>> Hello everyone. Welcome to theCUBEs coverage of Compute Engineered for your Hybrid World sponsored by HPE and Intel. Today we're going to dive into advanced performance of VDI with the fourth gen Intel Zion scalable processors. Hello I'm John Furrier, the host of theCUBE. My guests today are Alan Chu, Director of Data Center Performance and Competition for Intel as well as Denis Kondakov who's the VDI product manager at HPE, and also joining us is Cynthia Sustiva, CAD/CAM product manager at HPE. Thanks for coming on, really appreciate you guys taking the time. >> Thank you. >> So accelerating VDI to the Edge. That's the topic of this topic here today. Let's get into it, Dennis, tell us about the new HPE ProLiant DL321 Gen 11 server. >> Okay, absolutely. Hello everybody. So HP ProLiant DL320 Gen 11 server is the new age center CCO and density optimized compact server, compact form factor server. It enables to modernize and power at the next generation of workloads in the diverse rec environment at the Edge in an industry standard designed with flexible scale for advanced graphics and compute. So it is one unit, one processor rec optimized server that can be deployed in the enterprise data center as well as at the remote office at end age. >> Cynthia HPE has announced another server, the ProLiant ML350. What can you tell us about that? >> Yeah, so the HPE ProLiant ML350 Gen 11 server is a powerful tower solution for a wide range of workloads. It is ideal for remote office compute with NextGen performance and expandability with two processors in tower form factor. This enables the server to be used not only in the data center environment, but also in the open office space as a powerful workstation use case. >> Dennis mentioned both servers are empowered by the fourth gen Intel Zion scale of process. Can you talk about the relationship between Intel HPE to get this done? How do you guys come together, what's behind the scenes? Share as much as you can. >> Yeah, thanks a lot John. So without a doubt it takes a lot to put all this together and I think the partnership that HPE and Intel bring together is a little bit of a critical point for us to be able to deliver to our customers. And I'm really thrilled to say that these leading Edge solutions that Dennis and Cynthia just talked about, they're built on the foundation of our fourth Gen Z on scalable platform that's trying to meet a wide variety of deployments for today and into the future. So I think the key point of it is we're together trying to drive leading performance with built-in acceleration and in order to deliver a lot of the business values to our customers, both HP and Intels, look to scale, drive down costs and deliver new services. >> You got the fourth Gen Z on, you got the Gen 11 and multiple ProLiants, a lot of action going on. Again, I love when these next gens come out. Can each of you guys comment and share what are the use cases for each of the systems? Because I think what we're looking at here is the next level innovation. What are some of the use cases on the systems? >> Yeah, so for the ML350, in the modern world where more and more data are generated at the Edge, we need to deploy computer infrastructure where the data is generated. So smaller form factor service will satisfy the requirements of S&B customers or remote and branch offices to deliver required performance redundancy where we're needed. This type of locations can be lacking dedicated facilities with strict humidity, temperature and noise isolation control. The server, the ML350 Gen 11 can be used as a powerful workstation sitting under a desk in the office or open space as well as the server for visualized workloads. It is a productivity workhorse with the ability to scale and adapt to any environment. One of the use cases can be for hosting digital workplace for manufacturing CAD/CAM engineering or oil and gas customers industry. So this server can be used as a high end bare metal workstation for local end users or it can be virtualized desktop solution environments for local and remote users. And talk about the DL320 Gen 11, I will pass it on to Dennis. >> Okay. >> Sure. So when we are talking about age of location we are talking about very specific requirements. So we need to provide solution building blocks that will empower and performance efficient, secure available for scaling up and down in a smaller increments than compared to the enterprise data center and of course redundant. So DL 320 Gen 11 server is the perfect server to satisfy all of those requirements. So for example, S&B customers can build a video solution, for example starting with just two HP ProLiant TL320 Gen 11 servers that will provide sufficient performance for high density video solution and at the same time be redundant and enable it for scaling up as required. So for VGI use cases it can be used for high density general VDI without GP acceleration or for a high performance VDI with virtual VGPU. So thanks to the modern modular architecture that is used on the server, it can be tailored for GPU or high density storage deployment with software defined compute and storage environment and to provide greater details on your Intel view I'm going to pass to Alan. >> Thanks a lot Dennis and I loved how you're both seeing the importance of how we scale and the applicability of the use cases of both the ML350 and DL320 solutions. So scalability is certainly a key tenant towards how we're delivering Intel's Zion scalable platform. It is called Zion scalable after all. And we know that deployments are happening in all different sorts of environments. And I think Cynthia you talked a little bit about kind of a environmental factors that go into how we're designing and I think a lot of people think of a traditional data center with all the bells and whistles and cooling technology where it sometimes might just be a dusty closet in the Edge. So we're defining fortunes you see on scalable to kind of tackle all those different environments and keep that in mind. Our SKUs range from low to high power, general purpose to segment optimize. We're supporting long life use cases so that all goes into account in delivering value to our customers. A lot of the latency sensitive nature of these Edge deployments also benefit greatly from monolithic architectures. And with our latest CPUs we do maintain quite a bit of that with many of our SKUs and delivering higher frequencies along with those SKUs optimized for those specific workloads in networking. So in the end we're looking to drive scalability. We're looking to drive value in a lot of our end users most important KPIs, whether it's latency throughput or efficiency and 4th Gen Z on scalable is looking to deliver that with 60 cores up to 60 cores, the most builtin accelerators of any CPUs in the market. And really the true technology transitions of the platform with DDR5, PCIE, Gen five and CXL. >> Love the scalability story, love the performance. We're going to take a break. Thanks Cynthia, Dennis. Now we're going to come back on our next segment after a quick break to discuss the performance and the benefits of the fourth Gen Intel Zion Scalable. You're watching theCUBE, the leader in high tech coverage, be right back. Welcome back around. We're continuing theCUBE's coverage of compute engineer for your hybrid world. I'm John Furrier, I'm joined by Alan Chu from Intel and Denis Konikoff and Cynthia Sistia from HPE. Welcome back. Cynthia, let's start with you. Can you tell us the benefits of the fourth Gen Intel Zion scale process for the HP Gen 11 server? >> Yeah, so HP ProLiant Gen 11 servers support DDR five memory which delivers increased bandwidth and lower power consumption. There are 32 DDR five dim slots with up to eight terabyte total on ML350 and 16 DDR five dim slots with up to two terabytes total on DL320. So we deliver more memory at a greater bandwidth. Also PCIE 5.0 delivers an increased bandwidth and greater number of lanes. So when we say increased number of lanes we need to remember that each lane delivers more bandwidth than lanes of the previous generation plus. Also a flexible storage configuration on HPDO 320 Gen 11 makes it an ideal server for establishing software defined compute and storage solution at the Edge. When we consider a server for VDI workloads, we need to keep the right balance between the number of cords and CPU frequency in order to deliver the desire environment density and noncompromised user experience. So the new server generation supports a greater number of single wide and global wide GPU use to deliver more graphic accelerated virtual desktops per server unit than ever before. HPE ProLiant ML 350 Gen 11 server supports up to four double wide GPUs or up to eight single wide GPUs. When the signing GPU accelerated solutions the number of GPUs available in the system and consistently the number of BGPUs that can be provisioned for VMs in the binding factor rather than CPU course or memory. So HPE ProLiant Gen 11 servers with Intel fourth generation science scalable processors enable us to deliver more virtual desktops per server than ever before. And with that I will pass it on to Alan to provide more details on the new Gen CPU performance. >> Thanks Cynthia. So you brought up I think a really great point earlier about the importance of achieving the right balance. So between the both of us, Intel and HPE, I'm sure we've heard countless feedback about how we should be optimizing efficiency for our customers and with four Gen Z and scalable in HP ProLiant Gen 11 servers I think we achieved just that with our built-in accelerator. So built-in acceleration delivers not only the revolutionary performance, but enables significant offload from valuable core execution. That offload unlocks a lot of previously unrealized execution efficiency. So for example, with quick assist technology built in, running engine X, TLS encryption to drive 65,000 connections per second we can offload up to 47% of the course that do other work. Accelerating AI inferences with AMX, that's 10X higher performance and we're now unlocking realtime inferencing. It's becoming an element in every workload from the data center to the Edge. And lastly, so with faster and more efficient database performance with RocksDB, we're executing with Intel in-memory analytics accelerator we're able to deliver 2X the performance per watt than prior gen. So I'll say it's that kind of offload that is really going to enable more and more virtualized desktops or users for any given deployment. >> Thanks everyone. We still got a lot more to discuss with Cynthia, Dennis and Allen, but we're going to take a break. Quick break before wrapping things up. You're watching theCUBE, the leader in tech coverage. We'll be right back. Okay, welcome back everyone to theCUBEs coverage of Compute Engineered for your Hybrid World. I'm John Furrier. We'll be wrapping up our discussion on advanced performance of VDI with the fourth gen Intel Zion scalable processers. Welcome back everyone. Dennis, we'll start with you. Let's continue our conversation and turn our attention to security. Obviously security is baked in from day zero as they say. What are some of the new security features or the key security features for the HP ProLiant Gen 11 server? >> Sure, I would like to start with the balance, right? We were talking about performance, we were talking about density, but Alan mentioned about the balance. So what about the security? The security is really important aspect especially if we're talking about solutions deployed at the H. When the security is not active but other aspects of the environment become non-important. And HP is uniquely positioned to deliver the best in class security solution on the market starting with the trusted supply chain and factories and silicon route of trust implemented from the factory. So the new ISO6 supports added protection leveraging SPDM for component authorization and not only enabled for the embedded server management, but also it is integrated with HP GreenLake compute ops manager that enables environment for secure and optimized configuration deployment and even lifecycle management starting from the single server deployed on the Edge and all the way up to the full scale distributed data center. So it brings uncompromised and trusted solution to customers fully protected at all tiers, hardware, firmware, hypervisor, operational system application and data. And the new intel CPUs play an important role in the securing of the platform. So Alan- >> Yeah, thanks. So Intel, I think our zero trust strategy toward security is a really great and a really strong parallel to all the focus that HPE is also bringing to that segment and market. We have even invested in a lot of hardware enabled security technologies like SGX designed to enhance data protection at rest in motion and in use. SGX'S application isolation is the most deployed, researched and battle tested confidential computing technology for the data center market and with the smallest trust boundary of any solution in market. So as we've talked about a little bit about virtualized use cases a lot of virtualized applications rely also on encryption whether bulk or specific ciphers. And this is again an area where we've seen the opportunity for offload to Intel's quick assist technology to encrypt within a single data flow. I think Intel and HP together, we are really providing security at all facets of execution today. >> I love that Software Guard Extension, SGX, also silicon root of trust. We've heard a lot about great stuff. Congratulations, security's very critical as we see more and more. Got to be embedded, got to be completely zero trust. Final question for you guys. Can you share any messages you'd like to share with the audience each of you, what should they walk away from this? What's in it for them? What does all this mean? >> Yeah, so I'll start. Yes, so to wrap it up, HPR Proliant Gen 11 servers are built on four generation science scalable processors to enable high density and extreme performance with high performance CDR five memory and PCI 5.0 plus HP engine engineered and validated workload solutions provide better ROI in any consumption model and prefer by a customer from Edge to Cloud. >> Dennis? >> And yeah, so you are talking about all of the great features that the new generation servers are bringing to our customers, but at the same time, customer IT organization should be ready to enable, configure, support, and fine tune all of these great features for the new server generation. And this is not an obvious task. It requires investments, skills, knowledge and experience. And HP is ready to step up and help customers at any desired skill with the HP Greenlake H2 cloud platform that enables customers for cloud like experience and convenience and the flexibility with the security of the infrastructure deployed in the private data center or in the Edge. So while consuming all of the HP solutions, customer have flexibility to choose the right level of the service delivered from HP GreenLake, starting from hardwares as a service and scale up or down is required to consume the full stack of the hardwares and software as a service with an option to paper use. >> Awesome. Alan, final word. >> Yeah. What should we walk away with? >> Yeah, thanks. So I'd say that we've talked a lot about the systems here in question with HP ProLiant Gen 11 and they're delivering on a lot of the business outcomes that our customers require in order to optimize for operational efficiency or to optimize for just to, well maybe just to enable what they want to do in, with their customers enabling new features, enabling new capabilities. Underpinning all of that is our fourth Gen Zion scalable platform. Whether it's the technology transitions that we're driving with DDR5 PCIA Gen 5 or the raw performance efficiency and scalability of the platform in CPU, I think we're here for our customers in delivering to it. >> That's great stuff. Alan, Dennis, Cynthia, thank you so much for taking the time to do a deep dive in the advanced performance of VDI with the fourth Gen Intel Zion scalable process. And congratulations on Gen 11 ProLiant. You get some great servers there and again next Gen's here. Thanks for taking the time. >> Thank you so much for having us here. >> Okay, this is theCUBEs keeps coverage of Compute Engineered for your Hybrid World sponsored by HP and Intel. I'm John Furrier for theCUBE. Accelerate VDI at the Edge. Thanks for watching.

(bright upbeat music) >> Welcome back to theCube's coverage of HPE's Green Lake announcement. We've been following the caves of Green Lake's announcement for several quarters now, and even years. And we're going to look at cloud adoption and frameworks to help facilitate cloud adoptions. You know, in 2020, the world was on a forced march to digital and there was a lot that they didn't know. Big part of that was how to automate, how to reduce your reliance on physically, manually and plugging things in. And so, customers need an adoption framework to better understand and how to de-risk that journey to the cloud. And with me to talk about that are Alexia Clements, who's the Vice President at Worldwide go to market for GreenLake cloud services at HPE and Alexei Gerasimov who's the vice president of Hybrid Cloud Delivery advisory and professional services at Hewlett Packard Enterprise. Folks, welcome to theCube. >> Alexia: Thanks so much for having us. >> You're very welcome. So, Alexei, what is a cloud adoption framework? How does that all work? >> Gerasimov: Yeah, thanks Dave. So the framework is a structured approach to elevate the conversation, to help our customers get outcomes. So we've been helping customers adopt the benefits in the most of IT for a decade. And we've noticed that they basically focus on eight key areas as they transform to cloud-like capabilities. It's a strategy and governance, it's innovation, people, a dev ops applications, operations security, and data. So we've structured our framework around those core components to help our customers get value. Because end of the day, it's all about changing the way they operate. To get the advantage of all of it. >> Yes. So you can't just pave the cow path and kind of plug your existing process. There's a lot that's unknown, as I said up front. So, so Alexia, maybe you could talk a little bit more about some of the real problems that you're solving with customers that you see in the field. >> Alexey: Yeah, absolutely. So most customers are going through some form of digital transformation and these transformations are difficult and they need a structured approach to help them through that journey. I kind of like to think of it as a recipe to make a meal. So you need to know what ingredients to buy and what are the steps to perform to make that meal. >> Okay. So when you talk to customers, what do you, what do you tell them? That's in it for them after the, after you've actually successfully helped them deploy? What are they telling you? >> Yeah, well, they're telling they now have reached their business outcomes and they're, you know, they're a more agile organization. >> What's the experience look like when you, when you go through one of these journeys and you, you apply the adoption framework, can you sort of paint a picture for us? >> Yeah, absolutely. So every customer is in some sort of transformation, like Alexia said, that transformation implies you've got to know where you start and again, know where you're going. So the experience traditionally is customers need to understand what are my current hybrid cloud capabilities? What do I have, what am I missing? What's lacking and then determine where do you want to go? And in order to get from point A to point B, they have to get a prescriptive approach. So the framework sort of breaks down their path from where they are to their desired maturity. And it takes them in the very prescriptive path to get there. >> So you start with an assessment, you do a gap analysis based on their skill sets. I presume you identify what's possible, help them understand, you know, best practice, which they may not achieve, but this is kind of their north star. Right? And then do you help? How do you help them fill those gaps? Because are skills gaps. Everybody talks about that today. You guys presumably can provide additional services to do that, but so can you add a little bit color to that scope? >> Yeah, yeah, absolutely. And so to your point, the first is a maturity level. So once you figure out the maturity level, you understand what needs to be done. So if you look at our domain, the eight domains that I mentioned and the framework, people is a big one, right? Most of the folks are struggling with people's skills and organizational capabilities. And it's so because it's an operating model change, right? And people are the key component to this operating model change. So we help our customers figure out how do we achieve that optimal operating level and operating a model maturity. And that could be on-prem that could be on public cloud. That could be hybrid. That could be at the edge. And yeah, we, if we can HP, the framework, by the way is pretty, pretty open and pretty objective. If we can help our customers address and achieve their sales gaps great. If we can not directly, then we can have a partner that can help them, you know, plug in something that we don't have. >> Are you finding that, that in terms of the maturity that most people have some kind of experience with, with cloud, but they're struggling to bring that cloud experience to their on-premise state. They don't want to just shove everything into the cloud. Right. So, what does that kind of typical journey look like for folks? I know there's--it's a wide spectrum, or you've got people that are maybe more mature. Maybe some of the folks in financial services got more resources, but can you sort of give us a sense as to what the typical, the average. >> Oh yeah yeah yeah, absolutely. By the way. So that give you a customer example, perfect example of a large North American integrated energy company. They decided to go cloud fresh, like a lot of companies. that wants to do cloud first. And why? The reason was agility. So they started going to the cloud and they realized in order to get agility, you can't just go to you, pick your public CSP, you got to change the way to operate. So they brought us in and they asked, could you help me figure out how we can change the organization? So we actually operate on the proper level of maturity. So we brought our team in. We help them figure out what do we need to look at? We need to look at operations. We need to look at people. We need to look at applications, and we need to figure out what gives you the best value. So when all said and done, they realized that their initial desire of, you know, public first or cloud first, wasn't really public cloud first. It's a way to operate. So now the customer is in three different public CSPs. They're on-prem, there are at edge and everywhere. So that's the focus. Yeah. >> Is the scope predominantly the technical organization. How deep does it go into the, to the business? Is it obviously the application development team is involved, but how deep into the business does this go? The framework. >> Right, and it's absolutely not a technology focused, the whole concept areas, it's outcomes based, and it's a results based. So if you look at the framework, there's really not a single element of the framework that says tech, like storage or compute. No, it's its people, its data, it's business value, strategy and governance, because the goal for us is being objective is we're just trying to help them address the outcomes. Not necessarily to give them more tech. >> So Alexia, I like that answer because it's a wider scope as, I mean, if we just focused on the tech and that's the swim lane, it'd be a lot easier. But as we all know, it's the people in the process that are really the hard part. So that, that makes the challenge for customers greater. You're hurting more cats. So what are the, some of the obstacles that potentially you help customers before they dive in understand. >> Yeah. So we're giving them a roadmap on where they need to go. So we're like I mentioned that recipe, so we're really trying to identify what is their strategy and where do they, what are the outcomes that they're trying to drive and help them on a street, you know, with that path to meet those outcomes. So some of those, I mean, every customer's a little bit different. I mean, we had one customer, which was a, one of the largest hospitals in north America and they, they would needed to, they wanted to go to the cloud, but they realized they couldn't put all of their patient data on the cloud. So what we did was we helped them in changing their operating model and really look to see how does that, how do they need to what's that end game for them, and actually help redo their operating model to have some in the cloud and some on-prem and, and really identify, you know, where they needed to go for their roadmap. So that was an obstacle that they had, hey, we can't put all this stuff out there. How does that now need to work in this new world? >> I would think the data model is a big deal here. I mean, you just gave an example where there's a, there's a, there's a governance and compliance aspect to it. So thinking about that example, did they have to change the way in which they provided federated governance was that presumably identify whose whose responsibility that was to adjudicate, but also had to get the, the implementers to follow that's the, how does that all work? Is it just the deep conversations? And then you figure out how to codify it or. >> No. So what so we have, so through those eight domains that Alexia mentioned, we go through, step-by-step how they need to think about it. And within mind, what are their business outcomes and goals that they're trying to achieve? So really identifying how they need to change that operating model to meet those business outcomes. >> So what's the output, it's a plan, right. That's tailored to the customer. Is that, is that correct? And, and then sort of assistance in implementing downstream or what do they get? >> Yeah, yeah, absolutely. Just to piggyback to what Alexia said, the alignment, the early alignment, the strategy and governance, as you mentioned, this is probably the most important thing, because everybody says we want to be cloud first, but what does that mean? Cloud first means different things to everyone. So we said, give him a plan. The first we'll help with figure out is what does that mean for you? Because at the end of the day, you're not going to the cloud for the sake of cloud, or anywhere you go into the cloud to get some sort of value. So what's that alignment. So the plan is supposed to help you on your road to that value, right? So we'll help them figure out what I want to do, why, for what purpose, what's going to actually address my business value. So yes, they will get a plan as part of it. But more importantly, they get, they get a set of activities, communication plans, which by the way, another block that you got to address. >> Dave: Huge. >> Yeah. >> Yeah. I mean, a lot of executives tell me, look, if you don't change your operating model and go to the cloud, yeah. You're talking, you know, nickels and dimes. If you want to get telephone numbers, you know, big companies, you want to get into bees with billions, you have to change the operating model. And the problem that they tell me is a lot of times the corner offices, okay, we're doing this, but everybody in the fat middle says, what are we doing? >> Right. And now more than ever, I mean, customers need to look at that model like a more modern operating model to realize the benefits of cloud capabilities, whether that be at the edge, their data centers, their colos cloud. So they really need to look at that. And what we've seen is with our framework, we're really helping customers accelerate their business outcomes. De-risk their transformation, and really optimize that cloud operating model. >> It's that alignment you reducing friction within the organization, confusing confusion. When people don't know which direction they're going, they'll just going to go wherever they're pointed. Right. Right. >> And you back to the alignment. So you've got alignment and you mentioned communication. You have to communicate up and down and left and right across the organization because that's one of the most probably ignored elements of any transformation lots of people don't know. So you got to communicate. And then you have to actually measure and report on how they, you know, how the transformation is happening. So we can help in all three of those. >> Especially when everybody's remote. Yeah. Right. And then I said, hey, these digital transformations, there's so much, that's unknown. >> Alexia: Right. It's difficult. >> It's a lot of new. And so you also have to, I presume part of the plan is, Hey, you're not, it's not going to be a hundred percent perfect. So you have to have. >> Alexia: Right. And you're constantly iterating on that plan. >> What does this have to do with GreenLake? >> Alexia: Yeah. So, I mean, GreenLake is HPE's you know, cloud everywhere. And what we're really doing is this framework is helping customers with that path to get that cloud-like experience and as a service model. And so the framework is really helping clients understand where do they need to go and what GreenLake solutions can help them get there. >> So the fundamental assumption of not every cloud player necessarily bad, I would say most hyperscalers is, hey, ultimately, all the data and the workloads are going to go to the cloud, that's their operating premise. So they all have an operating framework to facilitate that. >> Alexia: Right. >> It's, it's tongue in cheek, but it's true. So, but everybody has one of these. How was yours different? >> Yeah. So like, like you said, there's lots of different, you know, frameworks out there, but what we're really focused on is meeting those business goals and outcomes for clients. So we didn't focus on the technology. Like we mentioned what we were really focusing around. I mean, we kind of learned early on that every customer has technical capabilities, applications, data in multiple clouds, on-prem in colos and at the edge. So we didn't focus on like just the technology. So it's really driving business outcomes and their goals and, and the tech, all those frameworks that we just mentioned, they're really specifically driving a particular technology tool or vendor implementing a particular technology or vendor. >> So we've talked about outcomes a lot, but I wonder if we could peel the onion on that. So, you know, the highest level outcome is I want to increase revenue, cut costs, drop to the bottom line, increase shareholder value, improve employee experiences and retention, make customers happier, grow my business. I mean, those are, I mean, I, I don't know a lot of businesses that don't... >> Alexia: Right. >> want to do that, So. Okay. That's cool. But then I'm imagining you really start to peel the layers and say, okay, this is how we're going to get there. And you get down to specific objectives as to the, how is that sort of how this works? >> Right, and that's due to echo at Alexia. So that's exactly why ours is different. We're not focusing on how to adopt Microsoft or AWS or Alibaba with focusing on how we can deliver the customer experience or a better revenue, you know, or, you know, increase the value for the consumer for whatever the company will help him. So the framework we'll look at that and figure out how do we actually address it, whether it's on public cloud, whether it's on prem, whether it's at the edge. >> You mentioned Alexia, that something, hey, if we don't have the skills, we can get a partner who does, a big company. You got a huge partner network. So for example, if you might not have necessarily a deep industry expertise, that's where you might lean on a partner or is that, is that a good example or is there a better one? >> Yes and we know. We're not going to just like you mentioned AWS or Microsoft, Alibaba thing that everything will go to public cloud. I don't believe so, but at the same time we know not everything will stay on-prem. So the combination of on-prem, the edge, you know, private cloud and public cloud is what the customers are after. So our partners could be either third party, system integrator that can help us implement something or even the public CSPs, because we know our customers have capabilities everywhere. So the question becomes, how can we holistically address their needs, whether it's on-prem, whether it's in public cloud. >> Great. Guys, thanks so much. >> Alexia: Thank you. Thanks for having us. Appreciate it. >> My pleasure and thank you for watching everybody's as theCube's continuous coverage of HPE's GreenLake announcement, keep it right there for more great content. (bright upbeat music)

(bright upbeat music) >> Okay, we're back with theCUBE's continuous coverage of HPE's latest GreenLake announcement, the continuous cadence that we're seeing here. You know, when you're trying to figure out how to optimize workloads, it's getting more and more complex. Data-driven workloads are coming in to the scene, and so how do you know, with confidence, how to configure your systems, keep your costs down, and get the best performance and value for that? So we're going to talk about that. With me are Chris Shin, who is the founder of CloudPhysics and the senior director of HPE CloudPhysics, and Sandeep Singh, who's the vice-president of Storage Marketing. Gents, great to see you. Welcome. >> Dave, it's a pleasure to be here. >> So let's talk about the problem first, Sandeep, if we could. what are you guys trying to solve? What are you hearing from customers when they talk to you about their workloads and optimizing their workloads? >> Yeah, Dave, that's a great question. Overall, what customers are asking for is just to simplify their world. They want to be able to go faster. A lot of business is asking IT, let's go faster. One of the things that cloud got right is that overall cloud operational experience, that's bringing agility to organizations. We've been on this journey of bringing this cloud operational agility to customers for their data states, especially with HPE GreenLake Edge-to-Cloud platform. >> Dave: Right. >> And we're doing that with, you know, powering that with data-driven intelligence. Across the board, we've been transforming that operational support experience with HPE InfoSight. And what's incredibly exciting is now we're talking about how we can transform that experience in that upfront IT procurement portion of the process. You asked me what are customers asking about in terms of how to optimize those workloads. And when you think about when customers are purchasing infrastructure to support their app workloads, today it's still in the dark ages. They're operating on heuristics, or a gut feel. The data-driven insights are just missing. And with this incredible complexity across the full stack, how do you figure out where should I be placing my apps, whether on Prim or in the public cloud, and/or what's the right size infrastructure built upon what's actually being consumed in terms of resource utilization across the board. That's where we see a tremendous opportunity to continue to transform the experience for customers now with data-driven insights for smarter IT decisions. >> You know, Chris, Sandeep's right. It's like, it's like tribal knowledge. Well, Kenny would know how to do that, but Kenny doesn't work here anymore. So you've announced CloudPhysics. Tell us more about what that is, what impact it's going to have for customers. >> Sure. So just as Sandeep said, basically the problem that exists in IT today is you've got a bunch of customers that are getting overwhelmed with more and more options to solve their business problems. They're looking at cloud options, they're looking at new technologies, they're looking at new sub-technologies and the level at which people are competing for infrastructure sales is down at the very, very, you know, splitting hairs level in terms of features. And they don't know how much of these they need to acquire. Then on the other side, you've got partners and vendors who are trying to package up solutions and products to serve these people's needs. And while the IT industry has, for decades, done a good job of automating problems out of other technology spaces, hasn't done a good job of automating their own problems in terms of what does this customer need? How do I best service them? So you've got an unsatisfied customer and an inadequately equipped partner. CloudPhysics brings those two together in a common data platform, so that both those customers and their partners can look at the same set of data that came out of their data center and pick the solutions that will solve their problems most efficiently. >> So talk more about the partner angle, because it sounds like, you know, if they don't have a Kenny, they really need some help, and it's got to be repeatable. It's got to be consistent. So how have partners reacting to this? >> Very, very strongly. Over the course of the four or five years that that CloudPhysics has been doing this in market, we've had thousands and thousands of VARs, SIs and others, as well as many of the biggest technology providers in the market today, use CloudPhysics to help speed up the sales process, but also create better and more satisfied customers. >> So you guys made... Oh, go ahead, please. >> Well, I was just going to chime into that. When you think about partners that with HPE CloudPhysics, where it supports heterogeneous data center environments, partners all of a sudden get this opportunity to be much more strategic to their customers. They're operating on real world insights that are specific to that customer's environment. So now they can really have a tailored conversation as well as offer tailored solutions designed specifically for the areas, you know, where help is needed. >> Well, I think it builds an affinity with the customer as well, because if the partners that trust advisor, if you give a customer some advice and it's kind of the wrong advice, "Hey, we got to go back and reconfigure that workload. We won't charge you that much for it". You're now paying twice. Like when an accountant makes a mistake on your tax return, you got to pay for that again. But so, you guys acquired CloudPhysics in February of this year. What can you tell us about what's transpired since then? How many engagements that you've done? What kind of metrics can you share? >> Yeah. Chris, do you want to weigh in for that? >> Sure, sure. The start of it really has been to create a bunch of customized analytics on the CloudPhysics platform to target specific sales motions that are relevant to HPE partners. So what do I mean by that? You'll remember that in May, we announced the Alletra Series 6,000 and 9,000. In tandem with that, CloudPhysics released a new set of analytics that help someone who's interested in those technologies figure out what model might be best for them and how much firepower they would need from one or the other of those solutions. Similarly, we have a bunch solutions and a market strength in the HCI world, hyper converged, and that's both SimpliVity and dHCI. And we've set up some analytics that specifically help someone who's interested in that form factor to accelerate, and again, pick the right solutions that will serve their exact applications needs. >> When you talk to customers, are they able to give you a sense as to the cost impacts? I mean, even if it's subjective, "Hey, we think we, you know, we save 10% versus the way we used to do it", or more or less. I mean, just even gut feel metrics. >> So I'll start that one, Sandeep. So there's sort of two ways to look at it. One thing is, because we know everything that's currently running in the data center - we discovered that - we have a pretty good cost of what it is costing them today to run their workloads. So anything that we compare that to, whether it's a transition to public cloud or a transition to a hosted VMware solution, or a set of new infrastructure, we can compare their current costs to the specific solutions that are available to them. But on the more practical side of things, oftentimes customers know intuitively this is a set of servers I bought four years ago, or this is an old array that I know is loose. It's not keeping up anymore. So they typically have some fairly specific places to start, which gives that partner a quick win, solving a specific customer problem. And then it can often boil out into the rest of the data center, and continual optimization can occur. >> How unique is this? I mean, is it, you know, can you give us a little glimpse of the secret sauce behind it? Is this kind of table stakes for the industry? >> Yeah. I mean, look, it's unique in the sense that CloudPhysics brings along over 200 metrics across the spectrum of virtual machines and guest OSs, as well as the overall CPU and RAM utilization, overall infrastructure analysis, and built in cloud simulators. So what customers are able to do is basically, in real time, be able to: A - be aware of exactly what their environment looks like; B - be able to simulate if they were going to move and give an application workload to the cloud; C - they're able to just right-size the underlying infrastructure across the board. Chris? >> Well, I was going to say, yeah, along the same lines, there have been similar technology approaches to different problems. Most notably in the current HPE portfolio, InfoSight. Best in class, data lake driven, very highly analytical machine learning, geared predominantly toward an optimization model, right? CloudPhysics is earlier in the talk track with the customer. We're going to analyze your environment where HPE may not even have a footprint today. And then we're going to give you ideas of what products might help you based on very similar techniques, but approaching a very different problem. >> So you've got data, you've got experience, you know what best practice looks like. You get a sense as to the envelope as to what's achievable, right? And that is just going to get better and better and better over time. One of the things that that I've said, and we've said on theCUBE, is that the definition of cloud is changing. It's expanding, it's not just public cloud anymore. It's a remote set of services, it's coming on Prim, there's a hybrid connection. We're going across clouds, we're going out to the edge. So can CloudPhysics help with that complexity? >> Yeah, absolutely. So we have a set of analytics in the cloud world that range from we're going to price your on-premise IT. We also have the ability to simulate a transition, a set of workloads to AWS, Azure, or Google Cloud. We also have the ability to translate to VMware based solutions on many of those public clouds. And we're increasingly spreading our umbrella over GreenLake as well, and showing the optimization opportunities for a GreenLake solution when contrasted with some of those other clouds. So there's not a lot of... >> So it's not static. >> It's not static at all. And Dave, you were mentioning earlier in terms such as proven. CloudPhysics now has operated on trillions of data points over millions of virtual machines across thousands of overall data assessments. So there's a lot of proven learnings through that as well as actual optimizations that customers have benefited from. >> Yes. I mean, there's benchmarks, but it's more than that because benchmarks tend to be static, okay. We consider rules of thumb. We're living in an age with a lot more data, a lot more machine intelligence. And so this is organic, it'll evolve. >> Sandeep: Absolutely. >> And the partners who work with their customers on a regular basis over at CloudPhysics, and then build up a history over time of what's changing in their data center can even provide better service. They can look back over a year, if we've been collecting, and they can see what the operating system landscape has changed, how different workloads have lost popularity, how other ones have gained. And they really can become a much better solution provider to that customer the longer CloudPhysics is used. >> Yeah, it gives your partners a competitive advantage, it's a much stickier model because the customer is going to trust your partner more if they get it right. So we're not going to change horses in the middle of the street. We're going to go back to the partner that set us up, and they keep getting better and better and better each time, we've got a good cadence going. All right. Sandeep, bring us home. What's your sort of summary? How should we think about this going forward? >> Well, I'll bring us right back to the way I started is, and to end, we're looking at how we continue to deliver best in class cloud operational experience for customers across the board with HPE GreenLake. And earlier this year, we unveiled this cloud operation experience for data, and for customers, that experience starts with a cloud consult where they can essentially discover services, consume services, that overall operational and support experience is transformed with HPE InfoSight. And now we're transforming this experience where any organization out there that's looking to get data-driven insights into what should they do next? Where should they place their workloads? How to right-size the infrastructure? And in the process, be able to transform how they are working and collaborating with their partners. They're able to do that now with HPE CloudPhysics, bringing these data driven insights for smarter IT decision-making. >> I like this a lot, because a lot of the cloud is trial and error. And when you try and you make a mistake, you're paying each time. So this is a great innovation to really help clients focus on the things that matter, you know, helping them apply technology to solve their business problems. Guys, thanks so much for coming to theCUBE. Appreciate it. >> Dave, always a pleasure. >> Thanks very much for having us. >> And keep it right there. We got more content from HPE's GreenLake announcements. Look for the cadence. One of the hallmarks of cloud is the cadence of announcements. We're seeing HPE on a regular basis, push out new innovations. Keep it right there for more. (bright upbeat music begins) (bright upbeat music ends)

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

>> From New York City, it's theCUBE, covering Welcome to the New Edge. Brought to you by Pensando Systems. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're on top of Goldman Sachs in downtown Manhattan. It was a really beautiful day a couple of hours ago, but the rain is moving in, but it's appropriate 'cause we're talking about cloud. And we're here for a very special event. It's the Pensando launch, I'll get the pronunciation right, Pensando launch, and it's really about Welcome to the New Edge. And to start off, I mean, I couldn't come up with two better tech executives who've been around the block, seen it all, and they're both here for this launch event which is pretty special. On my left, Antonio Neri, CEO and president of HP. Antonio, great to see you. >> Thanks for having me. >> And John Chambers, of course we know him from his many years at Cisco, but now he's the chairman of Pensando, and of course J2 Ventures, and an author, and John, you're keeping yourself busy. >> I am, tryin' to change the world one more time. >> All right, so let's talk about that changing the world, 'cause you are two very high, powerful people. You run big companies, and you talked about, in your opening remarks, the next wave. You talked about these kind of 10-year waves. And we're starting a new one, which is why you got involved. Why did you see that coming, what do you see in Pensando, and how are we going to address this opportunity? >> Well, when you think about it, every 10 years there's a new leader in the marketplace, and nobody has stayed on top longer than 10 years and has led in the next market transition. We think about mainframes, IBM clearly the leader there, the mini computers, I'm biased toward Wang, but DEC was there. Then the client server and obviously Microsoft and Intel playing a very key role, followed by the internet where Cisco was very, very successful. And then followed, literally by that, by social media and then the cloud and then what I think will be bigger than any of the prior ones, it's about what happens as the cloud moves to the edge. And we may end up having a different term every time, but that really is what we saw today. And how we came together with a common vision as the cloud moves to the edge, what could an ecosystem of partners do, with a foundation, with Pensando at the core of that, to really take advantage from how do you deliver services to our joint customers in a way that no one else can. And have the courage, really, to go challenge Amazon in terms of their market dominance, but provide choice and say it's a multi cloud world. How do you provide that choice and then how do you differentiate it together with each partner? >> Antonio, you guys have been talking about edge for a long, long time. You've been on this for a while. HP's such a great company. Used to be, I think, one of the great validators if anyone could do a deal with HP. It was really a technology validation and a business validation, and I think that still holds true. So you must have, knocking on your door all day long. What did you see in this opportunity with Pensando? >> Well, first of all, John and I see the world from the same lens. We see a world where the enterprise of the future will be essentially cloud enabled and data-driven. And therefore we have to remove these barriers, call it the cloud in one place or the other one. We are going to live what are calling a edge-to-cloud world where, is a cloudless. Where the cloud experience is distributed everywhere. And where action happens is where we live and work right now, right here. We're having a conversation, we're producing data, and we are transmitting this real time. So, the point is, we believe the edge is a new frontier and that's where the vast majority is being created, 75%. of it created the edge. And this is where it starts by having a common vision and ultimately a same DNA, same culture. John and I share the same values for passion for customers, passion for driving a customer-driven innovation, and ultimately change the world like we have done for decades. And I think Hewlett-Packard Enterprise is uniquely positioned to be the edge-to-cloud platform delivered as a service. And together with Pensando and the great technology I bring about from the silicon side and on the softer side, together with our own knowhow and engineering capabilities, we can change the world again. >> And the fun part is, we can almost finish each other's sentences. (all laughing) We have a little bit different accent. The stability to have a common vision, having never really talked about it, and then a view of the common culture. Because strategic partnerships are really hard. And you said it on stage, but I cannot agree with it more. If you're cultures aren't similar, if you don't think how does your partner win first and how do you win second, this is very hard to do. And we can finish each other's sentences. >> And I think there is another point here that John and I truly believe, because it's part of our values. It's to use technology for good. So, one thing is accelerating the business innovation and what our enterprise customers are going through, but then how apply that technology to deliver some good. And we as a company have a clear purpose in life, which is to advance the way people live and work. So, I think as we go through this massive inflection point, both from the business side and the technology side, not only we can create a better world, but also give back somewhat to the communities as well. >> There are massive changes, and it's a sea-change in infrastructure in the way things are done, but you hit on three really key, simple words in your remarks earlier. Trust, engineering-driven, which is HP's culture from the earliest garage days, and customer-centric. So, we hear about data-driven but in engineering, you don't necessarily want to lead with that. Customer-centric you do have to lead and it's pretty interesting at Pensando, you talk to all these customers, and you're just launching the company today, you've been in stealth for over two years. But all these customers have been engaged with you since the very, very beginning. Pretty interesting approach. >> It is, and we do share a common passion on that. Every company says they're customer-driven, but just ask how the CEO spends his or her time. I just asked their customers, do they replace them first on every issue? We share that common value completely. >> Yeah, I spend 50% of my time on the road talking to customers. That's my goal, because I believe the truth is in the cold face. When you talk to customers, you get the truth, what the challenges and opportunities are. And we need to bring that succinct feedback back into our problem management engineering team to try to solve there's a problem. So take advantage of those opportunities by delivering a better experience. It starts with experience first and technology comes second. >> The other piece you talked about is your team, and diversity and really the power of diversity. And, I think it was, the Lincoln cabinet, band of people that didn't get along with each other and had a bunch of different points of view. But because of that, it surfaces issues and it lets you see multi sides. You said you handpicked that team. What are some of the things you thought about when you handpicked your team when you took the reins a couple years ago from the-- >> Well, it starts by, thought leadership and what, how they see the world, ultimately what the strengths are and how we bring those strengths for the power of one. I agree with John, I believe a team comes first, individual comes second. And if you can bring the best of each individual in a concerted way where you create an environment for debate and ultimately for getting alignment and moving forward with execution. That's what that is all about, leadership. So, I handpicked those people because each of them had that unique quality. Whether it's, you know, being very self-centric in the way you deliver the value proposition or very technology-centric, or very services oriented. So, we have picked those people for a reason and it's not easy to manage a very opinionated team. (all laughing) But once you can get them aligned, is actually incredible fun to watch. >> You know, I would make one tweak to what you just asked the question on. I had a chance to watch his team for the first time in our garage startup at my house. And they are very diverse with different opinions, they are very comfortable with disagreeing with each other. But they have a common set of values and a common end goal. I'm not sure the Lincoln cabinet had that. And that's so important to realize, because what we're about to do together and what each of us are trying to do in our own endeavors, it's so important to have a team that has that type of culture and the ability to move for that. >> The other team that mentioned, that kept coming up throughout the day, was the team that you're working with on Pensando. And how this team has been together for, I think you said the new 20, right? 25 plus years, and have built multiple projects, multiple products over many, many years. And now have this cohesion as you keep saying, they can finish their own sentences. You know, a really specific approach to get this group together that you know is not going to be strategy, it's going to be delivery. >> It is going to be the combination, if I may. And it is very unique that a team works together for over 25 years. It's a team that is a family and we are about as diverse as it gets in our backgrounds, our accents, our countries that our families came from. But it's a team that competes purely on getting market transitions right, that is always driven by our customers and what we need to do and build and put 'em always first in everything we do. And then it's fearless. We outline audacious goals at being number one in everything we do, and out of the eight products that we built together, we are number one in all eight. All of 'em with over 50% market share, and there was no number two. And so the ability to execute with that type of precision, customer-driven and the courage to do it and understand what we know and what we don't know. Coming together one more time, I mean it's really exciting, it will be a new definition of 20 somethings in a startup. >> So, getting you the last word Antonio, as you looked at John's chart with those 10-year blocks and the garage has been around Palo Alto for a long time. >> 82 years. >> You guys have seen a lot, 82 years, you've been through a few of these and you're still here and still doing a great job and still winning. So, as you look at that from your current position as CEO, what goes through your head? How are you making sure you're keeping ahead? How are you avoiding the Clayton Christensen Innovator's Dilemma, to make sure you're killing your own business before somebody else kills kind of the old stuff and making sure you're out in front. >> When I became a CEO, in the transition from Meg to me, I established three key priorities for myself. One is our customers and partners. Keep them at the center of everything we do. That's one of our core values. Second is innovation, innovation, innovation. Innovation from a customer-driven approach. And third is the culture of the company. And what a great example here with John, you know, leading an iconic company for decades. And so to me, I have been working very aggressive on the three of those aspects. And I'm very pleased with the progress we have made. But, now is about writing the next chapter of this company. And in order to write that next chapter company, you need to have a strong alignment at the top, all the way down, what I call ropes to the ground. So, fun enough, John is going to be in my event here in a couple of weeks. We'll bring the leadership team, the top 400 leaders, talking about how to disrupt yourself and how you pay for the company into the future. And the future, as I said, is we see an enterprise that's edge-centric, cloud-enabled, and data-driven, delivered as a service. So we are going to be the, as a service company with an edge-to-cloud platform that accelerates business from the data. And the combination of Pensando technologies and engineering capabilities, with our vision and our own intellectual property, we think we can deliver those unique experience for the customers in a more agile, cost-effective way and democratize the cloud, as John say, for the world. So, I'm incredibly excited about doing this. And who thought that John Chambers and Antonio Neri would be here, you know. And the reality is it takes leadership, so I value leadership, I value trust, and this partnership is built on trust. And we both have the same values. >> I appreciate you taking the time. I mean, we're going to talk about the products a little bit later. We've got some of the deeper product people. But, you know, I think the leadership thing is so important and I think it's harder. I think it's hard to be a great leader, it's hard to lead through transitions, and the pace of change is only accelerating, so the challenge is only going to increase. But I think communication and trust is such a big piece. I saw Dave Pottruck speak many, many times and he's very, very good. And I asked him, 'cuz we had a thing at school. I said, "Dave, why are you so good?" And he said, "Very simple. "As a CEO, my job is to communicate. "I have three constituents. "I have my customers, I have the street, "and I have my employees. "And so I treat it as a skill, I practice, I got a coach, "and I treat it like any other skill." And it's so hard and so important to provide that leadership, provide that direction, so everybody can pull the rope in the same direction. Nothing but the best to both of you and thanks for taking a few minutes. >> Thank you. >> It was a lot of fun. >> All right. >> It's a pleasure. >> Thank you. >> He's Antonio, he's John, I'm Jeff. You're watching theCUBE, from the top of Goldman Sachs in Manhattan. Thanks for watching, we'll see you next time. (upbeat music)