 Live from Las Vegas, it's theCUBE. Covering InterConnect 2017, brought to you by IBM. Okay, welcome back everyone. We are live in Las Vegas at Mandalay Bay for IBM's InterConnect 2017. It's the cloud and big data Watson show that's all kind of coming together. This is theCUBE's three day coverage, wall to wall day two, coming to an end here. I'm John Furrier with my co-host Dave Vellante. Next guest is Dave Lindquist, IBM Fellow, Vice President of Cloud DevOps and Analytics at IBM, great to have you on theCUBE. Thanks for joining us. Thank you John, thank you Dave. So love to have the IBM Fellows on because we can then like get down and dirty, right? Get down and talk about the tech. I'll see Ginny's on stage today. I love the bumper sticker she has because she nails it. Enterprise Strong, Data First, Cognitive to the Core. So Enterprise Strong means there's a cloud readiness equation going on right now and we just came back from Google Next and hey, we got great technology, buy us. Oh, SLAs matter, you know, being Enterprise ready isn't always about the best tech. No, no, it's not. And it's about everything, it's the data, it's the machine learning, it's the software and also those table stakes going on in the enterprise. Unpack that for us. Sure, well I think a lot of what you just went through is at least part of the driving force between bringing ops into the dev space, this dev ops thing and we'll expand on that in a little bit. But one of the big pushes going on is really around site reliability engineering and how do you appropriately bring the skills together with the development teams to really set systems up in elastic scale, recovery oriented compute models so that you can scale out with the demand, you can recover from situations, you can recover from failures, you have a lot of redundancy built in the system. It takes a lot of time for teams to mature, to understand that aspect of delivering cloud services and delivering applications into a continuous available, a continuous available environment. What's IBM's formula right now is you guys ramp up and scale up the cloud, IBM cloud. You have the soft layer and that's now blue mix. So you have on the lower end of the stack you got to get that hardness infrastructure as a service and the platform as a service stuff. Then you start to bleed into the blue mix. There's all one blue mix now, but you got app developers, they want infrastructure as code, they want data as code, but then you got to have an uncoupling of set of services that look like one set of services. How hard is that and what are you guys doing specifically to talk to customers about the value you're bringing on both sides of that camp? You know, the hard workload, the focused hybrid to the creative sizzle of an app. Yeah, well, a lot in that question, there's a lot of parts there. One of the things that's clearly going on is taking that next step in loose coupling systems, creating more independent services that can scale elastically independently of each other, recovery oriented models and then presenting those services up at the layers you mentioned with the infrastructure layers, compute storage networking into the paths and container layers so that the application developers can very rapidly get the environment they need, compose the services that they need, like the runtimes, data, messaging, et cetera, as a loosely coupled system and then build their applications to be deployed into that environment. How much innovation is going on? You're starting to see now a new trend where there's more hardware engineering going into some chips and hardware configurations that's essentially software driven to offload maybe machine learning, some other cooler things that can assist some of the hard stuff that frees up more creativity on the software side. So machine learning is a great example. You start to see Intel and others start thinking, okay, let's put some stuff on a chip. You have 5G wireless, you got autonomous vehicles coming. A whole new hardware paradigm is kind of a merge with the cloud. How do you see that playing out from an innovation standpoint? How does that strategy play out from a cloud and IoT? To me, a lot of things that are so exciting that's going on in the cloud, part of the big driver in the cloud is this whole acceleration of innovation. How quickly can you get from instantiate an idea in field, iterate in field with your users towards a business outcome and as you hit those outcomes start scaling and expanding that out. And a lot of that innovation is building on some of the things that you mentioned, big data, cognitive, IoT, social, how you start bringing these things together. And so as you bring this together real time you clearly need just the exponential growth occurring in compute capacity, which is probably creating, not probably, it's creating all kinds of opportunities for breakthroughs and algorithms and breakthroughs in the hardware to support them. The other thing that we're seeing on, I get your thoughts and commentary on is how analytics is so compatible with the cloud because it really, you're seeing that sweet spot developing nicely and also with cloud native trend is booming, you're seeing cloud native, cloud native compute foundations got big traction and then the analytics, people have no problem putting that in the public cloud but yet they want the hybrid over here for some of this stuff. So the workloads are starting to settle into their swim lanes. Your thoughts on the DevOps equation as analytics moves through the cloud, not exclusively but for the majority cases and this cloud native trend that's coming down the pipe. Yeah, so break that down in a couple of pieces, the cloud native trend as well as the analytics trend. Cloud native trend, what you see is a lot of development with microservices and part of what makes that so exciting is the culture of the teams now they come together. You're basically seeing small teams, small integrated teams, often called two piece of teams or squads where you'll pull together designers with developers with tests, with data science, with business insights, business strategy into a team that then works together through the whole lifecycle, iterating incrementally and delivering in field to as they move towards that business outcome that they're trying to achieve. So what cloud native is doing is allowing that microservice model is really allowing many of these teams to work with relative autonomy but accountability for their service as it comes together to bring the system, the full system together. What we're learning is that, when you get a lot of speed like that, but then you need a level of analytics to help understand how that's coming together through that whole lifecycle. And what I mean by that is, how is the testing coming along? So everybody needs to start adopting more continuous testing from unit tests, all right performance testing, availability, right into security testing. So you start running basic simple analytics where you start gathering on how the teams are doing in the continuous testing and you can start setting soft and hard gates. Example, a soft gate might be code coverage is dropping. So send an alert to the team to say you got to step up the code coverage. Hard gate might be a security scan failed. So stop the deploy. And so that's a basic set of analytics but the fun areas to me, the exciting areas we're starting to apply much more sophisticated models are in understanding code health and how the teams are actually working together. So you start developing models. It's almost like team chemistry and coding working together. It's like, hey, you guys are good. You're in the zone. You're in the coding zone. But this is a good point. I want to highlight, just stop on that one point. I want to just drill down. I think that you nailed something that we've been kind of teasing out and you put it into words. The cloud native trend around microservices, you mentioned teams working together. Maybe some shared analytics and kind of code health, team, scoreboard or whatever. This is way beyond agile. I mean, agile has been a term that's been talked about inside companies. Hey, let's be agile. You're talking about a fundamental industry reconfiguration of players. So this is like a whole nother ball game. Yeah, to me it builds on agile. What's going on? It does build on, but it goes way beyond. And even the early thinking in DevOps, I think we're really pushing the envelope when we still call it DevOps because we're thinking of the broad life cycle of design practices. How do you begin to understand your users and what you're trying to accomplish with your users? Then you get into continuous integration, delivery and testing. But then where it gets real interesting is you start instrumenting everything and including getting direct land of sight insight into how your users are using what you're deploying. And that causes the ability to pivot very rapidly, daily, weekly, into guiding where you're going to take your next iterations. To me, that's what's really taking this way past what you typically saw in an agile. So what's happening to this traditional IT function and how is it adapting? Is it bimodal? Is there a subtraction layer coming in? Is there an equilibrium being reached between old and new? How would you describe what's going on? Yeah, fascinating question. What I often see in most of the enterprises I work in is they have a couple of investments going on. They're on a journey, a dev transformation journey. And a lot of that is really at the core of its embracing dev ops. But what you'll see is there's groups really pushing the envelope in these teams with cloud native, microservice development really all about speed. How quickly can they take small teams, get the idea into market? But then what you also see going on is large sets of very valuable assets, data transactional systems. And how do you start embracing more and more automation to really reduce the cycle times, improve the service levels, and to effectively start taking costs out of that full equation, that full life cycle? So what you're seeing is a lot of automation coming into the existing IT environment. You're seeing a lot more of taking down one of the silos of ops in development teams. And that's going on in the core areas. And in the more cloud native area you're seeing is actually a common team put together. And they basically own the whole spectrum. They build it, they run it, the whole piece. You would think the competitive implications of this are huge without naming names. Are you at this point able to discern patterns where organizations that are implementing this type of approach are becoming more competitive, becoming more profitable, gaining share? Do we have enough evidence of that yet? Yes. And well Gene, we were talking about Gene Kim earlier, and you can see from a lot of the breadth of the studies he has that you'll see how much more effective and high performance you're getting out of teams that are really embracing the best practices of DevOps and it is translating into financial results. So you are seeing that bridge occur. But part of what you got me thinking about is where we were talking about earlier, that the analytics that we've been exploring in the team insights and how the patterns you see and how teams are interacting in their code and where are the core committers, the extended community and the extended community, the extended ring outside of that. You can begin to see patterns that are working well, patterns that are starting to have problems that might actually be an architecture issue. It's a self healing concept too, if you think about it. This is actually taking into like, social media is the same problem on Twitter, it runs with the same voice. And even you can have a zillion followers and not have any influence that have, you know, a hundred followers that have a lot of influence based on, that's no measure for that. You're getting at something that's more scoring oriented and analytical. That's interesting to me. We don't follow up on that maybe another time. The question I want to ask you, because I want to, I can't get out of my mind as you, because you mentioned the cloud needs got me kind of really riffing on this. We believe it's a multi cloud world, right? And there's going to be a variety of clouds, not a winner take all. And they're all going to have differentiation. But having the traverse clouds is going to be really, really important. So Kubernetes is kind of interesting to me because you're looking at Kubernetes really kind of coming in and saying, hey, we could actually be a factor in orchestrating and managing the sets of containers and microservices. So it's almost like a whole nother land grab is going on around Kubernetes because it's so delicate. Can you share thoughts on that? Because it's kind of nuanced. Kubernetes has got great traction in containers and microservices, but it's super important. Why is it important and why is it fragile or is it fragile in the sense of its importance and not to be forked or tweaked? Yeah, well, first it's growing very rapidly. The use of containers for development and building largely cloud native microservice applications is growing at a very rapid rate. And then the ability to set up these Kube clusters in different clouds to be able to take advantage of the characteristics or services that are in those different clouds, including maybe you want to set up a cluster near where your data is so you can have the processing local to that data. Maybe you want to set up clusters around certain security or privacy or regulatory policies. So Kube is really providing almost a platform-like layer for the containers that is very robust. I wouldn't say it's fragile. And but with that flexibility to setting that up and where you want to set up that. It allows customers to really figure out where to put workloads that matter. So IoT would be a great use case for this. IoT say, hey, you know what? This cloud is awesome at this and put that app over there and this one goes over here because it's got something over there that I like. But now you need to have, I mean is that kind of where, this is like interoperability of networking in like the 80s. I'm a 90s when that whole trend started booming is really this importance. Yes, yes. It's openness. Well, the openness is critical. The, a lot of what we saw in distributed computing and the connectivity between clusters will be critical. But I do want to get to that point you mentioned on the openness. To me, the openness is critical from a number of dimensions. One certainly for interoperability and portability but probably the most important is the rallying point for innovation. That you get these ecosystems and with open technologies which really is an open governance with open standards. You find a lot of creativity and innovation occurring within that base. And that to me is what really causes these environments to explode and take off. And if they can take that openness into the data level then you're going to have a perfect storm of innovation because now you got open source which is thriving and continues to be great. Tier one by the way. And you choose to invest so much and give back so much to the community. Not everybody does that but you've made a business case for that. Why, why that strategy? I mean it's IBM you would think, you know historically IBM very close but you are almost overly aggressive about your open source investors. Yeah and not even sure it's historical. It dates back a long time but quite a while ago we went to Linux. They were the main player in Linux. You go back obviously the internet itself, TCPIP, Linux, Java, Eclipse. Track record's amazing. All these industry breakthroughs, things that shape the industry are often at its core there were at critical places there was an open ecosystem an open governance, open technology that really enabled it to just expand and grow it. I think Blockchain is perfect for you guys right now. Blockchain is another great example and people might be saying oh a little bit early I think that bet is going to be playing well. If you take the open source and this whole digital value thing, very interesting. Well I mean final thought, what are you excited about right now? I mean as an IBM fellow you get the canvas within the tech space. Obviously a lot of it's kind of intoxicating these days. It kind of went down memory lane with some old ways but there's a ton of great new things happening. What are you excited about? I mean what's getting you buzzed up about the current tech scene? The things that are really I find fascinating, exciting now is the different ways we're learning to apply AI cognitive machine learning into the different systems. We just sort of covering it just a little bit in the DevOps space itself. But we're learning to apply it from the end of test to understanding how we can predict where we have problematic code files and how you would improve your test or skills to the other spectrum of how is the community actually operating? Is the community healthy? Is it growing? How are my projects and my teams working together? How healthy is that? Or are there issues that I have to start looking at? Do I have a design issue? An architecture issue? A squad issue? So I can start doing that. This is all, we're learning how to take in big data and apply machine learning to this to get these types of insights. And to me, that's just one spectrum of how we're applying it. But that's to me what's so exciting is how we're applying it. Some of the examples that were shown with blockchain and cognitive and an IoT and AI. Data's changing the game. The algorithms are coming out as more like libraries not as custom stuff. And then you got compute over the top. Exactly. It's like, I wish I was 15 again, you know? Oh man, I wish, what a great time to be in the tech industry as a computer scientist or any kind of science field right now. It is a great time. It's just a super time. Appreciate it, Dave. Thanks for coming on theCUBE. Dave LeQuiz, IBM Fellow, Vice President of DevOps in the Cloud at IBM, sharing his insight, that great job. IBM's coverage continues here at day two in theCUBE. I'm John Furrier, Dave Vellante. Stay with us for our wrap after the stroke break.