>>Hey everyone. Welcome back to Miami. Lisa Martin here live with the Cube at IFS Unleashed 2022. We're so excited to be here. We just had a great conversation with Ifss, CEO of Darren Rouse. Now we've got another exciting conversation. F1 is here. You know how much I love f1. Christian Peterson joins us as well, the Chief Product Officer at ifs, and Sean Edwards IT business partner at Aston Martin. F1. Guys, it's great to have you on the program. Thank you for having >>Us. Thank you >>Very much. We were talking about F one. We probably could have an entire conversation just on that, but Christian, I wanna talk with you. It's been three years since the Cube has covered ifs obviously for obvious reasons during that time. So much momentum has happened. IFS cloud was launched about 18 months ago. Give our audience an o, a flavor of IFS, cloud and some of the milestones that you've hit in such a short time period. >>Yeah, I mean IFS cloud is really transformational in many ways. It's transformational for first and foremost for our customers in what enables them to do, but also transformational for us from a technology perspective, how we work and how we do everything. And at the end of the day, it has really surfaced, served around the the, the fact of what we need to do for our customers. And what we saw our customers often do back then, or any company, was they were out looking for EAP solutions or FSM Solutions or EAM Solutions or what have you. And then they were trying to stitch it all together and we, we said like, Hang on a second, these these traditional software s, those are some that I'm guilty. You know, there's some that we actually invented over the years together with analysts. So we invented EER P and we invented CRM and EAM and all these different things. >>But at the end of the day, customers really want a solution to what they are, they are what they're dealing with. And so in these conversations it became very clear that and very repeated conclusions from the conversations that customers wanted something that could manage and help them optimize the use of their assets. Regardless of what industry you're in, assets is such a key component. Either you are using your assets or you're producing assets. Second thing is really get the best use of of your people, your teams and your crew. How do you get the right people on the right job at the same time? How do you assemble the right crew with the right set of skills in the crew? Get them to the right people at the same time. So, and then the final thing is of course customers, you know all the things that you need to do to get customers to answer these ultimate questions, Will you buy from this company again? And they should say yes. That's the ultimate results of moments of service. So that's how we bring it all together and that's what we have been fast at work at. That's what IFS cloud is all about. >>And you, you talked about IFS cloud, being able to to help customers, orchestrate assets, people, customers, Aston Martin being one of those customers. Shawn, you came from ifs so you have kind of the backstory but just give the audience a little bit of, of flavor of your role at Aston Martin and then let's dig into the smart factory. >>Sure. So I previously worked at IFS as a manufacturing consultant. So my bread and butter is production planning in the ERP sector. So we, I Aston Martin didn't have an ERP system pre IFS or a legacy system that wasn't working for them and the team couldn't rely upon it. So what we did was bring IFS in. I was the consultant there and as IFS always preached customer first, well customer first did come and I jumped to support the team. So we've implemented a fully RP solution to manage the production control and the material traceability all the way through from design until delivery to track. And we've mo most recently implemented a warehouse solution at Trackside as well. So we are now tracking our parts going out with the garage. So that's a really exciting time for RFS. In terms of the smart factory, it's not built yet. >>We're we're supposed to move next year. So that's really exciting cause we're quadrupling our footprint. So going from quite a small factory spread out across the North Hampton Share countryside, we're going into one place quadruple in our footprint. And what we're gonna start looking at is using the technology we're implementing there. So enabling 5G to springboard our IFFs implementations going forward with the likes of Internet of things to connect our 15 brand new CMC machines, but also things like R F I D. So that comes with its own challenges on a Formula One car, but it's all about speed of data capture, single point of truth. And IFFs provides that >>And well, Formula One, the first word that comes to mind is speed. >>Absolutely. Second >>Word is crazy. >>We, we are very unique in terms of most customers Christian deals with, they're about speed but also about profit and efficiency. That doesn't matter to us. It is all about time. Time is our currency and if we go quicker in designing and manufacturing, which ifs supports ultimately the cargo quicker. So speed is everything. >>And and if we, if we think of of people, customers and assets at Asset Martin F one, I can't, I can't imagine the quantity of assets that you're building every race weekend and refactoring. >>Absolutely. So a Formula one car that drives out of the garage is made up of 13,000 car parts, most of which, 50% of which we've made in house. So we have to track that all the way through from the smallest metallic component all the way up to the most complex assembly. So orchestrating that and having a single point of truth for people to look at and track is what IFFs has provided us. >>Christian, elaborate on that a little bit in terms of, I mean, what you're facilitating, F1 is such a great example of of speed we talked about, but the fact that you're setting up the car every, every other weekend maybe sometimes back to back weeks, so many massive changes going on. You mentioned 50% of those 13,000 parts you manufacture. Absolutely. Talk about IFS as being a catalyst for that. >>I mean the, it's, it's fascinating with Formula One, but because as a technology geek like me, it's really just any other business on steroids. I mean we talk, we talk about this absolutely high tech, super high tech manufacturing, but even, even before that, the design that goes in with CFDs and how you optimize for different things and loose simulation software for these things goes into manufacturing, goes into wind tunnels and then goes on track. But guess what, when it's on track, it's an asset. It's an asset that streams from how many sensors are on the car, >>I think it's over 10,000 >>Sensors, over 10,000 sensors that streams maybe at 50 hertz or 50 readings. So every lap you just get this mountain of data, which is really iot. So I always say like F one if one did IOT before anybody invented the term. >>Absolutely. >>Yep. You know, F1 did machine learning and AI before anybody thought about it in terms of pattern recognition and things like that with the data. So that's why it's fascinating to work with an organization like that. It's the, it's the sophistication around the technologies and then the pace what they do. It's not that what they do is actually so different. >>It is, it absolutely isn't. We just have to do it really quickly. Really >>Quickly. Right. And the same thing when you talk about parts. I mean I was fascinated of a conversation with, with one of your designers that says that, you know, sometimes we are, we are designing a part and this, the car is now ready for production but the previous version of that part has not even been deployed on the car yet. So that's how quick the innovation comes through and it's, it's, it's fascinating and that's why we like the challenge that Esther Martin gives us because if we can, if we can address that, there's a lot of businesses we can make happy with that as far, >>So Sha I talk a little bit about this is, so we're coming up, there's what four races left in the 2022 season, but this is your busy time because that new car, the 23 car needs to be debuted in what February? So just a few months time? >>Absolutely. So it's a bit cancer intuitive. So our busiest time is now we're ramping up into it. So we co, we go into something called car build which is from December to December to February, which is our end point and there's no move in that point. The car has gotta go around that track in February. So we have got to make those 13,000 components. We've gotta design 'em, we've gotta make 'em and then we've gotta get 'em to the car in February for our moment of service. They said it on stage. Our moment of service as a manufacturing company is that car going around the track and we have to do it 24 times next year and we've gotta start. Well otherwise we're not gonna keep up. >>I'm just gonna ask you what a, what a moment, what's a moment of service in f1 and you're saying basically getting that >>Functional car >>On the track quickly, as quickly as possible and being able to have the technology underpinning that's really abstracting the complexity. >>Absolutely. So I would say our customer ultimately is the driver and the fans they, they need to have a fast car so they can sport it and they ultimately drive it around the track and go get first place and be competitive. So that is our moment of service to our drivers is to deliver that car 24 times next year. >>I imagine they might be a little demanding >>They are and I think it's gonna be exciting with Alonzo coming in, could the driver if we've gotta manage that change and he'll have new things that he wants to try out on a car. So adds another level of complexity to that. >>Well how influential are the drivers in terms some of the, the manufacturing? Like did they, are they give me kind of a a sense of how Alon Fernando Alanzo your team and ifs maybe collaborate, maybe not directly but >>So Alonzo will come in and suggest that he wants cars to work a certain way so he will feed back to the team in terms of we need this car, we need this car part to do this and this car part to do that. So then we're in a cycle when he first gets into the car in that February, we've then gotta turnaround car parts based off his suggestions. So we need to do that again really quickly and that's where IFS feeds in. So we have to have the release and then the manufacturer of the component completely integrated and that's what we achieve with IFFs and >>It needs to be really seamless. >>Absolutely. If, if we don't get it right, that car doesn't go out track so there's no moving deadline. >>Right. That's the probably one of the industries where deadlines do not move. Absolutely. We're so used to things happening in tech where things shift and change and reorgs, but this is one where the dates are set in their firm. >>Absolutely. And we have to do anything we can do to get that car on the track. So yeah, it's just a move. >>Christian, talk about the partnership a little bit from your standpoint in terms of how influential has Aston Martin F1 been in IFS cloud and its first 18 months. I was looking at some stats that you've already gotten 400,000 plus users in just a short time period. How influential are your customers in the direction and even the the next launch 22 R too? >>I mean our customers do everything plain and simple. That's that's what it is. And we have, we have a partnership, I think about every single customer as a partner of ours and we are partnering in taking technology to the next level in terms of, of the outputs and the benefits it can create for our customers. That's what it's all, all about. And I, I always think about these, these three elements I think I mentioned in our state as well. I think the partnership we have is a partnership around innovation. Innovation doesn't not only come from IFS or the technology partner, it comes from discussions, requirements, opportunities, what if like all these things. So innovation comes from everywhere. There's technology driven innovation, there's customer driven innovation, but that's part of the partnership. The second part of the partnership is inspiration. So with innovation you inspire. So when you innovate on something new that inspires new innovation and new thinking and that's again the second part of the partnership. And then the third part is really iterate and execute, right? Because it's great that we can now innovate and we can agree on what we need to do, but now we need to put it into products, put it in technology and put it into actual use. That's when the benefits comes and that's when we can start bringing the bell. >>And I think it's really intrinsically linked. I mean if you look at progress with Formula One teams and their innovation, it's all underpinned by our technology partners and that's why it's so important. The likes of Christian pushes the product and improves it and innovates it because then we can realize the benefits and ultimately save time and go faster. So it's really important that our, our partners and certainly inform one, push the boundaries and find that technology. >>And I think one of the things that we also find very, very important is that we actually understand our customers and can talk the language. So I think that was one of the key things in our engagement, Martin from the beginning is that we had a set of people that really understand Formula One felt it on their bodies and can have the conversation. So when the Formula One teams they say something, then we actually understand what we're talking about. So for instance, when we talk about, you know, track side inventory, well it's not that different from what a field service technician have in his van when he goes service. The only difference is when you see something happening on track, you'll see the parts manager go out to the pit lane with a tablet and say like, oh we need this, we need that, we need this and we need that. And then we'll go back and pick it and put it on the car and the car is service and maintain and off go. Absolutely. >>Yeah that speed always impresses me. >>It's unbelievable. >>Shannon, last question for you. From a smart factory perspective, you said you're moving in next year. What are some of the things that you are excited about that you think are really gonna be transformative but IFS is doing? >>So I think what I'm really excited about once we get in is using the technology they've already put in terms of 5G networks to sort of springboard that into a further IFS implementation. Maybe IFFs cloud in terms of we always struggle to keep the system up to date with, with what's physically happening so that the less data entry and the more automatic sort of data capture, the better it is for the formula on team cuz we improve our our single point of truth. So I'm really excited to look at the internet of things and sort of integrate our CNC machines to sort of feed that information back into ifs. But also the RFID technology I think is gonna be a game changer when we go into the new factory. So really >>Excited. Excellent. Well well done this year. We look forward to seeing Alonso join the team in 23. Fingers >>Crossed. >>Okay. Fingers crossed. Christian, Jeanette, it's been a pleasure to have you on the program. Thank you so much for sharing your insights and how ifs asked Martin are working together, how you really synergistically working together. We appreciate your time. >>Thank you very much for having us. Our >>Thanks for having us. And go Aston >>Woo go Aston, you already here first Lisa Martin, no relation to Aston Martin, but well, I wanna thank Christian Peterson and Shannon Edwards for joining me, talking about IFS and Aston Martin team and what they're doing at Speed and Scale. Stick around my next guest joins me in a minute. >>Thank you.

>>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.