>> live from Boston, Massachusetts. It's the Cube covering AWS Reinforce 2019. Brought to you by Amazon Web service is and its ecosystem partners. Welcome >> back, everyone. Day two of live coverage here in Boston, Massachusetts, for AWS Amazon Web services. Inaugural conference called Reinforce. This is a Cloud security conference, the first of its kind. It's the beginning of what we see as a new generation of shift in now new category called Cloud Security. Obviously, Cloud has been growing. Security equation is changing and evolving. I got a great guest here. Colby Alan, who's a platform architect at ZIP with based in Seattle. Great for joining us. Thanks for coming on. Thanks for having me. So we're chatting before we came on about your journey and your Dev ops chops you guys have built over there that I want to get into that just quickly explain what you guys do real quick. Set the context. >> Yes, it is on SMS text messaging provider way Specialize in toll free messaging. We also texting able landline phone numbers. Our business is kind of really split into two parts way. Have you know your traditional Sadd's application that ran runs like a sad That's where you can, you know, have the you I thio interface your landline phone number eight under number With that messaging, no, top that We run a carrier grade network. So we have direct binds into all the major carriers in the U. S. Bringing online some Canadian carriers. That's really where the power of our platform and we own the network on DSO way started Nicolo and over the last last year, which has spent nine months moving all that into Amazon and >> forget about that. So explain the architecture. You guys move yet polos with network you moved to Amazon with three people. Just classic devils. A lot of hard work, I'm sure take us through what happened. What was the old environment? And now what does it look like now? >> Yeah, so, you know, when I just started with, you know, they were interesting place. They were just starting a huge growth. And so at that point, they existed in a few data centers in the U. S. And running the empire workloads on or bare metal databases on. The problem was, there was just a scaling problem, right? I mean, we couldn't way We're looking at the type of scale we needed and trying to procure hardware. And we just couldn't physically get it fast enough with the right amount of budget. So I come from a previous place doing a job? Yes. I mean, that's kind of what I've done for a lot of years. So, you know, I convinced my boss stay here. Let's let's run the stats happen. Eight of us. So we built that ran it, launched our new version of arse as application in Amazon. And at that point, you know, our traffic skyrocketed. You know, I think last year we had somewhere to 180% growth, right? And, you know, our core infrastructure just wasn't surviving. Right is outages and problems. And so, you know, we took it and we we went to Amazon with it. And, you know, we rebuilt it all. And it was a really interesting thing, because Amazon was Luther releasing features and we were consuming them, right? Five. Siri's and Nitro came out, and we're like finally waken get performance of the networking interfaces. Then they released the D instances within ve Emmys, or like finally, our databases will survive and they can go fast enough, you know? And then we leveraging huge Aurore instances, real impact power, the back end of this thing. So you >> guys really tapped really? At the right time? You guys were growing. You saw the, you know, that scale potentially bursting. You saw the scale coming in growth coming in the company you could almost see. Okay, look, we got a plan. So you go to Amazon News Service is what's the impact on the staff has been any more people. What's been the impact on? >> Yeah, I think the big thing is the initial move. We did it for three of us. I mean, it was a lot of work. We spent a lot of time doing it. A lot of people, sleepless nights, a lot of long weekends. But now you know, we've got a really stable platform, and, you know, we were able to really continue processing our message. Growth is increased, and we know we haven't, you know, had to totally re architect things again, right? The architecture's work has grown and expanded. Stale ability has been fantastic for us. The performance, of course, is you know, some of >> the best walking commercial for eight of us, a question paper. But if you'll have that same experience, but what's interesting is you guys essentially are, in my opinion, representative of the trend that we're seeing, which is certainly in security as they catch up the devil. That's a big story here. Security now can level up with speed of the Dev ops kind of engineering philosophy and pointing, but it's it's the trend of building your own and a lot of companies. They're reinvesting in teams of people because they're close to the action and they can actually code if I quickly use cases that they know are bona fide, whether it's a low level platform service, primitive or right up into the app, using machine learning and data. So you know you have now that now you had security in there. This is where the action is and so cos I mean, I see the successful ones like you guys coming in saying You know what? Let's not boil the ocean over. Let's just solve one problem scale and then let's look at the service is that we can leverage to doom or take us through that philosophies. I think you guys were great example of that. >> So, I mean, if we touch on the security aspect, I think that that was a big thing is way. Don't run a dedicate security team. My team is the security team, right? And that was a big thing that both me and my director is. You know, we wanted the people building it to be doing the security. And, you know, the that was what was really, you know, easy with eight of us is, you know, we could turn on all these fancy features. It was just, you know, a flag and Terra formed all of a sudden way. Have encryption arrest. It's something we've never had before. So there's that. And then, you know, to the builder methodology be because we came from such a scrappy like way. Got to go fast, like we didn't have time to evaluate software bringing consultants, you know, it's so, you know, we kind of just kind of adopted that, you know, it's better for us a lot of times to kind of roll our own thing. Andan there, times where there's software that's a good fit for it. I mean, we do use some external vendors on things, and >> that's really more of a decision on the platform. But as you look at the platform engineer, you go. Okay, we gotta build here. Let's weigh No, he don't really is not me that be a core competency. Let's go look at some vendors for this, this and that. But ultimately, if you look at something that's really core, you can dig into it. And certainly with Kubernetes and with a lot of the service is coming out sas after taking eventually Cloud Native. >> Yeah, yeah, through you're you're so we're huge Criminality is 100% kubernetes everywhere, and I think that that's really been another big thing for us is you know, it's it's brought our application up a level to be able to integrate, be more reliable. I mean, you know where you used to have this external service discovery piece, and then you have your security peace. You know where kubernetes I can go deploy a container application. Describe it all at once, right? It's all in my coat config so I can audit it for our compliance sees. You know we can co to review for our compliance, sees but the same time I deploy the whole thing. I'm not. Here's this team to point the There's this other team then coming by trying to secure the app. It it's all together. >> The old way would have been kind of build it out, maybe use some software. Have all these silo teams. Yes, and that's kind of all kind of built in. >> Yeah, we kinda just opened it out, right? I mean, you know, from from arse, as teams leveraging a lot of, you know, the security features that are available to us to our core piece, which is a very different type of software, you know, is leveraging the same pieces and same type of monitoring principle. >> It's interesting, You know, the Kino. There's something people hemming and hard around, like the word Dev sec ops. I mean, I love Devon. We've been we've been part of that since day one. It's been fun to be part of it, but we saw the benefits of it. Clearly. You see, no doubt there's no debate. But when you start getting into some of the semantic definitions, go to security known feel that, by the way, is fragmented like crazy and now you get the growth of the cloud is starting to see cloud security become its own thing That's different than the on premises side. So what's your take on that? Because a lot of people are wanting their going to cloud anyway. So what's that they're saying on premise, security posturing and cloud security? In your opinion? >> Yeah, so I mean, it is drastically different. I think part of it's the tool set that's available, right? I mean, we ran data centers. I've automated data centers, but, you know, they're just not at the level of which I could do the automation in the auditing in the cloud. So I feel like I found actually, some respects makes it easier for me to do security on run security and audit security numbers. The data center. You know, I don't run a lot of tooling and a lot of things to get all the views. I need it, But there's a lot of really separate systems, you know, in the cloud you have, like this one. Nice, fundamental, a p I. That hi is a person who has to build the infrastructure can use, but it's the same a p I that I put my security had on that. Like I used to make security, right, security groups, things of that sort. It's all the same, right? I'm not having to learn five different applications has been really important for our team because, you know, my team comes from the vast majority of no true Dev ops Thio. You know, we've been upgraded from people in our knock, you know, and have them really just learned the one ecosystem >> is you don't want to fragment the team. Yeah, I don't wanna have five different skill sets, kind of >> their victims. We just We don't wanna have tools that only one person knew how to do right. We wanted people to take vacations right? And like, we don't want to have a tool that's like only only that person knows how to run it, nobody else does. And so >> that was the big thing for us. What you think about the show here, reinforce all say it's not an Amazon Webster's summit. They do the summits which assistance see a commercial version of reinventing regions. This is a branded show is obviously their cloud security going hard at it. What's your take. So far, >> I've really enjoyed it. I mean, so I've gone to some. It's I've been to reinvent for a few years spoken to reinvent once, you know? But, you know, those things were fun, but they're so big and there's so much going on, you know, it's it's refreshing to be in this reinforced conference and focus on the security side. Sitting talks were like, You have people getting into kms and like some of these really pivotal tools. Yeah, it's been really, really >> get down and dirty here. Yeah, And people talk to, you know, approachable >> without, like, having to deal with all of Amazon, right? I can focus on, like, this one little >> portion reinvent you kidding? Walked through the hallways just like >> yeah, I mean, Well, where one hotel Are you gonna >> be at that point now, right? Yeah. >> Okay. So I gotta ask you about the dev ops question. We've been commenting yesterday day Volonte, who is on his way in. He and I were talking with a lot of si sos and a lot of practitioners. And the conversation generally was security needs to catch up to Dev ops and to pay who you talk to. They may or may not believe that way. Think that to be true. We think security now has the level up with the speed of Dev ops from his agility things that are highlights. For example, you guys have What's your take on that when someone says, Hey, security's got to catch up the devil Is it really catching a prism or transformation? What's your view on this >> will be like when you say catching up like it takes a negative. You know, I don't want to be negative there on DSO. I feel like it's a transformation. That means the same thing of going from the data center as as just as an operational engineer to Amazon is, there wasn't catching up. It was you just changing everything you do and how you think. And I think you know that's That's the same thing that a lot of security people I've seen struggle with was their success. Life are the ones that have gone, and I understand that, like, >> what do you think is the most important story happening in this world security cloud security screen general that should be covered by media that should be covered by the industry that is covered him should be amplified Maur or isn't covered and should be talking about what's the what is the most important stories that should be told. >> Well, so again, you know, I'm a fundamental layer, so things to me that I are always over shouted or like, you know, just encryption, right? I mean, everybody's like train encryption on. But, you know, I feel that talks I've gone to today or deeper dives into that. I feel like, you know, the kms product of Amazon. I feel like is a very powerful product that isn't super talked about. It's been nice here because they talked about 100 like you go to reinvent you don't really see a lot of kms type things are crowded, just them. And, you know, I think it makes some of those very difficult products to run in a data center very easy. You know what you hear on the security side is unsecured, as three buckets are like. Security groups are in conflict. Configure it incorrectly. And you know, no one knows that commercial. Everyone knows that. You know Elasticsearch not turned into a new s three right compromises You choose your database of choice of public. But for me, I think it's like a part that I feel is missing with Amazon is the ease of use of like, clicking a button. And >> now I have >> full Aurora encryption by default >> and the service you can just turn on what's next for you guys. Give us a peek into some of the things they're working on. What excited about? >> So I mean, we're making Ah, big thing is, you know, so we spend a lot of building now we're kind of going back and really kind of wrapping are a lot of our compliance is so zip it is a hole has been working towards a lot of stock to type compliance, seize on things like that. So, you know, we've been working through governance and no deploying. You know, software that kind of is more actively watching our environment and alerting us or helping us make sure we're staying at C. I s type benchmark so that you know, when my boss comes to me and says, Show me that we're doing this, I can just say, Oh, here's dashboard. So we were really not like via more secure State is a big, big product that we're working with right now. We leverage cloud health and those kind of the two external vendors that we've really partnered with. And so, you know, this year's been adopting those into the system. That's when the eight of us side, you know, we still just run Cooper Nettie. So there's a lot going on in the Cuban aunties ecosystem that we're also working on. So, like, service, mash and things of that sort like, How can I take this idea of security groups in this least trust model infrastructural e up to kubernetes, which by default this kind of flattened open. And so, you know, we've been exploring envoy and sdo linker D or write our own, you know, you know, and looking through those things and and then again wrote, making more robust CCD pipeline. So container scanning vulnerability, protecting our edge way running cloudfront wife for a while. But, you know, a lot of this year's gonna be spent, you know, Evaluate Now you know, we deployed a lost about 10 and got it turned on right because it works. But diving more deeply into like some of the autumn mediations >> have a fun environment right now, is it? You can knock down some core business processes, scale them up, and then you got the toys to play with the open source front. You got kubernetes really a robust ecosystem. They're just It's a lot of fun. >> Yeah, Criminal has definitely been exciting to play with >> advice to fellow practitioners and platform engineers because, you know, you guys been successful with transmission A the best. You got your hands on a lot of cool things. You got a good view, the landscape on security side of the deaf, upside for the people out there who were like they want to jump in with a parachute open. Whatever makes you that nervous, Some people are aggressively going at it hard core. Some have cultural change issues. What's your invite? General advice to your >> fellow appears My advice is just jump in and do it right. I mean, you know, don't be afraid. I mean, we had a really fast transformation, and we failed a lot very fast, and we weren't afraid of it. I mean, you know, if we weren't failing, we weren't doing it right. You know, in my opinion, right. We had to fail a few times a year. I was gonna work. And so I think, you know, don't be scared to jump in and just build, you know, right the automation. See what it does. Run some tests against it. >> You know, it's almost like knowing what not to do is the answer. Get some testing out there, get his hands dirty. >> What's gonna work for you? What's gonna work for your business? And the only way you're going to do that is to actually do it. >> Showed up in specialized Colby. Thanks for coming and sharing the great insight. Kobe Alan, platform engineer for Zip Whip Great company here. The Cube. Bring all the action. Extracting the signal from the noise. Great insights. And here, coming from reinforced here in Boston, eight dresses. First conference around. Cloud security will be right back after this short break

(techno music) >> Announcer: Live from Las Vegas, it's theCUBE. Covering Dell Technologies World 2018. Brought to you by Dell EMC and its Ecosystem Partners. >> Welcome to Las Vegas everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm here with Stu Miniman and this is the inaugural Dell Technologies World and Pat Gelsinger's here, he's the- >> Hey, great to be with you today, >> Dave: the CEO of VMware, awesome to see you, >> Oh, thank you. >> Our number one guest of all time, this is our ninth Dell/EMC World and your 900th CUBE interview, But it never gets old Pat. It's really a pleasure to see you. >> Oh it's always fun to be with you guys. Thank you for the chance to spend some time on theCUBE, you've come a long way. >> So, thank you for noticing! So, you were the first, and people are recognizing this, to really sort of call the boom in the data center. We certainly have seen it with cloud, and we saw a little bit with data and big data, and now digital transformation, but well over a year ago, you said, we have tailwinds, it just feels right, so good call. >> Yeah, hey thank you, and you know clearly like the IDCs, Gartners, you know, they began last year, 2% to 3% growth, I said no, I think it's at least 2x that, and we ended of the year almost 6% growth in IT, and everybody's raised their forecast, and I think they're still a little bit conservative, and I think in this period, where technology is becoming more pervasive in everything, every business is becoming a tech business, every area of every business is becoming influenced by tech, and as a result, hey I think we're going to see a long run of tech strength and every company in tech is going to benefit and those that are well-positioned are going to benefit in a big way. >> Yeah, you see, you called it, "tech is breaking out of tech" >> Yep, yep absolutely, right, you know, we're no longer that little IT thing stuck in the back corner making sure your mail runs, it's now everything. You know, back office has become front office, right. You know, every aspect of data becomes mission-critical for the business. As some have called it, you know, data is the new oil, right, in the future. And it really is thrilling to see some of our customers, and Michael had a few on stage this morning doing really pretty cool things. >> Well VMware is on fire. I mean, it's only 10% of Dell's revenue, but it's half, it generates half of its operating cash flow. Obviously we love the software business, of course. Talk about your business, the core is doing really well, you got NSX crankin', vSAN cranking, the cloud now, there's Clarity in cloud, give us the overview of your business and give us the update. >> Sure, and as I say, you know, there's three reasons we're doing well. You know, one is our strategy is resonating with customers, and you know, when you got strategic resonance with customers, you're not in the purchasing department, you're in the business units, the CIO's office. So strategy is resonating well, across what we do for private cloud, what we're doing for public cloud, what we're doing for end user and workforce transformation, our security strategy, every aspect is resonating. You know, second, we're executing well. And I'll say, you know, your good strategy, you're executing it well, and you know, clearly the Dell momentum has helped us. We're ahead of schedules on the synergies that we've laid out, and that's been a powerful accelerant. It was like we're doing well, you know, and you put some turbochargers on, whoa, you know this is going, and then finally as we said, it's a good market, right. And well-positioned tech companies are benefiting from that. So across our product families, you know, NSX, vSAN, and HCI, you know, our cloud management is really performing, the end user computing, you know, all of these seeing, you know 30, 50, 100 percent growth rates. You know, my overall cloud business, you know, VMware is growing in the teens you know, my cloud business is growing in the 30s, and way ahead of the growth rate of the business, so pretty much everything that we've laid out is firing on all cylinders. >> Pat, I think most people understand some of the products of VMware. I think it's, you know, 20 years now, since server virtualization laws You've, you know great momentum with NSX with vSAN, wonder if you could talk a little bit about the digital platform though, you know how does VMware look, you know, for the next five to 10 years, fit into the Vision 2030 like Michael was talking about. >> Yeah, yeah, you know very much, you know, as I say, you know, our objective is to be the essential, ubiquitous, digital infrastructure, right. Where you know, this idea, you know, essential. You know we run this mission critical stuff and increasingly we're seeing businesses put their crown jewels running on VMware. You know, 'cause we ran a lot of the stuff of the past, we'd run your SharePoints, your Outlooks, and so on, but now, they're putting core banking on us, you know, core transactional platform. They just say, you are essential, ubiquitous, our strategy is to move all the way to the edge, and the IOT use cases, into the core networks of our service provider partners, You know, to as I say, build these four clouds, the private cloud, the public cloud, the telco cloud, and the NF or the IOT cloud. All of those on a common infrastructure, that enables applications to build on and leverage all of the above. So you know, we're increasingly ubiquitous, digital infrastructure, meaning that they can build their applications from the past as well as in the future on us. And as we're partnering with Pivotal with our PKS strategy, reaching more to the developer, right, and delivering that infrastructure for the next-generation apps, and of course the dirty secret is, is that almost all of the cool new apps are some ugly combination of new and old. And if we can give a common operational security management and automation environment that transcends their cool new container, and function as a service, but combine it, in a consistent operational and security environment with today's infrastructure, oh, that's like the big easy button for IT. Got it, we could take you to the future, without giving up the past. >> We hear from our, you know, CXOs, in our community, in our audience, they really, they want to get digital right. So my question to you is, what kind of conversations are you having with executives around getting digital right? >> Uh-huh, yeah, and lots of those things are, you know, like just with a big media company, was with a huge Bank, on the phone with a big consumer goods product last week. You know these interactions occurring, you know like you say they want to get it right. And with it we're seeing the conversation shift, because a lot of it used to be, you know best of breed. Oh that looks good, and I'll stitch it together with this, and maybe I'll put it that, and a lot of their bandwidth was being put to putting the pieces together, and we're saying no, right. What you going to do is have robust infrastructure. Increasingly rely on fewer, more strategic vendors. It's my job to put it together, so you can take your investments and put them into the applications and services that really differentiate your business. And this is becoming a sea change in how we work with customers and say, okay, yeah I can't stitch all these pieces together, I can't have a hundred security vendors, I must rely on fewer vendors, in much more strategic ways. And in that, obviously we're benefiting from that enormously and they're expecting us to step up like never before, to be a partner with them, and it really is a thrilling time for us. >> So that simplifies all the complexity on there, and at least in concept. Who's leading this charge? Do you discern any patterns of the guys that are getting it right, versus the guys that are maybe struggling, or maybe complacent, specifically in terms of leadership? >> Yeah, and it's super, super interesting, because I find leaders in every industry, right? You know, you find leaders and laggards in those, I had one customer not a lot, long say, "Hey is that virtualization stuff, can I really rely on it?" It's like, ding dong, you know, you're now the trailing edge of technology, but for every one of those trailers, we're seeing those front end customers, and you saw some of them on stage this morning. Where they're just really going and saying, boy we are now ready to ante in, in a big way. We're seeing that in car companies. We're seeing that in financial services companies. We're seeing that in supply chain companies. And some of those are now really seeing these startups now putting pressure on their business for the first time, and they say no, we got to innovate in a very aggressive way. And for that, you know, the Dell Technologies family, you know all of us coming together, you know with our, each skills and focus areas, but together being able to present that holistic solution that says, that's right, we can lead you on digital transformation, we could change your infrastructure, we can build-in security, we could transform your workplace, we could take you to the multi-cloud future, we got it. >> Pat, there was one of the things that caught my ear, Allison Dew, when she was talking about the Dell Technology Institute, said that, together you're going to become a force for good. I know that's something that's near and dear to your heart, >> Pat: Yeah. >> So, maybe, you talked about the tech, and the security and everything, what about the Dell families as a force for good out there? >> Yeah, and I've described this era, and I've said there's four superpowers. You know, technology superpowers that are bigger than any of us, right. And the four I described, you know, mobile. The ability to reach anyone, over half the planet is now connected. Cloud, the ability to scale as never before. AI, the ability to bring intelligence to everything, and IOT, the ability to bridge to the physical world everywhere. And those four are really reinforcing each other, right? They're accelerating each other, as Michael said, you know, "Today, the fastest day of your life. "Today, the slowest day of the rest of your life, "for tech evolution." And we see them just causing and accelerating each to go, as I mentioned in my talk this week at the Grow Awards in Silicon Valley, in 1986 I was making the 486, a great AI chip, right. It's like, what? 31 years ago? And now it's a success because the superpowers are coming together. The compute is now big enough, the data is now volumous enough, that we can do things never possible before. But with that, technology is neutral. The Gutenberg printing press did the Bible, you know, Luther's Bible, it also prints Playboy. It sort of doesn't care. Technology is neutral. And it's our job as a tech industry to shape technology for good. You know that's our obligation, and increasingly we need to be involved in, and shaping, legislations, policies, laws, to enable tech to be that force for good. >> Pat, you mentioned kind of the speed of change in the industry. You're a public company with you know, a lot of employees, how does, internally, how do you keep up with the pace of change, keep inspiring people, get them working on the next thing? You know, Michael talked about going private was one of the things that would help him restructure and get ready for that, so maybe discuss that dynamic. >> Well, you know and for us, you know, as a software company living in Silicon Valley, we feel it every day, right. I'll tell ya' you know, we see these startups, that are hovering around our people, and our buildings, and they got ideas, you know, so we're synthesizing those ideas. We have our own research effort, our advanced product efforts, we're engaging, you know, and thousands of customer interactions per day. And ultimately, it's my job to create a culture that enables my 8,000 software engineers to go for it every single day, right. Where they are just, you know, they love what we do as a company, they love who we are as a company, our values. And then find ways that we enable our teams to, what I say, innovate in everything. Not just in R and D, but how we sell our products, how we support our customers, you know, how we enable these new use cases. We have to innovate in everything, if we're going to keep pace with this industry, and to some degree, I think it's almost in the water in Silicon Valley, right. You know yeah, you got some crazy master's student coming out of Stanford, and he thinks he's going to start up a company to displace me. It's like, what are you talking about? But we feel that every day, and as we bring those people into our environment, creating that culture that allows everybody to innovate in everything, >> So it's hard to argue that things aren't getting faster, that speed, but speed is an interesting question. When you think about blockchains, and AI, and natural language processing, just digital in general, there's a lot of complexity in terms of adopting those things. So speed versus adoption. What do you see in terms of adoption? >> Yeah, you know in a lot of these things like, you know, you look at a technology like NSX, cool, breakthrough, you know we're five years old now, almost on NSX, right? Since we did the Nicira acquisition as a starting point, 4 1/2 years on NSX, and some of these things need to be sedimented, as I describe it, into the infrastructure. Hardened, you know when you've really proven all of the edge cases. You know, those things don't move every day. >> Dave: Right right, fossilized, Furrier word, >> Yeah, you know there is, you know similarly with vSAN. Boy, these edge use cases, data recovery, pounding on the periphery of failure cases, disk drives, failure modes on flash drives, some of those things need to be sedimented, but as you think about those layers, always it's you know, how do you sediment? How do you standardize? And then expose them as APIs and services to the next layer. And every layer as you go up the stack gets faster and faster right, so as somebody would consume the software-defined data center, they need to be able to do that pretty fast. You know, how can I make, you know VM, we just released 6.7. Which reduced by an order of magnitude the time to launch a VM. You know, increase the, by 20x the amount of V-Center bandwidth, just so I can go faster. Not that I needed to go faster for VMs, I needed to go faster that I can put containers in VMs, and they need much higher speed of operation. So to me, it's this constant standardization, sedimenting, integrating, and then building more and more agile surfaces, as you go higher in the stack, that allows people to build applications where literally they're pushing updates, and seeing their CICD pipeline allow new code releases every day. I'm not changing NSX every day, but I am changing my container environment for that new app literally every day, and the whole stack needs to support that. >> Cloud partnerships, we talked last year at Vmworld, about the clarity that the AWS deal brought, of course you have an arrangement with IBM, you're doing stuff with Kubernetes, so, just talk about your posture with the big cloud players, and how that has affected your business, and where you see it going. >> Yeah, you know, clearly the cloud strategy, the AWS partnership, as I said, more than anything else, when we announced that, people moved their views of VMware. Oh, I get it, VMware isn't part of my private cloud, or part of my past, they're the bridge to the future. And that has been sort of a game-changing perspective where we can truly enable this hybrid cloud experience. Where I could take you and take your existing data centers, I can move them into a range of public cloud partners, AWS, IBM, you know, and be able to operate seamlessly in a truly hybrid way. Oh your data center's getting a little hot, let's move a few workloads out. Oh, it's getting a little bit cool, let's move some workloads back. We can truly do that now, in a seamless, hybrid multi-cloud way, and customers, as they see that, it's not only the most cost-efficient, right, it also allows them to deal with unique business requirements, geo-requirements that they might have, oh, in Europe I have to be on a GDPR cloud in Germany. Okay, we support, we have a right, you know here's our portfolio. Other cases, it's like, oh, I really want to do take advantage of those proprietary services that some of the cloud vendors are doing, you know. You know, maybe in fact that new AI service is something that I could differentiate my business on, but the bulk of my workload, I want to have it on this hybrid platform that truly does give them more freedom and choice over time, while still meeting unique compliance, legal, security, issues, as they've come to know and love from VMware over time. >> So to clarify, is it, are you seeing it as use-case-specific, or is it people wanting to bring that cloud experience on-prem, or is it both? >> It is truly both, because what you've seen, is many people, and if we were talking four years ago, you would've been asking me questions, "oh, you know I just talked to Fred, "and he says everything is going to the cloud" right. And people tried that student body right to the cloud of their existing apps, and it was like, oh crap, right? You know, it's hard to re-platform, to refactor those applications, and when I got there, I got the same app, right. You know, it's like, wow that was a lot of investment to not get much return, right. Now, they look at it and they say, "Oh boy, you know, "I can build some new apps in cool new ways" right, with these cloud native services. I can now have this agile private hybrid cloud environment, and I truly can operationalize across that in a flexible way. And sometimes we have customers that are bringing workloads out of native cloud, and saying, oh that's become too big in my operation role. You know I have different governance requirements. I'm going to bring that one back. Other cases are saying, "Oh, I didn't want to move it to the VMware cloud on Amazon", or you know, IBM, the migration service is really powerful. I want to get out of the data center. Other cases, they look at their cost of capital, and the size and scale they're operating, and says, "Hey, I'm going to keep 80% on-premise forever, "but I never want to be locked in, "that I can't take advantage of that, "should there be a new service." It really is all of the above. And VMware, and our Dell relationship, and our key cloud partners, now 4,100 cloud partners strong, it's really stepping into that, in a pretty unique and powerful way. >> And the key is that operational impact, as Pat is saying. >> So Pat, just one of the challenges we've heard from users we talked to is, if this was supposed to get simpler, virtualizing it, you know, I kept all my old applications. Going the cloud, there's more SKUs of compute in the public cloud than there are, if I was to buy from Dell.com. You know, in management, you know we're making steps, but you know it's heterogeneous, it's always add, nothing ever dies, how do we help customers through this? >> Yeah, and I do think they're, you know we're definitely hearing that from customers. And they're looking to us to make these things simpler. And I think we've now, you know, laid the templates for a truly simpler world. Right, in the security domain, intrinsic security. Build many of the base security capabilities into the platform. Automation, automate across these multiple cloud environments, so you don't care about it, we're taking care of it against your policies. Being able to do that, you know, and have an increasingly autonomous infrastructure that truly is responding and operationalizing those environments, without you having to put personnel and specific investments, right at that fundamental operations level, because it's too big, it's too fast, you can't respond at the pace the business requires. So I feel really good, we have some key innovations, you'll see us announcing. Now, we're going to talk at VMworld right? >> Dave: Oh absolutely. >> Okay, >> I will 100% be there, >> I have some cool announcements in this area, by VMworld as well, specifically, in some of these management automation, we see some of that applying, some new AIML techniques, to be able to help with some of those workload management and policy management areas. So, some really cool things going on to help these problems specifically. >> We've seen, oh we saw blog recently, about you guys working on some blockchain stuff. I know it's early days there, but it's exciting new technology. >> Yeah, and the blockchain stuff is what I'm really, really pretty excited about. We have some algorithmic breakthroughs that right now, you know, blockchain on a log scale basically scales at you know log or super log, right. Which meaning, it's problematic right. Is you get lots of nodes, right, you know the time to resolve those, gets to be exponentially expensive, to be able to resolve. We've come up with some algorithmic breakthroughs that drop that to near linear. And when people look at that, they sort of say, wow, I can make my blockchain environments much larger, much more distributed as a result, so as a result of some of that work we'll be increasingly making blockchain as a primitive. We're not trying to deal with the application level, you know for insurance, for financial, but we can increasingly deliver a primitive infrastructure along with vSphere in the VMware environment, that says yeah, we've taken care of that base issue. We've guaranteed it from a vendor you trusted, and you might remember there was a couple of breaches, of some of the blockchain implementations, so yeah, we hope to take care of some of those hard problems for customers and bring some, a good breakthrough engineering, from VMware to that problem. >> Well, it's great to see companies like VMware and you know enterprise plays, IBM obviously involved, into bringing some credibility to that space, which everybody says "Crypto, oh", they don't walk they run, but there's real potential in the technology. I want to ask you about a Silicon Valley question. >> Pat: Okay. >> Any chance I get, so if I broadly define Silicon Valley, Let's include, you know, Seattle. And we generally don't do that, but that's okay, but I'm going to. >> We'll take this, we'll take 'em in okay. >> it's technology industry, but technology industry seems to have this dual disruption agenda. We've always sort of seen, tech companies own this horizontal stack, you know, and go attack, and cloud, and big data, and disruption, but it seems like, with digital, you're seeing them attack new industries. Whether it's healthcare, or groceries, or media. What do you make of that? Can Silicon Valley, broadly defined, pull off this dual disruption agenda? >> You know I really believe it can, right. In that, I'm, you know, being part of it. I'm a huge optimist on it. I don't think it will be exclusive to Silicon Valley, right. You know, there's a tech community in Boston, that's a bit more focused on healthcare, right. Obviously, the cloud guys coming out of Seattle. You know, Austin, and you know, Texas has increasing, Research Triangle, when you go around the world, you see more places because, you know, in that sense, one of my favorite, you know, cartoons, is a picture of a dog at a terminal. I'm sure it was a Dell terminal, but you know, and the caption reads right, "On the internet, "they don't know you're a dog." Right, you know the point being, hey, when you're on the net, it doesn't matter where you are, right. And it enables innovation, whether that's Afghanistan, whether that's Bangladesh, whether that's Myanmar, you know any of those places, become equal on the net, and it does open up that domain of innovation. So I view it much more as tech is disrupting everything. And that's my theme of, "tech is breaking out of tech". Clearly the hub of that, is Silicon Valley. Right you know, that's the center where you know, every third door is a new startup, as you walk down the street. It really is an incredible experience. But increasingly, you know, that innovative disruptive spirit is breaking out of Silicon Valley, to you know, literally across the world. The Chinese think they might be the number one. You know, Europeans, oh sort of a renaissance in France, you know that we haven't seen for many years, and so on. And I do believe that it will continue to be technology, in this horizontal way you know, but increasingly, and I think you know, Amazon has led the way on this. We're seeing boy, we can disrupt entire industries you know, leveraging that. You know, Tesla in automotive, and Airbnbs. All of these are changing industries in fundamental ways, and I do not see that slowing down at all. You know, I'm thrilled to see like, you know, health care, right. Boy, I have not seen this amount of disruptive technology startups in healthcare, healthcare one of the lowest percentage of spend on IT. Can you imagine that? Right, you know at that level, and boy, we're starting to see that pick up. So industry by industry I think we're just getting started. >> And that's an industry that is really ripe for disruption. >> Pat: Oh my gosh. >> So Pat, we're going to hear about some of this, this afternoon at your keynote, I presume? Maybe show us a little leg there, and we'll wrap. >> Yeah, yeah. >> Dave: Alright, take it home. >> Hey, you know we're, today's keynote, obviously going to talk about the better together aspects, we'll update on vSAN and HCI and our strategy there, some of the cool things we're doing with Dell, and AirWatch Workspace ONE, and the client space. Yeah, we're going to talk about networking. I'm going to lay out our networking strategy, and we're going to give a teaser this afternoon of a broad set of networking announcements that we're doing this week. And hope to really lay out, what we think of, as the virtual cloud network of the future, and how the network is essential to that future. So, we're going to have a little bit of fun there, and you'll see me don the VR headset, right, and hey we're going to go into the virtual, virtual data center today, >> Virtualization inception. >> There we go. >> Well Pat, on a personal note, you've been a great friend of theCUBE, and we really appreciate that, and you've been an awesome guest, we saw you come from Intel with an amazing career, and we just see it going from there. So congratulations on all your personal success, your team success and continued. >> Love you guys, it's always great to be on theCUBE. You guys do a fabulous job, >> Dave: Thank you. >> For live tech coverage, and it really has been a lot of fun, and next year we're going to go party for your 10 year anniversary on theCUBE. >> Dave: That's right. Love it. >> Okay, cool, very good. >> Alright. >> Thank you, thanks so much. >> Good. Thanks. >> Alright, keep it right there everybody. We'll be back with our wall-to-wall coverage of Dell Technologies World. You're watching theCUBE. (techno music)

>> Announcer: Live, from Stanford University, it's theCUBE, covering the Women in Data Science Conference 2017. (upbeat music) >> Hi and welcome back to theCUBE, I'm Lisa Martin and we are at Stanford University for the second annual Women in Data Science Conference. Fantastic event with leaders from all different industries. Next we're joined by Finale Doshi-Velez. You are the Associate Professor of Computer Science at Harvard University. Welcome to the program. >> Excited to be here. >> You're a technical speaker so give us a little bit of insight as to what some of the attendees, those that are attending live and those that are watching the livestream across 75 locations. What are some of the key highlights from your talk that they're going to learn? >> So my main area is working on machine learning for healthcare applications and what I really want people to take away from my talk is all the needs and opportunities there are for data science to benefit patients in very very tangible ways. There's so much power that you can use with data science these days and I think we should be applying it to problems that really matter, like healthcare. >> Absolutely, absolutely. So talking about healthcare you kind of see the intersection, that's your big focus, is the intersection of machine learning and healthcare. What does that intersection look like from a real world applicability perspective? What are some of the big challenges? And can you talk about maybe specific diseases that you're maybe working on-- >> Sure, absolutely. So I'll tell you about two examples. One example that we're working on is with autism spectrum disorder. And as the name suggests, it's a really broad spectrum. And so things that might work well for one sort of child might not work for a different sort of child. And we're using big data and machine learning to figure out what are the natural categories here and once we can divide this disease into subgroups, we can maybe do better treatment, better prognosis for these children, rather than lumping them into this big bucket-- >> Lisa: And treating everybody the same? >> Exactly. >> Lisa: Right. >> And another area we're working on is personalizing treatment selection for patients with HIV and with depression. And again, in these cases, there's a lot of heterogeneity in how people respond to the diseases. >> Lisa: Right. >> And with the large data sets that we now have available, we actually have huge opportunities in getting the right treatments to the right people. >> That's fantastic, so exciting. And it's really leveraging data as a change agent to really improve the lives of patients. >> Finale: Absolutely. >> From a human interaction perspective, we hear that machine learning is going to replace jobs. It's really kind of a known fact. But human insight is still quite important. Can you share with us-- >> Finale: Absolutely. >> where the machines and the humans come into play to help some of these dis-- >> Yes, so a big area that we work on is actually in formalizing notions of interpretability because in the healthcare setting, the data that I use is really really poor quality. There's lots of it. It's collected in a standard of care everyday but it's biased, it's messy. And you really need the clinician to be able to vet the suggestions that the agent is making. Because there might be some bias, some confounder, some reason why the suggestions actually don't make sense at all. And so a big area that we're looking at is how do you make these algorithms interpretable to domain experts such as clinicians, but not data experts. And so this is a really important area. And I don't see that clinician being replaced anytime soon in this process. But what we're allowing them to do is look at things that they couldn't look at before. They're not able to look at the entire patient's record. They certainly can't look at all the patient records for the entire hospital system when making recommendations. But they're still going to be necessary because you also need to talk to the patient and figure out what are their needs, do they care about a drug, that might cause weight gain for example, when treating depression. And all of these sorts of things. Those are not factors again that the machine are going to be able to take over. >> Lisa: Right. >> But it's really an ecosystem where you need both of these agents to get the best care possible. >> Got it, that's interesting. From an experimentation perspective, are you running these different experiments simultaneously, how do you focus your priorities, on the autism side, on the depression side? >> I see, well I have a lab, so that helps makes things easy. >> Lisa: Yup, you got it. >> I have some students working on some projects-- >> Lisa: Excellent >> And some students working on other projects, And we really, we follow the data. My collaborations are largely chosen based on areas where there are data available and we believe we can make an impact. >> Fantastic, speaking of your students, I'd love to understand a little bit more. You teach computer science to undergrads. >> Yes. >> As we look at how we're at this really inflection point with data science; there's so much that can be done in that, to your point, in tangible ways the differences that we can make. Kids that are undergrads at Harvard these days grew up with technology and the ability to get something like that; we didn't. So what are some of the things that have influenced them to want to become the next generation of computer or data scientists? >> I mean, I think most of them just realize that computers and data are essential in whatever field they are. They don't necessarily come to Harvard thinking that they're going to become data scientists. But in whatever field that they end up in, whether it's economics or government, they quickly realize, or business, they quickly realize that data is very important. So they end up in my undergraduate machine learning course. And for these students, my main focus is just to teach them, what the science, what the field can do, and also what the field can't do. And teach them that with great power comes great responsibility. So we're really focused on evaluation and just understanding on how to use these methods properly. >> So looking at kind of traditional computer, data science skills: data analytics, being able to interpret, mathematics, statistics, what are some of the new emerging skills that the future generation of data and computer scientists needs to have, especially related to the social skills and communication? >> So I think that communication is absolutely essential. At Harvard, I think we're fortunate because most of these people are already in a different field. They're also taking data science so they're already very good at communicating. >> Lisa: Okay. >> Because they're already thinking about some other area they want to apply in. >> So they've got, they're getting really a good breadth. >> They're getting a really great breadth, but in general, I think it is on us, the data scientists, to figure out how do we explain the assumptions in our algorithms to people who are not experts again in data science, because that could have really huge downstream effects. >> Absolutely. I like what you said that these kids understand that the computers and technology are important whatever they do. We've got a great cross section of speakers at this event that are people of, that are influencing this in retail, in healthcare, in education, and as well as in sports technology, on the venture capital side. And it really shows you that this day and age, everything is technology, every company we're in, we're sitting in Silicon Valley of course, where a car company is a technology company. But that's a great point that the next generation understands that it's prolific. I can't do anything without understanding this and knowing how to communicate it. So from your background perspective, were you a STEM kid from way back and you really just loved math and science? Is that what shaped your career? >> So I grew up in a family with like 15 generations back, accounting, finance, small business, and I was like, I'm never going to do any of this. (Lisa laughs) I am going to do something completely different. >> Lisa: You were determined, right. >> And so now I'm a data scientist. (laughing) >> At Harvard, that's pretty good, they must be proud. >> Working on healthcare applications. So I think numbers were definitely very much part of my upbringing, from the beginning. But one thing that I think did take a while for me to put together is that I came from a family where my great uncle was part of India's independence movement. My role models were people like Martin Luther King and Mother Teresa and I liked numbers. >> Lisa: Yeah. >> And, like how to put those together? And I think it definitely took me a while to figure out okay, how do you deliver those warm fuzzies with like cold hard facts. >> Lisa: Right. >> And I'm really glad that we're in a place today where the sort of skills that I have can be used to do enormous social good. >> What are some of the things that you're most excited about about this particular conference and being involved here? >> So I think conferences like these, like the Women in Data Science, I'm also involved in the Women in Machine Learning Conference, are a tremendous opportunity for people to find mentors and cohorts. So I went to my first Women in Machine Learning Conference over 10 years ago, and those are the people I still talk to whenever I need career advice, when I'm trying to figure out what I want to do with my research and what directions, or just general support. And when you're in a field where you maybe don't see that many women around you, it's great to have this connection so that you can draw on that wherever you end up. Your workplace may or may not have that many women but you know that they're out there and you can get support. >> Now that there's so much data available, a lot of the spirit of corporations that use data as a change agent have adopted cultures or tried, of try it, it might fail, but we're going to learn something from this. Do you see that mentality in your students about being free or being confident enough to try experiments and if they fail, take learnings from it and move forward as a positive? >> I mean, certainly that's what I try to teach my students. >> Lisa: Yeah, yeah. >> My graduate students I tell them, I expect you to make consistent progress. Progress includes failure if you can explain why it failed. And that's huge, that's how we learn and that's how we develop new algorithms, absolutely. >> Yeah, and I think that confidence is a key factor. You mention that Women in Machine Learning Conference, you've been involved in that for 10 years, how have you seen women's perspectives, maybe confidence evolve and change and grow as a result of this continued networking? Are you seeing people become more confident-- >> Finale: I think so. >> To be able to try things and experiments. >> I mean certainly, as people stay involved in the field, I've noticed that you develop that network, you develop that confidence, it's amazing. The first event had less than a hundred people. The last event that we had had over 500 people. The number of people at just the Women in Machine Learning event, was the same as the number of people at the entire conference 10 years ago. >> Right. >> Right, and so the field has grown but the number of women involved that you see through this events like WIDS and WIML I think is enormous. >> And the great thing that's happening here at WIDS 2017 is it's being live streamed. >> Finale: Right. >> Over 75 locations. >> So it's accessible to so many people. >> Exactly. >> Yes. >> We're expecting up to 6,000 people on the live stream. So the reach and the extension is truly global. >> Which is fantastic. >> It is fantastic and just the breadth of speakers that are here to influence. You mentioned a couple of your key influencers: Martin Luther King and Mother Teresa. From an education perspective, when you were trying to figure out your love of math and numbers and that, who were some of the people in your early career that were really inspiring and helped you gain that confidence that you would need to do what you're doing? >> So I think if I had to pick one person, it was probably a professor at MIT that I interacted quite a bit in my undergrad and continued to mentor me, Leslie Kaelbling, who is just absolutely fearless in just telling people to follow their passions. Because we really are super privileged as was mentioned earlier: we lose our jobs, we can just get another one. >> Lisa: Right. >> Right? And our skills are so in need that we can and we should try to do amazing things that we care about. And I think that message really stayed with me. >> Absolutely. >> So you got research going on in autism. You mentioned depression. What's next for you? What are some of your next interests? Cancer research, other things like that? >> So I'm actually really interested in mental health because I think that that's, you know, talk about messy spaces, in terms of data. (laughing) It's very hard to quantify but it has a huge, huge burden both to the people who suffer from mental health disorders, which is like close to 15 percent, 20 percent, depending on how you count. But also it has a huge burden on everyone else too, on like lost work, on the people around them. And so we're working with depression and autism, as I mentioned. And we're hoping to branch out into other neurodevelopmental disorders, as well as adult psychiatric disorders. And I feel like in this phase, it's even harder to find the right treatments. And the treatments take so long to test, six to eight weeks. And it can be so hard to keep up the morale, to keep trying out a treatment when your disorder is one that makes it hard to keep up trying whatever you need to try. >> Lisa: Right. >> So that's an area that I'm really focusing on these days. >> Well then your passion is clearly there. That intersection of machine learning and healthcare. You're right, you're talking about something that maybe isn't talked about nearly as much as some of other big diseases but it's one that is prolific. It affects so many. And it's exciting to know that there are people out there like you who really have a passion for that and are using data as a change agent to help current generations and future to come. So Finale, such a pleasure to have you on theCUBE. We wish you the best of luck in your technical talk and know that you're going to be mentoring a lot of people from far and wide. >> Thank you, my pleasure to be here. >> Absolutely, so I'm Lisa Martin. You've been watching theCUBE. We are live at the Women in Data Science Conference at Stanford University, but stick around, we'll be right back. (upbeat music)