>> Narrator: From around the globe, It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Hi, welcome back to theCUBE's coverage of IBM Think 2021 virtual. We're not yet in real life. We're doing another remote interviews with two great guests Cube Alumni. Of course, I'm John Furrier your host of theCUBE. We've got Jason McGee, IBM fellow VP and CTO of IBM's cloud platform and Octavian the Nazis senior vice president Hybrid Cloud engineering at NetApp. Both Cube alumni, is great to see you both. Thanks for coming on theCUBE >> Yeah, great to be here. >> Thanks for having us. >> So we were just talking before we came on camera that, it feels like we've had this conversation, a long time ago we have, Hybrid Cloud has been on a trajectory for both of you guys in many times on theCUBE. So now it's mainstream, it's here in the real world. Everyone gets it. There's no real debate. Now multicloud that's people are debating that which means that's right around the corner. So Hybrid Cloud is here and now Jason this is really the focus. And this is also brings together the NetApp in your partnership and talk about the relationship first with Hybrid Cloud. >> Yeah, I mean, you know look we've talked a number of times together. I think in the industry, maybe a few years ago people were debating whether Hybrid Cloud was a real thing. We don't have that conversation anymore. I think, you know, enterprises today, especially maybe in the face of COVID and kind of how we work differently now realize that their cloud journey is going to be a mix of on-prem and off-prem systems probably going to be a mix of multiple public cloud providers. And what they're looking for now is how do I do that? And how do I manage that hybrid environment? How do I have a consistent platform across the different environments I want to operate in? And then how do I get more and more of my workload into those environments? And it's been interesting. I think the first waves of cloud were infrastructure centric and externally application focused they were easier things. And now we're moving into more mission critical more stateful, more data oriented workloads. And that brings with a new challenges on where applications run and how we leverage the club. >> Octavian, you guys had a great relationship with IBM over the years, data centric company NetApp has always been great engineering team. You're on the cloud, Hybrid Cloud engineering. What's the current status of the relationship. Give us an update on how it's vectoring into the Hybrid Cloud since you're a senior vice president of Hybrid Cloud engineering. >> Well, so first of all, I want to recognize 20 years of a successful partnership with IBM. I think NetApp and IBM have been companies that have embraced digital transformation and technology trends to enable that digital transformation for our customers. And we've been very successful. I think there is a very strong joint Hybrid Cloud value proposition for customers on NetApps storage and data services compliment what IBM does in terms of products and solutions both for on-premise deployments in the cloud. I think together we can build more complete solutions, solutions that span data mobility, data governance for the new workrooms that Jason has talked about. >> And how has some of the customer challenges that you're seeing obviously software defined networking software defined storage, DevOps is now turned into DevSecOps. So you have now that programmability requirement with for dynamic applications, applications driven, infrastructure, all these buzz words point to one thing, the infrastructure has to be resilient and respond to the applications. >> Yeah, I would say infrastructure will continue to be top of mind for everybody, whether they're building a private cloud or whether they we're trying to leverage, something like IBM cloud. I think, you know, people want to consume, infrastructure is an API. I think they want to simplicity, security. I think they want to manage their costs very well. I think we're very proud to be partnering with IBM cloud to build such capabilities. >> Jason how are you guys helping some of these customers as they look at new things and sometimes retrofitting and refactoring previous stuff during transforming, but also innovating at the same time. There's a lot of that going on. What are you guys doing to help with the Hybrid challenges? >> Yeah, I mean, you know, there's a lot of dimensions to that problem but the one that I think has been kind of most interesting over the last year has been how kind of the consumption model of public cloud, API driven, self service, capabilities operated for you how that consumption model is starting to spread because I think one of the challenges with hybrid and one of the challenges as customers are looking at these, more mission critical data centric kind of workloads was well, I can't always move that application to the public cloud data center or I need that application to live out on the network, closer to my end users. So, you know, out where data is being generated, maybe in an IOT context and when you had those requirements you had to kind of switch operating models. You, you had to kind of move away from a public cloud service consumption model to a software deployment model. And we have a common platform and things like open shift that can run everywhere but the missing piece was how do I consume everything as a service everywhere? And so recently we launched this thing called IBM been satellite, which we've been working with Octavian and his team on, on how we can actually extend the public cloud experience back into the data center, out to the edge and allow people to kind of mix both location flexibility with public cloud consumption. And when you do that, you of course running a much more diverse infrastructure environment. You have to integrate with different storage environments and you wind up with like multi-tiered applications you know, some stuff on the edge and some stuff in the core. And so data replication and data management start to become really interesting because you're kind of distributing your workloads across this complex environment. >> Here we've seen that relationship between compute and storage change a lot over the past decade as the evolution goes. Octavian, I got to ask you this is critical path for companies. They want the storage ready infrastructure. You guys have been doing that for many decades pardon me with IBM, for sure. But now they're all getting Hybrid Cloud big time and it's not, it's attributed computing. It's what it is. It's the operating model. When someone asks you guys what your capabilities are how do you answer that in today's world? Because you have storage as well known. You got a great product people know that. But what is NetApp's capabilities? When I say I'm going all in and Hybrid Cloud complete changeover. >> So what we have been doing is basically rewriting a lot of our software with a few design points in mind. The software-defined has been definitely one of the key design points. The second is the Hybrid Cloud in the containerization of our operating systems. So they can run both in traditional environments as well as in the cloud. I think the last thing that we wanted to do it's enabled the speed of scale. And that has been by building, you know intrinsically in the product, both support or in also using Kubernetes as an infrastructure to achieve that agility, that scale. >> So how about this data fabric vision? Because to me, this is comes up all the time in my conversations with practitioners the number one problem at their, and problem that they're to solve in the conversation tends to I hear what was that control plane Kubernetes, horizontally scalable this all points to data being available., So how do you create that availability? What is data fabric mean? What does all this mean in a hybrid context? >> Well if you think about it, data fabric it's a Hybrid Cloud concept, right? This is about enabling data governance, data, mobility data security in an environment where some of the applications were run on premises or at the edge or the smart edge and many of the, perhaps data links and analytics, and services, rich services will be in a central locations or many or perhaps some large know data centers. So you need to have, the type of capabilities data services to enable that mobility that governance, that security across this continuum that spans the edge, the core and the cloud. >> Jason, you mentioned satellite before Cloud Satellite. Could you go into more detail on that? I know it's kind of a new product, what is that about and tell me what's the benefits and why is it exist and what problems does it solve? >> Yeah, so in the most simple terms, Cloud Satellite is the capability to extend IBM's, public cloud into on-prem infrastructure at the edge or in a multicloud context to other public cloud infrastructures. And so you can consume all the services in the public cloud that you need to to build your application, OpenShift as a service database, as DevTools, AI capabilities instead of being limited to only being able to consume those services in IBM's re you know, cloud regions you can now add your private data center or add your Metro provider, or add your AWS or Azure accounts and now consume those services consistently across all those environments. And that really allows you to kind of combine the benefits of public cloud with kind of location independence you see in hybrid and lets us solve new problems. Like, you know, it's really interesting. We're seeing like AI and data being a primary driver. You know I need my application to live in a certain country or to live next to my mainframe or to live like, in a Metro because all of my, I'm doing like video analytics on a bunch of cameras and I'm not going to stream all that data back to halfway across the country to some cloud region. And so it lets you extend out in that way. And when you do that, of course, you now move the cloud into a more diverse infrastructure environment. And so like we've been working with NetApp on how do we then expose NetApp storage into this environment when I'm running in the data center or I'm running at the edge and I need to store that data replicate the data, secure it. Well, how do I kind of plug those two things together? I think John, at the beginning you kind of alluded to this idea of, things are becoming more application centric, right? And we're trying to run a IT architecture that's more centered around the application. Well, by combining clouds knowledge of kind of where everything's running with that common platform like OpenShift with Kubernetes aware of data fabric and storage layer, you really can achieve that. You can have an application centric kind of management that spans those environments. >> Yeah, I'm want to come back to that whole impact on IT because this has come up as a major theme here. Think at the it transformation is going to be more about cloud scale, but I want to get to Octavian on the satellite on NetApp's role and how you compliment that. How do you guys fit in? He just mentioned that you guys are playing with Cloud Satellite. Obviously this looks like an operating model. How does NetApp fit in. >> Simply put we extend and enable the capabilities that IBM satellite platform provides. I think Jason referred to the storage aspects and you know what we are doing it's enabling not only storage but rich data services around new theory based on temperature, or replicated snapshots or capabilities around, you know, caching, high availability, encryption and so forth. So we believe that our technology integrate very well with red hat openShift and the Kubernetes aspect enable the application mobility in that translation of really distributed computing at scale, from the traditional data center to the edge and to the massive Ops that IBM is building. >> You know, I got to say, but watching you guys work together for many decades now and covering you with theCUBE for the past 10 years or 11 years now been a great partnership. I got to say one thing, that's obvious to me and our team and mainly the world is now you've got a new CEO over at IBM you have a Cloud Focus that's on unwavering. Arvind loves the cloud we all know that. Ecosystems are changing without, you already had a big ecosystem and partnerships. Now it seems to be moving to a level where you got to have that ecosystem really thrive in the cloud. So I guess we'll use the last couple of minutes. If you guys don't mind explaining how the IBM NetApp relationship in the new context of this new partnership new ecosystem or a new kind of world helps customers and how you guys are working together. >> Yeah, I mean, I could start, I mean I think you're right, that cloud is all about platforms and about kind of the overall environment people operate in and the ecosystem is really critical. And I think things like satellite have given us new ways to work together. I mean, IBM and NetApp, as we said I've been working together for a long time. We rely on them all in our public cloud, for example, in our storage tiers. But with the kind of idea of distributed cloud in the boundaries of public cloud spreading to all of these new environments, those were just new places where we can build really interesting valuable integrations for our clients so that they can deal with data, deal with these more complex apps, in all the places that they exist. So I think it's been actually really exciting to kind of leverage that opportunity to find, new ways to work together and deliver solutions for our clients. >> Octavian. >> I will say that data is the ecosystem and we all know that there's more data right now being created outside of the traditional data center be it in the cloud or at the edge. So our mission is to enable that, Hybrid Cloud or data mobility and enabled persistence rich data, storage services, whatever data is being created. I think IBM's new satellite platform, comes in and broadens the aperture of people being able to consume IBM's services at the edge and or a remote office and I think that's very exciting. >> You guys are both experts and solely season executives to DevOps, DevSecOps, DataOps, whatever you want to call data's here, ecosystems. Guys thanks for coming on theCUBE Really appreciate the insight. >> Thank you. >> Thank you. >> Okay, IBM Think CUBE coverage. I'm John Furrier, your host. Thanks for watching. (upbeat music) (tranquil music)

>>from around the globe. It's the cube with >>Digital coverage of IBM think 2021 brought to you by IBM. Welcome back to the cubes coverage of IBM Think 2021 virtual were not yet in real life. We're doing another remote interviews with two great guests cube alumni of course, I'm john for your host of the cube. We've got Jason McGee, IBM fellow VP and CTO of IBM cloud platform and octavian Tennessee. Senior Vice president Hybrid Cloud Engineering at Netapp. Both cube alumni. It's great to see you both. Thanks for coming on. Thank >>you. Great to be here. Thanks for having us. >>So we were just talking before we came on camera that you know what it feels like. We've had this conversation, you know, a long time ago we have Hybrid cloud has been on a trajectory for both of you guys many times on the cube. So now it's mainstream, it's here in the real world, everyone gets it. It's not, there's no real debate now. Multi cloud, that's that. People are debating that. Which means that's right around the corner. So Hybrid cloud is here and now, um, Jason this is really the focus and this is also brings together Netapp in your partnership and talk about the relationship first with hybrid cloud. >>Yeah, I mean, you know, look, we've talked to a number of times together I think in the industry, uh, maybe, maybe a few years ago people were debating whether Hybrid cloud was a real thing. We don't have that conversation anymore. I think, um, you know, enterprises today, especially maybe in the face of Covid and kind of how we work differently now realize that their cloud journey is going to be a mix of on prem and off premise systems. Probably going to be a mix of multiple public cloud providers, um, and what they're looking for now is how do I do that and how do I manage that hybrid environment? How do I have a consistent platform across the different environments I want to operate in. Um, and then how do I get more and more of my work into those environments? And it's been interesting. I think the first, the first waves of cloud, we're infrastructure centric and externally application focused, they were easier things. And now we're moving into more mission critical, more state fel more data oriented workloads. And that brings with it new challenges on where applications run and and how we leverage the club >>Octavia. You guys had a great relationship with IBM over the years, uh, data centric company that it has always been great engineering team. You're on the cloud. Hybrid cloud engineering. What's the current status of the relationship? Give us an update on how the it's vectoring into the hybrid clouds this year? Senior Vice President. Hybrid cloud engineering. >>Well, so first of all, I want to recognize 20 years of a successful partnership with IBM I think uh that happened. IBM have been companies that have embraced digital transformation and technology trends to enable that digital transformation for our customers. And we've been very successful. I think there is a very strong um joint hydrochloric value proposition for customers. Netapp storage and data services complement what IBM does in terms of products and solutions, both for on premise deployments in the cloud. I think together we can build more complete solutions solutions that span data mobility to the governance for the new workloads that Jason has talked about. >>And how are some of the customer challenges that you're seeing? Obviously software defined networking, software defined storage, uh, deVOps has now turned into Deb's sec ops. So you have now that program ability requirement with four dynamic applications, application driven infrastructure, all these buzzwords point to one thing the infrastructure has to be resilient and respond to the applications. >>Yeah, I would say uh infrastructure, you know, will continue to be uh you know, top of mind for everybody whether they're building a private uh you know, cloud or whether there um you know, trying to leverage, you know, something like IBM cloud, I think people want to consume, you know, infrastructure is an A P I I think they want simplicity, you know, security, I I think they want to manage their cost, you know very well. I think we're very proud to be partnering with IBM cloud to build such capabilities. >>Jason what's how are you guys help on some of these customers as they look at new things and sometimes retrofitting and re factoring previous stuff don't transforming but also innovating at the same time as a lot of that going on. What are you guys doing to help with the Hybrid challenges? >>Yeah, I mean, you know, there's a lot of dimensions of that problem, but the one that that I think has been kind of most interesting over the last year has been how um kind of the consumption model of public cloud, you know, api driven self service capabilities operated for you, how that consumption model is starting to spread because I think one of the challenges with hybrid and one of the challenges as customers are looking at these more mission critical data centric kind of workloads was well, I can't always move that applications of public cloud data center or I need that application to live out on the network closer to my end users out where data is being generated maybe in an IOT context. And when you had those requirements, you had to kind of switch operating models, you had to kind of move away from a public cloud service consumption model to a software deployment model. And you know, we have a common platform and things like open shift that can run everywhere. But the missing piece was how do I consume everything as a service everywhere. And so recently we launched this thing called have been brought satellite, which we've been working with the T V. And his team on on how we can actually extend the public cloud experience back into the data center out to the edge and allow people to kind of mix both locational flexibility with public consumption. When you do that, you of course running a much more diverse infrastructure environment. You have to integrate with different storage environments and you wind up with multi tier applications, you know, some stuff on the edge and some stuff in the core. And so data replication and data management start to become really interesting because you're kind of distributing your workloads across this. No complex environment. >>We've seen that relationship between compute and storage change a lot over the past decade. As the evolution goes okay, I gotta ask you this is critical path for companies. They want the storage ready infrastructure. You guys have been doing that for many, many decades party with IBM for sure. But now they're all getting a hybrid cloud big time and it's not it's attributed computing is what it is. It's an operating model. When someone asked you guys what your capabilities are, how do you answer that? In today's world? Because you have storage is well known. You got a great product, people know that, but what is net apps capabilities? When I say I'm going all in and hybrid cloud, complete changeover. >>So what we have been doing is basically rewriting a lot of our software with a few design points in mind. Um the software defined has been definitely, you know, one of the key design points. The second is the um, the hybrid cloud and the internalization of our operating system so they can run both in traditional environments as well as in the cloud. I think the last thing that we wanted to do, it's enabled the speed of scale and that has been by building um, you know, intrinsically in the, in the, in the product, both support or, and also using kubernetes as an infrastructure to achieve that agility that that scale >>talk about this data fabric vision because to me that comes up all the time in my conversations with practitioners. The number one problem that there is a problem that we're solving to solve and the conversation tends to I here was a control playing kubernetes horizontally scalable. This all points to data being available. So how do you create that availability? What does data fabric mean? What does all this mean in hybrid context? >>Well, if you if you think about it data fabric, it's a hybrid cloud, you know, concept, right. This is about enabling data governance, data mobility, data security in an environment where some of the applications will run on premises or at the edge of the smart edge and many of the, you know, perhaps data lakes and analytics, um, you know, and services rich services will be in a central locations or on many or perhaps some large, you know, data centers. So you need to have, you know, the type of, you know, capabilities, data services, you know, to enable that mobility, that governments governance, that that security across this continuum that spans the edge the core and the cloud, >>Jason, you mentioned satellite before. Cloud satellite. Can you go into more detail on it? I know it's kind of a new product, uh what is that about? And tell me what's the benefits and why does it exist and what problems does it solve? >>Yeah. So so in the most simple terms, cloud satellite is the capability to extend iBMS public cloud into on prem infrastructure infrastructure at the edge or in a multi cloud context to other public cloud infrastructures. And so you can consume all the services in the public cloud that you need to to build your application of open shift as a service databases. Deb tools, aI capabilities. Instead of being limited to only being able to consume those services in IBM's cloud regions, you can now add your private data center or add your metro provider or add your AWS or Azure account and now consume those services consistently across all those environments. Um and that really allows you to kind of combine the benefits of public ill with kind of location independence, you see in hybrid and let's solve new problems like, you know, it's really interesting, we're seeing like a I and data being a primary driver. I need my application to live in a certain country or to live next to my mainframe or to live like you know in a metro because all of my, I'm doing like video analytics on a bunch of cameras and I'm not going to stream all that data back to halfway across the country to some cloud region and so lets you extend out in that way and when you do that of course you now move the cloud into a more diverse infrastructure environment. And so like we've been working with Netapp on, how do we then expose um Netapp storage into this environment when I'm running in the data center where I'm running at the edge and I need to store that data replicate the data, secure it. Well how do I kind of plug those two things together? I think john at the beginning you kind of alluded to this idea of you know, things are becoming more application centric, Right? And we're trying to run an I. T. Architecture that's more centered around the application well by combining um clouds, knowledge of kind of where everything is running with a common platform like open shift with a kubernetes aware data fabric in storage layer, you really can achieve that. You can have an application centric kind of management that spans those environments. >>Yeah, I want to come back to that whole impact on I. T. Because this has come up as a major theme here. Think that the I. T. Transformation is going to be more about cloud scale but I want to get octavian on the satellite on Netapp role and how you complement that. How do you guys fit in? He just mentioned that you guys are playing with clouds satellite, obviously this was like an operating model, How does that fit in? >>Um simply put we extend and enable the capabilities that uh IBM satellite uh you know, platform provides, I think Jason referred to the storage aspects um and you know what we are doing, it's enabling not only storage but rich data services around tearing based on temperature or you know, replicated snapshots or you know, capabilities around, you know cashing, you know, high availability encryption and and so forth. So we believe that our our technology integrates very well with red hat open shift um and uh the kubernetes aspect enable the application mobility and in that translation of really distributed computing at scale, you know from you know from the traditional data center um to the edge and uh you know to the massive hubs that IBM is building, >>you know, I gotta say but watching you guys worked together for many decades now and and covering you with the queue for the past 10 years or 11 years now um been a great partnership. I gotta say one thing that's obviously too obvious to me and our team and mainly mainly the world is now you got a new Ceo over at IBM you have a cloud focus that's on unwavering Arvin loves the cloud. We all know that um ecosystems are changing with that. You have already had a big ecosystem and partnerships now it seems to be moving to a level where you gotta have that ecosystem really thrive in the cloud. So I guess we'll use the last couple of minutes if you guys don't mind explaining how the IBM Netapp relationship in the new context of this new partnership, new ecosystem or a new kind of world helps customers and how you guys are working together. >>Yeah, I mean I could start, I mean I think you're right that that cloud is all about platforms and about kind of the overall environment, people operating in the ecosystem is really critical and I think things like satellite have given us new ways to work together. I mean I'd be a minute up, as we said, I've been working together for a long time. We rely on them a lot in our public cloud, for example in our storage tiers but with with the kind of idea of distributed cloud and the boundaries of public cubs spreading to all these new environments. Those are just new places where we can build really interesting, valuable integrations for our clients so that they can deal with day to deal with these more complex apps, you know, in all the places that they exist. So I think it's gonna actually really exciting um to kind of leverage that opportunity to find new ways to work together and and uh and deliver solutions to our clients >>Octavia, >>I would say that data is the ecosystem and we all know that there is more data right now being created outside of the traditional data center, beat in the cloud or at the edge. Um so our mission is, you know, to enable that, you know, hybrid cloud or or that uh, you know, data mobility um and enable, you know, persistence rich data, you know, storage services, whatever data is being created. I think IBM's new satellite platform um you know, comes in and broadens the aperture of people being able to consume IBM services at the edge and or or the remote office. And I think that's very exciting. >>You guys are both experts and solely seasoned executives. Devops DEP sec ops, DEV data Ops whatever you wanna call, data's here. Ecosystems guys, thanks for coming on the key. Really appreciate the insight. >>Thank you. Thank >>you. Okay. IBM think cute coverage jOHN for your host. Thanks for watching. Mhm. Mhm. Mhm.

>> Announcer: From around the globe, it's theCUBE with digital coverage of IBM Think 2021, brought to you by IBM. >> Hi, welcome back to theCUBES coverage of IBM Think 2021 virtual. We're not yet in real life, we're doing another remote interviews with two great guests CUBI alumni. Of course, I'm John for your host of theCUBE. We got Jason MacGee, IBM fellow VP and CTO of IBM's cloud platform and Octavian Tanase senior vice president Hybrid Cloud Engineering at NetApp both CUBE alumni, it's great to see you both. Thanks for coming on theCUBE. >> Yeah, great to be here. >> Thanks for having us. >> So we were just talking before we came on camera that we it feels like we've had this conversation a long time ago we have. Hybrid cloud has been on a trajectory for both of you guys and many times on theCUBE. So now it's mainstream, it's here in the real world, everyone gets it, there's no real debate, now multicloud, people are debating that which means that's right around the corner. So hybrid cloud is here now, Jason this is really the focus and this is also brings together the NetApp in your partnership and talk about the relationship first with hybrid cloud. >> Yeah, I mean, look we've talked a number of times together I think in the industry. Maybe a few years ago people were debating whether hybrid cloud was a real thing, we don't have that conversation anymore. I think enterprises today, especially maybe in the face of COVID and kind of how we work differently now realize that their cloud journey is going to be a mix of on-prem and off-prem systems probably going to be a mix of multiple public cloud providers. And what they're looking for now is how do I do that? And how do I manage that hybrid environment? How do I have a consistent platform across the different environments I want to operate in? And then how do I get more and more of my workload into those environments? And it's been interesting. I think the first waves of cloud where infrastructure centric and externally application focused, they were easier things, and now we're moving into more mission critical more stateful, more data oriented workloads, and that brings with it new challenges on where applications run and how we leverage the club. >> Octavian, you guys had a great relationship with IBM over the years data centric company, NetApp has always been great engineering team, you're on the hybrid cloud engineering. What's the current status of the relationship, give us an update on how the it's vectoring into the hybrid cloud since you're senior vice president of Hybrid Cloud Engineering. >> Well, so first of all, I want to recognize 20 years of a successful partnership with IBM. I think NetApp have been IBM have been companies that have embraced digital transformation and technology trends to enable that digital transformation for our customers, and we've been very successful. I think there is a very strong joint hybrid cloud value proposition for customers on NetApp storage and data services compliment. What IBM does in terms of products and solutions both for on-premise deployments in the cloud. I think together we can build more complete solutions that span data mobility, data governance for the new workrooms that Jason has talked about. >> And how has some of the customer challenges that you're seeing obviously software defined networking software defined storage, DevOps is now turned into DevSecOps. So you have now that programmability requirement with for dynamic applications, application driven infrastructure, all these buzz words point to one thing. The infrastructure has to be resilient and respond to the applications. >> I would say infrastructure will continue to be a top of mind for everybody, whether they're building a private cloud or whether they're trying to leverage something like IBM Cloud. I think people want to consume infrastructure as an API, I think they want a simplicity, security, I think they want to manage their costs very well. I think we're very proud to be partnering with IBM Cloud to build such capabilities. >> Jason how are you guys helping some of these customers as they look at new things and sometimes retrofitting and refactoring previous stuff during transforming but also innovating at the same time. There's a lot of that going on. What are you guys doing to help with the hybrid challenges? >> Yeah, I mean there's a lot of dimensions to that problem but the one that I think has been kind of most interesting over the last year has been how kind of the consumption model public cloud, API driven self service, capabilities operated for you. How that consumption model is starting to spread. Because I think one of the challenges with hybrid and one of the challenges as customers are looking at these more mission critical data centric kind of workloads was well, I can't always move that application to the public cloud data center or I need that application to live out on the network closer to my end users, so out where data is being generated maybe in an IoT context. And when you had those requirements you had to kind of switch operating models, you had to kind of move away from a public cloud service consumption model to a software deployment model, and we have a common platform and things like OpenShift that can run everywhere but the missing piece was how do I consume everything as a service everywhere? And so recently we launched this thing called IBM Cloud Satellite which we've been working with Octavian and his team on how we can actually extend the public cloud experience back into the data center out to the edge and allow people to kind of mix both location flexibility with public cloud consumption. And when you do that, you of course running a much more diverse infrastructure environment, you have to integrate with different storage environments and you wind up with like multi-tiered applications, some stuff on the edge and some stuff in the core. And so data replication and data management start to become really interesting because you're kind of distributing your workloads across this more complex environment. >> We've seen that relationship between compute and storage change a lot over the past decade as the evolution goes. Octavian, I got to ask you this is critical path for companies, they want the storage ready infrastructure, you guys have been doing that for many decades partnering with IBM for sure but now they're all getting hybrid cloud big time and it's attributed computing is what it is, it's the operating model. When someone asks you guys what your capabilities are, how do you answer that in today's world? Because you have storage as well knowing you got a great product people know that, but what is NetApp's capabilities when I say I'm going all in a hybrid cloud complete changeover. >> So what we have been doing is basically rewriting a lot of our software with a few design points in mind. The software defined has been definitely one of the key design points, the second is the hybrid cloud in the containerization of our operating systems so they can run both in traditional environments as well as in the cloud. I think the last thing that we wanted to do it's enabled the speed of scale and that has been by building intrinsically in the product both support or in also using Kubernetes as an infrastructure to achieve that agility that scale. >> So how about this data fabric vision? Because to me, this is comes up all the time in my conversations with practitioners, the number one problem that they're solving to solve in the conversation tends to, I hear words like control plane, Kubernetes, horizontally scalable, this all points to data being available. So how do you create that availability? What does data fabric mean? What does all this mean in a hybrid context? >> Well, if you think about it data fabric it's a hybrid cloud concept, this is about enabling data governance, data mobility, data security in an environment where some of the applications were run on premises or at the edge or the smart edge and many of the perhaps data lakes and analytics, and services, rich services will be in a central locations or on many or perhaps some large data centers. So you need to have the type of capabilities data services to enable that mobility that governance that security across this continuum that spans the edge the core and the cloud. >> Jason, you mentioned satellite before cloud satellite. Could you go into more detail on that? I know it's kind of a new product, what is that about, and tell me what's the benefits and why is it exist and what problems does it solve? >> Yeah, so in the most simple terms, cloud satellite is the capability to extend IBM's public cloud into on-prem infrastructure at the edge or in a multicloud context to other public cloud infrastructures. And so you can consume all the services in the public cloud that you need to to build their application, OpenShift as a service database, as DevTools, AI capabilities instead of being limited to only being able to consume those services in IBM's cloud regions you can now add your private data center or add your Metro provider or add your AWS or Azure accounts and now consume those services consistently across all those environments. And that really allows you to kind of combine the benefits of public cloud with the kind of location independence you see in hybrid and lets us solve new problems. It's really interesting we're seeing like AI and data being a primary driver. I need my application to live in a certain country or to live next to my mainframe or to live like in a Metro because all of my, I'm doing like video analytics on a bunch of cameras and I'm not going to stream all that data back to halfway across the country to some cloud region now. And so it lets you extend out in that way. And when you do that, of course, you now move the cloud into a more diverse infrastructure environment. And so like we've been working with NetApp on how do we then expose NetApp storage into this environment when I'm running in the data center or I'm running at the edge and I need to store that data replicate the data, secure it. Well, how do I kind of plug those two things together? I think John, at the beginning you kind of alluded to this idea of things are becoming more application centric, right? And we're trying to run IT architecture that's more centered around the application. Well, by combining clouds knowledge of kind of where everything's running with that common platform like OpenShift with a Kubernetes aware data fabric and storage layer, you really can achieve that. You can have an application centric kind of management that spans those environments. >> Yeah, I want to come back to that whole impact on IT because this has come up as a major theme here. Think that the IT transformation is going to be more about cloud scale, but I want to get to Octavian on the satellite on NetApp's role and how you compliment that, how do you guys fit in? He just mentioned that you guys are playing with cloud satellite, obviously this was like an operating model. How does that fit in? >> Simply we extend and enable the capabilities that IBM satellite platform provides. I think Jason referred to the storage aspects and what we are doing it's enabling not only storage but rich data services around peering based on temperature or replicated snapshots or capabilities around caching, high availability, encryption and so forth. So we believe that our technology integrate very well with Red Hat OpenShift and the Kubernetes aspect enable the application mobility and in that translation of really distributed computing at scale from the traditional data center to the edge and to the massive hubs that IBM is building. >> You know, I got to say but watching you guys work together for many decades now and covering you with theCUBE for the past 10 years or 11 years now been a great partnership. I got to say one thing that's obviously too obvious to me and our team and mainly the world is now you've got a new CEO over at IBM, you have a cloud focus that's on unwavering, Octavian loves the cloud we all know that. Ecosystems are changing, IBM already had a big ecosystem and partnerships. Now it seems to be moving to a level where you got to have that ecosystem really thrive in the cloud, so I guess we'll use the last couple of minutes if you guys don't mind explaining how the IBM NetApp relationship in the new context of this new partnership a new ecosystem or a new kind of world helps customers and how you guys are working together? >> Yeah, I mean I think you're right that cloud is all about platforms and about kind of the overall environment people operate in and the ecosystem is really critical. And I think things like satellite have given us new ways to work together. I mean, IBM and NetApp, as we set up, been working together for a long time we rely on the MoD in our public cloud, for example, in our storage tiers, but with the kind of idea of distributed cloud and the boundaries of public cloud spreading to all these new environments those are just new places where we can build really interesting valuable integrations for our clients so that they can deal with data, deal with these more complex apps in all the places that they exist. So I think it's been actually really exciting to kind of leverage that opportunity to find new ways to work together and deliver solutions for our clients. >> Octavian. >> I will say that data is the ecosystem and we all know that there's more data right now being created outside of the traditional data center be it in the cloud or at the edge. So our mission is to enable that hybrid cloud or that data mobility and enable know persistence rich data storage services, whatever data is being created. I think IBM's new satellite platform comes in and broadens the aperture of people being able to consume IBM's services at the edge and or remote office and I think that's very exciting. >> You guys are both experts and solely seasoned executives to DevOps, DevSecOps, DevDataOps, what are we going to call data's here ecosystems. Guys, thanks for coming on the queue, really appreciate the insight. >> Thank you. >> Thank you. >> Okay, IBM, Think CUBE coverage, I'm John for your host. Thanks for watching. (upbeat music)

>> From Sunnyvale, California, in the heart of Silicon Valley, it's theCUBE, covering Accelerate Your Journey to AI. Brought to you by NetApp. >> Hi, I'm Peter Burris, with theCUBE and Wikibon, and we're here at the NetApp Data Visionary Center today to talk about NetApp, NVIDIA, AI, and data. We're being joined by two great guests. Jim McHugh is the Vice President and General Manager of Deep Learning Systems at NVIDIA, and Octavian Tanase is the Senior Vice President of ONTAP at NetApp. Gentlemen, welcome to theCUBE. >> Thanks for having me. >> So Jim, I want to start with you. NVIDIA's been all over the place regarding AI right now. You've had a lot of conversations with customers. What is the state of those conversations today? >> Well, I mean, it really depends on the industry that the customer's in. So, AI at at its core, is really a horizontal technology, right? It's when when we engage with a customer and their data and their vertical domain knowledge that it becomes very specialized from there. So you're seeing a lot of acceleration where there's been a lot of data, right? So it's not any secret that you're seeing a lot around autonomous driving vehicles and the activity going there. Health care, right? Because when you can marry the technology of AI with the years, and years, and years of medical research that's going on out there, incredible things come out, right? We've seen some things around looking at cancer cells, we're looking at your retina being sort of the gateway to so many health indications. We can tell you whether you have everything from Dengue fever, to malaria, to whether you're susceptible to have hypertension. All of these kind of things that we're finding, that data is actually letting us to be superhuman in our knowledge about what we're trying to accomplish. Now the exciting thing is, if you grew up like we did, in the IT industry, is you're seeing it go into mainstream companies, so you're seeing it in financial services, where they for years were, quants were very specialized, and they were writing their own apps, and now they figured out, hey, look, I could broaden this out. You're seeing it in cybersecurity, right? For years, if you wanted to check malware, what did we do? We looked up the definition in a database and said, okay, yeah, that's malware, stop it, right? But now, they're learning the characteristics of malware. They're studying the patterns of it, and that's kind of what it is. Go industry by industry, and tell me if there's enough data to show a pattern, and AI will come in and change it. >> Enough data to show a pattern? Well, that kind of introduces NetApp to the equation. A company that's been, especially more recently, very focused on the relationship between data and business value. Octavian, what has NetApp seen from customers? >> Well, we know a little bit about data. We've been the stewards of that data in the enterprise for more than 25 years, and AI comes up in every single customer conversation. They're looking to leverage AI in their digital transformation, so we see this desire to extract more value out of the data, and make better decisions, faster decisions in every sector of the industry. So, it's ubiquitous, and we are uniquely positioned to enable customers to do their data management wherever data is being created. Whether the data is created at the edge, in the traditional data center, what we call the core, or in the cloud, we enable this seamless data management via the data fabric architecture and vision. >> So, data fabric, data management, the ability to extract that, turn it into patterns. Sounds like a good partnership, Jim? >> Yeah, no, we say, data's the new source code. Really, what AI is, we're changing the way software's written. Where, instead of having humans going in, do the feature engineering and feature sets that would be required, you're letting data dictate and guide you on what the features are going to be of software. >> So right now, we've got the GPU, Graphic Data Processing revolution, you guys driving that. We've got some real advances in how data fabric works. You have come together and created a partnership. Talk a little bit about that partnership. >> Well, when we started down this journey, and it began, really, in 2012 in AI, right? So when Alex Krizhevsky discovered how to create AlexNet, NVIDIA's been focused on how do we meet the needs of the data scientists every step of the way. So beginning started around making sure they had enough compute power to solve things that they couldn't solve before. Then we started focusing on what is the software that was required, right? So how do we get them the frameworks they need? How do we integrate that? How do we get more tuned, so they could get more and more performance? Our goal has always been, if we can make the data scientists more productive, we can actually help democratize AI. As it's starting to take hold, and get more deployments, obviously we need the data. We need it to help them with the data ingest, and then deployments are starting to scale out to the point where we need to make this easy, right? We need to take the headaches of trying to figure out what are all the configurations between our product lines, but also the networking product lines, as well. We have to bring that whole, holistic picture, and do it from there. So our goal, and what we're seeing, is not only we've made the data scientists more productive, but if we can help the guys that have to do the equipment for him more productive as well, the data scientists, she and he, can get back to doing what their real core work is. They can add value, and really change a lot of the things that are going on in our lives. >> So fast, flexibility, simpler to use. Does that, kind of, capture some of the, summarize some of the strategies that NetApp has for Artificial Intelligence workloads? >> Absolutely, I think simplicity, it's one of the key attributes, because the audience for some of the infrastructure that we're deploying together, it's a data scientist, and he wants to adopt that solution with confidence, and it has to be simple to deploy. He doesn't have to think about the infrastructure. It's also important to have an integrated approach, because, again, a lot of the data will be created in the future at the core, or at edge more than in the core, and more in the cloud than in traditional data center. So that seamless data management across the edge, to the core, to the cloud, it's also important. And scalability, it's also important, because customers who look to start, perhaps, simple, with a small deployment, and have that ability to seamlessly scale. Currently, the performance of the solution that we just announced, basically beats the competition by a 4x, in terms of the performance and capability. >> So as we think about where we're going, this is a crucial partnership for both companies, and it's part of a broader ecosystem that NVIDIA's building out. How does the NetApp partnership fit into that broader ecosystem? >> Well, starting with our relationship, when the announcement we made, it should be no secret that we engaged our channel partners, right? 'Cause they are that last mile. They are those trusted advisors, a lot of times, of our customers, and going in, and we want them to add this to their portfolio, take it out to 'em, and I think we've had resounding feedback, so far, that this is something that they can definitely take, and drive out. On top of that, NVIDIA is focused on, again, this new way of writing software, right? The software that leverages the data to do the things, and so we have an ecosystem that's built around our inception program, which are thousan%ds of startups. If you add to that the thousands of startups that are coming through Sand Hill, and the investment community, that are based around NVIDIA compute, as well, all of these guys are standardizing saying, hey we need to leverage this new model. We need to go as quickly as possible, and what we've pulled together, together, is the ability for them to do that. So whether they want to do the data center, or whether they want to go with one of our joint cloud providers and do it through their service, as well. >> So a great partnership that's capable of creating a great horizontal platform. It's that last mile that does the specialization. Have I got that right? >> You had the last mile helping reach the customers who are the specialization. The customers, and their data, and their vertical domain expertise, and what the data scientists that they have bring to it. Look, they're creating the magic. We're giving them the tools to make sure they can create that magic as easy as possible. >> That's great, so one of the things, Octavian, that Jim mentioned, was industries that are able to generate significant value out of data are moving first. One of the more important industries is IT Operations, because we have a lot of devices, we're generating a lot of data. How is NetApp going to use AI in your product set to drive further levels of productivity, from a simplicity standpoint, so customers can, in fact, spend more time on creating value? >> So interestingly enough, we've been users, or practitioners, of AI for quite a while. I don't know if a lot of people in the audience know, we have a predictive analytics system called Active IQ, which is an implementation of AI in the enterprise. We take data from more than 300 thousand assets that we have deployed in the field, more than 70 billion data points every day, and we correlate that together. We put them in a data lake. We train a cluster, and we enable our customers to drive value in best practices from the data that we collect from the broader set of deployments that we have in the field, so this is something that we are sharing with our customers, in terms of blueprint, and we're looking to drive the ubiquity in the type of solutions that we enable customers to build on top of our joint infrastructure. >> Excellent, Jim McHugh, NVIDIA, Octavian Tanase, NetApp. Great partnership represented right here on theCUBE. Thanks very much for being on theCUBE tonight. >> All right. >> Thank you. >> Thank you for having us. (electronic music)

>> Announcer: Live from San Jose it's The Cube presenting Big Data, Silicon Valley brought to you by SiliconANGLE Media and its ecosystem partners. >> Good morning. Welcome to The Cube. We are on day two of our coverage our event Big Data SV. I'm Lisa Martin with my cohost Dave Vellante. We're down the street from the Strata Data Conference. This is The Cube's tenth big data event and we had a great day yesterday learning a lot from myriad guests on very different nuances of big data journey where things are going. We're excited to welcome back to The Cube an alumni, Octavian Tanase, the Senior Vice President of Data ONTAP fron Net App. Octavian, welcome back to The Cube. >> Glad to be here. >> So you've been at the Strata Data Conference for the last couple of days. From a big data perspective, what are some of the things that you're hearing, in terms of from a customer's perspective on what's working, what challenges, opportunities? I'm very excited to be here and learn about the innovation of our partners in the industry and share with our partners and our customers what we're doing to enable them to drive more value out of that data. The reality is that data has become the 21st Century gold or oil that powers the business and everybody's looking to apply new techniques, a lot of times machine learning, deep learning, to draw more value of the data, make better decisions and compete in the marketplace. Octavian, you've been at NetApp now eight years and I've been watching NetApp, as we were talking about offline, for decades and I've seen the ebb and flow and this company has transformed many, many times. The latest, obviously cloud came in, flash came into play and then you're also going through a major transition in the customer based to clustered ONTAP. You seemed to negotiate that. NetApp is back, thriving, stock's up. What's happening at NetApp? What's the culture like these days? Give us the update. >> I think we've been very fortunate to have a CEO like George Kurian, who has been really focused on helping us do basically fewer things better, really focus on our core business, simplify our operations and continue to innovate and this is probably the area that I'm most excited about. It's always good to make sure that you accelerate the business, make it simpler for your customers and your partners to do business with you, but what you have to do is innovate. We are a product company. We are passionate about innovation. I believe that we are innovating with more pace than many of the startups in the space so that's probably the most exciting thing that has been part of our transformation. >> So let's talk about big data. Back in the day if you had a big data problem you would buy a big Unix box, maybe buy some Oracle licenses, try to put all your data into that box and that became your data warehouse. The brilliance of Hadoop was hey we can leave the data where it is. There's too much data to put into the box so we're going to bring five megabytes to code to a petabyte of data. And the other piece of it is CFOs loved it, because we're going to reduce the cost of our expensive data warehouse and we're going to buy off the shelf components: white box, servers and off the shelf disk drives. We're going to put that together and life will be good. Well as things matured, the old client-server days, it got very expensive, you needed enterprise grade. So where does NetApp fit into that equation, because originally big storage companies like NetApp, they weren't part of the equation? Has that changed? >> Absolutely. One of the things that has enabled that transformation, that change is we made a deliberate decision to focus on software defined and making sure that the ONTAP operating system is available wherever data is being created: on the edge in an IoT device, in the traditional data center or in the cloud. So we are in the unique position to enable analytics, big data, wherever those applications reside. One of the things that we've recently done is we've partnered with IDC and what the study, what the analysis has shown is that deploying in analytics, a Hadoop or NoSQL type of solution on top of NetApp is half the cost of DAS. So when you consider the cost of servers, the licenses that you're going to have to pay for, these commercial implementations of Hadoop as well as the storage and the data infrastructure, you are much better off choosing NetApp than a white box type of solution. >> Let's unpack that a little bit, because if I infer correctly from what you said normally you would say the operational costs are going to be dramatically lower, it's easier to manage a professional system like a NetApp ONTAP, it's integrated, great software, but am I hearing you correctly, you're saying the acquisition costs are actually less than if I'm buying white box? A lot of people are going to be skeptical about that, say Octavian no way, it's cheaper to buy white box stuff. Defend that statement. >> Absolutely. If you're looking at the whole solution that includes the server and the storage, what NetApp enables you to do if you're running the solution on top of ONTAP you reduce the need for so many servers. If you reduce that number you also reduce the licensing cost. Moreover, if you actually look at the core value proposition of the storage layer there, DAS typically makes three copies of the data. We don't. We are very greedy and we're making sure that you're using shared storage and we are applying a bunch of storage efficiency techniques to further compress, compact that data for world class storage efficiency. >> So cost efficiency is obviously a great benefit for any company when they're especially evolving, from a digital perspective. What are some of the business level benefits? You mentioned speed a minute ago. What is Data ONTAP and even ONTAP in the cloud enabling your enterprise customers to achieve at the business level, maybe from faster time to market, identifying with machine learning and AI new products? Give me an example of maybe a customer that you think really articulates the value that ONTAP in the cloud can deliver. >> One of the things that's really important is to have your data management capability, whatever the data is being produced so ONTAP being consumed either as a VM or a service ... I don't know if you've seen some of the partnerships that we have with AWS and Azure. We're able to offer the same rich data management capabilities, not only the traditional data center, but in the cloud. What that really enables customers to do is to simplify and have the same operating system, the same data management platform for the both the second platform traditional applications as well as for the third platform applications. I've seen a company like Adobe be very successful in deploying their infrastructure, their services not only on prem in their traditional data center, but using ONTAP Cloud. So we have more than about 1,500 customers right now that have adopted ONTAP in the AWS cloud. >> What are you seeing in terms of the adoption of flash and I'm particularly interested in the intersection of flash adoption and the developer angle, because we've seen, in certain instances, certain organizations are able to share data off of flash much more efficiently that you would be, for instance, of a spinning disk? Have you seen a developer impact in your customer base? >> Absolutely I think most of customers initially have adopted flash, because of high throughput and low latency. I think over time customers really understood and identified with the overall value proposition in cost of ownership in flash that it enables them to consolidate multiple workloads in a smaller footprint. So that enables you to then reduce the cost to operate that infrastructure and it really gives you a range of applications that you can deploy that you were never able to do that. Everybody's looking to do in place, in line analytics that now are possible, because of this fast media. Folks are looking to accelerate old applications in which they cannot invest anymore, but they just want to run faster. Flash also tends to be more reliable than traditional storage, so customers definitely appreciate that fewer things could go wrong so overall the value proposition of flash, it's all encompassing and we believe that in the near future flash will be the defacto standard in everybody's data center, whether it's on prem or in the cloud. >> How about backup and recovery in big data? We obviously, in the enterprise, very concerned about data protection. What's similar in big data? What's different and what's NetApp's angle on that? >> I think data protection and data security will never stop being important to our customers. Security's top of mind for everybody in the industry and it's a source of resume changing events, if you would, and they're typically not promotions. So we have invested a tremendous deal in certifications for HIPAA, for FIPS, we are enabling encryption, both at rest and in flight. We've done a lot of work to make sure that the encryption can happen in software layer, to make sure that we give the customers best storage class efficiency and what we're also leveraging is the innovation that ONTAP has done over many years to protect the data, replicate its snapshots, peering the data to the cloud. These are techniques that we're commonly using to reduce the cost of ownership, also protect the data the customers deploy. >> So security's still a hot topic and, like you said, it probably always will be, but it's a shared responsibility, right? So customers leveraging NetApps safe or on prem hybrid also using Azure or AWS, who's your target audience? If you're talking to the guys and gals that are still managing storage are you also having the CSO or the security guys come in, the gals, to understand we've got this appointment in Azure or AWS so we're going to bring in ONTAP to facilitate this? There's a shared responsibility of security. Who's at the table, from your perspective, in your customers that you need to help understand how they facilitate true security? >> It's definitely been a transformative event where more and more people in IQ organizations are involved in the decisions that are required to deploy the applications. There was a time when we would talk only to the storage admin. After a while we started talking to the application admin, the virtualization admin and now you're talking to the line of business who has that vested interest to make sure that they can harness the power of the data in their environment. So you have the CSO, you have the traditional infrastructure people, you have the app administration and you have the app owner, the business owner that are all at the table that are coming and looking to choose the best of breed solution for their data management. >> What are the conversations like with your CXO, executives? Everybody talks about digital transformation. It's kind of an overused term, but there's real substance when you actually peel the onion. What are you seeing as NetApp's role in effecting digital transformations within your customer base? >> I think we have a vision of how we can help enterprises take advantage of the digital transformation and adopt it. I think we have three tenants of that vision. Number one is we're helping customers harness the power of the cloud. Number two, we're looking to enable them to future proof their investments and build the next generation data center. And number three, nobody starts with a fresh slate so we're looking to help customers modernize their current infrastructure through storage. We have a lot of expertise in storage. We've helped, over time, customers time and again adopt disruptive technologies in nondisruptive ways. We're looking to adopt these technologies and trends on behalf of our customers and then help them use them in a seamless safe way. >> And continue their evolution to identify new revenue streams, new products, new opportunities and even probably give other lines of business access to this data that they need to understand is there value here, how can we harness it faster than our competitors, right? >> Absolutely. It's all about deriving value out of the data. I think earlier I called it the gold of the 21st Century. This is a trend that will continue. I believe there will be no enterprise or center that won't focus on using machine learning, deep learning, analytics to derive more value out of the data to find more customer touch points, to optimize their business to really compete in the marketplace. >> Data plus AI plus cloud economics are the new innovation drivers of the next 10, 20 years. >> Completely agree. >> Well Octavian thanks so much for spending time with us this morning sharing what's new at NetApp, some of the visions that you guys have and also some of the impact that you're making with customers. We look forward to having you back on the program in the near future. >> Thank you. Appreciate having the time. >> And for my cohost Dave Vellante I'm Lisa Martin. You're watching The Cube live on day two of coverage of our event, Big Data SV. We're at this really cool venue, Forager Tasting Room. Come down here, join us, get to hear all these great conversations. Stick around and we'll be right back with our next guest after a short break. (electronic music)

(upbeat music) >> Announcer: Live from San Franciso, it's theCUBE covering the Spark Summit 2017. Brought to you by Databricks. >> You are watching theCUBE at Spark Summit 2017 I'm David Goad here with my friend George Gilbert. How you doing, George? >> Good. >> All right, but the man of the hour is over to my left. I'd like to introduce a Databricks partner, and his name is Octavian Tanase, he's the SVP for Data ONTAP Software and Systems Group at NetApp. Octavian. >> Thank you for having us. >> All right well you have kind of an interesting background. We were chatting before, you started as an engineer, developer? >> Yeah, so I'm in an executive role right now but I have an interesting trajectory. Most people in a similar role come from a product management or sales background. I'm a former engineer and you know, somebody that has a passion for technology and now for customers and building interesting technologies. >> Okay, well if you have a passion for this technology then, I'd like to get your take on the market place a little bit. Tell us about the evolution of the mainstream and what you see changing. >> I think your data is the new currency of the 21st century. You have a desire and a thirst to get more out of your data. You have developers, you have analysts looking to build the next great application to mine your data for great business outcomes. NetApp as a data management company is very much interested in working with companies like Databricks and a bunch of hyperscalers to enable that type of solutions that either enable in place analytics or data lakes or you know, solutions that really enable developers and analysts to harness that part of the data. >> Mhmm. So ... Maybe walk us through what you've seen to date in terms of the mainstream use cases for big data and then tell us where you think they're going, but what walls need to be pushed back with the confection of technologies to get there. >> Originally what I've seen a lot of people investing in data lake technologies. Data lakes in a nutshell are massive containers that are simple to manage, scalable performant where you can aggregate a bunch of data sources and then you can run a map-produced type of workload to correlate that data, to harness that part of data, to draw conclusions. That was sort of the original track. Over time, I think there's a desire, given how dynamic and diverse that the data is, to build a lot of this analytics in-line, in real time. That's where companies like Databricks comes and that's where the cloud comes to enable both the agility as well as the type of real time behavior to getting those analytics. >> Now this is your first Spark Summit? >> Absolutely, happy to be here. >> Oh I know it's just the first day, but what have you learned so far? Any great questions from other participants? >> Well I think I see a lot of people innovating very fast. I see both established players paying attention, I see new companies looking to take advantage of this revolution that is happening, you know, around data and the data services and data analytics. >> Maybe tell us a little more what we were talking about before we started about how some customers who are very sensitive to their data want to keep it in their data centers or Equinix which still counts as pretty much theirs, but the compute is often the cloud somewhere. >> As you can imagine, we work with a lot of enterprise customers and one thing that I've learned in the last couple of years is that their thought process has evolved, you know, banks, large financial institutions. Two years ago, we're not even considering the cloud. And I see that now changing and I see them wanting to operate like a cloud provider, I see them want to take advantage of the flexibility and the agility of the cloud. I see them being more comfortable with the type of security capabilities that the cloud offers today. Security has been probably the most troublesome issue that folks have looked to overcome and then the gravity of the data. The reality is that the data, it's very distributed in dynamic, diverse in nature as I mentioned earlier. There's data created at the edge, data created in the data center, and people want to be able to process that data in real time regardless where data is without necessarily having to move it in some cases. Everybody's looking for data management solutions that enable mobility, you know, governments, management of that data and this enabling analytics, wherever that data is. >> You said some really interesting things in there which is, I mean I can see where the customer's data center extended to Equinix, where they want to bring the compute to the data because the data's heavier than the compute, but what about on the edge? Does it make sense to bring, is there enough data there to keep it there and bring compute down to the edge or do you co-locate compute persistently? And then how much of the compute is done at the edge? >> The reality is that you're probably going to see customers do both. There is more data created at the edge than in the history before. You'll see a lot of the data management companies invest in software-defined solutions that require a very small footprint, both from the storage point of view as well as compute. One of the advantages of technology like ONTAP is the investment that has been made to enable data reduction because your ability to store data at the edge is not really very good, so you want to have these capabilities to reduce the footprint by compression, by deduping, by compacting that data, and then making some smart decisions at the edge. Perhaps do some in-line, in-place analytics there and moving some of the data back into a central data center where more batch analytics can take place. >> But when you talk about that compaction, deduping, there was one more, but I think everyone gets the point. Are you talking about having a NetApp ONTAP device near the edge or on the edge? >> That device, it's actually software only. >> Ahh. >> You guys probably are aware of the fact that ONTAP now ships in three flavors, or three form factors. There is an engineered appliance, and we will likely do that for many years to come. But we also have ONTAP running in a virtual environment, either on KVM or Vmware as well as ONTAP running in the cloud. We've been running in the AWS cloud since 2014. We're also running in the Azure cloud. We are talking to other vendors to improve the ubiquity of software-defined ONTAP. >> Just to be really specific, we're told now that an edge gateway, not an edge device, but gateway, it's about two gigs in memory and two cores. Is that something a software-defined ONTAP would run on? >> Absolutely. You'll see us running on a variety of devices in the field with energy companies. You'll see ONTAP running in the tactical sphere, and we have projects that I can't really tell you about, but you'll find it broadly deployed on the edge. >> George: Okay. >> Yeah, let's talk a little bit about NetApp. What are some of the business outcomes you're looking for here? Do you have good executive sponsorship of these initiatives? >> We are very excited to be here. NetApp has been in the data management realm for a very, very long time. Yeah, analytics is a natural place, a great adjacency for us. We've been very fortunate to work with NoSQL type of companies. We've been very happy to collaborate with some of the leaders in analytics such as Databricks. We are entering the IOT space and enabling solutions that are really edge focused. So overall, this is a great fit for us and we're very excited to participate at the Summit. >> What do you think will be ... We've heard from Mata that sort of the state of the art in terms of, I hate to say the word, its fantasy, but like experimentation perhaps, is structured streaming, so continuous apps which are calling on deep learning models. Where would you play in that and what do you think ... What are the barriers there? What comes next? >> I think any complete analytics solution will need a bunch of services and some infrastructure that lends itself for that type of a workload, that type of a use case so you need, in some cases, very fast storage with super low latencies. In some cases you will need tremendous throughput. In some cases you will need that small footprint of an operating system running at the edge to enable some of that in-line processing. I think the market will evolve very fast. The solutions will evolve very fast and you will need the type of industry sponsorship by companies that really understand data management and that have made it their business for a very, very long time. I see that synergy that is being created between the innovation in analytics, the innovation that happens in the cloud, and the innovation that a company like NetApp does around a data fabric and around the type of services that are required to govern, to move, to secure, to protect that data in a very cost efficient way. >> This is kind of key, because people are struggling with having some sort of commonality in their architecture between the edge, on PRAM, and the cloud, but it could be at many different levels. What's your sweet spot for offering that? I mean, you talked about deduping and ... >> Compression and compaction. >> Compression and snapshots or whatever. Having that available in different form factors, what does that enable a customer to do, perhaps using different software on top? >> I'm glad that you asked. The reality is that we want to enable customers to consolidate both second and third platform applications on the ONTAP operating system. Customers will find not only flexibility, but consistency on the data management regardless of where data is. Whether it's in the cloud, near the cloud, or on the edge. We believe that we have the most flexible solution to enable data analytics, data management, that lends itself for all these use cases that enable next generation type of applications. >> Okay but if that predicated on having not just data ONTAP, but also a common application architecture on top? >> I think we wanted to enable a variety of solutions being based there. In some cases we're building glue. What do I mean by glue? It's for example, an NFS to HDFS connector that enable that translation from the native format for most of the data in a Hadoop or Spark type of EMR system. We're investing in enabling that flexibility and enabling that innovation that would happen by many of the companies that we see here on the floor today. >> George: Okay, that makes sense. >> We have just a minute to go here before the break. If you could talk to the entire Spark community, and you are right now on theCUBE, what's on your wish list? What do you wish people would do more of? Or if you could get help with something, what would it be? >> I think that my ask is continue to innovate. Push boundaries, and continue to be clever in partnering both with small vendors that are really innovating with tremendous space, as well as with established vendors that have really made the data management their business for many years and then are looking to participate in the ecosystem. >> Let's innovate together. >> All right, very good. >> Octavian, thank you so much for taking some time here out of your busy day to share with theCUBE, and we appreciate you being here >> Very good. >> Thank you so much. >> Pleasure >> Thanks, Octavian. >> That's right, you're watching theCUBE here at Spark Summit 2017. We'll see you in a few minutes with our next guest. (upbeat electronic music)