>>Yeah. Okay. Now we're going to dig deeper into HP es moral and try to better understand how it's going to impact customers. And with me to do that are Robert Christensen is the vice president strategy in the office of the C, T. O. And Kumar Srikanth is the chief technology officer and head of software both, of course, with Hewlett Packard Enterprise. Gentlemen, welcome to the program. Thanks for coming on. >>Good seeing you. Thanks for having us. >>Always. Great. Great to see you guys. So, Esmeralda, kind of a interesting name. Catchy name. But tomorrow, what exactly is H P E s bureau? >>Yeah. It's indeed a catchy name. Our branding team done a fantastic job. I believe it's actually a derivation from Esmeralda. The Spanish for Emerald Berlin. Supposed to have some very mystical powers. Um, and they derived as moral from there, and we all actually, initially that we heard it was interesting. Um, so as well was our effort to take all the software, the platform tools that HB has and provide these modern operating platform to the customers and put it under one brand. It has a modern container platform. It has a persistent stories distribute the date of February. It has been foresight, as many of our customers similar, So it's the think of it as a container platform offering for modernization of the civilization of the customers. >>Yeah, it's an interesting to talk about platform, so it's not a lot of times people think product, but you're positioning it as a platform, so it has a broader implications. >>That's very true. So as the customers are thinking of this civilization, modernization containers and microservices, as you know there has become, has become the stable whole. So it's actually a container orchestration platform. It offers open source proven. It is as well as the persistence always bolted to >>so by the way, s moral, I think emerald in Spain, I think in the culture it also has immunity powers as well. So immunity >>from >>lock in and all those other terrible diseases. Maybe it helps us with covid to rob Robert. When you talk to customers, what problems do you probe for that that is immoral. Can can do a good job solving. >>Yeah, they That's a really great question because a lot of times they don't even know what it is that they're trying to solve for, other than just a very narrow use case. But the idea here is to give them a platform by which they can bridge both the public and private environment for what to do an application development specifically in the data side. So when they're looking to bring Container Ization, which originally got started on the public cloud and has moved its way, I should say, become popular in the public cloud and has moved its way on premises. Now Esmeralda really opens the door to three fundamental things. But how do I maintain an open architecture like you're referring to some low or oh, no lock in of my applications And there were two. How do I gain a data fabric or data consistency of accessing the data so I don't have to rewrite those applications when I do move them around and then, lastly, where everybody is heading down, the real value is in the AI ML initiatives that companies are are really bringing that value of their data and locking the data at where the data is being generated and stored. And so the is moral platform is those multiple pieces that I was talking about stacked together to deliver those solutions for the client. >>So come on, what's the How does it work? What's the sort of I p or the secret sauce behind it all? What makes HP different? >>Continuing our team of medical force around, uh, it's a moral platform for optimizing the data Indians who were close. I think I would say there are three unique characteristics of this platform. Number one is actually provides you both an ability to run stable and stateless were close under the same platform, and number two is as we were thinking about. Unlike analogues, covenant is open source. It actually produce you all open source government as well as an orchestration behind you. So you can actually you can provide this hybrid, um, thing that drivers was talking about. And then actually we built the work flows into it. For example, we're actually announced along with Esmeralda MLS, but on their customers can actually do the work flow management. Our own specifically did the work force. So the magic is if you want to see the secrets of is all the efforts that have been gone into some of the I p acquisitions that HBs the more years we should be. Blue Data bar in the nimble emphasize, all these pieces are coming together and providing a modern digitalization platform for the customers. >>So these pieces, they all have a little bit of a machine intelligence in them. Yeah, People used to think of a I as the sort of separate thing, having the same thing with containers, right? But now it's getting embedded in into the stack. What? What is the role of machine intelligence or machine learning in Edinburgh? >>I would take a step back and say, You know this very well. They're the customer's data amount of data that is being generated, and 95% or 98% of data is machine generated, and it has a serious amount of gravity, and it is sitting at the edge, and we were the only the only one that edge to the cloud data fabric that's built. So the number one is that we are bringing computer or a cloud to the data. They're taking the data to the cloud like if you go, it's a cloud like experience that provides the customer. Yeah, is not much value to us if we don't harness the data. So I said this in one of the blood. Of course, we have gone from collecting the data era to the finding insights into the data so that people have used all sorts of analysis that we are to find data is the new oil to the air and the data. And then now you're applications have to be modernized. And nobody wants to write an obligation in a non microservices fashion because you want to build the modernization. So if you bring these three things, I want to have a data. Gravity have lots of data. I had to build an area applications and I want to have an idea those three things I think we bring together to the customs. >>So, Robert, let's stay on customers from it. I mean, you know, I want to understand the business impact, the business case. I mean, why should all the you know, the cloud developers have all the fun? You mentioned that you're bridging the cloud and on Prem, uh, they talk about when you talk to customers and what they are seeing is the business impact. What's the real drivers for them. >>That's a great question because at the end of the day I think the reason survey that was that cost and performance is still the number one requirement for the real close. Second is agility, the speed of which they want to move. And so those two are the top of mind every time. But the thing we find in as moral, which is so impactful, is that nobody brings together the silicon, the hardware, the platform and all that stacked together work and combined, like as moral does with the platforms that we have and specifically, you know, when we start getting 90 92 93% utilization out of ai ml workloads on very expensive hardware, it really, really is a competitive advantage over a public cloud offering which does not offer those kind of services. And the cost models are so significantly different. So we do that by collapsing the stack. We take out as much intellectual property, give me, um, as much software pieces that are necessary. So we are closest to the silicon closest to the applications bring into the hardware itself, meaning that we can inter leave the applications, meaning that you can get to true multi tendency on a particular platform that allows you to deliver a cost optimized solution. So when you talk about the money side, absolutely. There's just nothing out there and then on the second side, which is agility. Um, one of the things that we know is today is that applications need to be built in pipelines. Right? This is something that has been established now for quite some time now. That's really making its way on premises. And what Kumar was talking about was, how do we modernize? How do we do that? Well, there's going to be something that you want to break into Microservices and containers. There's something you don't now the ones that they're going to do that they're gonna get that speed and motion etcetera out of the gate. And they can put that on premises, which is relatively new these days to the on premises world. So we think both will be the advantage. >>Okay, I want to unpack that a little bit. So the cost is clearly really 90 plus percent utilization. I mean, come on. You know, even even a pre virtualization. We know what it was like even with virtualization, you never really got that high. I mean, people would talk about it, but are you really able to sustain that in real world workloads? >>Yeah, I think when you I think when you when you make your exchangeable currency into small pieces, you can insert them into many areas. And we have one customer was running 18 containers on a single server and each of those containers, as you know, early days of data. You actually modernized what we consider we won containers of micro B. Um, so if you actually build these microservices and you have all anti affinity rules and you have rationing formulas all correctly, you can pack being part of these things extremely violent. We have seen this again. It's not a guarantee. It all depends on your application and your I mean, as an engineer, we want to always understand how this can be that sport. But it is a very modern utilization of the platform with the data and once you know where the data is, and then it becomes very easy to match those >>now. The other piece of the value proposition that I heard Robert is it's basically an integrated stack, so I don't have to cobble together a bunch of open source components. It's there. There's legal implications. There's obviously performance implications that I would imagine that resonates is particularly with the enterprise buyer, because they have the time to do all this integration. >>That's a very good point. So there is an interesting, uh, interesting question that enterprise they want to have an open source, so there is no lock in. But they also need help to implement and deploy and manage it because they don't have expertise. And we all know that Katie has actually brought that AP the past layer standardization. So what we have done is we've given the open source and you write to the covenant is happy, but at the same time orchestration, persistent stories, the data fabric, the ai algorithms, all of them are bolted into it. And on the top of that, it's available both as a licensed software and run on Prem. And the same software runs on the Green Lake so you can actually pay as you go and you don't we run it for them in in a collar or or in their own data center. >>Oh, good. I was one of my latter questions, so I can get this as a service paid by the drink. Essentially, I don't have to install a bunch of stuff on Prem and pay >>a perpetual license container at the service and the service in the last Discover. And now it's gone production. So both MLRS is available. You can run it on friends on the top of Admiral Container platform or you can run inside of the Green Bay. >>Robert, are there any specific use case patterns that you see emerging amongst customers? >>Yeah, absolutely. So there's a couple of them. So we have a really nice relationship that we see with any of the Splunk operators that were out there today. Right? So Splunk containerized their operator. That operator is the number one operator, for example, for Splunk, um, in the i t operation side or notifications as well as on the security operation side. So we found that that runs highly effective on top of his moral on top of our platforms that we just talked about what, uh, Kumar just talked about, but I want to also give a little bit of backgrounds to that same operator platform. The way that the Admiral platform has done is that we've been able to make highly active, active with a check availability at 95 nines for that same spark operator on premises on the kubernetes open source, which is, as far as I'm concerned. Very, very high end computer science work. You understand how difficult that is? Uh, that's number one. Number two, you'll see spark just a spark. Workloads as a whole. All right. Nobody handles spark workloads like we do. So we put a container around them, and we put them inside the pipeline of moving people through that basic, uh uh, ml ai pipeline of getting a model through its system through its train and then actually deployed to our MLS pipeline. This is a key fundamental for delivering value in the data space as well. And then, lastly, this is This is really important. When you think about the data fabric that we offer, um, the data fabric itself, it doesn't necessarily have to be bolted with the container platform to container at the actual data. Fabric itself can be deployed underneath a number of our for competitive platforms who don't handle data. Well, we know that we know that they don't handle it very well at all. And we get lots and lots of calls for people say, Hey, can you take your as Merrill data for every and solve my large scale, highly challenging data problems, we say yes. And then when you're ready for a real world full time but enterprise already, container platform would be happy to privilege. >>So you're saying if I'm inferring correctly, you're one of the values? Is your simplifying that whole data pipeline and the whole data science science project? Unintended, I guess. >>Okay, >>that's so so >>absolutely So where does the customer start? I mean, what what are the engagements like? Um, what's the starting point? >>It's being is probably one of the most trusted enterprise supplier for many, many years, and we have a phenomenal workforce of the both. The PowerPoint next is one of the leading world leading support organization. There are many places to start with. The right one is Obviously all these services are available on the green leg as we just start apart and they can start on a pay as you go basis. We have many customers that. Actually, some of the grandfather from the early days of pleaded and map are and they're already running, and they actually improvised on when, as they move into their next generation modernization, um, you can start with simple as metal container platform with persist with the story compared to this operation and can implement as as little as $10 and to start working. Um, and finally, there is a a big company like HP E. As an enterprise company defined next services. It's very easy for the customers to be able to get that support on the day to operation. >>Thank you for watching everybody's day volonte for the Cube. Keep it right there for more great content from Esmeralda. >>A mhm, okay.

>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen. You buy bread. >> Oh, good morning. Welcome back to our live coverage here on the Cube of Red Hat Summit twenty nineteen, along with two men. Timon, I'm John Walls were in Boston. A delightful day here in Beantown. Even made more so by the presidents of Jim White, her's president, CEO, Red hat. Jim, Thanks for joining us. Number one. Number two. What else could go right for you here this week? This has just been a great show. Great keynotes. You had great regulatory news on Monday. I mean, you've got a four leaf clover in that pocket there. I think for him >> to tell you what the weather is holding up well, for us, you're right with great partnership announcements. Amazing product launches. You have been a red hat, but eleven years now and this is only my third rail launch, right? When we deliver it, we commit to long lives. And so But it's awesome to be a part of that. And we had all the engineers on stage. I can't imagine how it could get any better. >> You >> win the lottery >> Oh, yeah? Well, yes. This one step at a time here. Relate and open share for we'LL get to those just a little bit. Let's go back to the keynote last night. First life, you have CEOs of IBM and Microsoft. Very big statements, right? We know about the IBM situation. I think a lot of people got a charge out of that a little bit. You know, Jenny commenting about have a death wish for this company. And I have thirty four billion reasons why I wanted to succeed. But a very good message. I think about this. This linkage that's about to occur, most likely. And the thought going forward from the IBM side of the fence? >> Yeah. I thought it was really good toe have her there. Not only to say that, you know, we're obviously bought it toe to make it grow, but also really making a statement about how important open source is to the future of IBM, right? Yeah. What became clear to me early on when we were talking is this is a major major. I would say that the company might be too strong a word, but it is a major kind of largest possible initiative around open source than you can imagine. And so I can't imagine, uh, imagine a better kind of validation of open source with one large technology companies the world basically going all in with us on it >> to talk about validation of open source, such a nadella up on stage. If you had told me five years ago that within a week I would see Satya Nadella up on stage with the CEO of'Em wear and then a week later up on stage with the CEO, right hat, I'm like, Are we talking about the same Microsoft? This is not the Microsoft that I grew up with on and worked with soap. We're talking your team and walking around. It wasn't just, you know, he flew in from Seattle. I did. The casino left. He was meeting with customers. There's a lot of product pieces that are going together, explain a little bit, that kind of the depth of the partnership and >> what we've made. Just tremendous progress over the last several years with Microsoft, you know, started back in two thousand fifteen. Where were you across certified hyper visors, And that's kind of a basic you know, let's work together. Over the last couple of years, it's truly blossomed into a really good partnership where, you know, I think they've and we both gotten over this, you know, Lennox versus Windows thing. And you know, I say, we've gotten over. I think we both recognized, you know, we need to serve our customers in the best possible way on that clearly means is two of the largest infrastructure software providers working closely together and what's been interesting. As we've gone forward, we find more and more common ground about how we could better serve our customers. Whether that's you know what might sound mundane. That's a big deal sequel server on Realm and setting benchmarks around that or dot net running on our platforms. Now all the way to really be able to deliver a hybrid cloud with a seamless experience with open shift from, you know, on premise to to Azure and having Deutsche Bank on State's twenty five a thousand containers running in production, moving back and forth to your >> you know what getting customers to change is challenging. You know, it's a little surprising even after that this morning to be like Oh, yeah. Let me pull up windows and log in and do all this stuff. We've talked to you a lot over the years about culture, you know, loved your book. We've talked a lot about it, but I really enjoyed. Last night is I mean, you had some powerful customers stories talking about how red hats helping them through the transformation. And like the Lockheed one for me was like And here's how we failed at first because we tried to go from waterfall to scrum Fall on. Do you know he definitely had the audience you're after? >> Yeah, I really wanted to make Mikey No talking about it called How we have so many great What's to talk about your rela a open ship for bringing all those capabilities from for OS. But I really wanted Teo talk about the hell, because that actually is the hardest part for customers. And so having kind of customers back in back to back to back, talking about success stories and failures to get there, and it really is about culture. And so that's where we called the open source way, which we kind of coin, which is, you know, beyond the code. It's, you know, meritocracy and how you get people to work together and collaboration. That's what more and more our customers want to talk about. In fact, I'd say ninety percent of the customer meetings I'm in, which are, you know, more CIA level meetings they're all about. Tell me about culture. Tell me how you go about doing that. Yeah, We trust the technology's gonna work. We don't have that issue with open source anymore. Everybody assumes you're gonna have open source. It's really how do you actually make that effective? And so that's what I really wanted to tow highlight over the course of the evening. >> You know, there was a lot of conversation, too. And you have your talking to Jenny about culture last night that you have multiple discussions over the course of the negotiation or of the conversations. So it wasn't just some cursory attention This I mean, the both of you had a really strong realization that this has to work in terms of this, you know, merging basically of philosophies and whatever. But you've had great success, right with your approach. So if you can share a little bit about how those cops is ations How you went through what transpired? Kind of how we got to where we are Now that you know, we're on the cusp of successful moment for you. Yeah, >> sure. So, yeah. I mean, from day one, that was the center of the discussion, I think early on. So year Agos, um, IBM announced, contain arising their software on open shift. And I think that's when the technical light went off about Hey. Having the same bits running across multiple clouds is really, really valuable in open shifts. The only real way to do that. And yes. Oh, Arvind was here from IBM on stage talking about that. And so I think technically, it was like, OK, ding, this makes sense. Nobody else could do it. And IBM, with their capabilities and services integration center. Just lot of strategic logic, I think the difficult part. Even before they approached this. Now, kind of looking back on it, having all these discussions with him now it's okay. Well, culturally, how do we bring it together? Because, you know, we both have strong cultures, mean IBM has a famous culture. We do that air very, very, very different. And so from the moment Jenny first approached me literally, you know, Hey, we're instant this, But let's talk about cultural, how we're going to make this work because, you know, it is a lot of money to spend on a company with No I p. And so you know, I think as we started to work through it, I think what we recognized is we can celebrate the strength of each other's cultures, and you know the key. And this is to not assume that there's one culture that's right for everything. We have a culture hyper optimized for collaboration and co creation, whether that's upstream with our source communities or downstream with our customers or with our employees and how that works. And that's great. Let's celebrate that for what it is. And, you know, IBM kind of run some of those big, most mission critical systems in the world, you know, on mainframes and how you do that looks and feels different. And that's okay. And it's okay to be kind of different. But together, if we can share the same values if we can, you know, share the same desire to serve our customers and put them first how we go about doing it. It's okay if those aren't exact. And as we got more comfortable with that, um, that's when I got more comfortable with it. And then, most importantly for me is we talk about culture. But a lot of our culture comes from the fact that we're truly a mission kind of purpose driven company, right? We're all about making open source the default choice in the world. And you know, to some extent remember, have these conversations with senior teams like, Hey, we were going to think we're going to change the world. You know? How better can we propel this for? This is such a huge platform to do it, and yet it's going to be hard. But aren't we here to do hard things? >> So it talked about it, You know, it's it's always been difficult selling when you don't have the. There's been a lot of discussions in the ecosystem today, as companies that build I p with open source and some of the models have been changing and some of the interactions with some of the hyper scale companies and just curious when you look at that, it's you know, related to what you're doing, what feedback you have and what you're seeing. >> Yeah. Look, first, I'LL say, I can't talk about that as an interested observer because our model is different than a lot of open source software companies. You know, Paul talked about in his keynote today, and we talked a lot about you know, our models one hundred percent open source, where we take open source code, typically getting involved in existing communities in creating life cycles, et cetera, et cetera, et cetera. And so that model's worked well for us. Other open source companies where I think this is more of a challenge with the hyper scale er's right more of the software themselves. And obviously they therefore need to monetize that in a more direct way. You know, our sins are businessmen always say it's a really bad business model the right software and give it away. You know, that's not what we do where hundreds and open source, but you know, if you look at our big communities were, you know, ten to twenty percent of the contribution, because we want to rely on communities. The issue for those companies that are doing Maur. The code contribution themselves is there's a leakage in the open source license, which is, you know, the open source, like the viral licenses. You know, if you make changes and you redistribute, you have toe also, you know, redistribute your code as well. And redistribution now is to find in a hyper scale is just different. So there's kind of a leakage in the model. I think that ultimately gets fixed by tweaks to the licenses. I know it's really controversial, and companies do it, but, you know, Mongo has done it. I think you'LL see continuing tweaks to the length the licenses would still allow broad use, but kind of close that loophole if you want to call that a loophole. >> Yeah, well, it's something that you know as observers. We've always watched this space and you know, when you talk about Lennox, you know, you've created over three billion dollar company, But the ripple effects of Lennox has been huge. And I know you've got some research that we want to hear about when we've looked at like the soup space. When you look at the impact of big data and now where is going you know, the hoodoo distribution was a very, very small piece of that. So, you know, talk a little bit about the ripples. Is some new research that >> way? Had some research that was that we commission to say, What is the impact of Lenin's right hand and press linens? And then we were all blown away. Ten trillion dollars. I mean, so this isn't our numbers or we had really experts do this and e. I mean, it really blew us away. But I think what happens is if you think about how pervasive it is in the economy, it's ultimately hard to have any transaction done that doesn't somehow ripple into technology and technology. Days primarily built around Lynn IQ. So in red headed President X is the leader, so it just pervades and pervades. When you look at the size in the aperture and you make a really good point around, whether it's a duper lennox, I mean, we could look a red hat, the leader and Lennox and we're, you know, less than four billion dollars of revenue. But we've created this massive ecosystem the same thing with the Duke. You think about how big an impactful. Big data and the analytics and built on it are massive. The company's doing are only a couple hundred million dollars, and I will say I've become comfortable with I'd say, five years ago, I used to say in my glass half empty day I'd be like we're creating all of this value yet we're just only getting this little tiny sliver. Um, I've now flip that around and say My glass Half full days I look and say Wow, with this lever we have with this little bit of investment were fundamentally changing the world. And so everybody's benefiting in a much larger scale around that. And when you think about it, that aperture is something really, really, really excited >> about. Well, you talk about, you know where the impact will be. Talk about Cloud, that the wave of container ization, you know, Where do you see that ending up? You know, I look, you know, Cooper Netease is one of those things. There's a lot of excitement and rightfully so. It was going to change the market, but it's not about a Cuban aunties distribution. It's going to be baked into every platform out there. Yeah, gunships doing quite well. And you know all the cloud providers, your partner with them and working with them. It's less fighting to see who leads and Maura's toe. How do we all work together on this? >> Well, you know, I think that's >> the great thing about ah well functioning, mature, open source projects is it behooves everybody to share. Now we'LL compete ultimately, you know, kind of downstream. But it who's everybody to share and build on this kind of common kind of component. And, you know, like any good open source project, it has a defined set of things that it does. I think you hit on a really important point. Cooper Netease is such an important layer. Doesn't work without Lennox, right? I mean, lyrics is, you know, containers or Lennox. And so how do you think about putting those pieces to gather manageability and automation thinks like answerable. And so, you know, at least from our perspective, it's How do you take these incredible technologies that are cadence ng, you know, at their own pace and are fundamentally different but can't work unless you put them all together? Which to us, you know, that creates a big opportunity to say, How do I take this incredible technology that thousands of, of really technically Swiss cave people are working on and make it consumable? Archer Traditional model has been like linnet, simply saying We're going to snap shot. We're going created to find life we're going back for, you know, do patching for what? And we still do that. But there's now an added sir sort of value, something like open shift, where you can say, Okay, we could put these pieces together in life cycle and together. And, you know, we see instances all the time where an issue with Cooper Netease requires, you know, a change analytics. And so being able to life cycle in together, I think we can really put out a platform where we literally now we're saying in the platform you're getting the benefits of millions of people working on overtime on Lenox with tens of thousands people working on Cooper, Netease and the Learnings are all been kind of wrapping back into a platform. So our ability to do that is it kind of open source continues to move up. The stack is really, really exciting. >> Now. You were talking about transformative technologies on DH. How great it is to be a part of that right now. You alluded to that last night in the keynote. So you're talking about this, You know your history lessons. You know how much you love doing that? Your ki notes and you know, the scientific method Industrial Revolution open source. Just without asking you to re can you are a recount. All that. Just give us an idea about how those air philosophically aligned it. How you think those air open source follows that lineage, if you will, where it is fundamentally changing the world. It is a true global game change. Yeah, And >> so the point last night was a really kind of illustrate how a change in thinking can fundamentally change the world we live in. And so what I talked about just kind of quickly is so the scientific method developed and kind of the fifteen hundreds ish time frame was a different way to discover knowledge. So it goes from kind of dictates coming down from, you know, on high, too. Very simple hypothesis, experiment, observation of the results of the things that go through that process and stand the test of time and become what we consider knowledge right? And that change lead immediately to an explosion of innovation, whether that with the underpinnings of the industrial revolution or enlightenment, what we've done in medicine, whole bunch of areas. And yeah, the analogy I came to was around well, the old way we just try to innovate constrains us in a more open approach is a fundamentally better way to innovate. But what I found so interesting in and I think you picked up on it if it didn't emphasize this much, wanted to excite and having a lot of time, its many of the same characteristics of scientific discovery. So the idea of you know, independence anybody could actually do this pinpoints the importance of experimentation and learning those Air Corps components of, you know, tef ops and agile and open source, right? It's very, uh, in the end, the characteristics are actually quite similar as well. I think that's just fascinating to see happen. >> So e think about that. And if you could bring it back to the customers you're talking to, you have a lot of executive conversation, said You focus a lot on the how is really challenging. We understand. You know, the organizational structure of most companies goes back over a hundred years to military. So you know, what you see is some of the one of the biggest challenges that, you know, executive thieves we're facing these days. And, you know, how are they getting past that? Stuck? >> Yeah. And so, you know, I think the simple is way to state. The problem, which I hear over and over again, is we tried an agile transformation, and it failed because our culture was already and cultures Mohr of, ah always tell the executor when they said to me, It's like, Okay, but recognized cultures and output, not an input. And it's an output of leadership behaviors, beliefs, values what's been rewarded over time. So if you want your culture to change, actually to think about changing the way that you lied and manage and broadly, the structures, the hierarchies, the bureaucratic systems that we have in place today are really good at driving efficiency in a static environment. So if you're trying to slightly take a little bit of cost out building a car, you start with what you did last year. You get a bunch of scientists are consultants to look at it, and then you direct some fairly small changes. So the structure were in places other wrong with them. When value creation was about standardization of economies of scale. The hierarchies work really, really well to distribute tasks and allow specialization and optimization. The problem is now most value creation. It's requiring innovation. It's how doe I innovate and how I engage with my customer. You know the example I used a couple years ago? Its summit was, you know, the average cars use ninety minutes today. So if you think about how to reduce the cost of transfer port ation, is it taking two percent out of the cost of building a car? Or is it figuring out whether it's ride sharing or other ways? Teo. A fractional ownership. Whether it is to increase the average utilization of the car, it's clearly the ladder. But you can't do that in about bureaucratic hierarchical system that requires creativity and innovation, and the model to do that requires injecting variants in. That's what allows innovation to happen. So as leaders, you have to show up and say, all right, how do I encourage descent, you know, how do I accept failure? Right. So this idea of somebody tries something and it fails. If you fire him, nobody's gonna try anything again. But experimentation by definition requires a lot of failures and how you learn from it. So how do you build that into the culture where as executives you say holding people accountable doesn't mean, you know, firing him or beating him up. If they make a mistake, it's how do I encourage the right level of risk taking in mistakes, you know, even down to the soft side. So you know, how do you hold somebody accountable in an agile scrum, right. Your leaders have to be mature enough to sit down, have a conversation. Not around here. The five things you were supposed to do and you did forum. So you get in eighty right now, you can't say exactly what they need to do because it's a little blurry. So you have to have leaders mature enough to sit down and have a conversation with somebody is I think you got an eighty. Thank you. Got an eighty because here's what you did well, and here's what you didn't. But it's subjective. And how do you build that skill and leaders? They oughta have those subjective conversations, right? That sounds really, really soft, but it's not gonna work if you don't have leaders who can do that right? And so that's why it's hard. Because, you know, changing peep people is hard. And so that's why I think so. Many CEOs and executives want to talk about it. But that's what I mean by it's a soft side. And how do you get that type of change to happen? Because if you do that, pick ours honestly, pick somebody else's, you know, agile Davis with methodologies. They'LL work if you have a culture, this accepting of it >> before they let you go. There were two things to our quick observations about last night. Number one rule Samant hitch up on the licensing, so I know you've got your hands full on that. Good luck with that. You mentioned licensing a little bit ago, and I learned that thirty four billion dollars is a good deal. Well, right, that's what you said I heard it from are absolutely well. Things >> were a separate entity. We don't have licenses. So I don't know how we would go into an l A >> given. We don't have a license to sell. So got some expectations setting >> we need to do with our customers and then, you know, but separately, You know, I think people do forget that Red Hat is a not only a really fast growing company were also really profitable company. Most of the other software companies that are growing at our pace on a gap basis makes little to no money. We have because we get the leverage of open source, we actually generate a very large amount of free cash flow. And if you actually not to get the details of the financials. But we look at our free cash flow generation in our growth, I would argue, was a smoking good deal. That thirty four. I was asking for a lot more than that. >> You could had smoking good the last night that was gonna work to give thanks for the time. >> It's great to be here. >> Thank you. Thank you for hosting us here. Great opportunities on this show for I know that's exciting to see two but continued success. We wish you all >> thanks. So much. Thank you for being here. It's great to have you, >> Jim. White House joining us back with more live coverage here on the Cube. You are watching our coverage here in Boston of Red Hat Some twenty nineteen. Well,