 from San Francisco. It's theCUBE, covering Red Hat Summit 2018. Brought to you by Red Hat. Hello, and welcome back. This is theCUBE's exclusive coverage of Red Hat 2018. I'm John Furrier, the co-host of theCUBE, with John Furrier, co-founder of Tech Reckoning, advisory firm. Next guest is Chris Wright, vice president and CTO chief technology office, Red Hat. Great to see you again, thanks for joining us today. Great to be here. Day one of three days of CUBE coverage again. Yesterday had sessions over there in Moscone South. Again, in classic Red Hat fashion, good vibes. Things are rockin'. Red Hat's got a spring to their step, making some good calls technically. That's right. Kubernetes, one notable, and CoreOS acquisition. Really interesting range, just gives, I mean, I think people are now connecting the dots on the tech, from the tech side, but also now on the business side, saying, okay, we can see now some wider market opportunity for Red Hat, not just doing its business, but Linux software, we're talking about a changing, modern software architecture for application developers. I mean, this is a beautiful thing. I mean, it's not just apps, but it's the operation side as well. So we've been at it for a long time. We've been doing something that's really similar for quite some time, which is building a platform for applications, independent from the underlying infrastructure. In the Linux days, that was x86 hardware. You get this heterogeneous hardware underneath, and you get a consistent standardized application runtime environment on top of Linux. Kubernetes is helping us do that at a distributed level. And it's taken some time for the industry to kind of understand what's going on. And we've been talking about Hybrid Cloud for years, and you really see it real and happening, and it's in action. And for us, that distributed layer around Kubernetes, which just lights up how do you manage distributed applications across complex infrastructure, makes it really real. It's exciting. It's also timing's everything too, right? I mean, good timing helps, evolution of the business. You always have these moments in these big ways where you can kind of see clunking going on, people banging against each other, and the glue layers developing, and then all of a sudden snaps into place, and then it just scales, right? So you start to see that. We've seen this in other ways, TCP IP, Linux itself, and you guys are certainly making that comparison, being Red Hat, but what happens next is usually an amazing growth phase. Again, small little and move the ball down the field, and then boom, it opens up. As a CTO, you have to look at that 20 mile stair now. What's next? What's that wave coming that you're looking at and the team that you have on Red Hat side and across your partners? What's the wave next? Well, there's a lot of activity going on that's beyond what we're building today. And so much of it, first of all, is happening in open source. So that itself is awesome. Like we're totally tuned into these environments, it's core to who we are, it's our DNA to be involved in these open source communities, and you look across all of the different projects and things like machine learning and blockchain, which are really kind of native open source developments become really relevant in ways that we can change how we build functionality and build business and build business value in the future. So those are the things that we look at, what's emerging out of the open source communities, what's going to help continue to accelerate developer's ability to quickly build applications, operations team's ability to really give that broad scale policy level view of what's going on inside your infrastructure to support those applications and all the data that we're gathering and needing to sift through and build value from inside the applications, that's very much where we're going. Well, I think we had a really good example of machine learning used in an everyday enterprise application this morning. They kicked off the keynote talking about optimizing the schedule and what sessions were in what rooms, using an AI tool, right? That's right. And so that's reality. As you look at, is that going to be the new reality as you're looking into the future of building in these kind of machine learning opportunities into everyday business applications that in the yesteryear would have just been some, I don't know, visual basic or whatever, depending on how far back you look, right? You know, is that really going to be a reality in the enterprise? It seems so. It is, absolutely. And so what we're trying to do is build the right platforms and build the right tools and then interfaces to those platforms and tools to make it easier and easier for developers to build what we've been calling intelligent apps or applications that take advantage of the data and the insights associated with that data right in the application. So the scheduling optimization that you saw this morning in the keynote is a great example of that. Starting with basic rules engine and augmenting that with machine learning and intelligence is one example. And we'll see more and more of that as the sophisticated tools that are coming out of open source communities building machine learning platforms start to specialize and make it easier and easier to do specific machine learning tasks within an application. So you don't have to be a data scientist and an app developer all in one. That's, there's different roles and different responsibilities and how do we build, develop, lifecycle manage models is one question. And how do we take advantage of those models and applications is another question. And we're really looking at that from a Red Hat perspective. And the enterprises are always challenged. They're always a laggard. And now cloud native speaks to both now, right? He's got hybrid cloud and now multi cloud on the horizon set perfectly up with open shifts kind of position in that kind of the linchpin. But you got, there's still two different worlds. You got the cloud native born in the cloud and that's pretty much every startup these days. And then you got legacy apps with containers. So the question is that people are asking is, okay, I get the cloud native. I see the benefits. I know what the investment is. The student upfront benefits are horizontally scalable, asynchronous, et cetera, et cetera. But I got legacy. I want to do microservices. I want to do serverless. Do I re-engineer that or just containerize? What's the technical view and recommendation from Red Hat? When you say, when the CIO says or enterprise says, hey, I want to go cloud native for over here, the new stuff, but I got all this old stuff. What do I do? Do I invest more re-engineer and just containerize it? What's the play? I think you got to ask kind of always why? Why are you doing something? So we hear a lot. Can I containerize it? Often the answer is yes. The different question might be, what's the value? And so a containerized application, whether it's an older application that's stateful or whether it's a newer cloud native application that's stateless and horizontally scalable and all the great things. There's value potentially in just the automation around the APIs that allow you to lifecycle manage the application. So the application itself is still continuing to change. We have some great examples with some of our customers like KeyBank doing what we call the fast moving monolith. So it's still a traditional application, but it's containerized and then you build a CICD model around it and you have automation around how you deliver and deploy into production. There's value there. There's also value in your existing system and maybe building some different services around the legacy system to give you access, API access to data in that system. So different ways to approach that problem. I don't think there's a one-size-fits-all. So Chris, some of this is also a cultural and a process shift. I was impressed this morning. We've already talked with two Red Hat customers from Aquari and Amadeus and Aquari was talking about, oh yeah, we moved 40 applications in a year to onto open shift and it turns out they were already started to be containerized and dockerized and oh yeah, that is standard operating procedure for that set of companies. There is a long tail of folks who are still dealing with the rest of the stuff we've had to do at the stack we've had to deal with for years. How is Red Hat and how are you looking at this kind of cultural shift? It's nice that it's real, right? It's not like we're talking about microservices as some sort of future Jets and sort of thing that's going to save us all. It's here today and they're doing it. How are you helping companies get there? Well, we have a practice that we put in place called the Open Innovation Lab. And it's very much an immersive practice to help our customers first get experienced building one of these cloud native applications. So we start with a business problem. What are you trying to solve? We take that through a workshop which is a multi-week workshop really to build on top of a platform like OpenShift, real code that's really useful for that business. And those engineers that go through that process can then go back to their company and be kind of the change agent for how do we build the internal cultural shift and the appreciation for agile development methodologies across our organization, starting with some of this practical, tangible and real. So that's one great example of how we can help. And I think part of it is just helping customers understand it isn't just technology. I'm a technologist, so it's part of me that feels pain to say that, but the practical reality is there's whole organizational shifts, there's mindset and cultural changes that need to happen inside the organization to take advantage of the technology that we put in place to build that. And the roles are changing too. Obviously the system admin kind of administrative, things getting automated away to a more operating role. I heard some things last week at KubeCon in Copenhagen, Denmark. I want to share some quotes and I want to get your reaction. This is the hallway, I won't attribute to names, but these were quotes. I need quote, I need to get away from VPNs and firewalls. I need user and application layer security with un-fishable access, otherwise I'm never safe. Second quote, don't confuse lift and shift with running cloud-native global platform. A lot of actors in the system already running seamlessly versus say a VMware running environment, running v-center, running in a data center is an example of a lift and shift. So the comments are one, perimeter-less cloud. You need to have some sort of security model. And then two, we did digital transformation before with VMs, that was a different world, but the new world's not a lift and shift. It's a re-architect of a cloud-native global platform. Your reaction to those two things and what that means to customers as they think about what they're going to look like as they build that bridge to the future. Security piece is critical. So every CIO that we're talking to, it's top of mind. Nobody wants to be on the front page of the Wall Street Journal for the wrong reasons. And so understanding, as you build a microservices software architect application, the components themselves are exposed to services, the services are APIs that become potentially part of the attack surface. Thinking of it in terms of VPNs and firewalls is the kind of traditional way that we manage security at the edge. Pardon at the edge, soft in the middle isn't an acceptable way to build a security policy around applications that are internally exposing parts of their APIs to other parts of the application. So looking at it from a application use case perspective, which portions of the application need to be able to talk to one another? And it's part of why something like Istio is so exciting because it builds right into the platform the notion of mutual authentication between services. So that you know you're talking to a service that you're allowed to talk to, encryption associated with that so that you get another level of security for data in motion. And all of that is not looking at what is the VPN or what is the VLAN tag or what is the encapsulation ID and thinking in layer two, layer three security, it's really application layer and thinking in terms of that policy. Which pieces of the application have to talk to each other and nobody else can talk to that service unless it's been understood that that's an important part for how the application works. So I think really agree and you could even say dev sec ops to me is something that I've come around to initially I thought it was a bogus term and I see the value in considering security at every step of build, test and deliver an application. Lift and shift, totally different topic. What does it mean to lift and shift? And I think there's still, some people want to say there's no value in lift and shift and I don't fully agree. I think there's still value in moving and modernizing the platform without changing the application but ultimately the real value does come in re-architecting and so there's that balance. What can you optimize by moving and where does that free up resources to invest in that real next generation application re-architecting? So Chris, we've talked about machine learning, right? Huge amounts of data. We've just talked about security, we've talked about multi-cloud. To me that says we might have an issue in the future with the data layer. How are people thinking about the data layer, where it lives, on-prem, in the cloud, think about GDPR compliance, all that sort of good stuff. How are you and Red Hat, how are you asking people to think about that? So data management is a big question. We build storage tooling, we understand how to put the bytes on disk and persist and maintain the storage. It's a different question, what are the data services and what is the data governance or policy around placement? And I think it's a really interesting part of the ecosystem today. We've been working with some research partners in the Massachusetts Open Cloud and Boston University on a project called Cloud Dataverse and it has a whole policy question around data. Because there, scientists want to share data sets. You have to control and understand who you're sharing your data sets with. So it's definitely a space that we are interested in, understand that there's a lot of work to be done there and GDPR just kind of shines a light right on it. It says policy and governance around where data is placed is actually fundamental and important. And I think it's an important part because you've seen some of the data issues recently in the news. And we got to get a handle on where data goes and ultimately I'd love to see a place where I'm in control of how my data is shared with the rest of the world. Certainly the trend. So final question for you, open source, obviously greatness going on. More and more good things are happening in projects and bigger than ever before. I mean, machine learning is a great example. You're seeing, you know, not just code snippets, code bases being, you know, TensorFlow jumps out at me, a variety of others. What are you doing here this year that's new and different from an open source standpoint but also from a Red Hat standpoint that's notable that people should pay attention to? Well, one of the things that we're focused on is that platform layer. How do we enable a machine learning workload to run well on our platform? So it starts actually at the very bottom of the stack, hardware enablement. You got to get GPUs functional. You got to get them accessible to virtual machine based applications and container based applications. So that's kind of table stakes. Accelerate a machine learning workload to make it usable and valuable to an enterprise by reducing the training and inference times for machine learning model. Some of the next questions are, how do we embed that technology in our own products? So you saw Access Insights this morning talking about how we take machine learning, look at all of the data that we're gathering from the systems that our customers are deploying and then derive insights from those and then feed those back to our customers so they can optimize the infrastructure that they're building and running and maintaining. And then, you know, the next step is that intelligent application. How do we get that machine learning capability into the hands of the developer and pair the data scientists with the developers that you build these intelligent applications, taking advantage of all the data that you're gathering as an enterprise and turn that into value as part of your application development cycle. So those are the areas that we're focused on for machine learning. And some of that is partnering, you know, talking through how do we connect some of these services from OpenShift to the cloud service providers that are building some of these great machine learning tools, so. Any new updates on Tosly that was a success of Red Hat just in the past two years to see the growth, core OS acquisition, you got OpenShift, kind of good calls there, positioned perfectly. Analysts, financial analysts are really giving you guys a lot of props on Wall Street about the potential revenue growth opportunities on the business side. What's it like now in Red Hat? I mean, do you guys look back and say, hey, it was only like three years ago we did this and I mean, the vibes are good. I mean, share some inside commentary on what's happening inside Red Hat. It's really exciting. We've been working on these things for a long time and the simplest example I have is the combination of tools like the JBoss middleware suite and Linux. Well, they could run well together and we have a lot of customers that combine those, but when you take it to the next step and you build containerized services and you distribute those broadly, you got a container platform, you got middleware components, you know, even providing functionality as services, you see how it all comes together and that's just so exciting internally and at the same time, we're growing. And a big part of it. Customers are using it. Customers are using it so putting things into production is critical. It's not just exciting technology, but it's in production. The other piece is we're growing and as we grow, we have to maintain the core of who we are. There's some humility that's involved. There's some really core open source principles that are involved in making sure that as we continue to grow, we don't lose sight of who we are. It's a really important thing for our internal culture. So. Great community driven, great job. Chris, thanks for coming on theCUBE. Appreciate Chris Red, CTO of Red Hat, sharing his insights here on theCUBE. Of course, bringing you all the live action as always here in San Francisco, at Moscone West for Red Hat Summit 2018. We'll be right back.