>>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.