>> From the SiliconANGLE media office in Boston, Massachusetts, it's theCUBE! Now, here's your host, Dave Vellante. >> Hi, everybody, welcome to this special CUBE Conversation. You know, big data workloads have evolved, and the infrastructure that runs big data workloads is also evolving. Big data, AI, other emerging workloads need infrastructure that can keep up. Welcome to this special CUBE Conversation with Patrick Osborne, who's the vice president and GM of big data and secondary storage at Hewlett Packard Enterprise, @patrick_osborne. Great to see you again, thanks for coming on. >> Great, love to be back here. >> As I said up front, big data's changing. It's evolving, and the infrastructure has to also evolve. What are you seeing, Patrick, and what's HPE seeing in terms of the market forces right now driving big data and analytics? >> Well, some of the things that we see in the data center, there is a continuous move to move from bare metal to virtualized. Everyone's on that train. To containerization of existing apps, your apps of record, business, mission-critical apps. But really, what a lot of folks are doing right now is adding additional services to those applications, those data sets, so, new ways to interact, new apps. A lot of those are being developed with a lot of techniques that revolve around big data and analytics. We're definitely seeing the pressure to modernize what you have on-prem today, but you know, you can't sit there and be static. You gotta provide new services around what you're doing for your customers. A lot of those are coming in the form of this Mode 2 type of application development. >> One of the things that we're seeing, everybody talks about digital transformation. It's the hot buzzword of the day. To us, digital means data first. Presumably, you're seeing that. Are organizations organizing around their data, and what does that mean for infrastructure? >> Yeah, absolutely. We see a lot of folks employing not only technology to do that. They're doing organizational techniques, so, peak teams. You know, bringing together a lot of different functions. Also, too, organizing around the data has become very different right now, that you've got data out on the edge, right? It's coming into the core. A lot of folks are moving some of their edge to the cloud, or even their core to the cloud. You gotta make a lot of decisions and be able to organize around a pretty complex set of places, physical and virtual, where your data's gonna lie. >> There's a lot of talk, too, about the data pipeline. The data pipeline used to be, you had an enterprise data warehouse, and the pipeline was, you'd go through a few people that would build some cubes and then they'd hand off a bunch of reports. The data pipeline, it's getting much more complex. You've got the edge coming in, you've got, you know, core. You've got the cloud, which can be on-prem or public cloud. Talk about the evolution of the data pipeline and what that means for infrastructure and big data workloads. >> For a lot of our customers, and we've got a pretty interesting business here at HPE. We do a lot with the Intelligent Edge, so, our Edgeline servers in Aruba, where a a lot of the data is sitting outside of the traditional data center. Then we have what's going on in the core, which, for a lot of customers, they are moving from either traditional EDW, right, or even Hadoop 1.0 if they started that transformation five to seven years ago, to, a lot of things are happening now in real time, or a combination thereof. The data types are pretty dynamic. Some of that is always getting processed out on the edge. Results are getting sent back to the core. We're also seeing a lot of folks move to real-time data analytics, or some people call it fast data. That sits in your core data center, so utilizing things like Kafka and Spark. A lot of the techniques for persistent storage are brand new. What it boils down to is, it's an opportunity, but it's also very complex for our customers. >> What about some of the technical trends behind what's going on with big data? I mean, you've got sprawl, with both data sprawl, you've got workload sprawl. You got developers that are dealing with a lot of complex tooling. What are you guys seeing there, in terms of the big mega-trends? >> We have, as you know, HPE has quite a few customers in the mid-range in enterprise segments. We have some customers that are very tech-forward. A lot of those customers are moving from this, you know, Hadoop 1.0, Hadoop 2.0 system to a set of essentially mixed workloads that are very multi-tenant. We see customers that have, essentially, a mix of batch-oriented workloads. Now they're introducing these streaming type of workloads to folks who are bringing in things like TensorFlow and GPGPUs, and they're trying to apply some of the techniques of AI and ML into those clusters. What we're seeing right now is that that is causing a lot of complexity, not only in the way you do your apps, but the number of applications and the number of tenants who use that data. It's getting used all day long for various different, so now what we're seeing is it's grown up. It started as an opportunity, a science project, the POC. Now it's business-critical. Becoming, now, it's very mission-critical for a lot of the services that drives. >> Am I correct that those diverse workloads used to require a bespoke set of infrastructure that was very siloed? I'm inferring that technology today will allow you to bring those workloads together on a single platform. Is that correct? >> A couple of things that we offer, and we've been helping customers to get off the complexity train, but provide them flexibility and elasticity is, a lot of the workloads that we did in the past were either very vertically-focused and integrated. One app server, networking, storage, to, you know, the beginning of the analytics phase was really around symmetrical clusters and scaling them out. Now we've got a very rich and diverse set of components and infrastructure that can essentially allow a customer to make a data lake that's very scalable. Compute, storage-oriented nodes, GPU-oriented nodes, so it's very flexible and helps us, helps the customers take complexity out of their environment. >> In thinking about, when you talk to customers, what are they struggling with, specifically as it relates to infrastructure? Again, we talked about tooling. I mean, Hadoop is well-known for the complexity of the tooling. But specifically from an infrastructure standpoint, what are the big complaints that you hear? >> A couple things that we hear is that my budget's flat for the next year or couple years, right? We talked earlier in the conversation about, I have to modernize, virtualize, containerizing my existing apps, that means I have to introduce new services as well with a very different type of DevOps, you know, mode of operations. That's all with the existing staff, right? That's the number one issue that we hear from the customers. Anything that we can do to help increase the velocity of deployment through automation. We hear now, frankly, the battle is for whether I'm gonna run these type of workloads on-prem versus off-prem. We have a set of technology as well as services, enabling services with Pointnext. You remember the acquisition we made around cloud technology partners to right-place where those workloads are gonna go and become like a broker in that conversation and assist customers to make that transition and then, ultimately, give them an elastic platform that's gonna scale for the diverse set of workloads that's well-known, sized, easy to deploy. >> As you get all this data, and the data's, you know, Hadoop, it sorta blew up the data model. Said, "Okay, we'll leave the data where it is, "we'll bring the compute there." You had a lot of skunk works projects growing. What about governance, security, compliance? As you have data sprawl, how are customers handling that challenge? Is it a challenge? >> Yeah, it certainly is a challenge. I mean, we've gone through it just recently with, you know, GDPR is implemented. You gotta think about how that's gonna fit into your workflow, and certainly security. The big thing that we see, certainly, is around if the data's residing outside of your traditional data center, that's a big issue. For us, when we have Edgeline servers, certainly a lot of things are coming in over wireless, there's a big buildout in advent of 5G coming out. That certainly is an area that customers are very concerned about in terms of who has their data, who has access to it, how can you tag it, how can you make sure it's secure. That's a big part of what we're trying to provide here at HPE. >> What specifically is HPE doing to address these problems? Products, services, partnerships, maybe you could talk about that a little bit. Maybe even start with, you know, what's your philosophy on infrastructure for big data and AI workloads? >> I mean, for us, we've over the last two years have really concentrated on essentially two areas. We have the Intelligent Edge, which is, certainly, it's been enabled by fantastic growth with our Aruba products in the networks in space and our Edgeline systems, so, being able to take that type of compute and get it as far out to the edge as possible. The other piece of it is around making hybrid IT simple, right? In that area, we wanna provide a very flexible, yet easy-to-deploy set of infrastructure for big data and AI workloads. We have this concept of the Elastic Platform for Analytics. It helps customers deploy that for a whole myriad of requirements. Very compute-oriented, storage-oriented, GPUs, cold and warm data lakes, for that matter. And the third area, what we've really focused on is the ecosystem that we bring to our customers as a portfolio company is evolving rapidly. As you know, in this big data and analytics workload space, the software development portion of it is super dynamic. If we can bring a vetted, well-known ecosystem to our customers as part of a solution with advisory services, that's definitely one of the key pieces that our customers love to come to HP for. >> What about partnerships around things like containers and simplifying the developer experience? >> I mean, we've been pretty public about some of our efforts in this area around OneSphere, and some of these, the models around, certainly, advisory services in this area with some recent acquisitions. For us, it's all about automation, and then we wanna be able to provide that experience to the customers, whether they want to develop those apps and deploy on-prem. You know, we love that. I think you guys tag it as true private cloud. But we know that the reality is, most people are embracing very quickly a hybrid cloud model. Given the ability to take those apps, develop them, put them on-prem, run them off-prem is pretty key for OneSphere. >> I remember Antonio Neri, when you guys announced Apollo, and you had the astronaut there. Antonio was just a lowly GM and VP at the time, and now he's, of course, CEO. Who knows what's in the future? But Apollo, generally at the time, it was like, okay, this is a high-performance computing system. We've talked about those worlds, HPC and big data coming together. Where does a system like Apollo fit in this world of big data workloads? >> Yeah, so we have a very wide product line for Apollo that helps, you know, some of them are very tailored to specific workloads. If you take a look at the way that people are deploying these infrastructures now, multi-tenant with many different workloads. We allow for some compute-focused systems, like the Apollo 2000. We have very balanced systems, the Apollo 4200, that allow a very good mix of CPU, memory, and now customers are certainly moving to flash and storage-class memory for these type of workloads. And then, Apollo 6500 were some of the newer systems that we have. Big memory footprint, NVIDIA GPUs allowing you to do very high calculations rates for AI and ML workloads. We take that and we aggregate that together. We've made some recent acquisitions, like Plexxi, for example. A big part of this is around simplification of the networking experience. You can probably see into the future of automation of the networking level, automation of the compute and storage level, and then having a very large and scalable data lake for customers' data repositories. Object, file, HTFS, some pretty interesting trends in that space. >> Yeah, I'm actually really super excited about the Plexxi acquisition. I think it's because flash, it used to be the bottleneck was the spinning disk, flash pushes the bottleneck largely to the network. Plexxi gonna allow you guys to scale, and I think actually leapfrog some of the other hyperconverged players that are out there. So, super excited to see what you guys do with that acquisition. It sounds like your focus is on optimizing the design for I/O. I'm sure flash fits in there as well. >> And that's a huge accelerator for, even when you take a look at our storage business, right? So, 3PAR, Nimble, All-Flash, certainly moving to NVMe and storage-class memory for acceleration of other types of big data databases. Even though we're talking about Hadoop today, right now, certainly SAP HANA, scale-out databases, Oracle, SQL, all these things play a part in the customer's infrastructure. >> Okay, so you were talking before about, a little bit about GPUs. What is this HPE Elastic Platform for big data analytics? What's that all about? >> I mean, we have a lot of the sizing and scalability falls on the shoulders of our customers in this space, especially in some of these new areas. What we've done is, we have, it's a product/a concept, and what we do is we have this, it's called the Elastic Platform for Analytics. It allows, with all those different components that I rattled off, all great systems in of their own, but when it comes to very complex multi-tenant workloads, what we do is try to take the mystery out of that for our customers, to be able to deploy that cookie-cutter module. We're even gonna get to a place pretty soon where we're able to offer that as a consumption-based service so you don't have to choose for an elastic type of acquisition experience between on-prem and off-prem. We're gonna provide that as well. It's not only a set of products. It's reference architectures. We do a lot of sizing with our partners. The Hortonworks, CloudEra's, MapR's, and a lot of the things that are out in the open source world. It's pretty good. >> We've been covering big data, as you know, for a long, long time. The early days of big data was like, "Oh, this is great, "we're just gonna put white boxes out there "and off the shelf storage!" Well, that changed as big data got, workloads became more enterprise, mainstream, they needed to be enterprise-ready. But my question to you is, okay, I hear you. You got products, you got services, you got perspectives, a philosophy. Obviously, you wanna sell some stuff. What has HPE done internally with regard to big data? How have you transformed your own business? >> For us, we wanna provide a really rich experience, not just products. To do that, you need to provide a set of services and automation, and what we've done is, with products and solutions like InfoSight, we've been able to, we call it AI for the Data Center, or certainly, the tagline of predictive analytics is something that Nimble's brought to the table for a long time. To provide that level of services, InfoSight, predictive analytics, AI for the Data Center, we're running our own big data infrastructure. It started a number of years ago even on our 3PAR platforms and other products, where we had scale-up databases. We moved and transitioned to batch-oriented Hadoop. Now we're fully embedded with real-time streaming analytics that come in every day, all day long, from our customers and telemetry. We're using AI and ML techniques to not only improve on what we've done that's certainly automating for the support experience, and making it easy to manage the platforms, but now introducing things like learning, automation engines, the recommendation engines for various things for our customers to take, essentially, the hands-on approach of managing the products and automate it and put into the products. So, for us, we've gone through a multi-phase, multi-year transition that's brought in things like Kafka and Spark and Elasticsearch. We're using all these techniques in our system to provide new services for our customers as well. >> Okay, great. You're practitioners, you got some street cred. >> Absolutely. >> Can I come back on InfoSight for a minute? It came through an acquisition of Nimble. It seems to us that you're a little bit ahead, and maybe you say a lot a bit ahead of the competition with regard to that capability. How do you see it? Where do you see InfoSight being applied across the portfolio, and how much of a lead do you think you have on competitors? >> I'm paranoid, so I don't think we ever have a good enough lead, right? You always gotta stay grinding on that front. But we think we have a really good product. You know, it speaks for itself. A lot of the customers love it. We've applied it to 3PAR, for example, so we came out with some, we have VMVision for a 3PAR that's based on InfoSight. We've got some things in the works for other product lines that are imminent pretty soon. You can think about what we've done for Nimble and 3PAR, we can apply similar type of logic to Elastic Platform for Analytics, like running at that type of cluster scale to automate a number of items that are pretty pedantic for the customers to manage. There's a lot of work going on within HPE to scale that as a service that we provide with most of our products. >> Okay, so where can I get more information on your big data offerings and what you guys are doing in that space? >> Yeah, so, we have, you can always go to hp.com/bigdata. We've got some really great information out there. We're in our run-up to our big end user event that we do every June in Las Vegas. It's HPE Discover. We have about 15,000 of our customers and trusted partners there, and we'll be doing a number of talks. I'm doing some work there with a British telecom. We'll give some great talks. Those'll be available online virtually, so you'll hear about not only what we're doing with our own InfoSight and big data services, but how other customers like BTE and 21st Century Fox and other folks are applying some of these techniques and making a big difference for their business as well. >> That's June 19th to the 21st. It's at the Sands Convention Center in between the Palazzo and the Venetian, so it's a good conference. Definitely check that out live if you can, or if not, you can all watch online. Excellent, Patrick, thanks so much for coming on and sharing with us this big data evolution. We'll be watching. >> Yeah, absolutely. >> And thank you for watcihing, everybody. We'll see you next time. This is Dave Vellante for theCUBE. (fast techno music)

>> Narrator: Live from Las Vegas. It's the Cube. Covering VMWorld 2017, brought to you by VMWare and it's ecosystem partners. >> Okay welcome back everyone live here at VMWorld 2017 behind us we got the stage here set on the VMVillage, a lot of people hanging out, I'm John Furrier with Dave Alante our next guest is Vish Muichand who's the Senior Director of Product Manager HPE, Cube alumni Eric Burgener, Research Director at IDC. Guys welcome to the Cube. >> Thanks very much John. >> Vish, lot of storage action going on VMWare, you see Vsan, the cloud's here, true private cloud report from Wikibonds off the charts, showing a huge growth on prem, cloud operations, storage is impacted. What's the dots that we're connecting here this week? What's the storage story this week? >> So clearly there's a lot of different things happening in the marketplace right, different modes of operation and that in itself is demanding different approaches to infrastructure. So I think what you are seeing in the industry a variety of different approaches in storage, right? Whether it's external storage, whether it's software-defined storage, whether it's hyperconversions, or that's all flash storage. All of these things are coming together and trying to respond to the needs of data and how you want to process that data. >> We've been talking with, we talk to you guys a lot on the Cube, HP Discover, and we always say software's eating the world, we just heard Sanjay Punin from VMWare talking about it, he likes to drop that soundbyte. We take it one step further. He's a Harvard MBA, we got the bapsen mojo here. We say if software's eating the world, then data's eating software. So you guys have had a software core competence and you mentioned data. What is the impact and compromise, more and more data comes in from the edge, this primary, this secondary storage, this backup this data protection, it seems to be like this melting pot of changing architectures. How are you guys handling that at HP? >> Filling software is a very key element because it provides you with those capabilities, right? To really deal with the logical instantiation of assets and in this very virtualized world, this very dynamic world right now, gone are the days where you can do hardware type desegregation. Software gives you that speed, that agility, it gives you that flexibility. Gives you the changeability to move quickly. >> Eric you're at IDC you guys, this is your job. You guys track the market share, you guys have the pulse it's like keeping track of the baseball game. What inning, how are the Red Sox doing? Are they in first place are the Yankees catching up? What is the current state of the server virtualization because you know certainly the game's changing a little bit the world's going to cloud. What are you guys seeing in your research? >> Well so obviously most mainstream computing is running on virtualization, whether that's in the cloud or that's on prem. There's very little physical infrastructure left. There is still some of that but clearly that is not the future, virtualization is the future. >> So I wonder if I may, so you're saying virtualization is the future, so I wonder if we can unpack that a little bit because the theme here is cloud and everything is cloud related. Is your feeling, Eric, that that's sort of over your skis marketing, getting ahead of where the customer really is, I wonder if you could sort of elaborate. >> I think what the customers are really looking for is an easier way to do their jobs for less cost. And cloud provides that flexibility that you don't necessarily get if you're managing your own on-premise infrastructure, that's not 100% true based on some scale issues, but by and large, I think that's really what cloud brings to the table is a different payment model, and a flexibility that you wouldn't necessarily have with on prem infrastructure. >> So what are you guys seeing, do you feel as though the on-prem infrastructure leaders like HP, there are others obviously, are going to be able to bring that cloud-like simplicity to what do you call private cloud or whatever on-prem, is that happening, how fast is it happening, is it viable? >> Yeah so I absolutely think that's happening, in fact that's one of the reasons why software-defined storage is growing so fast is those type of products give you the kind of agility that you would normally get from a cloud environment and if you're running that on prem and you've implemented the right infrastructure around it then you're getting many of those same kind of benefits. Now you're paying for that hardware and software in a different manner than you do for the cloud, but you're getting many of those IT agility benefits that you might otherwise get from the cloud. >> And Dave, you know HP's tagline is Making Hybrid IT Simple right and so our point of view is that there is both on premise and off premise, just depending on what the usage models are and what the problems you're trying to solve, right. And bringing that simplicity where you may be going from a 100% on premise to maybe 20% off, but we've also seen some people at 50% off premise trying to come back a little bit on premise, right? So both directions I think are very very key. >> Is your point of view and I want Eric if you could chime in as well, from HPE's perspective, is hybrid IT sort of horses for courses in other words, workloads on prem versus workloads off prem, or is it beyond that some kind of federation model? >> So we see three key use cases. The first is of course wholesale, applications running on the cloud. Office 365, the perfect example of that, Sharepoint, Dropbox right, that's one. Then there is what I would call disaster recovery as a service, where you may want to have your third site in the cloud even though you got two sites on premise. Then there's also the third use case or in archiving that says how do I archive a portion of my data maybe into the cloud so it is online, but I don't have to manage it and I don't have to maybe deal with some of the associated costs around it. So these are the three sort of cases I see. >> Dave: Okay, what are you seeing in the customer base, Eric? >> Well so I completely agree that hybrid cloud is the way data centers are going to be built going forward. There are reasons to keep certain workloads on prem, generally there's performance, security or some kind of regulatory requirements that might make you put workloads on prem versus putting them in the cloud. It also depends on how often you're using the data. So Vish mentioned archive use cases. So that's a case where you need a lot of storage capacity that you keep for a long time but you may not necessarily be accessing it that much. If you're going to be accessing data a lot, that's another reason why you might consider bringing it on prem, as opposed to leaving it off prem. And of course the access, the costing access models that you get from people like Amazon and Azure are going to impact where you draw the line on that. >> So is there a difference between multi-cloud, I got a bunch of different clouds in my organization, I'm going to choose where to put stuff and cross-cloud sometimes you call it inter-clouding was, I like that term. >> Vish: You could dual source your cloud. >> And either dual source or federate or actually split application work. >> So I have seen several different aspects of that. So a customer has said to me that they need to move 20% of their data off premise, to do that they need two cloud vendors, and to get to two cloud vendors they need to see four or five of them so they can narrow it down and they they says okay, HPE all of the data that I have today is in your premise or with your equipment, how are you helping us broker that kind of arrangement. What are you doing to help federate some of that data? And work with some of these cloud vendors. So I think that's an interesting customer ask. >> Okay, well there's also cost consideration because if you multi-source or you have the opportunity to multi-source, you've got a competitive environment that's going to drive lower costs for you. As opposed to if you just got one choice. The other issue there is data mobility. If I'm locked into cloud vendor one, and it's very difficult, there's major switching costs to move, then that's another reason that might offset the potential price advantage I get from being able to go to any vendor. So there's a lot of vendors out there now, infrastructure vendors that are talking about making it easier to move data on prem to off prem, into different clouds from cloud to cloud and I think that's something that creates a more level playing field that really is going to ultimately result in lower costs. >> That's a great point about the costs, we'll just double down a quick question on that. Where are customers tripping over themselves in terms of total cost of ownership because what you're getting at here is hidden costs, right in plain sight. What are those trip fault wires if you will? What's the pitfalls what should they be looking for? >> Well, so I'll give you a general answer to that, but I think that it's very specific to workload type and the regulatory requirements that you're in but I'll tell ya one of the cases where we see repatriation, workloads moving from the cloud back into on prem is when you get to a certain level of scale. And the largest enterprises. >> John: Scale in terms of when to bring it back? >> Well just in terms of how >> or when to leave >> So how much data do I need to basically maintain in this environment and use on a regular basis. And the larger scale environments are the one where larger enterprises are able to actually bring back, create their own cloud infrastructure on prem, with their own environments and actually manage that for less cost than what they could otherwise pay a public cloud provider. >> So just to take it one step further, connect the next dot, the CXO, the CIO has to try to get some stability and there's some uncontrollable things certainly in retail it's predictable that the holiday season needs bursting or whatever so you do some things in the cloud but that's a known pattern, so you're saying that they're starting to recognize some of these scale issues for predictability they bring them on prem. Is that kind of what I'm getting? >> Well so the scale from a cost point of view, so if you're creating your own private cloud infrastructure and you're using the same kind of highly agile software to find storage designs to build that environment, you somewhat have the same ability to burst. Now yeah, you have to buy the hardware and there's redeployment issues and hopefully when we move forward towards much more composable infrastructure that becomes a lot easier problem to solve but that's you know some years in the future. But what I'm really talking about it's the cost. If I'm going to be maintaining a five petabyte data set over a ten year period, and I know what my access patterns are, is it cheaper to put that in Amazon or is it cheaper for me to build an infrastructure in house and maintain that myself. >> That's a great point. That's huge and Vish what's your reaction, is this basically validates all the action going on on the private cloud right now, on prem activity is setting up the cloud models. They can't do that unless you have the operating model. >> I'll talk about two things right, one called Cloud Bank and another one called Nimble Cloud Volumes and soon to be called HPE Cloud Volumes. So Cloud Bank allows you to take on premise data running on a three part array, and actually take a portion of that data onto either an on premise object store or an off premise object store. And we call that Cloud Bank working together with something called Recovery Managed Central and store once bringing that cloud picture together. Now the HPE cloud volumes on Nimble Cloud Volumes, it's another interesting concept where you have a cloud service that's block storage service, but it gives you the six nines SLA, it gives you the ability to do snapshots and transform data without a lot of charges that Eric talked about. It gives you the ability to move the data to different clouds because it's disagregated from the major cloud providers, it's connected via a close proximity connection so these are just two examples I think that show you how putting these used cases into action. >> Hey can we geek out a little bit here? (laughter) >> Aren't we geeking out now? You want to go deeper? >> So people want simplicity, we know that, we're talking about bringing cloud on prem. How do they get there? Well one of the ways is VVOLs, we sort of been talking about this, they haven't really taken off. Eric you've written some content around this. Like you said off camera, customers don't wake up in the morning and say I got to get me some VVOLs. But they do want simplicity. >> Absolutely, yeah. >> What are VVOLs, why do they matter, and how does it relate to simplicity. >> So yeah, let's talk a little bit about that. So what everybody no matter whether they're putting storage in the cloud, they're building on prem, they're building a private cloud, everybody wants to be able to manage their environments more easily, more intuitively, and one of the things that we've seen as a trend over the last five years is in general across the industry, storage mangement tasks are migrating away from dedicated storage admin teams, more towards IT generalists. In many cases, those are the virtual administrators. To enable that kind of a move, you need to make storage much easier to manage. So the whole idea behind VVOLs is to basically allow a non-storage person who maybe thinks about things in terms of I'd like to do this operation to an application for example, I've got Oracle running or I've got this file system here and I want to create a snapshot of it or I want to do some other task on it. To be able to just select it at the application level and perform that operation, that's very intuitive, it's easy for a non-storage person to understand and VVOLs effectively enables that kind of an ease of use management in block based environments. >> An application view of the storage? >> That's right, and I mean it's effectively it ties storage operations to a single virtual machine, and basically you're running an app on a virtual machine and so that's how you get that tie in in that way. But one other thing I'll say about VVOLs is that so it's not just what VMWare provides, there's some work that needs to be done on the storage array side to integrate with that management framework. And then how that vendor has chosen to integrate with that framework is going to determine the functionality that you have access to when you're using that VVOLs API. >> And how have you chosen to integrate with that framework? >> Yeah so Dave if you look at VVOLs, both HPE and HPE 3Par nimble have bene very very strongly focused on VVOLs in fact we've been working with VMWare gosh over the last five years now, on the reference architecture for VVOLs. Most recently we've now introduced replication support for both 3Parand nimble platforms with VVOLs and I think that capability now within VVOLs is a very important watershed capability because everybody needs resilience, disaster recovery. >> Automation's right around the corner, orchestration all big topics here at VMWorld. >> Correct and so that's a very key piece. And I think if you look at to Eric's point around simplicity, VVOLs is one key area. Two layers maybe I'd like to highlight as well. Number one is the visibility to what the application sees and within the Nimble community, they've talked about this app data gap, which is the applications not knowing why they can't get access to data and so this notion of bringing that level of understanding visibility to that gap saying is it in your computer infrastructure, is it in storage, is it in the network? So this notion of VMVision, Infosight, the Nimble (inaudible) because you're going to bring out the rest of the HPE portfolio I think is very key around simplicity. The third thing let's not forget, VMWare's built a whole ecosystem of management platforms around V-Center, V-Realize operations, all the orchestration and operation pieces and so continuing to integrate and offer customers that view is very key, right, so three prong vector I would say on making things simple. >> Also it gives HPE discovers coming up in Madrid shortly. Congratulations good to see you, Eric thanks so much for stopping by and sharing the IDC perspective. Great job, live coverage here at VMWorld 2017, I'm John Furrier, Dave Alante we'll be right back with more live coverage after this short break. >> Thank you.