(gentle synth music) (music ends) >> Welcome back to Supercloud 2, an open industry collaboration between technologists, consultants, analysts, and of course practitioners to help shape the future of cloud. At this event, one of the key areas we're exploring is the intersection of cloud and data. And how building value on top of hyperscale clouds and across clouds is evolving, a concept of course we call "Supercloud". And we're pleased to welcome our friends from Enterprise Technology research, Erik Bradley and Darren Brabham. Guys, thanks for joining us, great to see you. we love to bring the data into these conversations. >> Thank you for having us, Dave, I appreciate it. >> Yeah, thanks. >> You bet. And so, let me do the setup on what is Supercloud. It's a concept that we've floated, Before re:Invent 2021, based on the idea that cloud infrastructure is becoming ubiquitous, incredibly powerful, but there's a lack of standards across the big three clouds. That creates friction. So we defined over the period of time, you know, better part of a year, a set of essential elements, deployment models for so-called supercloud, which create this common experience for specific cloud services that, of course, again, span multiple clouds and even on-premise data. So Erik, with that as background, I wonder if you could add your general thoughts on the term supercloud, maybe play proxy for the CIO community, 'cause you do these round tables, you talk to these guys all the time, you gather a lot of amazing information from senior IT DMs that compliment your survey. So what are your thoughts on the term and the concept? >> Yeah, sure. I'll even go back to last year when you and I did our predictions panel, right? And we threw it out there. And to your point, you know, there's some haters. Anytime you throw out a new term, "Is it marketing buzz? Is it worth it? Why are you even doing it?" But you know, from my own perspective, and then also speaking to the IT DMs that we interview on a regular basis, this is just a natural evolution. It's something that's inevitable in enterprise tech, right? The internet was not built for what it has become. It was never intended to be the underlying infrastructure of our daily lives and work. The cloud also was not built to be what it's become. But where we're at now is, we have to figure out what the cloud is and what it needs to be to be scalable, resilient, secure, and have the governance wrapped around it. And to me that's what supercloud is. It's a way to define operantly, what the next generation, the continued iteration and evolution of the cloud and what its needs to be. And that's what the supercloud means to me. And what depends, if you want to call it metacloud, supercloud, it doesn't matter. The point is that we're trying to define the next layer, the next future of work, which is inevitable in enterprise tech. Now, from the IT DM perspective, I have two interesting call outs. One is from basically a senior developer IT architecture and DevSecOps who says he uses the term all the time. And the reason he uses the term, is that because multi-cloud has a stigma attached to it, when he is talking to his business executives. (David chuckles) the stigma is because it's complex and it's expensive. So he switched to supercloud to better explain to his business executives and his CFO and his CIO what he's trying to do. And we can get into more later about what it means to him. But the inverse of that, of course, is a good CSO friend of mine for a very large enterprise says the concern with Supercloud is the reduction of complexity. And I'll explain, he believes anything that takes the requirement of specific expertise out of the equation, even a little bit, as a CSO worries him. So as you said, David, always two sides to the coin, but I do believe supercloud is a relevant term, and it is necessary because the cloud is continuing to be defined. >> You know, that's really interesting too, 'cause you know, Darren, we use Snowflake a lot as an example, sort of early supercloud, and you think from a security standpoint, we've always pushed Amazon and, "Are you ever going to kind of abstract the complexity away from all these primitives?" and their position has always been, "Look, if we produce these primitives, and offer these primitives, we we can move as the market moves. When you abstract, then it becomes harder to peel the layers." But Darren, from a data standpoint, like I say, we use Snowflake a lot. I think of like Tim Burners-Lee when Web 2.0 came out, he said, "Well this is what the internet was always supposed to be." So in a way, you know, supercloud is maybe what multi-cloud was supposed to be. But I mean, you think about data sharing, Darren, across clouds, it's always been a challenge. Snowflake always, you know, obviously trying to solve that problem, as are others. But what are your thoughts on the concept? >> Yeah, I think the concept fits, right? It is reflective of, it's a paradigm shift, right? Things, as a pendulum have swung back and forth between needing to piece together a bunch of different tools that have specific unique use cases and they're best in breed in what they do. And then focusing on the duct tape that holds 'em all together and all the engineering complexity and skill, it shifted from that end of the pendulum all the way back to, "Let's streamline this, let's simplify it. Maybe we have budget crunches and we need to consolidate tools or eliminate tools." And so then you kind of see this back and forth over time. And with data and analytics for instance, a lot of organizations were trying to bring the data closer to the business. That's where we saw self-service analytics coming in. And tools like Snowflake, what they did was they helped point to different databases, they helped unify data, and organize it in a single place that was, you know, in a sense neutral, away from a single cloud vendor or a single database, and allowed the business to kind of be more flexible in how it brought stuff together and provided it out to the business units. So Snowflake was an example of one of those times where we pulled back from the granular, multiple points of the spear, back to a simple way to do things. And I think Snowflake has continued to kind of keep that mantle to a degree, and we see other tools trying to do that, but that's all it is. It's a paradigm shift back to this kind of meta abstraction layer that kind of simplifies what is the reality, that you need a complex multi-use case, multi-region way of doing business. And it sort of reflects the reality of that. >> And you know, to me it's a spectrum. As part of Supercloud 2, we're talking to a number of of practitioners, Ionis Pharmaceuticals, US West, we got Walmart. And it's a spectrum, right? In some cases the practitioner's saying, "You know, the way I solve multi-cloud complexity is mono-cloud, I just do one cloud." (laughs) Others like Walmart are saying, "Hey, you know, we actually are building an abstraction layer ourselves, take advantage of it." So my general question to both of you is, is this a concept, is the lack of standards across clouds, you know, really a problem, you know, or is supercloud a solution looking for a problem? Or do you hear from practitioners that "No, this is really an issue, we have to bring together a set of standards to sort of unify our cloud estates." >> Allow me to answer that at a higher level, and then we're going to hand it over to Dr. Brabham because he is a little bit more detailed on the realtime streaming analytics use cases, which I think is where we're going to get to. But to answer that question, it really depends on the size and the complexity of your business. At the very large enterprise, Dave, Yes, a hundred percent. This needs to happen. There is complexity, there is not only complexity in the compute and actually deploying the applications, but the governance and the security around them. But for lower end or, you know, business use cases, and for smaller businesses, it's a little less necessary. You certainly don't need to have all of these. Some of the things that come into mind from the interviews that Darren and I have done are, you know, financial services, if you're doing real-time trading, anything that has real-time data metrics involved in your transactions, is going to be necessary. And another use case that we hear about is in online travel agencies. So I think it is very relevant, the complexity does need to be solved, and I'll allow Darren to explain a little bit more about how that's used from an analytics perspective. >> Yeah, go for it. >> Yeah, exactly. I mean, I think any modern, you know, multinational company that's going to have a footprint in the US and Europe, in China, or works in different areas like manufacturing, where you're probably going to have on-prem instances that will stay on-prem forever, for various performance reasons. You have these complicated governance and security and regulatory issues. So inherently, I think, large multinational companies and or companies that are in certain areas like finance or in, you know, online e-commerce, or things that need real-time data, they inherently are going to have a very complex environment that's going to need to be managed in some kind of cleaner way. You know, they're looking for one door to open, one pane of glass to look at, one thing to do to manage these multi points. And, streaming's a good example of that. I mean, not every organization has a real-time streaming use case, and may not ever, but a lot of organizations do, a lot of industries do. And so there's this need to use, you know, they want to use open-source tools, they want to use Apache Kafka for instance. They want to use different megacloud vendors offerings, like Google Pub/Sub or you know, Amazon Kinesis Firehose. They have all these different pieces they want to use for different use cases at different stages of maturity or proof of concept, you name it. They're going to have to have this complexity. And I think that's why we're seeing this need, to have sort of this supercloud concept, to juggle all this, to wrangle all of it. 'Cause the reality is, it's complex and you have to simplify it somehow. >> Great, thanks you guys. All right, let's bring up the graphic, and take a look. Anybody who follows the breaking analysis, which is co-branded with ETR Cube Insights powered by ETR, knows we like to bring data to the table. ETR does amazing survey work every quarter, 1200 plus 1500 practitioners that that answer a number of questions. The vertical axis here is net score, which is ETR's proprietary methodology, which is a measure of spending momentum, spending velocity. And the horizontal axis here is overlap, but it's the presence pervasiveness, and the dataset, the ends, that table insert on the bottom right shows you how the dots are plotted, the net score and then the ends in the survey. And what we've done is we've plotted a bunch of the so-called supercloud suspects, let's start in the upper right, the cloud platforms. Without these hyperscale clouds, you can't have a supercloud. And as always, Azure and AWS, up and to the right, it's amazing we're talking about, you know, 80 plus billion dollar company in AWS. Azure's business is, if you just look at the IaaS is in the 50 billion range, I mean it's just amazing to me the net scores here. Anything above 40% we consider highly elevated. And you got Azure and you got Snowflake, Databricks, HashiCorp, we'll get to them. And you got AWS, you know, right up there at that size, it's quite amazing. With really big ends as well, you know, 700 plus ends in the survey. So, you know, kind of half the survey actually has these platforms. So my question to you guys is, what are you seeing in terms of cloud adoption within the big three cloud players? I wonder if you could could comment, maybe Erik, you could start. >> Yeah, sure. Now we're talking data, now I'm happy. So yeah, we'll get into some of it. Right now, the January, 2023 TSIS is approaching 1500 survey respondents. One caveat, it's not closed yet, it will close on Friday, but with an end that big we are over statistically significant. We also recently did a cloud survey, and there's a couple of key points on that I want to get into before we get into individual vendors. What we're seeing here, is that annual spend on cloud infrastructure is expected to grow at almost a 70% CAGR over the next three years. The percentage of those workloads for cloud infrastructure are expected to grow over 70% as three years as well. And as you mentioned, Azure and AWS are still dominant. However, we're seeing some share shift spreading around a little bit. Now to get into the individual vendors you mentioned about, yes, Azure is still number one, AWS is number two. What we're seeing, which is incredibly interesting, CloudFlare is number three. It's actually beating GCP. That's the first time we've seen it. What I do want to state, is this is on net score only, which is our measure of spending intentions. When you talk about actual pervasion in the enterprise, it's not even close. But from a spending velocity intention point of view, CloudFlare is now number three above GCP, and even Salesforce is creeping up to be at GCPs level. So what we're seeing here, is a continued domination by Azure and AWS, but some of these other players that maybe might fit into your moniker. And I definitely want to talk about CloudFlare more in a bit, but I'm going to stop there. But what we're seeing is some of these other players that fit into your Supercloud moniker, are starting to creep up, Dave. >> Yeah, I just want to clarify. So as you also know, we track IaaS and PaaS revenue and we try to extract, so AWS reports in its quarterly earnings, you know, they're just IaaS and PaaS, they don't have a SaaS play, a little bit maybe, whereas Microsoft and Google include their applications and so we extract those out and if you do that, AWS is bigger, but in the surveys, you know, customers, they see cloud, SaaS to them as cloud. So that's one of the reasons why you see, you know, Microsoft as larger in pervasion. If you bring up that survey again, Alex, the survey results, you see them further to the right and they have higher spending momentum, which is consistent with what you see in the earnings calls. Now, interesting about CloudFlare because the CEO of CloudFlare actually, and CloudFlare itself uses the term supercloud basically saying, "Hey, we're building a new type of internet." So what are your thoughts? Do you have additional information on CloudFlare, Erik that you want to share? I mean, you've seen them pop up. I mean this is a really interesting company that is pretty forward thinking and vocal about how it's disrupting the industry. >> Sure, we've been tracking 'em for a long time, and even from the disruption of just a traditional CDN where they took down Akamai and what they're doing. But for me, the definition of a true supercloud provider can't just be one instance. You have to have multiple. So it's not just the cloud, it's networking aspect on top of it, it's also security. And to me, CloudFlare is the only one that has all of it. That they actually have the ability to offer all of those things. Whereas you look at some of the other names, they're still piggybacking on the infrastructure or platform as a service of the hyperscalers. CloudFlare does not need to, they actually have the cloud, the networking, and the security all themselves. So to me that lends credibility to their own internal usage of that moniker Supercloud. And also, again, just what we're seeing right here that their net score is now creeping above AGCP really does state it. And then just one real last thing, one of the other things we do in our surveys is we track adoption and replacement reasoning. And when you look at Cloudflare's adoption rate, which is extremely high, it's based on technical capabilities, the breadth of their feature set, it's also based on what we call the ability to avoid stack alignment. So those are again, really supporting reasons that makes CloudFlare a top candidate for your moniker of supercloud. >> And they've also announced an object store (chuckles) and a database. So, you know, that's going to be, it takes a while as you well know, to get database adoption going, but you know, they're ambitious and going for it. All right, let's bring the chart back up, and I want to focus Darren in on the ecosystem now, and really, we've identified Snowflake and Databricks, it's always fun to talk about those guys, and there are a number of other, you know, data platforms out there, but we use those too as really proxies for leaders. We got a bunch of the backup guys, the data protection folks, Rubric, Cohesity, and Veeam. They're sort of in a cluster, although Rubric, you know, ahead of those guys in terms of spending momentum. And then VMware, Tanzu and Red Hat as sort of the cross cloud platform. But I want to focus, Darren, on the data piece of it. We're seeing a lot of activity around data sharing, governed data sharing. Databricks is using Delta Sharing as their sort of place, Snowflakes is sort of this walled garden like the app store. What are your thoughts on, you know, in the context of Supercloud, cross cloud capabilities for the data platforms? >> Yeah, good question. You know, I think Databricks is an interesting player because they sort of have made some interesting moves, with their Data Lakehouse technology. So they're trying to kind of complicate, or not complicate, they're trying to take away the complications of, you know, the downsides of data warehousing and data lakes, and trying to find that middle ground, where you have the benefits of a managed, governed, you know, data warehouse environment, but you have sort of the lower cost, you know, capability of a data lake. And so, you know, Databricks has become really attractive, especially by data scientists, right? We've been tracking them in the AI machine learning sector for quite some time here at ETR, attractive for a data scientist because it looks and acts like a lake, but can have some managed capabilities like a warehouse. So it's kind of the best of both worlds. So in some ways I think you've seen sort of a data science driver for the adoption of Databricks that has now become a little bit more mainstream across the business. Snowflake, maybe the other direction, you know, it's a cloud data warehouse that you know, is starting to expand its capabilities and add on new things like Streamlit is a good example in the analytics space, with apps. So you see these tools starting to branch and creep out a bit, but they offer that sort of neutrality, right? We heard one IT decision maker we recently interviewed that referred to Snowflake and Databricks as the quote unquote Switzerland of what they do. And so there's this desirability from an organization to find these tools that can solve the complex multi-headed use-case of data and analytics, which every business unit needs in different ways. And figure out a way to do that, an elegant way that's governed and centrally managed, that federated kind of best of both worlds that you get by bringing the data close to the business while having a central governed instance. So these tools are incredibly powerful and I think there's only going to be room for growth, for those two especially. I think they're going to expand and do different things and maybe, you know, join forces with others and a lot of the power of what they do well is trying to define these connections and find these partnerships with other vendors, and try to be seen as the nice add-on to your existing environment that plays nicely with everyone. So I think that's where those two tools are going, but they certainly fit this sort of label of, you know, trying to be that supercloud neutral, you know, layer that unites everything. >> Yeah, and if you bring the graphic back up, please, there's obviously big data plays in each of the cloud platforms, you know, Microsoft, big database player, AWS is, you know, 11, 12, 15, data stores. And of course, you know, BigQuery and other, you know, data platforms within Google. But you know, I'm not sure the big cloud guys are going to go hard after so-called supercloud, cross-cloud services. Although, we see Oracle getting in bed with Microsoft and Azure, with a database service that is cross-cloud, certainly Google with Anthos and you know, you never say never with with AWS. I guess what I would say guys, and I'll I'll leave you with this is that, you know, just like all players today are cloud players, I feel like anybody in the business or most companies are going to be so-called supercloud players. In other words, they're going to have a cross-cloud strategy, they're going to try to build connections if they're coming from on-prem like a Dell or an HPE, you know, or Pure or you know, many of these other companies, Cohesity is another one. They're going to try to connect to their on-premise states, of course, and create a consistent experience. It's natural that they're going to have sort of some consistency across clouds. You know, the big question is, what's that spectrum look like? I think on the one hand you're going to have some, you know, maybe some rudimentary, you know, instances of supercloud or maybe they just run on the individual clouds versus where Snowflake and others and even beyond that are trying to go with a single global instance, basically building out what I would think of as their own cloud, and importantly their own ecosystem. I'll give you guys the last thought. Maybe you could each give us, you know, closing thoughts. Maybe Darren, you could start and Erik, you could bring us home on just this entire topic, the future of cloud and data. >> Yeah, I mean I think, you know, two points to make on that is, this question of these, I guess what we'll call legacy on-prem players. These, mega vendors that have been around a long time, have big on-prem footprints and a lot of people have them for that reason. I think it's foolish to assume that a company, especially a large, mature, multinational company that's been around a long time, it's foolish to think that they can just uproot and leave on-premises entirely full scale. There will almost always be an on-prem footprint from any company that was not, you know, natively born in the cloud after 2010, right? I just don't think that's reasonable anytime soon. I think there's some industries that need on-prem, things like, you know, industrial manufacturing and so on. So I don't think on-prem is going away, and I think vendors that are going to, you know, go very cloud forward, very big on the cloud, if they neglect having at least decent connectors to on-prem legacy vendors, they're going to miss out. So I think that's something that these players need to keep in mind is that they continue to reach back to some of these players that have big footprints on-prem, and make sure that those integrations are seamless and work well, or else their customers will always have a multi-cloud or hybrid experience. And then I think a second point here about the future is, you know, we talk about the three big, you know, cloud providers, the Google, Microsoft, AWS as sort of the opposite of, or different from this new supercloud paradigm that's emerging. But I want to kind of point out that, they will always try to make a play to become that and I think, you know, we'll certainly see someone like Microsoft trying to expand their licensing and expand how they play in order to become that super cloud provider for folks. So also don't want to downplay them. I think you're going to see those three big players continue to move, and take over what players like CloudFlare are doing and try to, you know, cut them off before they get too big. So, keep an eye on them as well. >> Great points, I mean, I think you're right, the first point, if you're Dell, HPE, Cisco, IBM, your strategy should be to make your on-premise state as cloud-like as possible and you know, make those differences as minimal as possible. And you know, if you're a customer, then the business case is going to be low for you to move off of that. And I think you're right. I think the cloud guys, if this is a real problem, the cloud guys are going to play in there, and they're going to make some money at it. Erik, bring us home please. >> Yeah, I'm going to revert back to our data and this on the macro side. So to kind of support this concept of a supercloud right now, you know Dave, you and I know, we check overall spending and what we're seeing right now is total year spent is expected to only be 4.6%. We ended 2022 at 5% even though it began at almost eight and a half. So this is clearly declining and in that environment, we're seeing the top two strategies to reduce spend are actually vendor consolidation with 36% of our respondents saying they're actively seeking a way to reduce their number of vendors, and consolidate into one. That's obviously supporting a supercloud type of play. Number two is reducing excess cloud resources. So when I look at both of those combined, with a drop in the overall spending reduction, I think you're on the right thread here, Dave. You know, the overall macro view that we're seeing in the data supports this happening. And if I can real quick, couple of names we did not touch on that I do think deserve to be in this conversation, one is HashiCorp. HashiCorp is the number one player in our infrastructure sector, with a 56% net score. It does multiple things within infrastructure and it is completely agnostic to your environment. And if we're also speaking about something that's just a singular feature, we would look at Rubric for data, backup, storage, recovery. They're not going to offer you your full cloud or your networking of course, but if you are looking for your backup, recovery, and storage Rubric, also number one in that sector with a 53% net score. Two other names that deserve to be in this conversation as we watch it move and evolve. >> Great, thank you for bringing that up. Yeah, we had both of those guys in the chart and I failed to focus in on HashiCorp. And clearly a Supercloud enabler. All right guys, we got to go. Thank you so much for joining us, appreciate it. Let's keep this conversation going. >> Always enjoy talking to you Dave, thanks. >> Yeah, thanks for having us. >> All right, keep it right there for more content from Supercloud 2. This is Dave Valente for John Ferg and the entire Cube team. We'll be right back. (gentle synth music) (music fades)

>> from Austin, Texas. It's Theo Cube, covering your storage. Accelerate 2019. Brought to you by pure storage. >> Welcome to Austin, Texas. This is the Cube. Live at the fourth annual pure accelerate. I'm Lisa Martin with David, Dante, Dave or in Texas, >> Texas again. >> Austin, Texas. Very interesting venue for this fourth annual hear stories. >> A lot of construction, >> music, a >> lot of music. >> So we just came from the keynote and news announcements, customers on stage. But the first thing to point out is, this is here is about to celebrate their 10th anniversary. Charlie Giancarlo, CEO and chairman who's coming on the program with us, and just a few minutes talking about what they have innovated and delivered these 10 X improvements and 10 years kind of this overnight success in 10 years and what's coming? What was with the things that really stuck out at you, Nicky Note. >> Well, first of all, ironically, this is the 10th year of the Cube, not our 10th anniversary, but it's the 10th year of doing the Cube. And so our fourth year, I think it's pure accelerate about what 3000 people here, >> you know, the keynotes >> pure was laying out what their vision is of the modern data experience and that I felt like the keynotes least there were sort of, ah, speed date of what's coming. There was a couple of major announcements that we'll talk about, >> Uh, but >> they really are trying to differentiate as the modern storage company turn a deep position. The competition, as the old guard is to use this term that Andy Jassy uses pure, didn't use that term. But they really talked about it's time to go Modern. And so they were an overnight success. It took him 10 years, was one of the comments that was on stage. So I think this is worth pointing out. A couple of things. I mean, let me lay out. Sort of my thoughts on Pure is a company. They were the only storage company Ah, in the past. Let's call a decade to reach what I'll call escape velocity. They achieved a billion dollars a couple years ago. They're doing their due about a billion and 1/2 on a trailing 12 month basis. They'll do 1.7 billion this year and evaluations about 4.5 billion. So they got a a three ex valuation in that fluctuates. That's pretty good for a storage company. Billy on Lee major storage company. That's really growing rapidly. They got 28% growth. I did a breaking analysis on Lincoln, and I'll just share with you some of the numbers. Dallas flat at 0%. So Del is actually gaining share with no growth has got a scary NetApp minus 16% in the quarter H P E minus 3% IBM minus 21%. And so it is pure A 28%. So they're really crushing it in terms of growth. They've also got a 69% gross gross margin, even if it's in its heyday. E emcees gross margins weren't that high, you know. They were in the sort of mid sixties, and so, and they've also got a good balance sheet. About a billion dollars in cash A little. A little more than that, they got some debt. They're shifting their model to a deferred revenue model. Now the only thing is, you know they're growing much, much faster than the competition. But they're throwing off a lot less cash because they're much smaller. Just as an example, they probably throw off 5 to 6% of their revenues in cash. Netapp probably throws about 23% of its revenues, often catch the big Delta there, so the point is long winded. But but pure storage is in growth mode. And until the market rewards more consistent with a cash flow, they're gonna, I think, stay in huge growth mode. >> There was a great analysis. Dave and I saw an analysis that you did with some spends data, just a couple of your reverence. A little bit of that. There's there seems to be a tailwind behind here you mention the 28% wrote that they announced in Q two, and some of the things that also they talked about were there. Adding about in Q two of F Y 2020 about seven net new customers every business day, adding about 450 new customers just in that quarter. Like you said, 3000 folks expected here today. The momentum is behind them, but they're also a company of firsts. You talked about this a number of times. The first, with all flashed the first with envy me on the back and a couple of additional firsts announced today. Talk about the as a service model and how that youth, in your opinion, you think might continue that trajectory that they're on. >> Yes, so basically pure laid out today, said that vast majority are Pouliot Portfolio is gonna be available as a service. That's the cloud consumption mall is important because pure has about $600 million in deferred revenue, largely coming from their evergreen service. But there they are, slowly shifting their model to a subscription model. It's gonna be very interesting to see how that plays out. Um, we've seen a number of companies do a tableau in Adobe kind of pulled the band Aid off and did it Splunk has taken years to do. It will be interesting to see how how pure goes. For that. I'll >> bring it >> back to the cloud up yours largely an on Prem storage company. That's where most of the revenues come from. But we heard the gentleman from Amazon today. I think it was E ethan whiner, not Ethan, anyway, Mr Whiner, he said. That gardener did A survey last year showed 88% of customers said they have a cloud for a strategy, but 86% of those customers continue to spend on prim. So here you have the cloud. Amazon gorilla wants everybody to go to the cloud pure would much rather they make much more money on Prem? But they realize customers air pulling them in. So they have to move to that as a service model. One of the interesting things that pure is done, which, you know, that's not really a first. But it certainly is for the large storage companies they've announced. Ah, block storage on AWS. So basically what they're doing is they're taking the pure experience. It all looks like pure software, and they're front ending cheap s3 storage from Amazon with E. C. To compute instances, and they've architected using Amazon service. Is this basically a block storage array in the cloud so Amazon gets paid, pure, gets paid? It's a little bit of a premium, but you get higher availability. You get great right performance and you get the pure cloud experience pretty interesting strategy, >> and they're talking about it really as this. This positioning it rather as a bridge, a bridge to hybrid cloud. This numbers that the Amazon gentlemen, share that you mentioned Gardner were really interesting both sides recognizing there's a forcing function there and that forcing function is the customers from the enterprise to the small business who need to have data available immediately wherever it is people to extract this insights from it quickly so that those companies, whether it's a capital one or a Delta Airlines or a smaller organization, can act on it quickly to Dr Competitive Advantage. Same kind of challenge that your storage has. But really that forcing function of the customer, clearly bringing the giant AWS together with yet another story >> so pure as they say reached escape velocity. They and Nutanix were the only on a new entrance that reached a billion dollars Nutanix. I really don't consider a storage company. They're kind of hyper converged. And the way they did that as they drove a truck through E emcees install base with flash. So they were the first within all flash array. Maybe maybe they weren't the first, but they were the first to really drive it. They hired a bunch of DMC sales reps. They knew where all the skeletons were buried and they really took out a lot of old Symmetric Se's and Claire eons and V. Max is and all the old sort of GMC install base, and that helped them catapult their way there 1st 10 years. Now they got to do that again. They got to get to get They're on their way to two billion. But how did they get to five billion? Um, and and so the way they do that is they have to expand their tam. I mean, we'll talk to Charlie Jean Carlo about this. My feeling is a big job of the CEO is to expand the Tamil. How do they do that? They go after new workloads like a i. They go for cloud. They go from multi cloud. These are all very large markets in which they don't participate. Data protection. They'll partner with Lex, Kohi City and Rubric and Beam to to have data protection software running on their flash. A raise with very, very fast restores. That's something that's taking off. It's gonna be really interested in seeing as they say, they've got this subscription model that's coming in. They've got all this deferred revenue that in a way, it's going to slow him down a little bit just from an accounting standpoint, cause when you recognize deferred revenue, you recognize that, you know over 12 months over 36 months, so that's a little bit of a transition. The other thing that pure is facing in a tactical basis is Nande pricing. It's like this countervailing effects nan pricing is coming down, which means lower prices, lower costs but also lower revenue. But at the same time, it becomes more competitive with spinning disk. This is something else. We'll talk to Charlie Jean. Cholera right about it opens up new markets. So this tam expansion is critical for pure in terms of driving this modern data experience into these new workloads and fighting the competition, the competition is not sitting still. All those companies that I mentioned the H P ease, the the Delhi emcees, et cetera, are basically taking a page out of your swords narrative, talking about the cloud experience, talking about, you know, flexible pricing models, building cloud products on prime and hybrid cloud and multi cloud. So it's hard sometimes for customers to squint through that. And really, no, I guess the bottom line, the last thing I'll say is pure. Doesn't have as many feet on the street is these other guys. So it's gotta leverage the channel increasingly, and that's how it gets beyond two billion on its way to five billion. >> And that was one of the factors that they attributed the second quarter. 28% year on year growth is to not just innovation, but also to the channel. So they've done a good job of really pivoting. There's large enterprise deals to be covered, direct and then bringing in the channel for those smaller mid size business customers. Adding a lot of momentum in cute to you mentioned the nan pricing that in some of the political climate with the start of China, most of their businesses in the Americas so they're not facing as many of those challenges. So they did lower guidance for the rest of it is >> the second time they've >> lowered 20. However, they kind of attributed that thio the nan supply oversupply and they say happy Matt to flatten out quickly, say they're >> not worried about the macro. I mean, look, if if the economy is good and is booming and people are spending money on cap ex. That's good for even a high growth company. They're basically positioning to the street that if if the economy does turn down and there's a softness at the macro, they'll actually gain share more rapidly. Which, by the way, is probably true. But look at the rising tide lifts all boats. Nobody wants to see Ah recession. Having said that, well, it's interesting. When you saw Pure Lower, its guidance stock took a hit, and then net app, I'd be him. All these other company you have to see a deli emcee they announced in the market said, Wow, pure must be doing really well compared to these other guys. So it's come back in a big way. My opinion pure is going to in the e. T. Our data shows this from a spending intentions Pure is going to continue to gain share at a much, much more rapid pace of the other. The other guys, from a product standpoint, delicacies consolidating its product portfolio, trying to lower its cost. H. P E is really focused on limbo. IBM needs a mainframe product cycle to get back going, Ned APS facing its challenges and its kind of tweaking its go to market model. So all these other companies air dealing with sort of some structural changes. Where is pure is like put the put the foot on the gas and accelerate no pun intended. And so I think they're gonna continue to gain share for quite quite a number of quarters. >> I want to talk about sustainability before we break. And one of the things that Charlie talked about on his keynote is in terms of the modern data experience, he said. It was three things. It was simple, seamless and sustainable, an inch sustainable. You really started talking about the evergreen model that they launched a while ago that seems to be really sticky with organizations. He also talked about sustainability is a lot of other organization I need to adjust in terms of, you know, waste and carbon emissions and things like that. But I'm just curious, since Pierre is much smaller than the competitors that you mentioned and a lot more focus, obviously all in on flash. Where does the evergreen model, in your opinion, give them that tail winter? That advantage? >> Well, the Evergreen model was first of all brilliant marketing strategy and a business strategy Because if you think about the traditional storage vendors, they make so much money on maintenance, they would never have done this unless pure force them to do it. Because they're making so much cash on the maintenance. You know, it's it's you. You put the storage array in and we're just gonna charge you maintenance. And if you're not on the maintenance contract, sorry. You don't get all the software upgrades, everything else. So it's just this, you know, this lock in strategy, which is work brilliantly for two decades pure, comes along and says, Hey, where? Software driven. We're gonna allow you to get all the modern software. As long as you're got a subscription with us, we'll swap out your controller for free. You know, the competitors hate that. There's all kinds of nuances and stuff, but it worked, and customers love it. And so it's very strong, and it's a fundamental as they said, they got $600 million in deferred revenue, largely from that evergreen model. So they, you know, Charlie mentioned first for non disruptive upgrades. First for cloud management, first for a I ops first for always on que Os first with always on encryption, and if they're really the first, we're probably the first big company. They got a lot of attention there. Last thing, it's it's a four big announcements today. There's a I ready infrastructure, airy. They're doing some stuff they were first to announce with video. You know, a year or so ago, they got cloud offerings. Ah, block storage for AWS. And they've got clout Snap for Azure, which is actually pretty hot. It's backup on Azure, and they got product extensions. They got cheaper flash with a flash or a C for capacity. And then they have extended their all flashy raise their flash played etcetera with storage class, memory and and storage memory. And in this, this as a service model. Those are really the four big announcements that were gonna dig into all this week. >> We are, and we're gonna be talking with This is a great event. Two days. The cube is going to be here. We have seven pure customers to talk to you that I think kind of a record, at least in my cube experience of the last >> AWS always puts a lot of customers up too. You know. All >> right, well, there's no better validation than the success of a brand, whether we're talking about Evergreen or their first or the reaction of the market to bringing flash down to satya prices. So excited to dig into customer stories with you, Dave. Course we'll talk to some partners who got c'mon slung Cisco somebody else and probably forgetting. And, of course, some of the pure, exactly gonna be exciting two days with you and looking for two days >> looking forward to at least a great >> all right stick around. Dave and I will be right back with our first guest, Charlie Giancarlo, chairman and CEO of Pier Storage. Stick around, come back Mawston in just a minute.

>> From Boston, Massachusetts. It's theCUBE. Covering Actifio 2019 Data Driven. (upbeat techno music) Brought to you by Actifio. >> Hello everyone and welcome to Boston and theCUBE's special coverage of Actifio Data Driven 19. I'm Dave Vellante. Stu Miniman is here. We've got a special guest, John Furrier is in the house from from Palo Alto. Guys, theCUBE we love to go out on the ground, you know, we go deep. We're here at this data theme, right? We were there in the early days, John, you called me up and say, "Get your butt here, we're going to cover the first of Doop World". And since then things have moved quite fast. Everybody thought, you know, Hadoop Big Data was going to take over the world. Nobody even uses that term anymore, right? It's kind of, now it's AI, and machine intelligence, and block chain, and everything else. So what do you think is happening? Did the early Big Data days fail? You know, Frank Genus this morning called it The experimentation phase. >> I mean, I don't really think Frank has a good handle on what's going on in my opinion, cause I think it's not an experimentation, it's real. That was a wave that was essentially the beginning of, not an experimentation, of realization and reality that data, unstructured data in particular was real and relevant. Hadoop looked good off the tee, mill the fairway as we say, but the thing about the Hadoop ecosystem is that validated big data. Every financial institution jumped on it. Everyone who knew anything about data or had data issues or had a lot of data, knew the value. It's just that the apparatus to build via Hadoop was too expensive. In comes Cloud computing at scale, so, as Cloud was accelerating, you look at the Amazon Web Services Revenue Chart you can almost see the D mark where the inflection point is on the hockey stick of Amazon's revenue numbers. And that is the point in time where Hadoop was on the declining of failure. Hortonworks sold the Cloudera. Cloudera's earnings are at an all-time low. A lot of speculation of their entire strategy, and their venture back company went public, but bet the ranch to be the next data warehouse. That wasn't the business model. The data business was a completely new industry, completely being re-transformed, and, far from experimentation, it is real and definitely growing like a weed, but changing because of the underpinning infrastructure dynamics of Cloud Native, Microservices, and that's only going to get highly accelerated and the people who talk about context of industry like Frank, are going to be off. Their predictions will be off because they don't really see the new picture clear enough, in my opinion, >> So, >> I think he's off. >> So it's not so much of a structural change like it was when we went from, you know, mainframes to PCs, it's more of a sort of flow, evolution into this new area which is being driven, powered by new technologies, we talk about block chain machine intelligence and other things. >> Well, I mean, the make up of companies that were building quote, "Big Data Solutions", were trying to build an apparatus or mechanisms to solve big data problems, but none of them actually had the big data problem. None of them were full of data. None of them had a lot of data. The ones that had problems were the financial institutions, the credit card companies, the people who were doing a lot of large scale, um, with Google, Facebook, and some of the hyperscalers. They were actually dealing with the data tsunami themselves, so the practitioners ended up driving it. You guys at Wikibomb, we pointed this out on theCUBE many times, that the value was going to come from the practitioners not the suppliers of so called technology. So, you know, the Clouderas of the world who thought Hadoop would be relevant and growing as a technology were right on one side, on the other side of the coin was the Cloud decimation of that sector. The Cloud computer just completely blew away that Hadoop market because you didn't have to hire a PhD, you didn't have to hire specialty skills to stand up Hadoop clusters. You could actually throw it in the Cloud and get agile quickly, and get value out of data very very quickly. That has been real, it has not been an experiment. There's been new case studies, new companies born, new brands, so it's not an experiment, it is reality, and it's only going to get more real every day. >> And I add of course now you've got, you mentioned Cloudera and Hortenworks, you also got Matt Bar reeling Stu. Let's talk about Actifio. So they coined the term Copy Data Management, they created the category, of course they do a lot of backup, I mean, everybody in this space does a lot of backup. And then you saw the Silicon Valley companies come in. Particularly Cohesity and Rubric, you know, to a lesser extent he got some other guys like Zerto and Durva, but it was really those two companies, Cohesity and Rubric, they raised more money in their D round than Actifio has since inception. But yet Actifio keeps, you know, plodding along, growing, you know, word is they're profitable, you know, they're not like this really sectioned very East Coast versus kind of West Coast mentality. What's your take on what's going on? >> Yeah, so, Dave right, you look at the early days of Actifio and you say great, Copy Data Management, I have all these copies of data, how do I reduce my cost, get greater utilization than I have and leverage the data? I love the title of the show here, Data Driven. You know, we know at the center of digital transformation if you can't become data driven, like the CMO Brian Regan got up on stage talk about that industrialization of data. How am I going along that journey being this, I collected data versus now, you know, data, you know, is the reason that I make decisions, how I make decisions, I get smarter. The Cloud of course is a huge enabler of this, there's all these services that I can instantly access to be able to get greater insight, and move along with that environment, and if you look underneath all of these backup companies, it's really how I can change that data into business value and drive my business, the metadata underneath and all those pieces, not just the wonky storage and technical solutions that make things better, and I get a faster ROI. It's that data at the core of what we do and how do I get that as a business to accelerate. Because we know IT needs to be able to respond back to the business and data needs to be that rocket fuel. >> Is it the case of data haves and data have-nots? I mean, Amazon has data >> I mean, you're right-- >> and Facebook has data. >> We're talking about Actifio, you brought that up, okay, on this segment, on the inside segment, which is cool, they're here at the event, but they have a good opportunity but they also, they got some challenges. I mean, the thing about Actifio is, to my earlier point, which side of the wave are they on? Are they out too much out front with virtualization and Amazon, the Cloud will take them away, or are they riding the Cloud wave, making that an enabler? And I think what really I like about Actifio is because they have a lot of virtualization capabilities, the question is can they scale that Stu, to containers and microservices, because, the real opportunity in this market, in my opinion, is going to build on the virtualization trend, and make container aware, microservices capabilities because if they don't, then that would be a tell sign. Now either way it's a hot M&A market right now, so I think being in the market, horse on the track as you say. You look at the tableau sales force deal monster numbers we are in clearly a hot IPO market and a major roll up market on the M&A side. I think clearly there's two types of companies, old and new, and that is really what people are looking at, are they part of the old guard, are they the new guard. So, you know, this to me is going to be a tell sign of what they do next, can they make the data driven value proposition, you articulated Stu, actually a reality It's going to come from the technology underneath. >> Well I think it's a really interesting point you're making because, Stu as you probably know, that Amazon announced the Amazon backup service right, and you talked about the backup guys and they're like, "Ah yeah it's backup, but it really doesn't do recovery, it's really not that robust". It's part of me says, "Uh oh"... >> Watch out. >> You better move fast", because Amazon has stated, "Hey if you don't move fast we're going to just keep gobbling", and you've seen Amazon do this. What are your thoughts on that? Can these specialists, can they survive, John's talking about M&A. Can the market support all these guys along with the big, you know, traditional guys like Veritas, and Dell EMC, and IBM and Combol? >> Right, well so Actifio started very much in the data center. They were before this Could wave really took off. It's really only in the last year that they've been sassifying their product. So the question is, does that underlying IP, which wasn't tied to hardware, but, you know, sat at really more of, you know, reminded us of that storage virtualization battles that we talked about for years, Dave, but now they are going in the Cloud. They've got all the partnerships in the Cloud, but they are competing against those new vendors that you talked about like Cohesity and Rubric out there, and there's big money chasing this environment. So, you know, I want to talk to the customers here and find out, you know, where they are using them, and especially some of those first customers using this--. >> Well they clearly need a Cloud play cause that's clearly where the action is. But if you look at what's going on with Amazon, Azure, and Google you see a lot of on premises, Stu, because that's where the customers are. So just because the customers are currently not migrating their existing workloads to the Cloud doesn't mean it's not going to happen. So I think there's an opportunity for any company like Actifio, who may or may not be on the curve on the tech side, one little misfire on a tech bet could cripple the company and also make the company. There's a lot of high risk, reward ratio. How they handle containers. How they build on virtualizations. Virtualization going to to be part of the future with Cloud. These are the kind of the dynamics that are going to be in play, and they got some time on their hands because the on premises growth is because the clients are trying to figure out what to do and they're not going to be migrating, lifting, and shifting workloads all off to the Cloud. New will be Cloud based, but enterprises have proven why we are in multi-Cloud and hybrid-Cloud conversation, that... The enterprise on premises is not going away anytime soon. >> I want to ask you guys, John you specifically, about this sort of new Silicon Valley growth model and how companies are achieving escape velocity. When you and I made our first trip to Barcelona, I was having dinner with David Scott who was the CEO of 3PAR and he said to me, When I came to 3PAR the board said, "Hey we're willing to invest 30 million dollars in this company". And David Scott said to them, "I need way more, I need 80 million dollars". Today 80 million dollars is nothing. You saw, you know, Pure Storage hit escape velocity, was just throwing money, and growing at the problem. You're seeing Cohesity-- >> Well you can debate that. I mean, If you have to build a rocket ship, hit critical mass and you want to fund that, you're going to to need an enterprise. However, there's arguments on the south side that you can actually get fly wheel effect going early with less capital. So again, that's 3PAR-- >> But so that's my point. >> Well so that's 3PAR, that was 2009. >> So, yeah that was early days so that's ancient history. But software is generally supposed to be a capital efficient market, yet these companies are raising many hundreds and hundreds of millions, you know, half a billion dollar raises and they are putting it largely in promotion. Is that the new model, is that sustainable, in your view? >> Well I think you're conflating capital market dynamics with viable companies to invest in. I think there's a robust seed in series A market but the series A market and Silicon Valley is you know, 15 to 25 million, it used to be 3 to 5. So the dynamics are changing on funding. There's just not enough companies, horses on the track, to deploy capital at tranches of 30, 50, 80 million. So the capital markets are clearly going to have the money available so it's a market for the startups and the broke companies. That's separate from actually winning. So you've got slacks going public this weeks, you have other companies who have built business on a sass fly wheel, and then everything else is gravy in terms of the go to market, they got a couple hundred million. I think slack got close to a billion dollars in cash that they've raised. So they're flooded with cash, they'll never spend it all. So there are some companies that can achieve success like that. Others have to buy market share, they got to push and build out a sales force, and it's going to be a function of the role of customer, customization, specialism, and whatnot. But with AI machine leaning there's more efficiencies coming in so I think the modern company can do more with less. >> What do you think of the ride sharing on IPOs, Uber and Lift, do you abol? Do you like 'em or do you think it's just, they're losing too money and can't sustain it? >> I was thinking about that this morning after looking at the article in the Wall Street Journal in our coverage on Silicon angle. You look at Zoom communications, I like models that actually can take a simple concept and an existing mature market and disrupt it by being Cloud efficient and completely sass and data driven. That is an example of success. That to me, Zoom Communications and Zscaler, another company that we talk to, these are companies that were built with a specific value proposition that made the product and they were targeting mature markets with leaders in it. Video conferencing, Webex, Citrix, Zoom came out of nowhere, optimized on simple value proposition, used Cloud scale and data, and crushed it. Uber, Lift, little bit different issue. They're losing money but I would bet on the long term that that is going to be the used case for how people will have transportation. I think that's the long game and I think that without regulatory kind of pressure, without, there's regulatory issues that's really the big risk. But I believe that Uber and Lift absolutely will be long brands and just like Facebook was early on, although they threw off a lot of cash, those guys are building for penetration, and that's where the funding matters. Penetration is critical. Now they're the standard, and people really don't take taxis anymore, but they're really using the ride sharing. And you get the scooters, you get the bikes, they're all sequencing into these adjacent markets which drains more cash but builds the brand, builds the footprint. >> Well that's what I want to ask you. So people compare the early Uber, Lift, Taxi, Ride sharing to Amazon selling books, but there's all these other adjacencies. You have a thought on this? >> Well, just, you know, right, Uber Eats is a huge opportunity for that environment and autonomous vehicles everybody talks about, but it's still quite a ways out. So there are a lot of different- >> Scooters are the same, we're in San Diego, there are 8 gazillion scooters. >> San Diego had fun, you know, going around on their electronic scooters, boy, talk about the gig economy, they pay people at the night, to like go pay by the recharge you do on that, what is the future of work, >> Yeah, that's a great point. >> and how can we have that-- >> Uber going to look a lot like Amazon. You subsidize the front end retail side of the business, but look at the data that they throw up. Uber's data that they're gathering on, not only customer behavior, but just mapping services, 3-D mapping is going to be huge, so you've got these cars that are essentially bots on the road, providing massive mapping and traffic analysis. So you're going to start to see data driven, like Actifio slogan here, be a big part of all design decisions and value proposition from any company out there. And if they're not data driven I think they're going to be toast. >> Probably could because there's that data and that machine learning underneath, that can optimize, you know, where the people are, how I use the system, such a huge wave that we're watching. >> How about one last topic which is heavily data driven, it's Facebook. Facebook is obviously a data driven company, the Facebook crypto play, I love it, I love Facebook. I'm a bull on Facebook, I think it's been beat up. I think, two billion users is hard to replicate, but what's your thoughts on their crypto play? >> Well it's kind of a middle finger to the United States of America but it's a great catalyst for the international market because crypto needed a whale to come in and bring all those users in. Bad timing, in my mind, for Facebook, because given all the anti-trust and regulatory conversations, what better way to show your threat to the world order when you say we're going to run a banking system with a collection of international companies. I think the US is going to look at this and say, "Oh my God! They can't even be trusted to handle personal information and we're going to now let them run a banking system? Run monetary, basically World Bank equivalent infrastructure?" No frickin way! I think this is going to to be a major road to home. I think Facebook has to really make this an ecosystem play if they want to make it work, that's their telegraphic move they're saying, "Hey we want to do for the community but we got our own wallet and we got our own network". But they bring a lot to the table so it's going to be a really interesting dynamic to see the coalescing around Facebook because they could make the market. Look what Instagram did to Snapchat. They literally killed the company, took all their users. That is what's going to happen in the digital money economy when Facebook brings billions of users user experience with money. What happened with Snapchat with Instagram is going to happen to the World Bank if this continues. >> Where do you stand on the government breaking up big tech? >> So Dave, you know, you look in these companies, it's not easy to pull those apart. I don't think our government understands how most of big tech works. You know, take Amazon and AWS, that's one company underneath it. You know, Facebook, Microsoft. You know, Microsoft went through all these issues. Question Dave, we've had lots of debates on Twitter you know, are they breaking the law, are they not doing trust? I have some trust issues with Facebook myself, but most of the big companies up there I don't think the anti-trust kicks in, I don't think it makes sense to pull them apart. >> Stu, the Facebook story and the YouTube story are simply this, they have been hiding under the platform rules, of the Digital Millennium Copyright Act, and they are an editing platform so you can't sue them. Okay, once they become a publisher they could be sued. Just like CNN, Fox News, and everybody else. And we're publishers. So they've been hiding behind the platform. That gig is up. They're going to have to address are you a platform or are you a publisher? You're making editing decisions around what users can see with software, you are essentially editing the feed, that is a publisher role, with that becomes responsibility, and then obviously regulartory. >> Well Facebook is conflicted right now. They're trying to figure out which side of the fence to go on. >> No no no! They want one side! The platform side! They're make billions of dollars! >> Yeah but so they're making decisions about you know, which content to show and whether they monetize it. And when it's controversial content, they'll turn down the ads a little bit but they won't completely eliminate it sometimes. >> So, Dave, the only thing that the partisans in politics seem to agree on though is that big tech has too much power. You know, What's your take on that? >> Well so I think that if they are breaking the law then they should be moderated. But I don't think the answer is to go hard after Elizabeth Warren. Hard after them and break them up. I think you got to start with okay, because you break these companies up what's going to happen is they're going to be worth more, it's going to be AT&T all over again. >> While you guys were at Sysco Live, we covered this at Amazon Web Service and Public Sector Summit. The real issue in government, Stu, is there's too much tech for bad on the PR side, and there's not enough tech for good. Tech is not bad, tech is good. There's not enough promotion around the apps around there. There's real venture funds being created to promote tech for good. That's going to where the tide will turn. When does the tech industry start doing good stuff, not bad stuff. >> All right we've got to wrap. John, thanks for sitting in. Thank you for watching. Be right back, we're here at Actifio Data Driven 2019. From Boston this is theCUBE, be right back. (upbeat techno music)

(orchestral music) >> Hi, I'm Peter Burris, and welcome to another Cube conversation, from our awesome studios in beautiful Palo Alto, California. With every Cube conversation, we pick a topic, find someone to talk about. The topic today is hybrid cloud. A lot of conversation. AWS introduced Outposts, we've got Microsoft Azure talking about centralize, as well as distributed cloud offerings. Oracle is doing the same thing. A lot of conversation about hybrid cloud and what it means. To have that conversation, we've got David Floyer with us. David is the CTO of Wikibon. David, welcome back to theCUBE. >> Thank you very much, Peter. >> David, let's start by saying, that there has to be a way of representing different options when we think about hybrid cloud. You've done a lot of research in this domain. How are you representing the continuum, the taxonomy of hybrid cloud for customers? >> On the slide, it shows that there are essentially, five different multiple clouds or hybrid clouds. From left to right, it's multi-cloud, and at the bottom of the slide, it says that this essentially a set of clouds, with an integrated network. And then the next is loosely-coupled hybrid cloud, and that adds in the data plane, where we look after storage, and data protection, data management, et cetera. The middle one is tightly-coupled hybrid cloud, and that's where the control plane, is now tightly integrated along with everything else. The next one is "true" distributed hybrid cloud, and those are the ones that you were talking about. Those are the AWS Outposts, the Azure Stack, the Oracle Cloud at Customer-type environments. Also, you could put IBM, some of IBM's recent announcements into that as well. Last but not least, and certainly one of the most interesting and different, is the autonomous stand-alone clouds, are going to be at the edge. They have to be autonomous, because they can't guarantee network availability to them. >> So, five classes of cloud, each distinguished by the degree, to which they share different types of resources, including state, integration, automation, and the degree to which the application is going to be common across each of these cloud types. >> That's correct. >> Have I got that right? >> Yeah, absolutely. >> Obviously, while this is theoretical. >> Yeah. >> In a sense that we're trying to create some way, so understanding about how to represent these things. It's based on some practical observations, about where we are within the industry. >> Yeah. >> Let's start talking about multicloud. Who do you place into that bucket, of multicloud hybrid cloud styles? >> If we talk first of all about the cloud themselves, there would be clouds from AWS or Azure, or IBM or Google. Those are the clouds that you start with, you might have one on premise, but the connection between them is just on a network basis. The people who are doing that would be clearly, Cisco is one of the leading people in that area, where they already have a lot of enterprise equipment, and experience of dealing with clouds, across the whole of the area. They would be the people, that are going to be a foremost vendor, in connecting those different clouds together, on a network plane. >> Okay, let's move to the right, and talk about the loosely-coupled hybrid clouds. Now here we're having more than network, common network. We're having a common data plane, which really boils down to a common set of data services, that are rendered commonly. >> Right, yeah. >> Across different cloud instances. >> Right. >> Who's there? >> To do that, you've got to be able to have your data services, actually on each of the clouds. You have to have it in software on AWS, or Azure, or IBM, or whatever it is. Two of the people that's probably leading the charge in that area are IBM themselves. They've gone completely software, with all of their spectrum line of software in that area, and Pure. Pure Storage have been very aggressive again, in putting things up, so that they can be reflected in each of the clouds. >> And there's other vendors, that are coming in from a data protection standpoint. >> Sure. >> Data security standpoint, and they may-- Some people like Veeam. >> -not have the full set of services. >> Yes. But they are looking at how they can apply their services. >> Correct. >> Across multiple cloud instances. >> And there's a lot of vendors there. People like Veeam or Rubric, or Cohesity. DellEMC. >> Et cetera, yes. >> Okay, so let's move to the right. Now we've moved from loosely-coupled, to tightly-coupled hybrid clouds, where we're starting to share a common automation framework, more control, sharing control data so that we can start to understand, the state of applications in multiple different locations. >> Yes. >> Who's leading there? >> Some of the leads in this area, are some of the traditional ones, like IBM for example. IBM Sysplex, which came out what, 20 years ago. >> We're not. >> That is where you have state being, time and state being shared, across a whole number of different instances, or notion within that Sysplex. >> Yeah, let's talk about that specifically. So, we're talking about a global shared memory notion. >> Yes. >> More than just a name space, but actually-- >> Correct. >> -a control plane, that has global incite into where resources are, has names for them. >> Yeah. >> They may be multiple name spaces, but it's bringing a common set of controls to that global set of resources. >> Yes, and time is obviously a key aspect to help stay-- >> Well, it's got to be synchronized. >> Yes. >> Exactly. >> That's right. >> If we move to the right to true distributed hybrid cloud, in the tightly-coupled, we have a common control plane, but not necessarily common software. >> Correct. >> Common code. >> Correct. >> At the compile level. We're still utilizing distribution formats, maybe specific, et cetera. But now in a true hybrid, or true distributor hybrid cloud, it's common-common. >> Yes. >> Who's there? >> Yes, it's common code. It can run on any node without having to be recompiled, or retested. You know it's going to work. The people in there, are the people that we were talking about earlier. It's people like AWS with Outposts, Microsoft with Azure Stack, Cloud at Customer from Oracle. Three large vendors, who are using this to use a cloud first-type model, in which they can grow, the central cloud, as quickly as possible, add things to it, and push that down into the Cloud at Customer, or the Outposts, or the Stacks. >> To be clear, we're not talking about a common cloud experience, we're talking about absolute common cloud services. >> Correct. >> All the way down to the executables, so that the same software can run wherever it needs to run. >> Yes. >> Finally, let's move one step further to the right. This is the autonomous stand-alone clouds. >> Yes, this is at the edge. >> Who's there? >> This is the most different of all of these. It has to be autonomous. If you think about mobile vehicles or planes, or even think about a factory or a nuclear power plant. You have to be able to run that, assuming that the network is not going to get through. It's on the edge, so it's the most vulnerable to network. It has to be autonomous, therefore it has to be able to run by itself. That sort of cloud is mainly concerned with the state, the state of that edge. All of the devices in that edge, the windmills in that edge, or the factory robotics in that edge. In military terms, the automated units in that edge, or the drones. Whatever it is, you're concerned about the state of that. >> But specifically, sustaining local control of state. >> Correct. >> Against a common understanding. >> Yes. >> Of how these things interact with each other. >> Right. >> It brings almost a network realtime of flavor to it. >> It is realtime. It has to be realtime so it's a shared state across. For example, across the city, in terms of the traffic lights. You would see multiple of these small clouds, in different parts of a large city, for example. Which need to communicate with each other. So, you have devices, which have an inference code running on them, and they're dealing with the device, on to which it's attached. And then you have connecting all of those devices together, to make this overall system representation of the sate. >> Okay, so we've got five classes of hybrid cloud. How is a CIO going to use this taxonomy, to make better decisions? >> Clearly by making this decision, what we're doing from a taxonomy point of view, is making each one individual, and different from the others. There's no sharing between them. That means that from a description point of view, we can describe the whole of this industry. We can say how much is going on in each one, who are winners and losers in each one. >> We'll use this to size different classifications. >> Right, and give that-- >> Talk about leader, describe competition and all that stuff. >> Yes. >> But if I'm a CIO, do I think, oh, I got a business problem that's associated with applications, on various levels of common data sharing, control sharing, et cetera. Do I use this to help me chose the specific architecture that I use? >> The best way that I think that CIO's are going to use this to say, "Where am I aiming to be? What is most important to me and my business? If it is the edge, then how am I going to go through these? Because I'm not going to get to the edge on day one. How am I going to chose my vendors and my protocols, and my standards, and my data planes, and my control planes, such that I can get to that particular end point?" Within each one, you'd want to look at them individually, because you're going to put together a, first of all, in a multi-cloud environment. But you should be looking into the future, as to how you want to traverse across this, and who your major partners and vendors will be. Or, strategic partners and vendors. >> And we'll use this as you said, we'll use this specifically to size the market, describe the competitive factors, et cetera. >> Correct, yeah. All right. David Floyer, thanks very much for being on theCUBE. >> Thanks very much, indeed. >> Once again, I'm Peter Burris, and we have been talking about Cube conversations, related to true hybrid cloud taxonomies. Wikibon research. Thanks very much for watching, and until our next Cube conversation. (orchestral music)

>> Live from Las Vegas, it's theCUBE! Covering VMworld 2018, brought to you by VMware and its ecosystem partners. >> Welcome back everyone. It's the live CUBE coverage here in Las Vegas for VMworld 2018, three days of wall-to-wall coverage. We got two sets. I'm John Furrier, my co-host Stu Miniman. Our next guest is Adam Rasner, who is Vice-President of Technology Operation of AutoNation. Welcome to theCUBE. Thanks for joining us. >> Yeah thanks for having me. >> So you guys are a customer of all this virtualization stuff. What's going on in your company? Tell us what's happening at AutoNation. What are you guys at now with IT operations? Where you guys going? How you guys building into the Cloud? What's the strategy? >> Sure, so AutoNation is exploding. We have 280 new car dealerships. We have 80 collision centers. We just launched our own precision parts line. We're also looking at other technologies to automate the car buying experience. So we want to make like an Amazon-like car buying experience online, so that requires a lot new technology and digitalization. >> Yeah, talk a little bit about that. 'Cause I know, I've looked at cars in the last couple of years and now you know, I do so much of it online. I feel like I could do the whole experience from my phone if I wanted. So how much are you a technology company? And how much of that's cloud? And what are those dynamics that you've been going through the last couple of years? >> Yeah I think the millennials this day, they're willing to go online and do the whole car buying experience end-to-end, from the buying of the car to the financing of the car all online. And we can roll a flat-bed up to their house, and deliver a car, and they sign on an iPad, and they're good to go. And I think that's where things are going. So to do all that requires a lot of technology on the back-end. So we have a lot of on-prem infrastructure. I'd say we're still 90% on-prem, 10% in an Azure, AWS infrastructure. But that's going to change in time as a lot of these new applications are written. >> As you guys are doing the digital transformation, and it sounds like there's a lot of action going on, new things happening, you're in the app business. You got to build apps for user experience. So you've got to make the infrastructure work for you, and make it be failover, fall-tolerant, all that good stuff, recovery, how do you look at that? How do you run at the speed you need to run at? What are some of they key things you guys have to do to keep on that treadmill, but yet not drop the ball in delivering apps to the users that drive the business? >> I think there's a few things. I think one is, we have to be able to keep the lights on with our existing infrastructure, our existing apps while we build these next generation of applications. We have to be able to scale up as needed and scale down, be able to support some of the new mobile platforms that we're going to be working on. So there's a lot of work going on and DR is a big part of this too. >> Yeah, I'm glad you brought that up. Because data is at the core here. So, can you tell us that role of data, and then you say data protection. How is that changing, what was it like before you went through this transformation? Then we'll of course get into what you're using. >> Sure, so we actually, were using an old Microsoft data protection manager product and just didn't scale the way we needed to, we were having some performance issues. And so, data protection, while not very sexy, it's something you have to do. It's table stakes in IT. It doesn't innovate, it doesn't make me sell more cars, it doesn't help the business sell more cars, but it's something we have to do. So we looked out there at what I call the legacy players and also the nextgen players and went through a full proof of concept with several of them. >> All right, and what were you looking for? What was kind of the key objective you said? Data protection doesn't make you money, or didn't make you money. We've talked to some customers, that's like, wait, might do some cool snapshotting, I can leverage that data, I can do some more things with my developers, and everything. So what was the goal of this transformation and then what was the criteria that you went through to make a decision? >> Yeah, so the data protection was the initial piece and we just needed a rock solid backup and recovery solution. And we started off with just a simple, hey, we wanted an integrated hardware software solution, we wanted something that could scale infinitely, we wanted a predictive cost model. And so a lot of those older legacy players don't play well in that space, they're expensive to support, eventually you hit a wall on hardware limitations and you have to use forklift upgrades. So we wanted something that was a little bit more nimble and then down the road, as we got into it, once the backup and recovery piece was kind of under control we started using our new solution for other things and secondary storage which was an added bonus. >> So you haven't mentioned, what is the solution that you chose and what were the key things that led to that? >> Yeah, so after going through several POCs with you know, NetBackup, Rubric and Cohesity, we ultimately chose Cohesity for performance, cost, ease of implementation, ease of the user interface, ease of management. >> And what was the comparison, on the floor here you see Rubric and Cohesity next in the huge booths. What's the difference between those two? >> Yeah, so we actually put them side by side in our data center, full blown POCs, and there was some performance differences, there were some technical challenges that we had with some of the other products. And ultimately the team, our engineering team felt most comfortable with Cohesity after spending six or eight months in a really in-depth POC. >> Big bake-off. I love the bake-offs. It's the only way to have the answer like that. So when you look at the solutions, are you guys mostly interested in the software side of the business that they had? What was they key piece of it? >> I think we're interested in the whole thing. I had been at other places where we had done the NetBackup and data domain story and you know, you're having a problem at three o'clock in the morning and you got the finger pointing, is it a software issue, is it a hardware issue? We wanted the one throat to choke kind of solution, and so, you know, that was a requirement right off the bat. Whatever we chose was going to be an integrated hardware software platform. >> Adam, walk us through from the deployment to the day two action. How did it go? What surprised you? What, you know, thrilled you? You know, what challenges did you have? >> Yeah, we've been a customer for- I think we were very early customer, probably almost about two years now. So, there's a lot we didn't know. There was a lot of things in the product that actually weren't fully mature when we first started the POC. And so we went through a full, a full blown bake-off, and one of the things we noticed it was much easier to implement, we didn't require any professional services to get it up and running and the technical support we were super impressed with. So I think, you know, the team, after going through the motions, really felt like this was the product for us. And again, really mainly around backup and recovery, but ultimately decided that we were going to use it for other things too. >> Adam, I was walking through the hallways yesterday, Stu and I were both checking out the booths. And I hear a lot of conversations and it comes up around the Cohesity, Rubric, all these different cloud solutions. Some are rinsed and repeat old models that just have, you know, not mostly those guys are, but the customers are concerned about I don't want the old way, I want the new way, I want to be cloud native, I want to work with cloud, One choke to throw, I need software, I need to have agility, and I need to have auto, you know, healing, all this kind of stuff. How do you sort through that? I know you've been through the POC but your peers that are out here at VMworld, they're squinting through the noise going okay, I got to really dig in here. What's your advice to those guys and gals? >> I think it's really challenging for the people that are, you know, neck deep in some of these other legacy products because it's a little bit hard to move. You know, it's costly, it's expensive, and it's a significant effort. I was in a rare position where I was able to start net new, and so that made it a little bit easier. But I think you start with a slow migration, start setting up your new infrastructure on a nextgen platform and then slowly migrate off. These next, these legacy players are very expensive, and they don't scale very well. That's probably one of our biggest challenges. >> One of the things you said, you started with a couple of use cases but you're now doing a bunch more. Talk about that, what more, what are the new things you're doing and what's the road map look forward at AutoNation? >> Sure. So we had a, a lot of apps, that we're probably not needing. Tier one, NetApp, all SSD, high performance SAN. I call it my Cadillac of storage, you know. It's our highest performance applications and we were having some apps that the hardware was starting to, you know, just go bad. And so the only place I could put it was either on my NetApp, or I didn't have any place else. So the story changed over time. Cohesity became not only our backup and recovery data protection appliance, we started landing some of our tier two storage on Cohesity. So moving things that we would normally put on NetApp, putting it on Cohesity for 40 percent of the cost and it's a win-win. >> All right, so, Adam, I couldn't help noticing you've got the Drive Pink pin on. >> Yes. >> So, maybe tell our audience a little bit about the, you know, AutoNation Drive Pink initiative and you know, do you have relationships with the suppliers here? Pat Gelsinger this morning talked about you know, we need to be as a technology community more doing good. It's foundational to what we're doing. >> Autonation, it's one of our core charities is cancer awareness. I think we've donated almost 30 million dollars. Every car that you buy, we try to put the Drive Pink license plate. And I think not only for business, I think in IT we also have to have a lens to some of these charities and some of these things that need our help. >> Issue driven businesses are doing well now, people expect that. Not just for profit, but the people involved. >> Yeah. >> Anyone can work anywhere these days, talent, it's also good. I mean, it's one of those things. >> Yeah, yeah, absolutely. >> All right, so, takeaway from this show, so far, your impression as a practitioner in the IT footprint space, looking at a cloud on the horizon, we just had Andy Bechtolsheim just on, been part of the early days. Cloud's coming fast, networking's got to get better, you got to, you know, seeing what solutions, integrating well together. How do you make sense of all this content coming out of VMworld? >> Yeah, I think what I get out of this and kind of AWS, all of these conferences, is that everything we buy has to be extendable to the cloud. You know, we still have a lot of on-premise infrastructure but everything we implement has to be cloudable, it has to be able to be used in our future use cases. >> I would love, we're talking a lot here in the keynote this morning it's like, right, this move, we know it's going to take time and Amazon's doing some things, VMware's doing some things, how's the industry doing, how do you see the progression, what would you like to see them do more better if we come back in a year, if I kind of give you that magic wand? >> Yeah. You know, I always leave a lot of these conferences and I feel like I'm behind the eight ball, in our cloud migration, but, companies like us that have a lot of legacy apps, they're slow to move. And so, I leave the conference, I feel like I'm behind the eight ball, but I get back and I talk to my peers and many of them are in the same situation I am. They're still maturing, but I think, yes, I think the net new generation apps that we're going to build are going to be in the cloud because the capabilities to autoscale and so I think that anything we buy, anything we implement we have to have a lens to that going forward. >> Well, thanks for coming on theCUBE, we really appreciate, sounds like you're happy with Cohesity? >> They've done a great job, we're really happy customers. >> How long was that bake-off by the way, that you ran that? >> We did it about six months. >> That's pretty good and long. >> Yeah, we actually had some, again we were very early to the game so there were features in the product that we needed that they didn't have yet and our agreement was we'll proceed after you can meet these requirements and they did. >> Yeah. And Pat Gelsinger and Andy Jassy on the stage, one of the things Andy Jassy, who's been on theCUBE talks about all the time is listening to customers. Sounds like they're listening to you guys. >> Absolutely, absolutely. You have to, it's such a competitive environment now. You know, if you can't meet the customer's minimal requirements, there's somebody else that can. >> You got to be cloud compatible. AutoNation breaking it down here, here at Vmworld bringing the practitioner perspective, the customer perspective, all of these suppliers try to bring cloud and on-premises together. It's theCUBE bringing you all the action here at Vmworld 2018. I'm John Furrier. Stu Miniman. Stay with us for more coverage after this short break.

>> Narrator: Live from the Bill Graham Auditorium in San Francisco, it's The Cube. Covering Pure Storage Accelerate 2018. Brought to you by Pure Storage. (techno music) >> Back to The Cube, we are live at Pure Storage Accelerate 2018. We are in San Francisco at the Bill Graham Civic Auditorium. This is a really cool building built in 1915, loads of history with artists. I'm with Dave Vellante. I'm wearing prints today in honor of the venue and we're excited to be joined by longtime Pure Storage customer Mercedes AMG Petronas Motorsport head of IT Matt Harris. Matt, it's great to see you again. >> Hey, good up, good morning I should say. >> I think it is still morning somewhere. (laughter) >> So, Matt, you know, for folks who aren't that familiar with Formula One one of the things, you know I'm a fan. It's such a data intense sport. You've got to set up a data center 21 times a year, across the globe, with dramatically different weather conditions, humidity, etc. Give our viewers an idea of your role as head of IT and what it is that your team needs to enable the drivers to do? >> Okay, so in general terms, we're but like any other normal business around the world. Yeah we have huge amounts of data created depending on what your company is doing. Ours comes from two cars going around the track. That is the lifeblood of our of our work, our day work, and all that data is always analyzed to work out how we can improve the car. But what we really have is an infrastructure the same as many other companies. We have some slight differences as you say. We go to 21 countries. In those countries we turn around and we have 36 hours roughly to put everything together in a different world, different place and then everybody turns up and uses it as though it's a branch office. A hundred people roughly sat there working in the normal environment. We use it for five days and then we take it apart in six hours, put it in two boxes, take it to another country, and we do the same thing again. We do that 21 times. Sometimes back-to-back, sometimes with a week in between. Week in between is quite easy. Back to back sometimes we go from Canada maybe all the way across the world from Monaco within the space of a week so if we've got the flights in the way and everything else and we also end up having to an engineer a car, run a car around the track, and hopefully win races. >> So, you basically got a data kit that you take around with you. >> Yeah. >> And then what did you do before you had this capability? Was it just gut feel? Was it finger in the wind? >> Um, so. For about 15 years, we've been running what everybody's classes and Internet of Things we've been doing for about 15-20 years the car. It's got around these days around 300 sensors on it. Without those sensors realistically we'll be running the car blind and we probably couldn't even start the car let alone actually run it these days or improve things. We turn around and we're always ingesting data from the cars real-time. That real-time data actually we transfer to the garage. That's no problem at all but we also bring it back to the factory because we're limited on the number of people that are allowed to travel with the team. So, we're physically only allowed to take 60 people. Rules tell us we can only take 60 people to work on the car. Now of those, around about 15 are probably looking at data. We're generating around about half a terabyte per race weekend these days and 15 people, it's not enough eyes realistically to turn around and look at all that data all the time. So we take it back to the UK and in the UK, again, we have anywhere between another 30 and maybe 800 staff will be looking at that data to help analyze particularly on a Friday. Friday is about running the car and learning. We discussed a few minutes ago, what's the weather like? What are the tires like? What's the track like? Has there been any change in track? Has it been resurfaced? What's going on with the car compared to what we think is its optimum? And on a Friday's iterative change and learning about tire degradation, tire life, tire wear, the weather conditions, how they're going to interact with the car, all based on data. The interesting thing for me has always been that we have all this data but the two drivers in the car are the biggest sensor for us. They turn around and tell us how they felt. When they were going round corners, Was it good, bad, indifferent? But as soon as they tell us something, we always go to data. We've taken their interpretation of how their body felt, we turn around and then look at the data to prove what they've told us. So, an interesting anecdote very quickly. last year in Singapore, Valtteri was going across the bridge and he said he could feel that the throttle felt like it was cutting and we couldn't see in data and we were looking and looking and eventually he said, "No, it absolutely happens every time I cross the bridge." and they found a 20 millisecond gap in throttle application basically because there was a magnetic field that the bridge was creating so a sensor was actually cutting the throttle. he could feel it. we could fit that eventually see in data, shielded the sensor, everybody's happy. so you go from the human being could feel a 20th, a 20 millisecond gap in throttle application for us finding in data, engineering a solution, and changing things. >> So, the human's still a critical part of? (crosstalk) >> So, where does Pure Storage fit into this whole thing? and give us the before and after on that. >> So, three years ago we started working with Pure because I have two different solutions. one in the track and one in the factory. one in the track realistically I have some constraints around space, power, heat. that most people would love to take the racks as we were talking about we take around the world, they would love to leave in a nice air-conditioned computer room and just leave it there all year. we move it around but that rack of information we have to spend $298 per kilo to transport IT equipment around, well any equipment, around the world. So, we've got tons of equipment that we take around the world. it's thousands and thousands of pounds of freight cost. So, we went from forty U of old-school spinning disk, lots of complexity in cabling, administration, down to 2-3 U and 20 arrays. Now, they're more heat tolerant. I have two power cables in each and two network cables so complexity is gone. it just works. It's heat tolerant. it doesn't create a lot of heat so I haven't got the added issue of that. it's not using a huge amount of power so my UPS solution has to be smaller. so everything just got smaller, cheaper. really simply at the track, we improve the performance for everybody. from an IT point of view, we got very, very simple. incredibly easy to look after and manage but it's very reliable and performant at the same time. we then went to the factory where I've got 800 people looking at data. the problem is when a car goes round and we offload it, there's one single file. we haven't got this distributed amount of data that everybody. so you got one file that everybody's trying to open, old-school discs, you've now got contention for that one file that everybody's opening. So, people would come back from the track and go, "Why is it so slow to open information in the factory compared to at the track?" Trying to explain to them contention of data in those days was a little bit difficult but now we have 800 people that don't need to care and why that matters for us is decision making. So, if you think about qualifying, those that don't understand Formula One, we have three sessions of qualifying and the car goes out roughly two times in each qualifying session with around about a couple of minute gap in between the times the car goes out. that couple of minutes is about changing the car to be optimal for the next run. if it takes you minutes and minutes to offload data, open the data, review the information that the driver told you, and make a change, you can't go back out a second time. So, everything is about optimal performance for those engineers to optimize the performance of the car. what we are able to do now is to turn around and make sure that we're making correct decisions because rather than data taking two or three minutes to open, it's in seconds instead. So, you can look at the data, make an informed decision, change the car, hopefully improve every time the car goes out. >> One of the things, Matt, that Charlie Giancarlo, the CEO of Pure Storage, said this morning during the keynote was that less than half a percent of data in the world is analyzed. talk to us about what Pure Storage is able to facilitate for your team to be able to analyze that data. how much of that data are you able to analyze? and talk to us about the speed criticality. >> Yeah, okay, so, and quite a lot of the work over the previous probably 10 or 15 years has been very human centric. So, it's what data I know I need to go and look at to understand to be able to compute, to turn around and maybe infer information from to be able to make a better decision. So, strategy is probably one of the best places these days where the data that we're learning all the time. we have data about ourselves but we also have data about the other teams. those teams have the same data about us as well, your GPS data, timing data, so we know what's going on so we can infer information on a competitor as well as ourselves. tire degradation, tire wear, tire life, all things that you can infer that mean that you were mentioning earlier on about a pit stop. if a safety car comes out should you pick, shouldn't you pick. those decisions are now based on accurate data about whether we think competitor will pit, whether we think the competitors tires will last, can we overtake that competitor? because actually the track does or doesn't allow overtaking. So, lots of decisions made real-time based on exactly what's happening now but inferred from previous races and we're always learning all the time. everything is about the previous races. information we're learning every time. >> and how much of that heavy lifting of that data is machines versus humans. Are the machines increasingly, I don't want to say making the decisions, but helping? >> Yes, so, we're not in a position at the moment where the machines are making decisions. they're helping us to be informed, to visualize. Yeah, we work with the likes of TIBCO as well as Pure and other partners or sponsors that we have where they turn around and actually they help us to visualize that data. the problem we've got at the moment is we're still looking at all the data. where we really want to get to is looking at exceptions. So, actually the norm, don't show us that data. we don't need to know, don't need to care. >> Want the outliers. >> we want the outliers that. our problem though is that our car changes every time it goes out. So, an outlier could be because we've made a change. So, now you've got to still have some human that's helping at moto. we're trying to understand how we can use machine learning techniques. in certain places we can so image recognition and another bits and piece like that we can actually start to take advantage of but decisions necessarily around configuration and the next change to the car at the moment it's still indicators given to us by simulation and then a human at the end of the day is making the decision. >> and the data that you talked about that is on your competitors, is that a shared data source or is that but it is. >> Yeah. >> everybody shares the same data. >> every car has a transponder on it. basically it's GPS with longitude, latitude, and all sorts but incredibly accurate. if you consider the cars are doing 200 mile-an-hour, we have an accuracy of around about it's less than 10 centimeters accuracy at 200 miles per hour. Now, if you think of your GPS on your phone, you struggle to know whether you're on the right street sometimes. >> but your differentiation there is your your speed at which you can analyze the data, your algorithms, your skill sets you're telling. and then obviously we're here at Pure there's a component of that speed which is Pure. aren't you worried that your competitors are going to get your secrets or is everybody in the track use Pure Storage? >> everybody is turning around and using their own methodologies, their main, their own software. the thing for us at the moment is to make sure that we keep the really secret things ourselves, our IP sensitive, keep those to ourselves. So, what we do with our storage people know about and other teams are copying and seeing the advantages of Pure as well as some of the other tools and partners we partner with. the benefit of us though is that we have a partnership with Pure not just a purchasing so we work, we've known about some of the products. So, flash blade we knew about a long time before it was released. Yeah, we work with the team on what's coming. we know some of the advances in the technology before it's live and that's critical for us because we can get a stick, a march on everybody else even if we're six months ahead of somebody else on a technology or a way of doing something, six months is a long time in F1. >> Yeah. >> sorry Dave, I was going to say, Pure calls this the unfair advantage. (laughter) and you are, Mercedes has last fall won the fourth consecutive Constructors Championship. Coincidence, I don't know, but talk to us about this symbiotic relationship. are you also able to help influence the design of the technologies at Pure? >> Yeah, so, and I wouldn't say that we help design necessarily but they'll take into consideration our requirements and our wishes. like a number of other people that will be here, you've heard other people talking on stage and we'll always be talking about what we would like to be doing, what we could be doing if we had, I don't know, some new technology whether it's s3 connectivity to the flash blade, s whether it's NFS, whether it's SIF, whatever that would be, the containerization of them, the storage front end, whatever that would be we're always talking about how we can work with the Pure Storage to improve what we're doing. so that ideally I take out the way of the business. my ideal is that IT's not seen, it's not heard, and it just works. obviously in IT that's not always the case but. >> I want to unpack something you said earlier. you said it was I believe two or three years ago, three years ago that you brought in Pure and you had substantial performance improvement. I talk to a lot of customers and what they'll typically do in that situation is they'll compare what they saw in 2015 with what they replaced which was probably a five or eight year old array. true in your case or not? if it is true, which I suspect it is, it had to be something else that led you to Pure because you could have bought the incumbents all flash array and got you know much better performance. What, first of all true or not? and what was it that led you to Pure to switch from the incumbent which is not trivial? >> So quickly and was it five or eight year old hardware? in some places yes, some places no. So, it wasn't, we took a decision to take a step back and look at storage from a different standpoint because we just kept adding more discs to try and get around an issue, you know, and we've got a fairly strange data model to compute. we don't need much compute, we need lots of storage. so some of the models that were talked about on stage where I need, you know, Matt Baer was talking about the fact of I want some more storage, you need to buy some more compute and that was just so annoying for us. so there was different reasons but the end goal, you're quite right, performance. Yeah, we could have got it probably from anywhere and being brutally honest lots of other technologies could give the performance 'cause we don't give that level of performance maybe if your a service now or a big financial institution, we've got data, it's important. we've got critical time scales to open and save data, okay critical to us as far as erasing, but what was important for me was simplicity. Absolutely, now we got other benefits. the Evergreen model was brilliant for us but simplicity was critical. we had a storage guy that was spending his life managing storage. nobody manages storage now. they turn around and they go into Vmware. they want a new VMware server, they just spin it up, and the disk is associated. we don't have to think about it. you don't have that storage specialist any longer. Yeah, we started working with other partners, you know, Rubric for instance, integration with them, the Pure arrays as well, again enabling us to get out the way and not having to worry about backup. traditionally or we'd headed a guy that was always changing tape. I saw on the slide several time today about tape archive, I'm going I never want to see a tape archive. I just don't care about it any longer. I just want to be able to turn around and give the business, the SLAs they want on the their data and then not care about it. Also, can I then still turn around and mine that data in those archive or backup, not back up bin, the archive location? So, there's huge differences but simple is the best thing for me. we could have a small IT team that we have to look after a huge amount of kit and if it's complex it's just I can't employ the right people. >> Simplicity, performance, portability, you mentioned integration. you've got a big partner ecosystem here that. >> Yeah. >> So, having the ability to integrate seamlessly with Rubric, TIBCO, Satirize Key. >> and yeah for us, the partners are extension of the team. my team in particular because I can't turn around and just keep adding staff. we have to look after the day-to-day and keep the lights on but I can't just keep adding staff to look after a new technology. it needs to look after itself so the simplicity is absolutely. performance was a sort of a no-brainer. evergreen was a brilliant one for us because just not having to do those forklift upgrades. I think in the three years, we've gone from M450s to M70s, we've gone from M20s to M50s, M50R2s. we've done all of these. I've been stood on stage before in a day when we've been doing an upgrade during the time I've been stood on stage. You know and so people talk about the forklift upgrade, I don't have to worry about it, it doesn't happen. >> totally non-disruptive. >> Yeah, yeah. >> you do change out the controllers right? >> Yeah, so we change out controllers. we've done all sorts, we've gone from capacity upgrade so complete shells of discs and completely different on from I can't remember the exact size from two terabyte to three terabyte drives, new controllers to give us the new functionality with the nvme and all during the day. we don't do it out of hours. there's a lot of the business a scared stiff when we turn around the wisp and they go oh no no no but we're running the winds on low. we're doing this CFD, we go doesn't matter zero downtime no matter zero no planned. obviously no one play it's planned? >> Yes, it's planned downtime but the user doesn't see it they no performance no downtime no nothing that's Nevada for RIT. Yeah, well it means I don't have to keep asking people to do long shifts through the night to do a simple upgrade what should be a simple your weekends are nice back hopefully we end up with we end up racing those unfortunately okay but that's the fun stuff yeah for those who aren't that familiar was Formula One I encourage you to check it out it's one of the coolest strategic sports that is really fueled by technology it's amazing without technology honestly the cars wouldn't be anywhere near their what they are today and IT systems go we underpin everything that the company does nobody really wants to say that I t's the lifeblood of the company they don't but we need to be able to deliver and actually let the business actually take on new technologies new techniques and get out the way so we've got a huge amount of work a lot of what Charlie said on stage earlier on I've been having conversations with the guys here about autonomous data centers immutable infrastructure it's critical for us to go out the way and allow business to if they want some new VMs new storage it just happens not not need a person to be in the way make it sound so simple well you one of your primary sensors Lewis Hamilton is currently in in the number one position battery talked to us in third Monaco coming up this weekend introduction of a new hyper soft tire some pretty exciting stuff yeah so the hope of soft tires going to be interesting first race with it before the Monaco track yeah so and they originally designed it for Monaco I believe it will go to another race as well in the short term but we didn't even run it in winter testing earlier in the year so the first time we ran it was actually Barcelona test last week I've actually heard nothing about it so I don't know whether it's good bad or indifferent I don't know what's going to happen but it's going to be an interesting week because it's a very different track to where we've been to so far traditionally some of the other teams are quite strong there so the this weekend's going to be an interesting one to see where we end up Monica is always exciting grace Matt thanks so much for stopping by the cube and sharing with us what you're doing and how you're enabling technology to drive the Sportage no comatose again I'm Lisa Martin with Dave Volante live at pure storage accelerate 2018 we were at the Bill Graham Civic I'm Prince for the day stick around Dave and I will be right back with our next guest

>> Announcer: Live from the Moscone Center, it's The Cube covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. >> Welcome back to our exclusive Cube coverage here at AWS, Amazon Web Services Summit 2018 in San Francisco. I'm John Furrier with my cohost, Stu Miniman. We have a special guest. We have an influencer, authority figure on AWS, Corey Quinn, editor of Last Week in AWS, also has got a podcast called Screaming, >> Corey: In the Cloud. >> Screaminginthecloud.com just launched. Corey, great to have you on. Thanks for joining us. >> No, thank you for letting me indulge my ongoing love affair with the sound of my own voice. (laughing) >> Well we love to have you on and again, love the commentary on the keynote on Twitter. Lot of action, we were in the front row, kind of getting all the scene. Okay, if you're going to write the newsletter next week for what happened this week, if this week was last week, next week, what's your take on this? Because again, Amazon keeps pounding the freight train that's just the cadence of AWF announcements. But they're laying it out clear. They're putting up the numbers. They're putting out the architecture. They're putting out machine learning. It's more than developers right now. What's your analysis, what's your take of what's happening this week? >> I think that certain trends are continuing to evolve that we've seen before where it used to be that if you're picking an entire technology that you're going to bet your business on, what you're going to build on next. It used to be which vendor do I pick, which software do I pick? Now even staying purely within the AWS ecosystem, that question still continues to grow. Oh so I want to use a database, great. I have 12 of them that I can choose between. And whatever I pick, the consensus is unanimous, I'm wrong. So there needs to be, I still think there needs to be some thoughtful analysis done as far as are these services solving different problems. If so, what are the differentiating points? Right now, I think the consensus emerges that when you look into a product or service offering from AWS, the first reaction all of us feel is to some extent confusion. I'm lost, I'm scared. I don't really know what's going on. And whatever I'm about to do, I feel like I'm about to do it badly. >> Yes, scale is the big point. I want to get your reaction. Matt Wood, Dr. Matt Wood, Cube alum, been on many times, he nailed it I thought when he said, look it, machine learning and data analysis was on megabytes and gigabytes, they're offering petaflop level compute, high performance, and then Werner Vogels has also said something around the services where, you can open things up in parallel scale. So, what's your reaction to that, as you look at that and say whoa, I've got a set of services I can launch in parallel, and the scale of leveraging that petaflops. I mean, this is kind of like the new, you know, compute model. Your reaction is it real? Are customers ready for it? Where are we in that evolutionary customer journey? Are they still cavemen trying to figure out how to make fire and make the wheel? I mean where are we with this? >> I think that we see the same thing continuing to emerge as far as patterns go, where they talk about, yes there's this service. Just start using it and it scales forever. And that's great in theory, but in practice, all of the demos, all of the quick starts, all of the examples, paint by numbers examples that they'll give you, tend to be at very small scale. And yes, it works really well when you have effectively five instances all playing together. When you have 5,000 of those instances, a lot of sharp edges start to emerge. Scale becomes a problem. Fail overs take far longer. And let's not even talk about what the bill does at that point. Additionally once you're at that point, it's very difficult to change course. If I write a silly blog, and effectively baby seals get more hits than this thing does, it's not that difficult for me to migrate that. Whereas if I'm dealing with large scale production traffic that's earning me money on a permanent basis, moving that is no longer trivial or in some cases feasible at all. >> Yeah Corey, how does anybody reasonably make a decision as to how they're going to build something because tomorrow, everything might change. You said oh okay great, I had my environment and I kind of you know, built my architecture a certain way, oh wait there's a new container service. Oh, and start building a, oh wait now there's the orchestrated version of that that I need to change to. Oh wait, now there's a serverless built way that kind of does it in a similar way. So you know, it seems like it used to be the best time to do things would've been two months ago, but now I should do it now. Now the answer is, the best time for me to do things would be if I could wait another quarter, but really I have to get started now. >> I tend to put as much on future Corey as I possibly can. The problem is that at one time I could've sat here and said the same thing to you about, oh virtualization is the way to go. You should migrate your existing bare metal servers there. And then from virtualization to Cloud and Cloud to containers. Then containers to serverless. And this narrative doesn't ever change. It's oh what you're doing is terrible and broken. The lords of thought have decried that now it's time to do this differently, and that's great, but what's the business use case for doing it? Well, we did this thing that effectively people get on stage at keynotes and make fun of us for now, so we should really change it. Okay maybe, but why? Is there a business value driving that decision? And I think that gets lost in the weeds of the new shiny conference ware that gets trotted out. >> Well I mean Amazon's not, I mean they're being pretty forthright. I mean, you can't deny what Intuit put out there today. The Intuit head of machine learning and data science laid out old way, new way. Classic case of old way, new way. Eight months, six to eight months, ton of cluster, you-know-what going on as things changed it. They're just data scientists. They're not back-end developers. They went to one week. Nine months to one week. That's undeniable right? I mean how do you, I mean that's a big company but, that seems to be the big enchilada that Amazon's going for, not the pockets of digital disruption. You know what I'm saying? So it's like, how do you square that out? I mean how do you think about that? >> Cloudability had a great survey that they released the results of somewhat recently where they were discussing that something like four or five of the, or I'm sorry 85% of the global spend on AWS went to four or five services that all have been around for a long time. RDS, EC2, S3, PBS, Data Transfer. And so as much as people talk about this and you're seeing pockets of this, it's not the common gaze by a wide margin. People don't get up on stage and talk about, well I have these bunch of EC2 instances behind a low balancer, storing data on S3 and that's good enough for me, because that's not interesting anymore. People know how to do that. Instead, they're talking about these far future things that definitely add capability, but do come at a cost-- >> I mean it's the classic head room. It's like here's some head room, but at the end of the day it's EC2, S3, Kinesis, Redshift, bunch of services that's U.S that seem to dominate. The question I want to ask you is that they always flaunt out the, every year it changes, Kinesis was at one point the fastest growing service in the history of AWS. Now it's Aurora. We made a, I made a prediction on the opening that a SageMaker will be the fastest growing service, because there just seemed to be so much interest in turn-key machine learning. It's hard as you-know-what to do it. >> I agree. >> Your thoughts on SageMaker? >> In one of my issues a few weeks back, I wound up asking, so who's using SageMaker and for what? And the response was ridiculous. What astounded me was that no two answers were alike as far as what the use case was. But they all started the same way. I'm not a data scientist, but. So this is something that's becoming-- >> John: What does that mean to you? What does that tell you? >> It tells me that everyone thinks they're unqualified to be playing around in the data science world, but they're still seeing results. >> But Corey I wonder because you know, think back a few years ago. That's what part of the promise of big data, is we have all this data and we're going to be able to have the business analysts rather than you know, some PhD sort this out. And machine learning is more right. We want to have these tools and we want to democratize data, you know. Data is the new bacon. It's the new oil. Data's the new everything. So you know, machine learning, you think this is all vapor and promise, or do you think it's real? >> I think big data is very real and very important. Ask anyone who sells storage by the gigabyte. And they will agree with me. In practice I think it's one of those areas where the allure is fascinating but the implementation is challenging. Okay we have history going back 20 years of every purchase someone has ever made in our book store. That's great, why do I still wind up getting recommendations? >> Well yeah and I guess, I want to talk that it was the, I see it more as, everything that was big data is now kind of moving to the ML and AI stage. Because big data didn't deliver on it, will this new wave deliver on the promise of really extracting value from my data? And it's things like this, live data. It's doing things now with my data, not the historical, lots of different types of data that we were trying to do with like the Hadoops of the world. >> Got ya. I think it's a great move because either yes it will or no it won't, but if it doesn't, you're going to see emergent behaviors of so why didn't it work? Well we don't understand the model that this system has constructed, so we can't even tell you why it's replacing the character I with some weird character that's unprintable, so let alone why we decide to target a segment of customers who never buys anything. So it does become defensible from that perspective. Whether there's something serious there that's going to wind up driving a revolution in the world of technology, I think it's too soon to say and I wouldn't dare to predict. But I will be sarcastic about it either way. >> Okay well let's get sarcastic for a second. I wan to talk to you about some moves other people are making. We'll get to the competition in a minute but Salesforce required MuleSoft. That got a lot of news and we were speculating on our studio session this week or last week with the CEO of Rubric that it's great for Salesforce. It can bring structured data in, on PRIM and the Cloud. Salesforce is one big SaaS platform. Amazon is trying to SaaS-ify business through the Cloud. So, but one of the things that's missing from MuleSoft is the unstructured data. So the question for you is, how are you seeing and how is your community looking at the role of the data as a strategic asset in a modern stack, one, both structured and unstructured data, is that becoming, even happening or is it more like, well we don't even know what it means. Your thoughts? >> I think that there's been a long history of people having data in a variety of formats and being able to work with that does require some structure. That's why we're seeing things emerging around S3's, increasing capabilities, being able to manipulate data at rest. We're seeing that with S3 and Glacier Select. We're seeing it with Athena which is named after the goddess of spending money on Cloud services, and there's a number of different tooling options that are, okay we're not going to move three x-abytes of data in so we have to do something with where it is. As far as doing any form of analysis on it, there needs to be some structure to it in order for that to make sense. From that perspective, MuleSoft was a brilliant acquisition. The question is, is what is SalesForce going to do with that? They have a history of acquisition, some of which have gone extremely well. Others of which we prefer not to talk about in polite company. >> It comes back down to the IDE thing. How many IDE's does Salesforce have now? I mean it's a huge number. >> I'm sure there's three more since we've started talking. (laughing) >> Yeah so Corey, you brought up, you know, money. So you know, the trillion dollar, what feedback are you getting from the community? You know there's always, well I get on Amazon and then my bills continue to grow and continue to grow. Same thing at Salesforce by the way if you use them. So you know, there's always as you gain power, people will push back against it. We saw with with Mike Hichwa with Oracle. I hear it some but it's not an overriding thing from when I talk to customers about Amazon. But I'm curious what you're hearing. Where are the customers feeling they're getting squeezed? Where is it you know, phenomenal? What are you seeing kind of on the monetary side of Cloud? >> In my day job, I solve one problem. I fix the horrifying AWS bill, both in terms of dollars and cents as well as analysis and allocation. And what astonishes me, and I'm still not sure how they did it. It's that AWS has somehow put the onus onto the customer. If you or I go out and we buy a $150,000 Ferrari, we wake up with a little bit of buyer's remorse of dear lord, that was an awful lot of money. When you do the equivalent in AWS, you look at that, and instead of blaming the vendor for overcharging, instead we feel wow, I'm not smart enough. I haven't managed that appropriately. Somehow it's my fault that I'm writing what looks like a phone number of a check every month over to AWS. >> John: It creeps up on you. >> It does. It's the boiling a frog problem. And by the time people start to take it seriously, there's a lot of ill will. There's a sense of, our team is terrible, and wasn't caring about this. But you don't ever cost-optimize your way to success. That's something you do once you have something that's up and working and viable. You don't start to build a product day one for the least possible amount of money and expect to attain any success. >> Well let's talk about that real quick to end the segment because I think that's a really important thing. Success is a double-edged sword. The benefit of the Cloud is to buy what you need, get proof of concept going, get some fly wheels going or whatever, virtuous circle of the application. But at some point, you hit a tipping point of oh shit this is working. And then the bill is huge. Better than over-provisioning and having a failed product. So where's that point with you guys or with your customers? Is there like analytics you do? Is that more of a subjective qualitative thing? You say, okay are you successful? Now let's look at it. So how do you deal with customers? 'Cause I can imagine that success is, it becomes the opportunity but also the problem. >> I think it's one of those, you know it when you see it type of moments, where if a company is spending $80,000 a month on their Cloud environment and could be spending 40, that's more interesting to a company that's three people than it is to an engineering team of 50. At that point, sorry they're embezzling more than that in office supplies every month. So that's not the best opportunity to start doing an optimization pass. More important than both of those scales to me has always been about understanding the drivers of it. So what is it that's costing that? Is it a bunch of steady state things that aren't doing work most of the time? Well, maybe there's an auto-scaling story in there. Maybe there's a serverless opportunity. Maybe nobody's using that product and it's time to start looking at rolling it in to something. >> They've left the lights on right? So to speak. >> Exactly. >> The server's are still up. Wait a minute, take them down. So, writing code, analytics, is that the answer? >> All of the above. In a vacuum, if you spin up an instance today, and don't touch it again, you will retire before that instance does. And it will continue to charge you every hour of every day. Understanding and being able to attribute who spun that up, when was it done, why was it done, and what project is it tied to? Is it some failed experiment someone did who hasn't worked here in six months? Or is that now our master database? We kind of need to know in either direction what that looks like. >> Alright before we wrap, you got to tell us, what do we expect to hear from your podcast? >> Good question. My podcast generally focuses on one-on-one conversations with people doing interesting things in the world of Cloud, which is vague enough for me to get away with almost anything as far as it goes. It's less sarcastic and snarky than some of my other work, and more at the why instead of the how. I'm not going to sit here and explain how to use an ABI. There are people far better at that than I am. But I will talk about why you might use a service, and what problem it reports to solve. >> Alright Corey, great to have you on. Uh the Screaming Pod, Screaming Cloud, >> Corey: ScreamingInTheCloud.com >> ScreamingInTheCloud.com, it's a podcast. Corey thanks for coming on and sharing the commentary, the insight on AWS, the how and the why, the Cube breaking down. All the action here in Moscone Western San Francisco, AWS 2018 Summit, back after more, after this short break. (spacey music)

>> Narrator: From the Silicon Angle Media office, in Boston, Massachusets. It's The Cube. Now here's you host, Stu Miniman. >> Hi, I'm Stu Miniman and we're coming to you from the Boston area studio here of The Cube. Excited to talk about some of my favorite topics. Talking about the culture, innovation, and really transformation in what's happening in data center. Digital transformation is on everybody's mind. Specifically happy to welcome Mike Grandinetti who is the Chief Marketing and Corporate Strategy Officer with Reduxio. Mike, thanks so much for joining us. >> Stu, thank you so much for having me. Great to be out here with you today. >> Alright, so you're a local guy? >> Mike: Yeah. >> We're glad that you could join us here. Before we jump into the company tells a little about your background, what you worked on, what brought you to Reduxio. >> In a nutshell I guess my background is all about innovation. I've sort of eat, breathe and slept innovation for the last 25 years of my career. So I started off as an engineer in Silicon Valley with HP back when Bill and Dave were still around. At a time when it was America's most admired company. Was a remarkable sort of introduction to what is possible. Went back, got my MBA, did several years at McKinzie doing corporate strategy consulting. Mostly around innovation related projects. And then I moved up here to Boston to be a part of the first of what is now eight consecutive enterprise venture capital backed start ups. And I've been lucky enough that two of those went public on the NASDAQ. The prior seven have all been acquired by companies like AT&T and Oracle. And now Reduxio is my eighth start up. We're really having a great time building this business. >> Great, we're definitely going to big into some of the innovations of Redux I O. >> Yes. >> So the name kind of tells itself. We've seen a few companies with the I O at the end. We've talked so much that when we've talked about kind of 2018 data is at the center of everything. Really what is driving business. So for an audience that hasn't run across Reduxio kind of give us the why and the what. >> Yeah, and so to your point, data's driving everything. Mark Andressen famously said software's eating the world. I think if we were to update that it's data is eating the world. And so I think you and I have had this discussion off camera. Whether it's fair or not, I think it's true. And it needs to be stated that the amount of innovation that has occurred in the storage industry over the last 20 years, has been disappointing at best. The solutions that have evolved have evolved in an extremely fragmented way. They are over, way too complex. They're way too expensive. And because it's a collection of piece parts, you've got to manage multiple screens, multiple learning curves. And a lot of things fall through the cracks. So when you go and look at some of the research data from a wide range of analysts, what you hear from them is there's this extraordinary lack of confidence that even though I've spend a ton of money, invested a lot of staff time and attention to building out this infrastructure, very lacking in confidence that I'm actually going to get that data back when I need it. So it's the old adage, it's time to fix it. So this is exactly what the founders of Reduxio saw. They were looking at this evolutionary path and saying people are just making it worse. So they did what many people would condsider to be radical. They threw out the entire playbook of what storage architecture has been and they took a clean sheet of paper, design centric approach. What are the use cases? Where are we in the world with regard to technology? And how do we design and experience for storage admin or BD admin or a person in the dev center that doesn't require a PhD in storage? And so that's kind of what the premise was. >> Yeah, so many things there that there are to dig into. Absolutely. I live, I worked for one of the storage companies for a decade. Absolutely complexity is how we would describe it. And what companies are looking for today, is they need simplicity. They need to focus on the business. Turing dials and worrying about do I have enough capacity? Do I have enough performance? Do I have enough of those things, is not what drives the business. >> Mike: Exactly. >> They need to focus on their applications. The bit flip we saw in big data, and we can argue whether or not big data was hype or whatever we had there, but it was oh my gosh I'm getting all this data to oh my gosh I have all of this data and therefore I can do more things, I can find more value. >> Mike: Absolutely. >> I worry a little bit when I hear things like oh, the storage admin. >> Yeah. >> The storage admin's job before was how to I triage and kind of deal with those issues? Many solutions now you look at the wave of hyper convergence. Let's push that to a cloud architect or the virtualization layer. How do we start with a clean slate and get out of the storage business and get into the data business? >> Mike: I love it. So I'm going to bring you back ten years to one of the most remarkable product introductions that has ever been conducted on this planet. It was the introduction of the iPhone. And if you recall in those first five minutes that Steve Jobs took the stage in a way that only Steve Jobs could. He went onto tease the audience by saying that we are going to be introducing three products today. And then over the next minute or two became clear that it wasn't three products, it was one very innovative product at the time. The iPhone. What they basically did is they integrated these three previously disparate pieces of technology. Certainly the mobile phone but also a music player and an internet navigator. Behind this gorgeous revolutionary user interface. So what we've tried to do is take a page out of the Job's iPhone innovation. We're integrating. And Forrester Research has written an incredible report about this and others, IDC and others, have consistently supported it. Chris Malore from the Register has written about this at length as well. Reduxio is integrating primary and secondary storage along with built in data protection. So those previously siloed capabilities are now one. We're also, like Jobs did, when you looked at the old style smart phone, the BlackBerry and the Trio and the- ya know all of those things that had all of those keyboards, is we've created a user interface using game designers so when our customers go home at night and they log into Reduxio, their little kids will say, hey dad what game are you playing? And dad will say, I'm not playing a game. I'm actually working on Reduxio. And so what that's done for us I think is it's allowed us to be able to drop a Reduxio system into any number of use cases with someone who may not have the luxury of being deep in storage. And literally get time to value that they put production workloads on the system that day. >> It's interesting, another piece that I'll draw from your analogy is when you talk about how did Apple take all of those pieces. And it's kind of certain technologies moving along. But there's one specific technology that really helped drive that adoption. And it's Flash. >> Mike: Yes. >> And the consumer adoption of Flash ten years ago drove the wave that we've seen in enterprise storage. >> Right. >> So help connect the dots for us, because we look at- I remember a decade ago primary to secondary storage oh I'll give you a big eleven refrigerator size cabinet and you can do both. >> Mike: Right, sure. >> But I put expensive stuff here, I put cheap stuff here. I used the software to put it together. I'm assuming I can consolidate it down and I think Flash has something to do with it. >> Yeah, and so it's a multi tiered system. The array itself. It's an appliance. And obviously most of the value is in the software. There's a management platform that allows us to peer deep into the data. But everything is time stamped and indexed. So we have a global view of the data. And you can tier it, the most hot data very mission critical, business app data, goes to Flash. Secondary data can go to spinning disk or now we can archive to the cloud. Specifically any S3 target, Amazon or any S3 target. But what I think makes it very relevant is we've illuminated the notion of snapshotting. So we've built something that we call the time OS or the time operating system. And it's a time machine for your data. What happens is rather than incur that incredible burden of having to schedule snapshots, that only requires you at another incredible heroic effort to bring the data back, you have continuous data protection. I can go back at any point in time and literally with a very graphical screen point and say I want to bring data back from two seconds ago. And one of our best examples of that is we had a customer who had been attacked, has suffered from a ransomware attack. They went down for a week, they went down hard for a week. And they came and found Reduxio. They got attacked again. And the second time around they lost only two minutes of data. And the recovery time was 20 minutes. So this is what we enable you to do. By being able to give you access to wherever you're data may be, anywhere in the world, you can- we're approaching near zero RPO and RTO. >> Mike, there's been a number of companies that come and said data protection's been broken. We've been hearing that for a while. I think right down the road from us, like Tiffeo, company that looked at data management. Companies like Cohesity and Rubric, have quite a bit of buzz. Give us a little compare, contrast how Redxio looks at it verses some of those other- >> Yeah, and I'd say again, for anybody watching I think the Forrester Research Report outlines Reduxio, Cohesity and Rubric, right? And of course Cohesity and Rubric are doing an extraordinary job. They're scaling rapidly. They've got world class in Silicon Valley money in the company. They've got a world class client base. I think the primary difference is that we are bringing that third component. We're integrating primary storage along with secondary storage in data protection. Both of them are focusing just on the secondary and the data protection. We take issue architecturally with the fact that you've got to make additional copies. We take issue with the fact that the way they're approaching this actually they're in some ways exacerbating the problem because they're creating more data. But at the same time, they're also, for a given amount of capability two to three times the cost. So what we're hearing from a lot of our customers and our vars that sell both is they're walking into a lot of more, let's call them price sensitive accounts. Where they don't believe that the incremental value of what Cohesity or Rubric is offering is easily justifiable. There's going to be some pretty extreme use cases to justify a $300,000 initial investment as you go into the data center. >> Another piece, when I talk to companies today, one of the biggest challenges they have is really figuring out what their strategy is and how that fits. You talked about tiering and how the cloud fits into it, but how does Reduxio fit in that overall cloud strategy for companies today? >> Again, it's very early in our product evolution and so with version three which we announced back in late June, we allow companies to archive to the cloud. But do instantaneous recovery from the cloud. So we have two capabilities. One is called no migrate. So there's no longer a need to migrate data. So you were at the Amazon invent show and you saw the snowmobile get rolled out. And the reason that Amazon rolled that snowmobile and at first I thought it was a joke, is because it takes an incredible amount of time and effort to move data from one data center to the next. Reduxio has this no migrate capability where if I need to move data from that data center, I set that data in motion. And I don't know if you're a Trekkie or not, but you remember the teleporter? In version three we've created a teleporter. You can move that data from the cloud and although it may take a long time for that data to actually get to its target, you can start working on that app as if that data had already been migrated. When we run usability tests, and I remember one of them very specifically. And I know that you speak a little bit of Hebrew. I speak zero Hebrew. But I can remember watching one of our Israeli customers seeing this happen and this visceral reaction, like oh my god, I can't believe they did that. So we're trying to bring that end to end ease of use experience to managing and protecting your data wherever it may be. Bringing it back with almost zero RPOs, zero RTO. >> Mike, one of the questions, I've been talking to a number of CMOs lately, and just you've worked for a number of start ups. Today, digital transformations on the mind, what's the changing role of the CMO today? What have you seen the last five to ten years that's different and exciting? >> It's a great question. And I'd say that, and again, I did my first start up in 1991. So I can't begin to tell you how much high tech marketing has changed. But everything changed with social, digital and inbound marketing. It used to be that the sales team was responsible for filling the funnel. It is very clear that is an incredibly non scalable unproductive effort. And so we now are all about acquiring high quality prospects. We're a hub spot shop. We're a highly automated shop. And we are very biased toward digital and social. Is doesn't mean that we're not going to events and things like that but we feel that the way that we're going to scale this business, especially when we compete against big guys like Dell EMC and HP and others, there's no way that we can go person to person. So I'm not a very big fan of cold calling. I'm not a very big fan of going to trade shows. And collecting business cards in fish bowls and giving away tee shirts. We really believe that our customers are too busy, the know what they need when they need it. They've built a fortress around themselves. They're getting hammered. Just like I'm a CMO. And I must get 150 LinkedIn inmails and emails a day telling me about the next great lead management service. I can't even imagine what our customers are putting up with. So our job is to find relevant personas with highly relevant content at the moment that that is relevant to them. And there's many ways to do that, but this is really what we have to do with the data. >> So, Mike, at the beginning of the conversation we talked a little bit about innovation. >> Mike: Yes. >> Those of us that have been in a while, they're too many peers of mine that I think if you say the word innovation they roll their eyes. You have the great opportunity, you're working with master students around the globe, talk to us the people coming out of those programs. What does innovation mean today? What are they looking for, from a career standpoint? >> It's a great question. I think you and I could probably go for the next three hours on this subject so we'll have to be careful. >> We'll make sure to post on the website the expanded audio. >> Okay, but I mean innovation is such an overused word. And most companies really can't spell it and they can't spell it because their culture doesn't allow for it. So first and foremost, I think any innovative company or any innovative team starts with a culture that is all about trying to manage at the bleeding edge of best practices and really understand what's current. I have the blessing of being both the Chief Marketing and Corporate Strategy Officer of Reduxio and a global professor of innovation entrepreneurship at the Hult International School of Business. I teach between 1,200 and 1,500 students a year. I teach them courses in entrepreneurship, in innovation, in digital marketing. And I run hackathons on campus. We do a lot of events that give me an insight into who's passionate about innovation. And it's one thing to think innovation is interesting, because you can get a good job. It's another thing to actually have the comfort level of living in a world of ambiguity and high velocity. So a lot of it is, I'm looking for students that really want to sort of push the envelope. And they exhibit that in the classroom, they exhibit that in hackathons. They exhibit that in some of the internships that we take. They exhibit it by getting certified on HubSpot. Without me telling them to. Getting certified on Idio without me telling them to. Going to conferences. Learning. And then me learning from them. Because nobody can know everything. It's just so much new stuff going on right now. I've now got a team of 11 people and nine of them were my former students. I had a chance to observe them in action over 18 months and they're world class. And they have that innovation gene in their DNA. We're really at a point where I'm learning from them everyday. It's a very symbiotic relationship. >> Mike, for closing comments, I want to give you the opportunity, people find out more about Reduxio. What should we be looking for in 2018? >> Yeah, and so again, the one thing is will say is we are now at 200 distinct customers. We have in a very short period of time, and you know, when you sell into the data center people don't have a real sense of humor. It's pretty important that the stuff works. So the first thing I would say is we've gotten to that point now where we've got a lot of very significant customer references across websites and a lot of peer review sites. So we're now, so 2018 is building on that foundation. I think what you're going to see from us is couple of very radically innovative new projects. One a software only project. That will allow us to drive an inflection point in growth. By making available some of our core capabilities to anybody. Whether they own a Reduxio system or not. We really want to go big now. We've validated the architecture. We've got some great early indications from the market that this stuff works as advertised. Our customers are telling us we're simplifying their lives, we're making them more productive. And 2018 is about to really kick this thing into high gear. >> Stu: Mike Grandinetti, pleasure chatting with you. Thanks so much for sharing. And thank you for watching The Cube. >> Mike: Great. (upbeat music)

>> Narrator: Live from Las Vegas it's the Cube. Covering Veritas Vision 2017. Brought to you by Veritas. >> Welcome back to Las Vegas everybody. This is the wrap for Veritas 2017. This is the Cube, the leader in live tech coverage, I'm Dave Vellante with Stu Mindeman. And Stu, two days where we're witnessing the evolution transformation of Veritas. Veritas used to be the gold standard for what wasn't known at the time as software design but just software function to deliver storage capabilities, no hardware agenda and now you're seeing investment under the leadership of new management. Some innovation, a cycle that's quite rapid. It's hard to tell how much of that is really taking shape in the customer base. Seems like the channel, partners are picking up on it. Customers are still sort of trying to figure out how to move beyond so their existing legacy situation, it's like Heath Townsend says. The vendor community tends to move at the speed of CIO. It's a great quote. But overall, I think very good show. Some surprises here in terms of specifically the breadth of the Veritas portfolio not just a backup company. Really focused on data management, focused on information management which obviously is relevant in the digital economy. What were your takeaways? >> So Dave the big strategy is the 360 data management. And I think one of the things we teased out in here is first of all, nobody thinks the cloud is simple. Multicloud, where customers are and when you dig into it and what Veritas has learned in the last year is that there's a lot of work to be done. Where are their deeper integrations that they need to have. There's different requirements from the different partners here. See Microsoft, the top level sponsor. Russinovich up on stage, giving kind of his usual hybrid cloud with a lot of open source pitch there but seems a good fit from the customers and partners that we talked to here to say Microsoft aligns well with what Veritas is doing. Amazon big player here. Lot of integration is happening behind the scenes to make sure that Veritas can work there. And then you follow Google of course, big focus around data, good to see where Veritas is going. We had a nice conversation with Google. Google seems very open on a lot of these not as much focus on some of the functionality that Veritas has so it's a good natural fit and then IBM and Oracle kind of rounding out the big players here. The thing I've come in, I think every show I've gone to this year Dave, is where do companies that have been around for more than a couple of years fit in this multicloud world and absolutely that's where the puck's going as Bill Coleman said that's where they're betting the company and putting it forward and we wondered coming in would it be like ah, yeah. This is a net backup and Veritas foundation suite with a new coat of paint on it? And no, I mean they really brought in a lot of new management team sure there's engineers here with a lot of expertise and experience to build on to know how to do this but I was pretty impressed with what I saw this week Dave. >> So no hardware agenda is evolving to no cloud agenda. That's one of the things we learned here and we had a good discussion. Got a little bit awkward at times but good discussion about why Veritas relative to the other players here. And what the answer we got back which we had to tease it out a little bit was essentially the upstart guys, the Rubrics, the Cohesity's to a certain extent Zerto I think they tried to put Veeam in that category we'll come back to Veeam it's kind of interesting Maybe not big enough to deliver on that multicloud vision. And they're really not even trying. Cohesity and Rubric I don't know. >> They've added a lot of cloud recently, actually Rubric's been doing it for a while, Cohesity definitely seen there. They understand that cloud but I think what maybe I'd say Dave, they tend to start from an on premises piece as opposed to you say this Veritas strategy is it doesn't matter and what many of the player, right, where is there natural gravity? Is it on premises or is in the public cloud and Nutanix, they partner with Google, they're doing the cloud. But absolutely, most of their >> Dave: They make more money. >> Stu: Most of their revenue is, you know, is found there. >> So the upstarts I kind of buy the Veritas argument that there maybe doesn't have the Gravitas and the heft to attack that multicloud other than pick at it and grow and they'll do hundreds of millions of dollars in revenue and maybe get to a billion and have a great exit. I think that'll happen. And then the other guys, the big guys, HPE, Dell EMC, IBM, they certainly have the capabilities to do that. But is it going to be the main focus of those companies? HPE maybe. We'll see. HPE and Veeam are an interesting partnership. My information suggests that Veeam is driving many tens of millions of dollars through Hewlett Packard Enterprise now that the microfocus deal has been done and they got rid of data protector. IBM they're kind of re-invigorating the storage business, data production is part of that. Dell EMC is I think challenged to invest They can't invest in as much as they used to certainly not in acquisitions. The acquisition pipeline is basically dried up. >> Stu: Dave, Dave, look at the DataMain was a great acquisition by EMC at the time now under Dell EMC. I mean, you're probably closer to it than me. I don't hear a strong cloud message coming out of that group when we talk about backup and the like. Dell corporate, of course they've got Microsoft partnerships Veeam has Amazon partnerships but it very much is tied to appliances or arrays or servers at the main piece, it's not a software message which is where Veritas is. >> Dave: If you look at Dell EMC's acquisitions recently, Isilon a couple billion, two and a half billion I think, Data Domain two and a half billion, DSSD a billion, which really hasn't turned into much at this point in time anyway. Extreme IO, not sure what they paid but you know you're hearing ebbs and flows on that but that my point is that is how under Joe Tucci EMC innovated. They would incrementally add on to their existing platforms. You were there. You saw it. And then they would invest in what Joe Tucci used to call tuck in acquisitions. And all that was well and good and they were able to sort of keep, not sort of, they were able to keep pace with the industry. That's basically stopped. That strategy. We've seen cuts and layoffs but still a financial windfall I think is coming for Dell. And VMware is a secret sauce there so we don't have to dig into that too much but my point is that services is going to be the lynchpin for that company in terms of attacking multicloud services and VMware. So now you >> Stu: And pivotal of course too. >> Dave: And pivotal as well, that's right. Great point. Now you come back to Veritas. Focused on that strategy of information management. Investing apparently in RND. Seemingly patient capital with Carlyle so you know me, I like to unpack the numbers. From what I can tell, my sources and got to do some more digging on this but when Veritas was acquired by Carlyle it was about 2.3 billion dollar company, wouldn't surprise me if on an income statement basis it's actually shrunk. It wouldn't surprise me at all. In fact, Bill Coleman kind of hinted to that. And especially if you start looking at rateable revenue models, maybe bookings could be up and I've heard numbers as high as 2.6, 2.7 billion but who knows. I've also heard now, the evaluation at the time of the acquisition was 7 billion and change. I've heard numbers as high as 14, 15 billion now, maybe a little inflated but I think easily over ten. And I think this company has an opportunity to get to three billion, get the evaluation up to 15, maybe even 20 billion. Big win for the private equity investors and the key to that, I think, is going to be a continuous investment. Go to market that aligns to those new areas that they're talking about and very importantly the ecosystem. I want to see this thing start exploding. The big highlights here were the cloud guys. What else would you highlight? You know, you walk around the shows a lot of smaller partners here Really would like to see that ecosystem grow. That's something that we're going to watch. And the audience grow. I think this show is up from last year next year I believe it's in Las Vegas again moving to the Cosmopolitan little bit better venue, bigger venue we'll see if they can get up to where the big boys go over time but overall I'd say pretty good second year for Veritas Vision. >> Yeah, you know Dave, when you look at the different areas Veritas has a full suite of software to find storage. The analogy I've used all the time storage industry is a knife fight in a dark alley. So you've got some big players out there that all have their software defined storage messaging out there of course Veritas would say they all have the hardware agenda. There's some truth to that but Veritas also has to partner with a bunch of these players to get there so where did they get the reach, how does the channel help them punch above their white, the differences there a two and a half, 2.6 billion dollar run rate company, revenue company that is private. So you know, they're trusted because they have history. They're not a small startup can this innovation and all the new team members come in and definitely the cloud piece is pretty interesting, Dave we see, we'll be back at Reinvent with the Cube and Veritas will have a presence there. Amazon, huge ecosystem, where do they play where do they show up, data, we've said so many times on here it becomes repetitive data is the new oil and customers need to take advantage of them. Can Veritas' message get them at the table and in a conversation where so much, it's about infrastructure and I love the message here at the show. It's not infrastructure technology it's information technology and we want to put a highlight on that so like the message, like where it's going, here are the customers but can they get at the table when there's so many different there's the startups, there's the big players everybody pulling at where the customers are and the GDPR was an interesting angle 'cause it was the crispest, the most crisp conversation I've heard on GDPR. I know you've been talking about it at least the last six months on some Cube interviews, I've done a number of interviews. But it really crystallized for me this week at the show. >> I'm glad you mentioned that because I've done a couple shows where GDPR has come up and I was like okay, yeah we get it. It's coming. It's nasty. How are you going to help me again? And I think Veritas did a really good job this week of saying look, we are here to help. We're going to start with Discovery and they sort of laid out the journey and I think they made a good case for their portfolio aligning well with solving that problem. So this could be a nice little kicker there. One of the things I wanted to sort of riff on a little bit was the tam, the data protection space. It reminds when ServiceNow went public I know it was a story about Gartner Antlis was very negative on and saying a helpdesk is a dead business and then Frank Sluman did a masterful job of expanding the tam, explaining that tam, guiding the company to a massive opportunity. And I see a similar dynamic here. On the one hand I say wow. Got a lot of companies in this data protection space even though it's exploding lot of VC money coming in, you're seeing new entrants like Datrium now gets in the space even though they're not just backup, that's not their primary but I mean you certainly saw SimpliVity with what's kind of their specialty. But guys like Datos.IO and some of these new guys coming in like we talked about Rubric, etc there's a lot of players here. Is the market big enough to support those? Part of me says ehh, I don't know but then I think back to that ServiceNow example. I think the tam is going to explode because it's not about backup. And it's not even just about data protection. It is about information management and I think Veritas got that right. What I like about their chances is they're big. They've got a big install base and I think their vision is right and they don't have that cloud agenda. They're a pure software company even though they do sell some appliances sometimes. And they got what seemingly is good management. I think I'd like to see them attract even more management as they grow and as they start executing this and as I say, the ecosystem has got to grow. >> Yeah, so Dave, IT has to deal with information governance. That's the defense they need to play. There's going to be money thrown at that. Some of the conversation we had this week IT operations becomes one of those tail winds that should lift companies like Veritas to be able to have further discussion and grow those budgets to be able to be a much more important piece. >> Alright good, Stu. Thank you. Good working with you again. It's been a long few weeks here but we're at it again next week. The Cube is at Big Data NYC which is done in conjunction with Strata in New York City. We've got a big party on Wednesday night. Actually we've got a presentation, Peter Burrows, Neil Raden, Jim Cubillas and we got a panel. Talking about software eating the edge. That's on Wednesday at 37 Pillars. Tweet me at @dvellante if you don't have an invitation I'll get you one although I heard there was a waitlist last week but we'll get you in, don't worry. And then we're also at Splunk next week, I'm going to be at Dotconf in DC. We've done Dotconf since I think 2011 was the first year we did Dotconf. >> And I'll be keeping a big eye on Microsoft Ignite next week while we don't have the Cube there. Obviously pretty important things like Aster Stack expected to roll out and got so many shows Dave. >> So the Cube, we love digital content creating content, sharing with you our community. Follow @thecube that handle for the Cube gems, you'll see a bunch of videos. Go to thecube.net, that's where we host all the videos from all of our shows. And then siliconangle.com is where we write up our news and analysis of these events and news of the day and of course wikibon.com is our research site. A lot of really good deep work going on there. So thanks for watching everybody. This is Dave Vellante with Stu Mindeman. We're out from Veritas Vision 2017. We'll see you next time. (music)

(energetic music playing) >> Hi, I'm Stu Miniman here at the Silicon Ango Media Office in Palo Alto, happy to welcome back to the program Kiran Bhageshpur, who is the CEO of Igneous Systems. Kiron, great to see you. >> Great to see you again, Stu. >> Alright, so we've been really busy at theCUBE looking at so many big trends, and of course, really looking at kind of massively scalable distributed type of architectures are something we've been looking at, and something I know Igneous has been doing since the earliest days. But, the exact focus of what you've been working on, I think's changed a little bit since you first came out of Stealth and we've been looking at what your doing. So, why don't you bring our audience up to speed. >> Love to do that. It's not changed so much as expanded if you will. We launched, I believe I was here last, in October of last year, just as we were getting ready to launch. And, at that time, we launched the company and the platform, which the beginning services was object of the service, televert as a service and the enterprise data center. And, that was just the beginning. We've gone on since then, expanded the number of native services available, but really what we have done is built applications on top of that. So, the first application that we have developed and deployed at customers is backup and archive for massive file systems. So, we are talking about people who have terabytes of data, billions of files, spread across hundreds of systems. So, that's kind of been a pretty exciting thing, and it's a very unique set of challenges both for customers and for us to go forward. >> So, it's interesting, just step back for a second, object storage is something. If you talk to anybody that's a storage technologist they're like absolutely the way we need to architect things. But, usually we tend to get away from talking about object storage itself, and truly what do I do with it, what are those applications, what are those use cases. So, there's still object underneath it if I understand it right, it's just you're getting closer, moving up the stack a little bit, and getting closer to what your customers were asking for. >> Absolutely. The underlying infrastructure is still a collection of cloud services, not just object and S3, but a bunch of other services, which are very API compatible with the cloud, but, really, that doesn't matter because those are just tools. What matters is what are you doing with that, and what we are doing to begin with is really backup, archive, and discovery of massive files inside the enterprise. >> Alright, so there're some backup we've been doing for a long time, but backup has been broken. We were at the VM world show, there was a lot of buzz around some of the new companies, sometimes they called them secondary storage; you know, Rubric, Cohesity, Veem who everybody knows from the virtualization world, why don't you tell us are you part of kind of a similar wave? How do you kind of compare and contrast that to some of those other players? >> Great question. It's similar, but quite different. So, if you look at Rubric or Veem, for example, Veem really came about by doing tight integration with Veemware and doing a Veemware specific backup, which was the right technology, the right time for VMS and virtualization. Similarly, Rubric, and for that matter Cohesity, are really re-imagining data protection primarily for structured workflows, databases, physical servers, VMS, tightly integrating it and re-imagining how that feels from an experience point of view. We are really looking explicitly at unstructured data. This is data which lives on network devices from a net-app or a deliMC or a whole bunch of others and the content is really digital assets. It's data that could be media data, it could be microscopy imaging, it could be design data for a variety of work flows and this stuff continues to grow. It is monotonically increasing in every place, whether it is on premises or on the cloud or the edge, and protecting and managing this data is really a challenge and getting worse for customers. >> Yeah, the word that keeps coming up a lot is data. And, one of the things I know we've been excited about storage use to be about storing it. Now when we're talking about data, how do I leverage it? How do I get get value out of it? How do I discover different pieces of it? How have you been seeing these changes, your background you worked on some of the scale-out NASA solutions in the past, so how do we see kind of, unlocking the value of data? >> Yeah, you are absolutely right. If you go back 10 years ago, the real problem with how do I store all of this data, today there are plenty of solutions for ways you store data, especially on the primary teir, right? The challenge is really getting data from where it lives to where it's needed, whether it is backing it up or archiving it into the cloud. Being able to automatically discover things about it. Simple things like how is it growing, who is using it, how big is it, how much of it is what size of data? What about things you can infer about it by looking at the type of data it is. This is what now becomes valuable because if you look at the data sets and sizes, even modest size businesses today will have para bytes of data, billions of files, and that's challenging for any system system to go, sort of understand, unless you build it as a part of the platform. >> Okay, how about organizationally? Yah know, one of the other shifts we've seen is, you know, it used to be the storage administrator. How do I, how do I grow, how do I manage it, how do I have all of my protections and things set? A lot of the types of applications you are using are closer to the business, this is what runs the business. The business user needs to be involved. How are you setting your solution up to, you know, do what the business user needs? >> Great, yeah that's a good question. Today if you look at this data sets, this is not stuff that is an IT application. It's an end-user business focused application where they research in a life sciences world, or its designed in an electronic design world, right? And in all of these cases, essentially the end-user cares, because this data is critical to their daily working, working experience. Now, IT is clearly involved; it's a clear sort of partner of the business unit and actually operationalizing this data and making it easier to go consume. But now, it's really a joint thing, the final decision maker is always the end-user. In fact, we find ourselves in multiple places where we talk to IT, and talk to the IT teams. They get excited, but very quickly they bring in the end-users to make certain, whether the end-users are researchers or software developers, or even (mumbles) to make it so that they're comfortable with what we're talking about and they get really excited and that's sort of the starting point for our deployments. >> Yeah, we saw a similar dynamic between the business and the IT when we talked about cloud. And when I talked cloud I specifically mean public cloud and your customers, I have to imagine, they're all using public cloud in one way or another. Maybe, explain that dynamic how public cloud fits in with what your doing and how some of those IT and business people. >> Right. Look, cloud is simply the most disruptive trend in the last 10 years. In fact, you have to go back to Veemware, and Veemware's virtualization to see another trend of that magnitude. And all of our customers are embracing the cloud. They are wanting to go adopt cloud patterns, if you will. But the 180 over there massively challenged is around large data sets. Think about it, if you have terabytes of data that continues to grow, it's billion of files, it's spread across multiple geographies and dozens to hundreds of systems, it's a challenge to go leverage this in the cloud. So they're looking to ask, to be able to go chart the journey from all on premise, to a true hybrid world where they can use those cloud patterns much more effectively. >> Yah know I'm curious, and maybe it doesn't fit exactly for what Igneous is doing today. But, we've been talking about the data center versus the public cloud and a lot of those environments. I talked to some companies, that, you know, when I'm building those data legs, I'm doing that in the public cloud too. Then the discussion that's come up a lot in the past year, is Edge; so, IOT applications, we know we're going to have orders of magnitude more devices, and there's going to be a lot of data but the requirement for the data center versus the public cloud versus the Edge are very different. How does Igneous look at that? How are you having those discussions? Customers, how do they get their arms around all the various places of data?-- >> Right. You're absolutely right. The requirements are different, as in the public cloud is this massive hyper-scale, always available. The enterprise is a smaller version of that. And the Edge has a very different physical characteristics. But, what we believe is important is the same patterns, the same API's are available everywhere. And if you look at what the big public cloud providers are doing, Amazon with, you know, Snowball, and Green Grass, they're trying to go move their API's out and we completely embrace that trend. And, that's one of the reasons we built our platform to be API compatible with the cloud, with a variety of the cloud services. Because that means the services we run can run in the enterprise data center or in the public cloud or on the Edge all on a platform which is appropriate for the three. >> Yeah, and, to drill down to specifically, you say API compatible, that's S3, that's fully compatible. And do we have an API creep every cloud seems to have not only one API but many API's especially our friends at Amazon, what are you seeing out there, and what is the breath of offering they have today? >> Yeah, so, its SS3 is a constant storage leg is the obvious one, but the ones we did not talk about the last time were things like index store. So this is the equal of Amazon's dynamoDB, or Azure's table store the ability to go store a massive amount of index. But it's not just that. It's also the ability to go around compute, close to the data, which boils down to Cubanaties and containers. So all these three are part of our on the line platform. We don't talk about that to customers except after they become customers; we really focus on the application which is back up, archive, and discovery of all of their file data. >> Yeah, Kiran, take me inside the customers you are talking to; a lot of times we're like, I hear this term secondary storage out there and I worked on converge and hyper-converge stuff, you know, those terms are something that customers hear about after awhile, but they don't solve the problem. What, can you help translate for us, what's going on in your customers and why is secondary storage important to them? What's different than traditional back up, and how do you fit in? >> Right, so if you look at all of these guys, the data, the fundamental truth is data sets are growing and they are growing monotonically. Every year it is more. We've talked to folks where in the two years that we've spent as we were growing up as a company, they've sort of essentially had a 40 percent growth in their on search data sets, right? So then, the question is a couple of things. One, they clearly realize that not all of that stuff needs to live, or should live, on high performance, relatively expensive primary tiers. Right? That's the first set of piece. But the question is, how do you find out, what is active what is not active and how do you move it to the appropriate place; so this is sort of trend line and this is the patterns that they are living with. What we do is go in, very simply start off by saying, lets go find all of your filers, you know some of them, some of them you may not even know about, and let's go automatically back-up all of the data, and give you intelligence about all that. What is sort of simple intelligence. The intelligence could be how infrequently are these data sets changing, how frequently are parts of this data being accessed or modified by your applications. So that's sort of first part of this. And when this drives to is, not only does this reduce the cost of backup, which is really an insurance policy, it makes possible a bunch of intelligence about the data itself which is the beginnings of, sort of appropriately staging data on the right infrastructure. >> Alright. Kiran, you've had a number of customers since the early days talk to us a little bit about the journey you've been going on with them. How many of them have been pulling you towards the direction you are now going? What's their response been? To I guess what you call it, kind of storage as a service? >> Yeah, you know people love the whole concept of our offering as a service; initially when we talked of customers they kind of a little skeptical of our ability to go do this but they very quickly fall in love with that. It's pretty amazing. What's not to like about infrastructure that is inside your data center but that you do not have to manage at all? And when I say do not manage, people don't even look at things like drives or CPUs or network. That's not the world they live in. They live in the world of what's logically important to them, which if my backup's running, is my data being archived, how quickly is my data growing, who is accessing this data? And so on, and it goes to the next level, which is they don't have to go to manage things like software updates, just like you don't know what version of Gmail you're running or you do not know what version of S3 is being used in the cloud. Our customers don't know what version it is. Is it API level compatible or is it guarantee the services are not interrupted; and they absolutely love that aspect once they get used to it. We tell our customers, "You don't call us, we call you if there is an issue." And we're living up to that and they are pretty jazzed about that. >> Yeah, I love that. Kind of the version control thing is something we said is something, is cloud experience is actually what we want. (Mumbles) when we wrote true private cloud is exactly that; you don't know or care what version of Azure you're running, you assume that they're going to test that out and do that. Can you give us any kind of concrete examples, customers, love if you can share any names, but a lot of your customers are quite big, but what are the concrete results? What are they seeing, any good stories you can share? >> Yeah! So I give you an example of one of our largest customers, can't mention the name, but it is a large tech company in California. There's a lot of large tech companies in California-- (giggles) >> There's a bunch, yeah. >> Well, lets go through the South in California. And, these folks had an enormous amount of data. We started off by telling them, "Hey give us your most "complex systems, the ones that you are not able "to go back up today." And we started with their file systems, which were literally had this thing called file density, which is an enormous number of files in a relatively small amount of storage. So you're talking about a billion plus files and terabytes of data, and this is things that they had never been able to back up and we go off and we were able to go back it up and completely system protect. So, that's an example of a used case where we can go to a customer and allow them to accomplish what they cannot do today just from a basic back-up point of view. And, take it to the next level. In fact they did this great demo for their internal teams where they showed how easy it is to search through this data and essentially accomplish in seconds what typically, in their current world, takes hours to do. >> Okay, yeah, that's great. Yeah, sounds like you have some really good interesting, large companies there. Is that, what's the typical profile you see? Is it really companies that have specific challenges because they've got the massive scale? How far down does this scale? >> So. Uh, that's a common question that comes along. And the way I like to answer that is we are applicable to people with lots of data. It turns out it could be much smaller companies with lots of data, so we've got customers who are in the hundreds of people only world-wide, maybe two or three locations, but they are really looking at a multi-terabyte sized data problem. Similar data density problem. In fact, another one that we are working with has got 300 million files and a terabyte of data. How do you back it up? How do you go discover information about that? That's what we solve, and for these smaller companies which still have the problem, they are actually starting to find out about us and come to us. Which is really gratifying. >> Okay, well you seem pretty excited about it, about the space, what's exciting you the most about where we are today with the technology. >> The really sure is, people talk about data and they immediately go to databases, they talk about virtualization and physical servers. But that's not where the data lives. The data hasn't lived there for over a decade. And more and more of the data lives outside in files and object and there is this sort of ability to go understand that better, manage that better, protect that better and last but not least, provide intelligence to users because this data is something they care about. People are not keeping this because somebody else told them to; it is their life blood. It is their sort of livlihood, if you will, from a company point of view, and helping customers be able to go take that to the next level will bring this sort of cloud patterns to these used cases. That's pretty exciting. >> Yeah, absolutely! Want to sort of give you the final word. I hear this and I think about, you know, the whole wave of big data, what we're starting to talk about, you know, continuously with AI and ML really it is about unlocking data, so huge opportunities going forward. Any of the other trends outside what we've discussed already that you want to give us for a final word? >> You know, the last thing that I say is it is about data. It is about complete automation all across the, across the sky, weather it is storing, managing, or deriving intelligence and the reason you want to go automate all that stuff using intelligence in the software systems itself is simply because it's too large. There's no other way to go do it. And last, but not the least, all of the stuff has to be offered as a service because the cloud has gotten people really hooked on this sort of, comparatively, easy world of not having to go managing infrastructure. And I think those are the three things we should, we hold by. >> Alright, Kiran Bhageshpur, I really appreciate the update on Igneus systems. Absolutely customers dealing with massive amounts of data, how do I unlock the value of that without having to be down in the guts which has really been the history of storage. I'm Stu Miniman, thanks so much for watching theCUBE. (energetic music playing)