 Live from San Francisco, it's theCUBE. Covering IBM Think 2019, brought to you by IBM. Welcome back to Moscone North. You're watching theCUBE's live coverage of IBM Think 2019. This is day three of four days of coverage. I'm Stu Miniman, my co-host is Dave Vellante. We've been talking so much about multi-cloud this week that Pineapple Express has hit San Francisco. Heavy winds and rains, but we're safe and dry inside. They're handing out ponchos and making sure that everybody can still get all the information that they have. Happy to welcome back to the program, Bala Rajaraman, who's an IBM Fellow and Vice President with the IBM Cloud Group. Bala, thanks so much for joining us. Very nice to meet you. Very nice to meet you guys. Thank you again. Very good to see you guys. So it's always, and I mean this, an honor to be able to talk to the IBM Fellows. I've had the pleasure of working with a number of IBM Fellows and of course we've had many of them on theCUBE. It is not just an honorific. It means you've done the work. You've been with IBM for more years than what we'll mention on camera, just to protect you there. But Bala, we had you on the program a year ago at Think. Give us the update as to what you've been working on and as we're speaking right now, the IBM research keynote is going on and I love the connection between what happens at IBM and some of the pure research that happens at universities and that funnel of innovation that happens through the company. That's a great question. I'm glad to be back here and it's been a fairly eventful year, as you guys know. I worked on our public cloud. We worked with a lot of clients and we looked at kind of the dynamics of the market and what is the transition to take advantage of cloud technologies and there was certain, not just barriers, but certain opportunities in terms of looking at things like private cloud and you guys have done some really good work and some of the research there. So private clouds became a point of focus for me and over the last year, working with a lot of clients, the notion of hybrid became really important and hybrid is not just a cloud structure, it is how you actually build applications on top of it. So when you look at some of the announcements around things like Watson everywhere, it is not driven by just having Watson in different places but the use cases it addresses. So things like manufacturing, where you're bringing more intelligence to the edge to the manufacturing floor, but you take advantage of big data analytics on the cloud. How does that work together? How do you address a lot of the technical movements of data, et cetera? And so that was really the great opportunity and insights that we saw and that drove our multi-cloud and public cloud strategy. Yeah, you bring up a really good point. I mean, the application is, the reason why infrastructure existed is to run the application and the data is important and I think back 10 years ago, it was like, well, am I going to burst applications? Are they going to stretch between them and the dialogue has changed quite a bit. It's now with microservices architectures. It's not that my application spread, it's that pieces of applications could live different places. They can live in a multi-cloud. I sometimes might be spinning them up in a geography or time. So IBM has strong ties, has lots of applications that deliver and working in all of these, developer microservices environment. How's this, show me, tell us where the work's happening and what you're doing for users. No, it's a really good question. So I think we really see three movements here. We accept the fact and the market is validated in terms of hybrid cloud, which is you've got pieces running on-prem, you have pieces running on the edge, you've got pieces running on one or more cloud providers. So the hybrid multi-cloud landscape is really a preferred architecture. But that architecture also brings complexity. And the three dimensions of complexity that I see are one around programming models and integration. How do all of these components integrate together from a programming perspective? Because you're choosing different clouds for different reasons and how do those capabilities integrate together? The second element is data. You've got data moving to different clouds, you've got compute moving to data. How does data governance, how does data integration work? And Rob Thomas talked a lot about some of our differentiators there. The third element is managing the environment from a security perspective, from a compliance perspective, from a configurational consistency perspective, from an upgrade perspective, from an availability and monitoring perspective. These three dimensions and the amount of work we are doing in that context, not just in terms of the existing portfolio around integration, but when you look at the complexity of microservices, a number of entities, you really start bringing in elements of AI into the discussion. So how do you enable operations with AI? How do you enable data placement, categorization, governance with AI? So it is, even though it might seem like different technologies, I think bringing them together to solve this problem is perhaps one of the most exciting things that we can provide to the market. So Bala, when it was becoming clear that public cloud was going to be a force, way back when people with large estates on-prem started talking about hybrid, we use that term now, maybe they didn't use it then. But the notion as Stu was describing that you'd have some parts of the workload in public, some parts in private, maybe it is bursting, this was long before EDGE and the ascendancy of microservices and Docker and CoreOS and the like. And then it became pretty obvious to a lot of users, wow, this is really complicated and the use cases just don't warrant the business case. So these things have changed. You, we've seen the ascendancy of these other services. You just laid out three complexities, the programming models, the data movement, which is huge and then how do you manage all that? So how are the use cases evolving? Is the business case more compelling now today than it was 10, 12 years ago? Yes, and I think that's a really, really good question because it takes a problem to the next level. The need for hybrid always existed. It was impractical to look at very, very large complex workloads, transactional needs, to say there was a one solution fits it all, I can move it somewhere. I think expanding and taking advantage of different cloud capabilities is much more of a realistic scenario and a more pragmatic, cost-effective, and it meets many of the business cases. And that's how we got to the 20% though what Ginny was calling chapter one. Yep, so now we have chapter two. Now why is chapter two realistic? Why did, your question was very apropos meaning that there's complexity and when you open up the aperture to more choices, the complexity expands exponentially. What has been really central to it has been the notion of what is, what degree of consistency can I get across all of these elements? And open source, the emergence of things like containers and Kubernetes, not just from a runtime perspective, but from a manageability and orchestration perspective and giving you a foundation against which you can, the consistency that you can take advantage of is been the fundamental revolution of the last two years which has made that intractable problem that we had with multiple choices and the complexity there to become much more feasible. And so if you look at our strategy underpinning those three dimensions of programming models and integration data and management which are not complexities but realistic needs for enterprises to take things into production. The notion of an underlying open multi-cloud hybrid platform based on technologies like containers and Kubernetes and orchestrating across that is the fundamental transformation that has happened. And that is the exciting part is now if it's open, you create an ecosystem, you really address enterprise concerns from how do I build stuff in a consistent way and leverage skills in the market to all the way how can manage it to production goals and security goals. I think we are in the cusp of something that can really transform the way enterprises build applications. And that's what Jenny was mentioning when she said that we are very well positioned to take advantage of the hybrid transformation and the markets behind it. That is the technical underpinnings of why we think we can do it. I'm glad you brought up ecosystem because it's vitally important and you've got a few larger companies. I mean, wouldn't it be nice if we just say I just use one cloud? Well, that's not going to happen. Nope. That's not practical. You'd love it to be IBM's cloud, Amazon would love it to be their cloud. It's just not going to happen. So you have this complexity. Ecosystem is critical. You've only got a few companies that really have the resources to deliver what you describe and to attract the ecosystem. So specifically, can you talk about the ecosystem and how that's evolving from IBM's perspective? So, we're just peeling the onion and I think we're going through a good progression. When you look at development of an ecosystem, the ability to provide choice to an enterprise and the foundations on which it is, the ecosystem is built is very critical. And if you look at the history of ecosystems, it's been built on certain standard programming models or certain APIs. So Arvin keeps talking about things like TCPIP was the foundation of why the internet became kind of a platform. So in a similar vein, when you look at things like Kubernetes, the open standards around it, the ability through all of these orchestration and runtime capabilities to create a variety of choice and the set of choices work together and can be managed together, that is going to create an immense ecosystem. We're already seeing pieces of it, right? I mean, Kubernetes is becoming a model in which many providers are providing the same component across different clouds. You see the adoption of Kubernetes across different clouds. So rather than looking at an individual part of the ecosystem, it is how can we create a broad ecosystem based on open standards, open capabilities, interoperable standards, whether they are formal standards or they are de facto standards. That is what is exciting about this environment. And you're essentially saying that Kubernetes is sort of that analog to old reliable TCPIP here? Is that? Yes, to a certain extent. I mean, I think if I combine TCPIP, HTTP, DNS, how things work together, how things can be managed together, you're coming up with, you're moving up to the next level of coherent standards across every provider. And that set of standards, the things that made the internet work, Kubernetes makes applications work. So networks work together, now applications work together and data works together, which is really. That's a rat hole, Stu, but those are largely government funded standards, which that's a while dried up because people said, okay, hey, we're there. And now this is, you got open sources, this sort of new leverage. Open sources, the engine for innovation. And I think it's a circuitous way to get to that pithy phrase that says open source is the engine of innovation, but that is really the progressive logic that gets you to the fact that it's important. All right, so if we have a solid foundational layer, one of the things, if I think back in my career, 10 years or even 20 years, things like automation and intelligence in my environment, we've been talking about it for a long time. Can you explain why now 2019 is different and how some of these are actually coming to reality more than some of the efforts we've done in the past? That's a great point, because there are two interesting trends that are happening. One of them is the ability to build intelligent systems at scale is being enabled by the cloud. You have the emergence of standard platforms. Now it becomes an application game, which is how can I leverage the scale, the availability, and the models of innovation to solve really tricky problems, whether it is supply chains that are globally distributed or enterprises that need survivability in different ways all the way from the clouds to the edge. What are the new architectures possible? But this distribution has also caused complexity. And when you have complexity, you have to bring some of these new technologies into play, like AI and so on and so forth. And so the combination of these three events, cloud, the emergence of open standards that span multiple clouds, and the complexity it creates, but the answers to that complexity that also have emerged is like to me is a very critical point for innovation. I think the landscape is going to look completely different going forward. And I don't think you had the business case for automation, right? You remember, people were afraid of automation. It's like, wow, why should we really do this? We can handle this manually, but today with digital transformation, data, machine intelligence, and the cloud, you can actually make a significant business case to transform your business and drive competitive advantage that you couldn't make 20 years ago. You have no choice but to look at automation today because the scale and that everything's there. And go back to the notion of microservices. You're taking something that you could fence and you could apply certain prescriptive measures to keep it under control. Now you have microservices, you have SaaS systems, you have data that is being dispersed. You have computing that's being dispersed. The only way to take advantage of that agility is to create a different level of being able to understand the systems, secure the systems, and that is going to be driven by new technologies, completely new technologies. All right, so, Bala, you mentioned one of my favorite words, innovation. So, you know, what are you seeing in the cloud, both from IBM, from your customers, from your partners? Where is that incubation for some of those next trends? You and I, as we were prepping this, thinking about like Bell Labs back in the day or the space race, you know, where do we get those, you know, ancillary innovations that help transform industries? How will cloud impact that? I think there's two interesting questions there. One is how will cloud impact innovation? But more importantly, how will innovation impact cloud? Right, and both of these directions are important. So, cloud really gives you the ability to cloud. And again, I look at cloud as kind of in quotes cloud because it includes a variety of easy access to resources, the open source innovation, the ecosystem that gets built. All of them are drivers of innovation. And it gives a way to easily exploit that innovation. I see that as the fundamental value of cloud. Now, the interesting part is there's a whole bunch of other innovations, whether you look at the debater from Watson, or you look at quantum technologies. You look at some of the Watson capabilities that are in conversation. How do those start transforming existing processes? So, when you look at, for example, to me one of the exciting things about debater is when you can process incredible amounts of information, not only to provide insight, but to provide rational insights and rationalizable insights. It is a tremendous innovation. Can that be applied to topics like, why is my network having a problem? And can you actually debate with a system to isolate the problem? The amount of possibilities, when you look at those, how they transform, how you run your clouds, how you run applications in the cloud, how you work across the ecosystem, I think there's tremendous amount of potential. And I think, obviously, with things like quantum, solving a different class of problems, making it easily accessible, solving different kinds of security issues, the potential is the accessibility to innovation with the innovation and how it impacts the foundation that delivers that innovation. I think this is a great marriage right now. Well, I want to give you the final word, lots going on here at IBM. We've seen a year ago, we were like five or six different shows pulled together. We're here at the renovated Moscone Center, thousands of people walking around going to so many different sessions, diversity. Give us a key takeaway for you that you want people to have when they walk away from IBM Think 2019. So, to me, the two key takeaways are one, your observation that everything is coming together is really symptomatic of the change in IBM. We are bringing things together to address complexity, make complexity simple for our clients, to bring innovation to our clients, so that's number one. And that has to be done in an open, in an ecosystem across, not just providers, but across a whole, not only a partnership, but a resource ecosystem, a open source ecosystem. And the drivers of innovation that we are participating in and how we are going to influence that is something that I look forward to as well. So, that's the combination. And it's got to be done through code. I mean, it can't just be services and I know IBM knows this, right? Oh, yes. It's built, it's this company, there's a recent chapter on top of services, but that's a huge opportunity for IBM to take. It's deep industry expertise, codify it through software and code and deliver on that vision. That is an enormous opportunity. Exactly, and the opportunities for code are great because now it's really transforming what new code, what is the potential of code in this ecosystem. All right, well, Bala, really appreciate you coming back, sharing your body of effort that's happening to help pull together and help simplify this multi-hybrid cloud environment. Great, thank you very much, guys. Great to have you again. Thanks. All right, and we're here for another two days, helping to break down all the complexities, go through the nuance, speak to the thought leaders, the customers, the partners. Dave Vellante is my co-host for this segment. John Furrier is here, Lisa Martins here, and I'm Stu Miniman, and as always, thank you for watching theCUBE.