(techy music) >> Hi, everybody, welcome to this special Cube conversation, my name is Dave Vellante. I'm very excited to be here in our Palo Alto studios in the heart of Silicon Valley, the innovation hub of technology. In 2015 we introduced a company to your community called Datrium and one of the co-founders, Brian Biles at the time, came on as one of our segments and shared with us a little bit about what they were doing. Well, several years on, three years on, this company Datrium is exploding and we're really excited to have Brian Biles back, who's the co-founder and chief product officer at Datrium and he's joined by Sazzala Reddy, who's the CTO and another co-founder. One of the, two of the five co-founders here, so gentlemen, great to see you again, thanks for coming on. >> Good to see you, Dave. >> Yeah, so Brian, I remember that interview and I remember, you know, trying to get out of you what that secret sauce was, exactly what you were doing. There were a lot of other start ups, you know, at that time and several have gone by the wayside. You guys are exploding, so I want to help people understand why you're being so successful. Now, I want to start with the two co-founders. Why did you and your other co-founders start the company? >> You know, we started the company... We hired our first people in 2013, and at that time, there were really two separate worlds. There was a cloud world and there was an on-prem world that was sort of dominated by VMware. So, there were these two evolving discussions about how each one was going to grow in it's own way but kind of within its sphere. We thought there was an opportunity to bridge the two, and to do that, you know, ultimately it becomes a questions of how to run sort of coordinating applications on public clouds and deal with data on public clouds but also to have a capable version of the same infrastructure on private clouds. So, our sort of job one was to build up, to sort of import cloud technology onto prem. We currently have, if you want an Amazon-like version of infrastructure on-prem, we're still the best place to go because we have a two layer model, where there's, you know, compute with fast flash, talking to a separate durability layer very much like EC to an S3. You want to do that, we're still the way to go. But the long term story is also developing. We have a footprint on cloud with a backup store on S3 that coordinates all our data services for global deduping security and so on in a very cost effective, simple SAS way, and that part is growing significantly over the next couple of years. So we're, you know, through with sort of phase one. It'll keep, you know, evolving but phase two is really just getting going. >> So Sazzala, as the chief technologist you had to think about the architecture of where the industry was going and the architecture that would fit that. And you know, that people talk about future proofing so if you think back to the original sort of founding premise, what were some of the challenges that you were trying to solve? >> Right, so there's a business use cases and then there's technology use cases. And as a CTO you have to think of both of them, not just technologies, so if you look at technology point of view, you know, in 2000, back in 2000, Google published a paper called Map Reduce that said hey, this is all we can do at large scale. It was the beginning of how to build large scale distributed systems. But it was built for one use case for surge. But if you look at, we started in a time when Google was already there and they built a system for multiple, unpredictable use cases. So you think differently how the problem is whereas Google start from, though. Some of the CI vendors, they've done good things. They kind of evolved in that direction. We have evolved in a new direction. To the technology point of view, that's kind of what we thought about. But from a business perspective, what do people want? You know, if you look at the next generation, the millennials, and look beyond that they're used to iPhone experience. They don't want, if you tell them about LUNs, they don't re-phone LUNs, they're going to just say what is this and why do you have this stuff, right? So you have to evolve away from that. So, it's the CIA wants to think about how do I make my idea the service? How do I consume, you know, how do I make it a consumption model, how do I make my IT not a cost center but a friendly way to you know, grow my business? And the developers want a platform they can develop things faster, they can adapt to newer, kind of newer technologies coming in, there's Mesos, there's Docker container, there's Kubernetes, thus things change rapidly. So that's going to build a framework in how we wanted to start the company. Basically build a cloud-like experience simple as a SAS, simple as a click and then just make that work. >> The thing that's interesting to me about Datrium is you know, the simplicity, like open. You know, I remember when Unix was considered open and then obviously the definition changes, simplicity has changed. I remember when converged infrastructure, bolting together, compute storage and networking, simplified things. Hyperconverge took that to another level. You guys are going beyond that taking it to yet another level of simplicity, so I wonder if you could talk about that-- >> Yeah, so-- Specifically in terms of the problems that you're solving today for customers. >> So if you look at the V block, I guess the VCE was the first, I guess that they made a successful convergence. So they did hardware convergence-- >> Right. which is a useful thing to do. Same thing with your head CI, the traditional vendors, they do hardware convergence, if you look at Hecht, probably stands for hardware convergence, maybe. But we took a little bigger step in the sense that what you really want us to think about is data convergence. Not, hyperconvergence is useful, but you also think operating about data convergence. What's the point of building your on-prem cloud- like experience when you still have to do backups and some other you know, some other boxes you are to buy. That's not a really good experience, but you need is this whole new hardware convergence, we also need data convergence to get that experience of like cloud-like simplicity in your on-prem. >> Right, in the cloud you don't think of backing it up, right, it's self protecting. That's just the nature of how you should be thinking about on-prem as well. So, when we imported that technology to be a two-layer approach, we built that stuff in so you don't have to think about it. It's kind of like there's no SQL or we're sort of like no backup. >> Yeah, we're going to talk some more about that but that's an important point is you get backup and data protection, you know, full capability, it's just there. I always use the example of Netflix or Spotify. I don't have to call up a salesperson or the billing department or the customer service department, it's just there and I deal with it. >> Right and it gives you, you know, this combination of, in the two layers, the ability to run multiple workloads at big scale, which is otherwise hard in some of these more historical approaches, with great performance that you know is off the charts. But it also means you don't have to move data around as much. So you restore, you restart, you don't restore. You don't copy stuff in and out. >> Yeah. >> That data mobility efficiency it turns out, is also super critical when you think about multi-cloud behavior. >> You have to be in the business to actually feel like you talk to backup admins and life is hell. It is really painful and it's also very fearful if you have a problem, you have to restore and everybody's watching you when you're restoring. So we try to eliminate all those problems, right? Make it, just, why worry about all these things? We are living in a new world, let's adapt to it. >> I think I've, tongue-in-cheek I think about the show Silicon Valley and you guys didn't start out to build a box. >> No. >> No. >> You settled this off some problems and so what you have is a set of best of breed storage services that are running the cloud, called multi-cloud, meaning on-prem or in the cloud so I want to try to juxtapose that to sort of the traditional storage model or even some of these emerging storage models of some of the very successful companies. So, how do you guys differentiate, help us understand what's different about Datrium from the classical storage model and even some of these emerging storage models? >> I'll kick it off and Sazzala can expand on it. You know, first we're bringing a cloud experience to on-prem, so it's not a storage system that you, like a SAN. We, you know, offer compute as well and a way to make that whole operation simple around you know, standard and emerging standard coordination frameworks like VMware and Red Hat and Docker. It includes these really powerful data services to make life simple so you don't have to add on a lot of different control panes and spots of data storage and so on. By getting that right, it makes multi-cloud coordination a lot easier because the hardest problem getting started in that, aside from, you know, just doing SAS applications to run it and so on, is getting data back and forth. Making it efficient and cost effective to move it. So, you want to expand? >> Yeah, so you know, I think you give examples of like maybe there are some successful companies in the market today. There is old school array market and there's the new school head CI markets. So, the old school array market, I mean, if some people are still comfortable with that model, I think they just because the flash array market has some performance characteristics but still it's, again, going back to that rotary phone landing, it doesn't map your, the lands don't map your business. It's just a very old school way of thinking about it. Those will probably vanish at some point because it makes no sense to have them around. And yes, they do provide higher performance but they're still, you know, it's still not providing you that level of ideal service. From a developer point of view, I can make my application life easier, I can do things like test and dev. Test and dev, simple thing like test and dev requires you to clone your application so they can run test and dev on them. It's a very powerful use case, it's a very common use case for most companies, including ours. So, you can't do any of that stuff with that old school style of array. And the new school style, they are making progress in terms of making that developer life a little bit more easier but they haven't thought deeply about data services. Like they built a nice packaging and like some UI frameworks but ultimately, data needs to be like stable. They didn't, you think about data in a how do you make it compressed, efficient and cost effective and make it so that it is easy to move data around. And you're think about the backup and DR. Because if we look at application, you've run it, you have to back it up and you have to do archiving for it. You have to think up the entire lifecycle of it. Which is kind of what most people are not doing, thinking of the entire lifecycle. They're solving a small piece of the puzzle but not the entire thing. >> I'll give you another example of that. In you know, to the operator of a private cloud, you're thinking about workloads, you're thinking about relationships between VMs you know, how to get them to the right place, copy them at the right rate, secure them in the right way. In a sort of old style, that kind of thinking about say protection, you might have a catalog in a backup software but you have volumes of VMs in a SAN. Those are completely different mindsets, we've merged them. So we have a completely scalable catalog you know and detailed validation, verification information about every scrap of data on the system that we can test everything four times a day for test restores. All that kind of stuff is organically in a single user interface that's VM focused, so you don't have to think about these different mindsets. >> But it's SAS really for data services. >> For data services, yeah. >> I mean is that a fair way to think about this? >> Yeah, I think so because what's better than one click? Zero clicks, so lot of people are aiming for one click. We are aiming for zero clicks. That's actually a harder problem to do. It's actually hard to actually think about how do I automate everything so they have to do nothing? That's kind of where we have really, really tried hard is that, as little clicks as possible. Aim for zero as much as possible. That's our goal, in the internal company engineers are told you must aim for zero clicks, actually a harder problem. >> Right so, when you think about how to then expand that to managing multiple sort of availability zones across multiple clouds there are additional problems. But starting from these capabilities, starting from great indexing of data, great cataloging of relationships between things, everything's workload specific and great data mobility infrastructure with data reduction and encryption and so on. As we forecast where we can go with that, it's profound. You can start to imagine some context for how to deal with information across clouds and how to both run and protect it in a way that's really just never been in the market. >> So I want to talk about that vision but before we do, before we leave sort of the differences let's take two examples. Two very successful companies, Nutanix and Pure, so how are you different from, let's start with Nutanix, for example. >> I think that there's some good things, I think they're moved the industry forward quite a bit. I think they've brought some new ideas to the market, they made it VM-centric, they said no LUNs. They've made quite some improvements, and then they're a successful company, but ultimately I think their focus tends to be mostly on how to make the UI shiny and how to kind of think about the hypervisor, which is kind of where they're going to. They don't hypervise in the world today, we don't want to go invent another hypervisor. >> Mm-hmm. >> There are so many other options and the world is changing a lot. Like you said, Kubernetes is coming, Mesos is coming, so we want to adapt to those newer ways or style of doing it, and we don't want to invest in making or building a new hypervisor, and we're good partners with VMware, so that's one angle to it. If you look at, you know, how... Because if you're going to go to large enterprises, they want to consolidate the workloads. They want large scale, they want exabyte scale, so you meet customers now who have exabyte scale data, they think they're the cloud. They're not thinking of any other cloud, they think they're the cloud, so how do you make them successful? So, you have to think about exabyte scale systems where basically you can operate it as a cloud internally, so we build those kinds of infrastructures and those kinds of tools to make that exabyte scale successful, and we probably are the fastest system on the planet. Right, so that's kind of where we come from is that we not only say that we scale, we actually prove that we scale. It's not just enough to say we have Google style and the scale, so it's actually you have to prove it, so we actually have tests where we can, we actually have run with other people that it actually works as we say it does. So, I think it's important that you have to speak, you have to not only produce a product which is useful from a UI point of view, that's useful, but also it has to actually work at scale, and we make it more resilient. We have a lot of features built in to make it more resilient and at scale, like what does a tier one mean, what is mission critical apps, how do you make sure that we don't lose data, for example. It runs at the highest performance possible at a price which is reasonable. >> Okay, and I guess the other difference is you're a pure SAS model in that you're responsible for (chuckles) the data services, right, and-- >> Yeah, that's right. >> Yeah, we've pulled a lot more into the data services in our cloud approach. >> Mm-hmm. >> And we've separated from the performance elements, so they're these two layers, so it's both self-protecting in a way that's independently provisioned if you want to expand capacity for backup retention, that's a standard thing. If you want to expand performance or workloads you do that independently on stateless hosts. >> Mm-hmm. >> An example of where this pays off is just the resilience of the system. In a standard hyperconverged model a good case is like what's the crater size when a, or the risk, you know, profile when a single component fails. So, if a motherboard fails in a sort of hyperconverged model that's standard, you know, a single layer thing, then all the data on that system has to be rebuilt. That puts enormous pressure on the network, and you know, some of these systems can have 80, 160 terabytes of data on a single node, that's like a crazy week, and if two of them go down then the whole thing stops. In our model the hosts are stateless, if any number of them go down for any reason the data's still safe, separate-- >> Mm-hmm, right. >> You know, in a hyperconverged model you can't really integrate backup well because when primary goes down back up goes down, too, then what? >> Okay, so that's, I think, clear how you differentiate from hyperconverged. Did you have another-- >> Yeah, I have one more point, it's about the data services you mentioned. We have, again, going back to zero-click, we built all our features into the system. For example, you know, there are a lot things like deduplication, compression, image recording, those are like, I mean, they're not like details, but ultimately they do bring the cost down quite a bit, like by 10 X to five X, right, that's a big difference. >> So, those are services that are inherent. >> That are inherent in the system. >> Yeah, okay. >> Either you can have check boxes, you can say one click and have to like check box, all that. I mean, you have to go and click it, but to click it then you must read a manual, you must do the manual, so then what is this right click and what happens to me, why isn't not on by default. >> Yeah. >> So, those are the problems, I think the differences between them, I think Nutanix and us, is that we kind of made it all, like, be seamless and all built in. >> Yeah, and when we, you know, if you have to, if it's an option that you ask for later that means it probably has some impact on the system that you have to decide about. In our case you can't turn it off, it's always there and we do all our benchmarking with all that stuff turned on, including software-based encryption. It's just a standard thing, and we still are like the fastest thing on the planet. >> Yeah. >> And let's talk about Pure a little bit, because they don't have-- >> Yeah. >> The networking component and then the compute component, it's, you know, flash array, so how would you position relative to Pure? >> Okay, so again, going back to that SAN array was built before the internet, it is just the same. It is just the same, it's just to deport SSDs behind those controllers in central hard drives. It is likely faster, but ultimately the bottleneck is those controllers, those two controllers they have, that's what it is. No matter how many, how awesome your... You put envy in drive, it doesn't matter. It's going to be as much as speed as your network pipe is going to be, and as much faster as your controllers are going to be. Ultimately, the latency, you cannot, like, basically it's over the wire. It will always be slower than what kind of having... >> So, the big thing here is-- >> Yeah, and it's not a private cloud. You know, that kind of model is for someone who's assembling a lot of parts to create a cloud. >> Yep. >> You know, we're integrating these parts, so it's a much simpler deployment of a cloud experience and you're not integrating all these double parts. >> I'm getting a cloud, I'm buying a cloud experience from you guys with the sets of services, let's talk about those services. So, mobility, discovery, analytics. >> Yeah. >> Governance, talked about the... >> Encryption, yeah. >> The other data reduction services, encryption... >> Right, the cataloging and indexing of the data so you can, you know, restart from old data. >> And I can run this on any cloud, including my on-prem cloud, correct? >> Well, that's the direction, we have some parts now and you know, you... (laughs) Sorry, Sazzala can talk about where we're going. >> So, architecturally it's designed to run on... >> Yeah, because I think fundamentally we chose that design philosophy that it has to be two-layer, right, that's a fundamental decision we made long ago, and it's a detail but it's a fundamental decision we made long ago that because if you go to Amazon it is two-layer. You cannot make one-layer work there. Like, you know, compute and storage has to be split to through that part, but they must work together in a nice way, and also S3's very weird. I don't know if you know about S3. S3's very weird behavior, it does not like random writes, it has to be all sequential writes, and that also happens to be how we built it. The way our system works is that we only do sequential writes to any device. It works beautifully in S3 with EC2, so just to step back a little bit, taking big picture, like so, we wanted a cloud-like experience for your on-prem, right. That's kind of what we built, we built a Datrium cloud on-prem, and then we, as of beginning of this year, we started offering services, multi-cloud services and started with Amazon first. The first service we enabled was backup and archiving, that's our first service. A lot of people like it and you have some stats from that, like from last quarter, like how people like it, because people like it because you don't have to have another on-prem infrastructure. You can just consume it as a SAS model, it's very convenient and it's as easy as an iPhone backup. I don't know if you use iPhone backup, it's like a click. >> Yeah. >> Okay, unfortunately it's a click. We have tried to avoid the clicks, but we can't really avoid it all the way, so you have to click it so that you can then start doing backups into the cloud and then can retrieve them in a very simple single pane of glass. It's very cost-effective because we do dedupe on the cloud and we dedupe over the wire, but dedupe over the wire, by the way, it's actually a very unique feature. Not many companies have it, like Nutanix and Pure you mentioned, they don't have it, so you know, so that's one of the things where I think we differentiate because data has gravity, right, so to move it somewhere you need an antigravity device. So, you need something to actually move this data faster, how to defeat speed of light. You have a pipe, you have a VAN network, so how do you defeat the speed of light, so what we have built is a feature, it's called Global Dedupe, is that you can move data in a much more efficient way across the cloud. So, now you may question, "Hey, I'm moving my data "from here to another place," obviously we have these cloud services... The question you may ask is, "Okay, how do "I know I get guaranteed security? "How do I know that it's going to be correct, "that I moved all these places," right? So, we do multiple things, one is that we have built in encryption. It's going to be globally encrypted, it's like an encryption across the whole thing, we call it blanket encryption. >> Mm-hmm. >> The other one is that we have blockchain-like features that are built into the systems so that if you move an object, like an app or whatever, you're going to move from one place to the other, it's built in kind of blockchain features where you cannot move something to another place and get it wrong. It's fundamentally going to be correct for you, so those are the kind of things we thought about, like never to worry about it again. It's going to guarantee the data's correct and it's moved in the most efficient way, so that's our first landing thing we've done is that we wanted to build an experience which is like on-prem cloud, I mean, onto also the cloud. Right, what other experience people are... People like simplicity, people want the SAS-like experience. They don't want to manage it, they don't want to think about it. They just consume the services, so the first service we have in Amazon is what we chose, is backup and DR. The next thing we are going to be shipping soon, announcing soon, and we'll have a demo in the VM World is something we call Cloud Shift. It's an app mobility orchestration framework where you can just click and move your workload to somewhere else, to Amazon, and you can run, so it's not just a backup thing, it'll also become you can run your workloads in Amazon and get a consistent experience from your on-prem and the cloud. So, one of the challenges is that if you move to another place, is it different tool sets, I have to change my whole lifestyle, no. >> Mm-hmm. >> We want to provide that seamless operational consistency that-- >> That's the key, right. >> That's the key. >> Whether it's on-prem or it's in the cloud it operates the same way. I'm accessing those sets of data services and-- >> Yeah. >> I don't really care where it is, is that-- >> That's right. >> The vision? >> Yeah, that's right. >> Exactly. >> That's right, so if it turns out that there's a cost advantage in moving from, you know, A to B, we make it super easy and the control panel from our standpoint is consistent, and it's... So, all of our control orientation moving forward will literally be SAS. It'll be running on a cloud even if you're managing on-prem stuff, because that way, assuming you're multi-cloud, you need a control plane to be dealing with the cloud stuff anyway, and it just sort of neutralizes the experience so that in a multi-cloud way it's always consistent, it's always simple, and the nice thing about sort of true SAS is you don't have to upgrade software parts. We do that for you in the background. >> Mm-hmm. >> So, it's just always up to date. >> So, I was saying before, Datrium takes care of everything. >> Yeah. >> And it's the true cloud experience. >> Just consume it. >> Right. >> Okay, I want to talk about, end on the two other areas: the operational impact and the developer impact. So, when you think of operations, we've talked about LUNs before. I've always said if you're in the business of managing LUNs you really want to think about, you know, updating your skill sets (chuckles) because that capability is not really going to be viewed as valuable. It isn't today and certainly in the future, so the operational impact, the degrees of automation that IT operations are driving is going through the roof. Cloud-like, we've talked about that, and the other is developer productivity. People are using containers, you know, Kubernetes... >> Yeah. >> And new styles of writing software-- >> Yeah. >> As everybody becomes a software company. So, can you talk about those two aspects? >> And ultimately there's going to be serverless. >> Right. >> Right. >> As we think about if you take a leap, in another 10 years I think serverless will probably be one of the important ways, because why do you even care how it runs. You just write some software and like, you know, we can run it. It should be that way, but I think we're not there completely yet, I think, so we want to adopt a methodology where we provide the framework where we don't dictate what apps, how we write your apps. That's, I think, very powerful because that's actually evolving faster as we move forward, because serverless is a new app framework. >> Mm-hmm. >> You cannot anticipate this, right, you cannot anticipate on building everything but what you can anticipate is services we can provide for the developers, which is, you know, no matter... Because it's the granularity of it. We can map their application granularity into our system, we have that fine level granularity, so that kind of was what you want to provide as a primitive. LUNs don't have that primitive, right, so we provide that level of primitive that whatever apps you have will have that level of primitives to global data services for you, and once you have the data services like that we'll guarantee that it's highest performance, which is what app developers want. Like, I get the highest performance, I can easily... And then we will also provide a way to clone those things easily, those apps, because sometimes you're at an app, you want to test it, too. Like a hundred times, you want to just... If you can copy all the data a hundred times or you can just, say, you know what, clone this thing a hundred times in a millisecond and run my tests fast and then okay, I'm done with my test, it looks good, I'll deploy it. >> Mm-hmm. >> That's kind of what developers really want is that they are able to run, write faster, develop faster, because tests on dev cycles are important. A lot of people think that hey, I can put my test on dev in some old box over there, but that's really bad because from business perspective testing does, engineering's expensive. Their test cycles have to be fast so that they can e-trade faster and kind of produce faster. The harder you make it to test your system, this is like, this is what happens in our company today. The harder it is to test your logic and your code, the longer it takes to, like, do e-trade. >> In some ways test and dev is becoming more strategic than the production system, I mean, really-- >> Well, it-- >> (chuckles) Because of speed. >> Yeah, I mean, it can take immediate advantage of some of these improvements in, you know, stacks. Like if, you know, if Kubernetes is better just, you know, go quickly to it. The things that these new stacks assume, though, is that it's, you know, a server-based data, so on-site you can accelerate mobility significantly by, you know, when people ask to copy things from here to there, clone it, you know, start another instance, we can help them do that by just, you know, faking it out with metadata-- >> Mm-hmm. >> And deduplication, and so we tried this with Jenkins just in our own development, moved to that model and you know, everything was suddenly twice as fast in development. To do a build all of a sudden you didn't have to copy data here to there. You were cloning, you know, with metadata. The way to do it across clouds is, again, kind of dedupe focused. If you have to actually move the data it takes a long time and it's expensive, especially for egress costs. If you can just, you know, validate which elements of the data are new versus old on either site you can move a lot less. >> Hmm... >> It might be, you know, six times less, and then the costs go down, the speed goes up, you defeat data gravity. >> Yeah, so-- >> Excellent, all right, we have to leave it there. >> Okay. >> Out of time, thanks so much, you guys, for helping us better understand, you know, Datrium. Congratulations on your success so far and all the great innovations that you've achieved. >> Okay, thank you. >> Okay, thanks for watching, everybody, this special CUBE conversation. This is Dave Vellante, see you next time. (techy music)

(techy music) >> Hi, everybody, this is Dave Vellante from theCUBE's Palo Alto studios, and welcome to this CUBE conversation. You know, theCUBE and SiliconANGLE/Wikibon have been documenting the evolution of data and storage over the last decade or so, and what we've seen is the simplification of storage. Going from hardware consolidation with conversion infrastructure and we saw hyper conversion infrastructure and sort of software-defined come on the stage, but now we're, you know, in the heart of the cloud era, and what we're seeing emerging is true cloud-like models for data services. So, we've asked Brian Biles and Sazzala Reddy from Datrium to come back into our CUBE studios and talk about this a little bit. Brian and Sazzala are both co-founders of Datrium. Brian is the chief product officer and Sazzala's the CTO. Gents, let's get into it, thanks for coming back on, and let's talk about that a little bit. So, your model, as we've talked about in the past, is a pure SAS model. You're accessing data services in a SAS-like, cloud-like experience, and people might say, "Well, isn't everything SAS today?" But in the storage world that's not the norm. Typically you would either install a box, you know, and that box might have a very rich set of software-defined services on top of it, but it's not really a cloud experience. We're starting to see certain models pop up. You're seeing some companies actually delivering that. You guys started there, that's your DNA, so let's talk about what you're doing and how that's different in the marketplace, Brian. >> Sure, you know, the way to maybe start the conversation is imagine that you're already, you know, embracing a multi-cloud, you know, plan in your IT organization, so you know, you might have a little Amazon, you might have some SAS. You know, software company, stuff going on, and you have some on-prem experience, and you want to make that as simple as possible-- >> You just described everybody. >> We want to make it as unified... (laughs) Yeah, as unified as you can, as simple as you can. You know, at that point you want to think about, you know, what is the highest leverage, simple thing to do on-prem that connects to that, you know, world of services in the cloud. How can you align that as closely as possible, so what Datrium is doing is trying to do that. We have, you know, our on-prem software is very Amazon-like, it has two layers, it operates in a very similar way, supporting many types of frameworks from VMware to Docker to Red Hat. What we've done with how to store, manipulate, mobilize data and orchestrate, you know, transitions between clouds is, it ends up feeling fundamentally different from other types of ways that you can deal with on-prem infrastructure. It's just much simpler, much more coordinated, and it allows more flexibility over time. So, Sazzal can maybe tell you about it. >> Okay, so but Nutanix, Sazzala, would say, "Okay, well we're cloud, we're creating "a cloud-like experience for on-prem," how are you guys different? >> I guess the fundamental difference is how we think of the problem. We want to say our goal is to run, protect applications in any cloud, because we cannot be in the business of building the infrastructure because that's an investment. There already are three players. What most customers want is to commoditize the cloud. They could care less if they're running on Amazon or Azure. In fact, they care that they're tied to one cloud vendor, so our goal is to make that cloud, commoditize the cloud, make it all seamless so they can move from one place to the other, whatever agreements you have. Tomorrow Google may give you credits, say, "You know what, I'll give you one year free, come on over." What you want is a one-click and move everything over to their stuff over the weekend. That's kind of where we are, that we want to provide that level of simplicity, run, protect your workloads in any cloud you want. So, Nutanix is, I think it looks like from at least from what we read from their press releases, is their cloud. They say one OS, one cloud, we are seeing any cloud. So, that's, I think we want to give that flexibility for people to not be locked in by any cloud vendor, that you can take advantage of it. You know, tomorrow Amazon may not be doing that well or tomorrow Amazon may be enemy to your business, so you want to click it and move it away to some other cloud-- >> Separating the data services from the underlying infrastructure. >> Yeah, that's right, so I think you have to separate the data services and the data management to the best, abstract it so it's so high level that then you don't care where it runs. It runs on-prem, it runs on Amazon, so it looks the same experience for you, that's what we're aiming for, that level of simplicity, but remember, to do these things you must run and protect. You can't just do run only, you must also protect because it's part of your data, you know, your IT philosophy that you must protect your data, you must have copies of it to guard against ransomware and other things, but compliance reasons, right? You want to manage your data, so it has to be a holistic view of the entire end-to-end lifecycle of your data. It cannot just be, "Run my apps here and there." >> How about Pure, how would you differentiate from Pure? Let's say pure wants to, say, OEM its stack to a cloud service provider, how is it different? >> So, the common denominator in cloud services is the workload, the instance, the VM. >> Mm-hmm. >> All of the coordination between clouds is going to be on that granularity. That's what we focus on, so, you know, we have a catalog to show relationships between VMs so that, you know, when we DR you can restart in a certain order or you can validate, you know, workload granularities, have policies at a workload granularity. That's how clouds', you know, behavior is sort of itemized today. If you buy separate parts, like you know, a SAN array, you have to buy something else to do that work. So, it's fundamentally limiting. You know, if you just take VMware because it's so well understood, you know, VMs are going to be put into a LUN as, you know, a file system of VMs. So, to transfer a LUN to a cloud, and then what do you do with it? You know, are... There's no instance to restart. So, you know, it doesn't, it just doesn't operate on the same granularity. >> Speaking different languages, essentially. >> Yeah, so you're either, you know, an ingredient to somebody who's building a cloud who's assembling lots of things to get to the level where Datrium is offering it today, or you could just be simple and... >> Ultimately are you a software company, are you a hardware company, right? That's the thing and the difference is how we are a software company. You have to think about it as a software scaling. You can scale and make it all scale quite well. >> So, let's talk about some of those services-- >> Yeah. >> Which are all software, so let's list some, and we've talked in the earlier segments about data reduction and... >> Right, so I think the company has built that background that we're going to enable the services one day, so the first service we enabled, and this, the beginning on the year, was backup and data archiving. So, it's a SAS platform, it's a multi-cloud services, this first one. Second one we are building right now, we're going to ship it pretty soon, it's something called Cloud Shift. It's a DR orchestration, app mobility orchestration kind of framework. You can just click, move your workloads anywhere you want, any cloud you want. It's a big piece of our next offering. The third offering we're going to be doing is how do you manage all these different data sets you have across multiple places you have, so we're going to offer that next. So, we also have something called Providence built into the system, like every object knows where it came from, where did it, like all these apps, they kind of know we have all the data, we kind of know where they came from, so that's the next one, we call it a Global Ledger, how do you keep track of all this stuff. And the fourth one is we have all this data now, we have all this metadata, how do we provide governance for the end user, because ultimately they do care about compliance, they do make sure, they want to make sure that they're not moving data to the wrong place, that they have made the SLAs, so that's the ultimately kind of like where are we going to, kind of that's a two-year road map-- >> Mm-hmm. >> Idea. >> Okay, so I've got mobility, discovery, there's analytics in here-- >> Analytics, yeah. >> You've got governance and compliance, obviously backup is something we talked about. >> Yep. >> Now, these are discreet services that I can acquire separately-- >> Yeah. >> Is it all included-- >> Well, in a SAN, yeah, you'd have to buy them separately. >> Yeah, okay, right, right, you do. >> In a cloud approach like ours, they're just automatic and always on, so you don't have to think about them. Global dedupe is an example, if we always have that on you can't turn it off, that helps it locally for cloning so you don't have to move data from server to server-- >> Mm-hmm. >> In a developer shop, for example. It's just, you just boot, you know, start it up and it all has access and it's very fast, or across clouds we don't send all the data when somebody says to move it. We look for the deltas between site A and site B and only send those in a compressed, encrypted way. So, having that stuff just be fundamental and always on means cloud mobility gets a lot easier and a lot faster. >> And I, backup's another good example. I don't need to go buy backup software from a backup software-- >> Or hardware. >> Vendor, or... (chuckles) >> Yeah, that's right. >> Or hardware, right, it's there. >> It's just standard. >> Yeah. >> It's self-protecting, so you know, when you think about cloud mobility it changes the way you think about the problems. For example, if you want to, you know, enable a context for automated DR from prem to cloud, there are a lot of risks in many of the current systems. I don't want to go through the whole, you know, problem set because it's bad and we're solving it in our own way, but just take the conversion problem. If you have to move from point A to point B, you know, 90% of the time if you convert a VMware VM to an Amazon instance it'll kind of work. Well, for DR that's not sufficient, so we're taking a much more sort of thoughtful and open approach to how we deal with, you know, stack providers. So, you know, we'll be able to... In the VMware case, for example, move things straight onto their cloud from our S3 data so that you don't have to convert, so it just always works. >> And I'm interfacing with your SAS, it looks the same where it's on-prem, whether it's in the cloud-- >> Yep. >> It's the same experience. >> We're hoping you have to do less work and less interaction because it's all built in, it all just works. >> Okay, so that, the vision is sets of discreet services separated from the underlying infrastructure-- >> Infrastructure. >> Able to call those services as needed, run on any cloud, on-prem-- >> Run, protect, any cloud. >> Full set of services. >> Right. >> Right. >> Integrated-- >> Right, and as time goes on all our sort of operating software and analytic software and governance, and so on, will actually be, you know, literally SAS in a cloud. That makes it much easier to control a multi-cloud deployment, to control stuff in the cloud, but it also means you don't have to update software, we do it for you. It's just way simpler, so as time goes on, you know, on-prem infrastructure, in our belief, will become more and more the, you know, the thing operated by the cloud and the sort of puppet master will be outside. >> And performance, can you address performance? >> Yeah, so we ran, so basically our system scales quite well because of the way we built it, and we ran, you know, benchmark to take some of the vendors because we wanted to prove it that we're really good at this stuff, and we are the fastest probably on the planet. Our performance is really, really, very good, and it's not because everybody wants it, it's because you don't have to think about it anymore. You don't have, you don't, like it's one of those things again, don't think about it, just works for you, the performance is super high. >> Hm... >> We have customer validations, via the way, we have gotten our reviews from customers who are really, really five-star. We have, like, raving fans for our product. >> Excellent, well guys, thanks very much for helping us parse through that and appreciate you coming back on. >> Okay, thank you very much. >> Thanks for having us. >> All right, thanks for watching, everybody, this special CUBE conversation from out Palo Alto studios. This is Dave Vellante, we'll see you next time. (techy music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering VMworld 2017. Brought to you by VMware and its ecosystem partners. >> Hey welcome back everyone. Live here in Las Vegas. This is Vmworld 2017, exclusive CUBE coverage. I'm John Furrier with theCUBE. My co-host Dave Vellante. Next guest Brian Biles, who's the CEO and founder of Datrium, former entrepreneur. Founder, Data Domain. Entrepreneur, great to have you. >> Great to be here. Good to see you guys. >> Big launch, Datrium. You guys are out there as the crest of the wave is hitting. >> Brian: The crest of which wave? >> The wave of cloud, data, all the waves. >> Dave: So many waves. >> I mean, okay question. What's the biggest wave you're riding right now? >> Within, so there are two big ones. One is you know, enterprises are shifting some of their deployment to public clouds. So, you know, we're helping navigate some of that. The other is, within private clouds, they're moving to converged infrastructure. So our business starts with that but it's starting to have dimensions on public cloud. >> And what does that mean for the customers, people out there right now coming to VMworld this year, they go "Okay, I know what cloud is. "It's a true private cloud on premise operating model "with bursting now, with Amazon, I've got clear picture. "Everything else I'll fill in the blank from there." >> Yeah, let me start in the other order. Within convergence, there's something like 10 percent, 20 percent of infrastructure has kind of moved to that model and it's growing. So traditional sort of specialized appliances are declining in favor of that. Most of our business is in that world. And we're able to combine compute primary and secondary storage in one scalable infrastructure. And that's never been done our way before. So we have a lot of great things to talk about there. Within migration to cloud, the sort of first thing that happened, if you're not moving like wholesale, a bunch of applications there, if you're doing a hybrid thing, the first thing that moves is like back up. Because it's a simple thing to move. It's a low cost store. So we're showing at this show, migration of snapshots in a pre compressed, pre de duplicated, encrypted way to S3 for restore to your on prem site. >> So as an entrepreneur, we're sitting around kind of like on the beach, playing golf, saying I just want to do a start-up. What was the motivation for you to do Datrium? >> For Datrium, so you guys have seen me for a while. I was the founder of Data Domain and Data Domain got bought by EMC. Frank Slootman who was running service now used to say as our CEO that after that acquisition it's sort of like being eaten by a python. Every day you look a little less like yourself. So we all sort of decided to move to a different thing. So the CTO group and I left about the same time. Decided to do something different. We met two guys who were principal engineers at VMware, had been there for 10 years and knew everything about the hypervisor world. We got together. And Datrium came out of that set of discussions. And it turned out, that was in 2012. Hyperconvergence was just starting to emerge so we were looking for the next thing after that. And then, Cloud was becoming big. How do we branch out to that? So all of these discussions were relevant to kind of early thinking even then. And now it's just become more clear. >> So Brian, this notion of bringing compute primary storage and secondary storage together. Where did that come from? Nobody really does that. >> Brian: No, and it's partly because of our background as people. Data Domain was a backup centric product. When I went to EMC, I ended up doing product strategy for the networker and Avamar products as well. We'd been in the backup world for 10 years. So we knew that space pretty well. Doing a storage system that was good for that on either disc or flash was something we knew how to do. But the people that were purely doing that couldn't figure out how to get it to work for primary storage. We took our understanding of that and with the help of our founders from VMware who knew how VM's expected primary IO to work, put together a different kind of framework. So we use hosts with Flash as a primary store. And a secondary set of chassis with spinning rust for persistence of data. So it's like a Pure on every host writing to, kind of a rubric for persistence. So if you actually had hyperconverged and a scale-out backup system, you'd have too much of everything. You'd have too many motherboards, too many persistence drives. You'd have duplicates of all kinds of hardware. By doing it together, we stripped it down so it's way more cost efficient. And it turns out way more scalable. >> So to share those resources and still solve those unique problems efficiently. >> That's right. So we can be as competitive as any data protection archiecture as well as being faster than the fastest all-flash array. >> You know there's a lot of debates going on. Mostly on the all-flash data center side. People say all-flash, it's here to stay. Flash is cheaper than spinning disc. There are a few people who say, "That's not true." And I think you're one of them. >> If you look at an actual implementation of an all-flash array, it's never alone. You're always doing back up to something else. And the something else is probably disc. We all the time see some all-flash array partnering with some disc based back up thing and that's the composite solution. Well you're not getting rid of spinning disc in that case. You're only doing it for the primary IO. But the secondary IO is going to disc. Or it might be going to tape. There are risk management cases where you might be going to Amazon with that backup data. You might be going to tape. But you're not getting rid of something low cost. And if you look at the list prices of an all-flash array versus the list prices of a scale-out backup array, it can be a quarter of the price. Because even if both have dedupe compression, you just, you're paying for insurance in the backup side. You don't want it to be super expensive. >> Yeah so, okay. And so you see that gap, indefinitely. >> You want to protect your data. And you want it to be low cost. We just engineered it together. >> So if we uplevel it beyond the media, Datrium, data is obviously fundamental to your name. Everybody talks about digital transformation. We see digital businesses as defined by the way in which you use your data. So how does Datrium fit into helping companies better leverage their data? >> Well you can sort of go through the life cycle of the data. At the end of the day, we're kind of a data management company that also lets you go fast. So in data management, you mostly want to work at a small granularity. Like VM or container level. An application level. Not at a sort of storage artifact level, like a LUN. You want to deal with apps. And so the convenient approximation of that is VM's are containers. That lets you deal with it easily. So when we have policies in our product for data protection, we don't do volume level snapshots. We let you do container level snapshots. Persistent volumes or VM level snapshots. Replicate them across any number of sites including AWS. Keep more than a million of these granular snapshots in a single system of shared data. So if you snapshot a VM on one host, it's immediately cloneable on another one in the rack. Or the same with a container. And otherwise, you can't really do that with a normal storage system. And this just makes it much more flexible. As it turns out, a lot faster. Because the read IO never leaves the host. It's always on local flash. >> We first had you on theCUBE at VMworld, I think two years ago. But you're moving beyond your VMware roots. >> Quite a bit. >> Dave: Into Linux and other areas. Maybe talk about that a little bit. >> Yeah thanks for bringing that up. This year we've had a lot of announcements. We changed the product considerably, the company. So not only can we do all this data management stuff, we can simultaneously support VMware hosts, Red Hat Virtualization, on just Linux hosts as well as Docker on bare metal. So that multi-hypervisor, multi-container ability in the same shared storage space is very unique. Even hyperconverged vendors don't do that. So yeah, that's opened up a lot of doors for us. >> What's the impact of customers? That's a unique opportunity for you guys. Why go that way and what's the impact to customers? >> Ultimately, people want to consolidate to converged infrastructure. But different application environments are optimized differently. If you want to consolidate, you have to support all the ones that matter. And that's why we're doing this. >> So give us the update on where you guys are right now as a company. Employee headcount, what's the vision, what's the next couple milestones for your success? >> We're about 140 people. We have sales in the U.S. predominantly. A little bit in some other locations. But mostly U.S. We'll be expanding that. We just over the course of this year done quite a lot. So we've gone from, you know, we've expanded our capacity and performance by more than an order of magnitude. We've expanded our number of snapshots and so on. And at the same rate, M by N replication across sites, including Amazon. What you'll see, so that's a lot. >> Lot of product work. Lot of product tech getting done. >> Yes, digestion of that and selling of that, we've moved to everything from commercial midrange, hyperconverged or array sales to sort of teleco, service provider class rack scale infrastructure opportunities. There's a lot. A lot of where we're investing is data management across multiple clouds. So we're showing Amazon replication today. We'll get to other clouds over time. And as well, do more things than just store backup data. We'll be doing more migration and disaster recovery. And a lot of things in the future with cloud. >> What's the most exciting thing happening that gets you excited right now in the industry? In the industry, as you guys look at your opportunity, cause you're the founder, CEO, you got the 20 mile steer. You kind of, lot of product work product CEO. You get to see the vision. As you guys got that trajectory going as a starter, you're forging new ground. What's getting you excited out there? >> In a sort of physical infrastructure sense, it's really interesting to see where NVMe fabric is going and how to leverage that. Because it's, first of all, going to be a different way to compose host instances. It has some problems. It's not a SAN, it doesn't let you do shared data. You can't do V motion using it because it's not a shared facility. And it requires hosts to do the aracia coding for the off-host storage. And that's not a normal model. It turns out it's what we do. So it's interesting. >> And that could be an opportunity or a challenge. >> Yeah. It's also really interesting to see where customers are going with their interface of data management across multiple clouds. It's very much an emerging territory. Similarly with containers. Containers have always been this sort of light weight stateless, it comes up it goes away kind of thing. Within a host, you don't really think about orchestrating container management across host in data management sense. But because we can do it, you can snapshot a container persistent volume on a host with us and then clone it immediately in the same name space under another host. For rapid development, no one's ever thought that through. And now we can offer that. So we're in a bunch of emerging dialogues in that stuff that no one's really had before. >> It's interesting. Bringing adult supervision to stateless apps. >> Yeah because containers are super useful as a development paradigm. It's lightweight, it's small. It allows migration in these really interesting ways. So people are trying to apply it to persistent data as well as stateless data. And that's giving a bunch of interesting new energy to the whole policy approach. >> Brian, great to have you on theCUBE. Great to see you. Congratulations on the venture, it's going great. And you had your launch recently. Big announcements. Keep on innovating, you're a pioneer. Looking forward to our next chat. Great to have you on theCUBE. Appreciate it. >> Thank you very much, thanks for the time. >> For live coverage, three days wall to wall coverage. Day one coming to an end. And here at VMworld 2017, it's theCUBE. Be right back with more coverage after this short break.

>> live from the Mandalay Bay Convention Center in Las Vegas. It's the king covering via World 2016 brought to you by IBM Wear and its ecosystem sponsors. Now here's your host stool minimum, >> including I Welcome back to the Q bomb stew. Minuteman here with my co host for this segment, Mark Farley, and we'll get the emerald 2016 here in Las Vegas. It's been five years since we've been in Vegas, and a lot of changes in five years back Elsa do this morning was talking about five years from now. They expect that to be kind of a crossover between public Cloud becomes majority from our research. We think that flash, you know, capacities. You know, you really are outstripping, You know, traditional hard disk drives within five years from now. So the two guests I have for this program, Brian Vials, is the CEO of Day Tree. Um, it's been a year since we had you on when you came out of stealth on really excited cause your customer along. We love having customers on down from Alaska, you know, within sight view of of of Russia. Maybe on Did you know Ben Craig, who's the c i O of Northern Bank. Thank you so much for coming. All right, so we want to talk a lot to you, but real quick. Ryan, why do you give us kind of the update on the company? What's happened in the last year where you are with the product in customer deployments? >> Sure. Last year, when we talked, daydream was just coming out of stealth mode. So we were introducing the notion of what we're doing. Starting in kind of mid Q. One of this year, we started shipping and deploying. Thankfully, one of our first customers was Ben. And, uh, you know, our our model of, ah, sort of convergence is different from anything else that you'll see a v m world. I think hearing Ben tell about his experience in deployment philosophy. What changed for him is probably the best way to understand what we do. >> All right, so and great leading. Start with first. Can you tell us a little bit about north from bank? How many locations you have your role there. How long you've been there? Kind of a quick synopsis. >> Sure. Where we're growing. Bank one of three publicly traded publicly held companies in the state of Alaska. We recently acquired residential mortgage after acquiring the last Pacific Bank. And so we have locations all the way from Fairbanks, Alaska, where it gets down to negative 50 negative, 60 below Fahrenheit down to Bellevue, Washington. And to be perfectly candid, what's helped propel some of that growth has been our virtual infrastructure and our virtual desktop infrastructure, which is predicated on us being able to grow our storage, which kind of ties directly into what we've got going on with a tree and >> that that that's great. Can you talk to you know what we're using before what led you to day tree? Um, you know, going with the startup is you know, it's a little risky, right? I thought, Cee Io's you buy on risk >> Well, and as a very conservative bank that serves a commercial market, risk is not something that way by into a lot. But it's also what propels some of our best customers to grow with us. And in this case, way had a lot of faith in the people that joined the company. From an early start, I personally knew a lot of the team from sales from engineering from leadership on That got us interested. Once we kind of got the hook way learned about the technology and found out that it was really the I dare say we're unicorn of storage that we've been looking for. And the reason is because way came from a ray based systems and we have the same revolution that a lot of customers did. We started out with a nice, cosy, equal logic system. We evolved into a nimble solution the hybrid era, if you will, of a raise. And we found that as we grew, we ran into scalability problems. A soon as we started tackling beady eye, we found that we immediately needed to segregate our workloads. Obviously, because servers and production beauty, I have a completely different read right profile. As we started looking at some of the limitations as we grew our video structure, we had to consider upgrading all our processors, all of our solid state drives, all of the things that helped make that hybrid array support our VD infrastructure, and it's costly. And so we did that once and then we grew again because maybe I was so darn popular. within our organization. At that time, we kind of caught wind of what was going on with the atrium, and it totally turned the paradigm on top of its head for what we were looking for. >> How did it? Well, I just heard that up, sir. How did the date Reum solution impact the or what did you talk about? The reed, Right balance? What was it about the day trim solution that solved what was the reed right? Balance you there for the >> young when we ran out of capacity with our equal logic, we had to go out and buy a whole new member when he ran out of capacity with are nimble, had to go out and buy a whole new controller. When we run out of capacity with day tree, um, solution, we literally could go out and get commoditized solid state drives one more into our local storage and end up literally impacting our performance by a magnifier. That's huge. So the big difference between day trim and these >> are >> my words I'm probably gonna screw this up, Bryant, So feel free to jump in, and in my opinion day trip starts out with a really good storage area network appliance, and then they basically take away all of you. I interface to it and stick it out on the network for durable rights. Then they move all of the logic, all of the compression, all of the D duplication. Even the raid calculations on to software that I call a hyper driver that runs the hyper visor level on each host. So instead of being bound by the controller doing all the heavy lifting, you now have it being done by a few extra processors, a few extra big of memory out on their servers. That puts the data as close as humanly possible, which is what hyper converging. But it also has this very durable back end that ensures that your rights are protected. So instead of having to span my storage across all of my hosts, I still have all the best parts of a durable sand on all the best parts of high performance. By bringing that that data closer to where the host. So that's why Atrium enabled us to be able to grow our VD I infrastructure literally overnight. Whenever we ran out of performance, we just pop in another drive and go and the performances is insane. We just finished writing a 72 page white paper for VM, where we did our own benchmarking. Um, using my OMETER sprayers could be using our secondary data center Resource is because they were, frankly, somewhat stagnant, and we knew that we'd be able to get with most level test impossible. And we found that we were getting insane amounts of performance, insane amounts of compression. And by that I can quantify we're getting 132,000 I ops at a little bit over a gig a sec running with two 0.94 milliseconds of late and see that's huge. And one of the things that we always used to compare when it came to performance was I ops and throughput. Whenever we talk to any storage vendor, they're always comparing. But we never talked about lately because Leighton See was really network bound and their storage bender could do anything about that. But by bringing the the brain's closer to the hosts, it solves that problem. And so now our latent C that was like a 25 minutes seconds using a completely unused, nimble storage sand was 2.94 milliseconds. What that translated into was about re X performance increase. So when we went from equal logic to nimble, we saw a multiplier. There we went from nimble toed D atrium. We saw three Export Supplier, and that translated directly into me being able to send our night processors home earlier. Which means less FT. Larger maintenance window times, faster performance for all of our branches. So it went on for a little bit there. But that's what daydreams done for us, >> right? And just to just to amplify that part of the the approached atrium Staking is to assume that host memory of some kind or another flash for now is going to become so big and so cheap that reads will just never leave the host at some point. And we're trying to make that point today. So we've increased our host density, for example, since last year, flash to 16 terabytes per host. Raw within line di Dupin compression. That could be 50 a 100 terabytes. So we have customers doing fairly big data warehouse operations where the reeds never leave the host. It's all host Flash Leighton see and they can go from an eight hour job to, ah, one hour job. It's, you know, and in our model, we sell a system that includes a protected repositories where the rights go. That's on a 10 big network. You buy hosts that have flash that you provisions from your server vendor? Um, we don't charge extra for the software that we load on the host. That does all the heavy lifting. It does the raid compression d do cloning. What have you It does all the local cashing. So we encourage people to put as much flash and as many hosts as possible against that repositories, and we make it financially attractive to do that. >> So how is the storage provisioned? Is it a They're not ones. How? >> So It all shows up, and this is one of the other big parts that is awesome for us. It shows up his one gigantic NFS datastore. Now it doesn't actually use NFS. Itjust presents that way to be anywhere. But previously we had about 34 different volumes. And like everybody else on the planet who thin provisions, we had to leave a buffer zone because we'd have developers that would put a bm where snapshot on something patches. Then forget about it, Philip. The volume bring the volume off lying panic ensues. So you imagine that 30 to 40% of buffer space times each one of those different volumes. Now we have one gigantic volume and each VM has its performance and all of its protection managed individually at the bm level. And that's huge because no longer do you have to set protection performance of the volume level. You can set it right in the B m. Um, >> so you don't even see storage. >> You don't ever have to log into the appliance that all you >> do serve earless storage lists. Rather, this is what we're having. It's >> all through the place. >> And because because all the rights go off, host the rights, don't interrupt each other the host on interrupt together. So we actually going to a lot of links to make sure that happens. So there's an isolation host, a host. That means if you want a provisional particular host for a particular set of demands, you can you could have VD I next door to data warehouse and you know the level of intensity doesn't matter to each other. So it's very specifically enforceable by host configuration or by managing the VM itself. Justus, you would do with the M where >> it gets a lot more flexibility than we would typically get with a hyper converge solution that has a very static growth and performance requirements. >> So when you talk about hyper convergence, the you know, number one, number two and number three things that we usually talk about is, you know, simplicity. So you're a pretty technical guy. You obviously understand this. Well, can you speak to beyond the, you know, kind of ecological nimble and how you scale that house kind of the day's your experience. How's the ongoing, how much you after, you know, test and tweak and adjust things? And how much is it? Just work? >> Well, this is one of the reasons that we went with the atrium is well, you know, when it comes down to it with a hyper converge solution, you're spanning all of your storage across your host, right? We're trying to make use of those. Resource is, but we just recently had one of our server's down because it had a problem with his bios for a little over 10 days. Troubleshooting it. It just doesn't want to stay up. If we're in a full hyper converged infrastructure and that was part of the cluster, that means that our data would've had to been migrated off of that hostess. Well, which is kind of a big deal. I love the idea of having a rock solid, purpose built, highly available device that make sure that my rights are there for me, but allows me to have the elastic configuration that I need on my host to be able to grow them as I see fit. And also to be able to work directly with my vendors to get the pricing points that I need for each. My resource is so our Oracle Servers Exchange Server sequel servers. We could put in some envy Emmy drives. It'll screen like a scalded dog, and for all of our file print servers, I t monitoring servers. We can go with Cem Samsung 8 50 e b o. Drives pop him in a couple of empty days, and we're still able to crank out the number of I ops that we need to be able. Thio appreciate between those at a very low cost point, but with a maximum amount of protection on that data. So that was a big song. Points >> are using both envy. Emmy and Block. >> We actually going through a server? Refresh. Right now, it's all part of the white paper that way. Just felt we decided to go with Internal in Vienna drives to start with two two terabyte internal PC cards. And then we have 2.5 inch in Vienna ready on the front load. But we also plumbed it to be able to use solid state drive so that we have that flexibility in the future to be able to use those servers as we see fit. So again, very elastic architecture and allows us to be kind of a control of what performance is assigned to each individual host. >> So what APS beyond VD? I Do you expect to use this for? Are you already deploying it further? >> VD I is our biggest consumer of resource is our users have come to expect that instant access to all of their applications eventually way have the ability to move the entire data center onto the day trim and so One of the things that we're currently completing this year is the rollout of beady eye to the remaining 40% of our branches. 60% of them are already running through the eye. And then after that, we're probably gonna end up taking our core servers and migrating them off and kind of through attrition, using some of our older array based technology for testing death. All >> right, so I can't let you go without asking you a bit. Just you're in a relationship with GM Ware House Veum. We're meeting your needs. Is there anything from GM wear or the storage ecosystem around them that would kind of make your job easier? >> Yes. If they got rid of the the Sphere Web client, that would be great. I am not a fan of the V Sphere Web client at all, and I wish they'd bring back the C Sharp client like to get that on the record because I tried to every single chance I could get. No, the truth is the integration between the day tree, um and being where is it's super tight. It's something I don't have to think about. It makes it easy for me to be able to do my job at the end of the day. That's what we're looking for. So I think the biggest focus that a lot of the constituents that air the Anchorage being where user group leader of said group are looking for stability and product releases and trying to make sure that there's more attention given to que es on some of the recent updates that they have. Hyper visor Weber >> Brian, I'll give you the final word takeaways that you want people to know about your company, your customers coming out. >> Of'em World. We're thrilled to be here for the second year, thrilled to be here with Ben. It's a It's a great, you know, exciting period for us. As a vendor, we're just moving into sort of nationwide deployment. So check us out of here at the show. If you're not, check us out on the Web. There's a lot of exciting things happening in convergence in general and atriums leading the way in a couple of interesting ways. All >> right, Brian and Ben, thank you so much for joining us. You know, I don't think we've done a cube segment in Alaska yet. so maybe we'll have to talk to you off camera about that. Recommended. All right. We'll be back with lots more coverage here from the emerald 2016. Thanks for watching the Cube. >> You're good at this. >> Oh, you're good.

it's the cube covering vmworld 2015 brought to you by VMware and its ecosystem sponsors and now your host dave vellante welcome back to moscone center everybody this is the cube silicon angles continuous production of vmworld 2015 Brian biles is here he's the CEO and co-founder of day trium Brian of course from data domain Fame David floor and I are really excited to see you thanks for coming on the cue that's great to see you guys again so in a while coming out of stealth right it's been a while you've been you've been busy right you get a domain work the DMC for a while kind of disappeared got really busy again and here you are yeah new hats got new books yeah yeah so tell us about daydream fundamentally guys on time yeah yeah well we're big on ties on the East Coast are you too well he's even more east than I am even though he goes out in California but uh yeah tell us about date you fundamentally different fundamentally different from other kinds of storage different kind of founding team so I was a founder of data domain and Hugo Patterson the CTO there BMC fellow became CTO for us we hadn't when we left emc we weren't sure what we were going to do we end up running into to VMware principal engineers who had been there 10 or 12 years working on all kinds of stuff and they believed that there was a market gap on scalable storage for VMS so we got together we use something about storage they knew something about BMS and three years later date reham is at its first trade show so talk more about that that Gavin happens all the time right guys alpha geeks nah no offense to that term it's a term of endearment yea sorry I'm a marketing guy tech ghastly ok so they get together and they sort of identify these problems and they're able to sniff them out at the root level so what really can you describe that problem or detail sure so broadly there are two kinds of storage right there's sort of arrays and emerging there's hyper converge they approach things in a very different way in a raise there tends to be a bottleneck in the controller the the electronics that that do the data services this the raid and the snapshotting and cloning and compression indeed even whatever and increasingly that takes more and more compute so Intel is you know helping every year but it's still a bottleneck and when you run out it's a cliff and you have to do a pretty expensive upgrade or migrate the data to a different place and that's sticky and takes a long time so in reaction hyper converged has emerged as an alternative and it you know it has the benefit of killing the array completely but it may have over corrected so it has some trade-offs that a lot of people don't like for example if a host goes down you know the host has assumed all the data management problems that are raised used to have so you have to migrate the data or rebuild it to service the hose if you know you can't have a fit very cleanly between a for example a blade server which has one or two drive bays and a hyper converged model where you know you look across the floor the sort of average number of capacity drives is four or five not to mention the cache drives so a blade server it's just not a fit so there's a lot of parts of the industry where that model is just not the right model you know if everybody is writing to everybody then there's a lot of neighbor noise it gets kind of weird to troubleshoot in tune arrays you know we're better in some respects things change with hyper converged a little different we're trying to create a third path in our model there's a box that we sell it's a 2u rackmount a bunch of drives for capacity but the capacity is just for at rest data it's where all the rights go it's where persistence goes but we move all the data service processing the CPU for raid for compression for dee doop whatever to host cycles we upload software to an ESX host and it uses you know anybody's x86 server and you bring your own flash for caching so you know Gartner did a thing at the end of the year where they looked at discounted street price for flash the difference between what you could pay on a server for flash you know just a commodity SSD and what you could pay in an array it was like an 8x difference so if you don't you know we don't put raid on the host all the rate is in the back end so that frees up another whatever twenty percent you end up getting an order of magnitude difference in pricing so what you can get from us in flash on a host is not you don't aim at ten percent you know of your active data in cash it gets close to a hundred dollars a terabyte after you do d Dupin compression on you know server flash so it's just cheap and plentiful you put all your data up there everything runs out of flash locally it never gets a network hit for a read we do read caching locally unlike a hyper converge we don't spread data in a pool across the host we're not interrupting every host for read for rights for you know somebody else everything is local so when you do a write it goes to our box on the end of the wire 10 gig attached but all of the compute operations are local so you're not interrupting everybody all the resourcing you would do for any i/o problem is a local either cores or flash resourcing so it's a different model and it you know it's a really well student from blade servers no one else was doing that in such a good way unlike a cash-only product it's completely organically designed for manageability you don't have a separate tier for managing on the host separate from an array where you know you're probably duplicating provisioning and having to worry about how to do dinner a snapshot when you have to flush the cache on the host it's all completely designed from the ground up so it means the the storage that we store too is minimal cost we don't have the compute overhead that you have with a controller you don't have the flash which is really expensive there that's just cycles on the host everything is you know done with the most efficient path for both data and hardware so if you look at designs in general the flash is either being a cache or it's been 100% flash or it's been a tier of story so you're just fine understand that correctly there isn't any tearing because you've got a hundred percent of it in flash so that your goals yeah we use flash on the host as a cash right but only in the sort of i only use that word guardedly initial degenerate case it's all of the data yeah so it's a cash in the spirit that if the coast dies you haven't lost any data the data is always safe somewhere else right but it's all the data it's all the data so that's sitting on the disk the back end I presume you're writing sequential event all the time with log files answering and you saw the the disk in the most effective way that's right at both sides move the flash it's a log structured and the disk it's a log stretch ownership yeah and you know we had the advantage of data domain it was the most popular log structured file system ever and you know we learned all the tricks about dee doop and garbage collection along time ago so that CTO team is uniquely qualified to get this right so what about if it does go down are you clustering it what happens when it goes down and you have to recover from those disk drives that could take a bit of time good so there's two sides of that if a host fails you know you you use vm h a to restart the vm somewhere else and life goes on if the back end fails it fails the way a traditional mid-range array might fail we have dual controllers so stay over there all the disks are dual attached there's you know dual networks on each controller you can have service which failover it's a raid 6 so there's a rebuild that happens if it disk fails but you could have two of those and keep going but a point i was getting it was that if you fail in the host you've lost all your active data be precise with them we've lost the cache copy in that local flash but you haven't lost any de una lista de menthe you've lost it from the point of view of the only from a standpoint of speed yeah so at that point you know if the ho is down you have to restart the vm somewhere else that's not instant that takes number of minutes and that gives us some time to upload data to that host to know that great good the data is all laid out in our system not for interactive views on the disk drives but for very fast upload to a cash right it's all sort of sequentially laid out unblended per vm for blasting too so what do you see is the key application times that this is going to be particularly suited full so we have the our back-end system has about 30 terabytes usable after all the you know raid and everything and dude even compressions so I figure you know 2 4 6 X data reduction call it 100 terabytes ish depends on mileage so 100 terabyte box will you know sell that that's kind of a mid-range class array it will sell mostly to those markets and our software supports only vm storage virtual disks so as long as it meets those criteria it's pretty flexible the host each host can have up to eight terabytes of raw flash you know post d doofen compression that could be 50 terabytes of effective capacity of flash / host and you know reads never leave the host so you don't get network overhead for read so that's usually two-thirds of most people I own so it's enormously price and cost effective and very performance performant as well right right latency stuff and your IP is the way you lay out the data on the media is that part of the well listen it's it's like to custom file systems from scratch yeah once in one of the hosts not to mention all the management to make it look like there's one thing you know so it's there's a lot going on it's a much more complex project than data domain wise yeah so you mentioned you know you learned from your blog structured file garbage collection days of data but the the problem that you're solving here is much closer to the host much more active data so was that obviously a challenge but so that was part of the new invention required or was really just directly sort of i mean it's at all levels we had to make it fit so we're very vm centric it looks to the software looks to ESX as though it's an NFS share right but NFS terminates in each host and then we use our own protocol to get across 10 gig to the backend and this gives us some special effects will be able to talk about overtime every version alike at entry design in some ways well it's an offense so so you get to see every VMs storage discreetly it's sort of a you know before v vols there was NFS what many support five dot five so this was a logical choice right so everything's vm centric all of the management just it just looks like there's a big pool of storage and everything else is per vm from from diagnostics to capacity planning to whatever clones are per vm you don't have to you know spend a lot of analytics to fig you know back out what the block Lunds look like with respect to the VMS and try to you know look it up figured out it's just that's all there is so I've talked to a lot of we keep on been talking to a lot of flash and you people and this is almost a flash only in the sense that you are everything is going all of the idea is going to that flash once flash is sufficiently cheap and abundant yes no so and we know we write to nvram which is the same as an all-flash array so one of the things that we've noticed is that what they find is that they have to organize things completely differently particularly as they're trying to share things and for example instead of having a the production system and then a separate copy for each application developer another separate coffee for the for the data warehouse they're trying to combine those and share the data across there with snapshots of one sort or knowledge to amortize they're very high costs just because it's much faster and quicker since the customers are doing this and I think you're not they did vendors they don't even know what's going on so but because they can share it you don't have to move the data well so it's good it's allows the developers have a more current copy the data so they can work on near production all right yeah so I was just wondering whether that was an area that you are looking at to again apply a different way of doing storage so it takes a test debuts case you saying yeah well testing or data warehousing or whatever I mean we're certainly sensitive to the overhead of having a lot of copies that's why you insolent Dean you and so on the way we do so it's but you can get so very efficient but it allows you to for example if you're doing a clone it's a you know a dee doo clone so it's it gives you a new name space entry and it keeps the rights separate but it it you know lets the common data the data with commonality across other versions be consistent so we gotta wrap but the time we have remaining so just quick update on the company headcount funding investors maybe just give us the rundown sure we raised Series A and B we've raised about 55 million so far NEA and light speed plus some angels Frank's luqman Kylie Diane Greene original founder of VMware and Ed Boon yan who was the original CTO right about a little over 70 people great and this is our first trade show and yeah awesome well congratulations Brian you know it's really awesome to see you back in and actually not to have been in action but now invisible action so well it's great to be here thanks very much for coming on cue congrat day everybody will be back right after this is the cube rely from vmworld 2015 right back

>> From Tavern on the Green in Central Park, New York, it's theCUBE, covering Veritas Vision Solution Day. Brought to you by Veritas. >> Hi everybody, welcome back to Tavern on the Green. We're in the heart of Central Park in New York City, the Big Apple. My name is Dave Vellante and you're watching theCUBE, the leader in live tech coverage. We're here at the Veritas Solution Day #VtasVision. Veritas used to have a big main tent day where they brought in all the customers. Now they're going out, belly-to-belly, 20 cities. Dave Raffo is here, he's the editorial director for TechTarget Storage. Somebody who follows this space very closely. David good to see you, welcome to theCUBE. >> Yeah, it's great to be on theCUBE. I always hear and watch you guys but never been on before. >> Well you're now an alum, I got to get him a sticker. So, we were talking about VMworld just now, and that show, last two years, one of the hottest topics anyway, was cloud, multi-cloud, Kubernetes of course was a hot topic. But, data protection was right up there. Why, in your view, is data protection such a hot topic right now? >> Well there's a lot of changes going on. First of all, couple years ago it was backup, nobody calls it backup anymore right. The whole market is changing. Data protection, you have newer guys like Cohesity and Ruberik, would come out with a, you know, architecture. They're basically, from scratch, they built scale-out and that's changing the way people look at data protection. You have all of the data protection guys, the Dell EMC, CommVault, Veeam, they're all kind of changing a little. And Veritas, the old guys, have been doing it forever. And now they're changing the way that they're reacting to the competition. The cloud is becoming a major force in where data lives, and you have to protect that. So there's a lot of changes going on in the market. >> Yeah I was talking to a Gartner analyst recently, he said they're data suggested about 2/3 of the customers that they talk to, within the next, I think, 18 months, are going to change they're backup approach or reconsider how they do backup or data protection as it were, as you just said. What do you think is driving that? I mean, people cite digital transformation they cite cloud, they cite big data, all the buzz words. You know, where there's smoke, there's fire, I guess. But what are your thoughts? >> Yeah, it's a little bit of all of those things, because the IT infrastructure is changing, virtualization containers, everything, every architectural change changes the way you protect and manage your data, right. So, we're seeing a lot of those changes, and now people are reacting to it and everybody's figuring out still how to use the cloud and where the data is going to live. So then, you know, how do you protect that data? >> And of course, when you listen to vendors talk, data protection, backup, recovery, it's very sexy when you talk to the customers they're just, oftentimes, drinking from the fire hose, right. Just trying to solve the next problem that they have. But what are you hearing from the customers? TechTarget obviously has a big community. You guys do a lot of events. You talk personally to a lot of customers, particularly when there are new announcements. And what does the landscape look like to you? >> So they're all, you know like I said, everybody's looking at the cloud. They're looking at all these, how they're going to use these things. They're not sure yet, but they want data protection, data management that will kind of fit in no matter which direction they go. It's kind of, you know, we know we're looking at where we're going to be in five years and now we want to know how we're going to protect, how we're going to manage our data, how we're going to use it, move it from cloud to cloud. So, you know, it's kind of like, it's a lot of positioning going on now. A lot of planing for the future. And they're trying to figure out what's the best way they're going to be able to do all this stuff. >> Yeah, so, you know the hot thing, it used to be, like you said, backup. And then of course, people said backup is one thing, recovery is everything. You know, so it was the old bromide, my friend Fred Moore, I think coined that term, back in the old storage tech days. But when you think about cloud, and you think about the different cloud suppliers, they've all got different approaches, they're different walled gardens, essentially. And they've got different processes for at least replicating, backing up data. Where do you see customers, in terms of having that sort of single abstraction layer, the single data protection philosophy or strategy and set of products for multi-cloud? >> Well, where they are is they're not there, and they're, you know, far from it, but that's where they want to be. So, that's where a lot of the vendor positioning is going. A lot of the customers are looking to do that. But another thing that's changing it is, you know, people aren't using Oracle, SQL databases all the time anymore either. They're using the NoSQL MongoDB. So that change, you know, you need different products for that too. So, the whole, almost every type of product, hyper-converged is changing backup. So, you know, all these technologies are changing the way people actually are going to protect their data. >> So you look at the guys with the big install base, obviously Veritas is one, guys like IBM, certainly CommVault and there are others that have large install bases. And the new guys, the upstarts, they're licking their chops to go after them. What do you see as, let's take Veritas as an example, the vulnerabilities and the strengths of a company like that? >> So the vulnerabilities of an old company that's been around forever is that, the newer guys are coming with a clean sheet of paper and coming up and developing their products around technologies that didn't exist when NetBackup was created, right. So the strength is that, for Veritas, they have huge install base. They have all the products, technology they need. They have a lot of engineers so they can get to the board, drawing board, and figure it out and add stuff. And what they're trying to do is build around NetBackup saying all these companies are using NetBackup, so let's expand that, let's build archiving in, let's build, you know, copy data protect, copy data management into that. Let's build encryption, all of that, into NetBackup. You know, appliances, they're going farther, farther and farther into appliances. Seems like nobody wants to just buy backup software, and backup hardware as separate, which they were forever. So you know, we're seeing the integration there. >> Well that brings up another good point, is you know, for years, backup's been kind of one size fits all. So that meant you were either over protected, or under protected. It was maybe an after thought, a bolt-on, you put in applications, put it in a server, an application on top of it. You know, install Linux, maybe some Oracle databases. All of the a sudden, oh, we got to back this thing up. And increasingly, people are saying, hey, I don't want to just pay for insurance, I'd like to get more value. And so, you're hearing a lot of talk about governance, certainly security, ransomware is now a big topic, analytics. What are you seeing, in terms of, some of those additional value, those value adds beyond that, is it still just insurance, or are we seeing incremental value to customers? >> Yeah, well I think everybody wants incremental value. They have the data, now it's not just, like you said, insurance. It's like how is this going to, how am I going to use this data? How's it going to help my business? So, the analytics is a big thing that everybody's trying to get in. You know, primary and secondary storage everybody's adding analytics. AI, how we use AI, machine learning. You know, how we're going to back up data from the edge into and out of thing. What are we going to do with all this data? How are we going to collect it, centralize it, and then use it for our business purposes? So there's, you know, it's a wide open field. Remember it used to be, people would say backup, nobody ever changes their backup, nobody wants to change backup. Now surveys are saying within the next two years or so, more than 50% of people are looking to either add a backup product, or just change out their whole backup infrastructure. >> Well that was the interesting about when, you know, the ascendancy of Data Domain, as you recall, you were following the company back then. The beauty of that architecture was, you don't have to change your backup processes. And now, that's maybe a challenge for a company like that. Where people are, because of digital, because of cloud, they're actually looking to change their backup processes. Not unlike, although there are differences, but a similar wave, remember the early days of virtualization, you had, you're loosing physical resources, so you had to rethink backup. Are you seeing similar trends today, with cloud, and digital? >> Yeah, the cloud, containers, microservices, things like that, you know, how do you protect that data? You know people, some people are still struggling with virtualization, you know, like, there's so many more VMs being created so quickly, and that you know, a lot of the backup products still haven't caught up to that. So, I mean Veeam has made an awful great business around dealing with VM backup, right? >> Right. >> Where was everybody else before that? Nobody else could do it. >> We storage guys, we're like the cockroaches of the industry. We're just this, storage just doesn't seem to die. You know the joke is, there's a hundred people in storage and 99 seats. But you've been following it for a long time. Yeah, you see all the hot topics like cloud and multi-cloud and digital transformation. Are you surprised at the amount of venture capital over the last, you know, four or five years, that has flooded in to storage, that continues to flood in to storage? And you see some notable successes, sure some failures, but even those failures, you're seeing the CEOs come out and sell to new companies and you're seeing the rise of a lot of these startups and a lot of these unicorns. Does it surprise you, or is that kind of your expectation? >> Well, I mean, like you said, that's the way it's always been in storage. When you look at storage compared to networking and compute, how many startups are there in those other areas. Very few, but storage keeps getting funded. A couple of years ago, I used to joke, if you said I do Flash, people would just throw hundreds of millions of dollars at you, then it was cloud. There always seem to be like a hot topic, a hot spot, that you can get money from VCs. And there's always four or five, at least, storage vendors who are in that space. >> Yeah, the cloud, the storage cloud AI blockchain company is really the next unicorn right? >> Right, yeah, if you know the right buzz words you can get money. And there's never just one right, there's always a couple in that same area and then one or two make it. >> Yeah, or, and or, if you've done before, right, you're seeing that a lot. I mean, you see what the guys like, for instance at Datrium are doing. Brian Biles he did it a Data Domain, and now he's, they just did a giant raise. >> Qumulo. >> Yeah, you know, Qumulo, for sure. Obviously the Cohesity are sort of well known, in terms of how they've done giant raises. So there's massive amount of capital now pouring in, much of which will go into innovation. It's kind of, it's engineering and it's you know, go to market and marketing. So, you know, no doubt, that that innovation curve will continue. I guess you can't bet against data growth. >> Right, you know, yeah, right, everybody knows data is going to grow. They're saying it's the new oil, right. Data is the big thing. The interesting thing with the funding stuff now is the, not the new companies, but the companies that have been around a little bit, and it's now time for them to start showing revenue. And where in the past it was easier for them to get money, now it seems a little tougher for those guys. So, you know, we could see more companies go away without getting bought up or go public but-- >> Okay, great. Dave, thanks very much for coming on theCUBE. >> Alright. >> It was great to have you. >> Thanks for having me on. >> Alright keep it right there everybody. We'll be back with our next guest. You're watching theCUBE from Veritas Vision in Central Park. We'll be right back. (theCUBE theme music)