>> Narrator: From Las Vegas it's theCUBE covering IBM Think 2018 brought to you by IBM. >> Welcome back to theCUBE. We are live finishing up our first day of three days of coverage on theCUBE. From the inaugural IBM Think event I'm Lisa Martin with Dave Vellante talking about snow conditions, we're in Vegas, though. It's a beautiful day, so we'll leave the snow to California and the east coast that's again getting slammed. Dave and I are joined by Mark Bregman, the SVP and CTO of NetApp. Great to have you on the show. >> Thank you. >> So what's new? I was talking about, before we started, that I was formerly at NetApp in marketing a few years ago. What's new at NetApp? What's going on with NetApp and IBM? >> Well first of all if you'd been at NetApp a few years ago you probably thought of us as a storage company but increasingly we think about ourselves as a data company because it's really all about the data and so we're doing a lot of work with IBM in a couple of different areas. One of those is extending our data fabric which is really the software capability to manage and move data across different types of storage, moving in and out of the Cloud and it's absolutely crucial, when you look at some of the things that IBM is trying to do with the IBM Cloud and with a lot of the machine learning applications. >> So Mark what's the difference between a storage company and a data company? >> Well, I think about it as, sort of, think about banking. 150 years ago if you wanted to get a bank you would probably go in and inspect whether they had a good solid vault to store your money. I guess when you opened your bank account you didn't do that. You just take that for granted but you want to know if they have the services to access my money, move my money, inspect my money and do those kind of things and the same thing is happening in our industry. Storage is still important, just as the vault is still important but it's not the first thing you think about. So the more important thing, the thing you do think about is what can I do with my data, how can I move my data, how can I get access to it, how do I protect it? And the actual storage is critical as an enabler but it's not what most people are focused on. >> So those activities that you just mentioned, those adjacent value producers, those are services that NetApp provides that it didn't use to provide or it provides them in a different way. How are things changing? >> Well, from the very beginning NetApp started as, actually, a software defined storage business long before that was a term. The first capabilities that NetApp delivered were software based on commodity hardware and over the years we had to also get into the hardware business. But most of our value historically has always been in the software and it's really been, how do we ensure the data doesn't get lost, how do we move the data efficiently, how do we make copies, and all of those things which are frankly more data oriented than storage oriented although they were sold with the storage systems. What's changed now is branching out beyond just the NetApp system, to be able to carry that capability to the Cloud and to other places that people want to keep their data. >> So what does that mean from a... Put your CTO hat on for a minute. It used to be it was WAFL and it was the operating system and that was sort of the core focus of the company, the products, still, I'm sure, great products. But it sounds like from a technical perspective you've had to evolve. Could you talk about that? >> Well we have. We've had to take those capabilities which we used to tightly integrate with hardware and build an appliance and sort of peel them apart and say we can take this capability and put it somewhere else. For example in the Cloud and that same capability in the cloud now allows us to essentially treat that element, from a data point of view treat the Cloud just like another NetApp target and that's what allows us to rapidly and easily move data back and forth. >> Talk to us about from an evolution perspective. I'm glad you brought that term Dave. How has NetApp's customer base helped facilitate this evolution to be able to give them the values that they're demanding in terms of Multi-Cloud, different vendors, What's that as a CTO that presumably meets up with your customers? >> I think it's been a very synergistic sort of thing which is, our customers as they move to the Cloud almost force us to figure out how can we continue to help them as they move their data to the Cloud and as we do that the customers and new customers say, oh that capability I didn't realize I could leverage and they find new ways to leverage their data in the Cloud and on traditional hardware in this kind of emerging hybrid environment and that's very crucial for a lot of our customers. >> So I want to go back to something you said before about you were always a software defined company. 10 years ago if you looked at it hardware companies, storage companies would sell a product. It would mark up a C8 disk drive 10X. But the real value was in the software wasn't it? >> Right. >> I don't know how many hardware versus software engineers work at NetApp but I'm guessing there's way more software engineers than there are hardware engineers. So is that essentially what you're doing to change your business? You're now selling software function? >> We are and we're doing it in two different ways. We sell software that you, a customer can put on their own hardware, sort of traditional software defined storage but increasingly we also sell software as essentially sell storage or data management as a service in a Cloud platform and then the customer doesn't have to even think about the software. The Cloud provider may have to think about it and we have a lot of relationships with cloud providers to do that but at that point it just becomes a service to the developer or the user that's building on that platform. >> Some of the announcements coming out this week with IBM with respect to Cloud, AI for example. What are some of the things that excites NetApp about what you're going to be able to help your customers achieve based on some of these new innovations? >> Well I think that the work that IBM is doing in the whole area of AI and machine learning is tremendous and we're benefiting in many ways. One is we are a user of that technology ourselves. We are increasingly using machine learning to analyze mass amounts of data from our customer base so that we can get, we have a solution called Active IQ which collects that data, 70 billion data elements, and allows us then to understand the behavior of our systems and our software in the field, make recommendations proactively to customers, for example, a single customer may have a configuration that isn't optimal. We know that because we see all the other customers. We can see that their configurations are getting better results and so that allows the whole marketplace to benefit and that's leveraging a lot of the AI and machine learning technologies. That is one of the areas where there's a lot of synergy between, in our work with IBM, we're often the storage that's underlying the machine learning and we're using the machine learning at the same time. >> So as you sort of go to market or partner with IBM. NetApp actually, people maybe don't know this, has always had a long relationship with IBM. IBM for years resold your filers and probably still does for all I know but how is that relationship evolving and changing? >> Well I would say it's mostly evolving in the sense that it's not just at the level of storage. It really is moving to this data layer as IBM is defining their platform we're a key partner in helping understand how to bring new capabilities in storage and data management to support their new capabilities in cognitive computing, AI, and machine learning. >> How does that change the way in which you develop products? Do you have to be more API friendly? >> Absolutely. As we build our products today we have to think about how to make our products at each layer a kind of platform for the next layer. So even though IBM is building a platform, at a lower layer they're also accessing our capabilities through API's and you could argue we're turning our data fabric into a platform. >> Does it change? You know people use the word future proof. How do you future proof your products in that world? >> Well I think the beauty of API's is that allows you to continually innovate just below the API's without having to disrupt everything above it and that's why this sort of layered approach between API's allows innovation at the storage layer, innovation in the data management layer, innovation in the AI and machine learning layers, all the way up to the end user application. Without the old world model where everything was monolithically built but if you make one change everything breaks. And so it's allowing us to move much more quickly with our rates of innovation independently of the other layers, the other players who are innovating as well. >> So NetApp has reinvented itself a number of times. >> Yeah. >> You've done it again. I remember NetApp when it started out it was like work station storage and then it was internet storage and then after the dot.com bubble blew up it was enterprise storage and then you changed your name. >> And we started with just filers as you said earlier. >> Right. >> And then we expanded into unified storage doing both NAS and SAN. We also supported initially just NFS and then we supported SIFs. We supported a huge transformation as we went into the virtualization world of VMware. So we've continually evolved and we're doing it again. >> And so how would you characterize the current wave? You said before it's about the data. >> I think the current wave is really, if you think about out traditional or our historical businesses being the appliance business I think we're going in three directions right now. One of which is extending away from the integrated appliance to the software defined, put the software on your own storage or your own system. We're also moving in a direction to put it on the Cloud and partnering with Cloud vendors and we're moving in a third direction which is moving higher up in value to data management, not just the storage elements. So certainly a customer could take our software today and use it purely for storage in the Cloud or on a WhiteBox but what they find is there's a lot of value in the higher value data management and that's where we're working with IBM and others. >> Now you've always focused on the data management piece of it. NetApp, correct me if I'm wrong, but you're kind of reluctant to go out and, for instance, buy a backup software company. You'd rather partner with folks like that, Is that-- >> We do that through partnerships, and we'll-- >> That philosophy has not changed, is that correct? >> It hasn't changed dramatically. There may be some areas where we have deep expertise and we extend a little further and there will be other areas where, frankly, we don't have that deep domain expertise and we provide the capability for others to extend that into broader data management. >> So as we've kind of touched on the evolution of NetApp we talked with a number of folks today alone, Dave, about this spirit of innovation as a culture within an organization. Is there a programatized innovation group or lab within NetApp that really helps to drive those three directions that you talked about? >> Well, yes and no. I have a small advanced technology group that experiments and looks at things well beyond the roadmaps, but really innovation is done across the company. Every engineering team is thinking about how to go beyond their road map, their driving innovation. We have a lot of communication across the company between my advanced technology groups and the individual business unit development of the teams because in many cases those feed each other. We find new challenges talking to the current business unit developers and they find new ideas talking to some of my team might be looking three or four years out into the future. A great example of that is a very hot topic right now is Blockchain and we're looking very hard at how could we use Blockchain to, again, rethink the way that you handle and manage data through its life cycle? Could you use this as a way to organize data management so that we know the authenticity of the data, we know who's seen the data, we know who's touched the data, and once you can do that you can think of lots of applications in data security, in data life cycle management, in data prominence, across the whole spectrum. >> So as a multi-multi-billion dollar company storage company, software defined, whatever you want to call it, when you see a company like Filecoin get launched, you know, cryptocurrency, peer-to-peer storage, the tendency of established, very credible players might be to laugh that off but we've laughed off a lot of folks, right? We've learned our lesson there but what do you make of a company like that trying to disrupt S3 for example. >> I think it's very interesting and we look at those very carefully. We try to understand what's the unique proposition that has value? Sometimes there's a unique proposition that just has visibility, let's say. Maybe that's not as valuable and sometimes there is really no uniqueness, they're just playing the game a slightly different way. My own personal view is that all of the excitement about, and whenever you put the name coin in it, that's always disturbing right now. All the excitement about the cryptocurrency relationship to Blockchain, I don't think is going to, in the long term matter that much. On the other hand these distributed ledger technologies which Blockchain has won I think are going to be fundamentally important and I think that we're going to find them turning up in core elements. You mentioned WAFL early on, if you think about, several years ago there was a lot of discussion about log-structured file systems. Could you use something like a distributed ledger technology to create that log in an immutable, distributed way where I don't have to trust any individual system, I don't have to worry about availability the same way because there are multiple copies. The Blockchain or the distributed ledger manages that. It could change fundamentally the way we architect these systems. It's not going to happen overnight but that's what we're looking at. We are looking at every one of these little startups that have new ideas. >> Well what I'm fascinated about, Filecoin is interesting because they raise 250 million dollars in like 30 minutes which is, forget about the crypto craze, that's more than a Series A for a storage company. So seemingly some smart guys, we'll see what happens with the innovation piece. The other interesting thing to me about Blockchain is there's these whole new sets of protocols being built out and there's an incentive for developers to actually develop them versus the government who years and years ago developed SNTP and DNS and IP, etc. >> Well to be fair, the government funded that but it was done by the same developers but this way there's a different source of money. >> Yeah but those guys didn't make any money. >> No, that's true. >> Nobody made any money off of Linux really. >> Yeah, you're right. >> So now there's a huge incentive for developers to do that so I'm really curious as to where the next wave of innovation is going to come from as a advanced technologist you got to look at that and say hmmm, I want to keep an eye on that. >> Oh absolutely, I mean that's why we're watching it. >> Do you think Blockchain, I know we got to go, but a lot of concerns about scaling. >> Well that's why I try to distinguish between Blockchain and distributed ledger technologies. There are a lot of emerging technologies that are fundamentally similar to very abstract level to Blockchain but are implemented differently. You have to remember Blockchain was built for cryptocurrency and it was built to be inefficient by design. >> Yes, right. >> And so taking that same idea and saying we're going to use it for these high performance applications is probably not the right approach but going back to the idea that I can have a distributed, fundamentally untrusted network and I can create a trusted ledger, that's pretty interesting and there are a lot of interesting emerging technologies that I think some of those will become the core. >> Dave: In use cases for sure. >> Yeah. >> Dave: Distributed databases have never been easy. >> Yeah. >> It's always been challenging for scale, performance, latency, etc., I wonder can those problems be solved? >> You think about the challenge of data prominence and in the world of GDPR and all of these things, the ability to say I know where all the data is, I know where it came from, I know who's touched it, all of the discussion going on, probably here at this conference about GANs where you can make video that looks just like you but you weren't in it, for example. How do you keep track of the data so I know this really came from that camera, it was really you and not a video reproduction, that's going to become more and more important and that's where I think these technologies could become really valuable. Something we've talked about, data prominence, for twenty years but we've never really been able to implement it at scale. >> Well, and you see the explosion of fake news and the like. Facebook is now more powerful than the UN and the 2020 election is going to be about fake news and so things like that are really technologies that could solve that problem, hopefully have legs. >> Mark: I think so. >> Awesome. Thank you. >> Great. Thank you. >> Mark, thanks so much for stopping by and sharing what's going on at NetApp, kind of walking us through you're evolution and some of the exciting things coming. We wish you a great rest of your fiscal year. >> Great, thank you very much. >> For Dave Vellante, I'm Lisa Martin and you've been watching theCUBE live from day one of IBM's inaugural Think event. Check out thecube.net where you can find all of the replays of our videos today and check over to siliconangle.com for the written articles about that. We want to thank you for sticking with us and we look forward to seeing you tomorrow. Thanks. (upbeat music)

Live from Berlin Germany, it's the queue Covering NetApp insight 2017 brought to you by Neda Welcome back to the cubes live coverage of net app insight here in Berlin Germany I'm your host Rebecca Knight along with my co-host Peter Burris. We are joined by Mark Bregman. He is the CTO of net app Thanks so much for coming on the cube Thanks for taking the time so you have been recently looking into your crystal ball to predict the future and you have some some fun sometimes counterintuitive Predictions about what we're going to be seeing in the next Year and decade to come right so so your first pitch in you said data will become Self-aware right what do you mean by that? Well the title is kind of provocative really the idea is that? Data is going to carry with it much more of its metadata Metadata becomes almost more important than the data in many cases and we can anticipate Sort of architectures in which the data drives the processing whereas today? We always have data is sort of a pile of data over here And then we have a process that we execute against the data that's our been our tradition in the computing world for a long long time as data becomes more self-aware the data as it passes through Will determine what processes get executed on it? So let me give you a simple analogy from a different field from the past in The communications world we used to have circuit switched systems There was some central authority that understood the whole network If you and I wanted to communicate it would figure out the circuit set up the circuit And then we would communicate and that's sort of similar to traditional Processing of data the process knows everything it wants to do it knows where to find the data. It does that it puts It somewhere else But in the communications world we move to packets which data, so now the packet the data Carries with it the information about what should happen to it And I no longer have to know everything about the network nobody has to know everything about the network I pass it to the nearest neighbor who says well I don't know where it's ultimately going, but I know it's going generally in that direction and eventually it gets there now Why is that better? It's very robust it's much more scalable and Particularly in a world where the rules might be changing. I don't have to necessarily redo the program I can change the the markup if you will the tagging of the data You can think of different examples imagine the data That's sitting in a autonomous vehicle and there's an accident now There are many people who want access to that data the insurance company the authorities the manufacturer the data has contained within it the Knowledge of who can do what would that data? So I don't have to now have a separate program that can determine Can I use that data or not the data says sorry you're not allowed to see this. This is private data You can't see this part of it Maybe the identify our data for the obviously the insurance company needs to know who the car owner is But maybe they don't need to know something else like where I came from The authorities might need both well he came from a bar So you can imagine that as an example if you the implications, yes marker are important for example if I Wanted to develop an application. That would be enhanced by having access to data I had to do programming to get to that data because some other application control that data and that data was defined contextually by that application right and so everything was handled by the application by moving the metadata into the data now I can bring that data to my Application more easily less overhead and that's crucial because the value of data accretes It grows as you can combine it in new and interesting ways so by putting the metadata end of the data I can envision a world where it becomes much faster much more Fasil to combine data and new and Exactly it. Also is easier to move the Processing through the data to the data because the processing is no longer a monolithic program It's some large set of micro services and the data organizes which ones to execute So I think we'll see I mean this is not a near-term prediction This is not one for next year because it requires rethinking How we think about data and processing, but I think we'll see it with the emergence of micro services compositional programming Metadata together with the data will see more functional programs little programs well That's your quick rush before we go on to the next one. It's almost like in the early night or the late 1970s It was networks of devices ARPANET the became the Internet and then the web was networks of pages And then we moved into networks of application services Do you foresee a day where it's going to be literally networks of data? Yes, and in fact That's a great example because if you think about what happened in the evolution of the web through what we called web 2.0 That the pages were static data They came alive in the web 2.0, and there was a much less of a distinction between the data and the program In the web layer right so that's what we're saying we see that emerging even further Next prediction was about virtual machines becoming rideshare machines well this is somewhat complementary to the first one they all kind of fit together and Here the idea is you know if we go back in the earlier days of IT it wasn't that long ago that if you needed? Something you ordered the server, and you installed it you owned it and then we got to the model of the public cloud, which is like a rental and by the same analogy if in the past if I wanted a vehicle I had to buy it and Then the rental car agencies came up, and I said well, you know when I go to Berlin I'm not gonna buy a car for three days I'll rent a car, but I can choose which car I want do I want the BMW, or do I want you know of Volkswagen That's very similar to the way the cloud works today. I pick what instances I want and They they meet my needs And if I make the right choice great and by the way I pay for it while I have it not for the work It's getting done so if I forget to return that instance. I'm still getting charged But the rideshare is kind of like uber and we're starting to see that with things like serverless computing In the model that I say I want to get this work done The infrastructure decides what shows up in the same way that when I call uber I don't get to pick what car shows up they send me the one that's most convenient for them and me and I get charged for the work going from point A to point B. Not for the amount of time There's some differentiation if there is so cool Ah, they come to that and and so that's more like a rideshare But as you point out even in the rideshare world. I have some choices. I can't choose if I want a large SUV I might get a BMW SUV or I might get a Mercedes SUV I can't choose that I can't choose it the silver or black But I get a higher class and what we're seeing with the cloud Or these kind of instances virtual solutions is they are also becoming more specialized I might it might be that for a particular workload I want some instance that has have GPUs in them or some neural chip or something else In much the same way that The rental model would say go choose the exact one you want The rideshare model would say I need to get this work done and the infrastructure might decide this is best serviced by five instances with GPU or Because of availability and cost maybe it's 25 instances of standard processors because you don't care about how long it takes so It's this compromise and it's really very analogous to the rideshare model now coming back to the earlier discussion as The units of work gets smaller and smaller and smaller and become really micro services Now I can imagine the data driving that decision hailing the cab hailing the rideshare and driving What needs to be done? So that's why I see them in somewhat complementary and so what's the upshot though? For the employee and for the company I think there are two things one is you got to make the right decision? You know if I were to use uber to commute to Sunnyvale every day It'd break the bank, and it would be kind of stupid so for that particular task I own my vehicle But if I'm gonna go to Tahoe for the weekend, and I meet an SUV I'm not gonna buy one neither am I going to take an uber I'm in a rent one because that's the right vehicle on the other hand when I'm going from you know where I live to the marina within San Francisco, that's a 15 minute drive I On demand I take an uber and I don't really care now if I have 10 friends I might pick a big one or a small one But again that the distinction is there so I think for companies They need to understand the implications and a lot of times as with many people they make the wrong initial choice And then they have then they learn from it so You know there are people who take uber everywhere And I talked and I said I had a friend who was commuting to HP every day by uber from the city from San Francisco That just didn't make sense he kind of knew that but The next one is data will grow faster than the ability to transport it, but that's ok it doesn't sound ok it Doesn't sound ok and for a long time. We've worried about that. We've done compression, and we've done all kinds of things We've built bigger pipes And we've but we were fundamentally transporting data between data centers or more recently between the data center and the cloud big chunks of data What this really talks about is with the emergence of quality IOT in a broad sense? Telematics IOT digital health many different cases there's going to be more and more and more data both generated and ultimately stored at the edge and That will not be able to be shipped all of that will not be able to be shipped back to the core And it's okay not to do that because there's also Processing at the edge so in an autonomous vehicle where you may be generating 20 megabytes per hour or more You're not gonna ship that all back You're gonna store it you're gonna do some local processing you're gonna send the summary of it the appropriate summary back But you're also gonna keep it there for a while because maybe there's an accident and now I do need all that data I didn't ship it back from every vehicle But that one I care about and now I'm gonna bring it back or I'm gonna do some different processing than I originally Thought I would do so again the ability to Manage this is going to be important, but it's managed in a different way. It means we need to figure out ways to do overall Data lifecycle management all the way from the edge where historically that was a silo we didn't care about it Probably all the way through the archive or through the cloud where we're doing machine learning rules generation and so on but it also suggests that we're going to need to do a better job of Discriminating or demarcating different characteristic yen classes of data, and so that data at the edge Real-world data that has real-world implications right now is different from data that summarizes business events which is different from data that Summarized as things models that might be integrated something somewhere else And we have to do a better job of really understanding the relationships between data It's use its asset characteristics etcetera, would you agree with that absolutely and maybe you see the method in my madness now? Which is that data will have? Associated with it the metadata that describes that so that I don't misuse it you know think about The video data off of a vehicle I might want to have a sample of that every I don't know 30 seconds, but now if there's really a problem and it may be not an accident Maybe it's a performance problem. You skidded I'd like to go back and see why was there a Physical issue with the vehicle that I need to think about as an engineering problem was it Your driving ability was it a cat jumped in front of the car so But I need to be able to as you pointed out in a systematic way distinguish what data I'm looking at and where it belongs and where it came from The final prediction it concerns the evolution from Big Data to huge data so that is Really driven by the Increasing need we have to do machine learning AI Very large amounts of data being analyzed in near real time to meet new needs for business And there's again a little like many of these things There's a little bit of a feedback loop so that drives us to new architectures for example being able to do in memory analytics But in-memory analytics with all that important data. I want to have persistence technologies are coming along like Storage class memories that are allowing us to build persistent storage persistent memory We'll have to re our Kotak the applications, but at the same time that persistent memory data I don't want to lose it so it has to be thought of also as a part of the storage system Historically we've had systems the compute system, and there's a pipe and there's a storage system And they're separate they're kind of coming together, and so you're seeing the storage Impinge on the system the compute system our announcement of Plexus store acquisition is how we're getting there But at the same time you see what might have been thought of is the memory of the computer System really be an extended part of the storage system with all the things related to copy management backup and and And so on so that's really what that's talking about and you know it's being driven by another factor I think which is a higher level factor. We started in the first 50 years of the IT industry was all about automating processes That ran the business they didn't change the business. They made it more efficient accounting systems etc since probably 2000 there's been a little bit of a shift Because of the web and mobile to say oh I can use this to change the relationship with my customer Customer in density I can use mobile and and I can change the banking business Maybe you don't ever come to the bank for cash anymore even to an ATM because they've changed that The wave that's starting now which is driving This is the realization in many organizations, and I truly believe eventually in all organizations that They can have new data-driven businesses That are transforming their fundamental view of their business so an example I would use is imagine a shoe maker a shoe manufacturer well for 50 years. They made better shoes They had better distribution, and they could do better inventory management and get better cost and all of that with IT in the last Seven or ten years, they've started to be able to build a relationship with their client. Maybe they put some Sensors in the shoe, and they're doing you know Fitbit like stuff mostly for them That was about a better client relationship, so they could sell better shoes cuz I wrench eiated now The next step is what happens if they wake up and say wait a minute We could take all this data and sell it to the insurance companies or healthcare companies or the city planners Because we now know where everyone's walking all the time That's a completely different business But that requires new kind of lytx that we can't almost not imagine in the current storage model so it drives these new architectures And there is one more prediction, okay? Which is that and it comes back again? It kind of closed the whole cycle as we see these Intelligence coming to the data and new processing forms and so on we also need a way to change data management to give us really Understanding of data through its whole lifecycle one of the one example would be how can I ensure? That I understand the chain of custody of data the example of an automobile there's an accent well How do I know that data was an alter or? how can I know whose touch this data along the way because I might have an audit trail and So we see the emergence of a new Distributed and mutable management framework if when I say those two words together you probably think Blockchain which is the right thing to think but it's not the blockchain. We know today there may be something It's something like that But it will be a distributed and immutable ledger that will give us new ways to access and understand our data Once you open up the once you open up Trying to get the metaphor once you decide to put the metadata next to the data Then you're going to decide to put a lot more control information in that metadata Exactly, so this is just an extension said it kind of closes the loop exactly Mark well, thanks so much for coming on the show and for talking about the future with us It was really fun to have you on the show we should come back in a year and see if maybe you're right exactly exactly Thank you. I'm Rebecca night. We will have more from NetApp insight. Just after this

>> Announcer: Live from Las Vegas, it's theCUBE covering NetApp Insight 2017. Brought to you by NetApps. >> Welcome back everyone, we are live in Las Vegas this is theCUBE, SiliconANGLE's flagship program where we go out to events and extract the signal from the noise. I'm John Furrier, my co-host Keith Townsend. We're here at NetApp Insight 2017 here at the Mandalay Bay with two great guests, a senior executive, senior NetApp folks, are going to share some insight on what's going on. We have Mark Bregman is the Senior Vice President and CTO thanks for coming on. John Woodall VP of Engineering at Integrated Archive Systems. The first partner of NetApp going back in the day. Welcome to theCUBE thanks for coming on. >> Thank you. >> Thank you. >> So we've seen that movie before, you know every cycle of innovation there's always opportunities. Interesting now we're in a cycle where you can see some new waves out there coming in. And we think we're surfing on some waves now, but the tsunami's coming. Everything from blockchain down to just cloud growth like crazy. You guys have done extremely well. You've seen them before, these transitions. People are busy right now, your customers are super busy. They've got app development going on, DevOps, they've got security unbuckling from IT becoming critical, data governance. What should they know about in this transition that they may miss or they should pay attention to. >> Well, I would say that the thing that is probably the most profound is we've gone through a couple of big transitions, as you mentioned, in the industry as a whole. 20, 30 years ago we would talk to customers and they'd start with infrastructure and they'd talk about servers and storage. 10, 15 years ago they start with applications and they'd talk about their ERP or whatever software. That would decide then the infrastructure. Today they're starting with data and companies are realizing that data is the thing that's going to transform their business. And then based on that data, what software am I going to use and then talk about infrastructure. So the conversation's kind of turned around completely from where it was 20 years ago. >> John, you've been a partner, I see the partner landscape certainly changing. You seeing resellers and VAR's and I think, does the word VAB even exist, value added business? They're actually building their own tech because there's opportunities to be a service provider. Almost like a telco, who would have thought? >> It's crazy, it's crazy. I think I think from our perspective as a longtime partner, we've been successful with NetApp through transitions. We were talking before about the resiliency of NetApp in going through transitions. They've done it again, the keynote today filled with a lot of, what I call, mic-drop moments of yet another level of innovation. But you're right things have flipped almost 180 degrees in the discussion that starting with data, starting with a business outcome, as part of the discussion. It's not about what can I sell, it's about in solving the problem, do I accelerate the pace of my business. Do I open up new ways to monetize in my business. Do I drive efficiencies in my business that translate to the bottom line. As a reseller and as a partner, we have to transition with that because the discussion changes, the skill sets change and it becomes much more of a services play on the front-end and to help through and then becomes managed services, as you know, and that. >> Mark I want to ask your a question. We were joking with the product marketing team on the cloud earlier that you know the slogan should be, I don't know NetApp could do that. It just keeps happening, oh, I didn't know they did that. While that's kind of a history NetApp, but I want to ask something specific. We see it's a success out there in the cloud, you look no further than Amazon Web Services. Now Microsoft's kind of catching up to the rear, Google's there's some other people are trying to kind of get in there. But Amazon's the winner when it comes to the number of announcements you see an event and I'm sure at Reinvent coming up is going to be a tsunami of their bigger announcements, more services so it's a plethora. And so that's an indicator of success. And also the new differentiator, at scale, as you got to keep iterating, you guys have a slew of announcements, so running engineering and being the CEO. What's going on at NetApp? What's the conversation like, you have all these roadmaps, is it just all this innovation, is it part of the plan and just give us some insight into how this all works. >> Well, I think for a long time, maybe for the first 20 years of the company, we were almost like a one product company. The innovations were all in that lane. They were all, you know, make this a better product, make ONTAP better and customers love that because they were growing with us. What's happened is it's kind of exploded in multiple dimensions. So we continue to innovate in our core. But at same time we're having to say, how can we use this capability in a completely different way, in the cloud? How can we help customers manage their data, no matter where it is, not just on our ONTAP systems. We made the acquisition of a little over a year ago, a year and a half ago, of SolidFire, to get into an area of a different approach to managing storage. And it's not sometimes people get it confused and they go that's how you got into flash. Frankly, we're already doing flash units and have flash in all of our product lines. The real reason we did that was to get into this more programmatic, scale out, API driven model of administration of storage. And we're having to do that in so many dimensions. so as we expand those dimensions, Of course we have to expand our innovation. We have to innovate at the given rate in each of threads. >> The old joke in Silicon Valley is you know get lucky once and you get rich. And it's hard, you know, the sophomore jinx whatever you want to call it, repeated successes is a sign of success and certainly as a partner you want to, you don't want to one trick pony at all. Now, I got to ask you, given the NetApp history of those successes, the data fabric is very good positioning I like that position because it's got a lot around it's super important, you think data is the new wave it's going to come bigger than cloud in terms of its impact. What from NetApp, for the customers that are watching and especially new customers, as you take new territory down with data, what is it about the NetApp portfolio, or the architecture the DNA that makes you guys relevant in this data fabric equation? Because you can't just get there overnight because of diseconomies of scale. What is it about NetApp that makes them super relevant? Couple things, one thing, what's the one thing? >> Well, I think I think it becomes back to I think you even said the term, DNA. It's what is it about NetApp, why are we one that's been around for 25 years and continue to make it through these transitions. And I think it's because, first of all, we don't rest on our laurels, we're not caught up in the innovator's dilemma of continuing to just refine what we already have. We'll do that, but we also recognize that there are emerging new customer needs. And our basic intellectual capital can be applied in different ways. So when I talk to our engineers, they don't talk about I build controllers that go into arrays that manage data. They realize that deeper down there's a kind of intellectual capital could go into a piece of software in the cloud. And there's a customer problem that we can go solve. So I think it's about being motivated by solving those customer data problems. >> So culture, some culture. >> It's culture. >> What are the products now, so you have a data, storage, storage stores data. So you don't need rocket science to figure out that you're storing data. >> I'll give you an example, there a lot of competitors in the flash storage business that have come into the market and basically gave up on us because we were late coming to that market. But we came in the market, we accelerated, we passed them, why is that? Partly, we built a good product at the flash storage layer. But more importantly we leveraged all of the storage management which we'd already built over 20 years. And so now we're suddenly out there with a very rock solid flash engine but it's supported by all the other capabilities which make it valuable to our customers. So it's not just, hey, here's a new tool, it's here's a new solution to your problem. And I think that's a big part of our DNA. And our technology side is we've been in data management for 20 years, we just never talked about it that way. >> So John, we had Dave Hitz on earlier, and he said that one of the keys to keeping away from the innovators dilemma has been that NetApp has leaned into the thing that will kill us. I tweeted that out, that's an awesome pull, that they've leaned into the things. As a partner though, that can be a bit scary. Technology is especially enterprise tech is a very stable thing. NetApp has been with ONTAP a very traditional partner even with fads and bringing those innovations to flash. How's that ride been for you guys over the past 25 years. >> It has been consistent, it has been a great partnership, and it continues to be a great partnership because as I look out and hone my portfolio of offerings and partnerships, NetApp stays very high in, that not just because we have a great run rate business, but because NetApp, in their innovation allows me to continue to solve problems with an existing partner, which makes us more efficient. Now, having said that we talked about you mentioned data fabric. That's a completely different discussion from a storage company. At first you think okay, I'm replicating data, I have a transport layer, that's fine. But what are you doing beyond that? I think you begin to see a new NetApp emerging as software defined. An organizing principle in my mind of the data fabric is it gives the customer freedom and flexibility that just buying storage doesn't give you. It gives them the flexibility to deploy in the cloud, next to the cloud, on-prem, as a virtual instance, as an AMI in the cloud, et cetera. So it allows the customer to place data and workloads where and when and how they want that makes sense for their business, not NetApp's business, or my business and so in that we're starting to see now with Anthony Lye's demo today of Cloud Orchestrator. >> Which, by the way, isn't shipping yet, but it's multi-cloud. >> Multi-cloud? >> It's multi-cloud instance. >> Yeah, that right there, and its applications, it's provisioning VM's, it's provisioning. >> If you guys get that to the market fast, it will be the first multi, True multi, orbiting call it real multi-cloud There's a lot of fake multi-cloud out there but that would be a real use case. >> And that's a completely different discussion so you know to kind of plagiarize, you can teach an old storage dog a new trick. So they transformed to meet the emerging needs of a new market, we are have to transform with them. So there's a bit of bumpiness that we're all going to experience as we learn that and do that. >> John, I just want to drill-down on that, I want to get also your both perspectives. What you're really teasing out with the Cloud Orchestrator demo in my mind, the impact of that demo significance is you guys as a storage company, now a data company, are enabling opportunities with the data. That's clearly what's happening, obviously, no debate there. But the impact is to developers. Now the developer dynamic is as these devops guys come in, there's new, there's re-skilling going on. So the biggest challenge of multi-cloud is each cloud has its own way to pipeline data or do things with data. So making that easy, I don't want to have to hire guys to program for each cloud. >> Mark: And they're hard to find. >> It's incredible, it's too hard. Abstracting that away is going to be a boon for the developer market. That's a new market, that's a different thing than NetApp. >> It's a very different market than we've been in before. >> So what are you doing? What's the plan, just continue to enable developers? >> Well, the comment you made earlier, about lean in to the thing that's going to kill you is exactly right, I wouldn't have said it quite like that but I'm not Dave Hitz. So we definitely, when we see a challenge we lean into it. And and that does two things, it's a little bit like, I don't know was it TaeKwonDo where you use the other competitors energy? >> I think it's judo. >> Think it's judo, use the other energy, the power the other opponent to win. And that's kind of what we're doing. I think when you do that it means we have to transform and our partners do, and you're a partner that's been with us long time, you've been through a lot of transitions. >> Yes we have. >> Well judo move is about leverage, and that's about having installed, you guys have that leverage with your customers. >> And the customers are moving as well, so we could try to keep them, hold them back. Or we can move with them and actually accelerate them to where they're going to our benefit, and to our partners benefit and I think that's what Dave was referring to. Well, Mark and John love to have you guys on, love to do a follow-up segment in Palo Alto, our offices are really across the yard from each other, certainly if you guys are in Sunnyvale This is a super important conversation. I'll give you guys the last word, impact to customers for NetApp with the new capabilities with data center innovation modernization, next gen data center, on-premise, true private cloud and power a horse in the cloud with data. All that working together in some cases end to end or in pieces whatever the customers is. What does it mean to the customer this new. >> I'll steal a line from our marketing teams and what it really means is it's going to enable customers to change the world with data. Transform their business, create new opportunities. >> It's a new wave in the economy. It's going to be disruptive and tumultuous for some. We have an opportunity to go into a customer and to help them find new ways, with their data, because the two key assets of company now is people and then data. So the people are there taking their data, allowing them to find new opportunities to go to market faster. NetApp's in a unique position. >> It reminds me of value creation, I mean a lot of stuff with blockchain you see the indicators, almost the Web1.0 again. You see in the new shift in architecture happening upside down it's almost reverse. >> The developer model's right. I mean you talk about Amazon, I think from 2008 until 2014 or 15 they introduced about three thousand new services on their platform. I don't see an average IT organization doing that. >> I think that rates gone up now. >> It's on an exponential growth there. >> I think we're starting to see the swim lanes, if you will, I'm calling them native clouds because they're so native. But they're also powering a new ecosystem and part of it, I wish we had more time to talk about the partner equation. There a lot of musical chairs going on in the partner ecosystem. You've been with NetApp from the beginning, congratulations. Congratulations on all the success on the platform and the product innovation. It's theCUBE bringing you the innovation and the data through our data fabric called theCUBE. We'll be back with more live coverage after this short break. >> Announcer: Coming off barrier breakers, status quo smashers, world.