>>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.

(upbeat music) >> Edge computing is projected to be a multi-trillion dollar business. 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 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 a mind-boggling but guess what we're going to 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 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 Omer Asad, VP and GM of Primary Storage and Data Management Services at HPE. Hello Omer, welcome to the program. >> Thanks Dave. 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? >> Dave, I think that's a super important question. I think your ideas are quite aligned with how we think about it. I personally think enterprises are accelerating their sort of digitization and asset collection and data collection, 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 has 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 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 this that more than 50% of an enterprises data especially if they operate globally around the world is going to be generated out at the edge. What does that mean? New data is generated at the edge what needs to be stored. It needs to be processed data. Data which 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, 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 multi-site deployments, ROBO, edge? How do you look at that? >> Oh, excellent question, Dave. Every customer that we talked to wants SimpliVity and no pun intended because SimpliVity is reasoned with a simplistic edge centric architecture, right? Let's take a few examples. You've got large global retailers, 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 IT staff out there because that adds cost. 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 manner. 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 out towards the edge in a hyper converged 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 HPE believe that it needs to be extremely simple, just give me two cables, a network cable, a power cable, fire it up, connect it to the network, push it state from the data center and back up it state from the edge back into the data center, extremely simple. >> It's got to be simple 'cause you've got so many challenges. You've got physics that you have to deal, you have latency to deal with. You got RPO and RTO. What happens if something goes wrong you've got to be able to recover quickly. So that's great. Thank you for that. Now you guys have heard news. What is new from HPE in this space? >> Excellent question, great. So from a deployment perspective, HPE SimpliVity is just gaining like it's exploding like crazy especially as distributed enterprises adopted as it's standardized edge architecture, right? It's an HCI box has got storage 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 distributed file system that is the heart and soul of the SimpliVity installation. In addition to that, the customers now do not have to buy any third-party software. Backup is fully integrated in the architecture and it's then efficient. In addition to that now you can backup straight to the client. You can back up to a central 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, we previously were one-on-one leaving VMware deployments out at the edge site now evolved 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 of customers that are now deploying containers, rapid manufacture 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 line no egress fees. That's a pain point for a lot of CIOs that I talked to. They grit their teeth at those cities. So you can't comment on that or? >> Excellent question. I'm so glad you brought that up and sort of at the point that pick that up. So along with SimpliVity, 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. One of the things that was missing with cloud backups is that every time you back up to the cloud, which is a great thing by the way, anytime you restore from the cloud there is that egress fee, 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 HPE's 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, can you, Omer, 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? >> Excellent question. So one of the major use cases that we see Dave is obviously 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. 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 DR 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 when a lot of these customers are generating a lot of the data at the edge. This is robotics automation that is going up in manufacturing sites. These is racing teams that are out at the edge of doing post-processing of their cars data. At the same time there is disaster recovery use cases where you have campsites and local 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 are just a few cases where we were deployed. There was a lot of data collection and there was a lot of mobility involved in these environments, so you need to be quick to set up, quick to backup, quick to recover. And essentially you're up to your next move. >> You seem pretty pumped up about this new innovation and why not. >> It is, especially because it has been taught through with edge in mind and edge has to be mobile. It has to be simple. And especially as we have lived through this pandemic which I hope we see the tail end of it in at least 2021 or at least 2022. 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 mobility is limited in these strange times that we live in. So from a central recenter you're able to deploy applications. You're able to recover applications. 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 an HPE customer that's actually using SimpliVity at the edge. (engine revving) >> Narrator: Formula one is a constant race against time Chasing in tens of seconds. (upbeat music) >> Okay. We're back with Matt Cadieux who is the CIO Red Bull Racing. Matt, it's good to see you again. >> Great to see you Dave. >> Hey, we're going to dig in to a real world example of using data at the edge in near real time to gain insights that really lead to competitive advantage. 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 at Red Bull Racing we're based in Milton Keynes in the UK. And the main 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 IT group needs to develop the applications use 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 23 and movable deadlines this big evolving prototype to manage with our car but we're also improving all of our tools and methods and software that we use to design 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 continue to say, make the car faster. That we're winning races, that we improve our methods in the factory and our tools. And so for IT 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 of needs. So my job is really to make sure we have the right staff, the right partners, the right technical platforms. So we can live up to expectations. >> And Matt 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? >> Yeah, exactly. Every track has a different shape. Some have lots of straight, some have lots of curves and lots are in between. The track surface is very different and the impact that has on tires, the temperature and the climate is very different. Some are hilly, some have big curbs that affect the dynamics of the car. So all that in order to win you need to micromanage everything and optimize it for any given race track. >> COVID has of course been brutal for sports. What's the status of your season? >> So this season we knew that COVID was here and we're doing 23 races knowing we have COVID to manage. And as a premium sporting team with Pharma Bubbles we've put health and safety and social distancing into our environment. And we're able to able to operate by doing things in a safe manner. We have some special exceptions in the UK. So for example, when people returned from overseas that they did not have to quarantine for two weeks, but they get tested multiple times a week. And we know they're safe. So we're racing, we're dealing with all the hassle that COVID gives us. And we are really hoping for a return to normality sooner instead of later where we can get fans back at the track and really go racing and have the spectacle where everyone enjoys it. >> Yeah. That's awesome. So important for the fans but also all the employees around that ecosystem. Talk about some of the key drivers in your business and some of the key apps that give you 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 need to be fast. We need to be able to design a car and it's all done in the virtual world, but the virtual simulations and designs needed to correlate to what happens in the real world. So all of that requires a lot of expertise to develop the simulations, the algorithms and have all the underlying infrastructure that runs it quickly and reliably. In manufacturing 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. And 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 and the safety car comes out or the weather changes, we revise our tactics and we're running Monte-Carlo for example. And use 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 to work at a very high level. >> Yeah, it's interesting. I mean, as a lay person, historically when I think about technology in 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 you are somebody who knows the track and where the hills are and experience and gut feel but today you're digitizing it and you're processing it and close to real time. Its amazing. >> I think exactly right. Yeah. The car's instrumented with sensors, we post process and we are doing video image analysis and we're looking at our car, competitor's car. So there's a huge amount of very complicated models that we're using to optimize our performance and to continuously improve our car. Yeah. The data and the applications that leverage it are really key 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 a lot of equipment to the track at the edge. And even though we have really a great wide area network link back to the factory and there's cloud resources a lot of the tracks are very old. You don't have hardened infrastructure, don't have ducks that protect cabling, for example and you can 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 I said infrastructure and it was really hard to manage, to make changes, it was too flexible. There were multiple panes of glass and it was too slow. It didn't run our applications quickly. 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'd introduced hyper convergence 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 hyper convergence. And we saw really excellent benefits for doing that. We saw up 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. The three X reduction in processing time really matters. We also 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 $100,000 a year in freight costs by shipping less equipment. Things like backup 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 DDI through SimpliVity backup at 90 seconds. And this enables engineers to focus on the car to make better decisions without having downtime. And we sent two IT 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 in the factory so it sounds like your goals are obviously number one KPIs speed to help shave seconds, awesome time, but also cost just the simplicity of setting up the infrastructure is-- >> That's exactly right. It's speed, speed, speed. So we want applications absolutely fly, get to actionable results quicker, get answers from our simulations quicker. The other area that speed's really critical is 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 very clearly the option. What did you look at? >> Yeah, so we have over five years of experience in the factory and we eliminated all of our legacy infrastructure five years ago. And the benefits I've described at the track we saw that in the factory. At the track we have a three-year operational life cycle for our equipment. When in 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 is 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 SimpliVity, why'd you choose HPE SimpliVity? >> Yeah. So when we first heard about hyper-converged way back in the factory, we had 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, would enough the hype was real or not. So we underwent some PLCs and benchmarking and the PLCs were really impressive. And all these speed and agility benefits we saw and HPE for our use cases was the clear winner in the benchmarks. So based on that we made an initial investment in the factory. We moved about 150 VMs and 150 VDIs into it. And then as we've seen all the benefits we've successfully invested and we now have an estate in the factory of about 800 VMs and about 400 VDIs. So it's been a great platform and it's allowed us to really push boundaries and give the business the service it expects. >> Awesome fun stories, just coming back to the metrics for a minute. So you're running Monte Carlo simulations in real time and sort of near real-time. And so essentially that's if I understand it, that's what ifs and it's the probability of the outcome. And then somebody got to make, then the human's got to say, okay, do this, right? Was the time in which you were able to go from data to insight to recommendation or edict was that compressed and you kind of indicated that. >> Yeah, that was accelerated. And so in that use case, what we're trying to do is predict the future and you're saying, well and before any event happens, you're doing what ifs and if it were to happen, what would you probabilistic do? So that simulation, we've been running for awhile but it gets better and better as we get more knowledge. And so that we were able to accelerate that with SimpliVity but there's other use cases too. So we also have telemetry from the car and we post-process it. And that reprocessing time really, is it's very time consuming. And 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 ultimately that meant an engineer could understand what the car was doing in 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? >> I think we're optimistic. Thinking our simulations that we have a great car we have a new driver lineup. We have the Max Verstapenn who carries on with the team and Sergio Cross joins the team. So we're really excited about this year and we want to go and win races. And I think with COVID people are just itching also to get back to a little degree of normality and going racing again even though there's no fans, it gets us into a degree of normality. >> That's great, Matt, good luck this season and going forward and thanks so much for coming back in theCUBE. Really appreciate it. >> It's my pleasure. Great talking to you again. >> Okay. Now we're going to bring back Omer for quick summary. So keep it right there. >> Narrator: That's where the data comes face to face with the real world. >> Narrator: Working with Hewlett Packard Enterprise is a hugely beneficial partnership for us. We're able to be at the cutting edge of technology in a highly technical, highly stressed environment. There is no bigger challenge than Formula One. (upbeat music) >> Being in the car and driving in on the limit that is the best thing out there. >> Narrator: It's that innovation and creativity to ultimately achieves winning of this. >> Okay. We're back with Omer. Hey, what did you think about that interview with Matt? >> Great. I have to tell you, I'm a big formula One fan and they are one of my favorite customers. So obviously one of the biggest use cases as you saw for Red Bull Racing is track side deployments. There are now 22 races in a season. These guys are jumping from one city to the next they got to pack up, move to the next city, set up the infrastructure very very quickly. An 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. And we accomplished that for the Red Bull Racing guys in basically two of you have two SimpliVity nodes that are running track side and moving with them from one race to the next race to the next race. And every time those SimpliVity nodes connect up to the data center, collect up 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 Omer. I really appreciate those summary comments. >> Thank you, Dave. Really appreciate it. >> All right. And thank you for watching. This is Dave Volante for theCUBE. (upbeat music)

(mellow music) >> Okay, we're back with Matt Cadieux who is the CIO Red Bull Racing. Matt, it's good to see you again. >> Yeah, great to see you, Dave. >> 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 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 at Red Bull Racing we're based in Milton Keynes in the UK. And the main 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 IT team needs to develop the applications used for the design, manufacturing, and racing. We also need to supply all the underlying infrastructure, and also manage security. So it's a 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 23 immovable deadlines, this big evolving prototype to manage with our car. 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 in the company, around continuous improvement. And the expectations are that we continue to make the car faster, that we're winning races, that we improve our methods in the factory and our tools. And so for IT 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 it needs. So my job is really to make sure we have the right staff, the right partners, the right technical platforms, so we can live up to expectations. >> And Matt 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 straight, some have lots of curves and lots are in between. The track's surface is very different and the impact that has on tires, the temperature and the climate is very different. Some are hilly, some are big curves that affect the dynamics of the car. So all that in order to win, you need to micromanage everything and optimize it for any given race track. >> And, you know, COVID has, of course, been brutal for sports. What's the status of your season? >> So this season we knew that COVID was here and we're doing 23 races knowing we have COVID to manage. And as a premium sporting team we've formed bubbles, we've put health and safety and social distancing into our environment. And we're able to operate by doing things in a safe manner. We have some special exhibitions in the UK. So for example, when people return from overseas that they do not have to quarantine for two weeks but they get tested multiple times a week and we know they're safe. So we're racing, we're dealing with all the hassle that COVID gives us. And we are really hoping for a return to normality sooner instead of later where we can get fans back at the track and really go racing and have the spectacle where everyone enjoys it. >> Yeah, that's awesome. So important for the fans but also all the employees around that ecosystem. Talk about some of the key drivers in your business and some of the key apps that give you 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 need to be fast. We need to be able to design our car and it's all done in the virtual world but 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 simulations, the algorithms, and have all the underlying infrastructure that runs it quickly and reliably. In manufacturing, 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, 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 and the safety car comes out or the weather changes, we revise our tactics. And we're running Monte Carlo for example. And using 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 to work at a very high level. >> You know it's interesting, I mean, as a lay person, historically 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 like, 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 it's somebody who knows the track and where the hills are and experience and gut feel. But today you're digitizing it and you're processing it in close to real-time. It's amazing. >> Yeah, exactly right. Yeah, the car is instrumented with sensors, we post-process, we're doing video, image analysis and we're looking at our car, our competitor's car. So there's a huge amount of very complicated models that we're using to optimize our performance and to continuously improve our car. Yeah, the data and the applications that leverage it are really key. 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. >> Sure. What does that look like? >> So we have to send a lot of equipment to the track, at the edge. And even though we have really a great lateral network link back to the factory and there's cloud resources, a lot of the tracks are very old. You don't have hardened infrastructure, you don't have docks that protect cabling, for example, and you can 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, legacy infrastructure and it was really hard to manage, to make changes, it was too inflexible. There were multiple panes of glass, and it was too slow. It didn't run our applications quickly. 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'd introduced hyper-convergence 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 this slow and inflexible expensive legacy and introduce hyper-convergence. And we saw really excellent benefits for doing that. We saw a three X speed up for a lot of our applications. So here where we're post-processing data, and we have to make decisions about race strategy, time is of the essence and a three X reduction in processing time really matters. We also 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 $100,000 a year in freight costs by shipping less equipment. Things like backup, mistakes happen. Sometimes a 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 DDI through SimpliVity backup in 90 seconds. And this makes sure, enables engineers to focus on the car, to make better decisions without having downtime. And we send two IT 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 HP 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. >> Yes, so you had the nice Petri dish in the factory, so it sounds like your goals obviously, number one KPI is speed to help shave seconds off the time, but also cost. >> That's right. Just the simplicity of setting up the infrastructure is key. >> Yeah, that's exactly right. >> It's speed, speed, speed. So we want applications that absolutely fly, you know gets actionable results quicker, get answers from our simulations quicker. The other area that speed's really critical is 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. And SimpliVity gives us the means of doing that. >> So did you consider any other options or was it because you had the factory knowledge, HCI was, you know, very clearly the option? What did you look at? >> Yeah, so we have over five years of experience in the factory and we eliminated all of our legacy infrastructure five years ago. And the benefits I've described at the track we saw that in the factory. At the track, we have a three-year operational life cycle for our equipment. 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 is 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. >> So why SimpliVity? Why do you choose HPE SimpliVity? >> Yeah, so when we first heard about hyper-converged, way back in the factory. We had 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 hyper-convergence. We didn't know if the hype was real or not. So we underwent some PLCs and benchmarking and the PLCs were really impressive. And all these, you know, speed and agility benefits we saw and HPE for our use cases was the clear winner in the benchmarks. So based on that we made an initial investment in the factory. We moved about 150 VMs and 150 VDIs into it. And then as we've seen all the benefits we've successfully invested, and we now have an estate in the factory of about 800 VMs and about 400 VDIs. So it's been a great platform and it's allowed us to really push boundaries and give the business the service it expects. >> Well that's a fun story. So just coming back to the metrics for a minute. So you're running Monte Carlo simulations in real-time and sort of near real-time. >> Yeah. And so essentially that's, if I understand it, that's what-ifs and it's the probability of the outcome. And then somebody's got to make, >> Exactly. then a human's got to say, okay, do this, right. And so was that, >> Yeah. with the time in which you were able to go from data to insight to recommendation or edict was that compressed? You kind of indicated that, but. >> Yeah, that was accelerated. And so in that use case, what we're trying to do is predict the future and you're saying well, and before any event happens, you're doing what-ifs. Then if it were to happen, what would you probabilistically do? So, you know, so that simulation we've been running for a while but it gets better and better as we get more knowledge. And so that we were able to accelerate that with SimpliVity. But there's other use cases too. So we offload telemetry from the car and we post-process it. And that reprocessing time really is very time consuming. And, 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 ultimately that meant an engineer could understand what the car was doing in 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, the sentiment? >> Yeah, I think we're optimistic. We with thinking our simulations that we have a great car. We have a new driver lineup. We have Max Verstappen who carries on with the team and Sergio Perez joins the team. So we're really excited about this year and we want to go and win races. And I think with COVID people are just itching also to get back to a little degree of normality, and, you know, and going racing again, even though there's no fans, it gets us into a degree of normality. >> That's great, Matt, good luck this season and going forward and thanks so much for coming back in theCUBE. Really appreciate it. >> It's my pleasure. Great talking to you again. >> Okay, now we're going to bring back Omar for a quick summary. So keep it right there. (mellow music)

>> Announcer: From Denver, Colorado it's theCUBE. Covering Super Computing 17, brought to you by Intel. Welcome back everybody, Jeff Frick here with theCUBE. We're at Super Computing 2017 in Denver, Colorado talking about big big iron, we're talking about space and new frontiers, black holes, mapping the brain. That's all fine and dandy, but we're going to have a little bit more fun this next segment. We're excited to have our next guest Bernie Spang. He's a VP Software Defined Infrastructure for IBM. And his buddy and guest Wayne Glanfield HPC Manager for Red Bull Racing. And for those of you that don't know, that's not the pickup trucks, it's not the guy jumping out of space, this is the Formula One racing team. The fastest, most advanced race cars in the world. So gentlemen, first off welcome. Thank you. Thank you Jeff. So what is a race car company doing here for a super computing conference? Obviously we're very interested in high performance computing so traditionally we've used a wind tunnel to do our external aerodynamics. HPC allows us to do many many more iterations, design iterations of the car. So we can actually kind of get more iterations of the designs out there and make the car go faster very quicker. So that's great, you're not limited to how many times you can get it in the wind tunnel. The time you have in the wind tunnel. I'm sure there's all types of restrictions, cost and otherwise. There's lots of restrictions and both the wind tunnel and in HPC usage. So with HPC we're limited to 25 teraflops, which isn't many teraflops. 25 teraflops. >> Wayne: That's all. And Bernie, how did IBM get involved in Formula One racing? Well I mean our spectrum computing offerings are about virtualizing clusters to optimize efficiency, and the performance of the workloads. So our Spectrum LSF offering is used by manufacturers, designers to get ultimate efficiency out of the infrastructure. So with the Formula One restrictions on the teraflops you want to get as much work through that system as efficiently as you can. And that's where Spectrum computing comes in. That's great. And so again, back to the simulations. So not only can you just do simulations 'cause you got the capacity, but then you can customize it as you said I think before we turned on the cameras for specific tracks, specific race conditions. All types of variables that you couldn't do very easily in a traditional wind tunnel. Yes obviously it takes a lot longer to actually kind of develop, create, and rapid prototype the models and get them in the wind tunnel, and actually test them. And it's obviously much more expensive. So by having a HPC facility we can actually kind of do the design simulations in a virtual environment. So what's been kind of the ahah from that? Is it just simply more better faster data? Is there some other kind of transformational thing that you observed as a team when you started doing this type of simulation versus just physical simulation in a wind tunnel? We started using HPC and computational fluid dynamics about 12 years ago in anger. Traditionally it started out as a complementary tool to the wind tunnel. But now with the advances in HPC technology and software from IBM, it's actually beginning to overtake the wind tunnel. So it's actually kind of driving the way we design the car these days. That's great. So Bernie, working with super high end performance, right, where everything is really optimized to get that car to go a little bit faster, just a little bit faster. Right. Pretty exciting space to work in, you know, there's a lot of other great applications, aerospace, genomics, this and that. But this is kind of a fun thing you can actually put your hands on. Oh it's definitely fun, it's definitely fun being with the Red Bull Racing team, and with our clients when we brief them there. But we have commercial clients in automotive design, aeronautics, semiconductor manufacturing, where getting every bit of efficiency and performance out of their infrastructure is also important. Maybe they're not limited by rules, but they're limited by money, you know and the ability to investment. And their ability to get more out of the environment gives them a competitive advantage as well. And really what's interesting about racing, and a lot of sports is you get to witness the competition. We don't get to witness the competition between big companies day to day. You're not kind of watching it in those little micro instances. So the good thing is you get to learn a lot from such a focused, relatively small team as Red Bull Racing that you can apply to other things. So what are some of the learnings as you've got work with them that you've taken back? Well certainly they push the performance of the environment, and they push us, which is a great thing for us, and for our other clients who benefit. But one of the things I think that really stands out is the culture there of the entire team no matter what their role and function. From the driver on down to everybody else are focused on winning races and winning championships. And that team view of getting every bit of performance out of everything everybody does all the time really opened our thinking to being broader than just the scheduling of the IT infrastructure, it's also about making the design team more productive and taking steps out of the process, and anything we can do there. Inclusive of the storage management, and the data management over time. So it's not just the compute environment it's also the virtualized storage environment. Right, and just massive amounts of storage. You said not only are you running and generating, I'm just going to use boatloads 'cause I'm not sure which version of the flops you're going to use. But also you got historical data, and you have result data, and you have models that need to be tweaked, and continually upgraded so that you do better the following race. Exactly, I mean we're generating petabytes of data a year and I think one of the issues which is probably different from most industries is our workflows are incredibly complex. So we have up to 200 discrete job steps for each workflow to actually kind of produce a simulation. This is where the kind of IBM Spectrum product range actually helps us do that efficiently. If you imagine an aerospace engineer, or aerodynamics engineer trying to manually manage 200 individual job steps, it just wouldn't happen very efficiently. So this is where Spectrum scale actually kind of helps us do that. So you mentioned it briefly Bernie, but just a little bit more specifically. What are some of the other industries that you guys are showcasing that are leveraging the power of Spectrum to basically win their races. Yeah so and we talked about the infrastructure and manufacturing, but they're industrial clients. But also in financial services. So think in terms of risk analytics and financial models being an important area. Also healthcare life sciences. So molecular biology, finding new drugs. When you talk about the competition and who wins right. Genomics research and advances there. Again, you need a system and an infrastructure that can chew through vast amounts of data. Both the performance and the compute, as well as the longterm management with cost efficiency of huge volumes of data. And then you need that virtualized cluster so that you can run multiple workloads many times with an infrastructure that's running in 80%, 90% efficiency. You can't afford to have silos of clusters. Right we're seeing clients that have problems where they don't have this cluster virtualization software, have cluster creep, just like in the early days we had server sprawl, right? With a different app on a different server, and we needed to virtualize the servers. Well now we're seeing cluster creep. Right the Hadoop clusters and Spark clusters, and machine learning and deep learning clusters. As well as the traditional HPC workload. So what Spectrum computing does is virtualizes that shared cluster environment so that you can run all these different kind of workloads and drive up the efficiency of the environment. 'Cause efficiency is really the key right. You got to have efficiency that's what, that's really where cloud got its start, you know, kind of eating into the traditional space, right. There's a lot of inefficient stuff out there so you got to use your resources efficiently it's way too competitive. Correct well we're also seeing inefficiencies in the use of cloud, right. >> Jeff: Absolutely. So one of the features that we've added to the Spectrum computing recently is automated dynamic cloud bursting. So we have clients who say that they've got their scientists or their design engineers spinning up clusters in the cloud to run workloads, and then leaving the servers running, and they're paying the bill. So we built in automation where we push the workload and the data over the cloud, start the servers, run the workload. When the workload's done, spin down the servers and bring the data back to the user. And it's very cost effective that way. It's pretty fun everyone talks often about the spin up, but they forget to talk about the spin down. Well that's where the cost savings is, exactly. Alright so final words, Wayne, you know as you look forward, it's super a lot of technology in Formula One racing. You know kind of what's next, where do you guys go next in terms of trying to get another edge in Formula One racing for Red Bull specifically. I mean I'm hoping they reduce the restrictions on HPC so it can actually start using CFD and the software IBM provides in a serious manner. So it can actually start pushing the technologies way beyond where they are at the moment. It's really interesting that they, that as a restriction right, you think of like plates and size of the engine, and these types of things as the rule restrictions. But they're actually restricting based on data size, your use of high performance computing. They're trying to save money basically, but. It's crazy. So whether it's a rule or you know you're share holders, everybody's trying to save money. Alright so Bernie what are you looking at, sort of 2017 is coming to an end, it's hard for me to say that as you look forward to 2018 what are some of your priorities for 2018. Well the really important thing and we're hearing it at this conference, I'm talking with the analysts and with the clients. The next generation of HPC in analytics is what we're calling machine learning, deep learning, cognitive AI, whatever you want to call it. That's just the new generation of this workload. And our Spectrum conductor offering and our new deep learning impact capability to automate the training of deep learning models, so that you can more quickly get to an accurate model like in hours or minutes, not days or weeks. That's going to a huge break through. And based on our early client experience this year, I think 2018 is going to be a breakout year for putting that to work in commercial enterprise use cases. Alright well I look forward to the briefing a year from now at Super Computing 2018. Absolutely. Alright Bernie, Wayne, thanks for taking a few minutes out of your day, appreciate it. You're welcome, thank you. Alright he's Bernie, he's Wayne, I'm Jeff Frick we're talking Formula One Red Bull Racing here at Super Computing 2017. Thanks for watching.

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante recent survey data from etr shows that enterprise tech spending is tracking with projected u.s gdp growth at six to seven percent this year many markers continue to point the way to a strong recovery including hiring trends and the loosening of frozen it project budgets however skills shortages are blocking progress at some companies which bodes well for an increased reliance on external i.t services moreover while there's much to talk about well there's much talk about the rotation out of work from home plays and stocks such as video conferencing vdi and other remote worker tech we see organizations still trying to figure out the ideal balance between funding headquarter investments that have been neglected and getting hybrid work right in particular the talent gap combined with a digital mandate means companies face some tough decisions as to how to fund the future while serving existing customers and transforming culturally hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we welcome back eric porter bradley of etr who will share fresh data perspectives and insights from the latest survey data eric great to see you welcome thank you very much dave always good to see you and happy to be on the show again okay we're going to share some macro data and then we're going to dig into some highlights from etr's most recent march covid survey and also the latest april data so eric the first chart that we want to show it shows cio and it buyer responses to expected i.t spend for each quarter of 2021 versus 2020. and you can see here a steady quarterly improvement eric what are the key takeaways from your perspective sure well first of all for everyone out there this particular survey had a record-setting number of uh participation we had uh 1 500 i.t decision makers participate and we had over half of the fortune 500 and over a fifth of the global 1000. so it was a really good survey this is the seventh iteration of the covet impact survey specifically and this is going to transition to an over large macro survey going forward so we could continue it and you're 100 right what we've been tracking here since uh march of last year was how is spending being impacted because of covid where is it shifting and what we're seeing now finally is that there is a real re-acceleration in spend i know we've been a little bit more cautious than some of the other peers out there that just early on slapped an eight or a nine percent number but what we're seeing is right now it's at a midpoint of over six uh about six point seven percent and that is accelerating so uh we are still hopeful that that will continue uh really that spending is going to be in the second half of the year as you can see on the left part of this chart that we're looking at uh it was about 1.7 versus 3 for q1 spending year over year so that is starting to accelerate through the back half you know i think it's prudent to be be cautious relative because normally you'd say okay tech is going to grow a couple of points higher than gdp but it's it's really so hard to predict this year okay the next chart is here that we want to show you is we ask respondents to indicate what strategies they're employing in the short term as a result of coronavirus and you can see a few things that i'll call out and then i'll ask eric to chime in first there's been no meaningful change of course no surprise in tactics like remote work and halting travel however we're seeing very positive trends in other areas trending downward like hiring freezes and freezing i.t deployments downward trend in layoffs and we also see an increase in the acceleration of new i.t deployments and in hiring eric what are your key takeaways well first of all i think it's important to point out here that uh we're also capturing that people believe remote work productivity is still increasing now the trajectory might be coming down a little bit but that is really key i think to the backdrop of what's happening here so people have a perception that productivity of remote work is better than hybrid work and that's from the i.t decision makers themselves um but what we're seeing here is that uh most importantly these organizations are citing plans to increase hiring and that's something that i think is really important to point out it's showing a real thawing and to your point in right in the beginning of the intro uh we are seeing deployments stabilize versus prior survey levels which means early on they had no plans to launch new tech deployments then they said nope we're going to start and now that's stalling and i think it's exactly right what you said is there's an i.t skills shortage so people want to continue to do i.t deployments because they have to support work from home and a hybrid back return to the office but they just don't have the skills to do so and i think that's really probably the most important takeaway from this chart um is that stalling and to really ask why it's stalling yeah so we're going to get into that for sure and and i think that's a really key point is that that that accelerating it deployments is some it looks like it's hit a wall in the survey and so but before before we get deep into the skills let's let's take a look at this next chart and we're asking people here how a return to the new normal if you will and back to offices is going to change spending with on-prem architectures and applications and so the first two bars they're cloud-friendly if you add them up at 63 percent of the respondents say that either they'll stay in the cloud for the most part or they're going to lower the on-prem spend when they go back to the office the next three bars are on-prem friendly if you add those up as 29 percent of the respondents say their on-prem spend is going to bounce back to pre-covert levels or actually increase and of course 12 percent of that number by the way say they they've never altered their on-prem spend so eric no surprise but this bodes well for cloud but but it it isn't it also a positive for on-prem this we've had this dual funding premise meaning cloud continues to grow but neglected data center spend also gets a boost what's your thoughts you know really it's interesting it's people are spending on all fronts you and i were talking in a prep it's like you know we're we're in battle and i've got naval i've got you know air i've got land uh i've got to spend on cloud and digital transformation but i also have to spend for on-prem uh the hybrid work is here and it needs to be supported so this spending is going to increase you know when you look at this chart you're going to see though that roughly 36 percent of all respondents say that their spending is going to remain mostly on cloud so this you know that is still the clear direction uh digital transformation is still happening covid accelerated it greatly um you know you and i as journalists and researchers already know this is where the puck is going uh but spend has always lagged a little bit behind because it just takes some time to get there you know inversely 27 said that their on-prem spending will decrease so when you look at those two i still think that the trend is the friend for cloud spending uh even though yes they do have to continue spending on hybrid some of it's been neglected there are refresh cycles coming up so overall it just points to more and more spending right now it really does seem to be a very strong backdrop for it growth so i want to talk a little bit about the etr taxonomy before we bring up the next chart we get a lot of questions about this and of course when you do a massive survey like you're doing you have to have consistency for time series so you have to really think through what that what the buckets look like if you will so this next chart takes a look at the etr taxonomy and it breaks it down into simple to understand terms so the green is the portion of spending on a vendor's tech within a category that is accelerating and the red is the portion that is decelerating so eric what are the key messages in this data well first of all dave thank you so much for pointing that out we used to do uh just what we call a next a net score it's a proprietary formula that we use to determine the overall velocity of spending some people found it confusing um our data scientists decided to break this sector breakdown into what you said which is really more of a mode analysis in that sector how many of the vendors are increasing versus decreasing so again i just appreciate you bringing that up and allowing us to explain the the the reasoning behind our analysis there but what we're seeing here uh goes back to something you and i did last year when we did our predictions and that was that it services and consulting was going to have a true rebound in 2021 and that's what this is showing right here so in this chart you're going to see that consulting and services are really continuing their recovery uh 2020 had a lot of declines and they have the biggest sector over year-over-year acceleration sector-wise the other thing to point out in this which we'll get to again later is that the inverse analysis is true for video conferencing uh we will get to that so i'm going to leave a little bit of ammunition behind for that one but what we're seeing here is it consulting services being the real favorable and video conferencing uh having a little bit more trouble great okay and then let's let's take a look at that services piece and this next chart really is a drill down into that space and emphasizes eric what you were just talking about and we saw this in ibm's earnings where still more than 60 percent of ibm's business comes from services and the company beat earnings you know in part due to services outperforming expectations i think it had a somewhat easier compare and some of this pen-up demand that we've been talking about bodes well for ibm and in other services companies it's not just ibm right eric no it's not but again i'm going to point out that you and i did point out ibm in our in our predictions one we did in late december so it is nice to see one of the reasons we don't have a more favorable rating on ibm at the moment is because they are in the the process of spinning out uh this large unit and so there's a little bit of you know corporate action there that keeps us off on the sideline but i would also want to point out here uh tata infosys and cognizant because they're seeing year-over-year acceleration in both it consulting and outsourced i t services so we break those down separately and those are the three names that are seeing acceleration in both of those so again a tata emphasis and cognizant are all looking pretty well positioned as well so we've been talking a little bit about this skill shortage and this is what's i think so hard for for forecasters um is that you know on the one hand there's a lot of pent up demand you know it's like scott gottlieb said it's like woodstock coming out of the covid uh but on the other hand if you have a talent gap you've got to rely on external services so there's a learning curve there's a ramp up it's an external company and so it takes time to put those together so so this data that we're going to show you next uh is is really important in my view and ties what we're saying we're saying at the top it asks respondents to comment on their staffing plans the light blue is we're increasing staff the gray is no change in the magenta or whatever whatever color that is that sort of purplish color anyway that color is is decreasing and the picture is very positive across the board full-time staff offshoring contract employees outsourced professional services all up trending upwards and this eric is more evidence of the services bounce back yeah it certainly is david and what happened is when we caught this trend we decided to go one level deeper and say all right we're seeing this but we need to know why and that's what we always try to do here data will tell you what's happening it doesn't always tell you why and that's one of the things that etr really tries to dig in with through the insights interviews panels and also going direct with these more custom survey questions uh so in this instance i think the real takeaway is that 30 of the respondents said that their outsourced and managed services are going to increase over the next three months that's really powerful that's a large portion of organizations in a very short time period so we're capturing that this acceleration is happening right now and it will be happening in real time and i don't see it slowing down you and i are speaking about we have to you know increase cloud spend we have to increase hybrid spend there are refresh cycles coming up and there's just a real skill shortage so this is a long-term setup that bodes very well for it services and consulting you know eric when i came out of college i somebody told me read read read read as much as you can and and so i would and they said read the wall street journal every day and i so i did it and i would read the tech magazines and back then it was all paper and what happens is you begin to connect the dots and so the reason i bring that up is because i've now been had taken a bath in the etr data for the better part of two years and i'm beginning to be able to connect the dots you know the data is not always predictive but many many times it is and so this next data gets into the fun stuff where we name names a lot of times people don't like it because the marketing people and organizations say well the data's wrong of course that's the first thing they do is attack the data but you and i know we've made some really great calls work from home for sure you're talking about the services bounce back uh we certainly saw the rise of crowdstrike octa zscaler well before people were talking about that same thing with video conferencing and so so anyway this is the fun stuff and it looks at positive versus negative sentiment on on companies so first how does etr derive this data and how should we interpret it and what are some of your takeaways [Music] sure first of all how we derive the data or systematic um survey responses that we do on a quarterly basis and we standardize those responses to allow for time series analysis so we can do trend analysis as well we do find that our data because it's talking about forward-looking spending intentions is really more predictive because we're talking about things that might be happening six months three months in the future not things that a lot of other competitors and research peers are looking at things that already happened uh they're looking in the past etr really likes to look into the future and our surveys are set up to do so so thank you for that question it's an enjoyable lead-in but to get to the fun stuff like you said uh what we do here is we put ratings on the data sets i do want to put the caveat out there that our spending intentions really only captures top-line revenue it is not indicative of profit margin or any other line items so this is only going to be viewed as what we are rating the data set itself not the company um you know that's not what we're in the game of doing so i think that's very important for the marketing and the vendors out there themselves when they when they take a look at this we're just talking about what we can control which is our data we're going to talk about a few of the names here on this highlighted vendors list one we're going to go back to that you and i spoke about i guess about six months ago or maybe even earlier which was the observability space um you and i were noticing that it was getting very crowded a lot of new entrants um there was a lot of acquisition from more of the legacy or standard entrance players in the space and that is continuing so i think in a minute we're going to move into that observability space but what we're seeing there is that it's becoming incredibly crowded and we're possibly seeing signs of them cannibalizing each other uh we're also going to move on a little bit into video conferencing where we're capturing some spend deceleration and then ultimately we're going to get into a little bit of a storage refresh cycle and talk about that but yeah these are the highlighted vendors for april um we usually do this once a quarter and they do change based on the data but they're not usually whipsawed around the data doesn't move that quickly yeah so you can see the some of the big names on the left-hand side some of the sas companies that have momentum obviously servicenow has been doing very very well we've talked a lot about snowflake octa crowdstrike z scalar in all very positive as well as you know several others i i guess i'd add some some things i mean i think if thinking about the next decade it's it's cloud which is not going to be like the same cloud as last decade a lot of machine learning and deep learning and ai and the cloud is extending to the edge in the data center data obviously very important data is decentralized and distributed so data architectures are changing a lot of opportunities to connect across clouds and actually create abstraction layers and then something that we've been covering a lot is processor performance is actually accelerating relative to moore's law it's probably instead of doubling every two years it's quadrupling every two years and so that is a huge factor especially as it relates to powering ai and ai inferencing at the edge this is a whole new territory custom silicon is is really becoming in vogue uh and so we're something that we're watching very very closely yeah i completely completely agree on that and i do think that the the next version of cloud will be very different another thing to point out on that too is you can't do anything that you're talking about without collecting the data and and organizations are extremely serious about that now it seems it doesn't matter what industry they're in every company is a data company and that also bodes well for the storage call we do believe that there is going to just be a huge increase in the need for storage um and yes hopefully that'll become portable across multi-cloud and hybrid as well now as eric said the the etr data's it's it's really focused on that top line spend so if you look at the uh on on the right side of that chart you saw you know netapp was kind of negative was very negative right but there's a company that's in in transformation now they've lowered expectations and they've recently beat expectations that's why the stock has been doing better but but at the macro from a spending standpoint it's still challenged so you have big footprint companies like netapp and oracle is another one oracle's stock is at an all-time high but the spending relative to sort of previous cycles or relative to you know like for instance snowflake much much smaller not as high growth but they're managing expectations they're managing their transition they're managing profitability zoom is another one zoom looking looking negative but you know zoom's got to use its market cap now to to transform and increase its tam uh and then splunk is another one we're going to talk about splunk is in transition it acquired signal fx it just brought on this week teresa carlson who was the head of aws public sector she's the president and head of sales so they've got a go to market challenge and they brought in teresa carlson to really solve that but but splunk has been trending downward we called that you know several quarters ago eric and so i want to bring up the data on splunk and this is splunk eric in analytics and it's not trending in the right direction the green is accelerating span the red is and the bars is decelerating spend the top blue line is spending velocity or net score and the yellow line is market share or pervasiveness in the data set your thoughts yeah first i want to go back is a great point dave about our data versus a disconnect from an equity analysis perspective i used to be an equity analyst that is not what we do here and you you may the main word you said is expectations right stocks will trade on how they do compared to the expectations that are set uh whether that's buy side expectations sell side expectations or management's guidance themselves we have no business in tracking any of that what we are talking about is top line acceleration or deceleration so uh that was a great point to make and i do think it's an important one for all of our listeners out there now uh to move to splunk yes i've been capturing a lot of negative commentary on splunk even before the data turned so this has been about a year-long uh you know our analysis and review on this name and i'm dating myself here but i know you and i are both rock and roll fans so i'm gonna point out a led zeppelin song and movie and say that the song remains the same for splunk we are just seeing uh you know recent spending intentions are taking yet another step down both from prior survey levels from year ago levels uh this we're looking at in the analytics sector and spending intentions are decelerating across every single customer group if we went to one of our other slide analysis um on the etr plus platform and you do by customer sub sample in analytics it's dropping in every single vertical it doesn't matter which one uh it's really not looking good unfortunately and you had mentioned this as an analytics and i do believe the next slide is an information security yeah let's bring that up and it's unfortunately it's not doing much better so this is specifically fortune 500 accounts and information security uh you know there's deep pockets in the fortune 500 but from what we're hearing in all the insights and interviews and panels that i personally moderate for etr people are upset they didn't like the the strong tactics that splunk has used on them in the past they didn't like the ingestion model pricing the inflexibility and when alternatives came along people are willing to look at the alternatives and that's what we're seeing in both analytics and big data and also for their sim in security yeah so i think again i i point to teresa carlson she's got a big job but she's very capable she's gonna she's gonna meet with a lot of customers she's a go to market pro she's gonna have to listen hard and i think you're gonna you're gonna see some changes there um okay so there's more sorry there's more bad news on splunk so bring this up is is is net score for splunk in elastic accounts uh this is for analytics so there's 106 elastic accounts that uh in the data set that also have splunk and it's trending downward for splunk that's why it's green for elastic and eric the important call out from etr here is how splunk's performance in elastic accounts compares with its performance overall the elk stack which obviously elastic is a big part of that is causing pain for splunk as is data dog and you mentioned the pricing issue uh is it is it just well is it pricing in your assessment or is it more fundamental you know it's multi-level based on the commentary we get from our itdms that take the survey so yes you did a great job with this analysis what we're looking at is uh the spending within shared accounts so if i have splunk already how am i spending i'm sorry if i have elastic already how is my spending on splunk and what you're seeing here is it's down to about a 12 net score whereas splunk overall has a 32 net score among all of its customers so what you're seeing there is there is definitely a drain that's happening where elastic is draining spend from splunk and usage from them uh the reason we used elastic here is because all observabilities the whole sector seems to be decelerating splunk is decelerating the most but elastic is the only one that's actually showing resiliency so that's why we decided to choose these two but you pointed out yes it's also datadog datadog is cloud native uh they're more devops oriented they tend to be viewed as having technological lead as compared to splunk so that's a really good point a dynatrace also is expanding their abilities and splunk has been making a lot of acquisitions to push their cloud services they are also changing their pricing model right they're they're trying to make things a little bit more flexible moving off ingestion um and moving towards uh you know consumption so they are trying and the new hires you know i'm not gonna bet against them because the one thing that splunk has going for them is their market share in our survey they're still very well entrenched so they do have a lot of accounts they have their foothold so if they can find a way to make these changes then they you know will be able to change themselves but the one thing i got to say across the whole sector is competition is increasing and it does appear based on commentary and data that they're starting to cannibalize themselves it really seems pretty hard to get away from that and you know there are startups in the observability space too that are going to be you know even more disruptive i think i think i want to key on the pricing for a moment and i've been pretty vocal about this i think the the old sas pricing model where essentially you essentially lock in for a year or two years or three years pay up front or maybe pay quarterly if you're lucky that's a one-way street and i think it's it's a flawed model i like what snowflake's doing i like what datadog's doing look at what stripe is doing look what twilio is doing these are cons you mentioned it because it's consumption based pricing and if you've got a great product put it out there and you know damn the torpedoes and i think that is a game changer i i look at for instance hpe with green lake i look at dell with apex they're trying to mimic that model you know they're there and apply it to to infrastructure it's much harder with infrastructure because you got to deploy physical infrastructure but but that is a model that i think is going to change and i think all of the traditional sas pricing is going to is going to come under disruption over the next you know better part of the decades but anyway uh let's move on we've we've been covering the the apm space uh pretty extensively application performance management and this chart lines up some of the big players here comparing net score or spending momentum from the april 20th survey the gray is is um is sorry the the the gray is the april 20th survey the blue is jan 21 and the yellow is april 21. and not only are elastic and data dog doing well relative to splunk eric but everything is down from last year so this space as you point out is undergoing a transformation yeah the pressures are real and it's you know it's sort of that perfect storm where it's not only the data that's telling us that but also the direct feedback we get from the community uh pretty much all the interviews i do i've done a few panels specifically on this topic for anyone who wants to you know dive a little bit deeper we've had some experts talk about this space and there really is no denying that there is a deceleration in spend and it's happening because that spend is getting spread out among different vendors people are using you know a data dog for certain aspects they're using elastic where they can because it's cheaper they're using splunk because they have to but because it's so expensive they're cutting some of the things that they're putting into splunk which is dangerous particularly on the security side if i have to decide what to put in and whatnot that's not really the right way to have security hygiene um so you know this space is just getting crowded there's disruptive vendors coming from the emerging space as well and what you're seeing here is the only bit of positivity is elastic on a survey over survey basis with a slight slight uptick everywhere else year over year and survey over survey it's showing declines it's just hard to ignore and then you've got dynatrace who based on the the interviews you do in the venn you're you know one on one or one on five you know the private interviews that i've been invited to dynatrace gets very high scores uh for their road map you've got new relic which has been struggling you know financially but they've got a purpose built they've got a really good product and a purpose-built database just for this apm space and then of course you've got cisco with appd which is a strong business for them and then as you mentioned you've got startups coming in you've got chaos search which ed walsh is now running you know leave the data in place in aws and really interesting model honeycomb it's going to be really disruptive jeremy burton's company observed so this space is it's becoming jump ball yeah there's a great line that came out of one of them and that was that the lines are blurring it used to be that you knew exactly that app dynamics what they were doing it was apm only or it was logging and monitoring only and a lot of what i'm hearing from the itdm experts is that the lines are blurring amongst all of these names they all have functionality that kind of crosses over each other and the other interesting thing is it used to be application versus infrastructure monitoring but as you know infrastructure is becoming code more and more and more and as infrastructure becomes code there's really no difference between application and infrastructure monitoring so we're seeing a convergence and a blurring of the lines in this space which really doesn't bode well and a great point about new relic their tech gets good remarks uh i just don't know if their enterprise level service and sales is up to snuff right now um as one of my experts said a cto of a very large public online hospitality company essentially said that he would be shocked that within 18 months if all of these players are still uh standalone that there needs to be some m a or convergence in this space okay now we're going to call out some of the data that that really has jumped out to etr in the latest survey and some of the names that are getting the most queries from etr clients which are many of which are investor clients so let's start by having a look at one of the most important and prominent work from home names zoom uh let's let's look at this eric is the ride over for zoom oh i've been saying it for a little bit of a time now actually i do believe it is um i will get into it but again pointing out great dave uh the reason we're presenting today splunk elastic and zoom are they are the most viewed on the etr plus platform uh trailing behind that only slightly is f5 i decided not to bring f5 to the table today because we don't have a rating on the data set um so then i went one deep one below that and it's pure so the reason we're presenting these to you today is that these are the ones that our clients and our community are most interested in which is hopefully going to gain interest to your viewers as well so to get to zoom um yeah i call zoom the pandec pandemic bull market baby uh this was really just one that had a meteoric ride you look back january in 2020 the stock was at 60 and 10 months later it was like like 580. that's in 10 months um that's cooled down a little bit uh into the mid 300s and i believe that cooling down should continue and the reason why is because we are seeing a huge deceleration in our spending intentions uh they're hitting all-time lows it's really just a very ugly data set um more importantly than the spending intentions for the first time we're seeing customer growth in our survey flattened in the past we could we knew that the the deceleration and spend was happening but meanwhile their new customer growth was accelerating so it was kind of hard to really make any call based on that this is the first time we're seeing flattening customer growth trajectory and that uh in tandem with just dominance from microsoft in every sector they're involved in i don't care if it's ip telephony productivity apps or the core video conferencing microsoft is just dominating so there's really just no way to ignore this anymore the data and the commentary state that zoom is facing some headwinds well plus you've pointed out to me that a lot of your private conversations with buyers says that hey we're we're using the freebie version of zoom you know we're not paying them and so in that combined with teams i mean it's it's uh it's i think you know look zoom has to figure it out they they've got to they've got to figure out how to use their elevated market cap to transform and expand their tan um but let's let's move on here's the data on pure storage and we've highlighted a number of times this company is showing elevated spending intentions um pure announces earnings in in may ibm uh just announced storage what uh it was way down actually so sort of still pure more positive but i'll comment on a moment but what does this data tell you eric yeah you know right now we started seeing this data last survey in january and that was the first time we really went positive on the data set itself and it's just really uh continuing so we're seeing the strongest year-over-year acceleration in the entire survey um which is a really good spot to be pure is also a leading position in among its sector peers and the other thing that was pretty interesting from the data set is among all storage players pure has the highest positive public cloud correlation so what we can do is we can see which respondents are accelerating their public cloud spend and then cross-reference that with their storage spend and pure is best positioned so as you and i both know uh you know digital transformation cloud spending is increasing you need to be aligned with that and among all storage uh sector peers uh pure is best positioned in all of those in spending intentions and uh adoptions and also public cloud correlation so yet again just another really strong data set and i have an anecdote about why this might be happening because when i saw the date i started asking in my interviews what's going on here and there was one particular person he was a director of cloud operations for a very large public tech company now they have hybrid um but their data center is in colo so they don't own and build their own physical building he pointed out that doran kovid his company wanted to increase storage but he couldn't get into his colo center due to covert restrictions they weren't allowed you had so 250 000 square feet right but you're only allowed to have six people in there so it's pretty hard to get to your rack and get work done he said he would buy storage but then the cola would say hey you got to get it out of here it's not even allowed to sit here we don't want it in our facility so he has all this pent up demand in tandem with pent up demand we have a refresh cycle the ssd you know depreciation uh you know cycle is ending uh you know ssds are moving on and we're starting to see uh new technology in that space nvme sorry for technology increasing in that space so we have pent up demand and we have new technology and that's really leading to a refresh cycle and this particular itdm that i spoke to and many of his peers think this has a long tailwind that uh storage could be a good sector for some time to come that's really interesting thank you for that that extra metadata and i want to do a little deeper dive on on storage so here's a look at storage in the the industry in context and some of the competitive i mean it's been a tough market for the reasons that we've highlighted cloud has been eating away that flash headroom it used to be you'd buy storage to get you know more spindles and more performance and you were sort of forced to buy more flash gave more headroom but it's interesting what you're saying about the depreciation cycle so that's good news so etr combines just for people's benefit here combines primary and secondary storage into a single category so you have companies like pure and netapp which are really pure play you know primary storage companies largely in the sector along with veeam cohesity and rubric which are kind of secondary data or data protection so my my quick thoughts here are that pure is elevated and remains what i call the one-eyed man in the land of the blind but that's positive tailwinds there so that's good news rubric is very elevated but down it's a big it's big competitor cohesity is way off its highs and i have to say to me veeam is like the steady eddy consistent player here they just really continue to do well in the data protection business and and the highs are steady the lows are steady dell is also notable they've been struggling in storage their isg business which comprises service and storage it's been soft during covid and and during even you know this new product rollout so it's notable with this new mid-range they have in particular the uptick in dell this survey because dell so large a small uptick can be very good for dell hpe has a big announcement next month in storage so that might improve based on a product cycle of course the nimble brand continues to do well ibm as i said just announced a very soft quarter you know down double digits again uh and there in a product cycle shift and netapp is that looks bad in the etr data from a spending momentum standpoint but their management team is transforming the company into a cloud play which eric is why it was interesting that pure has the greatest momentum in in cloud accounts so that is sort of striking to me i would have thought it would be netapp so that's something that we want to pay attention to but i do like a lot of what netapp is doing uh and other than pure they're the only big kind of pure play in primary storage so long winded uh uh intro there eric but anything you'd add no actually i appreciate it was long winded i i'm going to be honest with you storage is not my uh my best sector as far as a researcher and analyst goes uh but i actually think a lot of what you said is spot on um you know we do capture a lot of large organizations spend uh we don't capture much mid and small so i think when you're talking about these large large players like netapp and um you know not looking so good all i would state is that we are capturing really big organizations spending attention so these are names that should be doing better to be quite honest uh in those accounts and you know at least according to our data we're not seeing it and it's long-term depression as you can see uh you know netapp now has a negative spending velocity in this analysis so you know i can go dig around a little bit more but right now the names that i'm hearing are pure cohesity uh um i'm hearing a little bit about hitachi trying to reinvent themselves in the space but you know i'll take a wait-and-see approach on that one but uh pure and cohesity are the ones i'm hearing a lot from our community so storage is transforming to cloud as a service you're seeing things like apex and in green lake from dell and hpe and container storage little so not really a lot of people paying attention to it but pure about a company called portworx which really specializes in container storage and there's many startups there they're trying to really change the way david flynn has a startup in that space he's the guy who started fusion i o so a lot a lot of transformations happening here okay i know it's been a long segment we have to summarize and then let me go through a summary and then i'll give you the last word eric so tech spending appears to be tracking us gdp at six to seven percent this talent shortage could be a blocker to accelerating i.t deployments and that's kind of good news actually for for services companies digital transformation you know it's it remains a priority and that bodes well not only for services but automation uipath went public this week we we profiled that you know extensively that went public last wednesday um organizations they've i said at the top face some tough decisions on how to allocate resources you know running the business growing the business transforming the business and we're seeing a bifurcation of spending and some residual effects on vendors and that remains a theme that we're watching eric your final thoughts yeah i'm going to go back quickly to just the overall macro spending because there's one thing i think is interesting to point out and we're seeing a real acceleration among mid and small so it seems like early on in the covid recovery or kovitz spending it was the deep pockets that moved first right fortune 500 knew they had to support remote work they started spending first round that in the fortune 500 we're only seeing about five percent spent but when you get into mid and small organizations that's creeping up to eight nine so i just think it's important to point out that they're playing catch-up right now uh also would point out that this is heavily skewed to north america spending we're seeing laggards in emea they just don't seem to be spending as much they're in a very different place in their recovery and uh you know i do think that it's important to point that out um lastly i also want to mention i know you do such a great job on following a lot of the disruptive vendors that you just pointed out pure doing container storage we also have another bi-annual survey that we do called emerging technology and that's for the private names that's going to be launching in may for everyone out there who's interested in not only the disruptive vendors but also private equity players uh keep an eye out for that we do that twice a year and that's growing in its respondents as well and then lastly one comment because you mentioned the uipath ipo it was really hard for us to sit on the sidelines and not put some sort of rating on their data set but ultimately um the data was muted unfortunately and when you're seeing this kind of hype into an ipo like we saw with snowflake the data was resoundingly strong we had no choice but to listen to what the data said for snowflake despite the hype um we didn't see that for uipath and we wanted to and i'm not making a large call there but i do think it's interesting to juxtapose the two that when snowflake was heading to its ipo the data was resoundingly positive and for uipath we just didn't see that thank you for that and eric thanks for coming on today it's really a pleasure to have you and uh so really appreciate the the uh collaboration and look forward to doing more of these we enjoy the partnership greatly dave we're very very happy to have you in the etr family and looking forward to doing a lot lot more with you in the future ditto okay that's it for today remember these episodes are all available as podcasts wherever you listen all you got to do is search breaking analysis podcast and please subscribe to the series check out etr's website it's etr dot plus we also publish a full report every week on wikibon.com at siliconangle.com you can email me david.velante at siliconangle.com you can dm me on twitter at dvalante or comment on our linkedin post i could see you in clubhouse this is dave vellante for eric porter bradley for the cube insights powered by etr have a great week stay safe be well and we'll see you next time

>>Thank you for joining us for accelerate next event. I hope you're enjoying it so far. I know you've heard about the industry challenges the I. T. Trends HP strategy from leaders in the industry and so today what we wanna do is focus on going deep on workload solutions. So in the most important workload solutions, the ones we always get asked about and so today we want to share with you some best practices, some examples of how we've helped other customers and how we can help you. All right with that. I'd like to start our panel now and introduce chris idler, who's the vice president and general manager of the element. Chris has extensive solution expertise, he's led HP solution engineering programs in the past. Welcome chris and Mark Nickerson, who is the Director of product management and his team is responsible for solution offerings, making sure we have the right solutions for our customers. Welcome guys, thanks for joining me. >>Thanks for having us christa. >>Yeah, so I'd like to start off with one of the big ones, the ones that we get asked about all the time, what we've been all been experienced in the last year, remote work, remote education and all the challenges that go along with that. So let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environments. >>Uh So I I really think that there's a couple of things that have stood out for me when we're talking with customers about V. D. I. Um first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why, but what it really uncovered was how little planning had gone into this space around a couple of key dynamics. One is scale. Um it's one thing to say, I'm going to enable V. D. I. For a part of my work force in a pre pandemic environment where the office was still the central hub of activity for work. It's a completely different scale. When you think about okay I'm going to have 50, 60, 80, maybe 100 of my workforce now distributed around the globe. Um Whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning, Whether that's in the area of things like Formula one racing, where we had the desire to still have events going on. But the need for a lot more social distancing. Not as many people able to be trackside but still needing to have that real time experience. This really manifested in a lot of ways and scale was something that I think a lot of customers hadn't put as much thought into. Initially the other area is around planning for experience a lot of times the V. D. I. Experience was planned out with very specific workloads are very specific applications in mind. And when you take it to a more broad based environment, if we're going to support multiple functions, multiple lines of business, there hasn't been as much planning or investigation that's gone into the application side. And so thinking about how graphically intense some applications are. Uh one customer that comes to mind would be Tyler I. S. D. Who did a fairly large rollout pre pandemic and as part of their big modernization effort, what they uncovered was even just changes in standard Windows applications Had become so much more graphically intense with Windows 10 with the latest updates with programs like Adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than they had counted on. So, um, in addition to planning for scale, you also need to have that visibility into what are the actual applications that are going to be used by these remote users? How graphically intense those might be. What's the logging experience going to be as well as the operating experience. And so really planning through that experience side as well as the scale and the number of users is kind of really two of the biggest, most important things that I've seen. >>You know, Mark, I'll just jump in real quick. I think you covered that pretty comprehensively there and it was well done. The a couple of observations I've made, one is just that um, V. D. I suddenly become like mission critical for sales. It's the front line, you know, for schools, it's the classroom, you know, that this isn't Uh cost cutting measure or uh optimization in IT. measure anymore. This is about running the business in a way it's a digital transformation. One aspect of about 1000 aspects of what does it mean to completely change how your business does. And I think what that translates to is that there's no margin for error, right? You know, you really need to to deploy this in a way that that performs, that understands what you're trying to use it for. That gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be, whether it's a racetrack classroom or on the other end of a conference call or a boardroom. Right? So what we do in the engineering side of things when it comes to V. D. I. R. Really understand what's a tech worker, What's a knowledge worker? What's the power worker? What's a gP really going to look like? What time of day look like, You know, who's using it in the morning, Who is using it in the evening? When do you power up? When do you power down? Does the system behave? Does it just have the, it works function and what our clients can can get from H. P. E. Is um you know, a worldwide set of experiences that we can apply to, making sure that the solution delivers on its promises. So we're seeing the same thing you are christa, We see it all the time on beady eye and on the way businesses are changing the way they do business. >>Yeah. It's funny because when I talked to customers, you know, one of the things I heard that was a good tip is to roll it out to small groups first so you can really get a good sense of what the experiences before you roll it out to a lot of other people and then the expertise. Um It's not like every other workload that people have done before. So if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way. Okay. One of the other things we've been talking a lot about today is digital transformation and moving to the edge. So now I'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time I'll start with chris. >>All right Hey thanks. Okay so you know it's funny when it comes to edge because um the edge is different for every customer and every client and every single client that I've ever spoken to of. H. P. S. Has an edge somewhere. You know whether just like we were talking about the classroom might be the edge. But I think the industry when we're talking about edges talking about you know the internet of things if you remember that term from not too not too long ago you know and and the fact that everything is getting connected and how do we turn that into um into telemetry? And I think Mark is going to be able to talk through a a couple of examples of clients that we have in things like racing and automotive. But what we're learning about Edge is it's not just how do you make the Edge work? It's how do you integrate the edge into what you're already doing? And nobody's just the edge. Right. And so if it's if it's um ai ml dl there that's one way you want to use the edge. If it's a customer experience point of service, it's another, you know, there's yet another way to use the edge. So, it turns out that having a broad set of expertise like HP does, um, to be able to understand the different workloads that you're trying to tie together, including the ones that are running at the, at the edge. Often it involves really making sure you understand the data pipeline. What information is at the edge? How does it flow to the data center? How does it flow? And then which data center, which private cloud? Which public cloud are you using? Um, I think those are the areas where we, we really sort of shine is that we we understand the interconnectedness of these things. And so, for example, Red Bull, and I know you're going to talk about that in a minute mark, um the racing company, you know, for them the edges, the racetrack and, and you know, milliseconds or partial seconds winning and losing races, but then there's also an edge of um workers that are doing the design for the cars and how do they get quick access? So, um, we have a broad variety of infrastructure form factors and compute form factors to help with the edge. And this is another real advantage we have is that we we know how to put the right piece of equipment with the right software. And we also have great containerized software with our admiral container platform. So we're really becoming um, a perfect platform for hosting edge centric workloads and applications and data processing. Uh, it's uh um all the way down to things like a Superdome flex in the background. If you have some really, really, really big data that needs to be processed and of course our workhorse reliance that can be configured to support almost every combination of workload you have. So I know you started with edge christa but and and we're and we nail the edge with those different form factors, but let's make sure, you know, if you're listening to this, this show right now, um make sure you you don't isolate the edge and make sure they integrated with um with the rest of your operation, Mark, you know, what did I miss? >>Yeah, to that point chris I mean and this kind of actually ties the two things together that we've been talking about here at the Edge has become more critical as we have seen more work moving to the edge as where we do work, changes and evolves. And the edge has also become that much more closer because it has to be that much more connected. Um, to your point talking about where that edge exists, that edge can be a lot of different places. Um, but the one commonality really is that the edge is an area where work still needs to get accomplished. It can't just be a collection point and then everything gets shipped back to a data center back to some other area for the work. It's where the work actually needs to get done. Whether that's edge work in a used case like V. D. I. Or whether that's edge work. In the case of doing real time analytics, you mentioned red bull racing, I'll bring that up. I mean, you talk about uh, an area where time is of the essence, everything about that sport comes down to time. You're talking about wins and losses that are measured as you said in milliseconds. And that applies not just to how performance is happening on the track, but how you're able to adapt and modify the needs of the car, adapt to the evolving conditions on the track itself. And so when you talk about putting together a solution for an edge like that, you're right. It can't just be, here's a product that's going to allow us to collect data, ship it back someplace else and and wait for it to be processed in a couple of days, you have to have the ability to analyze that in real time. When we pull together a solution involving our compute products are storage products or networking products. When we're able to deliver that full package solution at the edge, what you see results like a 50 decrease in processing time to make real time analytic decisions about configurations for the car and adapting to real time test and track conditions. >>Yeah, really great point there. Um, and I really love the example of edge and racing because I mean that is where it all every millisecond counts. Um, and so important to process that at the edge. Now, switching gears just a little bit. Let's talk a little bit about um some examples of how we've helped customers when it comes to business agility and optimizing the workload for maximum outcome for business agility. Let's talk about some things that we've done to help customers with that >>mark, give it a >>shot. >>Uh, So when we, when we think about business agility, what you're really talking about is the ability to implement on the fly to be able to scale up and scale down the ability to adapt to real time changing situations. And I think the last year has been, has been an excellent example of exactly how so many businesses have been forced to do that. Um I think one of the areas that I think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds. Um if you take a look at the need that customers have to be able to migrate workloads and migrate data between public cloud environments, app development environments that may be hosted on site or maybe in the cloud, the ability to move out of development and into production and having the agility to then scale those application rollouts up, having the ability to have some of that. Um some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers. >>All right, well, we could keep going on and on, but I'll stop it there. Uh, thank you so much Chris and Mark. This has been a great discussion. Thanks for sharing how we help other customers and some tips and advice for approaching these workloads. I thank you all for joining us and remind you to look at the on demand sessions. If you want to double click a little bit more into what we've been covering all day today, you can learn a lot more in those sessions. And I thank you for your time. Thanks for tuning in today.

momentum is gathering [Music] business is evolving more and more quickly moving through one transformation to the next because change never stops it only accelerates this is a world that demands a new kind of compute deployed from edge to core to cloud compute that can outpace the rapidly changing needs of businesses large and small unlocking new insights turning data into outcomes empowering new experiences compute that can scale up or scale down with minimum investment and effort guided by years of expertise protected by 360-degree security served up as a service to let it control own and manage massive workloads that weren't there yesterday and might not be there tomorrow this is the compute power that will drive progress giving your business what you need to be ready for what's next this is the compute power of hpe delivering your foundation for digital transformation welcome to accelerating next thank you so much for joining us today we have a great program we're going to talk tech with experts we'll be diving into the changing economics of our industry and how to think about the next phase of your digital transformation now very importantly we're also going to talk about how to optimize workloads from edge to exascale with full security and automation all coming to you as a service and with me to kick things off is neil mcdonald who's the gm of compute at hpe neil always a pleasure great to have you on it's great to see you dave now of course when we spoke a year ago you know we had hoped by this time we'd be face to face but you know here we are again you know this pandemic it's obviously affected businesses and people in in so many ways that we could never have imagined but in the reality is in reality tech companies have literally saved the day let's start off how is hpe contributing to helping your customers navigate through things that are so rapidly shifting in the marketplace well dave it's nice to be speaking to you again and i look forward to being able to do this in person some point the pandemic has really accelerated the need for transformation in businesses of all sizes more than three-quarters of cios report that the crisis has forced them to accelerate their strategic agendas organizations that were already transforming or having to transform faster and organizations that weren't on that journey yet are having to rapidly develop and execute a plan to adapt to this new reality our customers are on this journey and they need a partner for not just the compute technology but also the expertise and economics that they need for that digital transformation and for us this is all about unmatched optimization for workloads from the edge to the enterprise to exascale with 360 degree security and the intelligent automation all available in that as a service experience well you know as you well know it's a challenge to manage through any transformation let alone having to set up remote workers overnight securing them resetting budget priorities what are some of the barriers that you see customers are working hard to overcome simply per the organizations that we talk with are challenged in three areas they need the financial capacity to actually execute a transformation they need the access to the resource and the expertise needed to successfully deliver on a transformation and they have to find the way to match their investments with the revenues for the new services that they're putting in place to service their customers in this environment you know we have a data partner called etr enterprise technology research and the spending data that we see from them is it's quite dramatic i mean last year we saw a contraction of roughly five percent of in terms of i.t spending budgets etc and this year we're seeing a pretty significant rebound maybe a six to seven percent growth range is the prediction the challenge we see is organizations have to they've got to iterate on that i call it the forced march to digital transformation and yet they also have to balance their investments for example at the corporate headquarters which have kind of been neglected is there any help in sight for the customers that are trying to reduce their spend and also take advantage of their investment capacity i think you're right many businesses are understandably reluctant to loosen the purse strings right now given all of the uncertainty and often a digital transformation is viewed as a massive upfront investment that will pay off in the long term and that can be a real challenge in an environment like this but it doesn't need to be we work through hpe financial services to help our customers create the investment capacity to accelerate the transformation often by leveraging assets they already have and helping them monetize them in order to free up the capacity to accelerate what's next for their infrastructure and for their business so can we drill into that i wonder if we could add some specifics i mean how do you ensure a successful outcome what are you really paying attention to as those sort of markers for success well when you think about the journey that an organization is going through it's tough to be able to run the business and transform at the same time and one of the constraints is having the people with enough bandwidth and enough expertise to be able to do both so we're addressing that in two ways for our customers one is by helping them confidently deploy new solutions which we have engineered leveraging decades of expertise and experience in engineering to deliver those workload optimized portfolios that take the risk and the complexity out of assembling some of these solutions and give them a pre-packaged validated supported solution intact that simplifies that work for them but in other cases we can enhance our customers bandwidth by bringing them hpe point next experts with all of the capabilities we have to help them plan deliver and support these i.t projects and transformations organizations can get on a faster track of modernization getting greater insight and control as they do it we're a trusted partner to get the most for a business that's on this journey in making these critical compute investments to underpin the transformations and whether that's planning to optimizing to safe retirement at the end of life we can bring that expertise to bayer to help amplify what our customers already have in-house and help them accelerate and succeed in executing these transformations thank you for that neil so let's talk about some of the other changes that customers are seeing and the cloud has obviously forced customers and their suppliers to really rethink how technology is packaged how it's consumed how it's priced i mean there's no doubt in that to take green lake it's obviously a leading example of a pay as pay-as-you-scale infrastructure model and it could be applied on-prem or hybrid can you maybe give us a sense as to where you are today with green lake well it's really exciting you know from our first pay-as-you-go offering back in 2006 15 years ago to the introduction of green lake hpe has really been paving the way on consumption-based services through innovation and partnership to help meet the exact needs of our customers hpe green lake provides an experience that's the best of both worlds a simple pay-per-use technology model with the risk management of data that's under our customers direct control and it lets customers shift to everything as a service in order to free up capital and avoid that upfront expense that we talked about they can do this anywhere at any scale or any size and really hpe green lake is the cloud that comes to you like that so we've touched a little bit on how customers can maybe overcome some of the barriers to transformation what about the nature of transformations themselves i mean historically there was a lot of lip service paid to digital and and there's a lot of complacency frankly but you know that covered wrecking ball meme that so well describes that if you're not a digital business essentially you're going to be out of business so neil as things have evolved how is hpe addressed the new requirements well the new requirements are really about what customers are trying to achieve and four very common themes that we see are enabling the productivity of a remote workforce that was never really part of the plan for many organizations being able to develop and deliver new apps and services in order to service customers in a different way or drive new revenue streams being able to get insights from data so that in these tough times they can optimize their business more thoroughly and then finally think about the efficiency of an agile hybrid private cloud infrastructure especially one that now has to integrate the edge and we're really thrilled to be helping our customers accelerate all of these and more with hpe compute i want to double click on that remote workforce productivity i mean again the surveys that we see 46 percent of the cios say that productivity improved with the whole work from home remote work trend and on average those improvements were in the four percent range which is absolutely enormous i mean when you think about that how does hpe specifically you know help here what do you guys do well every organization in the world has had to adapt to a different style of working and with more remote workers than they had before and for many organizations that's going to become the new normal even post pandemic many it shops are not well equipped for the infrastructure to provide that experience because if all your workers are remote the resiliency of that infrastructure the latencies of that infrastructure the reliability of are all incredibly important so we provide comprehensive solutions expertise and as a service options that support that remote work through virtual desktop infrastructure or vdi so that our customers can support that new normal of virtual engagements online everything across industries wherever they are and that's just one example of many of the workload optimized solutions that we're providing for our customers is about taking out the guesswork and the uncertainty in delivering on these changes that they have to deploy as part of their transformation and we can deliver that range of workload optimized solutions across all of these different use cases because of our broad range of innovation in compute platforms that span from the ruggedized edge to the data center all the way up to exascale and hpc i mean that's key if you're trying to affect the digital transformation and you don't have to fine-tune you know be basically build your own optimized solutions if i can buy that rather than having to build it and rely on your r d you know that's key what else is hpe doing you know to deliver things new apps new services you know your microservices containers the whole developer trend what's going on there well that's really key because organizations are all seeking to evolve their mix of business and bring new services and new capabilities new ways to reach their customers new way to reach their employees new ways to interact in their ecosystem all digitally and that means app development and many organizations of course are embracing container technology to do that today so with the hpe container platform our customers can realize that agility and efficiency that comes with containerization and use it to provide insights to their data more and more that data of course is being machine generated or generated at the edge or the near edge and it can be a real challenge to manage that data holistically and not have silos and islands an hpe esmerald data fabric speeds the agility and access to data with a unified platform that can span across the data centers multiple clouds and even the edge and that enables data analytics that can create insights powering a data-driven production-oriented cloud-enabled analytics and ai available anytime anywhere in any scale and it's really exciting to see the kind of impact that that can have in helping businesses optimize their operations in these challenging times you got to go where the data is and the data is distributed it's decentralized so i i i like the esmerel of vision and execution there so that all sounds good but with digital transformation you get you're going to see more compute in in hybrid's deployments you mentioned edge so the surface area it's like the universe it's it's ever-expanding you mentioned you know remote work and work from home before so i'm curious where are you investing your resources from a cyber security perspective what can we count on from hpe there well you can count on continued leadership from hpe as the world's most secure industry standard server portfolio we provide an enhanced and holistic 360 degree view to security that begins in the manufacturing supply chain and concludes with a safeguarded end-of-life decommissioning and of course we've long set the bar for security with our work on silicon root of trust and we're extending that to the application tier but in addition to the security customers that are building this modern hybrid are private cloud including the integration of the edge need other elements too they need an intelligent software-defined control plane so that they can automate their compute fleets from all the way at the edge to the core and while scale and automation enable efficiency all private cloud infrastructures are competing with web scale economics and that's why we're democratizing web scale technologies like pinsando to bring web scale economics and web scale architecture to the private cloud our partners are so important in helping us serve our customers needs yeah i mean hp has really upped its ecosystem game since the the middle of last decade when when you guys reorganized it you became like even more partner friendly so maybe give us a preview of what's coming next in that regard from today's event well dave we're really excited to have hp's ceo antonio neri speaking with pat gelsinger from intel and later lisa sue from amd and later i'll have the chance to catch up with john chambers the founder and ceo of jc2 ventures to discuss the state of the market today yeah i'm jealous you guys had some good interviews coming up neil thanks so much for joining us today on the virtual cube you've really shared a lot of great insight how hpe is partnering with customers it's it's always great to catch up with you hopefully we can do so face to face you know sooner rather than later well i look forward to that and uh you know no doubt our world has changed and we're here to help our customers and partners with the technology the expertise and the economics they need for these digital transformations and we're going to bring them unmatched workload optimization from the edge to exascale with that 360 degree security with the intelligent automation and we're going to deliver it all as an as a service experience we're really excited to be helping our customers accelerate what's next for their businesses and it's been really great talking with you today about that dave thanks for having me you're very welcome it's been super neal and i actually you know i had the opportunity to speak with some of your customers about their digital transformation and the role of that hpe plays there so let's dive right in we're here on the cube covering hpe accelerating next and with me is rule siestermans who is the head of it at the netherlands cancer institute also known as nki welcome rule thank you very much great to be here hey what can you tell us about the netherlands cancer institute maybe you could talk about your core principles and and also if you could weave in your specific areas of expertise yeah maybe first introduction to the netherlands institute um we are one of the top 10 comprehensive cancers in the world and what we do is we combine a hospital for treating patients with cancer and a recent institute under one roof so discoveries we do we find within the research we can easily bring them back to the clinic and vis-a-versa so we have about 750 researchers and about 3 000 other employees doctors nurses and and my role is to uh to facilitate them at their best with it got it so i mean everybody talks about digital digital transformation to us it all comes down to data so i'm curious how you collect and take advantage of medical data specifically to support nki's goals maybe some of the challenges that your organization faces with the amount of data the speed of data coming in just you know the the complexities of data how do you handle that yeah it's uh it's it's it's challenge and uh yeah what we we have we have a really a large amount of data so we produce uh terabytes a day and we we have stored now more than one petabyte on data at this moment and yeah it's uh the challenge is to to reuse the data optimal for research and to share it with other institutions so that needs to have a flexible infrastructure for that so a fast really fast network uh big data storage environment but the real challenge is not not so much the i.t bus is more the quality of the data so we have a lot of medical systems all producing those data and how do we combine them and and yeah get the data fair so findable accessible interoperable and reusable uh for research uh purposes so i think that's the main challenge the quality of the data yeah very common themes that we hear from from other customers i wonder if you could paint a picture of your environment and maybe you can share where hpe solutions fit in what what value they bring to your organization's mission yeah i think it brings a lot of flexibility so what we did with hpe is that we we developed a software-defined data center and then a virtual workplace for our researchers and doctors and that's based on the hpe infrastructure and what we wanted to build is something that expect the needs of doctors and nurses but also the researchers and the two kind of different blood groups blood groups and with different needs so uh but we wanted to create one infrastructure because we wanted to make the connection between the hospital and the research that's that's more important so um hpe helped helped us not only with the the infrastructure itself but also designing the whole architecture of it and for example what we did is we we bought a lot of hardware and and and the hardware is really uh doing his his job between nine till five uh dennis everything is working within everyone is working within the institution but all the other time in evening and and nights hours and also the redundant environment we have for the for our healthcare uh that doesn't do nothing of much more or less uh in in those uh dark hours so what we created together with nvidia and hpe and vmware is that we we call it video by day compute by night so we reuse those those servers and those gpu capacity for computational research jobs within the research that's you mentioned flexibility for this genius and and so we're talking you said you know a lot of hard ways they're probably proliant i think synergy aruba networking is in there how are you using this environment actually the question really is when you think about nki's digital transformation i mean is this sort of the fundamental platform that you're using is it a maybe you could describe that yeah it's it's the fundamental platform to to to work on and and and what we see is that we have we have now everything in place for it but the real challenge is is the next steps we are in so we have a a software defined data center we are cloud ready so the next steps is to to make the connection to the cloud to to give more automation to our researchers so they don't have to wait a couple of weeks for it to do it but they can do it themselves with a couple of clicks so i think the basic is we are really flexible and we have a lot of opportunities for automation for example but the next step is uh to create that business value uh really for for our uh employees that's a great story and a very important mission really fascinating stuff thanks for sharing this with our audience today really appreciate your time thank you very much okay this is dave vellante with thecube stay right there for more great content you're watching accelerating next from hpe i'm really glad to have you with us today john i know you stepped out of vacation so thanks very much for joining us neil it's great to be joining you from hawaii and i love the partnership with hpe and the way you're reinventing an industry well you've always excelled john at catching market transitions and there are so many transitions and paradigm shifts happening in the market and tech specifically right now as you see companies rush to accelerate their transformation what do you see as the keys to success well i i think you're seeing actually an acceleration following the covet challenges that all of us faced and i wasn't sure that would happen it's probably at three times the paces before there was a discussion point about how quickly the companies need to go digital uh that's no longer a discussion point almost all companies are moving with tremendous feed on digital and it's the ability as the cloud moves to the edge with compute and security uh at the edge and how you deliver these services to where the majority of applications uh reside are going to determine i think the future of the next generation company leadership and it's the area that neil we're working together on in many many ways so i think it's about innovation it's about the cloud moving to the edge and an architectural play with silicon to speed up that innovation yes we certainly see our customers of all sizes trying to accelerate what's next and get that digital transformation moving even faster as a result of the environment that we're all living in and we're finding that workload focus is really key uh customers in all kinds of different scales are having to adapt and support the remote workforces with vdi and as you say john they're having to deal with the deployment of workloads at the edge with so much data getting generated at the edge and being acted upon at the edge the analytics and the infrastructure to manage that as these processes get digitized and automated is is so important for so many workflows we really believe that the choice of infrastructure partner that underpins those transformations really matters a partner that can help create the financial capacity that can help optimize your environments and enable our customers to focus on supporting their business are all super key to success and you mentioned that in the last year there's been a lot of rapid course correction for all of us a demand for velocity and the ability to deploy resources at scale is more and more needed maybe more than ever what are you hearing customers looking for as they're rolling out their digital transformation efforts well i think they're being realistic that they're going to have to move a lot faster than before and they're also realistic on core versus context they're they're their core capability is not the technology of themselves it's how to deploy it and they're we're looking for partners that can help bring them there together but that can also innovate and very often the leaders who might have been a leader in a prior generation may not be on this next move hence the opportunity for hpe and startups like vinsano to work together as the cloud moves the edge and perhaps really balance or even challenge some of the big big incumbents in this category as well as partners uniquely with our joint customers on how do we achieve their business goals tell me a little bit more about how you move from this being a technology positioning for hpe to literally helping your customers achieve their outcomes they want and and how are you changing hpe in that way well i think when you consider these transformations the infrastructure that you choose to underpin it is incredibly critical our customers need a software-defined management plan that enables them to automate so much of their infrastructure they need to be able to take faster action where the data is and to do all of this in a cloud-like experience where they can deliver their infrastructure as code anywhere from exascale through the enterprise data center to the edge and really critically they have to be able to do this securely which becomes an ever increasing challenge and doing it at the right economics relative to their alternatives and part of the right economics of course includes adopting the best practices from web scale architectures and bringing them to the heart of the enterprise and in our partnership with pensando we're working to enable these new ideas of web scale architecture and fleet management for the enterprise at scale you know what is fun is hpe has an unusual talent from the very beginning in silicon valley of working together with others and creating a win-win innovation approach if you watch what your team has been able to do and i want to say this for everybody listening you work with startups better than any other company i've seen in terms of how you do win win together and pinsando is just the example of that uh this startup which by the way is the ninth time i have done with this team a new generation of products and we're designing that together with hpe in terms of as the cloud moves to the edge how do we get the leverage out of that and produce the results for your customers on this to give the audience appeal for it you're talking with pensano alone in terms of the efficiency versus an amazon amazon web services of an order of magnitude i'm not talking 100 greater i'm talking 10x greater and things from throughput number of connections you do the jitter capability etc and it talks how two companies uniquely who believe in innovation and trust each other and have very similar cultures can work uniquely together on it how do you bring that to life with an hpe how do you get your company to really say let's harvest the advantages of your ecosystem in your advantages of startups well as you say more and more companies are faced with these challenges of hitting the right economics for the infrastructure and we see many enterprises of various sizes trying to come to terms with infrastructures that look a lot more like a service provider that require that software-defined management plane and the automation to deploy at scale and with the work we're doing with pinsando the benefits that we bring in terms of the observability and the telemetry and the encryption and the distributed network functions but also a security architecture that enables that efficiency on the individual nodes is just so key to building a competitive architecture moving forwards for an on-prem private cloud or internal service provider operation and we're really excited about the work we've done to bring that technology across our portfolio and bring that to our customers so that they can achieve those kind of economics and capabilities and go focus on their own transformations rather than building and running the infrastructure themselves artisanally and having to deal with integrating all of that great technology themselves makes tremendous sense you know neil you and i work on a board together et cetera i've watched your summarization skills and i always like to ask the question after you do a quick summary like this what are the three or four takeaways we would like for the audience to get out of our conversation well that's a great question thanks john we believe that customers need a trusted partner to work through these digital transformations that are facing them and confront the challenge of the time that the covet crisis has taken away as you said up front every organization is having to transform and transform more quickly and more digitally and working with a trusted partner with the expertise that only comes from decades of experience is a key enabler for that a partner with the ability to create the financial capacity to transform the workload expertise to get more from the infrastructure and optimize the environment so that you can focus on your own business a partner that can deliver the systems and the security and the automation that makes it easily deployable and manageable anywhere you need them at any scale whether the edge the enterprise data center or all the way up to exascale in high performance computing and can do that all as a service as we can at hpe through hpe green lake enabling our customers most critical workloads it's critical that all of that is underpinned by an ai powered digitally enabled service experience so that our customers can get on with their transformation and running their business instead of dealing with their infrastructure and really only hpe can provide this combination of capabilities and we're excited and committed to helping our customers accelerate what's next for their businesses neil it's fun i i love being your partner and your wingman our values and cultures are so similar thanks for letting me be a part of this discussion today thanks for being with us john it was great having you here oh it's friends for life okay now we're going to dig into the world of video which accounts for most of the data that we store and requires a lot of intense processing capabilities to stream here with me is jim brickmeyer who's the chief marketing and product officer at vlasics jim good to see you good to see you as well so tell us a little bit more about velocity what's your role in this tv streaming world and maybe maybe talk about your ideal customer sure sure so um we're leading provider of carrier great video solutions video streaming solutions and advertising uh technology to service providers around the globe so we primarily sell software-based solutions to uh cable telco wireless providers and broadcasters that are interested in launching their own um video streaming services to consumers yeah so this is this big time you know we're not talking about mom and pop you know a little video outfit but but maybe you can help us understand that and just the sheer scale of of the tv streaming that you're doing maybe relate it to you know the overall internet usage how much traffic are we talking about here yeah sure so uh yeah so our our customers tend to be some of the largest um network service providers around the globe uh and if you look at the uh the video traffic um with respect to the total amount of traffic that that goes through the internet video traffic accounts for about 90 of the total amount of data that uh that traverses the internet so video is uh is a pretty big component of um of how people when they look at internet technologies they look at video streaming technologies uh you know this is where we we focus our energy is in carrying that traffic as efficiently as possible and trying to make sure that from a consumer standpoint we're all consumers of video and uh make sure that the consumer experience is a high quality experience that you don't experience any glitches and that that ultimately if people are paying for that content that they're getting the value that they pay for their for their money uh in their entertainment experience i think people sometimes take it for granted it's like it's like we we all forget about dial up right those days are long gone but the early days of video was so jittery and restarting and and the thing too is that you know when you think about the pandemic and the boom in streaming that that hit you know we all sort of experienced that but the service levels were pretty good i mean how much how much did the pandemic affect traffic what kind of increases did you see and how did that that impact your business yeah sure so uh you know obviously while it was uh tragic to have a pandemic and have people locked down what we found was that when people returned to their homes what they did was they turned on their their television they watched on on their mobile devices and we saw a substantial increase in the amount of video streaming traffic um over service provider networks so what we saw was on the order of 30 to 50 percent increase in the amount of data that was traversing those networks so from a uh you know from an operator's standpoint a lot more traffic a lot more challenging to to go ahead and carry that traffic a lot of work also on our behalf and trying to help operators prepare because we could actually see geographically as the lockdowns happened [Music] certain areas locked down first and we saw that increase so we were able to help operators as as all the lockdowns happened around the world we could help them prepare for that increase in traffic i mean i was joking about dial-up performance again in the early days of the internet if your website got fifty percent more traffic you know suddenly you were you your site was coming down so so that says to me jim that architecturally you guys were prepared for that type of scale so maybe you could paint a picture tell us a little bit about the solutions you're using and how you differentiate yourself in your market to handle that type of scale sure yeah so we so we uh we really are focused on what we call carrier grade solutions which are designed for that massive amount of scale um so we really look at it you know at a very granular level when you look um at the software and and performance capabilities of the software what we're trying to do is get as many streams as possible out of each individual piece of hardware infrastructure so that we can um we can optimize first of all maximize the uh the efficiency of that device make sure that the costs are very low but one of the other challenges is as you get to millions and millions of streams and that's what we're delivering on a daily basis is millions and millions of video streams that you have to be able to scale those platforms out um in an effective in a cost effective way and to make sure that it's highly resilient as well so we don't we don't ever want a consumer to have a circumstance where a network glitch or a server issue or something along those lines causes some sort of uh glitch in their video and so there's a lot of work that we do in the software to make sure that it's a very very seamless uh stream and that we're always delivering at the very highest uh possible bit rate for consumers so that if you've got that giant 4k tv that we're able to present a very high resolution picture uh to those devices and what's the infrastructure look like underneath you you're using hpe solutions where do they fit in yeah that's right yeah so we uh we've had a long-standing partnership with hpe um and we work very closely with them to try to identify the specific types of hardware that are ideal for the the type of applications that we run so we run video streaming applications and video advertising applications targeted kinds of video advertising technologies and when you look at some of these applications they have different types of requirements in some cases it's uh throughput where we're taking a lot of data in and streaming a lot of data out in other cases it's storage where we have to have very high density high performance storage systems in other cases it's i gotta have really high capacity storage but the performance does not need to be quite as uh as high from an io perspective and so we work very closely with hpe on trying to find exactly the right box for the right application and then beyond that also talking with our customers to understand there are different maintenance considerations associated with different types of hardware so we tend to focus on as much as possible if we're going to place servers deep at the edge of the network we will make everything um maintenance free or as maintenance free as we can make it by putting very high performance solid state storage into those servers so that uh we we don't have to physically send people to those sites to uh to do any kind of maintenance so it's a it's a very cooperative relationship that we have with hpe to try to define those boxes great thank you for that so last question um maybe what the future looks like i love watching on my mobile device headphones in no distractions i'm getting better recommendations how do you see the future of tv streaming yeah so i i think the future of tv streaming is going to be a lot more personal right so uh this is what you're starting to see through all of the services that are out there is that most of the video service providers whether they're online providers or they're your traditional kinds of paid tv operators is that they're really focused on the consumer and trying to figure out what is of value to you personally in the past it used to be that services were one size fits all and um and so everybody watched the same program right at the same time and now that's uh that's we have this technology that allows us to deliver different types of content to people on different screens at different times and to advertise to those individuals and to cater to their individual preferences and so using that information that we have about how people watch and and what people's interests are we can create a much more engaging and compelling uh entertainment experience on all of those screens and um and ultimately provide more value to consumers awesome story jim thanks so much for keeping us helping us just keep entertained during the pandemic i really appreciate your time sure thanks all right keep it right there everybody you're watching hpes accelerating next first of all pat congratulations on your new role as intel ceo how are you approaching your new role and what are your top priorities over your first few months thanks antonio for having me it's great to be here with you all today to celebrate the launch of your gen 10 plus portfolio and the long history that our two companies share in deep collaboration to deliver amazing technology to our customers together you know what an exciting time it is to be in this industry technology has never been more important for humanity than it is today everything is becoming digital and driven by what i call the four key superpowers the cloud connectivity artificial intelligence and the intelligent edge they are super powers because each expands the impact of the others and together they are reshaping every aspect of our lives and work in this landscape of rapid digital disruption intel's technology and leadership products are more critical than ever and we are laser focused on bringing to bear the depth and breadth of software silicon and platforms packaging and process with at scale manufacturing to help you and our customers capitalize on these opportunities and fuel their next generation innovations i am incredibly excited about continuing the next chapter of a long partnership between our two companies the acceleration of the edge has been significant over the past year with this next wave of digital transformation we expect growth in the distributed edge and age build out what are you seeing on this front like you said antonio the growth of edge computing and build out is the next key transition in the market telecommunications service providers want to harness the potential of 5g to deliver new services across multiple locations in real time as we start building solutions that will be prevalent in a 5g digital environment we will need a scalable flexible and programmable network some use cases are the massive scale iot solutions more robust consumer devices and solutions ar vr remote health care autonomous robotics and manufacturing environments and ubiquitous smart city solutions intel and hp are partnering to meet this new wave head on for 5g build out and the rise of the distributed enterprise this build out will enable even more growth as businesses can explore how to deliver new experiences and unlock new insights from the new data creation beyond the four walls of traditional data centers and public cloud providers network operators need to significantly increase capacity and throughput without dramatically growing their capital footprint their ability to achieve this is built upon a virtualization foundation an area of intel expertise for example we've collaborated with verizon for many years and they are leading the industry and virtualizing their entire network from the core the edge a massive redesign effort this requires advancements in silicon and power management they expect intel to deliver the new capabilities in our roadmap so ecosystem partners can continue to provide innovative and efficient products with this optimization for hybrid we can jointly provide a strong foundation to take on the growth of data-centric workloads for data analytics and ai to build and deploy models faster to accelerate insights that will deliver additional transformation for organizations of all types the network transformation journey isn't easy we are continuing to unleash the capabilities of 5g and the power of the intelligent edge yeah the combination of the 5g built out and the massive new growth of data at the edge are the key drivers for the age of insight these new market drivers offer incredible new opportunities for our customers i am excited about recent launch of our new gen 10 plus portfolio with intel together we are laser focused on delivering joint innovation for customers that stretches from the edge to x scale how do you see new solutions that this helping our customers solve the toughest challenges today i talked earlier about the superpowers that are driving the rapid acceleration of digital transformation first the proliferation of the hybrid cloud is delivering new levels of efficiency and scale and the growth of the cloud is democratizing high-performance computing opening new frontiers of knowledge and discovery next we see ai and machine learning increasingly infused into every application from the edge to the network to the cloud to create dramatically better insights and the rapid adoption of 5g as i talked about already is fueling new use cases that demand lower latencies and higher bandwidth this in turn is pushing computing to the edge closer to where the data is created and consumed the confluence of these trends is leading to the biggest and fastest build out of computing in human history to keep pace with this rapid digital transformation we recognize that infrastructure has to be built with the flexibility to support a broad set of workloads and that's why over the last several years intel has built an unmatched portfolio to deliver every component of intelligent silicon our customers need to move store and process data from the cpus to fpgas from memory to ssds from ethernet to switch silicon to silicon photonics and software our 3rd gen intel xeon scalable processors and our data centric portfolio deliver new core performance and higher bandwidth providing our customers the capabilities they need to power these critical workloads and we love seeing all the unique ways customers like hpe leverage our technology and solution offerings to create opportunities and solve their most pressing challenges from cloud gaming to blood flow to brain scans to financial market security the opportunities are endless with flexible performance i am proud of the amazing innovation we are bringing to support our customers especially as they respond to new data-centric workloads like ai and analytics that are critical to digital transformation these new requirements create a need for compute that's warlord optimized for performance security ease of use and the economics of business now more than ever compute matters it is the foundation for this next wave of digital transformation by pairing our compute with our software and capabilities from hp green lake we can support our customers as they modernize their apps and data quickly they seamlessly and securely scale them anywhere at any size from edge to x scale but thank you for joining us for accelerating next today i know our audience appreciated hearing your perspective on the market and how we're partnering together to support their digital transformation journey i am incredibly excited about what lies ahead for hp and intel thank you thank you antonio great to be with you today we just compressed about a decade of online commerce progress into about 13 or 14 months so now we're going to look at how one retailer navigated through the pandemic and what the future of their business looks like and with me is alan jensen who's the chief information officer and senior vice president of the sawing group hello alan how are you fine thank you good to see you hey look you know when i look at the 100 year history plus of your company i mean it's marked by transformations and some of them are quite dramatic so you're denmark's largest retailer i wonder if you could share a little bit more about the company its history and and how it continues to improve the customer experience well at the same time keeping costs under control so vital in your business yeah yeah the company founded uh approximately 100 years ago with a department store in in oahu's in in denmark and i think in the 60s we founded the first supermarket in in denmark with the self-service and combined textile and food in in the same store and in beginning 70s we founded the first hyper market in in denmark and then the this calendar came from germany early in in 1980 and we started a discount chain and so we are actually building department store in hyber market info in in supermarket and in in the discount sector and today we are more than 1 500 stores in in three different countries in in denmark poland and germany and especially for the danish market we have a approximately 38 markets here and and is the the leader we have over the last 10 years developed further into online first in non-food and now uh in in food with home delivery with click and collect and we have done some magnetism acquisition in in the convenience with mailbox solutions to our customers and we have today also some restaurant burger chain and and we are running the starbuck in denmark so i can you can see a full plate of different opportunities for our customer in especially denmark it's an awesome story and of course the founder's name is still on the masthead what a great legacy now of course the pandemic is is it's forced many changes quite dramatic including the the behaviors of retail customers maybe you could talk a little bit about how your digital transformation at the sawing group prepared you for this shift in in consumption patterns and any other challenges that that you faced yeah i think uh luckily as for some of the you can say the core it solution in in 19 we just roll out using our computers via direct access so you can work from anywhere whether you are traveling from home and so on we introduced a new agile scrum delivery model and and we just finalized the rolling out teams in in in january february 20 and that was some very strong thing for suddenly moving all our employees from from office to to home and and more or less overnight we succeed uh continuing our work and and for it we have not missed any deadline or task for the business in in 2020 so i think that was pretty awesome to to see and for the business of course the pandemic changed a lot as the change in customer behavior more or less overnight with plus 50 80 on the online solution forced us to do some different priorities so we were looking at the food home delivery uh and and originally expected to start rolling out in in 2022 uh but took a fast decision in april last year to to launch immediately and and we have been developing that uh over the last eight months and has been live for the last three months now in the market so so you can say the pandemic really front loaded some of our strategic actions for for two to three years uh yeah that was very exciting what's that uh saying luck is the byproduct of great planning and preparation so let's talk about when you're in a company with some strong financial situation that you can move immediately with investment when you take such decision then then it's really thrilling yeah right awesome um two-part question talk about how you leverage data to support the solid groups mission and you know drive value for customers and maybe you could talk about some of the challenges you face with just the amount of data the speed of data et cetera yeah i said data is everything when you are in retail as a retailer's detail as you need to monitor your operation down to each store eats department and and if you can say we have challenge that that is that data is just growing rapidly as a year by year it's growing more and more because you are able to be more detailed you're able to capture more data and for a company like ours we need to be updated every morning as a our fully updated sales for all unit department single sku selling in in the stores is updated 3 o'clock in the night and send out to all top management and and our managers all over the company it's actually 8 000 reports going out before six o'clock every day in the morning we have introduced a loyalty program and and you are capturing a lot of data on on customer behavior what is their preferred offers what is their preferred time in the week for buying different things and all these data is now used to to personalize our offers to our cost of value customers so we can be exactly hitting the best time and and convert it to sales data is also now used for what we call intelligent price reductions as a so instead of just reducing prices with 50 if it's uh close to running out of date now the system automatically calculate whether a store has just enough to to finish with full price before end of day or actually have much too much and and need to maybe reduce by 80 before as being able to sell so so these automated [Music] solutions built on data is bringing efficiency into our operation wow you make it sound easy these are non-trivial items so congratulations on that i wonder if we could close hpe was kind enough to introduce us tell us a little bit about the infrastructure the solutions you're using how they differentiate you in the market and i'm interested in you know why hpe what distinguishes them why the choice there yeah as a when when you look out a lot is looking at moving data to the cloud but we we still believe that uh due to performance due to the availability uh more or less on demand we we still don't see the cloud uh strong enough for for for selling group uh capturing all our data we have been quite successfully having one data truth across the whole con company and and having one just one single bi solution and having that huge amount of data i think we have uh one of the 10 largest sub business warehouses in global and but on the other hand we also want to be agile and want to to scale when needed so getting close to a cloud solution we saw it be a green lake as a solution getting close to the cloud but still being on-prem and could deliver uh what we need to to have a fast performance on on data but still in a high quality and and still very secure for us to run great thank you for that and thank alan thanks so much for your for your time really appreciate your your insights and your congratulations on the progress and best of luck in the future thank you all right keep it right there we have tons more content coming you're watching accelerating next from hpe [Music] welcome lisa and thank you for being here with us today antonio it's wonderful to be here with you as always and congratulations on your launch very very exciting for you well thank you lisa and we love this partnership and especially our friendship which has been very special for me for the many many years that we have worked together but i wanted to have a conversation with you today and obviously digital transformation is a key topic so we know the next wave of digital transformation is here being driven by massive amounts of data an increasingly distributed world and a new set of data intensive workloads so how do you see world optimization playing a role in addressing these new requirements yeah no absolutely antonio and i think you know if you look at the depth of our partnership over the last you know four or five years it's really about bringing the best to our customers and you know the truth is we're in this compute mega cycle right now so it's amazing you know when i know when you talk to customers when we talk to customers they all need to do more and and frankly compute is becoming quite specialized so whether you're talking about large enterprises or you're talking about research institutions trying to get to the next phase of uh compute so that workload optimization that we're able to do with our processors your system design and then you know working closely with our software partners is really the next wave of this this compute cycle so thanks lisa you talk about mega cycle so i want to make sure we take a moment to celebrate the launch of our new generation 10 plus compute products with the latest announcement hp now has the broadest amd server portfolio in the industry spanning from the edge to exascale how important is this partnership and the portfolio for our customers well um antonio i'm so excited first of all congratulations on your 19 world records uh with uh milan and gen 10 plus it really is building on you know sort of our you know this is our third generation of partnership with epic and you know you are with me right at the very beginning actually uh if you recall you joined us in austin for our first launch of epic you know four years ago and i think what we've created now is just an incredible portfolio that really does go across um you know all of the uh you know the verticals that are required we've always talked about how do we customize and make things easier for our customers to use together and so i'm very excited about your portfolio very excited about our partnership and more importantly what we can do for our joint customers it's amazing to see 19 world records i think i'm really proud of the work our joint team do every generation raising the bar and that's where you know we we think we have a shared goal of ensuring that customers get the solution the services they need any way they want it and one way we are addressing that need is by offering what we call as a service delivered to hp green lake so let me ask a question what feedback are you hearing from your customers with respect to choice meaning consuming as a service these new solutions yeah now great point i think first of all you know hpe green lake is very very impressive so you know congratulations um to uh to really having that solution and i think we're hearing the same thing from customers and you know the truth is the compute infrastructure is getting more complex and everyone wants to be able to deploy sort of the right compute at the right price point um you know in in terms of also accelerating time to deployment with the right security with the right quality and i think these as a service offerings are going to become more and more important um as we go forward in the compute uh you know capabilities and you know green lake is a leadership product offering and we're very very you know pleased and and honored to be part of it yeah we feel uh lisa we are ahead of the competition and um you know you think about some of our competitors now coming with their own offerings but i think the ability to drive joint innovation is what really differentiate us and that's why we we value the partnership and what we have been doing together on giving the customers choice finally you know i know you and i are both incredibly excited about the joint work we're doing with the us department of energy the oak ridge national laboratory we think about large data sets and you know and the complexity of the analytics we're running but we both are going to deliver the world's first exascale system which is remarkable to me so what this milestone means to you and what type of impact do you think it will make yes antonio i think our work with oak ridge national labs and hpe is just really pushing the envelope on what can be done with computing and if you think about the science that we're going to be able to enable with the first exascale machine i would say there's a tremendous amount of innovation that has already gone in to the machine and we're so excited about delivering it together with hpe and you know we also think uh that the super computing technology that we're developing you know at this broad scale will end up being very very important for um you know enterprise compute as well and so it's really an opportunity to kind of take that bleeding edge and really deploy it over the next few years so super excited about it i think you know you and i have a lot to do over the uh the next few months here but it's an example of the great partnership and and how much we're able to do when we put our teams together um to really create that innovation i couldn't agree more i mean this is uh an incredible milestone for for us for our industry and honestly for the country in many ways and we have many many people working 24x7 to deliver against this mission and it's going to change the future of compute no question about it and then honestly put it to work where we need it the most to advance life science to find cures to improve the way people live and work but lisa thank you again for joining us today and thank you more most importantly for the incredible partnership and and the friendship i really enjoy working with you and your team and together i think we can change this industry once again so thanks for your time today thank you so much antonio and congratulations again to you and the entire hpe team for just a fantastic portfolio launch thank you okay well some pretty big hitters in those keynotes right actually i have to say those are some of my favorite cube alums and i'll add these are some of the execs that are stepping up to change not only our industry but also society and that's pretty cool and of course it's always good to hear from the practitioners the customer discussions have been great so far today now the accelerating next event continues as we move to a round table discussion with krista satrathwaite who's the vice president and gm of hpe core compute and krista is going to share more details on how hpe plans to help customers move ahead with adopting modern workloads as part of their digital transformations krista will be joined by hpe subject matter experts chris idler who's the vp and gm of the element and mark nickerson director of solutions product management as they share customer stories and advice on how to turn strategy into action and realize results within your business thank you for joining us for accelerate next event i hope you're enjoying it so far i know you've heard about the industry challenges the i.t trends hpe strategy from leaders in the industry and so today what we want to do is focus on going deep on workload solutions so in the most important workload solutions the ones we always get asked about and so today we want to share with you some best practices some examples of how we've helped other customers and how we can help you all right with that i'd like to start our panel now and introduce chris idler who's the vice president and general manager of the element chris has extensive uh solution expertise he's led hpe solution engineering programs in the past welcome chris and mark nickerson who is the director of product management and his team is responsible for solution offerings making sure we have the right solutions for our customers welcome guys thanks for joining me thanks for having us krista yeah so i'd like to start off with one of the big ones the ones that we get asked about all the time what we've been all been experienced in the last year remote work remote education and all the challenges that go along with that so let's talk a little bit about the challenges that customers have had in transitioning to this remote work and remote education environment uh so i i really think that there's a couple of things that have stood out for me when we're talking with customers about vdi first obviously there was a an unexpected and unprecedented level of interest in that area about a year ago and we all know the reasons why but what it really uncovered was how little planning had gone into this space around a couple of key dynamics one is scale it's one thing to say i'm going to enable vdi for a part of my workforce in a pre-pandemic environment where the office was still the the central hub of activity for work uh it's a completely different scale when you think about okay i'm going to have 50 60 80 maybe 100 of my workforce now distributed around the globe um whether that's in an educational environment where now you're trying to accommodate staff and students in virtual learning uh whether that's uh in the area of things like uh formula one racing where we had uh the desire to still have events going on but the need for a lot more social distancing not as many people able to be trackside but still needing to have that real-time experience this really manifested in a lot of ways and scale was something that i think a lot of customers hadn't put as much thought into initially the other area is around planning for experience a lot of times the vdi experience was planned out with very specific workloads or very specific applications in mind and when you take it to a more broad-based environment if we're going to support multiple functions multiple lines of business there hasn't been as much planning or investigation that's gone into the application side and so thinking about how graphically intense some applications are one customer that comes to mind would be tyler isd who did a fairly large roll out pre-pandemic and as part of their big modernization effort what they uncovered was even just changes in standard windows applications had become so much more graphically intense with windows 10 with the latest updates with programs like adobe that they were really needing to have an accelerated experience for a much larger percentage of their install base than than they had counted on so in addition to planning for scale you also need to have that visibility into what are the actual applications that are going to be used by these remote users how graphically intense those might be what's the login experience going to be as well as the operating experience and so really planning through that experience side as well as the scale and the number of users uh is is kind of really two of the biggest most important things that i've seen yeah mark i'll i'll just jump in real quick i think you you covered that pretty comprehensively there and and it was well done the couple of observations i've made one is just that um vdi suddenly become like mission critical for sales it's the front line you know for schools it's the classroom you know that this isn't a cost cutting measure or a optimization nit measure anymore this is about running the business in a way it's a digital transformation one aspect of about a thousand aspects of what does it mean to completely change how your business does and i think what that translates to is that there's no margin for error right you really need to deploy this in a way that that performs that understands what you're trying to use it for that gives that end user the experience that they expect on their screen or on their handheld device or wherever they might be whether it's a racetrack classroom or on the other end of a conference call or a boardroom right so what we do in in the engineering side of things when it comes to vdi or really understand what's a tech worker what's a knowledge worker what's a power worker what's a gp really going to look like what's time of day look like you know who's using it in the morning who's using it in the evening when do you power up when do you power down does the system behave does it just have the it works function and what our clients can can get from hpe is um you know a worldwide set of experiences that we can apply to making sure that the solution delivers on its promises so we're seeing the same thing you are krista you know we see it all the time on vdi and on the way businesses are changing the way they do business yeah and it's funny because when i talk to customers you know one of the things i heard that was a good tip is to roll it out to small groups first so you could really get a good sense of what the experience is before you roll it out to a lot of other people and then the expertise it's not like every other workload that people have done before so if you're new at it make sure you're getting the right advice expertise so that you're doing it the right way okay one of the other things we've been talking a lot about today is digital transformation and moving to the edge so now i'd like to shift gears and talk a little bit about how we've helped customers make that shift and this time i'll start with chris all right hey thanks okay so you know it's funny when it comes to edge because um the edge is different for for every customer in every client and every single client that i've ever spoken to of hp's has an edge somewhere you know whether just like we were talking about the classroom might be the edge but but i think the industry when we're talking about edge is talking about you know the internet of things if you remember that term from not to not too long ago you know and and the fact that everything's getting connected and how do we turn that into um into telemetry and and i think mark's going to be able to talk through a couple of examples of clients that we have in things like racing and automotive but what we're learning about edge is it's not just how do you make the edge work it's how do you integrate the edge into what you're already doing and nobody's just the edge right and and so if it's if it's um ai mldl there's that's one way you want to use the edge if it's a customer experience point of service it's another you know there's yet another way to use the edge so it turns out that having a broad set of expertise like hpe does to be able to understand the different workloads that you're trying to tie together including the ones that are running at the at the edge often it involves really making sure you understand the data pipeline you know what information is at the edge how does it flow to the data center how does it flow and then which data center uh which private cloud which public cloud are you using i think those are the areas where where we really sort of shine is that we we understand the interconnectedness of these things and so for example red bull and i know you're going to talk about that in a minute mark um uh the racing company you know for them the the edge is the racetrack and and you know milliseconds or partial seconds winning and losing races but then there's also an edge of um workers that are doing the design for for the cars and how do they get quick access so um we have a broad variety of infrastructure form factors and compute form factors to help with the edge and this is another real advantage we have is that we we know how to put the right piece of equipment with the right software we also have great containerized software with our esmeral container platform so we're really becoming um a perfect platform for hosting edge-centric workloads and applications and data processing yeah it's uh all the way down to things like our superdome flex in the background if you have some really really really big data that needs to be processed and of course our workhorse proliance that can be configured to support almost every um combination of workload you have so i know you started with edge krista but but and we're and we nail the edge with those different form factors but let's make sure you know if you're listening to this this show right now um make sure you you don't isolate the edge and make sure they integrate it with um with the rest of your operation mark you know what did i miss yeah to that point chris i mean and this kind of actually ties the two things together that we've been talking about here but the edge uh has become more critical as we have seen more work moving to the edge as where we do work changes and evolves and the edge has also become that much more closer because it has to be that much more connected um to your point uh talking about where that edge exists that edge can be a lot of different places but the one commonality really is that the edge is is an area where work still needs to get accomplished it can't just be a collection point and then everything gets shipped back to a data center or back to some some other area for the work it's where the work actually needs to get done whether that's edge work in a use case like vdi or whether that's edge work in the case of doing real-time analytics you mentioned red bull racing i'll i'll bring that up i mean you talk about uh an area where time is of the essence everything about that sport comes down to time you're talking about wins and losses that are measured as you said in milliseconds and that applies not just to how performance is happening on the track but how you're able to adapt and modify the needs of the car uh adapt to the evolving conditions on the track itself and so when you talk about putting together a solution for an edge like that you're right it can't just be here's a product that's going to allow us to collect data ship it back someplace else and and wait for it to be processed in a couple of days you have to have the ability to analyze that in real time when we pull together a solution involving our compute products our storage products our networking products when we're able to deliver that full package solution at the edge what you see are results like a 50 decrease in processing time to make real-time analytic decisions about configurations for the car and adapting to to real-time uh test and track conditions yeah really great point there um and i really love the example of edge and racing because i mean that is where it all every millisecond counts um and so important to process that at the edge now switching gears just a little bit let's talk a little bit about some examples of how we've helped customers when it comes to business agility and optimizing their workload for maximum outcome for business agility let's talk about some things that we've done to help customers with that mark yeah give it a shot so when we when we think about business agility what you're really talking about is the ability to to implement on the fly to be able to scale up to scale down the ability to adapt to real time changing situations and i think the last year has been has been an excellent example of exactly how so many businesses have been forced to do that i think one of the areas that that i think we've probably seen the most ability to help with customers in that agility area is around the space of private and hybrid clouds if you take a look at the need that customers have to to be able to migrate workloads and migrate data between public cloud environments app development environments that may be hosted on-site or maybe in the cloud the ability to move out of development and into production and having the agility to then scale those application rollouts up having the ability to have some of that some of that private cloud flexibility in addition to a public cloud environment is something that is becoming increasingly crucial for a lot of our customers all right well i we could keep going on and on but i'll stop it there uh thank you so much uh chris and mark this has been a great discussion thanks for sharing how we helped other customers and some tips and advice for approaching these workloads i thank you all for joining us and remind you to look at the on-demand sessions if you want to double click a little bit more into what we've been covering all day today you can learn a lot more in those sessions and i thank you for your time thanks for tuning in today many thanks to krista chris and mark we really appreciate you joining today to share how hpe is partnering to facilitate new workload adoption of course with your customers on their path to digital transformation now to round out our accelerating next event today we have a series of on-demand sessions available so you can explore more details around every step of that digital transformation from building a solid infrastructure strategy identifying the right compute and software to rounding out your solutions with management and financial support so please navigate to the agenda at the top of the page to take a look at what's available i just want to close by saying that despite the rush to digital during the pandemic most businesses they haven't completed their digital transformations far from it 2020 was more like a forced march than a planful strategy but now you have some time you've adjusted to this new abnormal and we hope the resources that you find at accelerating next will help you on your journey best of luck to you and be well [Music] [Applause] [Music] 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>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> As you may recall, coming into the second part of 2019 we reported, based on ETR Survey data, that there was a narrowing of spending on emerging tech and an unplugging of a lot of legacy systems. This was really because people were going from experimentation into operationalizing their digital initiatives. When COVID hit, conventional wisdom suggested that there would be a flight to safety. Now, interestingly, we reported with Eric Bradley, based on one of the Venns, that a lot of CIOs were still experimenting with emerging vendors. But this was very anecdotal. Today, we have more data, fresh data, from the ETR Emerging Technology Study on private companies, which really does suggest that there's a notable decline in experimentation, and that's affecting emerging technology vendors. Hi, everybody, this is Dave Vellante, and welcome to this week's Wikibon Cube Insights, powered by ETR. Once again, Sagar Kadakia is joining us. Sagar is the Director of Research at ETR. Sagar, good to see you. Thanks for coming on. >> Good to see you again. Thanks for having me, Dave. >> So, it's really important to point out, this Emerging Tech Study that you guys do, it's different from your quarterly Technology Spending Intention Survey. Take us through the methodology. Guys, maybe you could bring up the first chart. And, Sagar, walk us through how you guys approach this. >> No problem. So, a lot of the viewers are used to seeing a lot of the results from the Technology Spending Intention Survey, or the TSIS, as we call it. That study, as the title says, it really tracks spending intentions on more pervasive vendors, right, Microsoft, AWS, as an example. What we're going to look at today is our Emerging Technology Study, which we conduct biannually, in May and November. This study is a little bit different. We ask CIOs around evaluations, awareness, planned evaluations, so think of this as pre-spend, right. So that's a major differentiator from the TSIS. That, and this study, really focuses on private emerging providers. We're really only focused on those really emerging private companies, say, like your Series B to Series G or H, whatever it may be, so, two big differences within those studies. And then today what we're really going to look at is the results from the Emerging Technology Study. Just a couple of quick things here. We had 811 CIOs participate, which represents about 380 billion in annual IT spend, so the results from this study matter. We had almost 75 Fortune 100s take it. So, again, we're really measuring how private emerging providers are doing in the largest organizations. And so today we're going to be reviewing notable sectors, but largely this survey tracks roughly 356 private technologies and frameworks. >> All right, guys, bring up the pie chart, the next slide. Now, Sagar, this is sort of a snapshot here, and it basically says that 44% of CIOs agree that COVID has decreased the organization's evaluation and utilization of emerging tech, despite what I mentioned, Eric Bradley's Venn, which suggested one CIO in particular said, "Hey, I always pick somebody in the lower left "of the magic quadrant." But, again, this is a static view. I know we have some other data, but take us through this, and how this compares to other surveys that you've done. >> No problem. So let's start with the high level takeaways. And I'll actually kind of get into to the point that Eric was debating, 'cause that point is true. It's just really how you kind of slice and dice the data to get to that. So, what you're looking at here, and what the overall takeaway from the Emerging Technology Study was, is, you know, you are going to see notable declines in POCs, of proof-of-concepts, any valuations because of COVID-19. Even though we had been communicating for quite some time, you know, the last few months, that there's increasing pressure for companies to further digitize with COVID-19, there are IT budget constraints. There is a huge pivot in IT resources towards supporting remote employees, a decrease in risk tolerance, and so that's why what you're seeing here is a rather notable number of CIOs, 44%, that said that they are decreasing their organization's evaluation and utilization of private emerging providers. So that is notable. >> Now, as you pointed out, you guys run this survey a couple of times a year. So now let's look at the time series. Guys, if you bring up the next chart. We can see how the sentiment has changed since last year. And, of course, we're isolating here on some of larger companies. So, take us through what this data means. >> No problem. So, how do we quantify what we just saw in the prior slide? We saw 44% of CIOs indicating that they are going to be decreasing their evaluations. But what exactly does that mean? We can pretty much determine that by looking at a lot of the data that we captured through our Emerging Technology Study. There's a lot going on in this slide, but I'll walk you through it. What you're looking at here is Fortune 1000 organizations, so we've really isolated the data to those organizations that matter. So, let's start with the teal, kind of green line first, because I think it's a little bit easier to understand. What you're looking at, Fortune 1000 evaluations, both planned and current, okay? And you're looking at a time series, one year ago and six months ago. So, two of the answer options that we provide CIOs in this survey, right, think about the survey as a grid, where you have seven answer options going horizontally, and then 300-plus vendors and technologies going vertically. For any given vendor, they can essentially indicate one of these options, two of them being on currently evaluating them or I plan to evaluate them in six months. So what you're looking at here is effectively the aggregate number, or the average number of Fortune 1000 evaluations. So if you look into May 2019, all the way on the left of that chart, that 24% roughly means that a quarter of selections made by Fortune 1000 of the survey, they selected plan to evaluate or currently evaluating. If you fast-forward six months, to the middle of the chart, November '19, it's roughly the same, one in four technologies that are Fortune 1000 selected, they indicated that I plan or am currently evaluating them. But now look at that big drop off going into May 2020, the 17%, right? So now one out of every six technologies, or one out of every selections that they made was an evaluation. So a very notable drop. And then if you look at the blue line, this is another answer option that we provided CIOs: I'm aware of the technology but I have no plans to evaluate. So this answer option essentially tracks awareness levels. If you look at the last six months, look at that big uptick from 44% to over 50%, right? So now, essentially one out of every two technologies, or private technologies that a CIO is aware of, they have no plans to evaluate. So this is going to have an impact on the general landscape, when we think about those private emerging providers. But there is one caveat, and, Dave, this is what you mentioned earlier, this is what Eric was talking about. The providers that are doing well are the ones that are work-from-home aligned. And so, just like a few years ago, we were really analyzing results based on are you cloud-native or are you Cloud-aligned, because those technologies are going to do the best, what we're seeing in the emerging space is now the same thing. Those emerging providers that enable organizations to maintain productivity for their employees, essentially allowing their employees to work remotely, those emerging providers are still doing well. And that is probably the second biggest takeaway from this study. >> So now what we're seeing here is this flight to perceive safety, which, to your point, Sagar, doesn't necessarily mean good news for all enterprise tech vendors, but certainly for those that are positioned for the work-from-home pivot. So now let's take a look at a couple of sectors. We'll start with information security. We've reported for years about how the perimeter's been broken down, and that more spend was going to shift from inside the moat to a distributed network, and that's clearly what's happened as a result of COVID. Guys, if you bring up the next chart. Sagar, you take us through this. >> No problem. And as you imagine, I think that the big theme here is zero trust. So, a couple of things here. And let me just explain this chart a little bit, because we're going to be going through a couple of these. What you're seeing on the X-axis here, is this is effectively what we're classifying as near term growth opportunity from all customers. The way we measure that effectively is we look at all the evaluations, current evaluations, planned evaluations, we look at people who are evaluated and plan to utilize these vendors. The more indications you get on that the more to the top right you're going to be. The more indications you get around I'm aware of but I don't plan to evaluate, or I'm replacing this early-stage vendor, the further down and on the left you're going to be. So, on the X-axis you have near term growth opportunity from all customers, and on the Y-axis you have near term growth opportunity from, really, the biggest shops in the world, your Global 2000, your Forbes Private 225, like Cargill, as an example, and then, of course, your federal agencies. So you really want to be positioned up and to the right here. So, the big takeaway here is zero trust. So, just a couple of things on this slide when we think about zero trust. As organizations accelerate their Cloud and Saas spend because of COVID-19, and, you know, what we were talking about earlier, Dave, remote work becomes the new normal, that perimeter security approach is losing appeal, because the perimeter's less defined, right? Apps and data are increasingly being stored in the Cloud. That, and employees are working remotely from everywhere, and they're accessing all of these items. And so what we're seeing now is a big move into zero trust. So, if we look at that chart again, what you're going to see in that upper right quadrant are a lot of identity and access management players. And look at the bifurcation in general. This is what we were talking about earlier in terms of the landscape not doing well. Most security vendors are in that red area, you know, in the middle to the bottom. But if you look at the top right, what are you seeing here? Unify ID, Auth0, WSO2, right, all identity and access management players. These are critical in your zero trust approach, and this is one of the few area where we are seeing upticks. You also see here BitSight, Lucideus. So that's going to be security assessment. You're seeing VECTRA and Netskope and Darktrace, and a few others here. And Cloud Security and IDPS, Intrusion Detection and Prevention System. So, very few sectors are seeing an uptick, very few security sectors actually look pretty good, based on opportunities that are coming. But, essentially, all of them are in that work-from-home aligned security stack, so to speak. >> Right, and of course, as we know, as we've been reporting, buyers have options, from both established companies and these emerging companies that are public, Okta, CrowdStrike, Zscaler. We've seen the work-from-home pivot benefit those guys, but even Palo Alto Networks, even CISCO, I asked (other speaker drowns out speech) last week, I said, "Hey, what about this pivot to work from home? "What about this zero trust?" And he said, "Look, the reality is, yes, "a big part of our portfolio is exposed "to that traditional infrastructure, "but we have options for zero trust as well." So, from a buyer's standpoint, that perceived flight to safety, you have a lot of established vendors, and that clearly is showing up in your data. Now, the other sector that we want to talk about is database. We've been reporting a lot on database, data warehouse. So, why don't you take us through the next graphic here, if you would. >> Sagar: No problem. So, our theme here is that Snowflake is really separating itself from the pack, and, again, you can see that here. Private database and data warehousing vendors really continue to impact a lot of their public peers, and Snowflake is leading the way. We expect Snowflake to gain momentum in the next few years. And, look, there's some rumors that IPOing soon. And so when we think about that set-up, we like it, because as organizations transition away from hybrid Cloud architectures to 100% or near-100% public Cloud, Snowflake is really going to benefit. So they look good, their data stacks look pretty good, right, that's resiliency, redundancy across data centers. So we kind of like them as well. Redis Labs bring a DB and they look pretty good here on the opportunity side, but we are seeing a little bit of churn, so I think probably Snowflake and DataStax are probably our two favorites here. And again, when you think about Snowflake, we continue to think more pervasive vendors, like Paradata and Cloudera, and some of the other larger database firms, they're going to continue seeing wallet and market share losses due to some of these emerging providers. >> Yeah. If you could just keep that slide up for a second, I would point out, in many ways Snowflake is kind of a safer bet, you know, we talk about flight to safety, because they're well-funded, they're established. You can go from zero to Snowflake very quickly, that's sort of their mantra, if you will. But I want to point out and recognize that it is somewhat oranges and tangerines here, Snowflake being an analytical database. You take MariaDB, for instance, I look at that, anyway, as relational and operational. And then you mentioned DataStax. I would say Couchbase, Redis Labs, Aerospike. Cockroach is really a... EValue Store. You've got some non-relational databases in there. But we're looking at the entire sector of databases, which has become a really interesting market. But again, some of those established players are going to do very well, and I would put Snowflake on that cusp. As you pointed out, Bloomberg broke the story, I think last week, that they were contemplating an IPO, which we've known for a while. >> Yeah. And just one last thing on that. We do like some of the more pervasive players, right. Obviously, AWS, all their products, Redshift and DynamoDB. Microsoft looks really good. It's just really some of the other legacy ones, like the Teradatas, the Oracles, the Hadoops, right, that we are going to be impacted. And so the claw providers look really good. >> So, the last decade has really brought forth this whole notion of DevOps, infrastructure as code, the whole API economy. And that's the piece we want to jump into now. And there are some real stand-outs here, you know, despite the early data that we showed you, where CIOs are less prone to look at emerging vendors. There are some, for instance, if you bring up the next chart, guys, like Hashi, that really are standing out, aren't they? >> That's right, Dave. So, again, what you're seeing here is you're seeing that bifurcation that we were talking about earlier. There are a lot of infrastructure software vendors that are not positioned well, but if you look at the ones at the top right that are positioned well... We have two kind of things on here, starting with infrastructure automation. We think a winner here is emerging with Terraform. Look all the way up to the right, how well-positioned they are, how many opportunities they're getting. And for the second straight survey now, Terraform is leading along their peers, Chef, Puppet, SaltStack. And they're leading their peers in so many different categories, notably on allocating more spend, which is obviously very important. For Chef, Puppet and SaltStack, which you can see a little bit below, probably a little bit higher than the middle, we are seeing some elevator churn levels. And so, really, Terraform looks like they're kind of separating themselves. And we've got this great quote from the CIO just a few months ago, on why Terraform is likely pulling away, and I'll read it out here quickly. "The Terraform tool creates "an entire infrastructure in a box. "Unlike vendors that use procedural languages, "like Ants, Bull and Chef, "it will show you the infrastructure "in the way you want it to be. "You don't have to worry about "the things that happen underneath." I know some companies where you can put your entire Amazon infrastructure through Terraform. If Amazon disappears, if your availability drops, load balancers, RDS, everything, you just run Terraform and everything will be created in 10 to 15 minutes. So that shows you the power of Terraform and why we think it's ranked better than some of the other vendors. >> Yeah, I think that really does sum it up. And, actually, guys, if you don't mind bringing that chart back up again. So, a point out, so, Mitchell Hashimoto, Hashi, really, I believe I'm correct, talking to Stu about this a little bit, he sort of led the Terraform project, which is an Open Source project, and, to your point, very easy to deploy. Chef, Puppet, Salt, they were largely disrupted by Cloud, because they're designed to automate deployment largely on-prem and DevOps, and now Terraform sort of packages everything up into a platform. So, Hashi actually makes money, and you'll see it on this slide, and things, Vault, which is kind of their security play. You see GitLab on here. That's really application tooling to deploy code. You see Docker containers, you know, Docker, really all about open source, and they've had great adoption, Docker's challenge has always been monetization. You see Turbonomic on here, which is application resource management. You can't go too deep on these things, but it's pretty deep within this sector. But we are comparing different types of companies, but just to give you a sense as to where the momentum is. All right, let's wrap here. So maybe some final thoughts, Sagar, on the Emerging Technology Study, and then what we can expect in the coming month here, on the update in the Technology Spending Intention Study, please. >> Yeah, no problem. One last thing on the zero trust side that has been a big issue that we didn't get to cover, is VPN spend. Our data is pointing that, yes, even though VPN spend did increase the last few months because of remote work, we actually think that people are going to move away from that as they move onto zero trust. So just one last point on that, just in terms of overall thoughts, you know, again, as we cover it, you can see how bifurcated all these spaces are. Really, if we were to go sector by sector by sector, right, storage and block chain and MLAI and all that stuff, you would see there's a few or maybe one or two vendors doing well, and the majority of vendors are not seeing as many opportunities. And so, again, are you work-from-home aligned? Are you the best vendor of all the other emerging providers? And if you fit those two criteria then you will continue seeing POCs and evaluations. And if you don't fit that criteria, unfortunately, you're going to see less opportunities. So think that's really the big takeaway on that. And then, just in terms of next steps, we're already transitioning now to our next Technology Spending Intention Survey. That launched last week. And so, again, we're going to start getting a feel for how CIOs are spending in 2H-20, right, so, for the back half of the year. And our question changes a little bit. We ask them, "How do you plan on spending in the back half year "versus how you actually spent "in the first half of the year, or 1H-20?" So, we're kind of, tighten the screw, so to speak, and really getting an idea of what's spend going to look like in the back half, and we're also going to get some updates as it relates to budget impacts from COVID-19, as well as how vendor-relationships have changed, as well as business impacts, like layoffs and furloughs, and all that stuff. So we have a tremendous amount of data that's going to be coming in the next few weeks, and it should really prepare us for what to see over the summer and into the fall. >> Yeah, very excited, Sagar, to see that. I just wanted to double down on what you said about changes in networking. We've reported with you guys on NPLS networks, shifting to SD-WAN. But even VPN and SD-WAN are being called into question as the internet becomes the new private network. And so lots of changes there. And again, very excited to see updated data, return of post-COVID, as we exit this isolation economy. Really want to point out to folks that this is not a snapshot survey, right? This is an ongoing exercise that ETR runs, and grateful for our partnership with you guys. Check out ETR.plus, that's the ETR website. I publish weekly on Wikibon.com and SiliconANGLE.com. Sagar, thanks so much for coming on. Once again, great to have you. >> Thank you so much, for having me, Dave. I really appreciate it, as always. >> And thank you for watching this episode of theCube Insights, powered by ETR. This Dave Vellante. We'll see you next time. (gentle music)

>>Live from San Diego, California It's the Q covering Koopa and Cloud Native Cot brought to you by Red Cloud, Native Computing Pounding and its ecosystem March. >>Welcome back to the Cube here at Q. Khan Club native Khan, 2019 in San Diego, California Instrumental in my co host is Jon Cryer and first of all, happy to welcome back to the program. Diane Mueller, who is the technical of the tech lead of cloud native technology. I'm sorry. I'm getting the wrong That's director of community development Red Hat, because renew. Goodbye is the technical lead of cognitive technologies at in video game to the end of day one. I've got three days. I gotta make sure >>you get a little more Red Bull in the conversation. >>All right, well, there's definitely a lot of energy. Most people we don't even need Red Bull here because we're a day one. But Diane, we're going to start a day zero. So, you know, you know, you've got a good group of community of geeks when they're like Oh, yeah, let me fly in a day early and do like 1/2 day or full day of deep dives. There So the Red Hat team decided to bring everybody on a boat, I guess. >>Yeah. So, um, open ships Commons gathering for this coup con we hosted at on the inspiration Hornblower. We had about 560 people on a boat. I promised them that it wouldn't leave the dock, but we deal still have a little bit of that weight going on every time one of the big military boats came by. And so people were like a little, you know, by the end of the day, but from 8 a.m. in the morning till 8 p.m. In the evening, we just gathered had some amazing deep dives. There was unbelievable conversations onstage offstage on we had, ah, wonderful conversation with some of the new Dev ops folks that have just come on board. That's a metaphor for navigation and Coop gone. And and for events, you know, Andrew Cliche for John Willis, the inevitable Crispin Ella, who runs Open Innovation Labs, and J Bloom have all just formed the global Transformation Office. I love that title on dhe. They're gonna be helping Thio preach the gospel of Cultural Dev ops and agile transformation from a red hat office From now going on, there was a wonderful conversation. I felt privileged to actually get to moderate it and then just amazing people coming forward and sharing their stories. It was a great session. Steve Dake, who's with IBM doing all the SDO stuff? Did you know I've never seen SDO done so well, Deployment explains so well and all of the contents gonna be recorded and up on Aaron. We streamed it live on Facebook. But I'm still, like reeling from the amount of information overload. And I think that's the nice thing about doing a day zero event is that it's a smaller group of people. So we had 600 people register, but I think was 560 something. People show up and we got that facial recognition so that now when they're traveling through the hallways here with 12,000 other people, that go Oh, you were in the room. I met you there. And that's really the whole purpose for comments. Events? >>Yeah, I tell you, this is definitely one of those shows that it doesn't take long where I say, Hey, my brain is full. Can I go home. Now. You know I love your first impressions of Q Khan. Did you get to go to the day zero event And, uh, what sort of things have you been seeing? So >>I've been mostly I went to the lightning talks, which were amazing. Anything? Definitely. There. A number of shout outs to the GPU one, of course. Uh, friend in video. But I definitely enjoyed, for example, of the amazing D. M s one, the one about operators. And generally all of them were very high quality. >>Is this your first Q? Khan, >>I've been there. I've been a year. This is my third con. I've been accused in Europe in the past. Send you an >>old hat old hand at this. Well, before we get into the operator framework and I wanna love to dig into this, I just wanted to ask one more thought. Thought about open shift, Commons, The Commons in general, the relationship between open shift, the the offering. And then Okay, the comments and okay, D and then maybe the announcement about about Okay. Dee da da i o >>s. Oh, a couple of things happened yesterday. Yesterday we dropped. Okay, D for the Alfa release. So anyone who wants to test that out and try it out it's an all operators based a deployment of open shift, which is what open ship for is. It's all a slightly new architectural deployment methodology based on the operator framework, and we've been working very diligently. Thio populate operator hub dot io, which is where all of the upstream projects that have operators like the one that Reynolds has created for in the videos GP use are being hosted so that anyone could deploy them, whether on open shift or any kubernetes so that that dropped. And yesterday we dropped um, and announced Open Sourcing Quay as project quay dot io. So there's a lot of Io is going on here, but project dia dot io is, um, it's a fulfillment, really, of a commitment by Red Hat that whenever we do an acquisition and the poor folks have been their acquired by Cora West's and Cora Weston acquired by Red Hat in an IBM there. And so in the interim, they've been diligently working away to make the code available as open source. And that hit last week and, um, to some really interesting and users that are coming up and now looking forward to having them to contribute to that project as well. But I think the operator framework really has been a big thing that we've been really hearing, getting a lot of uptake on. It's been the new pattern for deploying applications or service is on getting things beyond just a basic install of a service on open shift or any kubernetes. And that's really where one of the exciting things yesterday on we were talking, you know, and I were talking about this earlier was that Exxon Mobil sent a data scientist to the open ship Commons, Audrey Resnick, who gave this amazing presentation about Jupiter Hub, deeper notebooks, deploying them and how like open shift and the advent of operators for things like GP use is really helping them enable data scientists to do their work. Because a lot of the stuff that data signs it's do is almost disposable. They'll run an experiment. Maybe they don't get the result they want, and then it just goes away, which is perfect for a kubernetes workload. But there are other things you need, like a Jeep use and work that video has been doing to enable that on open shift has been just really very helpful. And it was It was a great talk, but we were talking about it from the first day. Signs don't want to know anything about what's under the hood. They just want to run their experiments. So, >>you know, let's like to understand how you got involved in the creation of the operator. >>So generally, if we take a step back and look a bit at what we're trying to do is with a I am l and generally like EJ infrastructure and five G. We're seeing a lot of people. They're trying to build and run applications. Whether it's in data Center at the and we're trying to do here with this operator is to bring GPS to enterprise communities. And this is what we're working with. Red Hat. And this is where, for example, things like the op Agrestic A helps us a lot. So what we've built is this video Gee, few operator that space on the upper air sdk where it wants us to multiple phases to in the first space, for example, install all the components that a data scientist were generally a GPU cluster of might want to need. Whether it's the NVIDIA driver, the container runtime, the community's device again feast do is as you go on and build an infrastructure. You want to be able to have the automation that is here and, more importantly, the update part. So being able to update your different components, face three is generally being able to have a life cycle. So as you manage multiple machines, these are going to get into different states. Some of them are gonna fail, being able to get from these bad states to good states. How do you recover from them? It's super helpful. And then last one is monitoring, which is being able to actually given sites dr users. So the upper here is decay has helped us a lot here, just laying out these different state slips. And in a way, it's done the same thing as what we're trying to do for our customers. The different data scientists, which is basically get out of our way and allow us to focus on core business value. So the operator, who basically takes care of things that are pretty cool as an engineer I lost due to your election. But it doesn't really help me to focus on like my core business value. How do I do with the updates, >>you know? Can I step back one second, maybe go up a level? The problem here is that each physical machine has only ah limited number of NVIDIA. GPU is there and you've got a bunch of containers that maybe spawning on different machines. And so they have to figure out, Do I have a GPU? Can I grab one? And if I'm using it, I assume I have to reserve it and other people can't use and then I have to give it up. Is that is that the problem we're solving here? So this is >>a problem that we've worked with communities community so that like the whole resource management, it's something that is integrated almost first class, citizen in communities, being able to advertise the number of deep, use their your cluster and used and then being able to actually run or schedule these containers. The interesting components that were also recently added are, for example, the monitoring being able to see that a specific Jupiter notebook is using this much of GP utilization. So these air supercool like features that have been coming in the past two years in communities and which red hat has been super helpful, at least in these discussions pushing these different features forward so that we see better enterprise support. Yeah, >>I think the thing with with operators and the operator lifecycle management part of it is really trying to get to Day two. So lots of different methodologies, whether it's danceable or python or job or or UH, that's helm or anything else that can get you an insult of a service or an application or something. And in Stan, she ate it. But and the operator and we support all of that with SD case to help people. But what we're trying to do is bridge the to this day to stuff So Thea, you know, to get people to auto pilot, you know, and there's a whole capacity maturity model that if you go to operator hab dot io, you can see different operators are a different stages of the game. So it's been it's been interesting to work with people to see Theo ah ha moment when they realize Oh, I could do this and then I can walk away. And then if that pod that cluster dies, it'll just you know, I love the word automatically, but they, you know, it's really the goal is to help alleviate the hands on part of Day two and get more automation into the service's and applications we deploy >>right and when they when they this is created. Of course it works well with open shift, but it also works for any kubernetes >>correct operator. HAB Daddio. Everything in there runs on any kubernetes, and that's really the goal is to be ableto take stuff in a hybrid cloud model. You want to be able to run it anywhere you want, so we want people to be unable to do it anywhere. >>So if this really should be an enabler for everything that it's Vinny has been doing to be fully cloud native, Yes, >>I think completely arable here is this is a new attack. Of course, this is a bit there's a lot of complexity, and this is where we're working towards is reducing the complexity and making true that people there. Dan did that a scientist air machine learning engineers are able to focus on their core business. >>You watch all of the different service is in the different things that the data scientists are using. They don't I really want to know what's under under the hood. They would like to just open up a Jupiter Hub notebook, have everything there. They need, train their models, have them run. And then after they're done, they're done and it goes away. And hopefully they remember to turn off the Jeep, use in the woods or wherever it is, and they don't keep getting billed for it. But that's the real beauty of it is that they don't have to worry so much anymore about that. And we've got a whole nice life cycle with source to image or us to I. And they could just quickly build on deploy its been, you know, it's near and dear to my heart, the machine learning the eyesight of stuff. It is one of the more interesting, you know, it's the catchy thing, but the work was, but people are really doing it today, and it's been we had 23 weeks ago in San Francisco, we had a whole open ship comments gathering just on a I and ML and you know, it was amazing to hear. I think that's the most redeeming thing or most rewarding thing rather for people who are working on Kubernetes is to have the folks who are doing workloads come and say, Wow, you know, this is what we're doing because we don't get to see that all the time. And it was pretty amazing. And it's been, you know, makes it all worthwhile. So >>Diane Renaud, thank you so much for the update. Congratulations on the launch of the operators and look forward to hearing more in the future. >>All right >>to >>be here >>for John Troy runs to minimum. More coverage here from Q. Khan Club native Khan, 2019. Thanks for watching. Thank you.

>> Narrator: Live from Nice, France. It's The Cube covering .Net's Conference 2017 Europe. Brought to you by Nutanix. >> Welcome back to The Cube. I'm Stu Miniman, happy to be joined on the program by two gentleman from Intel. We have Michael Kawalik, Michal Kowalik, sorry, and Justin Wheeler. Thank you both for joining us today. >> Michal: Pleasure. >> Michal let's start with you. Tell us a little bit about, you know, your role, how long you've been at Intel, a little bit about your background. >> I might skip how long I've been at Intel because it would reveal how old I am. But I run Sale Swift ISV's so as you can imagine Nutanix is one of our top partners and hyper converged. And it's a pleasure to be here in Nice and see all those crowds interested in software defined, so happy to be here. >> Alright so you say you've been through a couple of cranks and more cycle... >> It's been a long seventeen years now. >> Yeah we say bring the Intel people, tick tock. We keep you moving. >> Yes. >> Alright Justin same question for you. Tell us a little bit about your background and how long you've been at Intel. >> Yeah, I'm a storage solutions Architect with the non volitile memory solution's group, thankfully called NSTRY for short, one of the good uses for acronyms. So basically I talk about anything flash, anything solutions oriented around storage. Quite a broad range subject but very insaning one, and one that I enjoy immensely as well. >> Alright, so Michal, what brings Intel to the event of course, you know, most of the Nutanix deployments run on some flavor of your processors but maybe take us a little beyond that as to you know, what the partnership looks like. >> Sure, I understand. So the reason we're working with Nutanix is because we believe that they're our key partners to change the market of the software defined and the general data center and to the hyper converged. So we're working with the key partners and the fastest running rabbits like Nutanix to talk to our end customers for them to see the benefit. What is a hyper converge, what is software defined center. And with Nutanix we're able to turn those customers into the newest technology that is the fastest. It's more about the new technologies. It's more about new work loads, new use cases. That's why we're here. We really appreciate the business of Nutanix but we're here to make it faster, better, bigger. >> Justin, you actually give a presentation here at the show. Sounds like it ties in a lot of this. Why don't you give us a little bit of thumbnail of what you we're talking about. >> So basically building on what Michal was saying, technologies evolve massively, you know, the way people are thinking about infrastructures especially from a storage perspective, the agility, the new solutions provider and hyper convergents. You know, really the technology that enables that is main part of what that talk was this morning. So Envyame becoming more mainstream as devices where the prevalence of you got two in connectivity of choice in most service now a days. So really kind of like dropping the shackles of the old ways of doing things and how we fit in with that from CPU, storage and networking perspective. >> Yeah I heard in the key note this morning, you know Skylike and Envyame were the two things that you know, made me think of what your organization is doing. >> Very much so, and I think we're still actually involved in the run, as I mentioned in the conversation this morning. There's so much more development that can be done. It's an exciting time to be involved. You know, be in point with these guys at Nutanix is one of the key things. You know this is storage sanctual for us. You know, the story that we have is very much hand in glove with what these guys, you know, want to achieve as well. >> Yeah, I'm curious, you know, when we think about customers one of the challenges they always have is upgrade cycles. And upgrade cycles have actually been useful for Intel but when we go to hyper converge, in some ways I think it would make it easier for, you know, how we manage those upgrades. Is there any commentary on that? >> Sure, so we're working with Nutanix ongoing basis and we had a very interesting meetings in Dubai two weeks ago when we sat with Nutanix, okay. How can we turn the customers using current infrastructure which very often is really softer defined but this is like a few years ago. And they just said we need to go there with the demo kits. You know you're talking about the small computers, three tiers and we're just showing them, look. You just plug it in, you put a few work loads bubbles your ankle. So that's how we can accelerate together the, refresh the replacements and basically make their lives better and easier. >> The moral of this story is quite something that most people's blood would run cold in especially if you're on the south side of things. But given, like Michal was saying there, we got minish and nucks that we can actually go out and we can run what was previously considered an enterprise class storage solution on a couple of desktop PC's in effect now. You know, the agility is really the key thing here. You know, when you're talking about hyper converge software defined, converged solutions, whatever alteration you're looking at there, the agility this brings to you now a days is just fantastic and it's a compelling story. And it's getting out there and telling the people about it. You know, shout it from the rooftops you know. But it's not just the technical, it's also the business case around it. It's hand in glove again. >> How does Ageve fit in to that? Is Intel pretty much agnostic on that or is there anything special from the hypervisor stand point? >> No, that's one of the best things about Intel. I mean previous jobs I've had, I've been one trick pony or you know only talk about storage. I mean, as I said early on, we've got all three major components of any solution now days. So that's a network computing storage, we work across them. Same with the application perspective. Workloads for us, we don't have to be specific about it. We talk about what's good for the customer. What they want from their storage infrastructure. And it's not just from technical perspective. It's how they view their business evolving. Again we come back to the agility work. >> And it's exactly how we do it. So Intel is well known and sometimes a little bit you know, too well know of putting a lot of bench marks, those features. So what we're doing right now with all the hypervisors and basically the software defined centers is we're showing the use case bench mark. So our customer, you have an SQL on your bare metal. Here's the bench mark. Here's how faster it's going. Here's more availableness or here's the adjuster recovery stuff we have together. So we're no longer talking about the pure performance. We're talking about what is the value for our customer for implementing obtains or implementing skylights or any other technology. >> You've got commonality that needs to be maintained. People have invested a large amount of money and skills sets of individuals in their department. You know, you've got to take into consideration also the cloud strategy, whatever that may be. Whether it be hybrid or whether that be for cloud. You know, moving migrating work loads data in and out. You know, it's a big part of it, so it's not a one solution fits all. Everyone's built differently. People look at ESXI, you have the one Acropolis, the one at Cavium, the one Hyperv. We play across all of those. That's the fun part of the job. >> What feedback are you getting from customers, you know, at the event or just in general or Nutanix space? >> Is it a deploy for starters. It's a highly skilled sales force. Very good technical support. And we're trying to follow Nutanix. We have an engineering support on our side as well. So wherever we can help, whatever we can... improve or increase velocity of those replacements, we're going together. But customers are generally happy with Nutanix, which we're very happy with, because for us, again one of the key partners to drive the hyper converge infrastructure. >> I mean as we mentioned earlier on the story resounce you know, it's a good story to tell. You just got to look at the attendance here today to see how well Nutanix hours company. And as I mentioned earlier, you know we just sort of bought and run here. You know, when you actually talking about replacement of traditional storage systems towards a hyper convergent you want to make sure that that is something that's easy to deploy, easy to manage, cost effective. There's not a lot not to like about Nutanix Solutions. So you can see that attendance here, everyone speaks very highly of it. You know, and I think it's just a snapshot of the people that's here. Technically it makes sense, commercially it makes sense. >> Justin any tips from your presentation for customers as to help them get things done even simpler than what they've been doing before? >> I thought when you we're talking about tips, about the thing that I was going to say, don't drink Red Bull before you give a good presentation. But no, consultative approach really the way to go about it. Don't believe everything that you hear. I'm self confessed, you know, not a great fan of bench mark figures because they're unrealistic in many workloads that's out there now a days. The key thing for us is come to talk to us. Let us consult with you with our partners. Understand your business, your workloads. Deployment side of things comes very easy after that. You've got to do the groundwork but you can't just dismiss good design practice or good best practice. >> Yeah I mean for the entry point to start playing and doing things with Nutanix is pretty well. They make it easy to test things out and almost every customer I talk to is like, they have to prove themselves and it's a testament to Nutanix that, you know, they've got so many customers and they keep growing because if they couldn't deliver on what they said they wouldn't be where they are. >> That is correct and the funny thing is in a conversation with Nutanix, how can we help them to accelerate the deployments or accelerate the demos so this very beginning, they said we actually don't want to use the full fledge boxes because the customers don't want to give them back. So we have to have something smaller so they need to buy it at some stage. It was a very good comment that it means it works and that Nutanix knows how to do it. >> Yeah I think if I read, Derodge was like he loves his thing and that they can fit in a processor in the palm of his hand 'til we stick it in a drone. I think he wants to be able to deliver it to the customer, have them demo it and then he'll remote control it back after a certain... >> That's already possible with Intel technology and a pleasure to deploy it. >> I mean as with everything you know, it's use the architectural set, it's everything that's sturdy, that's lasted years it's been built on solid foundations. You get foundations right on any infrastructure, and it's the same with that, it will be there. You can build on it. You can, you know, continue on and evolve as business grows. So rather build something that you can roll with. >> Well Justin, Michal, really appreciate you sharing the update on Intel's partnership with Nutanix. We'll be back here with lots more coverage from Nutanix .Next in Nice, France. I'm Stu Minnamin and you're watching The Cube. (electronic music) >> Narrator: Live from Nice, France, it's the Cu...

(upbeat music) >> Hey, welcome back everybody. Jeff Frick here with the Cube. We're having the Cube conversation in our Palo Alto studio. The conference season is taking a little bit of a break, so now we can do interviews in the studio which is a little bit more comfortable situation, and we're really excited to have first time guest Karen Steele. She's the GVP of corporate marketing at Marketo. Karen, welcome. >> Thank you, very happy to be here Jeff. >> Absolutely. So, you are talking about something that I've seen in the research coming up to this about engagement. And right, everybody talks about engagement. What is engagement? People are trying to measure engagement, >> Karen: Yep. >> But then it seems like so many people are still stuck though on the mass broadcasting kind of numbers. The want big numbers which is a very different number than engagement. So You guys are getting really into this. Obviously Marketo a leader in marketing innovation and marketing platform. Is this new? Is it renewed focus? I mean, how do you guys deal with this whole concept of engagement? >> Yeah, so thanks. It's a great opening question because we are passionate about engagement. And in fact, we believe that today, people, human beings want to be engaged with as opposed >> to marketed to. >> Right. >> So our CEO created a vision of this idea called The Engagement Economy. And the idea is that everybody and everyone is connected. Today with the digital transformation happening around us, you can touch people, touch customers anywhere and everywhere throughout their journey. You know, before they buy from you, during the sales process and post sale. So, it's all about creating experience and we think the way to do that is through engagement. >> But it's kind of interesting 'cuz the dichotomy is we're in this Google world, right? And the Google world is, you know, build great engineering, people will come. It's all about the data. It's cookies and where have you been and you know, recommendation engines. And more of this kind of, feels more machine-y And not necessarily engage-y, Which is more of a person to person than necessarily a machine to person. >> Karen: Correct. >> But yet, even the person to person is still supported by and enabled by a lot of this technology. So it's this inter, intertwining of both kind of a person to machine, or machine to person, >> excuse me. >> Yep. >> Versus really connecting with, whether it be the brand, Whether it be a person that represents >> the brand >> Right. >> So how, how do you see this kind of evolving and how can people not get too wrapped up >> in the machine-y part? >> Right. >> And actually build a relationship, another word instead of engagement, with their customers, or even take it another step, with their constituents, if you will? >> Yes. >> And their community, >> even more passionate. >> Yes. Yeah, so I think it's interesting you brought up the machine aspect, 'cuz there's sort of a positive and negative. So if you think about the space we're in, it's called Marketing Automation. And it does feel sort of process oriented and machine-like. But at the end of the day, marketing has always been about the human being and building that relationship. And technology has just simply helped facilitate that and do it through multiple channels like never before. But it still comes down to the marketer's primary role is to connect with, in a personalized way, in an authentic way and create a relationship. A relationship that's going to generate advocacy for the brand, that's going to ultimately generate revenue for their business. So it's really important that engagement is about the human being and it's about how you can create positive experience throughout the lifecycle of the journey. >> Right, it's interesting you say experiences too, 'cuz we've seen a huge shift in into customers wanting really more of an experience or an engagement that's potentially tied to a brand. But you look at great experience marketers like Red Bull, >> Yep. >> To pull one out. >> That you know, buying and drinking a Red Bull, the way they've positioned that in the marketplace is really being part of this really cool thing. It's visually stimulating, it's you know, a lot of >> adrenaline, >> Yes. >> and a lot of cool stuff. And then the other one I always think of is Harley Davidson. And the passion that that community has around that motorcycle. But it's so much more than driving that motorcycle, >> You know? >> Yep. >> It's the open road and it's all the accessories and stuff that they put. You know people brand it on their arm. >> A lot of people. >> Right. >> So, in terms of you know how, how does that translate with newer brands? How do you try to get that type of connection with your customers, hold it, and I think you've mentioned in some of the things I've looked up for the interview you know, really thinking about the lifetime value of the customer as opposed to a transactional relationship? >> Right. >> That's a one time shot. >> Yeah, I mean a lot of the examples you, you just gave are very experiential in terms of the physical aspects of seeing, and feeling, and touching a brand. But a lot of digital marketing is, is not physical. And so you're communicating with people through a lot of channels that that are bits and bytes, and they're not looking somebody in the eye. And so I think being in touch with your brand and the messages you want to deliver. Making sure they're relevant and they carry your brand promise forward, and they connect with what that person wants to hear at exactly the right times. So for us engagement is, is about being smart in terms of reaching the person. If I use a social, or excuse me, a mobile device and that's my preferred way of communicating with you, I want you to reach me through that device, and not try and get me through direct mail or an email campaign. I might not pay attention to any of those things. So having that intelligence about your customer, or your prospect, or your partner, or even your employee is going to give you a better option to engage with them and create that one to one while you're still marketing one to many. >> Right. >> In terms of >> the actual relationship. >> And the other challenge a marketer obviously has too, is, I don't know who said it, we do too many shows. But you know, when it's done well, when suggestive selling is done well and recommendation engines are working well, it's magical. >> Yep. >> Right? >> It's what I want, when I want and it's presented to me. >> Yep. >> If it's done poorly, >> it's creepy, right? >> Yep. >> I don't necessarily >> know that you want to know that that was, you know what I was looking at. And obviously the target example which now is way far in the rear view mirror. But you know just because you have all the data, doesn't mean you can use all the data. And the challenge and the nuance of knowing what to use, when and where. >> Right. >> Well now you have >> so much more, kind of ammunition in >> your quiver if you will. >> Yep. >> Is a whole different type of a challenge. >> Yeah I think it's, it's a good point, and I think you're right. You don't want it to feel like big brother and somebody's following or stalking you, that's the last thing you want. But I think paying attention to the response, paying attention to a personalized message, testing that message, seeing what comes back, and helping execute the next thing that you do. And so there's sort of a fine line, but I definitely think the marketers are using the analytics today and it's just getting smarter and smarter. And we're going to talk about adaptive coming up here, >> I hope? >> Right, right. >> And you know, the big buzz right now which is AI, you know, what does AI mean for engagement? And we have some ideas around that >> as well. >> Right. >> Okay, so you broke it down to >> the big threes >> Yep. >> of the engagement economy. So the art of story telling. >> Karen: Yep. >> Adaptive engagement, >> as you just mentioned. >> Yep. >> And then advocacy. >> Karen: Yep. >> Which you talked about earlier before. So let's, let's kind of touch base on each one of those >> things. >> Great. >> How do you define 'em? Why are they important? So start out with the story telling. >> Yeah so it comes back to what we've already been talking about, which is the one to one relationship. Understanding who you're talking to. Crafting a message that, that resonates. Having that message be front and central to what your brand value is. You know, we are more prone to buy from somebody if we value their brand. You might make choices and pay a price premium if you care about a brand or how a brand interacts with you. So crafting the art of story telling is the right message, making sure it resonates, understanding your audience, and connecting it to the brand so you can make that >> emotional connection. >> Right, right. >> So how do you >> So, done, done well, >> you can do a very good job. >> Right, and it's always interesting to me, I always think, I watch sports on TV, right? I always think of the poor guy that just got assigned, I got to do a car commercial. Like, how many car commercials have been created up till now? And I got to think of a new one. >> Right. >> But, >> But you know, kind of traditional, kind of high end TV broadcast commercials are really story telling. I mean, some of them are fascinating what they can actually convey in a 30 second >> ad. >> Right. >> Or whether it's a Coke commercial and makes you cry at the end. So that, that, and that format has, has pretty well developed. But how are you seeing it translated into all these various digital formats and really short engagements, or it's a Snapchat, or it's (snaps fingers) you know a quick hit on Instagram, or it's a Facebook post. >> Karen: Yep. >> How are you seeing some of that story telling evolve into these different kind of communication mediums, if you will? >> Yep. >> And, and you >> you have so many that you have >> to >> Right. >> Jeff: to manage, right? A huge challenge. >> Yeah, and again, I think it's the authenticity as I said, but also the personalized nature of it. I want to deliver a message that matters to you. Where you want to receive that message. I might want to deliver something different to somebody else through an entirely different channel. So, but crafting the story, having the story be based on what you stand for as a brand, and the value for that customer, or whoever the message is, you're attempting to land it on >> Right. >> is still foundational and fundamental. And I think that a lot of the marketing, because technology's automated so much, we've lost a little bit of the art of the story. And really making the story connect back to you as a brand so you deliver the best message to your customer. >> Right. So that kind of feeds into your second one which you described as adaptive engagement. Which I presume is situational, contextual. >> Correct. >> That defines the how, the when, the where, the why. >> Yeah. Yeah, and I think in terms of our vision, so yes it is about delivering the right message, at the right time, to the right person to get the response you want. That's sort of the basics of adaptive and being able to do that very flexibly with technology. But when we think about adaptive and the next generation of it, we think about the impact that AI will have on engagement or marketing. So imagine a marketer today could say to their engagement platform, let's say the Marketo engagement platform, "I want to understand an outcome "and the best way to go about it. "I want to know how I can increase sales "in a particular region, in a particular quarter." And the engagement platform, based on that outcome that I want, will help determine what the right campaign is, what creative elements you put in that campaign based on the assets you've created, and importantly, who you target. And what is the audience? And think of almost just creating that outcome, having the platform deliver that whole experience when you push a button. And that entire campaign gets executed. >> Right, right. >> So that, I think is the future of adaptive. >> Because you'll be able to run you know, A/B test is probably not a very accurate description, >> right? >> Right. >> 'Cuz it's a multi, much more multivariate test that you can run and really >> start to optimize >> Right. >> for a much tighter group of attributes of your customer. >> Than >> Right. >> you ever could >> Yeah, and we >> in the past. >> Jeff: Or try to think of every kind of variable. >> And we do that today, but I think, I think now what we're saying is the marketer's going to truly be in the power seat where they can say not just, "Here's two ideas, test one against the other." It's basically, here's the outcome I want. >> Jeff: Right. >> Tell me exactly the best way to put that message out. What channel it should go through, who it should be delivered to, and run it. And so I think that's going to be the future of adaptive. >> Interesting. And then the third A, that you have, of engagement economy is advocacy. >> Heart and soul of any brand strategy. You know customers, loyal customers, are great customers and you want to create advocacy and relationships. I think when companies talk about advocacy, they talk about "I want a customer reference. "I want somebody who's going to approve a customer story "or a quote in a press release." We go far beyond that when we think about advocacy. We want customers that are going to partner with other customers and make the community around us better. >> And so, >> Right. >> they're speaking on behalf of our brand, Marketo, but they're also making our brand stronger and the relationships they're creating around Marketo. So we have a program called Purple Select, which has about 1200 customers, that every single day you know, we're putting challenges forward for them. We're offering them places to go, you know, generate conversations in community. And as a result they give stuff back to us. >> And they >> Right, right. >> make things available to us that otherwise wouldn't be. >> It's really kind of analogous to open source, right? The fact that you know >> all the smartest people >> Yep. >> in the world, don't happen to reside in your four walls. >> And >> Yep. >> you know, if you can use your product service offering platform, store, as a basis point for an engaged community to engage around, through, with. >> Correct. >> You know, >> you get you know, one plus one makes three, or ten for that, so huge. >> Absolutely. >> Huge kind of shift in, in thinking to really kind of open it up and to share and be collaborative and find out what other people >> are doing. >> And let, >> I think that's a great point. And let the advocates be your heroes. Let them advance their careers based on learning your technology, participating in your community and taking you know, their businesses forward in terms of success from a marketing standpoint. >> So I'm just curious in terms of the holy grail of measuring engagement. You know, kind of your thoughts on that. I mean there are obviously engagement measures out there. >> Karen: Right. >> How do you, you know, what are some of the things you look at to measure engagement. Or that you tell people they should look at to measure engagement. And how do you see engagement as a metric, as an actionable metric kind of evolving? Now that we have so many more potential touchpoints, >> datapoints, >> Right. >> other ways to measure. >> Yeah, so I think in the traditional marketing automation world, which we have played a big part in over the years, the true measurement has always been about pipeline. >> 'Cuz you're >> Right. >> you're doing campaigns to generate revenue for your business. I don't think that goes away, but it gets extended to across the entire lifecycle. So it's not just new customer acquisition. It's up-sell, it's cross-sell, it's renewals if you're in a softwares as service business. So it's lifetime value, not just revenue. >> Jeff: Right, right. >> It's advocacy, not just references. It's you know, peer to peer. There's this whole idea of voice of the customer. There're new companies out there like TrustRadius and G2 Crowd which provide platforms now for customers to do reviews on products and rank companies. And making that available to users gives everybody a voice in the process. >> So. >> Right. >> There's a whole bunch of new metrics, many of them are going to be, you know, very, very much around emotional connections back to your brand. And participation in the community. Today we have the marketing nation which is a 60,000 person community. The way I can cultivate content on that and grow people's roles in participating in that dialogue, is certainly an engagement measure for us. And it will lead to stronger sales, it will lead to stronger you know, preference in terms of our brand. It will lead to premium pricing if we want to do that in the future, et cetera. >> And then I wonder too, if you could just speak to the evolving role of marketing. Not only within the company, but specifically within IT spend, and business analytics spend, and really as a driver. >> Because before >> Yep. >> the analytics was really a service provider to the rest of the company >> and we gave you >> Yep. >> your quarterlies and your weekly sales reports and you know, that was kind of the role of IT. Now we're seeing IT as a business partner stepping in to say, "Here's all these cool technologies." But now marketing and the marketing automation which is way ahead of the automation >> Right. >> in a lot of >> the other places, is really driving that, and you've got measure, measurable results, and you can connect to all the different channels that are new that weren't there two years ago when you just had newspaper and >> Yep. >> and billboards and TVs. >> So you know, as that has evolved how have you seen, you know, marketing's role change in terms of kind of, power seat at the table, driving IT, investment decisions and those types of things? >> Obviously Marketo's >> Yep. >> were those decisions for a lot of companies. >> Yeah and it's a great conversation because there's been a lot of talk about the, the hybrid CMO, and what does that look like today? Because the CIO and the CMO now have to be in lockstep. In many cases now, the CMO's technology budget is looking as large as the CIO's technology budget. >> Right, right. >> And so. >> And then there's this other notion of if marketing owns the customer experience, or all things around customer engagement, are they not, in fact, the chief customer officer? And so, there's a whole bunch of things that I think are crossing lines. But I think it's great news for the marketer, because they need to be more customer centric, they need to be more data centric, and ultimately they sit in a really pivotal place in the organization to achieve many of those things. >> Right. And it's still interesting, and for all the soft things, I'll call it a soft thing, of engagement and lifetime value and some of these, some of these things that aren't necessarily tied to the bottom line at the end of the quarter, >> Right. >> every quarter. >> We still have to respond to that. And at the end of the day there has to be some, some ties, some connection, some demonstrated >> value of these efforts. >> Right. >> It can't just be for you know, apple pie and lemonade, I forget the expression. But anyway (laughs). So, 'cuz it still has to tie back to business, right? >> Absolutely. >> Still has to pay the bills, >> still has to get more sales. >> Absolutely. >> But what you're >> saying is, is it does. Engagement does translate into sales. >> Engagement translates to sales. Engagement translates to brand preference. Engagement translates to price premium. Engagement translates to advocacy. I mean, engagement is, it's such an active way to move the market forward that I think there's going to be a whole set of new metrics that combine sales enablement and sales processes as well because as marketing and sales partner, you know, from a sales engagement standpoint to go after named accounts, the ones that are most strategic to the business we're going to see a huge shift in terms of sales, sales engagement metrics as well. >> Just as you're saying that, I'm thinking of brands, right? And always the debate about the power of brand, and does brand still have power? And I think it does, but the market's really kind of bifurcated where either the brand is super powerful, or has zero power, you know, kind of depending on the product or the engagement. It sounds like really, engagement is probably the best way to make sure your brand can't be replaced by the old white label stuff that they used to have at the grocery store. >> Karen: Yeah. >> 'Cuz people got to be connected. >> Karen: Yep. >> Jeff: Not just a label. >> And they need to care about, people need to ultimately care about the relationship. Not the one thing. You know it used to be you dropped a direct mail, it was sort of an episode and you were never having a dialogue. Today, there's so many ways and so many channels to reach people, you have to have a consistent way to engage and a consistent way to look at, did I move the needle forward? Am I ultimately renewing that customer? Or generating more loyalty from that customer? Or you know, referenceability or advocacy. And so, engagement helps you do that through all the channels. >> It's interesting 'cuz the customer can engage with you, whether you, or communicate with you, whether you >> necessarily want it or not. >> That's right. >> And in new ways that were heretofore nonexistent. >> Karen: That's right. >> Fun stuff. >> Yeah. >> Great place to be. >> Well Karen, I loved >> Yeah. >> sitting down and talking about engagement. It's a thing we talk about here all the time. >> Great. >> It's really how we should measure success, it's how we know we're getting through and look forward to a follow up. I know you have some research coming out, and some books coming out, and Marketo's up to all kinds of stuff. So we will look for that in the not so distant future. >> Awesome. >> Alright. >> Thank you. >> We look forward to it. >> Absolutely, she's Karen >> Thanks a lot. >> Steele from Marketo, I'm Jeff Frick, you're watching the Cube. Thanks for watching, we'll see ya next time. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering HPE Discover 2017. Brought to you by Hewlett-Packard Enterprise. >> Okay, welcome back everyone. We are here live in Las Vegas for SiliconANGLE Media's, theCUBE's exclusive coverage for three days for HPE Discover 2017. We're on day three, down to the wire here. I'm John Furrier with SiliconANGLE with my co-host Dave Vellante, my partner in crime with Wikibon. Our next guest, Ric Lewis. Software Defined Cloud Senior Vice President, President and GM of HPE, welcome back to theCUBE. >> Thank you. >> And Kate Swanborg, Senior Vice-President Tech Communications and Strategic Alliances, DreamWorks Animation. Welcome back as well. >> Thank you. >> John: Great to have you guys back. >> It's good to be here. >> So obviously DreamWorks, you guys are a big customer, Ric you are now leading up the team for Software Defined infrastructure, as we call it programmable infrastructure, a lot of great things. >> Ric: Yeah. >> Synergy we talked heavily about last year. >> Ric: Yeah. >> I kind of was geeking out with you on that in terms of all that programming ability and automation. Meg story this week was simplifying hybrid IT, which is the key part of where Software's coming in. >> That's exactly right. >> And so we got DreamWorks here, what's your vision in how that's going to happen? How do you take that simple message and put it into practice? >> Yeah so, we're completely about making hybrid IT simple, and we have three primary vectors that we're driving in order to make that happen. The first is our hyperconverged appliances that we deliver, and the second is HPE Synergy, our composable, and the third is our hybrid IT management stacked software that we have. And we've got momentum across all of those. In Hyper Converged, you guys know we acquired SimpliVity, it closed in February. Got a lot of customers on that. We had Red Bull on-stage here at Discover talking about their use case of that in their racing. It was a packed house, people completely interested in all the things we're doing in hybrid IT. That's SimpliVity. Synergy, we now have almost 400 customers that have adopted Synergy. We started shipping in volume in December, and DreamWorks Animation is one of those customers, and real excited for you to hear a little bit about how they're using it, but we had, I think we had around 10 customers from Synergy across all kinds of verticals and use cases, including service providers that were on-stage here. And the final thing is our hybrid IT management stack, a program that we introduced here at Discover called Project New Stack. So, that's what's going on in Software Defined & Cloud, it's a lot right now. >> And we had a SimpliVity customer on by the way, they were really glowing. >> Yeah. >> Great to see that happen. >> That was a great story. >> Great story, Kate, so DreamWorks, you guys have a business, you've got to put a product out there and so you got to look at technology, make it work for you, and sometimes you got to get in the weeds, there's pieces and pieces, at the end of the day you got a product to deliver. How are you guys taking some of the things that are coming out at HPE and putting them into action? What are some of the things you're doing? >> Well, I think one of the things that is often surprising to people is just how much technology we consume to make a CG feature animated film. These films take 80 million compute hours to render the images, petabytes of storage and we're typically working on five or six active films in production because they take us four or five years to make. And so we want to be able to have the capability of releasing two or three films a year, we must have simultaneous production. But of course, not all of the productions are exactly the same, and we've also got other media opportunities, whether it's television or theme park. And so, what's critical to us is that we're actually able to provision the right amount of digital resource to the right project quickly and easily so that as those creative inspirations are growing and burgeoning at the studio, we've got the resource behind it in an effortless fashion. >> And how are you making that happen with the Synergy for example, because last year we were looking at thinking well this has got a lot of potential. I mean you can do it through the orchestration, making the management work kind of takes that, abstracts away a lot of the complexity. How are you guys dealing with that, I mean how have you put that into action? >> Well, we've been working within a hybrid environment for years now, so the idea of a hybrid environment isn't new to us. The key however, is that it's labor intensive. It's time-consuming. In order to get all of the right configurations of the networking and the storage, the compute to actually work in a realtime environment for our artists, that has taken us an enormous amount of effort over the years. What we're looking for in the Synergy deployment is to reduce those weeks down to days and those days down to hours. Once we're able to do that, our engineers can go off and focus on the niche technology solutions that actually matter to the artists. And that's where we want to get the business benefit. >> And with Synergy, compute, storage and fabric all managed under the same management domain. >> That's right. >> Single API that you can get access to all those resources, so it makes it super easy. It's the world's easiest way to do infrastructure as a service, it's built into the platform natively. >> That's right, and one of the things that's been so impressive to us is that we've been working with the Pointnext team to come in and actually configure this for our environment. Everybody uses a high-performance compute environment, but nobody's is exactly the same. The configure ability of this and the customability of this to our environment has been critical, and we've seen incredible benefits from that. >> So Ric, we kind of pushed you in theCUBE last year, cause you were saying "there's nothing like this in the marketplace". We said, okay define what's different. (John laughs) One of the things you touched on was the fluid pools of infrastructure. >> Yes. >> And Kate, what you just described is bringing technology to different digital teams. >> The dynamicism if you will. >> Absolutely. >> Being able to dynamically configure the thing, yes. >> So, let's test it. I mean, it sounds like that's exactly what you're doing, and how is this different than the infrastructure that you used to have? >> So, the reason that it's different is that we've got, we've got a simply said, a single infrastructure. We've got a compute farm, we've got storage, and historically what we had to do was actually partition off certain pieces of that for certain productions in order to protect their resources. The problem with that is that any given day, particularly in a creative environment, maybe they're using all of it, maybe they need more, maybe they need less. The challenge is is that historically if they needed less we can't reprovision that to another production in order to take advantage of their inspiration and their business motivations. Now we can. Now we have the opportunity to actually have the infrastructure be as dynamic as our creative environment, and that's saying a lot. >> And you can reconfigure those resources three clicks, five minutes, you literally can deprovision -- >> Kate: That's it. >> So the old way they're like bitchin and moanin, where's the servers? >> Absolutely. >> Right. >> And running around scrambling. >> They're on order. (all laugh) >> Six weeks. No this what we're talking about. >> Yeah. >> This is about speed, right? I mean this is -- >> It absolutely is. >> Alright, so I want to ask you a question about the HPE event. You mentioned you're here. So, a lot of people go to these events and they try and extract all the action. You've heard a lot of firsts, last year was Synergy first, big claim there. We're hearing some security stuff with servers here. >> Ric: Yeah. >> As a practitioner that comes to these shows, what's your strategy when you come to an event like HPE Discover, and obviously the schmooze is going on and getting wined and dined by HP, a big customer, but like when you go in there, what are you looking for, how do you connect the dots, what tea leaves do you read, what's your strategy? >> Well, I'll tell you, one of the things that really interests me about Discover is we've got a deep partnership with Hewlett-Packard Enterprise. We're talking to Hewlett-Packard Enterprise all the time. So we might actually think that we know what's going on. It's not true, there's so much innovation happening that when we bring our team to this show, we learn things that could really help our business. I'll give you a great example, so we learned this week about SimpliVity. Now, we had sort of heard about it, but we had not taken our time out of our schedules to really understand how that could help our VM environment. Our team's sitting in one of the panels this week, and he's texting other engineers on our team going "We have got to look at this next week at DreamWorks Animation". That's the kind of environment this is. I'll tell you something else, New Stack, we're going to lean heavy into New Stack because we believe that the innovation that we're seeing in that space is really, finally going to deliver on this promise of cloud that's been out there. >> What specifically about New Stack do you like? I want to just double down on that. Is it the rule of your own, is it the flexibility, what's the big thing there? >> Well, again this is one of those things where our team today is actually writing code and creating architectures that are sort of New Stack-like, but we're having to do it, we're having to invest our own time. It's trial and error, some of the things work some of the things don't, and that time is not being spent focused on our animation productions. The fact of the matter is, here's Hewlett-Packard actually doubling down and making sure that there is going to be a robust solution that works, that we can bring into our environment. >> We're in enterprises across the world every day. We're having these conversations, and most enterprises are doing kind of a roll-your-own cloud kind've thing. >> That's right. >> They're playing with OpenStack, they're playing with Kubernetes, they're playing with all these tools, they got a bunch of custom code, but we're really what we're trying to do with New Stack is take the best of what they're all trying to do, constrain that down, take our standard Software Defined infrastructure as the base, put a stack on top of that that they can count on to do a private cloud with bridge-to-hybrid capabilities, that's standard, that ships, that delivers and has updates, so that they're not messing around with it. Their developers don't want to spend time doing that, they just want to have a private cloud installation that has hybrid capabilites and have it installed. >> This is super relevant, this is super relevant, and we call you a tech athlete because you want to go out there and deliver value to your group and actually build products, right? >> That's right. >> The film. But Dave's team just put out the True Private Cloud Report which shows on PRAM, cloud-like environment, $260 billion dollar TAM, but the notable thing is that the labor costs were non-differentiated spend is going up by a $150 billion shifting in 10 years. >> Yeah. >> That's exactly the point here that you're talking about, is my guy's aren't working on the product that they need to be building. They're doing the R&D, so the OpenStack and all these things you're talking about, they're doing the R&D. Here, you're doing the R&D, delivering the product to the customer. >> Well and when we deliver that, we're still going to leverage all of those technologies. OpenStack is a key part of New Stack. Kubernetes is a key part of New Stack, but what we're doing is pulling that together so that they don't have to curate their own private cloud. >> Kate: That's right. >> We create that, deliver it in a way that's an appliance-like way, just like we deliver Hyper Converged today, in a controlled plane that manages that hybrid IT estate and gives them visibility into public cloud uses and private cloud, and it's really going to help them a lot, and it's going to help a whole lot of other customers cause we're making it standard and easily deployable. >> Well, we've seen this story unfold over this decade, where the corner office has said I don't want to spend money on that caching and provisioning. Okay, so go to the cloud. And then IT said, well, eh, we can't do that. (laughs) Okay, and so they get in with Hewlett-Packard Enterprise and others say what's the answer? Okay, but what you've described is this horizontal infrastructure capability that you can throw any workload at. >> That's right. >> And so my question is, what does it mean for the business? Does it mean you can do things faster, you have happier animators, you can do more movies, what does it mean? >> I think it means a couple of things. First of all, opportunity cost. In our business, a new opportunity for a creative endeavor, that comes up all the time, and the key is is that you want to be able to explore that as quickly as possible. Creative ideas work out sometimes, sometimes they don't, but they key is is that if takes you time and effort and money to just explore it, you've got an opportunity cost you don't want. >> Yeah, yep. >> Something like Synergy will allow us to provision resources to new ideas and new potentials quickly enough, easily enough, and at a cost-effective measure, so that we can actually determine which creative endeavors are going to work more quickly in our environment. That's a huge deal. >> So you were missing opportunities because of the infrastructure limitations, is that right? >> That's -- >> The mockups and everything have to get done. >> That's right! >> All the CG work. >> Again, when our filmmakers have a new idea for a new sequence, a new character, those types of characters, they take tremendous amounts of resources. I often talk about the dragon in Shrek. Back in 2001 we released Shrek, and it had this beautiful, huge pink dragon in it. And she was fantastic, but frankly she was so complex and so computationally heavy, we actually had to cut her out of parts of the film because we couldn't produce the shots she was in. Fast forward a few years, and we decide to make a movie called How to Train Your Dragon that's nothing but dragons. The key is is that we never want to be in a position again where we're tabling a great creative idea because we can't resource for it. And solutions like SimpliVity and Synergy and particularly where we're going with New Stack and the ability to actually harness the cloud without having to do all the work ourselves, that's going to bring that potential to reality. >> John: And then you know, your application in this opportunity cost is for your business. Other companies have apps, right? So their opportunity costs are very similar. >> That's right. >> John: This is the classic how shadow IT was born. >> Oh, yes! >> And people want to experiment, show proof of concept. Not a PowerPoint, an actual demo of real working product. It may not have the scale there, but you get to that point of where it's workable. >> Look, every business is facing some element of this right now, and I will tell you the other reason of the two reasons that I think that this is going to make a difference. It's future-proofing our environment. >> Ric: Yeah. >> The world is so dynamic right now, things are changing so quickly. Even in our environment with media and entertainment, the world of what people want to consume and how they want to consume it and the nature of how we're looking at innovation in both filmmaking techniques, as well as new media opportunities, the key in all of that is is that we have to be dynamic in order to be future-proofed. These types of solutions give us the confidence that we're actually putting the money in the right place. It's an investment in our future. >> Earlier you mentioned Pointnext services, and the narrative from Hewlett-Packard Enterprise is my inference is it's more cloud-like. Do different types of business models. Are you seeing that? I mean, is it more than just a new name, a new brand, are you starting to see an evolution of the way in which you engage with Hewlett-Packard services? >> We absolutely are, and it's one thing to talk about strategy, but at the end of the day, you don't call up your technology and have a conversation with it, you call up people. And what we're seeing is that Hewlett-Packard Enterprise is investing in a level of expertise within the Pointnext services organization that is unparalleled. That is a massive change over the course of the last five, six, 10 years. These folks are coming into our environment now and we're finding that we are inspired by their strategies. We're not having to teach them about our business, they're actually coming in with all of these other learnings that they've gotten from all of these corporations and they're looking at our ambitions and going hey, we think we've got some ideas here. I'll tell you, our engineers are hard to impress. >> That's the truth. >> They are used to, what was your phrase, rolling it on their own. >> Yeah. >> They are used to being responsible, and they have very little tolerance for actually giving other people time within our organization. Pointnext has blown them away. We could not be doing the work that we're doing on Synergy as quickly and as effectively, installation and strategy around that without the Pointnext team. >> Well, that's the proof, that is the proof in the pudding in my opinion when your people who are, I won't say cocky, but they're kind of, sounds like they're pretty cocky. (laughs) >> Ric: Confident. >> But that you're in a, you're in media entertainment. It is one of the most disruptive, being disrupted markets right now. Smart Cities, IoT, media entertainment it's, you're the leading trend in IT right now, media entertainment. >> And in our team, there's simply no tolerance at DreamWorks Animation for technology getting in the way of the business. The fact of the matter is technology always has to be enabling the storytellers, enabling the filmmakers, enabling the business and ambition. And the key is is that our engineering team, they feel responsible to that. One of the things that we're finding with the new Hewlett-Packard Enterprise, the Pointnext team, Ric's team with the Synergy deployments, is that we actually feel like we've got a partner that can up our own game. >> John: Good. >> And we do deep beta programs with them on everything that we're doing to make sure that we're meeting that next generation of what they need. It's a fantastic partnership. >> Well Ric, congratulations on the success, and Kate thanks for sharing all the great stories and your experience DreamWorks Animation. Great to see that trend, again media entertainment, you guys are doing great stuff. We're doing our share with digital TV here, we're not a, we live on the edge of the network with theCUBE here at HP Discover. With DreamWorks Animation, I'm John Furrier, Dave Vellante, stay with us for more day three coverage here in Las Vegas at HP Discover. We'll be right back. (tech music)

(electronic music) >> Announcer: Live from Austin, Texas, it's The Cube. Covering South By Southwest 2017. Brought to you by Intel. Now, here's John Furrier. >> Hey, welcome back, everyone, we're here live in Austin, Texas, for South By Southwest Cube coverage at the Intel AI Lounge, #IntelAI if you're watching, put it out on Twitter. I'm John Furrier of Silicon Angle for the Cube. Our next guest is Alison Yu who's with Cloudera. And in the news today, although they won't comment on it. It's great to see you, social media manager at Cloudera. >> Yes, it's nice to see you as well. >> Great to see you. So, Cloudera has a strategic relationship with Intel. You guys have a strategic investment, Intel, and you guys partner up, so it's well-known in the industry. But what's going on here is interesting, AI for social good is our theme. >> Alison: Yes. >> Cloudera has always been a pay-it-forward company. And I've known the founders, Mike Olson and Amr Awadallah. >> Really all about the community and paying it forward. So Alison, talk about what you guys are working on. Because you're involved in a panel, but also Cloudera Cares. And you guys have teamed up with Thorn, doing some interesting things. >> Alison: Yeah (laughing). >> Take it away! >> Sure, thanks. Thanks for the great intro. So I'll give you a little bit of a brief introduction to Cloudera Cares. Cloudera Cares was founded roughly about three years ago. It was really an employee-driven and -led effort. I kind of stepped into the role and ended up being a little bit more of the leader just by the way it worked out. So we've really gone from, going from, you know, we're just doing soup kitchens and everything else, to strategic partnerships, donating software, professional service hours, things along those lines. >> Which has been very exciting to see our nonprofit partnerships grow in that way. So it really went from almost grass-root efforts to an organized organization now. And we start stepping up our strategic partnerships about a year and a half ago. We started with DataKind, is our initial one. About two years ago, we initiated that. Then we a year ago, about in September, we finalized our donation of an enterprise data hub to Thorn, which if you're not aware of they're all about using technology and innovation to stop child-trafficking. So last year, around September or so, we announced the partnership and we donated professional service hours. And then in October, we went with them to Grace Hopper, which is obviously the largest Women in Tech Conference in North America. And we hosted a hackathon and we helped mentor women entering into the tech workforce, and trying to come up with some really cool innovative solutions for them to track and see what's going on with the dark web, so we had quite a few interesting ideas coming out of that. >> Okay, awesome. We had Frederico Gomez Suarez on, who was the technical advisor. >> Alison: Yeah. >> A Microsoft employee, but he's volunteering at Thorn, and this is interesting because this is not just donating to the soup kitchens and what not. >> Alison: Yeah. >> You're starting to see a community approach to philanthropy that's coding RENN. >> Yeah. >> Hackathons turning into community galvanizing communities, and actually taking it to the next level. >> Yeah. So, I think one of the things we realize is tech, while it's so great, we have actually introduced a lot of new problems. So, I don't know if everyone's aware, but in the '80s and '90s, child exploitation had almost completely died. They had almost resolved the issue. With the introduction of technology and the Internet, it opened up a lot more ways for people to go ahead and exploit children, arrange things, in the dark web. So we're trying to figure out a way to use technology to combat a problem that technology kind of created as well, but not only solving it, but rescuing people. >> It's a classic security problem, the surface area has increased for this kind of thing. But big data, which is where you guys were founded on in the cloud era that we live in. >> Alison: Yeah. >> Pun intended. (laughing) Using the machine learning now you start with some scale now involved. >> Yes, exactly, and that's what we're really hoping, so we're partnering with Intel in the National Center of Missing Exploited Children. We're actually kicking off a virtual hackathon tomorrow, and our hope is we can figure out some different innovative ways that AI can be applied to scraping data and finding children. A lot of times we'll see there's not a lot of clues, but for example, if we can upload, if there can be a tool that can upload three or four different angles of a child's face when they go missing, maybe what happens is someone posts a picture on Instagram or Twitter that has a geo tag and this kid is in the background. That would be an amazing way of using AI and machine learning-- >> Yeah. >> Alison: To find a child, right. >> Well, I'll give you guy a plug for Cloudera. And I'll reference Dr. Naveen Rao, who's the GM of Intel's AI group, was on earlier. And he was talking about how there's a lot of storage available, not a lot of compute. Now, Cloudera, you guys have really pioneered the data lake, data hub concept where storage is critical. >> Yeah. >> Now, you got this compute power and machine learning, that's kind of where it comes together. Did I get that right? >> Yeah, and I think it's great that with the partnership with Intel we're able to integrate our technology directly into the hardware, which makes it so much more efficient. You're able to compute massive amounts of data in a very short amount of time, and really come up with real results. And with this partnership, specifically with Thorn and NCMEC, we're seeing that it's real impact for thousands of people last year, I think. In the 2016 impact report, Thorn said they identified over 6,000 trafficking victims, of which over 2,000 were children. Right, so that tool that they use is actually built on Cloudera. So, it's great seeing our technology put into place. >> Yeah, that's awesome. I was talking to an Intel person the other day, they have 72 cores now on a processor, on the high-end Xeons. Let's get down to some other things that you're working on. What are you doing here at the show? Do you have things that you're doing? You have a panel? >> Yeah, so at the show, at South by Southwest, we're kicking off a virtual hackathon tomorrow at our Austin offices for South by Southwest. Everyone's welcome to come. I just did the liquor order, so yes, everyone please come. (laughing) >> You just came from Austin's office, you're just coming there. >> Yeah, exactly. So we've-- >> Unlimited Red Bull, pizza, food. (laughing) >> Well, we'll be doing lots and lots tomorrow, but we're kicking that off, we have representatives from Thorn, NCMEC, Google, Intel, all on site to answer questions. That's kind of our kickoff of this month-long virtual hackathon. You don't need to be in Austin to participate, but that is one of the things that we are kicking off. >> And then on Sunday, actually here at the Intel AI Lounge we're doing a panel on AI for Good, and using artificial intelligence to solve problems. >> And we'll be broadcasting that live here on The Cube. So, folks, SiliconAngle.tv will carry that. Alison, talk about the trend that, you weren't here when we were talking about how there's now a new counterculture developing in a good way around community and social change. How real is the trend that you're starting to see these hackathons evolve from what used to be recruiting sessions to people just jamming together to meet each other. Now, you're starting to see the next level of formation where people are organizing collectively-- >> Yeah. >> To impact real issues. >> Yeah. >> Is this a real trend or where is that trend, can you speak to that? >> Sure, so from what I've seen from the hackathons what we've been seeing before was it's very company-specific. Only one company wanted to do it, and they would kind of silo themselves, right? Now, we're kind of seeing this coming together of companies that are generally competitors, but they see a great social cause and they decide that they want to band together, regardless of their differences in technology, product, et cetera, for a common good. And, so. >> Like a Thorn. >> For Thorn, you'll see a lot of competitors, so you'll see Facebook and Twitter or Google and Amazon, right? >> John: Yeah. >> And we'll see all these different competitors come together, lend their workforce to us, and have them code for one great project. >> So, you see it as a real trend. >> I do see it as a trend. I saw Thorn last year did a great one with Facebook and on-site with Facebook. This year as we started to introduce this hackathon, we decided that we wanted to do a hackathon series versus just a one-off hackathon. So we're seeing people being able to share code, contribute, work on top of other code, right, and it's very much a sharing community, so we're very excited for that. >> All right, so I got to ask you what's they culture like at Cloudera these days, as you guys prepare to go public? What's the vibe internally of the company, obviously Mike Olson, the founder, is still around, Amr's around. You guys have been growing really fast. Got your new space. What's the vibe like in Cloudera now? >> Honestly, the culture at Cloudera hasn't really changed. So, when I joined three years ago we were much smaller than we are now. But I think one thing that we're really excited about is everyone's still so collaborative, and everyone makes sure to help one another out. So, I think our common goal is really more along the lines of we're one team, and let's put out the best product we can. >> Awesome. So, what's South by Southwest mean to you this year? If you had to kind of zoom out and say, okay. What's the theme? We heard Robert Scoble earlier say it's a VR theme. We hear at Intel it's AI. So, there's a plethora of different touchpoints here. What do you see? >> Yeah, so I actually went to the opening keynote this morning, which was great. There was an introduction, and then I don't know if you realized, but Cory Booker was on as well, which is great. >> John: Yep. >> But I think a lot of what we had seen was they called out on stage that artificial intelligence is something that will be a trend for the next year. And I think that's very exciting that Intel really hit the nail on the head with the AI Lounge, right? >> Cory Booker, I'm a big fan. He's from my neighborhood, went to the same school I went to, that my family. So in Northern Valley, Old Tappan. Cory, if you're watching, retweet us, hashtag #IntelAI. So AI's there. >> AI is definitely there. >> No doubt, it's on stage. >> Yes, but I think we're also seeing a very large, just community around how can we make our community better versus let's try to go in these different silos, and just be hyper-aware of what's only in front of us, right? So, we're seeing a lot more from the community as well, just being interested in things that are not immediately in front of us, the wider, either nation, global, et cetera. So, I think that's very exciting people are stepping out of just their own little bubbles, right? And looking and having more compassion for other people, and figuring out how they can give back. >> And, of course, open source at the center of all the innovation as always. (laughing) >> I would like to think so, right? >> It is! I would testify. Machine learning is just a great example, how that's now going up into the cloud. We started to see that really being part of all the apps coming out, which is great because you guys are in the big data business. >> Alison: Yeah. >> Okay, Alison, thanks so much for taking the time. Real quick plug for your panel on Sunday here. >> Yeah. >> What are you going to talk about? >> So we're going to be talking a lot about AI for good. We're really going to be talking about the NCMEC, Thorn, Google, Intel, Cloudera partnership. How we've been able to do that, and a lot of what we're going to also concentrate on is how the everyday tech worker can really get involved and give back and contribute. I think there is generally a misconception of if there's not a program at my company, how do I give back? >> John: Yeah. >> And I think Cloudera's a shining example of how a few employees can really enact a lot of change. We went from grassroots, just a few employees, to a global program pretty quickly, so. >> And it's organically grown, which is the formula for success versus some sort of structured company program (laughing). >> Exactly, so we definitely gone from soup kitchen to strategic partnerships, and being able to donate our own time, our engineers' times, and obviously our software, so. >> Thanks for taking the time to come on our Cube. It's getting crowded in here. It's rocking the house, the house is rocking here at the Intel AI Lounge. If you're watching, check out the hashtag #IntelAI or South by Southwest. I'm John Furrie. I'll be back with more after this short break. (electronic music)

live from San Francisco California it's the queue at vmworld 2014 brought to you by vmware cisco EMC HP and nutanix now here are your hosts John furrier and Stu minimum okay welcome back around here live in San Francisco for VMware 2014 this is our fifth year with the cube extracting the city from the noise at vmworld always a pleasure and we have the chief marketing officer Robin Matlock here inside the queue of my Coast stupid minute for this segment Robin welcome back to the cube thank you great keynote this morning you opened it up in front of a packed house for Pat Gelsinger and delivered an amazing keynote before we get some icky knows what some of the stats with the show here obviously vmworld it just keeps getting bigger and bigger and bigger every year well you know it's amazing the energy is fantastic here this year we're going strong we have well over twenty two thousand attendees the solutions exchange is packed there's about 250 companies that are they're exhibiting we have all kinds of breakout sessions and content I mean if you just walk around here the energy is just really thrive and the theme is no limit so I got to get some a back story on the theme I'll see no limits breaking through this is the transformation market the sign is just break it was a quick taste of wow how this all came together yeah what's the meaning behind the pictures are they're all on the hall you know it's really fun the themes that every year actually put just tremendous effort into them they can really be stressful but at the end when you land or right when it feels so good this whole notion of concrete you know in breaking through and that there's something on the other side that is truly infinite for us that just really spoke to our business it spoke to what our customers are going through and it truly spoke to the potential of this incredible you know this incredible industry you know i was when i think of the No Limits I think about the space jump the Red Bull I think about some of the things with it within the cloud that developers are doing you know Pat mentioned uber they have no asses of mass evaluation of hurts and to cumbies combined this is the kind of dream that entrepreneurs think about is like this is this inflection point stuff right so is that was that some of the vibe you guys were thinking absolutely and I think when we look at where we are in our journey relative to cloud relative to a software-defined world we're really passionate that you know the customers and the attendees of this conference are very well positioned to truly break through some of the silos that have been holding us back for a long time and we are at Crossroads um you know we believe vehemently that the data center is destined to be software-defined and that many of these attendees are well positioned to take us on that journey so I got to ask you because I see you're involved in the brain trust and all the formulation of the strategy the company and out of how to communicate it's always a challenge when it's like a moving train of innovation but you have some new things going on this year first of all nothing new on strategy it's the same marching orders with with Pats cadence hybrid cloud you know March to that cadence ops ii server defined data center but now AirWatch comes on over the top how did that affect things for you or did it it's just more of more the same so actually they bring in there some of that security and the apps piece of the business did that change some of the thinking and all I know it's an interesting question but I think at the end of the day the three strategic priorities for VMware have been very consistent now for multiple years you know largely under Pat's leadership it's about a software-defined world that's the software-defined data center it's about extending that to the hybrid cloud and it's always been about end-user computing I think the air watch acquisition just took it up a couple notches really the world of mobility we're big advocates and believers that the mobile workforce is exploding but there's a really strong connective value between what's happening at the infrastructure layer and what we can do to enable that mobile workforce so I think it was very consistent with the strategy but I do think the air guac acquisition is changing the game it's certainly producing Pat was giving us a little taste on the cube talk about the steams of the show today we had Pat had bill father's Carl up sure do a little Q&A a little little cube action almost on stage with Bill and what's what's tomorrow did you guys bring it up by thieves share with the folks out here Shey lay the land here what's the what's the contracts for tomorrow so today what we try to do is really telex the expanse of entire story what's going on holistically and you know the Karl part of it was a lot about getting our customers to really talk about what's working for them I think that's really important because we laid out a vision for VMware um you know a couple years ago and it's important to make that tangible and real and I hope the customers were able to bring that to life for people tomorrow is all about the technical under the hood let's get you know inside and really understand how the technologies are delivering against that vision and we're going to go through the whole thing it's going to cover the infrastructure it's going to talk about the hybrid cloud and we're going to talk a lot about mobility well the geeks want under the hood I mean it gets a gig show the end of the day it's very content rich at vmworld as we know it super busy a lot of parties going off as Deb going on certainly the business transactions are happening but it's still a geek show you guys have preserved that here right you know if we ask ourselves every year you know how how and should or shouldn't we evolve vmworld and i tell you we're really resolved at the end of the day this is largely a practitioner show they come for technological information education certifications and we have no desire to take a square pose and put in a round hole I mean it works so well for this audience let's just give this crowd what they need and I want to do more of it year after year yeah and we can always tell how good the conferences are in terms of content based upon how much Twitter activity there is in terms of like if people are just talking a lot on Twitter and not say anything that means it's kind of a boring show when there's not a lot of Twitter activity mostly it's text sessions people have too busy running around between between the events I mean are you guys seeing the sessions packet but we haven't had a chance to go out there what's happening yeah well to be really honest I haven't at a moment to scan too much but from what I'm hearing they are overflowing and frankly they were booked you know even before we showed up today because we do give people the schedule builder and a chance to book their sessions so I know that they are all full we're doing repeats we're trying to get you know more breakouts so people can deal with Wednesday and Thursday as things settle down but all the reports I'm getting so far is that we are pretty much over sold and oversubscribed yeah so buds do you Robin I was just gonna say you know is my fifth year now coming to vmworld it's all we impressive just the passion of the people in the virtualization community it's such a good community everybody gives back I really like what you guys did with the charity event that's going I mean what's a destination give by 25,000 with 250 oh not twenty five thousand two hundred and hundred and fifty thousand dollars that that's fantastic you know I got to talk to the hands-on lab guys today and things were running so smooth and so many people do it because as John said the geeks really love to geek out here I noticed it looked like on the badge it had you know the show spread out beyond just the north south and the West you brought the analysts kind of off to off to a hotel because they don't need to be in the center of all the geeks and everything the show floor is cranking as usual so you know it sounds like you still have the core and just pieces add on to it yeah i mean the core of the program if you were to look at breakout sessions keynotes labs that's going to stay right here in moscone but the reality is we're bursting out of the scenes and we love San Francisco we loved the venue but we have to take advantage of all the hotel space around so we got things at the w we got things at the westin we got things at the marriott we got things at the Intercontinental I mean we're or everywhere frankly but you're right we are having to kind of spread out a little bit so I got to ask you about the 10-year anniversary because that was a pretty epic event and you mentioned you made a comment on stage where'd that world go and i love the Golden Gate Bridge metaphor you put together what's changed for you over the past year it seems to be like it seems like seven years ago internet years it seems like a decade ago almost from last year yeah a lots changed and you share your perspective yeah I think a lot has changed I think on though um to be almost all for the good in my view I think you know VMware had built such a business on kind of one core platform which was compute virtualization and over the last several years we've really broadened our wings right and we are now dealing with networking and storage and security and automation and cloud and mobility and I think the diversity that that brings um from a customer perspective from an ecosystem perspective from our routes to market perspective I mean certainly it is definitely a charge because there's just so much tremendous diversity it also means we got a lot of things to cover so you know I think with that comes a responsibility to make sure our customers can understand all these different diverse you know offerings what's your objective for the show what's your preferred outcomes you can look back and just fast forward to thursday evening friday morning you know you're in a hot tub relaxing maybe it's saturday or monday morning what do you want to have happen what's your ideal outcome for vmworld beyond the fact that i like my feet attached to my body because right now i'm afraid they might fall off but let's say personal attributes aside you know i really hope that these attendees you know 22,000 plus people get on those airplanes fly home and feel like they had one of the most invigorating educational inspirational experiences professionally that they're going to have all year I hope that they got to the content that was relevant for them that they were able to navigate and you know really spend time in the areas of focus for them and I hope that people met dozens and dozens of new people that will only help them broaden their career so I have this little prop I brought because I was attended the VIP event you guys had an amazing event mark injuries since the NBC was broadcasting there Joe Tucci was there and then you know opening up your new facility which could have been around for a while so we've got some new new areas got these hot pens there so I'm going to ask you about the culture and the brand future brand for vmware I mean it's an amazing campus eco-friendly beautiful design high quality is this the brand of VMware that you seeing vision for me and you what's your vision for the brand I mean it's evolving in in real time for the company it is evolving but at the same time I think our brand and what we stand for as a company is also very stable it's great that you came to that event and saw the final unveiling of the last building as we finished it up and certainly it's a beautiful campus and it's green you know it's very you know natural woods and doing all kinds of things to protect the environment I think at the core of VMware there's you know five key values and those values are sustaining the test of time you know it's about innovation it's about community it's about people it's about integrity and it's about our customers and I think really no matter what products and services and solutions we wrap around our company I think we still stand for the same core values and I hope that never changes so I got to ask you out the community I think it's one of those things and you know something to pat about how doctor is implemented community aspect of the open source of their product and made them success you guys have had great community over the years really part of the backbone of vmware versus other companies some don't even have a heartbeat to a community you guys have a great thriving ecosystem how do you maintain that as we get more connected with the crowdsourcing with the Twitter expansion and all the people talking and it's not just forums anymore it's and more it's it's it's a virtual event every day it's like vmworld every day out there how do you handle that what's your vision and how you going to get your arms around that going forward well it's yeah I think it's really critical first of all just like anything whether you're talking about technologies you're talking about engaging with customers you have to evolve you can't use the same techniques that you use last year really to propel you next year so I think it's all about making sure you understand how our customers choosing to engage and then embrace that for us our social channels are really important our communities are really important and we're all about enabling facilitation and engagement and I think we're really that's kind of philosophically how we go about our whole social strategy it's all about enablement so that's a personal question for you to you always loved your eye for you know detail remember the first VMware we did you had pointed out the vmware stickers which ended up being perfect camera location ibly I like her I like this Robin woman she's awesome but what are you excited about now I mean what are you personally motivated upon right now what gets you really excited about the tech industry about what you what you're involved in what's the what's the one thing that get you so excited you know frankly I'm extremely proud to be the CMO of VMware I think there was a great company and I think we're part of something truly meaningful I think there was a time when maybe we weren't going to be as relevant we and by we I don't mean to see him or I mean this this whole thing that maybe we weren't going to be as relevant in the next decade but we collectively as a mystery are making bold moves we're doubling down on software we're pushing the boundaries of the data center we're getting out beyond compute we're going to storage or going to networking we're looking at security we're layering in automation and I think we are really securing our future as an industry that we are relevant and we need a seat at the table a strategic seat at the table and I'm thrilled to be a part and you certainly the global footprint the virtualization has been a great part of enabling that that mindset great to have you on the cube any other tidbits about the show you'd like to share the folks you know I think the main thing is just get involved and try some things that are different push your own personal boundaries explore there's so much content there's so many networking opportunities there's breakouts and I think definitely sampling a little bit of everything and making sure that you go home exhausted and then I'll be happy but certainly is exhausting show but Pat brought up the whole brave concept that's really about bold moves writing that's about that's kind of the whole theme here right yeah I think you know the notion of bravery is in the sense that given that things are changing so rapidly and the world is so dynamic and fluid as a business climate it's going to take some calculated risk you're going to have to really decide where are you partnering where are you betting what kind of steps are you going to take and I think action is key and the one thing it probably isn't going to work is status quo Robin Matlock the chief marketing officer for VMware keynote speech this morning set the table for Pat Gelsinger great jobs at the big picture laid out everything out the holistic vision of VMware continues to thrive thanks for coming down the cube always great to have you it's the Cubist retin from the noise we'll be right back with our next guest after the short break great thanks John you