>> from Austin, Texas. It's Theo Cube, covering your storage. Accelerate 2019. Brought to you by pure storage. >> Hi, Lisa Martin with the Cube. Dave Ilan Taste. My co host were at pure Accelerate 2019 in Austin, Texas. One of our Cube alumni is back with us. We have probably the VP and chief architect at Pier Storage. Rob. Welcome back. >> Thanks for having. >> We're glad you have a voice. We know how challenging these events are with about 3000 partners, customers press everybody wanting to talk to one of the men that was on the keynote stage yesterday for announcements came out really enjoyed yesterday's keynote. But let's talk about one of those announcements in particular Piers Bridge to the hybrid cloud. >> Absolutely, absolutely. Yeah. No, I mean, I think it's been a really exciting conference for us so far. Like you said, a lot of payload coming out, you know, as faras the building, the bridge of the hybrid cloud. This has been, you know, this has been I would say a long time coming, right? We've been working down this path for for a couple of years. We started by bringing some of the cloud like capabilities that customers really wanted and were able to achieve into the cloud back into the data center. Right. So you saw us do this in terms of making our own prem products easier to manage, easier to use, easier to automate, you know. But what? Working with customers of the last couple of years, you know, we realized, is that, uh as the cloud hype kind of subsided and people were taking a more measured view of where the cloud fits into their strategies, what tools it brings. You know, we realized that we could add value in the public cloud environment, the same types of enterprise capabilities, the same type of features rich data service is feature sets things like that that we do on premise in the cloud. And so what we're looking to achieve is actually quite simple, all right. We want to give customers the choice whether whether customers want to run on premise or in the cloud. That's just a choice of we wanted. We wanted to make an environmental choice. We don't want it. We don't wanna put customers in a position where they have to make that choice and feel trapped in one location another because of lack of features, lack of capabilities. You know, our economics on DSO the way that we do that is by building the same types of capabilities that we do on Prem in the cloud giving customers the freedom and flexibility to be agile. >> But, you know, you mentioned economics and you were talking from a customer standpoint. I wanna flip it from a from a technology supplier standpoint, the economics of a vendor who traditionally cells on Prem. You would think would be better than one in the cloud. Because you gotta you pay an Amazon for all their service is or I guess, the customers paying for it. But you kind of saw your way through that. A lot of companies would be defensive on. I wonder if you could add any comment. Yeah. No, I mean so So, look, I think >> the >> hardware is only one piece of it, right? At the end of the day, you know, even our products on Prem are really they're really priced for value. Right? There were delivering value to customers in our capabilities are ease of use or simplicity. The types of applications and work close to being able. Um, and basically, everything I just said is pretty much driven by software features by bringing those same capabilities into the cloud, you know, naturally, we you know, naturally that most of that work is really in software, you know, And then, as faras comparing the economics directly of on Prem versus Cloud. You know, it's it's really no secret as the industry's gotten Maur. Understanding that, you know the cloud isn't isn't the low cost option in a lot of use cases, right? And so, rather than comparing apples to apples on premises cloud either on performance or economics, our goal is really to build the best products in either environment. So if a customer wants to run on Prem wanna build the best darn products in that environment, the customer wants to run in the public cloud. We want to build the best darn product for them in that environment on dhe. Increasingly, as customers want Thio use, both environments hand in hand, want to build the right capabilities to allow them. TOC mostly do that >> Well, I think it makes sense because, as you know, we're talking to some customers. Last night he asking what they have in their data center. And they got a lot of stuff in the data center. To the extent that a company like pure can say, OK, you've got simple, fast et cetera on prim. And we've now extended that to the cloud. Your choice. They're going to spend Maur with you than they are with the guys that fight that. >> Yeah, absolutely. And, you know, I think if you look at our approach and how we've built the products and how were, you know, taking them to market? We've taken a very different approach than some of the competitive set. You know, in some ways, we've really just extended the same way that we think about innovation and product engineering from our existing on prime portfolio into the cloud, which is we look for heart problems to solve way take the hard road, we build differentiated products. Even if it takes us a little bit longer, you can see that, you know, in the product offerings, right? We've really focused on enabling tier one mission critical applications. If you look at the competitive, said they haven't started their their reason why we did that. All right, is we knew that you know, we had customers telling us, like if if you're a customer and you want to use the cloud and you want to think about the cloud is a D R site well, when something goes wrong and you two fell over duty, our site, you you need to be sure that it works exactly the same way there as it did on problem. That's everything from data service is data path features to all of the work flows. An orchestration to go around it because when your primary site goes down is not the time when you want to be discovering that. Oh, there's a footnote on that future and it's that's not supported in the cloud version, that sort of thing on dso you know that, Like I said, you know, the focus that we've put on the product development we've done towards Cloud Block stores really been around creating the same level of enterprise grade features on enabling those applications in the cloud as we do in private. >> You know, we don't make the Amazon storage. We make the Amazon storage better. What's that commercial? Essentially what? That's essentially >> what we've done You know, the great thing about that is that we've done it in close partnership with Amazon, right? You know, we had Amazon on stage yesterday on day, were talking a little bit about that partnership process. And ultimately, I think why that partnership has been so successful is we're both ultimately driven by the same thing, which is customer success. All right. In the early days of working with Amazon as we started coming up with the concept of club block store and consulting them on, we're thinking about building it this way. What do you think? What service is should be, You know, should we leverage and m in eight of us to make this happen? It became pretty clear to them that we were setting out to build a differentiated product and not just tick off check boxes on dhe. That's when they their eyes really okay, way. We really would like you to do a differentiated product here. >> Hey, if this takes off, we're gonna sell all the C two at three. >> What are some of the things Sorry day that you've been with here about six years? What are some of the things that have surprised you pleasantly that the customers have catalysed from an architecture perspective that customer feedback coming back t your team and the and the guys and girls engineering the product. Customers are demanding a certain thing that maybe wasn't something that was an internal idea but really was catalyzed by customers anything that just really I think it's very cool. Very surprising. >> Yeah. No, I mean, I think I think a >> couple of things. I think personally one of the things that surprised me was, you know, when I joined Pure in 2013 you know, we're all we're all about simplicity, right? You talk to cause who I think you had on the show earlier. You know, in the early days who tell you our differentiators gonna be simplicity and I got to say when I first joined the company is a little skeptical is like All right, I get it. Simplicity is a thing. Is it really a differentiator? I very quickly was surprised based on customer feedback that no, it really is very, very meaningful on. And that's something that we take all the way through Engineering. Write everything down, Thio how we design features and put them in the user interfaces. If there's, you know, there's an engineer that wants to put a configuration hook or a knob or ah on option in the user interface way kind of stop and say, Well, G, how would you document that? How would you suggest the user make a decision? Tea set that value will describe and say, Okay, well, g, we can make that decision, can't we? Right? Like, why don't we just want we just make it simpler And so that's been That's been a big surprise, I think, from a customer catalyzed, uh, point of view. What I'd say is we've been really surprised at a lot of the use cases that the flash blade product has been put into play for. And, you know, I think a I was one of them when we when we first set out, we had really targeted Flash played at addressing a segment of the commercial HPC Chip Design Hardware Design software development market. Andi is actually a set of customers, very large Web property customer that came to us with an A I use case. They said, Hey, you know, we've got a ton of data video images, uh, text postings. And we want to do a lot of analysis of this. All right, I want to do a facial recognition. We want to do content and sentiment analysis. We've got the Jeep use. We think you guys have the right storage product for that, and that's really that's really taken off. And that was very much a customer driven area. We >> talked a little bit about that within video yesterday. About some of the customer catalyzed innovation where a is concerned. >> Absolutely. What do you see is the critical technical skills that pure needs in the next decade. I mean, you're five. Correct? Remember, you can't have a networking background. Internal networking, I guess of you got guys from Veritas, right? Obviously strong software file system. What do you What do you see is the critical skill. Yeah, that's >> a good question. You know, we have a very diverse team, all right? We we in engineering typically higher and look for people with strong systems, backgrounds that are willing to learn and want to solve her problems. We, you know, typically haven't hired very specific domain areas myself, my doctor, and is in language run times and compilers, Oh, distributed systems so a bit all over the map, You know, What I'd say is that the first phase of pure the first kind of decade was really about reinventing the storage experience on for me. I look at it as taking lessons from the consumer experience, bringing him into the storage on Enterprise World. Three iPhones, example. That's used a lot. There's a couple of examples you can think of. I think the next phase of what we're trying to do and you heard Charlie talk about this on stage with a modern date experience is take some lessons from the cloud experience and bring them into the enterprise. Right? So the first phase is about consumer simplicity for a human think the next phase is really about bring in some more of the cloud experience for enabling automation and dev ops and management orchestration. >> So what kind of work? A long, long, lot of work to do to get we envisioned this massively scalable distributed system where you have that cloud experience no matter where your data lives, that's not there today, Um, and you don't want to ship your date around, it'd be too much data. So you're on a ship metadata and have the intelligence tow. Bring the compute to that. That data. >> What do you >> got to do? What's the work that you have to do to actually make that seamless? That there's that over word overuse word again. It's not seamless today. Yeah, >> so? So, look, I mean, I think there's there's a lot of angles to it right on. And we're gonna We're gonna work our way there to your point. You know, it's not there today, but, you know, you're you're starting to see us lay the groundwork with all the announcements that came out today, right under the umbrella of Hey, we want to end up creating more portable, more seamless, more agile experience for customers. You can see where, as we bring Maur storage media's into play different classes of service, different balances of performance and cost, bringing those together in a way so that an application can use them income in the right combinations, you know, bring a I into play to help customers do that seamlessly and transparently eyes a big part of it. You can see multiple location kind of agility that we're bringing into play with Claude Block >> store >> enabled, like loud snap and snap shot mobility. Things like that on Dhe. Then you know, I think, as we move beyond the block world and way look att, what we can able with applications that sit on top of file on object protocols. There's a lot of, ah, a lot of greenfield there, right? So you know, we think object storage is very attractive, and we're starting to see that as the application vendors, right, as the applications that sit on top of the storage layer are really embracing object storage as the cloud native storage interface, if you will, that's creating a lot of, ah, a lot of, uh, you know, a lot of ways to share data, right? We're starting to see it, even within the data center, where multiple applications now are able to share data because object storage is being used. And so, like I said, there's a lot of angles to this right. There's there's bringing multiple discreet A raise together under the same management plane. There's bringing multiple different types of storage media a little bit closer together from a seamless application mobility perspective. There's bring multiple locations, data centers, clouds together from a migration a d R perspective. And then there's, you know, there's bringing a global name space type of capability to the table, so it's a long journey. But you know, we think it's the right one. And you know what we ultimately want to do is, you know, have customers be able to think about, be ableto provisioned, be able to manage to not just an array, but really more of like an A Z, right. I want a pool. I want it to be about a fast. But you know, I'm willing to pay about yea much for it, and I need this types of data protection policies for it. Please make it happen >> and anywhere do you So you see, it is technically feasible to be able to run any app, any workload on any cloud or on Prem without having a re compile the application, make changes to the application. That's what I really kind of meant by Seamus that you see that as technically feasible in the next called 5 to 10 years, I'll give you I think >> I think it'll take a long wait a long time we'll get there. And I think, you know, I think it'll depend on the application. All right. I think there are gonna be some combinations that look. I mean, if if you have a high, high frequency, low latent see trading database, there's physical limitations, you're not going to run the application here and put the storage in the cloud. But if we if we step back from it, right, the concept, Yeah. I mean, I think that a lot of a lot of things are becoming possible to make this happen, right? Fastener networking is everywhere. It's getting faster application architectures and making it more feasible. You know, the media costs and what we're able to drive out of the media are bringing a lot a lot more than work leads to flash A eyes is coming into play. So, like I said, it's gonna be different on the on the application. But, you know, I think we're entering a phase where, you know, the modern software developer doesn't wanna have to think too hard about where is you know where physically what six sides of sheet metal is. My dad is sitting on. They want to think about what I need from it. What do we need from in terms of capacity, what we need from it in terms of performance, what we need from it in terms of data service capabilities. All right, ends, you know, And I need to be able to control that elastic Lee. I need to be able to control that through my application through software, and that's kind of what we're building towards. >> Last question, Rob, as we wrap up here, feedback that you've heard the last day and 1/2 on some of the news that came out yesterday from customers, analysts, partners. >> Yeah, you know, I'd say if I were to net it out. I think the one piece of you, Doc, we've gotten this. Wow, you guys have a lot of stuff on. It's really nice to see you guys talking about stuff. It's available today, right? That >> that's a >> lot of eyes on that screen. And, you know, I think I had a KN analysts say to me, You know, this is it's really refreshing. Thio kind of See you guys take a both you know, the viewpoint of the customer. What you're delivering the customer, what you're enabling on then be, You know, I got a lot of tech conferences and I hear a lot about, like, way off in the future. Envisioned Andi feedback we got was you guys had a really good balance of reality today. What, You're helping customers today? What's available today to do that? And enough of the hay. And here's where we're headed. So >> we actually heard the same thing. So good stuff, right? Well, congrats on the 10th anniversary, and we appreciate you joining us on the Cube. We look forward to next year already in whatever city. You're gonna take us to >> two. Thanks a lot. >> All right. For day, Volante. I'm Lisa Martin. You're watching the Cube. Thanks for watching.

>> from Austin, Texas. It's Theo Cube, covering pure storage. Accelerate 2019. Brought to you by pure storage. >> Welcome to the Cube. The leader in live tech coverage covering up your accelerate 2019. Lisa Martin with Dave Ilan in Austin, Texas, this year. Pleased to welcome a couple of guests to the program. Please meet Charlie Boyle, VP and GM of DJ X Systems at N Video. Hey, Charlie, welcome back to the Cube, but in a long time ago and we have Brian Schwartz, VP of product management and development at your brain. Welcome. >> Thanks for having me. >> Here we are Day one of the event. Lots of News This morning here is just about to celebrate its 10th anniversary. A lot of innovation and 10 years. Nvidia partnerships. About two is two and 1/2 years old or so. Brian, let's start with you. Give us a little bit of an overview about where pure and and video are, and then let's dig into this news about the Aye aye data hub. >> Cool, it's It's been a good partnership for a couple of years now, and it really was born out of work with mutual customers. You know we brought out the flash blade product, obviously in video was in the market with DJ X is for a I, and we really started to see overlap in a bunch of initial deployments. And we really realized that there was a lot of wisdom to be gained off some of these early I deployments of capturing some of that knowledge and wisdom from those early practitioners and being able to share it with the with the wider community. So that's really kind of where the partnership was born going for a couple of years now, I've got a couple of chapters behind us and many more in the future. And obviously the eye data hub is the piece that we really talked about at this year's accelerate. >> Yeah, areas about been in the market for what? About a year and 1/2 or so Almost >> two years. >> Two years? All right, tell us a little bit about the adoption. What what customers were able to dio with this a ready infrastructure >> and point out the reason we started the partnership was our early customers that were buying dejected product from us. They were buying pure stored. Both leaders and high performance. And as they were trying to put them together, they're like, How should we do this? What's the optimal settings? They've been using storage for years. I was kind of new to them and they needed that recipe. So that's, you know, the early customer experiences turned into airy the solution, and, you know, the whole point of this to simplify. I sounds kind of scary to a lot of folks and the data scientists really just need to be productive. They don't care about infrastructure, but I t s to support this. So I t was very familiar with pure storage. They used them for years for high performance data and as they brought in the Nvidia Compute toe work with that, you know, having a solution that we both supported was super important to the I T practitioners because they knew it worked. They knew we both supported it. We stood behind it and they could get up and running in a matter of days or weeks versus 6 to 9 months if they built it >> themselves. >> You look at companies that you talk to customers. Let's let's narrow it down to those that have data scientists least one day to scientists and ask him where they are in their maturity model, if one is planning to was early threes, they got multiple use cases and four is their enterprise wide. How do you see the landscape? Are you seeing pretty aggressive adoption in those as I couched it, or is it still early? >> I mean so every customers in a different point. So there's definitely a lot of people that are still early, but we've seen a lot of production use cases. You know, everyone talks about self driving cars, but that's, you know, there's a lot behind that. But real world use cases say medicals got a ton? You know, we've got partner companies that you are looking at a reconstruction of MRI's and CT scans cutting the scan time down by 75%. You know, that's real patient outcome. You know, we've got industrial inspection, we're in Texas. People fly drones around and have a eye. Models that are built in their data center on the drone and the field operators get to re program the drones based on what they see and what is happening. Real time and re trains every night. So depending on the industry really depends on where people are in the maturity her. But you know, really, our message out to the enterprises are start now. You know, whether you've got one data scientist, you've got some community data scientists. There's no reason to wait on a because there's a use case that work somewhere in your inner. >> So so one of the key considerations to getting started. What would you say? >> So one thing I would say is, look any to your stages of maturity. Any good investment is done through some creation of business value, right? And an understanding of kind of what problem you're trying to solve and making sure it's compelling. Problem is an important one, and some industries air farther along. Like you know, one of the ones that most everybody's familiar with is the tech industry itself. Every recommendation engine you've probably ever seen on the Internet is backed by some form of a I behind it because they wanted to be super fast and, you know, customized to you as a user. So I think understanding the business value creation problem is is a really important step of it and many people go through an early stage of experimentation, data modeling really kind of, say, a prototyping stage before they go into a mass production use case. It's a very classic i t adoption curve. Just add a comment to the earlier kind of trend is it's a megatrend. Yes, not everybody is doing it in massive wide scale production today. There's some industries that are farther ahead. If you look forward over the next 15 to 20 years, there's a massive amount of Ai ai coming, and it's a It is a new form of computing, the GPU driven computing and the whole point about areas getting the ingredients right. Thio have this new set of infrastructure have storage network compute on the software stack all kind of package together to make it easier to adopt, to allow people to adopt it faster because some industries are far along and others are still in the earlier stages, >> right? So how do you help for those customers and industries that aren't self driving cards of the drones that you talked about where we use case, we all understand it and are excited about it. But for other customers in different industries. How do you help them even understand the A pipeline? And where did they start? I'm sure that varies very >> a lot. But, you know, the key point is starting a I project. You have a desired outcome from Not everything's gonna be successful, but you know Aye, aye. Projects aren't something that it's not a six month I t project or a big you know, C r m. Refresh it. Something that you could take One of our classes that we have, we do a lot of end user customer training are Deep Learning Institute. You can take 1/2 day class and actually do a deep learning project that day. And so a lot of it is understanding your data, you know, and that's where your and the data hub comes in, understanding the data that you have and then formulating a question like, What could I do if I knew this thing? That's all about a I and deep learning. It's coming up with insights that aren't natural. When you just stare at the data, how can the system understand what you want? And then what are the things that you didn't expect defined that A. I is showing you about your data, and that's really a lot of where the business value comes. And how do you know more about your customer? How do you help that customer better, eh? I can unlock things that you may not have pondered yourself. >> The other thing. I'm a huge fan of analogies when you're trying to describe a new concept of people. And there's a good analogy about Ai ai data pipelines that predates, Aye aye around data warehousing like there's been industry around, extract transformers load E T L Systems for a very long period of time. It's a very common thing for many, many people in the I T industry, and I do think there's when you think about a pipeline in a I pipeline. There's an analogy there, which you have data coming in ingress data. You're cleansing it, you're cleaning it. You're essentially trying to get some value out of it. How you do that in a eyes quite a bit different, cause it's GP use and you're looking, you know, for turning unstructured data into more structure date. It's a little different than data. Warehousing traditionally was running reports, but there's a big analogy, I think, to be used about a pipeline that is familiar to people as a way to understand the new concept. >> So that's good. I like the pipeline concept. One of the one of the counters to that would be that you know, when you think about e. T ells complicated process enterprise data warehouses that were cumbersome Do you feel like automation in the A I Pipeline? When we look back 10 years from now, we'll have maybe better things to say than we do about E D W A R e g l. >> And I think one of the things that we've seen, You know, obviously we've done a ton of work in traditional. Aye, aye, But we've also done a lot in accelerated machine learning because that's a little closer to your traditional Data analytics and one of the biggest kind of ah ha moments that I've seen customers in the past year or so. It's just how quickly, by using GPU computing, they can actually look at their data, do something useful with it, and then move on to the next thing so that rapid experimentation is all you know, what a I is about. It's not a eyes, not a one and done thing. Lots of people think Oh, I have to have a recommend er engine. And then I'm done. No, you have to keep retraining it day in and day out so that it gets better. And that's before you had accelerated. Aye, aye pipeline. Before you had accelerated data pipelines that we've been doing with cheap use. It just took too long so people didn't run those experiments. Now we're seeing people exploring Maur trying different things because when your experiment takes 10 minutes, two minutes versus two days or 10 days, you can try out your cycle time. Shorter businesses could doom or and sure, you're gonna discard a lot of results. But you're gonna find those hidden gems that weren't possible before because you just didn't have the time to do >> it. Isn't a key operational izing it as well? I mean again, one of the challenges with the analogy that you gave a needy W is fine reporting. You can operationalize it for reporting, and but the use cases weren't is rich robust, and I feel as though machine intelligence is I mean, you're not gonna help but run into it. It's gonna be part of your everyday life, your thoughts. >> It's definitely part of our everyday lives. When you talk about, you know, consumer applications of everything we all use every day just don't know it's it's, you know, the voice recognition system getting your answer right the first time. You know there's a huge investments in natural language speech right now to the point that you can ask your phone a question. It's going through searching the Web for you, getting the right answer, combining that answer, reading it back to you and giving you the Web page all in less than a second. You know, before you know that be like you talked to an I. V R system. Wait, then you go to an operator. Now people are getting such a better user experience out of a I back systems that, you know over the next few years, I think end users will start preferring to deal with those based systems rather than waiting on line for human, because it'll just get it right. It'll get you the answer you need and you're done. You save time. The company save time and you've got a better outcome. >> So there's definitely some barriers to adoption skills. Is one obvious one the other. And I wonder if Puritan video attack this problem. I'm sure you have, but I'd like some color on it. His traditional companies, which a lot of your customers, their data is in pockets. It's not at the core. You look at the aye aye leaders, you know, the Big Five data their data cos it's at the core. They're applying machine intelligence to that data. How has this modern storage that we heard about this morning affected that customers abilities to really put data at their core? >> You know, it's It's a great question, Dave and I think one of the real opportunities, particularly with Flash, is to consolidate data into a smaller number off larger kind of islands of data, because that's where you could really drive the insights. And historically, in a district in world, you would never try to consolidate your data because there was too many bad performance implications of trying to do that. So people had all these pockets, and even if you could, you probably wouldn't actually want to put the date on the same system at the same time. The difference with flashes as so much performance at the at the core of it at the foundation of it. So the concept of having a very large scale system, like 150 blade system we announced this morning is a way to put a lot of the year and be able to access it. And to Charlie's point, a lot of people they're doing constant experiment, experimentation and modeling of the data. You don't know that how the date is gonna be consumed and you need a very fast kind of wide platform to do that, Which is why it's been a good fit for us to work together >> now fall upon that. Dated by its very nature. However, Brian is distributed and we heard this morning is you're attacking that problem through in a P I framework that you don't care where it is. Cloud on Prem hybrid edge. At some point in time, your thoughts on that >> well, in again the data t be used for a I I wouldn't say it's gonna be every single piece of data inside an organization is gonna be put into the eye pipeline in a lot of cases, you could break it down again. Thio What is the problem? I'm trying to solve the business value and what is the type of data that's gonna be the best fit for it? There are a lot of common patterns for consumption in a I AA speech recognition image recognition places where you have a lot of unstructured data or it's unstructured to a computer. It's not unstructured to you. When you look at a picture, you see a lot of things in it that a computer can't see right, because you recognize what the patterns are and the whole point about a eyes. It's gonna help us get structure out of these unstructured data sets so the computer can recognize more things. You know, the speech and emotions that we as humans just take for granted. It's about having computers, being able to process and respond to that in a way that they're not really people doing today. >> Hot dog, not a hot dog. Silicon Valley >> Street light. Which one of these is not a street lights and prove you're not about to ask you about distributed environments. You know customers have so much choice for everything these days on Prem hosted SAS Public Cloud. What are some of the trends that you're seeing? I always thought that to really be able to extract a tremendous amount of value from data and to deliver a I from it you needed the cloud because you needed a massive volumes of data. Appears legacy of on print. What are some of the things that you're seeing there and how is and video you're coming together to help customers wherever this data is to really dry Valley business value from these workloads, >> I have to put comments and I'll turn over to Charlie. So one is we get asked this question a lot. Like where should I run my eye? The first thing I always tell people is, Where's your data? Gravity moving these days? That's a very large tens of terror by its hundreds of terabytes petabytes of data moving very large. That's the data is actually still ah, hard challenge today. So running your A II where your date is being generated is a good first principle. And for a lot of folks they still have a lot on premise data. That's where their systems are they're generating the systems, or it's a consolidation point from the edge or other other opportunities to run it there. So that's where your date is. Run your A I there. The second thing is about giving people flexibility. We've both made pretty big investments in the world of containerized software applications. Those things are things that can run on grammar in the cloud. So trying to use a consistent set of infrastructure and software and tooling that allows people to migrate and change over time, I think, is an important strategy not only for us but also for the end users that gives them flexibility. >> So, ideally, on Prem versus Cloud implementations shouldn't be. That shouldn't be different. Be great. It would be identical. But are they today? >> So at the lowest level, there's always technical differences, but at the layers that customers are using it, we run one software stack no matter where you're running. So if it's on one of our combined R E systems, whether it's in a cloud provider, it's the same in video software stack from our lowest end consumer of rage. He views, too. The big £350 dejected too you see back there? You know, we've got one software stack runs everywhere, And when the riders making you know, it's really Renee I where your data is And while a lot of people, if you are cloud native company, if you started that way, I'm gonna tell you to run in the cloud all day long. But most enterprises, they're some of their most valuable data is still sitting on premise. They've got decades of customer experience. They've got decades of product information that's all running in systems on Prem. And when you look at speech, speech is the biggest thing you know. They've got, you know, years of call center data that's all sitting in some offline record. What am I gonna do with that? That stuff's not in the cloud. And so you want to move the processing to that because it's impossible to move that data somewhere else and transform it because you're only gonna actually use a small fraction of that data to produce your model. But at the same time, you don't want to spend a year moving that data somewhere to process it back the truck up, put some DJ X is in front of it. And you're good to go. >> Someone's gonna beat you to finding those insides. Right? So there is no time. >> So you have another question. >> I have the last question. So you got >> so in video, you gotta be Switzerland in this game. So I'm not gonna ask you this question. But, Brian, I will ask you what? Why? You're different. I know you were first. He raced out. You got the press release out first. But now that you've been in the market for a while what up? Yours? Competitive differentiators. >> You know, there's there's really two out netted out for flash played on why we think it's a great fit for an A i N A. I use case. One is the flexibility of the performance. We call multi dimensional performance, small files, large files, meditated intensive workloads. Flash blade can do them all. It's a it's a ground up design. It's super flexible on performance. And but also more importantly, I would argue simplicity is a really hallmark of who we are. It's part of the modern date experience that we're talking about this morning. You can think about the systems. They are miniaturized supercomputers And yes, you could always build a supercomputer. People have been doing it for decades. Use Ph. D's to do it and, like most people, don't want to happen. People focused on that level of infrastructure, so we've tried to give incredible kind of capabilities in a really simple to consume platform. I joke with people. We have storage PhDs like literally people. Be cheese for storage so customers don't have to. >> Charlie, feel free to chime in on your favorite child if you want. I >> need a lot of it comes from our customers. That's how we first started with pure is our joint customers saying we need this stuff to work really fast. They're making a massive investment with us and compute. And so if you're gonna run those systems at 100% you need storage. The confusion, you know, pure is our first in there. There are longest partner in this space, and it's really our joint customers that put us together and, you know, to some extent, yes, we are Switzerland. You know, we love all of our partners, but, you know, we do incredible work with these guys all up and down the stack and that's the point to make it simple. If the customer has data we wanted to make be a simplest possible for them to run a ay, whether it's with my stuff with our cloud stuff, all of our partners, but having that deep level of integration and having some of the same shared beliefs to just make stuff simple so people can actually get value out of the data have I t get out of the way so Data scientists could just get their work done. That's what's really powerful about the partnership. >> And I imagine you know, we're out of time, but I imagine to be able to do this at the accelerated pace accelerated, I'm gonna say pun intended it wasn't but, um, cultural fed has to be pretty align. We know Piers culture is bold. Last question, Brian and we bring it home here. Talk to us about how the cultural cultures appearing and video are stars I lining to be able to enable how quickly you guys are developing together. >> Way mentioned the simplicity piece of it. The other piece that I think has been a really strong cultural fit between the companies. It's just the sheer desire to innovate and change the world to be a better place. You know, our hallmark. Our mission is to make the make the world a better place with data. And it really fits with the level of innovation that obviously the video does so like to Silicon Valley companies with wicked smart folks trying to make the world a better place, It's It's really been a good partnership. >> Echo that. That's just, you know, the rate of innovation in a I changes monthly. So if you're gonna be a good partner to your customers, you gotta change Justus fast. So our partnership has been great in that space. >> Awesome. Next time, we're out of time, But next time, come back, talk to a customer, really wanna understand it, gonna dig into some of the great things that they're extracting from you guys. So, Charlie Brian, thank you for joining David me on the Cube this afternoon. Thanks. Thanks. Thanks for David. Dante. I'm Lisa Martin. You're watching the Cube. Y'all from pure accelerate in Austin, Texas.

>> Las Vegas. Extensive signal from the noise. It's the Q covering interconnect 2016. Brought to you by IBM. Now your host, John Hurry and Dave Ilan. >> Okay, Welcome back, everyone. We are here live in Las Vegas for exclusive coverage of IBM interconnect 2016. This is Silicon Angles. The Q. That's our flagship program. We go out to the events and extract the signal from the noise. I'm John Ferrier with my Coast Day Volante. Our next guest, Steve Robinson News. The GM of client technical engagement before that, in the cloud doing all the blue mix now has the army of technical soldiers out there doing all the action because it's so much robust. So much demand for horizontally scale. The sluices with vertically targeted, prepackaged application development. That's horrible. First you name it big data. Welcome back. Good to see you, John. Thanks. Good to be with you again. Always, like great to have you on because you got a great perspective. You understand the executive viewpoint. A 20 mile stare in the industry. But also you got the in the nuts and bolts in under the hood. >> That's right. A >> lot of action happening under the hood. So let's get that right away. Blue, Mrs Hot Night. Now it's about the developers. What's going on under the hood right now that customers are caring about? >> I always love the Cube. You guys were like one of the first guys talking to us two years ago when we just launched a blue makes on stage. We walked off, got in front of cameras here, and it was great. Over the past year, it's been it's been outstanding. We we're writing about 20,000 folks toe blue mix right now on public, we came out with dedicated and then what people had really been warning was local blue mix as well. So we finally have full hybrid chain that goes from behind the firewall to a single client dedicated cloud all the way up to the public as well. So we've been building that out with service is as well, so have over 106 service is on top of it. You'll see things like Watson, which is unique, our Dash CB analytics, which is unique Internet of things coming in as well. So it's been a great year old building it out and getting more clients on top of it, >> it's like really trying to change the airplane engine in 30,000 feet. Or, in your case, you guys were taken off and from the runway. How has that been? It's been growing pains, of course. Unlearning What? What's going on? What have you learned? Give us the update on >> changing the engine while the plane is flying, and we've used that analogy quite a bit in the labs and way have to show relevance in this market. You know, this market is probably the fastest face technical market I think I've ever been in, and it's moving at such a rapid pace. We had to ship a lot of technology out last year is well, we have every new middleware group in IBM. Putting service is on top of blue mix, so let's get it out there. Let's get it out fast. Now, of course, this year we're gonna harden it up a little bit as well. So more architectures, more points of view. Better look on how this stuff works together hardening up our container strategy, pulling it all the way back to the virtual machine. So both continue to expand it out but let's make it enterprise grade at the same time. >> And also, some differentiation with Watts has been a big play around Catnip. Yeah, really is different because right now with the quote, um, market the way it is court monetization is on number one's mind. Start from startups to enterprises. If you're in business, you want you're top line if you're starting to get monetization. So there's a little bit of IBM in here for people to take in. Well, >> you know, if you look at Watson, you know, when we first started with it, you know, it was this very large big chunk of software that she had to buy. And and we work with Mike Rodents Team toe. Can we chop it up into a set of service is Let's really make this a set of AP eyes, and we started noticing, you know, you saw in Main stage the other day out from Otis. You know, this was a pure startup. He's started picking up the social semantics. Let's pick up the you know, some of the works to text etcetera, conversions, and all of a sudden they're starting to add it in. They said they would have never had access to this technology before way Have that a P I said. Not growing up to 28 we announced a couple cool things this morning. We even showed how would improve your dating life. Probably need some of that with my wife is well to translate between the sexes there, but what people are doing with it now, it's kind of like blowing people. His mind is far beyond what the initial exception waas. >> So your team of your niche is when they get right. It's a large team. It's, but it's a new initiative. New Justice unit, New role for you Talk about that >> way. Kinda had >> a couple pockets of this, but way clearly found that getting clients to the cloud is both a technology challenge as well as a cultural challenge as well. So he brought together some technical experts to kind of help through that entire life chain help up front. You know, many clients are trying to figure out what their overall cloud strategy is, where they truly today and where do they want to get to be? And how can we help him with a road map? That kind of helps them through the transition. Many accounts are very comfortable with the only wanting to be private and only glimpsing forward Thio Public Cloud Helping us bridge across that as well. Then we have the lab service's teams and these air the rial ninjas, the Navy seals. They go as low as you can go and what they're helping. A good way. Yeah, that's good. That's good. That's why they're helping with this very specific technical issue. Technical deployments. A lot of our dedicated local environment. These guys, they're they're really helping it wire in a cz Well, and then we have the garages, you know, we're up Thio. Five of those were going. We announced four new Blockchain garages as well. And this is where firms air coming in to kind of explore do the innovative type project as well. So I think all the way from the initial inception through rolling it out into production, having that team to be able to support him across the >> board. And so this capability existed in IBM previously, But it existed in a sort of bespoke fashion that coordinated >> couple pockets here and there. We always have supports. We had various pockets a lap service's. But we won't really wanna have the capability of seeing that client all the way through their journey, bringing it all under me. We now can easily pass the baton, Handoff says. We need to have that consistent skill there with the clients all the way through their >> journey and is the What's the life cycle of these service is? Is it Is it both pre sales in and post there? Just posted >> many times we'll get involved like our cloud advisers would get involved. Presale. They'll say a specific workload wants to go to the cloud. What are the steps we need to take to make that happen? A CZ well, with our Laps Service's teams, you know, we kind of have, you know, anywhere from a 4 to 6 week engagement. Thio do a specific technology. Let's get it in place. Let's get it wired in et cetera, and then in the garage is you know, we could just take a very novel idea and get it up to, ah, minimal viable product in about a six week period. So again, we're not doing dance lessons for life but strategically placing key skills in with accounts toe. Help him get over that next hump of their journey. >> Steve, when you look at the spectrum from from public all the way down to private and everything in between are you, I wonder if you could describe the level of capability that you are able to achieve with the best practice on Prem with regard to cloud ability. It's service is all the wonderful attributes of child that we've come to know and love. Are you able to, you know, somewhat replicate that roughly replicate that largely replicate, exactly. Replicate that. Where are we today? >> Yeah, I think >> it's a great question. I think. You know, I think most of the clients that we're dealing with have been dealing with some virtualized infrastructure, probably more VMC as they as they've been kind of progressing. That story. One of the things we did it IBM is Could we bring a true cloud infrastructure back behind the firewall? Could we bring an open stack? We bring a cloud foundry base past all the way back through because the goal, of course, is if we could have the same infrastructure private, dedicated and public as they continue to grow and got more comfortable with the public cloud that could start taking work clothes that they had built in one location and start to migrate it out with you. That that local cloud the Maur used for EJ cases. So taking that system of record and building a p i's and allowing to do extensions to that allowing you access into data records that you have today dealing with a lot of extension type cases, you know the core application still needs to be federally regulated. It needs to be under compliance domain. It's gotta be under audit. But maybe I wantto connect it in with a Fitbit or connected in with with a lot Soon are connected in with the Internet of things sensor. I gotta go public cloud for that as well. So locally we can bring that same infrastructure in and then they could doom or service. Is that extended out in the hybrid scenario >> code basis? Because this has come up. Oracle claims this is their big claim to fame. That code base is the same on premise hybrid public. Is that an issue with that? Is that just their marketing, or does it matter what's IBM take on this? >> But we've done ah lot of work with the open standard communities to let's get to a true reference implementation. So on open Stack, we've been doing a lot of work with them, and this is one of the reasons we picked up the Blue box acquisition. Could we really provide a standard open stack locally and also replicate that dedicated and, of course, have it match a reference architecture in public as well? We've also done the same thing with clout. Foundry worked with Sam Ram G to be one of the first vendors, have a certified cloud. Foundry instance is the same local dedicated in public. I think that's kind of the Holy Grail. If you could get the same infrastructural base across all, three, magic can happen. >> But management's important and integration piece becomes the new complexity. I mean, I would say it sounds easy, but it's really hard. Okay, developing in the clouds. Easy, easier ways always used to be right, right well, but not for large enterprises. The integration becomes that new kind of like criteria, right? That separates kind of the junior from the senior type players. I mean do you see the same thing and what we believe >> we do? I think there's usually two issues. We start to see that this model looks great. Let's have the same code base across all three environments. What things? We noticed that a lot of folks, when you get into Private Cloud, had tried to roll their own. You know, open Stack is an open source Project clout. Foundry is an open source project. Let's pull it down and let's see units roll it out and manage it ourselves. These air a little bit you they're very dynamic environments, and they're also a bit punishing if you don't stay current with them, both of them update on a very regular basis. And we found a lot of firms once they applied tenor well, folks to it, they just could not keep up with the right pace of change. So when the technologies we invented was a notion called relay on, this allowed us to actually to use the public cloud is our master copy and then we could provide updates to get down to the dedicated environment and down to the local. This takes the headache completely away from the firm's on trying to keep that local version current. It's not manage service, but it's kind of a new way that we can provide manage patches down to that environment. >> So one of the problems we hear in our community is and presume IBM has some visibility on this. I'm thinking about last year, John, we're at the IBM Z announcement in January, rose 1,000,000 company talked a lot about bringing transaction analytic capabilities together. But one of the problems that our community has practitioners in our community course the data for analytics. A lot of it's in the cloud and a lot of transaction data sitting, you know, on the mainframe, something. How do they bring those two together? Do I remove the data into the data center? Do I do I move pieces in how you see >> we're seeing a lot of that. A lot of it was. Bring the technology down to where the data is, and and now you know the three amount of integration you can do with public data sources, private data sources, et cetera. We're seeing a lot more of the compute want to go out to the cloud as well. You know, we've done some things like around the dash, CB Service's et cetera, where I can start to extract some of that transactional data, but maybe only need a few pieces to really make the data set. That is important to me as I move it out, so I can actually, you know, extract that record. I can actually mask it into being something brand new, and then I could minute we mix it with public data tohave. It do brand new things as well, so I think you're gonna see a lot of dynamic capability across that with or cloud computing technologies coming back behind the firewall and then more ability to release that data be intermixed with public data as well. >> What's the number one thing that you're seeing from customers that you guys were executing on? There's always the low hanging fruit for the easy winds from bringing a team of street team, if you will out. Technical service is out to clients where they really putting that gather, not their five year plans, but their one year. Of course, there's a lot of that agile going on right now. New technologies. You can't isolate one thing and break everything. Za new model. What a customer is caring about, right? What's that? What's the common thing? I think >> over there in 2015 I think the discussion changed and went from Are we going to go to the cloud or we're going to the cloud now? How are we going to do it? And the nice thing about I think a lot of enterprise architecture groups kind of took a step back to say, What do we truly have to do? What is a common platform? What is an integration layer? How do we take some of our old applications and decomposed those into a set of AP eyes? How can we then mix that with public AP eyes? So probably taking one or two projects to be proof points so they could say, this thing really has the magic associated with it. We can really build stuff fast. If we do it the right way, it's gonna be in a catalyst to have the I t. Organization now take the tough steps in what's gonna be the commonality? What common service is are we going to use and how do we start breaking up >> around things you know, we have our own data science and our backcourt operation and one of the things that we always looked at with bloom. It's way start our Amazon. But now, with blue mix, you have a couple things kind of coming together in real time. You said it's getting hard, but those hardened areas are important identity. For instance, where's the data is an instruction and structure. I want a little mongo year or something over there, but with blue mix and compose, I oh, really has a nice fit. I want to explain to the folks we talked before he came on about this new dynamic of composed Io and some of the things that are gluing around blue mix. Could you share this >> William Davis King right? And I think people look to the Cloud Data Service is air. Probably it's the most critical, the most visible, and the one we have to harden up the most is well, even though IBM has been well known for D. B two and we've been a >> wire composed right >> that we did Cognos first, and then we followed up with composed by you because recent waded about, we did compose. I know about eight months ago what we liked about it was all of your favorite flavors, you know? So your your progress, your mongo, you're you're ready. But really having it behave like Like what you would want an enterprise database to do. You can back it up. You can have multiple versions of it. We can replicate itself >> is a perfect cloud need of civic >> class. It has all the cloud properties to it and all the enterprise. Great capabilities with it. Yeah, we've got that now in public, and then you're gonna start seeing dedicated, and you want >> to go bare metal, Just go to soft layer. It's not required right on these things where this will work in the cloud, and then you get the bare metal object you want pushed up the bare metal. No problem. Well, I think >> you know it. Almost hybrid is not gonna get a new definition around it. So it's all gonna be around control and automation, more automation. You need to go all the way up to a cloud foundry where it's managing all the health, checking and keeping your apple. I've etcetera. If you want to go all the way down to bare metal so you can tune it audited et cetera. You can do that as well. I think I've got one of the broader spectrum, is there? >> I'm impressed with the composer. I got to say, Go ahead, get hotel Excited by what? I get excited by just about every way. Just love the whole Dev Ops has been just a game changer in extras. Code has been around for a while, but it's actually going totally mainstream. That's right. The benefits are just off the charts. With Mobile, we have the mobile first guys on. Earlier in the Swift, we had 10 made 12 year old kid. I mean, it's just really amazing. Now that the APS themselves aren't the discussion, it's the under the hood. That's right, so you can have an app look and feel like it's targeted for a vertical, say, retail or whatever. But the actions under the hood yeah, yeah, more than ever. Now >> it's, you know it's funny this year, you know, Dick Tino to the Devil Obsession yesterday and you're the amount of proof points we had around it last year. We were scrambling a little bit and this year it's just we always had to thin out. That's how many guys were having great success with this stuff is coming into its own. >> It totally is. And you guys are give you guys Props were running as fast as you can and you're working hard. And it's not just talk. Yeah, it's It's it's legit. I'm gonna ask you a question. What's the big learnings from last year? This year? What's happened? What do you look back and say? Wow, we really learned a lot or something that might have been Magda ified for you in this journey this past year. >> A lot of it goes back to, you know, this changing culture at IBM, you know, the amount of code we put out in two years was just just unbelievable. But I think also the IBM becoming a true cloud company. Some of that we did with our own shop some, but we did through injecting it with acquisitions. You know, like to compose Io the cloud and team, the blue box guys, et cetera. I think we got the chops now to play it play pro ball way worked very hard, Teoh. How many folks, Can we attract the blue mix? We're getting up to 20,000 week. Right now. We're starting. Get some great recognition and the successes are rolling in as well. So a lot of hard work and a lot of busted knuckles. A lot of guys are tired. Definitely, definitely straight in the game now. >> Ready for the crow bait? Taking the pro GameCube madness starts on cute madness. There were, you know, keep matched all the brackets of the Cube alumni and vote on it turns into a hack a phone because everyone stuffed the ballots. Let's talk about pro ball for next year, a CZ. You guys continue? Sure. The theme here obviously is developer. I mean, the show could be dedicated 100%. The blooming LeBlanc up there kind of going fast at the end of this booth on the clock anymore. Time >> right. Like the Star Wars trailer we had >> going up, he needed more time. So it's good props you got for this year. What's going on the road map this year? What if some of the critical goals that you guys see on your group and then just in general for the thing a >> lot of the activities were gonna be doing again is hardening the stack. I've got a brand new team now called a Solution Architecture, where we're looking at it from top to bottom, taking customer scenarios and really testing it out. How do you do? Back up. How do you do? Disaster recovery? How do you do? Multi geography, You know, things like PC I compliance. The rial enterprise problems are now coming to the class global and their global. And with security and compliance, they're changing in a very dynamic fashion. We have to show how you can do those in the cloud. You'd be amazed on how many conversations we have with Si SOS every single week. Is the cloud secure? How do we do enterprise? Great workloads. IBM is bringing that story to the cloud as well. That's the story of >> a potato that content >> Curation is unbelievable, right? That's the hardest part. And it's not that we have it fixed either. But you were doing more of aggregating it together so that we can really pull it all together. I call it the diamond Mine versus the jewelry store. You know, we always have really did you got yet? The great answers out there somewhere. But if you don't start to pull it together into a single place So one of things we did this year was launched the blue mixed garage methodology where we took all of our best practices. We took text test cases, even sample code, and brought it into a single methodology site where people start to go out, pull it down, use it, etcetera. Previously, we had it scattered all over the place, and we're gonna be doing more things like that. Bring in the assets to the programmers, things that we've tried, things we've tested being more open about it, putting in a single location. >> Well, we certainly would like to help promote that. Any kind of those kind of customer reference architectures. Happy to pump on silicon angle with the bond outlook for the vibe. I'm sorry. Five for the show things year. What's the vibe this year? You know, I think I've >> been very impressed with it, and I think, you know, I've been stepping up its game If you go down to the blue. Mixed garages are motives. A motorcycle on stage, you know, kind of getting a little more hip and happening as well. But I think the clients here and this is always about the customer stories and some of the things that we're hearing from the three guys start ups that are doing GPS logistical management 22 to the big accounts, and the big banks that you really see have embraced the cloud and doing great stories on it as well. I think people come to this show so they see what their peers were doing. And they definitely walk away with a sense that the cloud Israel it's happening and 2016. It is really going to driving it home. That has to be part of everybody. Strategy motorcycles I had put on the Harley Man. We'll take it for a spin guarantee. Come on down >> and give my wife. When I got married, it was terms of conditions. That's right. That's right. Last, Watson that Yeah, Thanks, Steve. Thanks. Taking the time and great to see you again. Congratulations. What? They get technical engagement team that you have all the work that you did that blue mix noted certainly by the cube. Congratulations and continued success with Loomis congratulating >> you guys. Well, always a pleasure. >> Okay. Cube Madness, March 15th Cube Gems go to Twitter. And speaking of jewelry, we have Cube gems hashtag Cube gems. That's the highlights of the videos up there. Real time. And, of course, we're gonna get that TV for all. All the action videos are up there right now. I'll be right back with more coverage after this short break here in Las Vegas.

>> live from San Francisco, California It's the queue at PM World 2014 Brought to you by VM where Cisco, E M, C, H P and Nutanix. Now, here are your hosts John Courier and Dave Ilan. Take >> Okay. Welcome back when live in San Francisco, California v m World 2014. This is the Cube where we extract the signal in the noise. I'm John for day. Volante are 50 year here Of'em world broadcasting wall to wall. Three days of live coverage. Our next guest, John Gill Martin, GM and VP of the Supper defined Data center business unit. Welcome to the Cube. >> Thank you. Glad to be here. >> Yeah. So this is an area. That may be mean. Streams. Not on top of what we love to geek out stuffing. Find data center Two years ago. Maybe three years. Feels like 10 years ago. See your acquisition and Martine's been on multiple times. Suffer. Virtualization really has set the agenda for what's going on in the data center. And remember, it was very much a buzzword. Std. See some fun data center. But now it's becoming a reality. I want first question get your perspective. Is Where is the meat on the bone right now. This year with somebody find designer. What is materializing right now in market that's available in happening >> has been fantastic, because if you think about our customers, they're all trying to move to this notion of self service. Cloud help the developers be more agile, be more productive and soft, defined clearly the right architecture to go do that. And the last year has really brought us the last couple of pieces to go. Make that a reality, Obviously never. Fertilization is a huge component. Delivery of NSX is really brought us a kind of leaps and bounds forward around that. The adoption of that has been great and then now a virtual sand as well, just to bring soft defined into the storage space. We were seeing a tremendous amount of interest. You take all of that, you fully virtualized your infrastructure, and then you bring management on top of that automate on top of that and really, now we have the ability building self service files inside the enterprise. Start to meet the meeting with developers, and you have this kind of a self service agile idea. >> It's almost as if you change in the airplane engine out at 30,000 feet with summer defined data center, people said on the Q bond. It's very difficult, but I want to get your perspective of where the pressure points of innovation are coming from coming from the APS service containers show the app, sir, setting the agenda were close. Now diversities another variable. It used to be the infrastructure would enable on top of it. Now we seem to be rushing down from the top, and this dynamic provisioning environment seems to be this DEV ops requirement all that's in place. So how do you how do you How do we talk about the innovation of the pressure point? What are those pressure >> points? Yeah, well, as you point out, it's really about the applications and the requirements of applications. And pushing down on the infrastructure, and in particular, is you look a kind of new style cloud native applications, which tend to be a bit different than traditional laps. They asking different things the infrastructure, and that's asking. Your developers are asking to do different things than necessarily what kind of fish in a lapse of required developers are looking for portability. They're looking for agility. They're looking for a difference that a tooling really. And you know they want that experience where they go to a website that Newton A P I and programmatically spin up infrastructure. And so that's really what enterprise like the organization's now our challenge to go Dio is to go provide that type of investor, actually support that for the helpers. Technology today is fundamental to the business model of every company out there. Used to just be about back office operations. Now it's really about the marketing organization, the sales organization, product development organizations. Every part of the business depends on technology is changing business models, and therefore this is really what's asking Iike organizations to be much more responsive and to do a lot more than they initially ever have in the past to support the business, to move >> quickly. So in terms of network organization, So how much is that? A part of this new model >> in our virtual station? Cooley a critical component to this right and, you know, a super interesting. When we first brought out NSX last year, a lot of value proposition was around the speed agility. And if you look at the big cloud providers, you like the big financial firms. That was the kind of primary motivation. Initially, we still see that a lot. It's been interesting, though, the last year to start to see the value proposition for network organization really shift. And if you're looking more than mainstream now, it's really a lot about this notion of micro segmentation. This notion of how do I bring security from that used to just be in the perimeter and start to bring that inside the data center. And that's been driving a lot of the interest and be able to get security controls all way down to the PM and the application >> itself. Just on Fridays. Pregame crowd shot we had Steve Perrin chimed in, Gone. The security question. I were the big opportunity for start ups, and he said Security. Yep, and it's really not about perimeter security anymore. It's about something else. Could you describe what he means by that icy perimeter? Security was the old way. Secure the perimeter. But people are getting in. Protect the queen with a moat. What does he mean by that? And why do you say that opportunities there? >> Yeah, that's the traditional model of security. The data center is you put up this big as you said moat around the data center, and you hope that no one get over that The problem was, if someone did, then it's all exposed on the inside it. And so the notion now is how do we bring security inside the data center? Protect those applications. But in order to do that, you know that traditional models were doing that, or just two operationally complex or too expensive just can't do it. Physical systems. So the beauty of never quit realization use and start to bring that in inside the data center, bring those security controls the BM and do so in with enough automation and policy based on mation that it's operationally feasible to manage. >> Well, what about the flip side of that? When the queen wants to leave her castle, >> how do >> you secure that use case? If I'm making sense and >> I'm not sure I understand. >> So Okay, so you get queen being the data, let's say and the data by its very nature is distributed. Right? So, um, okay, protect the perimeter. That's that's not enough. Now I can go deeper inside the data center and provide tools to make it simpler to deploy. Or if Aiken, you know, find a problem faster toe to solve that problem. But it's the data starts to become dispersed. How do I create a security model on? Does this software defined data center Help me do that. Accommodate that dispersed data that distributed data model? >> Yeah, because I mean the great thing is as you bring security controls into software and set it in the hardware, then you can travel and be part of that application. And actually, as the application moves or the date of that application moves, you can tie the security policies. The application itself >> was an application centric data centers security model, >> and it's and it's a platform also that you know, an ecosystem is building on top of to go, bring even deeper set of security capabilities. And top of you talk about the startups you're talking about a second ago, you know, it's this whole platform doubted for innovation. On top of that, you could bring really interesting ways of thinking about new security. >> Two years ago, when Pat Gelsinger took over as the C E o m. C. Had a financial analyst meeting, and Pat was part of that of your new C C F O stood up and talked about tam on gave a really good Chris presentation run that. I'm sure you're seeing these slides a lot. We see them as analysts big, big opportunity for VM wear, and a huge part of that opportunity is the software to find data center. So I wanted to dig into that a little bit. Specifically, when I look at things like Tam, I say, Okay, what's the business case? Because the business case is gonna ultimately determine the degree of the rapidity of the adoption. So I want if you could talk about the business case for the software defined data center, maybe compare it to sort of phase one, which is, you know, virtualized compute. Yes, this case was enormous. It was a 10 X value proposition. Is this bigger? Similar, Smaller, twice as big when we could talk about a little bit. >> And when you say business case obviously thinking about from the customer perspective, >> Wellit's, either I'm gonna cut costs or I'm gonna create some other kind of incremental business value. Other. I'm gonna drive revenues. I'm gonna reduce cycle times or introduce the lap times timeto value, et cetera. >> Yes, that's the interesting thing is often find data centers really kind of hitting on all of those things where the key motivators is really moving faster and be able to reduce like a times instead of four weeks to deploy an application. Let's get it down to a couple of minutes. Let's be able to meet the needs of developers to do Dave off style soft development. So it's all about speed and kind of driving revenue from the back end. If you start to think about the operating expense and capital expense, so shoot with the infrastructure. You can start to address those pretty aggressively, you know, if you think about virtual sand, for example, it's all about a different operating model for deploying storage virtual machines, its applications centric and V M Central, and so you can reduce the amount of time that initiators of spending, managing infrastructure and get them focused on the energy and kind of applications. So, one way to address topics, or if you think about the capital expense, what we see now you've done quite a bit of analysis is by virtual izing network fertilizing storage you can actually get down to anywhere between I think it's 35 49% reduction in the total capital expense of building your data center. So really significant opportunities to reduce costs both on the operating expense side through automation, but also the capital expense side by moving more intelligence into the hardware itself so that just like with virtualization, if you go back, you know, 5 10 years virtualization was a very simple capital expense story here. Now, where we have a story that's well, much broader than that, but still inclusive all those kind of capital expense benefits. >> I gotta ask you about competition. Just chicken out. What's going on around the conversations? Um, obsolete VM where staking their claim out Amazon on one front. But Microsoft's a player in the enterprise. So what do you guys do? These of the Microsoft partner frenemy. They're in there and start stuff. Our players got plowed. So how do you guys look at those guys? You guys too far down S o. >> You know, with Microsoft? Yeah. At this point, we still are. Let's see ourselves. It's really kind of leading the way around sort of virtual ization. And that's really been the kind of core in the foundation which we started from, and we still have tremendous set of capabilities there. And so that's kind of a starting point. And then you build off on everything we're doing around network fertilization, everything you're doing around soft defined storage, really a very differentiated set of capabilities and your eyes really unique set of capabilities from be able to build that whole virtualized infrastructure, then your episode of management capabilities on that that are increasingly header genius in nature. And we have this ability to kind of extend the data center in unique ways, you know, managing automated here but extended after the cloud as well. So pretty powerful set of kind of technology. >> Car legend Box said that VM wears it is a data center automation company. Um, should he added orchestration to that, too, or talk about that. What is data center automation company mean? Because he's referring to the South to find a descent course cloud certainly is automation, orchestration and the cloud, but from your in your world What does that mean? >> Automation is really about taking a lot of the manual activities that United Administrator or anybody else who's spending time infrastructures does. And let's run that in software. And that's not tie ourselves to operations that are specific, proprietary pieces of hardware. Let's get to a model where everything could be automated through software. We could get the scalable models of deployments and operations naturally, what automation means. Automation then allows you to start to move at the speed of business rather than being tied to the kind of infrastructure in the hardware and everything else underneath. >> So the other quote from Carl was awesome, by the way. Great interview, he said. How glad the customers still on friend. Okay, I buy that you have a zillion customers, a lot of Amon prim. Why not private club or private cloud is today? Or his private cloud, the halfway house or a way station to the hybrid cloud? So talk about that dynamic. You know, summer defined data center at the end of the day could be software driven. The end of the day is still a data center. You still have a data center somewhere where the damn ploughed or on Prem talk about that on premise dynamic. Yeah, >> so, yeah. Ultimately, if you think about kind of hybrid Cloud hybrid Cloud is really the combination of assets that you own inside the data center, along with assets. They're sitting someplace else. And you know, the motivations for that are I want to be able to think about how do I optimized? I want to think about how Doe I optimize my choices, a placement for projects that are either short lived, etcetera. And so there's a set of applications or projects where makes sense to go rent capacity. But if you actually look at the total total cost of ownership inside the data center, you can actually get too much better economics by owning the assets yourself, building on top. So there's definitely a ongoing and continued rule for the private cloud. But there's a very clear you said the use cases for extending periodically into the hybrid cloud. So, really, you know, let's combine both of those that could boast best of both. So let's do that away that seamless. So we really treat the management. The operations of everything is the same, regardless of whether it's inside or outside, right? >> So I mean the buzzword. Bingos all getting resect is the new new new names Air coming out of that re naming convention? I gotta ask you about kind of specifically around the suite that Pat talks about talks with sweet. So I just don't understand how that parses out relative the hyper conversion and describe to the folks what is hyper converge. That's the new buzzword I know. I know. Hyper scale is a hyper scale with convergence. Is that Web scale? So what you guys to find hyper converged as hyper >> converged is, in our mind, really kind of the coming together of prescriptive hardware definition with software that's preinstalled on tightly integrated so that it's really easy to get to time to die So you could get up running virtual machines in less than 15 minutes and do that all with kind of a prescriptive design, guidance, prescriptive kind of price understanding and a single support organization that call and get support. If you need help on, that's really >> built definition right here, up and running with >> 15 minutes right and one of the key enabler. So that is the sphere and other key enablers virtual sand and really building all that and types of inside. One of these kind of off the show, >> called Converge, Prepackaged, converge on purpose, built, converged essentially. But that's where it's going, right? That would be me. That's >> where it's headed, right? And it's so it's really about making it easy for an organization to get up and running, get person machines deployed super quickly on, then be able to expand that in a building block way that's expand very quickly and easily. >> John Gill Martin is the V P and general manager. Somebody find business unit for the M. Where, um, tell the folks out there the last word he had in the segment. Um, what's the biggest misconception of summer defined data center in context? Of'em, where >> I think the biggest misconception is that it's something that's far into the future. The reality is this is something that people are doing today. Technology exists. We can build this, and you know this is the way in the architecture that everyone's headed down doors. >> And what's the one thing that you could share that they might not know about you guys? It's a very positive thing. >> Well, you know, I hopefully people saw all the announcements and work we're doing around open staff, for example, Really looking to bring these types of open a pea eye's been a neutral AP eyes on top of this soft to find platform. And yeah, that's a big news item for us. I wanna make sure that everybody saw that. It's a big part of Webber Head >> Open Stack and Dr Too Big Documents. Relevant news pieces exactly. Gives the app developers essentially access to infrastructure without being infrastructure. Guys. Right, that's fundamentally >> again helping enterprise guys set up in infrastructure that developers can access. Programmatically. That's >> John Gill Martin inside the Cube. We're here live in San Francisco for the emerald 2014. I'm John for what David wanted right back after this short break