 Live from Las Vegas, it's The Cube. Covering IBM Think 2018. Brought to you by IBM. We're back at IBM Think 2018. This is day three of our wall-to-wall coverage. My name is Dave Vellante, and you're watching The Cube, the leader in live tech coverage. A lot of times in The Cube, we talk about how CIOs understood a while ago they just can't take their business and put it up into the cloud. Rather, they have to bring the cloud operating model to their data. So that's a topic that we're going to talk about with Dave Lindquist, who is a serious IBM fellow and vice president of Private Cloud at IBM, and Ajay Apte, who's a distinguished engineer of IBM Cloud Private. Gentlemen, welcome to The Cube. Good to see you again. Good to see you, Dave. So Dave, let's start with you. IBM Cloud Private, you heard my little narrative at the beginning. I think it's consistent with what your philosophy is, but what is IBM Cloud Private? What's it all about? Sure. Why don't we first start with there's public clouds, private clouds, hybrid clouds, and the ability to match your workload requirements with the particular cloud is very important. And having that consistency between private and public, so you have that flexibility, whether it's security, performance, cost aspects, regulatory, et cetera, is an important part of a multi-cloud strategy. With Private Cloud in particular, we introduced Private Cloud, the offering is called IBM Cloud Private, last year, and the demand has been through the roof of enterprises. What we're effectively doing is bringing cloud-native technologies right into the enterprise. It's really quite cool. We're bringing Kubernetes and containers into the enterprise, optimizing a lot of the core enterprise middleware so it runs on this optimized Kubernetes environment and then integrating it with the security and operational systems of the enterprise. You said you only recently really announced IBM Cloud Private and you talked about Private Cloud for years as did others, but others maybe had an offering, but the offering really didn't work. It really wasn't the cloud, it really wasn't the cloud experience. So what did you guys have to go through? I mean, it's not trivial to get that cloud experience. So maybe, RJ, you can talk about sort of how you got there and what you had to do to get there. Right, so we started with some use cases that we had in mind. So let me talk about three very core use cases that we started with. The first one is IBM has an enormous enterprise-grade production-ready footprint of middleware in our customer's data center. We wanted to bring that footprint to a containerized world to a cloud-based operational model. When I say enterprise-grade footprint that customers have today, they measure the success of that footprint in terms of KPIs, in terms of resiliency, in terms of reliability, in terms of security and compliance, these kinds of things. We wanted to bring the same qualities of services to a cloud, private cloud, kind of a model in a container world. That was probably one of the main use cases that we were targeting or that we started targeting. On the other side of the spectrum, the cloud-native microservices-based deployment. This is where most of the developers are interested in today. This is where really high-velocity, agility can be achieved. So that was the second use case that we were targeting. In both those cases, the key also is that customers already have existing tools and practices, those kind of things in the data center. The idea was to very seamlessly integrate into that set of tools and practices and even people within the data center while providing the same cloud operational model. And then the third main use case was around integration. By integration, there are various dimensions to integration. There's integration between the footprint that's running on-prem with the things that are not running in containers. They may be running in VMs or bare metal instances or maybe host systems running on our mainframe, like IGMZ systems. And then there will be other services maybe running as SaaS services in public cloud. So the integration scenarios basically expanded from our legacy footprint all the way into the public cloud SaaS kind of thing. So that integration was the third use case for us. So those three use cases, I would say, became the foundation of what we did over the last one year. So Dave, in thinking about bringing the cloud operating model to the data, what should clients expect in terms of that experience? Is it substantially similar, identical? Are there huge gaps? What do you tell people? Well, that's a good question. What they're going to experience is when you're using cloud environments, public cloud environments, what you'll see is your developers get rapid access to the content they need to start developing applications. And it fits very well into their agile DevOps life cycles, high iterations. And what you'll see is operations teams often referred to as site reliability engineering in a cloud model. They have access to all the efficiencies of cloud for deployment, scale, recovery, maintenance, all those types of pieces. So what a customer will experience is we're bringing those capabilities into the data center. But as Ajay pointed out, we're then able to run a lot of the core transactional data, analytic messaging workloads right on that environment. So the developers get rapid access to that type of content what they need, and the operations can leverage those capabilities on a cloud infrastructure. So that's the experience we're going to get, matching up the enterprise requirements with the cloud native. Is the impetus to take that sort of, that proprietary data, that 80% of data Jenny Rometti talked about, that isn't searchable on the public web. Is the impetus to get leverage out of that data that they don't want to put into the public cloud? Or is it to modernize their applications and cut their costs, and there's probably both but I don't know if you can talk to those. There are many higher level type of scenarios and use cases. So one that Ajay went through was really modernizing your applications and extending with innovation. But as what Jenny talked about, and I think you probably had sessions earlier on IBM Cloud Private for data, what we're seeing is how we can bring many of the critical data services together from data science experience and data analytics and data governance and movement and management into this cloud technology so that it can be used against the data that's in the data center, within the enterprise, to start getting insights into that data and furthering their business. Ajay, I wonder if you could take us inside the development process, even the thought process behind how you approach this, the secret sauce, how you approach this challenge maybe differently than historically you've approached system design. Right, so since the whole idea of IBM Cloud Private is around cloud operational model, high velocity, agility, those are the things we are preaching to our customers, the very key principle here is using those in our development as well. Our development itself is built on the same open source DevOps tool chains, the cloud operational principles so that we can achieve the exact same velocity, agility that our customers are expecting to achieve with the kind of offerings that we are trying to make over here. So that's sort of the first key principle for us. The second principle is around production readiness. When we are expecting our customers to run production ready workloads with security, compliance, reliability, these kinds of things, the same principles apply back to the platform that they are going to use for running those workloads as well. So the first thing is we are our own customers. We have to apply the same principles to our platform so that customers can do the same thing. Our platform is sort of a layered model where we have Kubernetes Cloud Foundry as the containerization model, but we also have a plethora of IBM and non-IBM and open source middleware, software that's running on top of that and then we have customer applications running on top of that. So we have to make sure as we build this platform all these layers are taken care of in terms of how we can deliver a production-grade offering end-to-end. When we talk about Watson Studio with Jeannie mentioned yesterday running as part of ICP for data, for example. The idea of running that where it's not just about ICP running a database, it's about what happens to the life cycle of the data and how ICP gets designed to make sure the life cycle of the data can be managed in a containerized model. Those are the kinds of things that became very important for our philosophy. Having a little fun. Our development team rocks. They are incredible. What our organization has done is it's fully embraced all the Angel DevOps capabilities. It's all developed on a cloud environment. We actually use ICP in our development and in our private. It's weekly iterations, two-week sprints, and every quarter we have a major release. We've done that the last four quarters we've had a major release come out. It's really been exciting. One of the great things about shows like this is that you can't walk around without bumping into a customer. So my question Dave is what are they telling you? What's resonating with the customers in terms of the services We did what we consider a soft launch in June where we wanted to get some experience and feedback from users and operations and what we actually did is opened a open Slack channel with our users. So we had tens of thousands of downloads that came with that very first release and we got feedback continually on what they liked from content how they liked the environment the whole experience. In the beginning of the fourth quarter with all the middleware capabilities that content on the platform it just took off. We since that time we have upwards of 150 global accounts picked up IBM Private and started going through the deployment somewhere even going into production. The thing that resonates with them so quickly is they have so many existing workloads that they've been trying to really bring is this dev transformation trying to bring into cloud technologies and this creates a journey a path for them through application modernization and then adding all kinds of innovation with microservices to refactoring or even adding a Watson artificial intelligence services into the environment. I started off asking you where you got the motivation your answer was outside in started with the customers, looked at use cases having said that you kind of replicate and mimic to the greatest degree possible the cloud public cloud experience so there's a reference model there so when you think about what's next do you sort of hop over to your public cloud colleagues in the IBM cloud and have a little bake-off and see where do you get your motivation going forward your sort of roadmap ideas obviously the customers but do you benchmark yourself against public cloud to try to close that gap, how do you approach that? Sure, there are multiple dimensions customers of course is one of the important ones having a consistent story between IBM public cloud and IBM cloud private is an absolutely key principle for us, it's not just a requirement but it's not just about keeping them functionally consistent keeping them experience wise consistent but making sure that when customers embark on the journey of hybrid deployment in terms of doing my dev test in public and then moving to IBM cloud private for production or be a bursting scenario these kinds of things, customers not only want to run their application seamlessly they want performance they want network connectivity, they want secure connectivity, these kinds of things so that becomes another angle in terms of how we are growing this from we have public, we have private, we can build a seamless hybrid story today but how do we evolve that hybrid story and make sure that we can give them the same quality of services, just because you move your application from public private to public, if your data stays on private the performance is really impact, they suffer, how do you make sure that those kinds of things are taken care of when customers truly build that, so that's the second dimension of it that how do we really take the customers on the hybrid journey and the third important one is that customers of course are going to deploy on our cloud on other clouds, they will always have multiple clusters geographically distributed, how do we manage that entire footprint and give them the right views for deployment, management accountability, these kinds of things across that entire real estate what we generally call hybrid cloud management multi-cloud management and that's a really fundamental technical challenge presumably to create that similar capability that consistency, maintaining performance, you got a lot of challenges there, good thing these guys are rock stars alright Dave, we'll give you the last word if you had to summarize think 2018 in less than 10 words I would just say accelerate your transformation with cloud that's what I would say, leverage the technologies across IOT public, private, cloud AI, blockchain and accelerate the transformation awesome, Ajay Dave thanks very much for coming to theCUBE alright, keep it right there buddy we'll be back with our next guest you're watching theCUBE, we're live from IBM Think 2018