sort of the governance that I t needs to bring. So we work best in a environment where you have that in user autonomy. You could do E tail workloads, data prep and Glenn bringing your own information on then work with i t. To get that into the right server based environment to scale out in the thought spot and other applications that you develop new insights for the business. So I see it is ah, two sides of the same coin. In many ways, a home. And >>with that we're gonna hand it back over to a Paula. >>Thank you, Nate, Yasmin and Steve for the insights into the journey of the analyst of the future. Next up in a couple minutes, is our third session of today with Ruhollah Benjamin, professor of African American Studies at Princeton University, and our chief data strategy officer, Cindy House, in do a couple of jumping jacks or grab a glass of water and don't miss out on the next important discussion about diversity and data.

>>from San Francisco. It's the queue covering our essay conference. 2020. San Francisco Brought to you by Silicon Angle Media >>Welcome back to our C for cube coverage Here in our state conference, I'm John Furrier with the Cube. Our next guest is a car guy who's with the McAfee, and he's a technical fellow, formerly chief scientist and co founder of Sky High Networks, which was acquired by really pioneering. Some of what we're seeing is Cloud is the driver screen paradigm. Thanks for coming on, John. Thank you so much. I know a lot of times we'll jump right in. The cloud is changing the game. You guys saw the wave early at sky high. So how is it rendered itself today? Was seeing the signals out there. How all the members earnings were down this week because of their on premises is shifting to the cloud. We think we'll do well, but it's also impacting. Everyone's got a shift, including their customers. What's going >>on? This is amazing, you know, last year, I think a few months back we did a survey of large enterprises. For the first time, we found that the majority of the CIOs and CSOs felt that cloud is more secure than on Prem. That's a big deal. I mean, I've never seen that before. I didn't expect it to be this quick, but that that actually manifest itself in and Price is ready to be cloud first are very cloud friendly. And that's significantly different from when we started Sky High and even a couple of years ago on. Because of that, how you secure the data, how you secure it connects to the kind of threats I need to be looking at the different lens on. I mean, you've seen breaches happen every week. If you look back over the last year and a lot of those cloud native threats, these are not malware based breaches of data, which is what you would think of any traditional look at micro services breaches. No, these cloud breaches, because Cloud has It's very good, right? It's got transparency. It's got AP eyes. So whatever AP eyes use, a bad actor could use it as well, really. Land exfiltrate on expanding the cloud footprint is very different from how traditional malware attacks happen within the enterprise. And so we've been looking at cloud native. That's on what it means to even secure data in the cloud, which is very different from, you know, securing data in your enterprise. For example, I run a deal, be on my laptop. You know what kind of since the data's there, but in the cloud you don't do that because the data is cloud native and we've In our analysis, you've seen that 50% of traffic is cloud to cloud, so it bypasses a traditional enterprise network by positive devices. And so when you talk about data protection, you need to look at new ways of understanding, cloud and integrating into. >>It's interesting I've talked to many CSOs have been cloud native and born in the cloud, and they say their their their worst day in cloud security is better than any day they've had on premise security. There's actually more security in the cloud, but then when they start getting into hybrid, and now what we see is multi clouds. That third wave coming, you start to look at on premise to Cloud Cloud Cloud. You have a network component becomes a big part of Could you share your vision on how the network needs to evolve because Amazon and Azure they have their own networks. It's also not on premise, either, So I want to run a route from here to here. What's the network? And >>I don't think network this security controls going away. And if you look at what McAfee and insist today is what we call the unified cloud edge, we acknowledge that security's it's security at the end point at the cloud and in the network. So we are the first product really. Teoh integrated policies on visibility into data flow between the clouds you want from the cloud on any device. And so in that model you have a network components of users Secure Gateway, which is cloud hosted. So it's interesting you see that a lot of security do there also becoming cloud native. So that's what we've leveraged. Our cloud Native Cloud security platform, cloud, native Swat, Web gateway as well as ER and endpoint. Protection from the >>question is the chief scientist Andrew you, are the security posture of companies certainly is changing the cloud. How would you describe the current posture from a customer perspective? The cloud in a good way. What do they need to be thinking about. >>Yeah, I think actually, Gartner said it very well. In fact, a couple of years you last year they had a mq Mr. Actually said that 99% off your data breaches in the cloud is going to be because of customer fall. It may be the most trivial things, but those are the ones that get you right. And it turns out that cloud is easy and quick that up. It's very easy to miss configure >>stuff. So human error. >>Yeah, it's completely, and I kid you not. Majority of the shoes are failure to understand your shared responsibility >>model or the cost of a breach. When the doors wide open, they're just walking through. That's not really a breach that called just the door's open they walk through. I mean, that's what you're talking about >>exactly. I have the responsibility of the customers to configure it appropriately. I think that will take care of the lowest hanging fruit for them and then as their wall, their workloads moving into the cloud. They need to think about hybrid and not get into the trap of creating silos. That's a classic example, right? Security vendors were created building that kind of product companies around it, the container security. They're VM security. There's cloud security. At the end of the day, our customers are moving their workload and application in the cloud. They need a consistent way to ensure that configurations right data is secure and there's no threats to it. I we need to make that model of simplicity of consistency across all of these vendors. >>It's clear that McAfee is transforming their business to cloud. You guys have been a big part of that. Congratulations. How would you describe McAfee? Is current situation with respect to the cloud growth Now the on premise, cloud hybrid integration and multi cloud coming because you now have this entire systems architecture, a k a cloud, multi cloud hybrid public all need to work together. >>I think McAfee is very well positioned and honestly, when we joined McAfee, McAfee strength was in the end point and actually got a very good business in the server and pointed out with the CWS product when we came into the cloud native approach where that product was selling very well for the private data center on Prem, what we were able to do is add a cloud security story, but also create a sort of be the catalyst for ambition and vision is really this broad umbrella within McAfee for doing orderly cloud security. But, er insights, not products which can run in the cloud at scale in a multi tenant manner. >>You can create a data driven approach to make that human personalization work. Exactly. Don't forget, secure. That s three bucket. Exactly. I think when you go to your car is like you left your keys in. There's a new level of personalization coming from the data that you say that the >>video, clearly what we see with customers is going back to the shared responsibility model. It's almost like you're in the car. The center has some responsibilities rental agency and the car manufacturer responsibility that all of us have Understanding what those >>responsible. Just talking Another guest. We're saying, Hey, that role is used data to tell the human not to screw up. Yeah, you're flying on a plane, you gotta go secure your door. It's about reminding the environment you're working with getting >>doing it, doing it in real time because configurations change in the CD pipelines and real time right on being able to catch that and what we've done a part of my career the last year is do something that we call it Shift left, which is really before an application is born to make it secure. And it's possible in the cloud because it's very transparent. We can infrastructure this quote. So as the court gets checked in weaken, validate it. And >>well, I'm glad you brought that point real quick. I know you got to go. Dev. Ops has been a real influence on a lot of infrastructure as code, but now you have SEC ops dev sec off. So it's kind of the same melting pot. That's agility iteration real time. What's your version of security version of Dev Ops? >>Yeah, it is that it is basically playing whack a mole after the fact, you know, going and looking at configuration failures, DLP, whatever Push it. It actually helps the security team because they don't have bandwidth. They want to be able to coop developers and literally 100 X more developers and security folks. And so being able to integrate it with the tooling for continuous integration deployment is something we've done. It's a huge win for customers. >>Thanks for sharing the inside. We'll be able to empower event coming up. We'll do more interviews there and do a deep dive real quick. What are you working on right now? That's exciting. That's getting you motivated. That puts a little spring in your step. What's happening? >>I mean, this is a huge issue on Cloud Native sets on how we use miter and other frameworks to make the soccer teams more not get lost in all the nice on. You. See a lot of that work from us, but there's a lot of exciting >>work that innovation coming out of a lot of innovation. Software driven, obviously. Cloud. Yeah, we'll get back and talk about some of the cloud native nuances. KUBERNETES. State State. We've done a lot of data. We had a lot of action, lot of tech, a lot of potential opportunities, challenges. Thanks for coming on the Cube here with the Cube. We're here on the ground at RSA Conference. We'll be right back. Thanks for watching. >>Yeah, yeah,

>>Live from Copenhagen, Denmark. It's the cube covering Nutanix dot. Next 2019 brought to you by Nutanix. >>Welcome back everyone to the cubes live coverage of next here in Copenhagen. We are of course here at the Nutanix show. We are wrapping up a fantastic today show. I'm your host, Rebecca Knight. Been Cosa hosting alongside of Stu Miniman. We are joined by Simon Taylor. He is the CEO of haiku, a good friend of the cube. Thank you so much for coming back on the show. It's a pleasure to be here. It's great to see you guys again. Final guest. Oh my gosh. It's a, it's a fare to stay interested in your energy. Yes. So for our viewers who are not as familiar with haiku, tell us a little bit about your business and how you are a strategic partner of Nutanix. >> Sure, sure. So haiku actually is a software company that focuses on data protection as a service. We actually started by spinning out of a much larger company called calm train that had about a thousand engineers and was doing all sorts of things, but they had an amazing talent for building backup and recovery software. >>Um, my vision was really that we can move up the value chain and we can establish ourselves as our own brand, as long as we could find a place in the market that was fast growing, building like a rocket ship and was really requiring a new kind of data protection and backup. And honestly, as soon as we fell, we saw Nutanix, we sort of fell in love. We realized that, you know, they had developed an entirely new category of business with hyperconverged and they were really a pioneer in that space. So we said is why don't we build the world's first purpose-built backup and recovery for Nutanix? And that's exactly what we did. And I think, you know, Stu was actually one of the first people to ever hear about it. Uh, we came on the cube and we talked about that. We've GA that in 2017 in July. I think@that.next, um, so just two and a half years later, we now have 1200 customers and we're in 62 countries around the world. So it's been absolutely astonishing. It's been wonderful growth. We're seeing 300% year over year growth. Uh, and really a lot of that is just based on our ability to protect the data of Nutanix customers around the world. >>Well and and Simon, right? That early question was, is new CanOx is going to be big enough to support ISV is that, you know, can run the, you know, grow their business underneath them before we get further and talk about mine and everything. Give us a little bit, you know, the state of the state for haiku because started with Nutanix, but that's not the only solution they are offering Dave. So just give us kind of the snapshot of the whole business. >>What we realized as we were building out high Q in this purpose build backup recovery for new TEDx. We said that's the on-prem, you know, but there's a lot of on prem that is still legacy three tier architecture. So we added a VMware product. But really the goal was to offer true multi-cloud data protection as a service. So what we did is we built the independent purpose-built backup and recovery service from Nutanix, one for VMware. Then we built the world's first purpose build backup as a service for Google cloud. And I'm really thrilled to announce the next month we're launching Azure backup as well. And the brilliant thing about our system and our solution is that we actually enabled customers to not only back up their data independently for that cloud, but that then migrate their data to whatever other cloud they want to use. So we actually becomes data protection as a service, data migration, and dr. >>So for, for customers, this is wonderful, but how is it to be strategic partners with all of these big players? >> Oh yeah, absolutely. I think you have to place your bets, right? So if you notice, I didn't say AWS and almost every company that I talked to says, why wouldn't you start with AWS? They're the biggest, you know, that's never been our philosophy. You know, I think the fact that we attach ourselves to Nutanix so early, not just because they were a rocket ship on fire, but also because we truly believed in their vision. We believe in the Nutanix products, we love Daraja entire philosophy around simplicity and customer delight and we felt like we could be students of Nutanix, we could actually build out our product with those same philosophies and principles in mind. You know? So I think really going deep with Nutanix is number one for us remains number one. I would also say though that you know, Google has been an excellent partner and Microsoft been an excellent partner. So with the large cloud providers you have to take a different approach. You cannot offer a downloadable product, right? All of our public cloud backup and recovery is a true managed service. You go into their app store, you turn it on rather than download it, you configure and you're able to perform all your backup and do all your recovery right from the console. >>All right, so Simon let, let's get into the kind of the, the, the guts of what's happening at Nutanix. Mine, of course is a partnership to extend for data protection, partnering with Veeam and haikus as a, as the first two partners. Uh, the other thing that everybody's pretty excited about is XY clusters. And that sounds like, and we've talked to Newtanics people, you know, as Nutanix brings their stack into the clouds, not just on the clouds, will that pull things like mine along with them. And so, so give us what you're seeing with mine first and maybe he's, I clusters along. >>Yeah. So maybe we start with mine, right? This whole concept that I think that these guys have pioneered and they've done a really terrific job of it. I think, you know, the, the vision there, and you know, I count marketing or Meyer in this group and Tim Isaacs and some wonderful folks on the product team in Nutanix. Their vision was, you know, there's rubric and there's Cohesity, there's these sort of large secondary storage platforms. Personally, when I look at them, what I see as Newtanics with a backup workload, right? And I think that, you know, Nutanix being the original is the best. It's the most complete solution. And it's very, very comprehensive. So I think the, the tannics folks understood this intuitively and their idea was instead of us building our own backup and going after that space, we've got amazing partners like haiku. Why don't we just natively integrate them into the mind platform and offer that sort of secondary storage workload, uh, as a key part of Nutanix is product proposition. >>So the really exciting thing for us is that we are skewed up with Nutanix. Nutanix, we'll be able to resell haiku as a part of mine. Uh, and I think that's gonna really complete their end tour tire story when it comes to being able to own the data center, uh, and really own the sort of cloud in general. You know. So I think your second question still was about clusters. And I think that the answer there is very simple. You know, multi Gloucester is, has become extremely important for Nutanix customers. They've done a great job of going after that. The simple fact is if you don't support XY clusters as a backup vendor, you really can't compete in this market. So I'm really thrilled to announce, of course, that haiku is the first backup recovery vendor that does support. Gluster. >>Okay. So interesting. We talked about how you hadn't done a solution for AWS. Sounds like this might be a path for you to get with Nutanix onto AWS. >>Absolutely, absolutely. And again, for us it's not about looking for some Trojan horse or backdoor into a go to market strategy. It's about making sure that the customers are truly delighted by the value that we provide. And I think that when we go after a specific market, we want to do it the best, you know, so we don't go shallow and just sort of check the box. We want to make sure, for example, when we build out Azure that we're not just dealing with, you know, the, the general principle of backing up and keeping things consistent. We want to make sure the applications people are running on Azure or supported by haiku. That's what we do with Nutanix. That's what we do with GCP. We want to always go as deep as possible so we can really compliment the platform in a really, really comprehensive way. >>One of the things you said earlier was that your philosophy is very much aligned with Nutanix, your your end goal to simplify and delight the customer, uh, this, this much more intuitive, uh, youth and user interface. So talk a little bit about how you, you said you wanted to become a student of Nutanix, yo, this, this cross company learning is very interesting to me. How, how, what have you learned? Yeah. What have you learned and how do you go about being tutored by your customers? >>No, I'm a very visual guy, right? And whenever I think about Nutanix, I always had this image in my head. All right. Whenever I thought about legacy, three-tier architecture and the move to hyperconverged, rather, I always pictured an 80 stereo system. Remember those big eighties boxes? And they have all the graphic equalizers and all the way down. And some kid would come and push them all down. You could never reset the darn things, you know? And then along comes, you know, automation and suddenly, you know, you press a button and you listen to jazz and it sounds like good jazz and the treble and the bass all fixed themselves. You know, I effectively think that Nutanix brought that same concept, funnily enough into the data center. They simplified so much that was impossible to handle for admins across the world. They made it so simple to use their product that actually the customers could start to enjoy their work more. >>And I really love that. That's a true, that's a really an intangible sort of value proposition that I think people don't talk about it enough. Yes, you want to save time. Yes, you want to save money, but if you could enjoy your job more as a result of getting a product, what's better than that? Um, so I think that philosophy is something we baked into haiku in the following ways. You know, the first is when we were designing the UI, we wanted it to look and feel like the platform it supports. So when you use haiku for Nutanix, it looks like prism, when you are using our console for GCP, you're gonna feel like you're using GCP. The idea is that backup and recovery should be an extension of that cloud expression, that platform, so that the customer who is an expert with that platform can easily manage this with no training at all. So again, driving that simplicity right there and in the platform. >>Yeah. So Simon, you know, one of the things we love to do is get hear from customers and what they're doing. Of course you've got 1200 customers that are Nutanix customers. So we'd love to hear, you know, any insights you have in a lot of discussion about AHV in the last 12 months has been about half of the deployment. Is there anything around HV or any of the, you know, new software features and products and experiences that Nutanix has been launching that you hear customers buzzing and talking to you about? >>I mean, I, I, the first thing I would say is it is truly a multicloud world now. Um, I think that legacy vendors are having a harder and harder time coping with the fact that cloud washing no longer works. You know, if you show up to the market and you say, Oh, this, now I can deploy an agent into this cloud, it's sort of stop, stop, don't say agent around me. You know? So I think, I think the ability to really natively integrate into any of these clouds and support all of these clouds equally is key. You know? So in the past a vendor would start with one thing and it would be great, right? And I won't use names here, but then they would do something else. They might move to another hypervisor and it was a little bit less great. Right. And I think that that notion has to change in a multicloud world, which brings me to the concept of HV. >>I think that HV has really grown. I mean, I would say that right now, you know, over half of our customers are HV customers. And I would say that that grows every single quarter and it not only grows in terms of net new logos, it also grows in terms of existing customers that we're finding SWAT to switch to HV and they want to switch fast. You know, they don't want to pay the V tax anymore, but more than that, I think they're seeing HV as a really robust enterprise hypervisor that really meets the complete need for the customer. And I think that's, that's been terrific to watch. So when you hear at.next, and this is not your first hot next, but what kinds of conversations are you having? What's been interesting to you? What are you going to take back to haiku? Yeah, head back to Brookline. Yeah. >>I mean obviously there's all the new stuff. I mean, Kubernetes, you know, containers. Um, I think these are all things we've been working on for some time. We'll have some surprises for you guys in Q4 at the end of Q four around that. Um, but you know, I think the big takeaway for me is we spent the first two years building our brand, getting the word out there, proving to companies and customers around the world that we were truly enterprise ready cause we were the new kid on the block. And you have to sort of start somewhere and show that. I think now we, you know, we added physical last year, we added tape support, we've really got all of the major applications covered at this point. I think that conversation, we've checked the box, right? So today's conversations are about what's next, how much more deeply will you integrate with Nutanix? >>How can I use Nutanix to then manage my data in the cloud and bring it back again? And can haikus support that or will it distract me? And you know, the simple answer is it will support that completely because it's so natively integrated. You know. And again, I think when you choose a platform at this stage, and this is something we've seen again and again and again, people do not want a second silo, right? In order to, you know, run their backup and recovery. You know, customers who are choosing Nutanix or choosing any platform want to run that platform and they want to make that one holistic experience. You know, they want to reduce the training required and they want to make sure they get the most out of their investment. So we're where I think two or three years ago, Stu, when we first met, everybody was trying new things, right? It was sort of, there were all these new platforms and it was all very exciting. I think now people are doubling, tripling, quadrupling down on the platforms they fundamentally believe in. And we're thrilled about that because we support those platforms and we'll continue to do so. >>Great. Excellent little. Simon, thank you so much for coming on the cube. It was a real pleasure talking to you and it's been great. Yes, no, absolutely. Thank you very much. Thank you so much. Thank you for having me. That wraps up two brilliant days in Copenhagen at the Bella center at Nutanix dot. Next. Thank you so much for joining us and we hope to see you next time.

>>live from Seattle, Washington. It's the key nude covering smartsheet engaged 2019. Brought to you by Smartsheet. >>Hello, everyone. We are wrapping up one day of coverage at Smartsheet. Engage here in Seattle. I'm Rebecca Knight. Been coasting all day with Jeff Rick. It's been a pleasure sitting next to you together, and it has just been so much fun. It's a great show. >>And you've never been to Seattle before >>my time in the city? Exactly. So you've >>covered this space, Rebecca, in your in your non key black for a very long time. So first off, you know, kind of general impressions of new way to work. We hear about it every show we got to talk about new way to work. So, you know, kind of your global perspective a little bit and then, you know, kind of some takeaways from some of the conversations today. >>Well, we know that the situation is pretty bleak right now that there are the statistics are horrible just in terms of the number of employees that are really checked out, totally disengaged, would would love to quit, but they need the health insurance. And so we're already sort of starting from from a pretty low place, where in terms of people's engagement at work, and I think a lot of the things that that drive people nuts about their work. Uh, of course, is a bad boss and not a great parking spot and everything, but it's it's it's it's the little things that get in your way of doing your job. And it's it's the things that just drive you nuts about some sort of process that takes forever. And, oh, I have to keep doing this. And I just already sent you that email and how come you're looking at this other version? And it's all those impediments that really drive people crazy and that makes people stressed out and and unhappy in their jobs. So I do think that if you are a company like Smartsheet and you have you realized this and you can slowly chip away at those impediments and the aggregate aggravate aggravations that people feel, I think that's not a bad business model. I think I think they're on to something here. Don't worry, though >>sometimes is just is just additive, right? It's just another thing we talked. It's one of the interviews. And when I'm at work, I have three big monitors, each one split into two screens. I've got mail open calendar, open sales force open, slack open asana open YouTube. Twitter. Um, it's probably a couple. And then if I have to, like, look something up and and you know there's this kind of constant confusion is what it what is the screen that's open when you work? And it used to just be e mail, which is not a good solution at all. So I think if if you know, they can become the place that people do, their work right, and we talked about all the integrations like it's that integrate with slack. So maybe you know, the people that work primarily and slacker primarily there, and maybe the people in some other department are primarily on spark cheat, and somebody else is primarily on another tool. But it just seems still like keep adding, tourists were not necessarily taking a lot of them away. >>Well, that will be the job for Anna Griffin, who is the first ever cmo this company. You just started in April, and she's got her work cut out for her because you're right. There are a lot of screens. That's that does not describe my work day. But I know it describes a lot of people's work day, Um, and that that that will be. What she needs to figure out is how to be your number one You're going to the one that you rely on to get your job done. >>The part that I took away from her interview is really She talked a lot about engagement, and you just talked about engagement, an empowerment, you know, not only not only getting the obstacles out of the way, but making me feel like what I do matters, matters to me, matters to my boss, matters to my clients and matters. And then I think that does finally drive to innovation, which is the Holy Grail that everyone talks about. But it's really not that easy to execute. >>Everyone wants more innovative, of course, >>and then the last thing which she talked about, why part of the reason why she came here? His leadership. But I think the way we really can't have this conversation around engagement without talking about leadership, because it's such a critical piece to the puzzle for everyone to rally around, you know, a mission. So this is the execution details. But you also need some type of a mission that you can feel good about, as well as feeling that you can contribute to. >>Absolutely. And I think that what you were just talking about with the ownership piece and so these air these employees, as we said, they're removing the impediments to their job. But then they're also able to then focus on higher level tasks, assignments, thinking, strategy. They're able to use their brains for what they were hired for, not thinking about certain tasks and other files that are old versions. And so if they if they could do those things and then, as you said, feel like they matter, feel like that work, they matters to their boss. However, you are right in that if you got a bad boss, all bets are off. If it works, still gonna stink and you're there. There's nothing you can do about it. >>The other piece that came up, which I was interesting, is really about prioritization. What and what do you optimizing for? And my favorite part of Clayton Christian since Innovator's dilemma, is the conversation about that you must prioritize. You cannot engineer for everything equally, and you have to force up. That pressurization, I think, is interesting here about Smart Cheat is for all the talk about digital transformation. Most people talk about the products, and service is that they sell. They talk about the engagement with their customers. They don't talk about transforming the life of their employees and the way their employees get stepped on and the way the employees actually engage with the company through the applications. And I thought that was a really interesting and insightful take, especially in the day where everything is a service. And again your people walk out the door every night and you hope they come back the next day. So I think, you know, spinning the digital transformation story into more of an employee enable men and engagement story is pretty powerful. >>You I could not agree more because because that that is the critical piece. If you have a bunch of people coming to work every day who hate their jobs, they're not gonna be giving your customers the experience that you want their customers tohave. So it really does start with Happy workers, right? Andi, I think that I think smart. She really gets that. So that's that's what I am struck by today. >>Yeah, it's just those other ones that we're going to bring along. And Dion may have made a good point and said, You know, some people don't want to be engaged work. Some people don't want >>you >>next level things like that they like their roads in the routine gives him comfort. They come to work, they do the road in the routine and they go home. So it's gonna be interesting. Time for those peoples can reach it in time for people to not necessarily have expertise in a broad range of categories formerly siloed categories like product marketing, product management, finance sales, biz, Dev production. But you least have tohave in a kind of an inch. De Milo gave those teams. So you put together a SWAT team, if you will, to accomplish the task. And that's what I'm curious to see. Some of the 4 51 research that how how he was pointing to kind of a restructuring of the silos of teams and organizations within it within a company that We don't hear much about how that's going to restructure on kind of a dev ops, fast assembly, fast, complete kind of assemble and disassemble around projects, which is what Dev Ops says. We'll see you know how that how that impacts organizational structure. >>And I think that could be very cool and very different, particularly with different. I mean, we know that diverse groups make better decisions than lone geniuses. And so if we have a bunch of people who have different perspectives, different levels of expertise and even if it's not expertise, it's just sort of a general knowledge about a lot of different things, right. We know that if we can get those people working together on a task, it's got a lot of potential. So I think I think you're right, right. >>Last thing is that I think really interesting. Here is the is the acknowledgment of team beyond even the company walls. So you've got your core team, you know, cross departmental collaboration, and then was a mere it over and over here here today, collaboration outside the walls to external teams. And it was Mark talking about putting on these big events mean there's so many external stakeholders in place holders and vendors involved in this humongous dance that becomes our enjoyment of the Final Four event. I think that's really insightful. Kind of take that. You have to have the ability to engage, collaborate with a large group or an extended group for any particular project. And And that really changes the way you think about what the application is high share information >>and that they all have to feel ownership in the process to yes, very >>important. All right, Rebecca. Well, >>this was so much fun. I Jeff, I had a great time working with you, and we had a great team. We had Andrew in Jay and Brendan and Taylor Welcome Taylor to the to the show. It was great. I can't wait to come back and do it again. >>It will be big next time. All right, >>Thanks. That is wrapping up our coverage of engaged 2019. I'm Rebecca Knight for Jeff. Rick. Thanks a lot for watching

>> Live from San Francisco, it's theCUBE covering IBM Think 2019, brought to you by IBM. >> Welcome back everyone, live here in Moscone North in San Francisco, it's theCUBE's exclusive coverage of IBM Think 2019. I'm John Furrier, Dave Vellante. We're bringing down all the action, four days of live coverage. We've got two great guests here, Elenita Elinon, Executive Director of Quantitative Research at JP Morgan Chase, and John Thomas, Distinguished Engineer and Director of the Data Science Elite Team... great team, elite data science team at IBM, and of course, JP Morgan Chase, great innovator. Welcome to theCUBE. >> Welcome. >> Thank you very much. >> Thank you, thank you, guys. >> So I like to dig in, great use case here real customer on the cutting edge, JP Morgan Chase, known for being on the bleeding edge sometimes, but financial, money, speed... time is money, insights is money. >> Absolutely. Yes. >> Tell us what you do at the Quantitative Group. >> Well, first of all, thank you very much for having me here, I'm quite honored. I hope you get something valuable out of what I say here. At the moment, I have two hats on, I am co-head of Quantitative Research Analytics. It's a very small SWAT, very well selected group of technologists who are also physicists and mathematicians, statisticians, high-performance compute experts, machine learning experts, and we help the larger organization of Quantitative Research which is about 700-plus strong, as well as some other technology organizations in the firm to use the latest, greatest technologies. And how we do this is we actually go in there, we're very hands-on, we're working with the systems, we're working with the tools, and we're applying it to real use cases and real business problems that we see in Quantitative Research, and we prove out the technology. We make sure that we're going to save millions of dollars using this thing, or we're going to be able to execute a lot on this particular business that was difficult to execute on before because we didn't have the right compute behind it. So we go in there, we try out these various technologies, we have lots of partnerships with the different vendors, and IBM's been obviously one of few, very major vendors that we work with, and we find the ones that work. We have an influencing role as well in the organization, so we go out and tell people, "Hey, look, "this particular tool, perfect for this type of problem. "You should try it out." We help them set it up. They can't figure out the technology? We help them out. We're kind of like what I said, we're a SWAT team, very small compared to the rest of the organization, but we add a lot of value. >> You guys are the brain trust too. You've got the math skills, you've got the quantitative modeling going on, and it's a competitive advantage for your business. This is like a key thing, a lot of new things are emerging. One of things we're seeing here in the industry, certainly at this show, it's not your yesterday's machine learning. There's certainly math involved, you've got cognition and math kind of coming together, deterministic, non-deterministic elements, you guys are seeing these front edge, the problems, opportunities, for you guys. How do you see that world evolving because you got the classic math, school of math machine learning, and then the school of learning machines coming together? What kind of problems do you see these things, this kind of new model attacking? >> So we're making a very, very large investment in machine learning and data science as a whole in the organization. You probably heard in the press that we've brought in the Head of Machine Learning from CMU, Manuela Veloso. She's now heading up the AI Research Organization, JP Morgan, and she's making herself very available to the rest of the firm, setting strategies, trying different things out, partnering with the businesses, and making sure that she understands the use case of where machine learning will be a success. We've also put a lot of investments in tooling and hiring the right kinds of people from the right kinds of universities. My organization, we're changing the focus in our recruiting efforts to bring in more data science and machine learning. But, I think the most important thing, in addition to all that investment is that we, first and foremost, understand our own problems, we work with researchers, we work with IBM, we work with the vendors, and say, "Okay, this is the types of problems, "what is the best thing to throw at it?" And then we PoC, we prove it out, we look for the small wins, we try to strategize, and then we come up with the recommendations for a full-out, scalable architecture. >> John, talk about the IBM Elite Program. You guys roll your sleeves up. It's a service that you guys provide with your top clients. You bring in the best and you just jump in, co-create opportunities together, solving problems. >> That is exactly right. >> How does this work? What's your relationship with JP Morgan Chase? What specific use case are you going after? What are the opportunities? >> Yeah, so the Data Science Elite Team was setup to really help our top clients in their AI journey, in terms of bringing skills, tools, expertise to work collaboratively with clients like JP Morgan Chase. It's been a great partnership working with Elenita and her team. We've had some very interesting use cases related to her model risk management platform, and some interesting challenges in that space about how do you apply machine learning and deep learning to solve those problems. >> So what exactly is model risk management? How does that all work? >> Good question. (laughing) That's why we're building a very large platform around it. So model risk is one of several types of risk that we worry about and keep us awake at night. There's a long history of risk management in the banks. Of course, there's credit risk, there's market risk, these are all very well-known, very quantified risks. Model risk isn't a number, right? You can't say, "this model, which is some stochastic model "it's going to cost us X million dollars today," right? We currently... it's so somewhat new, and at the moment, it's more prescriptive and things like, you can't do that, or you can use that model in this context, or you can't use it for this type of trade. It's very difficult to automate that type of model risk in the banks, so I'm attempting to put together a platform that captures all of the prescriptive, and the conditions, and the restrictions around what to do, and what to use models for in the bank. Making sure that we actually know this in real time, or at least when the trade is being booked, We have an awareness of where these models are getting somewhat abused, right? We look out for those types of situations, and we make sure that we alert the correct stakeholders, and they do something about it. >> So in essence, you're governing the application of the model, and then learning as you go on, in terms of-- >> That's the second phase. So we do want to learn at the moment, what's in production today. Morpheus running in production, it's running against all of the trading systems in the firm, inside the investment bank. We want to make sure that as these trades are getting booked from day to day, we understand which ones are risky, and we flag those. There's no learning yet in that, but what we've worked with John on are the potential uses of machine learning to help us manage all those risks because it's difficult. There's a lot of data out there. I was just saying, "I don't want our Quants to do stupid things," 'cause there's too much stupidity happening right now. We're looking at emails, we're looking at data that doesn't make sense, so Morpheus is an attempt to make all of that understandable, and make the whole workflow efficient. >> So it's financial programming in a way, that's come with a whole scale of computing, a model gone astray could be very dangerous? >> Absolutely. >> This is what you're getting at right? >> It will cost real money to the firm. This is all the use-- >> So a model to watch the model? So policing the models, kind of watching-- >> Yes, another model. >> When you have to isolate the contribution of the model not like you saying before, "Are there market risks "or other types of risks--" >> Correct. >> You isolate it to the narrow component. >> And there's a lot of work. We work with the Model Governance Organization, another several hundred person organization, and that's all they do. They figure out, they review the models, they understand what the risk of the models are. Now, it's the job of my team to take what they say, which could be very easy to interpret or very hard, and there's a little bit of NLP that I think is potentially useful there, to convert what they say about a model, and what controls around the model are to something that we can systematize and run everyday, and possibly even in real time. >> This is really about getting it right and not letting it get out of control, but also this is where the scale comes in so when you get the model right, you can deploy it, manage it in a way that helps the business, versus if someone throws the wrong number in there, or the classic "we've got a model for that." >> Right, exactly. (laughing) There's two things here, right? There's the ability to monitor a model such that we don't pay fines, and we don't go out of compliance, and there's the ability to use the model exactly to the extreme where we're still within compliance, and make money, right? 'Cause we want to use these models and make our business stronger. >> There's consequences too, I mean, if it's an opportunity, there's upside, it's a problem, there's downside. You guys look at the quantification of those kinds of consequences where the risk management comes in? >> Yeah, absolutely. And there's real money that's at stake here, right? If the regulators decide that a model's too risky, you have to set aside a certain amount of capital so that you're basically protecting your investors and your business, and the stakeholders. If that's done incorrectly, we end up putting a lot more capital in reserve than we should be, and that's a bad thing. So quantifying the risks correctly and accurately is a very important part of what we do. >> So a lot of skillsets obviously, and I always say, "In the money business, you want the best nerds." Don't hate me for saying that... the smartest people. What are some of the challenges that are unique to model risk management that you might not see in sort of other risk management approaches? >> There are some technical challenges, right? The volume of data that you're dealing with is very large. If you are building... so at the very simplistic level, you have classification problems that you're addressing with data that might not actually be all there, so that is one. When you get into time series analysis for exposure prediction and so on, these are complex problems to handle. The training time for these models, especially deep learning models, if you are doing time series analysis, can be pretty challenging. Data volume, training time for models, how do you turn this around quickly? We use a combination of technologies for some of these use cases. Watson Studio running on power hardware with GPUs. So the idea here is you can cut down your model training time dramatically and we saw that as part of the-- >> Talk about how that works because this is something that we're seeing people move from manual to automated machine learning and deep learning, it give you augmented assistance to get this to the market. How does it actually work? >> So there is a training part of this, and then there is the operationalizing part of this, right? At the training part itself, you have a challenge, which is you're dealing with very large data volumes, you're dealing with training times that need to be shrunk down. And having a platform that allows you to do that, so you build models quickly, your data science folks can iterate through model creation very quickly is essential. But then, once the models have been built, how do you operationalize those models? How do you actually invoke the models at scale? How do you do workflow management of those models? How do you make sure that a certain exposure model is not thrashing some other models that are also essential to the business? How do you do policies and workflow management? >> And on top of that, we need to be very transparent, right? If the model is used to make certain decisions that have obvious impact financially on the bottom line, and an auditor comes back and says, "Okay, you made this trade so and so, why? What was happening at that time?" So we need to be able to capture and snapshot and understand what the model was doing at that particular instant in time, and go back and understand the inputs that went into that model and made it operate the way it did. >> It can't be a black box. >> It cannot be, yeah. >> Holistically, you got to look at the time series in real time, when things were happening and happened, happening, and then holistically tie that together. Is that kind of the impact analysis? >> We have to make our regulars happy. (laughing) That's number one, and we have to make our traders happy. We, as quantitative researchers, we're the ones that give them the hard math and the models, and then they use it. They use their own skillsets too to apply them, but-- >> What's the biggest needs that your stakeholders on the trading side want, and what's the needs on the compliance side, the traders want more, they want to move quickly? >> They're coming from different sides of it. Traders want to make more money, right? And they want to make decisions quickly. They want all the tools to tell them what to do, and for them to exercise whatever they normally exercise-- >> They want a competitive advantage. >> They want that competitive advantage, and they're also... we've got algo-trades as well, we want to have the best algo behind our trading. >> And the regulator side, we just want to make sure laws aren't broken, that there's auditing-- >> We use the phrase, "model explainability," right? Can you explain how the model came to a conclusion, right? Can you make sure that there is no bias in the model? How can you ensure the models are fair? And if you can detect there is a drift, what do you do to correct that? So that is very important. >> Do you have means of detecting sort of misuse of the model? Is that part of the governance process? >> That is exactly what Morpheus is doing. The unique thing about Morpheus is that we're tied into the risk management systems in the investment bank. We're actually running the same exact code that's pricing these trades, and what that brings is the ability to really understand pretty much the full stack trace of what's going into the price of a trade. We also have captured the restrictions and the conditions. It's in the Python script, it's essentially Python. And we can marry the two, and we can do all the checks that the governance person indicated we should be doing, and so we know, okay, if this trade is operating beyond maturity or a certain maturity, or beyond a certain expiry, we'll know that, and then we'll tag that information. >> And just for clarification, Morpheus is the name of the platform that does the-- >> Morpheus is the name of the model risk platform that I'm building out, yes. >> A final question for you, what's the biggest challenge that you guys have seen from a complexity standpoint that you're solving? What's the big complex... You don't want to just be rubber-stamping models. You want to solve big problems. What are the big problems that you guys are going after? >> I have many big problems. (laughing) >> Opportunities. >> The one that is right now facing me, is the problem of metadata, data ingestion, getting disparate sources, getting different disparate data from different sources. One source calls it a delta, this other source calls it something else. We've got a strategic data warehouse, that's supposed to take all of these exposures and make sense out of it. I'm in the middle because they're there, probably at the ten-year roadmap, who knows? And I have a one-month roadmap, I have something that was due last week and I need to come up with these regulatory reports today. So what I end up doing is a mix of a tactical strategic data ingestion, and I have to make sense of the data that I'm getting. So I need tools out there that will help support that type of data ingestion problem that will also lead the way towards the more strategic one, where we're better integrated with this-- >> John, talk about how you solve the problems? What are some of the things that you guys do? Give the plug for IBM real quick, 'cause I know you guys got the Studio. Explain how you guys are helping and working with JP Morgan Chase. >> Yeah, I touched upon this briefly earlier, which is from the model training perspective, Watson Studio running on Power hardware is very powerful, in terms of cutting down training time, right? But you've got to go beyond model building to how do you operationalize these models? How do I deploy these models at scale? How do I define workload management policies for these models, and connecting to their backbone. So that is part of this, and model explainability, we touched upon that, to eliminate this problem of how do I ingest data from different sources without having to manually oversee all of that. We need to manually apply auto-classification at the time of ingestion. Can I capture metadata around the model and reconcile data from different data sources as the data is being brought in? And can I apply ML to solve that problem, right? There is multiple applications of ML along this workflow. >> Talk about real quick, comment before we break, I want to get this in, machine learning has been around for a while now with compute and scale. It really is a renaissance in AI, it's great things are happening. But what feeds machine learning is data, the cleaner the data, the better the AI, the better the machine learning, so data cleanliness now has to be more real-time, it's less of a cleaning group, right? It used to be clean the data, bring it in, wrangle it, now you got to be much more agile, use speed of compute to make sure that you're qualifying data before it comes in, these machine learning. How do you guys see that rolling out, is that impacting you now? Are you thinking about it? How should people think about data quality as an input in machine learning? >> Well, I think the whole problem of setting up an application properly for data science and machine learning is really making sure that from the beginning, you're designing, and you're thinking about all of these problems of data quality, if it's the speed of ingestion, the speed of publication, all of that stuff. You need to think about the beginning, set yourself up to have the right elements, and it may not all be built out, and that's been a big strategy I've had with Morpheus. I've had a very small team working on it, but we think ahead and we put elements of the right components in place so data quality is just one of those things, and we're always trying to find the right tool sets that will enable use to do that better, faster, quicker. One of the things I'd like to do is to upscale and uplift the skillsets on my team, so that we are building the right things in the system from the beginning. >> A lot of that's math too, right? I mean, you talk about classification, getting that right upfront. Mathematics is-- >> And we'll continue to partner with Elenita and her team on this, and this helps us shape the direction in which our data science offerings go because we need to address complex enterprise challenges. >> I think you guys are really onto something big. I love the elite program, but I think having the small team, thinking about the model, thinking about the business model, the team model before you build the technology build-out, is super important, that seems to be the new model versus the old days, build some great technology and then, we'll put a team around it. So you see the world kind of being a little bit more... it's easier to build out and acquire technology, than to get it right, that seems to be the trend here. Congratulations. >> Thank you. >> Thanks for coming on. I appreciate it. theCUBE here, CUBE Conversations here. We're live in San Francisco, IBM Think. I'm John Furrier, Dave Vellante, stay with us for more day two coverage. Four days we'll be here in the hallway and lobby of Moscone North, stay with us.

>> Live from Las Vegas, it's theCUBE. Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome back. This is theCUBE in Las Vegas. VMworld 2018. Three days wall-to-wall coverage with two sets. We've got about 95 guests and so many sessions that people go to in this, happy to have one of the sessions that just went on come to give you a view into what people attending VMworld are talking about. I'm Stu Miniman with my cohost Justin Warren. Happy to welcome back to the program Sazzala Reddy, who's the Chief Technology Officer with Datrium. He's brought a customer along with him. His name is also Stuart like mine, spelled the proper Scottish way S-T-U-A-R-T, Lewallen, who is the Data Center Team Lead with Sonoma County. Gentleman, thanks so much for joining us. >> Happy to be here. >> Thanks for having us. >> Stuart, we're going to get to the tech and your role, but first of all Sonoma County. Some, I guess, interesting might not be the right thing to say, but it's been a lot of activity going on. Maybe you can share what's been happening in your neck of the woods. >> Last October, we had a little bit of excitement. We had some wildfires roll through. Burned about 140 square miles. Burned a little bit over 5,000 houses. Unfortunately, 42 people lost their life in the disaster. A lot of lessons were learned from that. >> Horrific. We've seen what's happened. I've got a lot of friends and some family in California. We've seen people far and wide that have been effected. How were you involved with this and I know you talked a little bit about it in your session? >> I was wakened in the middle of the night by a page, somebody letting me know hey, we got a problem here. They were telling me they were already evacuating. At that point, I knew it was something serious so I started getting my family ready for evacuation. Started trying to gather news about what was actually going on and what I had found was the fire had started in Napa County and was being driven by 16 mile an hour winds. It had moved 12 miles in the first three hours. Nobody was able to get a handle on it. Nobody really even knew which way it was going. That's what our emergency operations center was trying to track is where is it and where is it headed to try to get people there. >> We have a bit of familiarity with wildfires in Australia. It's well-known, it's horrific to be involved with. Tell us a little bit about how you were managing that situation day to day. What does that actually do to your normal day, it just goes out the window. What did that feel like, what was that like when you were in that situation? >> That's a fantastic question. My entire team was scattered all over Northern California. I was in San Anselmo, one of my guys was in Fresno, one of the guys had packed up his trailer and went to the beach. One of the guys was in an evacuation center and everybody was ready to go. Everybody was scattered. The county center, the fires had gotten within three blocks of our data center, so the county center had been evacuated and they wouldn't let us back. Everybody was working remote. That mostly worked OK, but again, we had a lot of learning points. From the after action, we learned a lot from what worked well and what didn't. >> Sazzala, people often talk about the human things, but technology's a lot of times involved in a lot of these emergencies, disaster recovery. I remember numerous times in my career when I worked on the vendor side where SWAT teams are helping and you've got the base product, but bring us in as to how technology plays in. >> If you talk to anybody and say what's your dream plan of DR, they can draw a nice picture, but the reality is it can be too expensive. Even if the money's not the problem, then it's painful to set up and it's fearful when you have a problem. You have fear, like is it going to work for me? If you still look at the innovation in the last decade, there was deduplication, VMware has changed infrastructure, cloud is here, AI is here, but still DR happens to be still one of those not moved forward in terms of innovation. That's something where we see the opportunity for us to help customers take to the next level. >> That's true, and maybe you can bring that in of going well how did Datrium actually help you in this situation with that DR aspect? What did that look like? >> During the event, there was really not a lot of involvement of Datrium other than the fact that one of their field engineers emailed me and said hey, do you need anything? Anything at all. I'll bring you a generator, water, food, whatever you need. Which was fantastic, you think who does that? Datrium does. Sorry, I had to get a little plug in there for you guys. Very happy with that. But, in the aftermath, when we were evaluating what we did good and what we did bad, what needs improvement and how do we do that? That's where they really came in and helped us. Helped us to get an easy way to move our data offsite. That was a fantastic product, and that's one we just started using and recently came out is the ability to back-up local data to AWS in a very simplistic way. >> If you have a data center, you also have a second data center most people set up so they can do DR for it. It's an expensive operation. It just sits there, does nothing, and then waiting for one day to show up and be used magically. If you change anything here, you got to go change something there. It is untenable kind of a model. It's a cost center for a CIOs. A lot of people I talk to, that's an easy one to eliminate and get rid of it. The cloud is here, let's take advantage of it. It's an on-demand infrastructure. Let's use that leverage for doing disaster recovery in the cloud. Because it's expensive, as you all know, cloud. There's a 80-page manual for AWS, just for pricing. It's expensive but for a week or two weeks of disaster, it is a perfectly awesome use case. There are a few things you need. It has to work well, it has to be cost effective, and it has to be operationally consistent. What I mean by that is that if you move from your workloads from your data center to the public cloud, it has to look the same. If it looks different from you, then you're not going to use it. Fundamentally, that's a thing where we have helped is that how do we bring that, how do you do back-ups to the cloud? How do you think about the orchestration software and how does that work? How do you bring up the workloads in the cloud so that it looks similar when you move from here to there? To some degree, cloud is a commodity, right? Let's use it that way. Let's take advantage of the hybrid cloud because it's already there. This is what Datrium is doing. >> A few more things that came out of our experience was we realized that failover had to be simple. The reason it had to be simple was exactly what I said before. You have no idea who you're going to have on your staff that's able to pull the trigger on this. It can't be some complex thing that only two people in your organization can do and it takes three days just to get it kicked off. It's got to be a push button, it really does these days. To make it effective. And it's got to be able to be tested. You've got to be able to validate that it's going to work. You can't wait and just hope and pray that when that day comes that it's going to work. I think, finally, it's got to be affordable. If it's not in your budget, it's not even a starter. You're going back to scripts and people running things. >> (laughing) The idea that you have to hope that that script that you wrote once is actually going to work in the middle of that disaster. You're going, oh yeah, that's right, I forgot to fix that bug. It's not something that you really want to do. Just being able to rely on something in that situation is really important. Stuart, you mentioned something before we went on to camera that you were quite interested in, which is coming from Datrium, which is around that movement of data into the cloud. Maybe you could tell us a little bit more about what that feature is and why you find it interesting. >> Think of it as like on offsite tape back-up, that's basically what it replaced. We used to spend, back in the day when we had mainframes, we spent a bazillion dollars having tapes shipped offsite. That's what everybody did back in the day. Then you went to on-site tapes that got moved, and then you went to disk arrays and you went to a remote disk array. That's kind of how things have transitioned and now instead of having a disk array somewhere else, why not just put it up in the cloud? AWS is very money-efficient as far as putting data there. If you don't need to do anything with it, which is what you're describing is your offsite back-up, it's a fantastic use case. >> This feature's coming out soon, I believe? >> It's coming out soon, we announced it-- >> And I'm sorry, I missed what it's called. >> Sorry? >> The feature? >> Yes, it's going to come out, it's called CloudShift. >> Thank you. >> It's going to be happening pretty soon. We're announcing it today. We have some demos in our booth, you can come by and check it out. If you look at applications, most people think about the application life cycle. There is the running of applications at high-performance, there's backing it up, and then doing DR. That's how the life cycle is. But if you look at the, no company has solved it end to end. I don't know why, but everybody seems to be doing piecemeal solutions, so you end up with five different products in your data center and they work together very well. Then you pray, like Murphy's Law, that it's all going to work together for you, when you actually have a problem, to get it resolved. That's kind of hoping for things to work well for you. >> Stuart, now you like five different products, right? >> No. (all laughing) I like one different product. The reality is everything's been cobbled together for years. Truly, if it was that simple, I'd be doing something else probably, they wouldn't pay me to do what I do. In this particular case, it's got to be simple. You can't rely on having your best or any particular people there in an emergency, so it's got to be simple. Has to be. >> Yeah. >> Having that (mumbles) platform really changes the game, basically. >> Stuart, talk to us, what are you looking for from the vendor community going forward? We talked about this one feature. Anything else on your wish list to make things simpler, as you've said, I think is one of the key criteria that you're looking for? >> You see all the commercials these days. Make it simple. People have simple buttons and everybody wants push button, everybody wants it simple. They want to make technology simple for everybody, for the average person. I think it's a laudable effort. I think that's where it has to go. It can't be all complex and it can't be the old days where you had guys that they were the only guys that knew anything and they became indispensable. These days, everybody has to know how to do things. You can't rely on one person cause, God forbid, what if they get hit by a bus? What if they just go to a different company and then you're left with this big hole? Simplicity is the key to any organization, really. >> You know what's simpler than one click? Zero clicks. Because one click requires you to read the manual. You'll just see what does it do for me? That's something, how we think about it, really try hard to do zero click. But it's very hard, though, because you have to build a lot more things into the system to imagine how this is going to work for the customer and imagine the best case scenario for the customer. >> It's certainly something, we're seeing a trend in a lot of companies here is automation and actually taking all of that manual effort out of things and having that automation actually be baked into the product as well, rather than relying on customers to have to automate their own environment. It just comes with it, which goes to that we just want an easy button. We want to have something which I don't even have to press the button, it presses its own buttons. >> We're living in the age of convenience. >> Yeah. >> (mumbles) Amazon to ship us products before we know it. (all laughing) >> I'll subscribe to that. >> I shudder to think what my house would fill up with there. (all laughing) >> Excellent. Sazzala and Stuart, really appreciate you giving the update. Stuart, we hope that things with the wildfires settle down, we know it's been challenging to deal with there. Thanks so much for sharing the story. >> Thanks for having me. >> Thanks for having us. >> Absolutely. Justin Warren, and I'm Stu Miniman, we'll be back with more coverage here from VMworld 2018. Thanks for watching theCUBE. (electronic tones)

>> Live, from Las Vegas! It's theCube! Covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome back everyone, it's theCube's live coverage in Las Vegas for VMworld 2018, it's theCube. We got two sets, 24 interviews per day, 94 interviews total. Next three days, we're in day two of three days coverage. It's our ninth year of covering VMworld. It's been great. I'm John Furrier with Dave Vellante, next guest, Cube alumni, number one in the leading boards right now, Sanjay Poonen did a great job today on stage, keynote COO for VMware. Great to have you back. Thanks for coming on. >> John and Dave, you're always so kind to me, but I didn't realize you've been doing this nine years. >> This is our ninth year. >> That's half the life of VMware, awesome. Unreal. Congratulations. >> We know all the stories, all the hidden, nevermind, let's talk about your special day today. You had a really, so far, an amazing day, you were headlining the key note with a very special guest, and you did a great job. I want you to tell the story, who was on, what was the story about, how did this come about? Tech for good, a big theme in this conference has really been getting a lot of praise and a lot of great feedback. Take us through what happened today. >> Well listen, I think what we've been trying to do at VMware is really elevate our story and our vision. Elevate our partnerships, you've covered a lot of the narrative of what we've done with Andy Jessie. We felt this year, we usually have two 90 minute sessions, Day One, Day Two, and it's filled with content. We're technical company, product. We figured why don't we take 45 minutes out of the 180 minutes total and inspire people. With somebody who's had an impact on the world. And when we brainstormed, we had a lot of names suggested, I think there was a list of 10 or 15 and Malala stood out, she never spoke at a tech conference before. I loved her story, and we're all about education. The roots of VMware were at Stamford Campus. Diane Greene, and all of that story. You think about 130 million girls who don't go to school. We want to see more diversity in inclusion, and she'd never spoken so I was like, you know what, usually you go to these tech conferences and you've heard somebody who's spoken before. I'm like, lets invite her and see if she would come for the first time, and we didn't think she would. And we were able to score that, and I was still a little skeptical 'cause you never know is it going to work out or not. So thank you for saying it worked, I think we got a lot of good feedback. >> Well, in your first line, she was so endearing. You asked her what you thought a tech conference, you said too many acronyms. She just cracked the place up immediately. >> And then you heard my response, right? If somebody tells me like that, you tell VMotion wrong she looked at me what? >> Tell them about our story, real quick, our story I want to ask you a point in question. Her story, why her, and what motivated you to get her? >> Those stories, for any of you viewers, you should read the book "I'm Malala" but I'll give you the short version of the story. She was a nine year old in the Pashtun Area of the Swat Valley in Pakistan, and the Taliban setted a edict that girls could not go to school. Your rightful place was whatever, stay at home and become a mom with babies or whatever have you. You cannot go to school. And her father ran a school, Moster Yousafzai, wonderful man himself, an educator, a grandfather, and says know what, we're going to send you to school. Violating this order, and they gave a warning after warning and finally someone shot her in 2012, almost killed her. The bullet kind of came to her head, went down, and miraculously she escaped. Got on a sort of a hospital on a plane, was flown to London, and the world if you remember 2012, the world was following the story. She comes out of this and she's unscathed. She looks normal, she has a little bit of a thing on the right side of her face but her brains normal, everything's normal. Two years later she wins the Nobel Peace Prize. Has started the Malala Fund, and she is a force of nature, an amazing person. Tim Cook has been doing a lot with her in the Malala Fund. I think that actually caught my attention when Tim Cook was working with her, and you know whatever Apple does often gets a little bit of attention. >> Well great job selecting her. How's that relevant to what you guys are doing now, because you guys had a main theme Tech for Good? Why now, why VMware? A lot of people are looking at this, inspired by it. >> There are milestones in companies histories. We're at our 20 year birthday, and I'm sure at people's birthday they want to do big things, right? 20, 30, 40, 50, these decades are big ones and we thought, lets make this year a year to remember in various things we do. We had a 20 year anniversary celebration on campus, we invited Diane Greene back. It was a beautiful moment internally at Vmware during one of our employee meetings. It was a private moment, but just with her to thank her. And man, there were people emotional almost in tears saying thank you for starting this company. A way to give back to us, same way here. What better way to talk about the impact we're having in the community than have someone who is of this reputation. >> Well we're behind your mission 100%, anything you need. We loved the message, Tech for Good, people want to work for a mission driven company. People want to buy >> We hope so. >> from mission driven companies, that stated clear and the leadership you guys are providing is phenomenal. >> We had some rankings that came out around the same time. Fortune ranked companies who are changing the world, and VMware was ranked 17th overall, of all companies in the world and number one in the software category. So when you're trying to change the world, hopefully as you pointed out it's also an attractor of talent. You want to come here, and maybe even attractor of customers and partners. >> You know the other take-away was from the key note was how many Cricket fans there are in the VMworld Community. Of course we have a lot of folks from India, in our world but who's your favorite Cricketer? Was it Sachin Tendulkar? (laughs) >> Clearly you're reading off your notes Dave! >> Our Sonya's like our, >> Dead giveaway! >> Our Sonya's like our Cricket Geek and she's like, ask him about Sachin, no who's your favorite Cricketer, she wants to know. >> Sachin Tendulkar's way up there, Shayuda Free, the person she likes from Pakistan. I grew up playing cricket, listen I love all sports now that I'm here in this country I love football, I love basketball, I like baseball. So I'll watch all of them, but you know you kind of have those childhood memories. >> Sure >> And the childhood memories were like she talk about, India, Pakistan games. I mean this was like, L.A. Dodgers playing Giants or Red Socks, Yankee's, or Dallas Cowboys and the 49ers, or in Germany playing England or Brazil in the World Cup. Whatever your favorite country or team rivalry is, India Pakistan was all there more, but imagine like a billion people watching it. >> Yeah, well it was a nice touch on stage, and I'd say Ted Williams is my favorite cricketer, oh he plays baseball, he's a Red Sock's Player. Alright Sanjay, just cause your in the hot seat, lets get down to business here. Great moment on stage, congratulation. Okay Pat Gelsinger yesterday on the key note talked about the bridges, VMware bridging, connecting computers. One of the highlights is kind of in your wheelhouse, it's in your wheelhouse, the BYOD, Bring Your Own Device bridge. You're a big part of that. Making that work on on the mobile side. Now with Cloud this new bridge, how is that go forward because you still got to have all those table stakes, so with this new bridge of VMware's in this modern era, cloud and multicloud. Cluely validated, Andy Jassy, on stage. Doing something that Amazon's never done before, doing something on premise with VMware, is a huge deal. I mean we think it's a massive deal, we think it's super important, you guys are super committed to the relationship on premises hybrid cloud, multicloud, is validated as far as we're concerned. It's a done deal. Now ball's in your court, how are you going to bring all that mobile together, security, work space one, what's your plan? >> I would say that, listen on as I described in my story today there's two parts to the VMware story. There's a cloud foundation part which is the move the data center to the cloud in that bridge, and then there's the desk job move it to the mobile. Very briefly, yes three years of my five years were in that business, I'm deeply passionate about it. Much of my team now that I put in place there, Noah and Shankar are doing incredible jobs. We're very excited, and the opportunity's huge. I said at my key note of the seven billion people that live in the world, a billion I estimate, work for some company small or big and all of them have a phone. Likely many of those billion have a phone and a laptop, like you guys have here, right? That real estate of a billion in a half, maybe two billion devices, laptops and phones, maybe in some cases laptop, phone, and tablets. Someone's going to manage and secure, and their diverse across Apple, Google, big option for us. We're just getting started, and we're already the leader. In the data center, the cloud world, Pat, myself, Raghu, really as we sat three years ago felt like we shouldn't be a public cloud ourselves. We divested vCloud Air, as I've talked to you on your show before, Andy Jassy is a friend, dear friend and a classmate of mine from Harvard Business School. We began those discussions the three of us. Pat, Raghu, and myself with Andy and his team and as every quarter and year has gone on they become deeper and deep partnerships. Andy has told other companies that VMware Amazon is the model partnership Amazon has, as they describe who they would like to do business more with. So we're proud when they do that, when we see that happen. And we want to continue that. So when Amazon came to us and said listen I think there's an opportunity to take some of our stack and put it on premise. We kept that confidential cause we didn't want it to leak out to the world, and we said we're going to try'n annouce it at either VMworld or re:Invent. And we were successful. A part with these projects is they inevitably leak. We're really glad no press person sniffed it out. There was a lot of speculation. >> Couldn't get confirmation. >> There was a lot of speculation but no one sniffed it out and wrote a story about it, we were able to have that iPhone moment today, I'm sorry, yesterday when we unveiled it. And it's a big deal because RDS is a fast growing business for them. RDS landing on premise, they could try to do on their own but what better infrastructure to land it on than VMware. In some cases would be VMware running on VxRail which benefits Dell, our hardware partners. And we'll continue doing more, and more, and more as customers desire, so I'm excited about it. >> Andy doesn't do deals, as you know Andy well as we do. He's customer driven. Tell me about the customer demand on this because it's something we're trying to get reporting on. Obviously it makes sense, technically the way it's working. You guys and Andy, they just don't do deals out of the blue. There's customer drivers here, what are those drivers? >> Yeah, we're both listening to our customers and perhaps three, four, five years ago they were very focused on student body left, everybody goes public cloud. Like forget your on premise, evaporate, obliterate your data centers and just go completely public. That was their message. >> True, sweep the floor. >> Right, if you went to first re:Invent I was there on stage with them as an SAP employee, that's what I heard. I think you fast forward to 2014, 2015 they're beginning to realize, hey listen it's not as easy. Refactoring your apps, migrating those apps, what if we could bring the best of private cloud and public cloud together enter VMware and Amazon. He may have felt it was harder to have those cultivations of VMware or for all kinds of reasons, like we had vCloud Air and so on and so forth but once we divested that decision culminations had matured between us that door opened. And as that door opened, more culminations began. Jointly between us and with customers. We feel that there are customers who want many of those past type of services of premise. Cause you're building great things, relational database technology, AI, VI maybe. IoT type of technologies if they are landing on premise in an edge-computing kind of world, why not land on VMware because we're the king of the private cloud. We're very happy to those, we progress those discussion. I think in infrastructure software VMware and Amazon have some of the best engineers on the planet. Sometimes we've engineers who've gone between both companies. So we were able to put our engineering team's together. This is a joint engineering effort. Andy and us often talk about the fact that great innovation's built when it's not just Barny go to Marketing and Marketing press releases this. The true joint engineering at a deep level. That's what happened the last several months. >> Well I can tell you right now the commitment I've seen from an executive level and deep technology, both sides are deep and committed to this. It's go big or go home, at least from our perspective. Question I want to ask you Sanjay is you're close to the customer's of VMware. What's the growth strategy? If you zoom out, look down on stage and you got vSAN, NSX at the core, >> vSANjay (laughs) >> How can you not like a product that has my name on it? >> So you got all these things, where's the growth going to come from, the merging side, is the v going to be the stable crown jewels at NSX? How do you guys see the growth, where's it going to come from? >> Just kind of look at our last quarter. I mean if you peel back the narrative, John and Dave, two years ago we were growing single digits. Like low single digits. Two, three percent. That was, maybe the legacy loser description of VMware was the narrative everyone was talking about >> License revenue was flattish right? >> And then now all of sudden we're double digits. 12, 15 sort of in that range for both product revenue. It's harder to grow faster when you're bigger, and what's happened is that we stabilize compute with vSphere in that part and it's actually been growing a little bit because I think people in the VMware cloud provider part of our business, and the halo effect of the cloud meant that as they refresh the servers they were buying more research. That's good. The management business has started to grow again. Some cases double digits, but at least sort of single digits. NSX, the last few order grew like 30, 40%. vSAN last year was growing 100% off a smaller base, this year going 60, 70%. EUC has been growing double digits, taking a lot of share from company's like Citrix and MobileIron and others. And now, also still growing double digits at much bigger paces, and some of those businesses are well over a billion. Compute, management, end-user computing. We talked about NSX on our queue forming called being a 1.4 billion. So when you get businesses to scale, about a billion dollar type businesses and their sort of four, training five that are in that area, and they all get to grow faster than the market. That's the key, you got to get them going fast. That's how you get growth. So we focus on those on those top five businesses and then add a few more. Like VMware Cloud on AWS, right now our goal is customer logo count. Revenue will come but we talked on our earnings call about a few hundred customers of VMware Cloud and AWS. As that gets into the thousands, and there's absolutely that option, why? Because there's 500,000 customers of VMware and two million customers of Amazon, so there's got to be a lot of commonality between those two to get a few thousand. Then we'll start caring about revenue there too, but once you have logos, you have references. Containers, I'd like to see PKS have a few hundred customers and then, we put one on stage today. National Commercial Bank of Jamaica. Fantastic story of PKS. I even got my PKS socks for this interview. (John laughs) >> So that give you a sense as to how we think, there will be four, five that our businesses had scale and then a few are starting to get there, and they become business to scale. The nature of software is we'll always be doing this show because there will be new businesses to talk about. >> Yeah, hardware is easy. Software is hard, as Andy Patchenstien said on theCUBE yesterday. Congratulations Sanjay and all the success, you guys are doing great financially. Products looking really good coming out, the bloom is rising from the fruit you guys have harvested, coming together. >> John if I can say one last thing, I shared a picture of a plane today and I put two engines behind it. There's something I've learned over the last years about focus of a company, and I joked about different ways that my name's are pronounced but at the core of me there's a DNA. I said on stage I'd rather not be known as smart or stupid but having a big heart. VMware, I hope is known by our customers as having these two engines. An engine of innovation, innovating product and a variety of other things. And focused on customer obsession. We do those, the plane will go a long way. >> And it's looking good you guys, we can say we've been to Radio Event, we've been doing a lot of great stuff. Congratulations on the initiative, and a great interview with you today on doing Tech for Good and sharing your story. Getting more exposure to the kind of narratives people want to hear. More women in tech, more girls in tech, more democratization. Congratulations and thanks so much for sharing. >> Thank you John and Dave. >> Appreciate you being here. >> Sanjay Poonen, COO of VMware. Friend of theCUBE, Cube Alumni, overall great guy. Big heart and competitive too, we know that from his Twitter stream. Follow Sanjay on Twitter. You'll have a great time. I'm John Furrier with Dave Vellante, stay with us for more coverage from day two live, here in Las Vegas for VMware 2018. Stay with us. (tech music)

lie from las vegas it's the cube covering discover 2016 las vegas brought to you by Hewlett Packard Enterprise now here's your host Jeff Frick hey Jeff Rick here with the cube we're in Las Vegas at the hpe discovered 2016 the first year that HP Enterprises has discovered in Vegas they flipped the switch before they went to a London last year so we're excited to be back a lot of changes a lot more green squares all over the place green frames so it's pretty exciting but you know obviously what's at the forefront of all this is data in big data what's happening with data so we're excited to get somebody from the trenches who's out working with customers first off crystal and obviously VP biz dev cube alumni been on all the time we'll see him in Boston how long Krista that show the end of August a little further and then ken Chris the director of data analytics for pwc welcome thank you nice to be here absolutely so welcome so data a lot of talk about data in kind of this this this change in data as it's kind of a liability back in the day like what am I going to do with all this stuff i'm going to sample to now I've got the data but that's not really enough you need to get the data to information you got to get the information to incite then you got to get the insight into actionable information so what are you seeing out in the real world with some of the customers that you work with so I think that a lot of what we're seeing with customers out there I mean I was walking through the floor earlier today and to see all the things that HP is doing with various technologies the people are partnering with very impressive but fundamentally at the end of the day a lot of those technologies are producing data and like you said clients and customers are trying to figure out how do i generate value from this how do I get it in the right hands of the people that can make decisions what am I seeing out in the industry today a lot of stuff particularly around customers personalization better service client experience we have the whole concept of CX which is that customer experience end-to-end don't just worry about you know how am I going to retain customers and prevent churn but also go up the the lifecycle and figure out how to attract more customers using data personalizing my service offerings improving my digital products things of that nature I'd love to get your perspective there's a lot of talk of you know there's never enough data scientists right how we're going to get enough data scientist but it takes me back to the day when there's never going to be enough chauffeur's this car thing is never going to take off I mean are you seeing the you know this kind of this vision of getting the data into the decision-makers hands getting it out of the hallowed halls of just the data science are you seeing that happening in the real world and what are some of the ways that that happened definitely I mean we've talked a long time about the concept of the data scientists being that individual that is like the unicorn it doesn't exist right so what we talk more about now is like pulling together those SWAT teams where you have someone that understands the data someone that understands the business problem someone that understands deep analytics spin teams like that up go out and find the answers yeah that's funny that you said that because we hear that a lot that data science is not an individual's it's a team sport you know you really have to bring a lot of people to bear and it's it's not just this this hallowed thing down a mahogany row at the very end it's actually getting that in you know and getting dirty with a lot of folks yeah that and I would also say another thing that's going to help with regards to the whole data scientist crunch is machine learning robotics things of that nature artificial intelligence I definitely think that that's something that people kid about as something that's far down the future but I think it's coming very quickly and something that customer sorry excuse me company should pay attention today so Chris you've been playing in the space forever you've seen a lot of transformation wonder if you could speak specifically to how the cloud has really impacted this whole kind of big data meme in this big data discussion because now suddenly it's a lot of people that have a lot of access to a lot of stuff that aren't necessarily connected to the VPN you know back at corporate headquarters that enable that to go out well it's allowed a lot of customers to iterate faster to try new things more quickly set them up take them down it's gotten business people involved one of the things can and I talked about in the session we just gave together was about how this is becoming more of a business discussion so our partnership with solution partners like PwC become more and more important because it's not always just IT people these days driving the data lakes it's now you're starting to see other sea level execs you know CFO the CMO starting to drive some of these initiatives and cloud-based solutions make those things more accessible so we're definitely seeing both quicker iteration and more business involvement the other thing we hear Kendall a lot about was back in the day right you had to sample you know you couldn't store all the data you couldn't process all the data yeah there was a lot of sampling going on right now that's that's changing you know you can store the data you can grab a lot more than you even think that you might need today but what you might need tomorrow and you can run big processes against big data sets that you couldn't do before you seen that kind of manifest itself in the market oh yeah all over the place i mean my specialty is within the entertainment media and communications business so when you talk about the cable companies and phone companies out there digesting set-top box data data coming off of phones if you go into the world where you know people Internet of Things sensor data just that you know we call it data to lose where where where it's just coming in Fast and Furious and the folks that are responsible for maintaining protecting and serving that data up are challenged more and more today and there's a lot of business pressure because people that use you know apps on their phone don't understand why can't I do the same thing with data that I know that we have to makes it make it insightful and actionable and allow me to do my job right but then kind of the dark side of that is if you have too much data you know our argues are you swimming in data that's not necessarily an indication of the change that you're trying to impact or you know it's not an indicator of something that you can take action so how are people kind of filtering through to get the right data to the right people at the right time yeah I mean Chris mentioned this and one of his previous answers but the attack that we take and that we stress with our clients is to take a business capabilities driven approach so when you think about the guy in the field that's responsible for sales or the person in the call center that's responsible for customer service taking the viewpoint of how what data do they need how do they need it served up how do they need it parsed and when do they need it that is the key to the approach to figuring out how do i find the signals through the noise what data is really worthwhile and do i really need to protect and make sure it gets served up versus this stuff i can keep versus this stuff i really don't need right and of course the other big trend is is an actual word spark summit we had another crew up there is this whole move to real time right and streaming data and not not you know grabbing capturing reviewing and looking back but watching it in real time and taking action while it's dreaming totally changing the business yeah fascinating and big data are used you know you use that car analogy before and if you heard Meg in the keynote say I think every driverless car is going to create three library of congress's worth of in fourth of data so and obviously it's very important right so you want to aggregate the data about what's going on with if you're running a fleet of cars but obviously you also have to know what's going on in the car and that's that's about as real time as it gets so and so these things are complementary big data and fascinator highly complementary and we're seeing a lot more activity out at the edge and obviously we made some announcements here both in terms of partners and some of our initiatives at HB around that here so Ken last question video we hear over and over and over the videos and increasing proportion of the total traffic on the Internet nobody ever thought that people would hang out on their phones and watch Game of Thrones or an NFL game or go warriors and you're in the media comes or the cube that's right well we knew they would watch a cute Chris um they're only 18 minutes but that's a huge huge stressor on resources a huge stress Iran on capacity storage networking and yet the customers want it right the expectation is going to be there it's going to look good so how is that impacting the guys on the back end that are responsible for delivering a good experience but they also have pricing pressure and they've got a ton of demands on their resources yeah yeah it's funny that you bring that up I walked into my house last week and hell-bent on having some good family time with my wife and kids and the TV was on and all of them had multiple devices actually iPads and iPhones that they were and everything was sucking off the internet which was kind of amusing to me but that's exactly your point and a lot of the companies that we're working with in the communications industry specifically their main goal and focuses to make sure that the pipes are big enough that they're utilized properly to make sure people have the best experience possible so utilizing the technology not only capture the data but really deep analytics to pinpoint where are my peaks and troughs and utilization and usage going to be how do i divert and make sure the right resources are available again also that can provide the best customer experience just can't over provision it like bananas oh yeah but it's expensive so you don't want those pipes of the empty either that's the thing you want to have enough capacity but you don't want / build that so it's it's an analytics challenge this analytics challenge and it's I always think of the old AT&T ma belle you know problem on Mother's Day everybody calls mom on mother's day back in the day you had to build the pipe to support mother's day even though most people aren't calling or not on Mother's Day well can Chris thanks for stopping by can give you last word we're looking forward to in the next six months as you know see some of the exciting things your customers are working on yeah i mean the technological advances are really great i will say that customers especially business consumers of the data getting very much more smarter much more savvy er so the demands on the folks serving up that data storing that data and protecting that data are going to be you know more and more crucial but it's it's just great business to be a part of it's great to see it's great to see the technology and some of the stuff that you guys are doing so we're proud to be part of it and happy to be here thanks for stopping by Ken Chris crystal and I'm Jeff Rick you're watching the cube we'll see you next time