>>Hey everyone. Welcome back to Miami, Miami Beach. Specifically, not a bad location to have a conference. Lisa Martin here with the Cube live at IFS Unleashed. We're gonna be having a great conversation next about Ization moments of Service Rules. Royces here, as is the C of IFS for aerospace and defense. Scott Camani. Nick Ward joins us as well, the VP of Digital Systems at Roll Royce. Guys, excited to have you on the program and welcome back. >>Thank you very much. Nice to be back. It's >>Been three years since the last IFS show. I love How's Scott? I was talking with Darren Roots earlier today and I said, Well, didn't it used to be IFS world? And he said, Yes. And I said, I love the name. I would love to, to unpack that with your cheek marketing officer because it, there's a lot of, of, of power behind Unleash. A lot of companies do such and such world or accelerate, but we're talking about unleashing the power of the technology to help customers deliver those moments of service. Yes. Love it. So Scott, start us off here. Talk about ization. That's a relatively new term to me. Sure. Help me understand what it means, because IFS is a pioneer in this sense. >>We are. So one of the things that IFS is always trying to do is to try to find a way to help our customers to realize a moment of service. And that moment of service is really when they found the ability to delight their customers. And when we look at the way in which we're trying to drive those business outcomes for our customers, ization seems to be at the core of it. So whether it's the ability for a company to use a product, a service, or an outcome, they're driving ization in a way where they're shaping their business. They're orchestrating their customers and their people and their assets behind a val value chain that helps them to provide a delightful experience for their customers. And with IFS being focused on Lifecycle asset management, we no longer have customers that have to choose from best of suite or best of breed. They can actually have both with ifs. And that's something we're really excited to provide to our customers and more excited for our customers to realize that value with their customers, their partners. Along the way. >>You, you mentioned customer delight and it's a term that we, we all use it, right? But there's so much power and, and capabilities and metrics behind that phrase, customer delight, which will unpack Nick bringing you into the conversation. Talk to us a little bit about what your role is at Rolls Royce. My first thought when I saw you was, oh, the fancy cars, but we're talking about aerospace and the fence, so give us a little bit of a history. >>Okay. So yes, we don't make cars is the first point. So we are, we are power, we do power as a service. So we are most well known, I guess for large aircraft airliners. You know, if you've, if you've flown here to Miami, there's probably a 50 50 chance you've flown on a Rod Roy powered aircraft. Our market segment is what we call wide bodied aircraft where you go on, there's two aisles. So the larger section of the market, and we, we provide power, so we provide the engines, but more importantly, we've been a ization company, a service company for at least two decades. We, we have a, a service relationship we call total care. And the whole idea of total care is, yes, I have my engine, it's on my aircraft, but I take care of it. I make sure it's available to fly when you need to fly it. And all of the things that have to come together to make that happen, it's a service company. >>Service company. Talk to me a little bit about, and I wanna get got your perspective as well, but the relationship that Roll Royce and IFS have this is a little bit unique. >>Well, I can start, but I I think Nick's gonna be better served to tell us about that as our customer. Nick and I actually started this journey about four years ago, and what we did was, is we were working closely with our perspective customer Rolls-Royce identified what they were looking for as a desired business outcome. And then we found a way through the technology and the software that we provide to all of our enterprise customers globally to find a solution that actually helped to provide a, an outcome not only to Rolls-Royce, but also to our collective downstream customers, commercial operators around the globe. So that's where we started the journey and we're continuing our discussions around other solutions, but that's how we started and it's been an incredible partnership. We're so happy and proud to have Nick as a customer and a advocate of all things ifs and I'll let him kind of continue from his point of view how he sees the partnership in the relationship. >>No, thank you Scott. I think we've, we've always, we've valued the kind of relationship that we have because I think IFS has always got Rolls Royce in terms of strategic direction. What do we try to do? I said, we're a service company. You know, we, we are, we have to have a service relationship with our, our customers, our airlines. To have a service relationship, you have to be able to connect to your service customer. And ifs is a big part of how we connect for data. That's how do we understand what the airline is doing with the engines, but it's also how we return data back into the airline. So we are, we're get a very close integrated relation between us, our airlines, through a bridge that, that ifs create through the maintenance product. Got it. So it works really well. >>I I think I'd make one other point. One of the things that we've always focused on is quantifiable business value. The only way a partnership like this could possibly work is if we have a desired business outcome, but if we're providing value, So the value work that we did in conjunction with Rolls Royce and really identifying that helped to support the business case that allowed this partnership to really begin and flourish. So I I, I'd be remiss if I didn't mention that business value element that's really core to everything we do and all the, the conversations that Nick and I have. >>Well, it's all about outcomes. Absolutely. It's all about outcomes. It >>Is, it has to be about, it's about moments of service, right? That's why we're here, right? So perhaps a moment of service for Robs Royce is every time you're a passenger, you're going through the terminal. You expect your aircraft to be there, ready, waiting for you to get on and depart on time. And our moment of service is every aircraft takes off on time, every time we live. When we die by the quality of that statement, how well we live up to that statement, I think I checked this morning, there's something alike, 600 aircraft in the sky right now with Rolls Royce power carrying passengers. All of those passengers have relied on that moment. Service happening regularly like clockwork. Every single time you don't get any forgiveness for a delay, you get very little forgiveness for a cancellation that has to happen. And then so many things have to come together for that to happen. >>Those 600 aircraft, that's maybe 200,000 people right now in the sky, Wow. Those 200,000 people are trying to connect, They're trying to connect with friends, they're trying to connect with loved ones, family, colleagues, whatever the purpose is of that trip. It's really important to them. And we just have to make sure that that happens for us. We've had something like a million flights so far this year, 300 million people relying on that moment of so is happening. So I really resonate with, with the language that Scott users about the importance of sort of that focal point on when does it all come together? It comes together when as a passenger, I get on the plane and it goes and I get no issues. >>Right. Well people don't tolerate fragmented experiences anymore. No, no. I think one of the things that was in short supply during the pandemic was patience and tolerance. Sure. Not sure how much of that's gonna come back, right? But those integrated connected experiences, as you described so eloquently, Nick, those are table stakes for the customers, but also the brands behind them because of customers are unhappy, the churn rates go way up. And you see that reflected in obviously the success of the business and what you guys are doing together is seems to be quite powerful. Now then when you were on the cube with us three years ago in Boston at IFS back then you first introduced the intelligent engine and the Blue Data thread. Let's talk about the intelligent engine. Just give our audience a refresher of what that actually entails. >>So perhaps if we just step one one step back for that, just to understand how this fits in. So Roro is a service organization. We talked about that. What that means is we take a lot of the, the risk and the uncertainty away from our airline customers on the availability, the costs and maintenance effort associated with having a, having a chat engine. These are incredibly complicated and complex and sophisticated pieces of equipment. The most expensive, most sophisticated pieces of an aircraft. Managing that is, is difficult. And every airline does not want to have to focus on that. They wanna focus on being able to get the passenger on the air after, fly it, look after the airframe. So our role in that is to take that risk away, is to manage those engines, look after their health, look after their life, make sure they're available to fly whenever they need to fly. >>So for us to understand that, we then have to have data, we have to understand the state of every engine, where it is, the health of the engine, the life of that engine, what do we need to do next to that engine? And we can't do that unless we have data and that data flows into a digital platform. The intelligent engine, which is our cloud based ai, big data, all of the iot, all of the big buzzwords are there, right? So the data flows into that, that lets us run the models. It lets us understand, I can see something maybe it's a, it's a small issue, but if I leave it alone, it become a bigger issue. And maybe that will cause disruption further down the line. So we need to understand that we need to preempt it. So preemptive predictive maintenance is a, is a big part of the intelligent engine, but it's more than just that. >>It's also, we can understand how that engine is being flown. We can understand is it having a really intense flight? Is it having a more benign, gentle flight? Wow. That change time after the flight, typically after the flight. But what that means is we can then understand, actually we can keep that engine on the wing longer then you might otherwise have to do, If you have no data, you have to be conservative, safety rules, everything. Sure. So data allows you to say, actually I'm being overly conservative in this space. I can get more flying bios, flying hours from my product by extending the interval between maintenance and the intelligent engine has a large part to play in us justifying that we're able to do that. And then the final part that it does is eventually the engine is gonna have to come off from maintenance. >>These things fly 5 million miles between overhauls. You imagine you try to do that in your family car. It's, it doesn't happen. It's incredibly sophisticated thing can fly 5 million miles and then we take it off for a major overhaul. But there are thousands of these engines in the fleet. We have to understand which engine is going to come off when for what reason, and prepare our maintenance network to then receive the engine and deal with it and get it back to the customer. So the intelligent engine has a massive part to play in understanding the maintenance demand that the flying fleet is then creating. >>Wow, that's fascinating. And so you talked about that three years ago. What's next for that? I imagine there's only more evolution that's gonna happen. >>It keeps growing. It keeps growing. It's driven by the data. The more data we have, the more that we can do with that. I think as well that, you know, one of the big places that we've we've gone is you can do as much predictive analytics as you, like, there's a lot of people we'll talk about doing predictive analytics, but if you don't do the hard yards of turning predictive analytics into outcome Yeah. Then what did you get? You, you got a bit of smart advice. So we, we take that maintenance demand, we then have to understand how that drives the orchestration and the management of all the parts, the people, the work scope definition, the allocating an engine into a maintenance slot, exactly when it's gonna go. And what are we gonna do to, how do we control and manage our inventory to make sure that engine is gonna go through. >>How do we then actually execute the work inside our, our our overall shops? How do we get that engine back and and integrate our logistics process. So the intelligent engine is, if you like, the shiny front end of a process, it's all the buzzwords, but actually the hard yards behind the scene is just as if not more important to get right. And again, this is why I really like the moment of service concept. Because without that, the moment of service doesn't happen. The engine's not there, the part wasn't there. The field service maintenance guy wasn't there to go fix it. >>And brands are affected >>An, an aircraft on the ground earns no revenue for anybody. No. It's, it's a cost. It's it's a big sink of cost. It >>Is, it is. Absolutely. >>And you're helping aircraft only earn engines only earn when they fly. Yeah, >>Yeah. Absolutely. And what a fascinating, the intelligent engine. Scott, talk a little bit about, we talking about power, we can't not talk about sustainability. Yes, I understand that IFS has a new inaugural awards program that Rolls Roys was a recipient of the Change for Good sustainability awards. Congratulations. Thank you very much. And to Scott, talk to me a little bit about the Change for Good program sustainability program. What types of organizations across the industries of expertise are you looking for and why does Rules ROY really highlight what a winner embodies? >>So since Darren has joined IFS as the ceo, he's had a lot of intentional areas that we focused on. And sustainability has been one that's at the top of the list. IFS has a US ambassador Lewis Pew, who's our Chief Sustainability officer, and he helps us to provide worldwide coverage of the efforts around sustainability. So it's not just about ifss ability to become a more sustainable organization, but it's the solutions that IFS is putting together in the five verticals that we focus on that can help those organizations achieve a level of sustainability for their, for their downstream customers, their partners, and for their enterprises themselves. So when we look at, you know, the social ability for us to be more conscientious about leaving the world a better place or trying to do our best to leave the world not as bad as we came into it, sustainability is a real focus for us. And, you know, the way in which we can support an organization like Rolls Royce and Nickel obviously share those areas of focus from Rolls Royce. It's a perfect fit. And congratulations again for the award. Thank you. We're, we're, we're so excited to, to have shared that with you. We have some other customers that have achieved it across different categories, but it's an area of current and continuous focus for ifs. >>Nick, talk to us, take us out here as our last question is the, the focus on sustainability at Rolls Royce. Talk to us a little bit about that and what some of the major efforts are that you've got underway. >>I think, you know, very similar as, as, as Scott taught there, the focus within Rolls Royce as a strategic group level is really high aviation particularly, I mean we're a, we're an engineering company. We're a power company. Power inherently consumes natural resources. It tends to generate climate affecting outcomes. But at the same time, we are an innovative organization and if anybody's gonna help solve climate challenges, it's gonna be organizations like Rolls Royce who are able to bring different technologies into the market. So we have a responsibility to manage and, and optimize the behavior of our, our existing product suite. But we also have a, a vested interest in trying to move aviation on into the next, the next phase. We talk about sustainable aviation. Aviation has to earn the right to exist. People have choices. We've come out of covid, people are used to doing zoom and not flying. >>People are used to doing things when they don't necessarily get on an aircraft and do something. The aviation business always has to earn the right from the public to exist. And increasingly people will make choices about how they fly when they fly, how far they fly based on the sustainability footprint. So it's really important to us to help both our customers operate the aircraft in as sustainable and climate friendly way as we can. It's really important to find those, those balance points between the cost of an operation and it's the impact of an operation. If you go all over and say, I am going to be net, well, not even net to, but zero carbon by almost inference, that means I'm not gonna operate. You have to operate to get to an outcome. But how do I do that? Why I manage my cost, I manage the, the profitability, the organization doing it, right? >>So it has to be financially sustainable, it has to be sustainable for the people operating within it. It has to be sustainable for the planet, right? So we do that in lots of different ways in small places and, and in big places. So small things we do is we help the operator understand if you change your flight profile, you'll generate fewer emissions. You may avoid controls if you flying a different way, maybe you create trails, you'll lose, you'll lose less fuel while you're doing that. So it's cost effective for you. There was always a balance point there between the wear and tear on the engine versus the, the, the environmental impact. And you find that optimum place. One of the first things we started doing with, with Scott is we have a, a way that we life our engine components. And one of the very simple outcomes of that is using that data, the blue data for connection to the customer. >>If we can see, effectively see inside the engine about how well it's wearing and we can extend those maintenance intervals as we talked about, what that eventually does is it reduces the need to take the engine off, ship it around the world. Probably on a great big 7, 4 7 or maybe year or two ago on an Anson off four big engines flying a long distance trek, shipping our engine to an overhaul facility. We're avoiding something like 200 of those shop visit overhauls a year. So every year that's 200 flights there and back again, which don't happen, right? Collectively that's around about 15,000 automobile equivalent emissions just don't happen. So simple things we can do just starts to have accumulative effect, >>Right? Simple things that you're doing that, that have a huge impact. We could talk for so much longer on stability, I'm sure we're out of time, but I can see why Roll Royce was, was the winner of the Inocular award. Congratulations. Well deserved. Well >>Deserved. I well >>Deserved. So interesting to hear about the intelligent engine. So you're gonna have to come back. Hopefully we'll be here next year and we can hear more of the evolution. Cuz I have a feeling there's never a dual moment in what you're doing. >>It's never a dull moment. There's never an end point. >>No. >>Okay, >>Going Scott, Nick, thank you so much for joining me on the program today. Thank you, Lisa. It's great to have you talk through what's going on at ifx and the partnership with Rolls Royce. We >>Appreciate, and again, Nick, Nick, thank you for your continued support in the partnership. >>I thank you, Scott. We appreciate it. Likewise, thank >>You. Kudos all around. All right, for my guests, I'm Lisa Martin, you're watching a Cube live from Miami. We're at IFS unleashed. We'll be back shortly after a break with our next guests. So stick around.

>> Voiceover: Live, from Las Vegas it's theCUBE Covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. >> We're back at AWS re:Invent, this is theCUBE, the leader in live tech coverage. I'm Dave Vellante with my co-host, Justin Warren. This is day one of AWS re:Invent. Rob Lee is here, he's the Vice President and Chief Architect at Pure Storage. And he's joined by Rob Walters, who is the Vice President, General Manager of Storage as a Service at Pure. Robs, welcome to theCUBE. >> Thanks for having us back. >> Yep, thank you. >> Dave: You're welcome. Rob, we'll start with, Rob Lee we'll start with you. So re:Invent, this is the eighth re:Invent, I think the seventh for theCUBE, what's happened at the show, any key takeaways? >> Yeah, absolutely it's great to be back. We were here last year obviously big launch of cloud data services, so it's great to be back a year in. And just kind of reflect back on how the year's gone for uptick at cloud data services, our native US. And it's been a banner year. So we saw over the last year CloudSnap go GA Cloud Block Store go GA and you know just really good customer uptake, adoption and kind of interest out of the gate. So it's kind of great to be back. Great to kind of share what we've down over the last year as well as just get some feedback and more interest from future customers and prospects as well. >> So Rob W, with your background in the cloud what's you take on this notion of storage as a service? How do you guys think about that and how do you look at that? >> Sure, well this is an ever more increasingly important way to consume storage. I mean we're seeing customers who've been you know got used to the model, the economic model, the as a service model in the cloud, now looking to get those benefits on-prem and in the hybrid cloud too. Which if you know, you look at our portfolio we have both there, as part of the Pure as a service. >> Right okay, and then so Pure Accelerate you guys announced Cloud Block Store. >> Yeah, that's when we took it GA. Right so we've been working with customers in a protracted beta process over the last year to really refine the fit and use cases for tier one block workloads and so we took that GA in Accelerate. >> So this is an interesting, you're a partner obviously with Amazon I would think many parts of Amazon love Cloud Block Store 'cause you're using EC2, you're front-ending S3 like you're helping Amazon sell services and you're delivering a higher level of availability and performance in certain workloads, relative to EVS. So there's probably certain guys at Amazon that aren't so friendly with you. So that's an interesting dynamic, but talk about the positioning of Cloud Block Store. Any sort of updates on uptake? What are customers excited about? What can you share? >> Yeah, no absolutely You know I'd say primarily we're most pleased with the variety of workloads and use cases that customers are bringing us into. I think when we started out on this journey we saw tremendous promise for the technology to really improve the AWS Echo system and customer experience for people that wanted to consume block storage in the cloud. What we learned as we started working with customers is that because of the way we've architected the product brought a lot of the same capabilities we deliver on our flash arrays today into AWS, it's allowed customers to take us into all the same types of workloads that they put flash arrays into. So that's their tier one mission critical environments, their VMware workloads, their Oracle workloads, their SAP workloads. They're also looking at us from everything from to do lift and shift, test and dev in the cloud, as well as DR right, and that again I think speaks to a couple things. It speaks to the durability, the higher level of service that we're able to deliver in AWS, but also the compatibility with which we're able to deliver the same sets of features and have it operate in exactly the same way on-prem and in the cloud. 'Cause look, if you're going to DR the last time, the last point in time you want to discover that there's a caveat, hey this feature doesn't quite work the way you expect is when you have a DR failover. And so the fact that we set out with this mission in mind to create that exact level of sameness, you know it's really paying dividends in the types of use cases that customers are bringing us into. >> So you guys obviously a big partner of VMware, you're done very well in that community. So VMware cloud on AWS, is that a tailwind for you guys or can you take advantage of that at this point? >> Yeah no, so I think the way I look at it is both VMware, Pure, AWS, I think we're all responding to the same market demands and customer needs. Which at the end of the day is, look if I'm an enterprise customer the reality is, I'm going to have some of my workloads running on-premise, I'm going to have some of my workloads running in the cloud, I expect you the vendors to help me manage this diverse, hybrid environment. And what I'd say is, there are puts and takes how the different vendors are going about it but at the end of the day that's the customer need. And so you know we're going about this through a very targeted storage-centric approach because that's where we provide service today. You know and you see VMware going after it from the kind of application, hypervisor kind of virtualization end of things. Over time we've had a great partnership with VMware on-premise, and as both Cloud Block Store and VMware Cloud mature, we'd look to replicate the same motion with them in that offering. >> Yeah, I mean to to extent I mean you think about VMware moving workloads with their customers into the cloud, more mission critical stuff comes into the cloud, it's been hard to get a lot of those workloads in to date and that's maybe the next wave of cloud. Rob W., I have a question for you. You know Amazon's been kind of sleepy in storage over the, S3, EBS, okay great. They dropped a bunch of announcements this year and so it seems like there's more action now in the cloud. What's your sort of point of view as to how you make that an opportunity for Pure? >> The way I've always looked at it is, there's been a way of getting your storage done and delivered on AWS and there's been the way that enterprises have done things on-premise. And I think that was a sort of a longer term bet from AWS that that was the way things will tend to fall towards into the public cloud. And now we see, all of the hyperscalers quite honestly with on-prem, hybrid opportunities. With the like Outpost today, et cetera. The hybrid is a real things, it's not just something people said that couldn't get to the cloud, you know it's a real thing. So I think that actually opens up opportunity from both sides. True enterprise class features that our enterprise class customers are looking for in the cloud through something like CBS are now available. But I think you know at Amazon and other hyperscale are reaching back down into the on-prem environments to help with the onboarding of enterprises up into the cloud >> So the as a service side of things makes life a little bit interesting from my perspective, because that's kind of new for Pure to provide that storage as a service, but also for enterprises as you say, they're used to running things in a particular way so as they move to cloud they're kind of having to adapt and change and yet they don't fully want to. Hybrid is a real thing, there are real workloads that need to perform in a hybrid fashion. So what does that mean for you providing storage as a service, and still to Rob Lee's point, still providing that consistency of experience across the entire product portfolio. 'Cause that's quite an achievement and many other as storage providers haven't actually been able to pull that off. So how do you keep all of those components working coherently together and still provide what customers are actually looking for? >> I think you have to go back to what the basics of what customers are actually looking for. You know they're looking to make smart use of their finances capex potentially moving towards opex, that kind of consumption model is growing in popularity. And I think a lot of enterprises are seeing less and less value in the sort of nuts and bolts storage management of old. And we can provide a lot of that through the as a service offering. So had to look past the management and monitoring. We've always done the Evergreen service subscription, so with software and hardware upgrades. So we're letting their sort of shrinking capex budget and perhaps their limited resources work on the more strategically important elements of their IT strategies, including hybrid-cloud. >> Rob Lee, one of the things we've talked about in the past is AI. I'm interested in sort of the update on the AI workloads . We heard a lot obviously today on the main stage about machine learning, machine intelligence, AI, transformations, how is that going, the whole AI push? You guys were first, really the first storage company to sort of partner up and deliver solutions in that area. Give us the update there. Wow's it going, what are you learning? >> Yeah, so it's going really well. So it continues to be a very strong driver of our flash play business, and again it's really driven by it's a workload that succeeds with very large sums of data, it succeeds when you can push those large sums of data at high speed into modern compute, and rinse and repeat very frequently. And the fourth piece which I think is really helping to propel some of the business there, is you know, as enterprises, as customers get further on into the AI deployment journeys what they're finding is the application space evolves very quickly there. And the ability for infrastructure in general, but storage in particular, because that's where so much data gravity exists to be flexible to adapt to different applications and changing application requirements really helps speed them up. So said another way, if the application set that your data scientists are using today are going to change in six months, you can't really be building your storage infrastructure around a thesis of what that application looks like and then go an replace it in six months. And so that message as customers have been through now the first, first and a half iterations of that and really sort of internalize, hey AI is a space that's rapidly evolving we need infrastructure that can evolve and grow with us, that's helping drive a lot of second looks and a lot of business back to us. And I would actually tie this back to your previous question which is the direction that Amazon have taken with some of their new storage offerings and how that ties into storage as a service. If I step back as a whole, what I'd say is both Amazon and Pure, what we see is there's now a demand really for multiple classes of service for storage, right. Fast is important, it's going to continue to get more and more important, whether it's AI, whether it's low latency transactional databases, or some other workload. So fast always matters, cost always matters. And so you're going to have this stratification, whether it's in the cloud, whether its on flash with SCM, TLC, QLC, you want the benefits of all of those. What you don't want is to have to manage the complexity of tying and stitching all those pieces together yourself, and what you certainly don't want is a procurement model that locks you out or in to one of these tiers, or in one of these locations. And so if you think about it in the long term, and not to put words in the other Rob's mouth, where I think you see us going with Pure as a service is moving to a model that really shifts the conversation with customers to say, look the way you should be transacting with storage vendors, and we're going to lead the charge is class of service, maybe protocol, and that's about it. It's like where do you want this data to exist? How fast do you want it? Where on the price performance curve do you want to be? How do you want it to be protected? And give us room to take care of it from there. >> That's right, that's right. This isn't about the storage array anymore. You know you look at the modern data experience message this is about what do you need from your storage, from a storage attribute perspective rather than a physical hardware perspective and let us worry about the rest. >> Yeah you have to abstract that complexity. You guys have, I mean simple is the reason why you were able to achieve escape velocity along with obviously great product and pretty good management as well. But you'll never sub optimize simplicity to try to turn some knobs. I mean I've learned that following you guys over the years. I mean that's your philosophy. >> No absolutely, and what I'd say is as technology evolves, as the components evolve into this world of multis, multi-protocol, multi-tier, multi-class of service, you know the focus on that simplicity and taking even more if it on becomes ever more important. And that's a place where, getting to your question about AI we help customers implement AI, we also do a lot of AI within our own products in our fleet. That's a place where our AI driven ops really have a place to shine in delivering that kind of best optimization of price, performance, tiers of service, so on, so forth, within the product lines. >> What are you guys seeing at the macro? I mean that to say, you've achieved escape velocity, check. Now you're sort of entering the next chapter of Pure. You're the big share gainer, but obviously growing slower than you had in previous years. Part of that we think is this, part of your fault. You put so much flash into the marketplace. It's given people a lot of headroom. Obviously NaN pricing has been an issue, you guys have addressed that on your calls, but still gaining share much, much more quickly than most. Most folks are shrinking. So what are you seeing at the macro, what are customers telling you in terms of their long term strategy with regard to storage? >> Well, so I'll start, I'll let Rob add in. What I'd say is we see in the macro a shift, a clear shift to flash. We've called the shots since day one, but what I'd say is that's accelerating. And that's accelerating with pricing dynamics, with and you know we talked about a lot of the NaN pricing and all that kind of stuff, but in the macro I think there's a clear realization now that customers want to be on flash. It's just a matter of what's the sensible rate? What's the price kind of curve to get there? And we see a couple meaningful steps. We saw it originally with our flash array line taking out 15K spinning drives, 10K's really falling. With QLC coming online and what we're doing in FlashArray//C the 7200 RPM drive kind of in the enterprise, you know those days are numbered, right. And I think for many customers at this point it's really a matter of, okay how quickly can we get there and when does it make sense to move, as opposed to, does it make sense. In many ways it's really exciting. Because if you think about it, the focus for so long has been in those tier one environments, but in many ways the tier two environments are the ones that could most benefit from a move to flash because a couple things happen there. Because they're considered lower tier, lower cost they tend to spread like bunnies, they tend to be kind of more neglected parts of the environment and so having customers now be able to take a second look at modernizing, consolidating those environments is both helpful from a operational point of view, it's also helpful from the point of view of getting them to be able to make that data useful again. >> I would also say that those exact use cases are perfect candidates for an as a service consumption model because we can actually raise the utilization, actually helping customers manage to a much more utilized set of arrays than the over consumption, under consumption game they're trying to play right now with their annual capex cycles. >> And so how aggressive do you see customers wanting to take advantage of that as a service consumption model? Is it mixed or is it like, we want this? >> There's a lot of customers who are just like we want this and we want it now. We've seen a very good traction and adoption so yeah, it's a surprisingly large, complex enterprise customer adoption as well. >> A lot of enterprise, they've gotten used to the idea of cloud from AWS. They like that model of dealing with things and they want to bring that model of operating on site, because they want cloud everywhere. They don't actually want to transform the cloud into enterprise. >> No, exactly, I mean if I go back 20 plus years to when I was doing hands on IT, the idea that we as a team would let go of any of the widgetry that we are responsible for, never would have happened. But then you've had this parallel path of public cloud experience, and people are like well I don't even need to be doing that anymore. And we get better results. Oh and it's secure as well? And that list just goes on. And so now as you say, the enterprise wants to bring it back on-prem for all of those benefits. >> One of the other things that we've been tracking, and maybe it falls in the category of cloud 2.0 is the sort of new workload forming. And I'll preface it this way, you know the early days, the past decade of cloud infrastructures of service have been about, yeah I'm going to spin up some EC2, I'm going to need some S3, whatever, I need some storage, but today it seems like, there's all this data now and then you're seeing new workloads driven by platforms like Snowflake, Redshift, you know clearly throw in some ML tools like Databricks and it's driving a lot of compute now but it's also driving insights. People are really pulling insights out of that data. I just gave you cloud examples, are you seeing on-prem examples as well, or hybrid examples, and how do you guys fit into that? >> Yeah, no absolutely. I think this is a secular trend that was kicked off by open source and the public cloud. But it certainly affects, I would say, the entire tech landscape. You know a lot of it is just about how applications are built. If you about, think back to the late '80s, early '90s you had large monoliths, you had Oracle, and it did everything, soup to nuts. Your transactional system, your data warehouse, ERP, cool, we got it all. That's not how applications are built anymore. They're built with multiple applications working together. You've got, whether it's Kafka connecting into some scale out analytics database, connected into Cassandra, connected right. It's just the modern way of how applications are built. And so whether that's connecting data between SaaS services in the cloud, whether it's connecting data between multiple different application sets that are running on-prem, we definitely see that trend. And so when you peel back the covers of that, what we see, what we hear from customers as they make that shift, as they try to stand up infrastructure to meet those need, is again the need for flexibility. As multiple applications are sharing data, are handing off data as part of a pipeline or as part of a workflow, it becomes ever more important for the underlying infrastructure, the storage array if you will, to be able to deliver high performance to multiple applications. And so the era of saying, hey look I'm going to design a storage array to be super optimized for Oracle and nothing else like you're only going to solve part of the problem now. And so this is why you see us taking, within Pure the approach that we do with how we optimize performance, whether it's across FlashArray, FlashBlade, or Cloud Block Store. >> Excellent, well guys we got to leave it there. Thanks so much for coming on theCUBE and sharing your thoughts with us. And have a good rest of re:Invent. >> Thanks for having us back >> Dave: All right, pleasure >> Thank you >> All right, keep it right there everybody. We'll be back to wrap day one. Dave Vellante for Justin Warren. You're watching theCUBE from AWS re:Invent 2019. Right back (electronic music)

>> Announcer: Live from San Jose, in the heart of Silicon Valley, it's theCUBE, covering DataWorks Summit 2017, brought to you by Hortonworks. >> Hi, welcome to theCUBE. We are live in San Jose, in the heart of Silicon Valley at the DataWorks Summit, day one. I'm Lisa Martin, with my co-host, George Gilbert. And we're very excited to be talking to two Robs. With Rob squared on the program this morning. Rob Bearden, the CEO of Hortonworks. Welcome, Rob. >> Thank you for having us. >> And Rob Thomas, the VP, GM rather, of IBM Analytics. So, guys, we just came from this really exciting, high energy keynote. The laser show was fantastic, but one of the great things, Rob, that you kicked off with was really showing the journey that Hortonworks has been on, and in a really pretty short period of time. Tremendous inertia, and you talked about the four mega-trends that are really driving enterprises to modernize their data architecture. Cloud, IOT, streaming data, and the fourth, next leg of this is data science. Data science, you said, will be the transformational next leg in the journey. Tell our viewers a little bit more about that. What does that mean for Hortonworks and your partnership with IBM? >> Well, what I think what IBM and Hortonworks now have the ability to do is to bring all the data together across a connected data platform. The data in motion, the data at rest, now have in one common platform, irrespective of the deployment architecture, whether it's on prim across multiple data centers or whether deployed in the cloud. And now that the large volume of data and we have access to it, we can now start to begin to drive the analytics in the end as that data moves through each phase of its life cycle. And what really happens now, is now that we have visibility and access to the inclusive life cycle of the data we can now put a data science framework over that to really now understand and learn those patterns and what's the data telling us, what's the pattern behind that. And we can bring simplification to the data science and turn data science actually into a team sport. Allow them to collaborate, allow them to have access to it. And sort of take the black magic out of doing data science with the framework of the tool and the power of DSX on top of the connected data platform. Now we can advance rapidly the insights in the end of the data and what that really does is drive value really quickly back into the customer. And then we can then begin to bring smart applications via the data science back into the enterprise. So we can now do things like connected car in real time, and have connected car learn as it's moving and through all the patterns, we can now, from a retail standpoint really get smart and accurate about inventory placement and inventory management. From an industrial standpoint, we know in real time, down to the component, what's happening with the machine, and any failures that may happen and be able to eliminate downtime. Agriculture, same kind of... Healthcare, every industry, financial services, fraud detection, money laundering advances that we have but it's all going to be attributable to how machine learning is applied and the DSX platform is the best platform in the world to do that with. >> And one of the things that I thought was really interesting, was that, as we saw enterprises start to embrace Hadoop and Big Data and Segano this needs to co-exist and inter-operate with our traditional applications, our traditional technologies. Now you're saying and seeing data science is going to be strategic business differentiator. You mentioned a number of industries, and there were several of them on stage today. Give us some, maybe some, one of your favorite examples of one of your customers leveraging data science and driving a pretty significant advantage for their business. >> Sure. Yeah, well, to step back a little bit, just a little context, only ten companies have out performed the S&P 500 in each of the last five years. We start looking at what are they doing. Those are companies that have decided data science and machine learning is critical. They've made a big bet on it, and every company needs to be doing that. So a big part of our message today was, kind of, I'd say, open the eyes of everybody to say there is something happening in the market right now. And it can make a huge difference in how you're applying data analytics to improve your business. We announced our first focus on this back in February, and one of our clients that spoke at that event is a company called Argus Healthcare. And Argus has massive amounts of data, sitting on a mainframe, and they were looking for how can we unleash that to do better care of patients, better care for our hospital networks, and they did that with data they had in their mainframe. So they brought data science experience and machine learning to their mainframe, that's what they talked about. What Rob and I have announced today is there's another great trove of data in every organization which is the data inside Hadoop. HDP, leading distribution for that, is a great place to start. So the use case that I just shared, which is on the mainframe, that's going to apply anywhere where there's large amounts of data. And right now there's not a great answer for data science on Hadoop, until today, where data science experience plus HDP brings really, I'd say, an elegant approach to it. It makes it a team sport. You can collaborate, you can interact, you can get education right in the platform. So we have the opportunity to create a next generation of data scientists working with data and HDP. That's why we're excited. >> Let me follow up with this question in your intro that, in terms of sort of the data science experience as this next major building block, to extract, or to build on the value from the data lake, the two companies, your two companies have different sort of, better markets, especially at IBM, but the industry solutions and global business services, you guys can actually build semi-custom solutions around this platform, both the data and the data science experience. With Hortonworks, what are those, what's your go to market motion going to look like and what are the offerings going to look like to the customer? >> They'll be several. You just described a great example, with IBM professional services, they have the ability to take those industry templates and take these data science models and instantly be able to bring those to the data, and so as part of our joint go to market motion, we'll be able now partner, bring those templates, bring those models to not only our customer base, but also part of the new sales go to market motion in the light space, in new customer opportunities and the whole point is, now we can use the enterprise data platforms to bring the data under management in a mission critical way that then bring value to it through these kinds of use case and templates that drive the smart applications into quick time to value. And just increase that time to value for the customers. >> So, how would you look at the mix changing over time in terms of data scientists working with the data to experiment on the model development and the two hard parts that you talked about, data prep and operationalization. So in other words, custom models, the issue of deploying it 11 months later because there's no real process for that that's packaged, and then packaged enterprise apps that are going to bake these models in as part of their functionality that, you know, the way Salesforce is starting to do and Workday is starting to do. How does that change over time? >> It'll be a layering effect. So today, we now have the ability to bring through the connected data platforms all the data under management in a mission critical manner from point of origination through the entire stream till it comes at rest. Now with the data science, through DSX, we can now, then, have that data science framework to where, you know, the analogy I would say, is instead of it being a black science of how you do data access and go through and build the models and determine what the algorithms are and how that yields a result, the analogy is you don't have to be a mechanic to drive a car anymore. The common person can drive a car. So, now we really open up the community business analyst that can now participate and enable data science through collaboration and then we can take those models and build the smart apps and evolve the smart apps that go to that very rapidly and we can accelerate that process also now through the partnership with IBM and bringing their core domain and value that, drivers that they've already built and drop that into the DSX environments and so I think we can accelerate the time to value now much faster and efficient than we've ever been able to do before. >> You mentioned teamwork a number of times, and I'm curious about, you also talked about the business analyst, what's the governance like to facilitate business analysts and different lines of business that have particular access? And what is that team composed of? >> Yeah, well, so let's look at what's happening in the big enterprises in the world right now. There's two major things going one. One is everybody's recognizing this is a multi-cloud world. There's multiple public cloud options, most clients are building a private cloud. They need a way to manage data as a strategic asset across all those multiple cloud environments. The second piece is, we are moving towards, what I would call, the next generation data fabric, which is your warehousing capabilities, your database capabilities, married with Hadoop, married with other open source data repositories and doing that in a seamless fashion. So you need a governance strategy for all of that. And the way I describe governance, simple analogy, we do for data what libraries do for books. Libraries create a catalog of books, they know they have different copies of books, some they archive, but they can access all of the intelligence in the library. That's what we do for data. So when we talk about governance and working together, we're both big supporters of the Atlas project, that will continue, but the other piece, kind of this point around enterprise data fabric is what we're doing with Big SQL. Big SQL is the only 100% ANSI-SQL compliant SQL engine for data across Hadoop and other repositories. So we'll be working closely together to help enterprises evolve in a multi-cloud world to this enterprise data fabric and Big SQL's a big capability for that. >> And an immediate example of that is in our EDW optimization suite that we have today we be loading Big SQL as the platform to do the complex query sector of that. That will go to market with almost immediately. >> Follow up question on the governance, there's, to what extent is end to end governance, meaning from the point of origin through the last mile, you know, if the last mile might be some specialized analytic engine, versus having all the data management capabilities in that fabric, you mentioned operational and analytic, so, like, are customers going to be looking for a provider who can give them sort of end to end capabilities on both the governance side and on all the data management capabilities? Is that sort of a critical decision? >> I believe so. I think there's really two use cases for governance. It's either insights or it's compliance. And if you're focus is on compliance, something like GDPR, as an example, that's really about the life cycle of data from when it starts to when it can be disposed of. So for compliance use case, absolutely. When I say insights as a governance use case, that's really about self-service. The ideal world is you can make your data available to anybody in your organization, knowing that they have the right permissions, that they can access, that they can do it in a protected way and most companies don't have that advantage today. Part of the idea around data science on HDP is if you've got the right governance framework in place suddenly you can enable self-service which is any data scientist or any business analyst can go find and access the data they need. So it's a really key part of delivering on data science, is this governance piece. Now I just talked to clients, they understand where you're going. Is this about compliance or is this about insights? Because there's probably a different starting point, but the end game is similar. >> Curious about your target markets, Tyler talked about the go to market model a minute ago, are you targeting customers that are on mainframes? And you said, I think, in your keynote, 90% of transactional data is in a mainframe. Is that one of the targets, or is it the target, like you mention, Rob, with the EDW optimization solution, are you working with customers who have an existing enterprise data warehouse that needs to be modernized, is it both? >> The good news is it's both. It's about, really the opportunity and mission, is about enabling the next generation data architecture. And within that is again, back to the layering approach, is being able to bring the data under management from point of origination through point of it reg. Now if we look at it, you know, probably 90% of, at least transactional data, sits in the mainframe, so you have to be able to span all data sets and all deployment architectures on prim multi-data center as well as public cloud. And that then, is the opportunity, but for that to then drive value ultimately back, you've got to be able to have then the simplification of the data science framework and toolset to be able to then have the proper insights and basis on which you can bring the new smart applications. And drive the insights, drive the governance through the entire life cycle. >> On the value front, you know, we talk about, and Hortonworks talks about, the fact that this technology can really help a business unlock transformational value across their organization, across lines of business. This conversation, we just talked about a couple of the customer segments, is this a conversation that you're having at the C-suite initially? Where are the business leaders in terms of understanding? We know there's more value here, we probably can open up new business opportunities or are you talking more the data science level? >> Look, it's at different levels. So, data science, machined learning, that is a C-suite topic. A lot of times I'm not sure the audience knows what they're asking for, but they know it's important and they know they need to be doing something. When you go to things like a data architecture, the C-suite discussion there is, I just want to become more productive in how I'm deploying and using technology because my IT budget's probably not going up, if anything it may be going down, so I've got to become a lot more productive and efficient to do that. So it depends on who you're talking to, there's different levels of dialogue. But there's no question in my mind, I've seen, you know, just look at major press Financial Times, Wallstreet Journal last year. CEOs are talking about AI, machine learning, using data as a competitive weapon. It is happening and it's happening right now. What we're doing together, saying how do we make data simple and accessible? How do we make getting there really easy? Because right now it's pretty hard. But we think with the combination of what we're bringing, we make it pretty darn easy. >> So one quick question following up on that, and then I think we're getting close to the end. Which is when the data lakes started out, it was sort of, it seemed like, for many customers a mandate from on high, we need a big data strategy, and that translated into standing up a Hadoop cluster, and that resulted in people realizing that there's a lot to manage there. It sounds like, right now people know machine learning is hot so they need to get data science tools in place, but is there a business capability sort of like the ETL offload was for the initial Hadoop use cases, where you would go to a customer and recommend do this, bite this off as something concrete? >> I'll start and then Rob can comment. Look, the issue's not Hadoop, a lot of clients have started with it. The reason there hasn't been, in some cases, the outcomes they wanted is because just putting data into Hadoop doesn't drive an outcome. What drives an outcome is what do you do with it. How do you change your business process, how do you change what the company's doing with the data, and that's what this is about, it's kind of that next step in the evolution of Hadoop. And that's starting to happen now. It's not happening everywhere, but we think this will start to propel that discussion. Any thoughts you had, Rob? >> Spot on. Data lake was about releasing the constraints of all the silos and being able to bring those together and aggregate that data. And it was the first basis for being able to have a 360 degree or wholistic centralized insight about something and, or pattern, but what then data science does is it actually accelerates those patterns and those lessons learned and the ability to have a much more detailed and higher velocity insight that you can react to much faster, and actually accelerate the business models around this aggregate. So it's a foundational approach with Hadoop. And it's then, as I mentioned in the keynote, the data science platforms, machine learning, and AI actually is what is the thing that transformationally opens up and accelerates those insights, so then new models and patterns and applications get built to accelerate value. >> Well, speaking of transformation, thank you both so much for taking time to share your transformation and the big news and the announcements with Hortonworks and IBM this morning. Thank you Rob Bearden, CEO of Hortonworks, Rob Thomas, General Manager of IBM Analytics. I'm Lisa Martin with my co-host, George Gilbert. Stick around. We are live from day one at DataWorks Summit in the heart of Silicon Valley. We'll be right back. (tech music)