>> Live, from San Jose, in the heart of Silicon Valley, it's theCUBE, covering DataWorks Summit 2018. Brought to you by Hortonworks. >> Welcome back everyone to theCUBE's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight, along with my cohost James Kobielus. We are joined by Mike McNamara, he is the Senior Product and Solutions Marketing at NetApp. Thanks so much for coming on theCUBE. >> Thanks for having me. >> You're a first timer, >> Yes, >> So this is very exciting! >> Happy to be here. >> Welcome. >> Thanks. >> So, before the cameras were rolling, we were talking about how NetApp has been in this space for a while, but is really just starting to be recognized as a player. So, talk a little bit about your company's evolution. >> Sure. So, in the whole analytic space, is something NetApp was in a long time ago, and then sort got out of it, and then over the last several years, we've gotten back in, and we recognize it's a huge opportunity for data storage, data management, if you look at IDC Data, massive, massive market, but, the opportunity for us, is like you know what, they're mainly using a direct attached storage model where compute and storage is tied together. And now, with data just exploding, and growing like crazy, it's always been growing, but now it seems like it's just growing like crazy now, that, and customers wanting to have data on-prem, but also being able to move it off to the cloud, we're like, hey this is a great opportunity for us to come in with a solution that's, external storage solution that can come in and show them the benefits of have a more reliable, have an opportunity to move their data off to the cloud, we've got great solutions with that, so it's gone well, but it's been a little bit different, like at this show, a lot of the people, the data scientists, data engineers, some who know us, some still don't like, so, NetApp, what do you guys do, and so it's a little bit of an education, 'cause it's not a traditional buyer, if you will, we look at them as influencers, but it's only one influence than we traditionally have sold to say Vice President of Infrastructure, as an example, or maybe a Director of Storage Admin, but most of those folks are not here, so we're, this is just kind of a new market for us that we're making inroads. >> How do data scientists, or do they influence the purchase of storage solutions, or data management solutions? >> Sure, so they want to have access to the data, they want to be able analyze it quickly and effectively, they want to make sure it's always available, you know, at their fingertips so to speak. We can help them by giving them very fast, very reliable solutions, and specially with our software, they want to do for example, do some virtual clone of that data, and just do some testing on that without impacting their production data, we can do that in a snap, so we can make their lives a lot easier, so we can show them how, hey, mister data scientist, we can make your life a little easier-- >> Or miss data scientist. >> Or miss, we were talking about that, >> There are a lot of women in this field. >> Yeah, yeah. >> More than we realize, and they're great. >> So we can help you do your job better, and then, that, him or her can then influence who's making the purchase decisions. >> Yeah, training sets, test sets, validation sets of data for the machine learning and analytics development pipeline, yes, you need a solid storage infrastructure to do it right. >> Absolutely. >> So, when you're getting inside the head of your potential buyer here, the VP of Infrastructure, or data admin, what is it that you're hearing from those people most, what are their concerns, what keeps them up at night, and where do you come in? >> Yeah, so one of the concerns is, often times, you're, hey, how do I, do you have a cloud storage, connected to the cloud, you know, I'm doing things on-prem now, but is there a path, so that's a big one. And we, NetApp, pride ourselves on being the most cloud-connected, all flash storage in the industry. So, that's a big focus, big push for us. If you saw our marketing, it shows data authority for the hybrid cloud, so we really honestly do, whether it's with Google, or Azure, or AWS, we know our software runs in those environments, it also runs on-premises, but because it's the same on-tap software, we can move data between those environments. So, we get a real good storage, so we can you know, boom, check the box, we got you covered if you want to utilize the cloud, and I think the next piece of that is just from a protecting, protecting the data, you know, again I said data is just growing so much, I want to make sure it's always available, and we can back it up and all that, and that's been a core, core strength, versus like a lot of these traditional solutions they've been using, these direct attached models, they just don't have anywhere near the enterprise-grade data protection that NetApp has always prided itself on, over many decades now. And so, we can help them do that, and quite honestly, a lot of people think, well you know, you guys are external storage, how do you compare versus direct attached storage from our total cost, that's another one. I can tell you definitively, and we've got data to back it up from a total cost of ownership point of view, because of the fact that, of the advantages we bring from, up-time, and you know from RAID, but you know, in a Hadoop environment, often times there's three copies of data. With our solution, a good piece of software, there's only one copy of your data, so have three versus one is a big saving, but even what we do with the data, compressing it, and compacting it, a lot of benefits. So, we do have honest to goodness, outwards to 50% better total cost of ownership, versus a DAS model. >> Do you use machine learning within your portfolio? I'm hearing of more stories, >> Great question, yeah. >> Incorporating machine learning to automate or facilitate more of the functions in the data protection or data management life-cycle. >> Yeah, that's a great question, and we do use, so we've got a piece of software which we call Active IQ, it was referred to as Ace Update, you may have, it may ring a bell, but to answer your question, so we've got thousands of thousands of NetApp systems out there, and those customers that allow us, we have, think of it as kind of a call home feature, where we're getting data back from all our installed customers, and then we will go and do predictive analytics, and do some machine learning on that data, so then we can go back to those customers and say, hey you know what, you've got this volume that's unprotected, you should protect this, or we can show them, if you were to move that data off into our cloud environment, here's maybe performance you would see, so we do do a lot of that predictive-- >> Predictive performance assessment, it sounds like there's anomaly detection in there as well. >> Anomaly as well, letting them know, hey, you know, it's time for this drive, it may fail on you, let's ship you out a new drive now before it happens, so yeah, a lot of, from an analytics, predictive analysis going on. And you know, it's a huge benefit to our customers. Huge benefit. >> I know you're also doing a push toward artificial intelligence, so I'd like to hear more about that, and then also, if there's any best practices that have emerged. >> Sure, sure, so yes. That is another big area, so it's kind of a logical progression from where we were, if you will, in the analytics space, data lakes, but now moving into artificial intelligence, which has always been around, but it's really taking more of a more prominent role, I mean just a quick fun fact, I read that, you know that at the royal wedding that recently happened, did you know that Amazon used artificial intelligence to help us, the TV viewer, identify who the guests were. >> Ooh. >> So, you know it's like, it's everywhere, right? And so for us, we see that trend, a ton of data that needs to be managed, and so we kind of look at it from the edge to the core, to the cloud, those three, not pillars, but directional ways, taking data from IOT centers at the edge, bring it into the core, doing training, and then if the customer so chooses, out to the cloud. So, yeah it is a big push for us now, and we're going a lot with Nvidia, is a key partner with us. >> Really? This is a bit futuristic, but I can see a role going forward for AI to look into large data volumes, like video objects, to find things like faces, and poses and gestures and so forth, and see, to use that intelligence to be able to reduce the data sets down to where it's reduced, to de-duplicate, so that you can use less storage and then you can re-construct the original video objects or whatever going forward, I mean as a potential use of AI within the storage efficiency. >> Yep, yeah you're right, and that again, like in the analytic space, how we roll our in-line efficiency capabilities and data protection, is you know, very important, and then being able to move the data off into the cloud, if the customer so chooses, or just wants to use the cloud. So yeah, some of the same benefits from cloud connectivity, performance and efficiency that analytics apply certainly to AI. You know, another fun fact too about AI, which might help us, you and I living in the Boston area, is that I've read IBM has a patent out to use AI in traffic signaling, so in conjunction with cameras, to get AI, so hopefully that, you know, that works well it could alleviate-- >> Lead them out of the Tip O'Neill tunnel easy. (laughing) >> You got it maybe worse in D.C. (laughing) >> I'd like to hear though, if you have any best practices that with this moving into AI, how are you experimenting with it, and how are you finding it used most efficiently and effectively. >> Yeah, so I think one way we are eating our own dog food, so to speak, in that we're using it internally, we're using it on our customers' data, as I was explaining to help look at trends, and do analysis. So that's one, and then it's other things, just you know, partnering with companies like Nvidia as well and coming out with a joint solution, so we're doing work with them on different solution areas. >> Great, great. Well, Mike thanks so much for coming on theCUBE, >> Thanks for having me! >> It was fun having you. >> You survived! >> Yes! (laughs) >> We'll look forward to many more CUBE conversations. >> Great to hear from NetApp, you're very much in the game. >> Indeed, indeed. >> Alright, thank you very much. >> I'm Rebecca Knight for James Kobielus, we will have more from theCUBE's coverage of DataWorks coming up in just a little bit. (electronic music)

>> Live from San Francisco, it's The Cube, covering Google Cloud Next 2018. Brought to you by Google Cloud and its ecosystem partners. >> Hello, everyone. Welcome back to our live coverage. It's The Cube here, exclusive coverage of Google Cloud, Google Next 2018. I'm John Furrier, co-host with Dave Vellante, both co-founders of The Cube and SiliconANGLE, here with our special guest Diane Greene, who's the CEO of Google Cloud, legend in the industry, former CEO of VMware, among other great things. Diane, great to see you, great to have you on The Cube for the first time. >> Really fun to be here, I'm really happy to be here. >> One of the things about Google Cloud that's interesting that we've been observing is, you mentioned on stage, two years now in, you're starting to see some visibility into what Google Cloud is looking to do. They're looking to make things really easy, fast, and very developer-centric, an open source culture of inclusion, culture of openness, but hardcore performance. Talk about that vision and how that's translating as you're at the helms driving the big boat here. >> Yeah, sure. Obviously we had this amazing foundation with our modern enterprise company, Google Cloud. But what we've done with Google Cloud is we've realized that Google values engineering so much, and so do our customers. So one is, we're taking a very engineering-centric approach. People really love our open source philosophy. And then we're so double down on both security and artificial intelligence. So if you have this underlying, incredibly advanced, scaled infrastructure, high performance, security, availability, and all the goodness, and then you start taking people somewhere where they can really take advantage of AI, where they can be more secure than anywhere else and you have the engineering to help them really exploit it and to listen to the customer, it's about where they want to go, we're just getting incredible results. >> I've been following Google since the founders, Sergey and Larry, started it, it's been fun to watch. They really are the biggest Cloud ever to be built and Facebook certainly has built-- >> We have seven applications that have over a billion active users. >> Massive scale-- >> And actually, we're just this week on track to have the next one drive. >> 25 years of expertise. I've seen them move from buying servers to making their own, better airflow, just years and years of trajectory, of economies of scale, and then when Google started The Cloud a couple years ago, it's like, oh, great, everyone wants to be like Google so we'll just offer our Googleness to everyone and they're like wait, that didn't really work. People want to consume what Google has, not necessarily be Google, because not everyone can be Google. So there's a transition where Google's massive benefits are now being presented and sold, or offered as a service. This is a core strategy. What should people know about? Because people are squinting through all this market share, this company's got more revenue than that one, and if I bundle in AdWords and G Suite, you'd be the number one Cloud provider on the planet by far. So buyers are trying to figure out who's better for what. How do you talk to customers if someone says, are you behind, are you winning, how do I know if Google Cloud is better than the other Cloud? >> Well, the only way you're going to know is to kind of do a proof of concept and see what happens, you know, pull back the covers. But what we can explain to people is that we're so... One is that it's all about information. That's why I say Google's a modern enterprise company because we're about it. I said that in my keynote. We take information, we organize it, and we supercharge it. We give a lot of intelligence to it and that's what every business needs to do, and we're the best in the world at it. And then AI is this revolutionary thing going on where you can just apply it to anything. Someone made a joke about Cloud, they said it's like butter, it's better with everything. Well, The Cloud is better with everything. I think it's AI, actually. So when you combine our ability to manage data, our ability to do artificial intelligence, with our open source and then our security, not to mention the fact that the underlying infrastructure is, everybody pretty much acknowledges the most advanced technology in the world, it's a pretty unbeatable competition, I mean combination. But the thing is, we needed to bring it to market in a way that everybody could trust it and use it. One of the first things we did, which we hadn't had to do, is serving our internal customers. Have roadmaps, so customers can know what's going on, and what's coming when, that we won't ever turn something off, and all those things that an enterprise company expects and needs, for good reason. I have to say, our engineering team is loving working with external customers. Everybody said, you'll never get that engineering team caring about customers. And I knew we would because we had the same quality engineers at VMware and they loved it. And I knew it was just a matter of getting everybody to see how many interesting things that we-- >> And it's problems to solve, by the way, too. >> There's so many problems to solve and we're having even broader impact now, going to the enterprise, going to every company. >> You said in your keynote, IT is no longer a cost center, it's a key driver of business. Tech is now at the core of every product. You go back 15 years, I remember somebody said to me, have you seen what VMware can do and how fast it can spin up a server? That was cost, right? >> Yeah. >> Talk about the enterprise today. When you talk to customers, what are those problems they're solving, what are those opportunities? >> There is a class of customers, typically the internet companies, they are looking for the best infrastructure, they are looking to save cost, but they're also looking, you know, are people realizing, why should I do it all? Why don't I concentrate on my core competence? It's well known we've had Snap from day one and we were in their prospectus when they filed to go public. Then we have Twitter, we recently announced Spotify, and so forth. So those are very technically sophisticated. People, they come, they use BigQuery, they use our data analytics and our infrastructure. But then you get into the businesses, and we've taken this completely verticals approach. So they're coming to solve whatever problems it is they have. And because we have these exceptional tools and we're building platform tools, a lot of them with applied AI in every vertical, they can come to us and we can talk to them in their language and solve their problems. I talked about it in my keynote, with IT driving revenue, everybody's re-engineering how they do business. It's the most exciting time I've ever seen in the enterprise. I mean, I've always though tech was interesting, but now, it's the whole world. >> It's everywhere. You have an engineeering background, you went to MIT, studied there. If you were the lead engineer of most of these companies that are re-architecting and re-engineering, they're almost re-platforming their companies. They're allowed to think differently, it's not just an IT purchase, because they're not buying IT anymore, they're deploying platforms. >> And they're digitizing their whole business. They're using their information, they're using their data. That changes so many business processes. It changes what they can do with their customers, how they can talk to them, it changes how they can deliver anything. So it's just a radical rethink of... It's so amazing when we work deeply with the customer because they might start out talking about infrastructure and how they're going to move to The Cloud and how we can help them, and then we start talking about all the things our technologies can do for them and what's possible. And they'll kind of pause and then they'll come back and they'll go, holy cow, we are rethinking our whole company, we are redefining our mission, we're much more, you know, it's very exciting. >> I had a chance to interview some of your employees and the phrase comes up, kid in the candy store a lot. So I've got to ask you, with respect to customers, is there more of an engineering focus? As you see some of the adoption, you mentioned Twitter, Spotify, these are internet companies, these are nerds, they love to geek out, they know large scale, so not a hard sell to get them over the transom into the scale of The Cloud. As you get to the enterprise, is there a makeup, is their an orientation that attracts Google to them, and why are you winning these deals? Is it the tech, the people, the process, obviously the tech's solid, but-- >> It's a combination of all of the above. What'll happen is we'll all come in and start pitching these companies, and what we do, we really understand what they're trying to do. And then we send in the appropriate engineers for what it is they're trying to do. You get this engineer-to-engineer collaboration going that lets us know exactly how to help that company. >> They give you a list and you go, check, I've done that. Okay, next, check, check, you go down the checkbox, or is it-- >> Well, we brainstorm with them, and companies like that, because they don't necessarily understand all the technology. I always like to think what an engineering orgs does is one, it gets requirements from the customers about what they need, and we call that all the table stakes, and we get it done, and some of it's pretty hard to do. But then, the engineers, after they get to know customers, they can invent things that the customer had no idea was possible, but that solves their problem in a much more powerful way. And so, that's the magic. And that's how we're going into the market. Wherever we can, we'll take things and make it available to everybody. We're very, you know, that open source philosophy of all technology is for everybody, and it's a very nice environment to work in. >> The number one sound John and I have been talking all day about in your keynote was, security's the number one worry, AI is the number one opportunity. >> I was writing my keynote and it hit me. I'm like, oh, this is how it is. >> So please, when you talk to customers, how are you addressing that worry, and how are you addressing the opportunity? >> We're pretty proud of our security because it really is, at every layer, very deeply integrated, thought through. We don't think in terms of a firewall because if you get inside that firewall, all bets are off. So it's really everything you do needs to be looked at and you've got to make sure, and that's why the Chromebook with the hardware based two-factor authentication, and G Suite. Google, which went to that, and since we did, not a single one of our 85,000 employees have been phished. Kind of amazing. >> Yeah. >> Because it's the biggest source of attack. >> Ear phishing is the easiest way to get in. >> Yeah, but you cannot do it once you have that combination. It's all the way up there, all the way down to proprietary chips that check that the boot hasn't been tampered with every time you boot. Our new servers all have it, our Chromebooks all have it, and then everything in between. We think we have an incredibly powerful, we had to add in enterprise features like fine-grain security controls, ways to let our users manage their own encryption keys. But anyhow, we have just at a really phenomenal, and our data centers are so bulletproof. We have those catchers that'll pick up a car. We even have one of those. We had a UPS truck try and tailgate someone and got picked up in it. >> The magic of the engineering at Google. This is the value that we hear from customers, is that, we get that the technology and the engineers are there, we see the technology. But you've been involved in transformative businesses, beyond where Dave was mentioning, certainly changed IT. And it was new and transformed. Cloud's transformational as well. We were just talking earlier about the metaphor of the horse and buggy versus the car, things get automated away, which means those jobs now are gone, but new functionality. You're seeing a lot of automation machine learning, AutoML is probably one of the hottest trends going on right now. AI operations seems to be replacing what was categorically an industry, IT operations. You're starting to see IT again being disrupted. And the shifting into the value up the stack. And this is developers. >> That's the point. Because I don't feel like, yes, all those really painful jobs are going away. >> That no one wanted to do. >> That no one wanted to do anyhow. VMware was the same way. We eliminated tons of drudgery. And AI is doing it systematically across every industry but then you repurpose people. Because we still need so many people to do things. I gave the example in my keynote about the dolphin fins and using AutoML to find them and identify them. Well, that was PhD researchers and professors were looking at that. Is that what they should be doing? I don't think so. You free them up and think of the discoveries they're going to make. I mean, humans are really smart. I think all humans are, we just have to do a better job at helping them realize their potential. >> I want to talk about that, that's a great point. Culture's everything. I also interviewed some of your folks. I just wrote an article on my Forbes column about the four most powerful women in Google that aren't Diane Greene. It was some of your key lieutenants. >> That was a great piece. >> The human story came up, where you have machines and humans working together. One of the conversations was, artistry is coming back to software development. We were on this thread of modern software developers is not just your software engineer anymore. You don't need three PhDs to write code. The aperture of software development engineering and artistry and craft is coming back. What's your reaction to that? Because you're starting to see now a new level of range of software opportunities for everybody. >> Yeah, my daughter is a computer science major and she just taught at coding camp this summer, and they started from kindergarten and went up. It was amazing to hear what those kids were doing. I think a lot of applications are almost going to be like assembling lego. You have all these APIs you can put in, you have all these open source libraries, you have Serverless, so you just plop it in these little containers, and everything is taken care of for you. You're right, it's like a new age in building applications. You will still need, Google needs systems engineers but-- >> Under the hood, you've got to fix engines, mechanics. >> You guys talked about this in your article, the shifts toward creativity becomes a much more important ingredient. >> And also the human computer interface and the UX. You heard from Target, I was talking to him, they do an agile workshop for six weeks for all their developers. Their productivity, he said, an order of magnitude higher. I think the productivity of developers, in The Cloud, with all these technologies, is across the board, an order of magnitude better, at a minimum. >> Mike McNamara, the CIO of Target, was up on stage with you today. >> Yeah, he's a really impressive person. >> So I want to ask you about differentiation. You talked about open source, and specifically your contribution to open source, that's different from most Cloud players. The other thing you talked about, and I want to understand it better, is that you provide consistency with a common core set of primitives. What do you mean, and why is that important? >> Right. So when we build out all our services, we want to have one uniform way of thinking about things. So, how do you do queueing? It's common across every service. How do you do security? It's common across every service. Which means it's very intuitive and it's easy to use this system. Now, it slows you down. Software development at that layer, when you have to do that, goes more slowly. And if you have to make a change, you know, in a core primitive, everybody's got to change, right? However, you take the other side, where everybody just builds a service vertically and with disregard for how things are done, and now you've got this potpourri of ways to do things and everybody has to have specialized expertise in every service. So it really slows down the operators and the developers. You get a lot of inconsistency. So it's super high value and I have to believe people are going to start appreciating that and it's really going to be-- >> I think that's a huge problem that people don't really understand. Just as an example, if you're building out a data pipeline and tapping all these different services, you've got then different APIs for every single service that you have to become an expert at. >> That's exactly right. >> That's a real challenge. Like you said, from a software development-- >> And it's annoying. >> Yes, users who really understand this stuff are getting annoyed with it. But it's an interesting trade-off and a philosophy that you've taken that's quite a bit different from-- >> Well, Google has such a high bar for how they do things. >> That sounds foundational though. It's slower, but it's more foundational. But doesn't that accelerate the value? So the value's accelerated significantly-- >> Oh yes. >> So you go a little slower down. >> Our going a little slower makes everybody else go way faster, at a higher quality. The trade-off, it wins. >> Diane, thank you for taking the time to join us in The Cube today. >> I want to ask one final question. Culture in Google Cloud, how would you describe the DNA within Google Cloud? A lot of energy, a lot of enterprise expertise coming in big time, a lot of great stuff happening. How would you describe the DNA of Google Cloud? >> I would say just tremendous excitement because we're just moving so fast, we're scaling so fast, we're sort of barely in control, it's moving so fast. But such good things happening and the customers are loving us. It's so rewarding and everybody's increasingly taking more and more ownership and really making sure that we do super high quality work for our customers. Everybody's proud, we're all really proud. >> What's the one thing that you want people to know about that they may not know about Google Cloud, that they should definitely know about? >> Geez, you know, it's worth coming to and giving it a try. The biggest thing is how early we are, and it's the right place to be because you want the highest quality, you want the most advanced technology. And AI and security are pretty important. >> Diane Greene, the CEO of Google Cloud here inside The Cube, live in San Francisco. We're at the Moscone Center. I'm John Furrier with Dave Vellante. We'll be back with more live coverage. Stay with us for more from day one of three days of live coverage. We'll be right back.