(upbeat music) >> Hello and welcome back to theCUBES coverage of Red Hat summit 21 virtual. I'm John Furry, host of theCUBE. We've two great guests here, returning back CUBE alumni here to give us their perspective. Dave Linquist GM VP of engineering hybrid cloud management at Red Hat. Joe Fitzgerald, general manager VP of the management business unit Red Hat. Guys, welcome back to theCUBE. Congratulations, Red Hat summits, ongoing virtual. Great to see you. >> Thank you, John. >> Thanks John. >> So I'd love to get the low down. A lot going on the productivity this year. Looking back from last year, a lot's been done and we've been in the pandemic now, now circling back a full year. A lot's happened- a lot of productivity, a lot of clear visibility on, on what's working, what's not, you guys got some great news. Let's just jump right into it. What's the big announcement? >> So one of the things that we announced here at Summit, John, is an expansion of our Red Hat insights brand. Basically we announced Red Hat insights for our RHEL platform back in 2015. Over the years, we've increased the amount of data and visibility into those systems. Here at summit, we've now announced Red Hat insights for both OpenShift, and for the Red Hat Ansible platform. So it's a pretty significant increase in the visibility that we have to the platforms. >> Oh, so can you repeat that one more time? So the expansion is through which platform style specifically? >> So Red Hat insights is a way that we connect up to different platforms that Red Hat provides. Historically it was for Red Hat enterprise Linux realm. We've now expanded it to the Red Hat, OpenShift family, the platforms as well as the Red Hat Ansible automation platform as well. >> So a nice broad expansion and people want that data. What's what was the motivation behind it? Was it customer demand? Was it more access to the data? Just, was it on the roadmap? What's the motivation- where where's this going? What's what's the purpose of all this? >> Well, I don't think customers say, Hey, please, you know take more data. I think it's customers say, can you keep me more secure? Can you keep my systems more optimized? Can you help me set more things to automatic? And that requires that you get data from these systems that you can auto tune on, auto- secure, auto optimize. Right? So it's really all those benefits that we get by connecting to these systems, bringing the telemetry data that config different kinds of information, and using that on customer behalf to optimize secure to the systems. >> You know, one of the biggest trends I think now for multiple years has been observability with cloud native, more services are being turned on and off enterprises are are getting a lot of pressure to be modern in their in their application development processes. Why is data more important than ever now? Can you guys take a minute to expand on that? Because this idea of telemetry across the platform is a very interesting announcement because you're turning that data into value, but can you guys expand where's that value coming, turning into? What is the value proposition? Where are people seeing the, the, the key key value points? >> Well, a couple of points, John, as you started out is in a hybrid cloud environment with cloud native applications and a lot of application modernization and the current progressiveness of DevOps and SRE teams, you're seeing a lot of dynamics and workloads and continuous delivery and deployments that are in public environments and private environments, distributed models. And so consequently, there's a lot of change in dynamics in the environment. So to sustain these high levels of service levels to sustain the security and the compliance, the ability to gather data from all these different points, to be able to get visibility into that data. It'd be able the ability to process that with various analytics and understand what when something's gone wrong or when an update is needed or when a configuration has drifted is increasingly critical in that in a hybrid cloud environment. >> So on the telemetry piece is that in open shift as well that that's supporting that as in there has that work. >> It's it's in OpenShift, as Joe mentioned, it's in braille it's in V2 Ansible and the OpenShift space we'd have an offering advanced cluster management that understands fleets of deployments, clusters, wherever they're deployed however they're running infrastructure public private hybrid environments. And it also collects in the context of the workloads that are deployed on those on those clusters to multi-question burn. >> I want to ask you guys a question. I get this all the time on theCUBE. Hey, you know, I need more data. I have multiple systems. I need to pull that data into one kind of control plane but I'm being pushed more and more to keep scaling operations. And this becomes a huge question mark for the enterprises because they, they have to turn up more, more scale. So this is becomes a data problem. Does this solve it here? How do you guys answer that? And what was the, what would be your response to that trend? >> Well, I think the, the thirst for data, right? There's a lot of things you can do with more data. There is a point where you can't ship all the data everywhere, right? If you think about logs and metrics and all the data it's too heavyweight to move everything everywhere. Right? So part of it is, you know, selecting the kind of data that you're going to get from these systems and the purpose you're going to use it for. And in the case of Red Hat, we take data from these different systems, regardless of whether they're deployed bring it in, and then we did predictive analytics against that data. And we use that telemetry that can take that health data right to do everything from optimize for performance or security costs, things like that. But we're not moving, you know, huge quantities of data from every system to Red Hat in order to, you know, pour through it. We are very selectively moving certain kinds of data for very specific purposes. >> Dave, what's your take on that because you know you got to engineer these systems. What's the optimized path for data? Do you keep it in the silo? Do you bring it together? What's the customer's view on, on how to deal with the data? >> Yeah. It is a complex problem. No doubt. You don't want it to be pulling all the data and trying to transmit all that data back into your analytics system. So you ended up curating some data, some of it you afford on often it's done under it will be done under control of policies. So that data that is sensitive, that should stay within the environment that it's in, will stay, but curated or alerts or information that's particularly relevant say to configurations, updates, any any of that type of information will go up into the analytics, into the insights. And then in turn, the alerts will come back down in a manner that are presented to the user. So they understand what actions need to be taken place whether there's automated actions or or they have to get approvals to maybe make an update to a certain environment. >> All right, you got telemetry, data power, the the advanced cluster management ACM. What's the overlap of the visibility and automation here. Can you guys talk about that? >> Well, let's say it's a great question, John what we'd like to do is we'd like to sort of separate the different areas. There's the seeing, right. And what's going on in these environment. Right. So getting the data analyzing it and determining what needs to be done. And then the, you know the recommendation of the automation. As Dave said, in a lot of environments, there's a process of either approvals or checkpoints or, you know evaluation of the changes being made to the system. Right. So separating the data and the analysis from the what do you want to do at this and making that configurable I think is really powerful. >> Yeah. I mean, that's, I mean I think that's the number one thing is like, you know everyone always asks, what do you optimize for do you optimize for the automation or the visibility? And I think, you know, there's always a trade-off and that's always interesting question David- love to get your thoughts. If someone asks you, Hey, I'm a I'm I have a team of people. What do I optimize for? The visibility or the automation or both? Is or is there a rule of thumb or is there a playbook? What w how would you answer that question? >> Well, there's a couple of things. I first, I think the, the ability to pull the data together to get visibility across the environment is critical. And then what becomes often complex is how the different disciplines, how the different parts of the system are able to work together on common understanding of the resources common understanding the applications. That's usually where systems start falling down. And so it's too siloed. So one of the key things we have with with our systems, particularly with OpenShift and row and with ACM and Ansible is the ability to have the common back lane and the ability to have a common understanding of the resources and the applications. And then you can start integrating the data around that common, those common data models and take appropriate actions on that. So that's how you ended up getting the visibility integrated with the automation. >> When you think about this, Joe about the security aspect of it and the edge of the network which has been a big theme this year and going into next year, a lot more discussion just the industrial edge, you know, that's important. You got to take all this into account. How do you, how would you talk about folks who are thinking about embedding security and thinking about now the distributed edge specifically? >> Right. So we thought it was complicated before, right? It goes up a notch here, right? As you have, you know, more and more edge applications I think at the edge, you're going to want automated policies and automated configurations in force so that when a device connects up to a network or is, you know analyzed that there's a set of policies and some configurations and versions that need to be applied to that device, these devices, aren't always connected. There's not always high bandwidth. So you basically want a high degree of automation in that case. And to get back to your early point there are certain things you can set like policies about security or configuration. You say, I always want it to be like this and make it so and there's other things where they're more you know, complicated, right. To, to address or have regulatory requirements or oversight issues. And those things you want to tell somebody I think this should be done. Is this the right thing to do? Is it okay? Do it, but at the edge you're going to have a lot more sort of lights out automation to keep these things secure, to configure. Right. >> It's funny. I was, some of the Ansible guys are talking about, you know code for code, changing code all the time and dynamic nature of some of the emerging tech coming out of the Red Hat teams. It's pretty interesting. You guys have going on there, but you know, you can bring it down to the average enterprise and main street, you know enterprise out there, you know, they're looking at, okay I got some public loud. Now I got hybrid. I'm going a hundred percent hybrid. That's pretty much the general consensus of all the enterprises. Okay. So now you say, okay, if I understand this correctly you got insights on REL, OpenShift and Ansible platform. So I'm, am I set up for an open hybrid cloud? That's the question I want to ask you guys does that give me the foundation to allow me to start the cloud adoption with an, a true distributed open way >> I'll I'll offer to go first. I think there's a couple of things you need in order to run across hybrid clouds. And I think Red Hat from a platform point of view the fact that Red Hat platforms run across all those different environments from the public cloud to on-premise and physical vert to edge devices. Now you have consistency of those platforms whether it's your traditional on REL, your container based workloads on shift or automation that's being turned in by Ansible. Those are consistent across all these different hybrid cloud environments. So reduces the complexity by standardizing those platforms across any and all of those different substrates. Then, when you can take the data from those systems bring them centrally and use it to manage those things to a higher degree of automation. Now you take an, another sort of chunk of complexity out of the problem, right? Consistency of getting data from all those different systems being able to set policies and enforce things across all those distributed environments is huge. >> Yeah. And then, you know, it fills in the gaps when you start thinking about the siloed teams, you know, the, the, I think one of the messages that I've been hearing out of Red Hat Summit in the industry that's consistent is the unification trend that's going on. Unifying development teams in a way that creates more of an exponential value curve rather than just linear progressions in, in traditional IT. Are you guys seeing that as well? I mean, what's your take on this? That's that piece of the story? >> Well, I think the shift that we've seen for the last few years actually quite a few years with DevOps and SRE is started to bring a lot of the disciplines together that you mentioned that are traditionally silos. And you're finding the effectiveness of that is really around many of the areas that we've been discussing here which is open platforms that can run consistently across a hybrid environment, the ability to get data and visibility out of this platform. So you can see across the distributed environment across the hybrid environment and then the ability to take actions in Bourse or update environments through automation is, is is really what's critical to bring things to to bring it all together. >> Yeah. I think that's such an important point, Joe. You know, I was talking with Chris right around and we we've covered this in the past red hats success with academics in the young people coming into in the universities with computer science. It's not just computer science anymore. Now you have engineering degrees kind of cross-disciplinary with SRS is SRE movement because you're looking at cloud operations at scale. That's not an IT problem anymore. It's actually an IT next gen problem. And this is kind of what, there's no real degree. There's no real credential for, you know large scale hybrid cloud environment. You guys have the mass open cloud initiative. I saw that going on. That's some really pretty big things. This is a, a change and, and talent. What's your, what's your view on this? Because I think people want to learn what what do I need to be in the future? What position? >> So John it's a great question. I think Ansible actually addresses a number of the issues you brought up, which is, you know historically there've been different tools for each of the different groups. So, you know, developers had their favorite set of tools and different, IT areas their favorite set of tools and technologies. And it was sort of like a tower of Babel. People did not share the same, you know sort of languages and tools. Ansible crosses both your your development test and operational teams. So creates a common language, now that can be used across different teams. It's easy to understand. So it sort of democratizes automation. You don't have to be deeply skilled in some, you know misspoke language or technology in order to be able to do some level of automation. So I think sort of sharing the same technology and tools I'd like an answer, more democratizing it so that more people can get involved in automating sharing that automation across teams and unifying those worlds is huge, right? So I think that's a game changer as well in terms of getting these teams work holistically integrated. >> Yeah. And there's also a better together panel on the Ansible and advanced cluster management session. Folks watching should check it out on on the virtual event platform on that point while I got you here on that point, let's let's talk about the portfolio updates for advanced cluster management for Kubernetes, what's new since the Ansible Fest, Ansible Fest announcements >> There's quite a bit that's been new since Ansible Fest. Ansible Fest well actually going back to Summit last year we introduced advanced cluster management. For years, we've been seeing the growth of Kubernetes with cloud native and clusters. And what ACM really allows enterprises to do is is scale out their deployments of OpenShift. Well, one of the things we found is that as you're deploying workloads or clusters or trying to take care of the compliance, the importance of integrating that environment with the breadth of capabilities that Ansible has in automation. So that's what we announced that at Ansible Fest following last year's summit what we've done is put a lot more focus on that integration with Ansible. So when you bring up, provision a cluster maybe you need to make some storage or security configurations on behalf of that cluster or if you're taking care of the compliance how do you remediate any issues with Ansible or one of the things that get shown a lot, demonstrate a lot with customers like is when you're deploying applications into production, how do you configure the network? Do the network configurations like a load balancer maybe a ticket into your service management system along with say a threat detection on your security. So a lot of advances with ACM and the integration with a broader ecosystem of IT, in particular with, with Ansible >> What's the ecosystem update for partners? And this has comes up all the time. I want to make sure I get this in there. I want it, I missed it. Last time we chatted, you know, the partner impact to this. You mentioned the ecosystem and you've got native Coobernetti's, non-native what's native to open. You guys have a lot of native things and sometimes it's just support for other clouds. So you start to get into the integration questions. Partners are very interested in what you guys are doing. Can you share the partner update on how they play and what impacts them the most here? >> Yeah. On the events, cluster management ACM front first with this integration with Ansible that actually allows us to integrate with the wealth of partner ecosystem the Ansible apps, which is huge. So that's, that's one, one space. And then the way ACM works, this policy desirous state model is we've been able to integrate with a large number of partners around particularly the security space model the service management space, where they, where we can enforce the use of certain security tools on the on the clusters themselves. So it's really opened up how quickly partner offerings can be integrated into the OpenShift environment at scale across all the clusters that you want, that you need to support it on what the appropriate configurations and policies >> I got to ask you on the insight side you mentioned the expansion across the platform. Now, if you go out and take out to the ecosystem, you know there's guard rails around governance how far can partners push their data in terms of sharing? That's something that might come up when you comment on that. >> Sure. So Red Hat, you know, takes, you know our customer data very seriously. We're a trusted partner to our customers. So the data that we get from systems we make sure that we are following all of the governance and oversight necessary to protect that data. So far, we have basically been collecting that data and using that data at Red Hat. Our plan really is to allow partners with the right degree of governance and control to be able to use some of that data in the future, under the right conditions whether it's anonymized or aggregated, things like that to be able to take that data and to add value to customers if they can enrich customers or or help customers by getting some access to that data without every vendor or partner, having to go out to systems and having to connect and pull data back. That's a pretty tough situation for customers to live with. But I think that fact that we're ahead is trusted. We've been doing this for awhile. We know how to handle the data. We know how to provide the governance. But our plan really is to enable partners to use that data ecosystem. I will say that initially what they had said about ACM and partners, Ansible has been working with partners on the automation side at a very large scale, right? So if you look at the amount of partners that are doing automation, work with us we have some pretty strong, you know, depth there. But in terms of working with partners, our plan is to take the data ecosystem, expand that as well. >> It's really a nice mix between the Ansible OpenShift and then REL, do you guys have great insights across now? I think the open innovation just continues to be every year. I say the same thing. It's almost like a broken record but every year it just gets better and better. You know, innovation out in the open you guys doing a great job and continuing and now certainly as the pandemic looks like it's coming to an end soon, post-pandemic, a lot more projects are being worked on a lot more productivity, as we said at the top. So to end the segment out I'd love to get you guys to weigh in on what happens next. As we come out of the pandemic, the table has been set. The foundation's there, cloud native is continuing to accelerate rapidly in the open OpenSource, going through them on another level. What's next what's, what's going to what's next for customers. Are they going to continue to double down on those? The winds they're going to shut down certain projects. What happens after this pandemic? How do people grow, Dave? We'll start with you. >> Well, I think, yes we all see the light at the end of the tunnel, John. It's great. And I think if a positive, is it really throughout this? We've been accelerated in the digitization and at modernization cross the board across industries. Okay. And that is really teaching all of us a lot about the importance of how do you start managing and running this at scale and securing this at scale. So I think what we'll see coming out of this is just that much more effort, open ecosystems. How you really bring together data across insights? How do you bring in increasing the amount of analytics AI to now do something turn that data into information that you can respond with and that in turn, close it, closing the loop with automation against or against your hybrid cloud environment? We're just going to see acceleration of that occurring. >> Awesome, great insights there. Open data insights, automation, all kind of coming together. AI. You don't have AI in your, your plans. Someone was Wall Street was joking. That's going to be the future stable stakes get listed on Wall Street. You got to have some sort of AI piece. They have great insight, Joe, your take on what's next? What, what what's going to what's going to happen as we come out of the pandemic? >> Yeah. We've definitely seen people, you know advance their digital transformation. And I don't think it's going to stop. Right? So the speed scale and complexity or just put more pressure on teams, right? To be able to support these environments that are evolving at light speed. So I think Red Hat is really well positioned and is a great partner for folks who are trying to get more digital, faster trying to leverage these technologies from the hybrid cloud to the edge. They're going to need lots of help. Red Hat is in a great position. >> Okay. >> You guys doing great work, Dave Linquist, Joe Fitzgerald. Great to have you back on again. Open, always wins. And as end users become much more participants in the open source ecosystem and user contributions and user interactions software at scale, it's now a new come next generation commercial environment, You guys are doing a great job. Thank you for sharing. Appreciate it. >> Thank you John. >> Thanks John. >> Okay. Red Hat Summit 21 CUBE coverage. I'm John Furrier getting all the action from the experts who've been there, done that living through it, being more productive and have bringing benefits to you being open source. Thanks for watching.

>> Narrator: 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 CIO's 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 Linquist, who's here. He's an IBM fellow and Vice President of Private Cloud at IBM and Ajay Apte, who's a Distinguished Engineer of IBM Cloud Private. Gentleman, welcome to the Cube. Good to see you again! >> Good to see you Dave. >> Thank you. >> 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. Well why don't we just 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, cross aspects, regulatory, et cetera, is an important part of a multi-cloud strategy. With Private Cloud, in particular, we introduce Private Cloud, the offering is called IBM Cloud Private, last year. And the demand has been through the roof at the 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. >> So as you said, you only recently, really, announced the 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 experience, so what did you guys have to go through... I mean, it's not trivial to get that cloud experience. So maybe Ajay, you can talk about, sort of, how you got there and what you had to do to get there. >> Right. 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 anonymous enterprise grade, production ready, footprint of middleware in our customer's data center. We wanted to bring that footprint to a containerized wall, 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 resilience, in terms of reliability, in terms of security and compliance, these kind of things. We wanted to bring the same qualities of services to a private cloud model, in a container model That was probably one of the main use cases that we started targeting. On the other side of the spectrum, the cloud-native micro-services based department. 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 kinds of things, 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 PrIM with the things that are not running in containers. They my be running in DMs or bare metal instances or maybe whole systems running on our main frame, like IBM Z systems, right? And then there will be other services, may be running SAS services in public cloud, so the integration scenario is basically expanded from our legacy footprint all the way into the public cloud SAS connector, 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 last one year. >> So Dave, in thinking about, you know, 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 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 refer to it 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. That's the experience they're going to get, matching up the enterprise requirements with the cloud-native. >> Is the impetus to take that proprietary data, that 80% of data Ginni Rometty 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 to modernize their applications and cut their costs? Probably both, but I wonder if you can talk to-- >> There are many higher level, type of scenarios and use cases, so one that Ajay went through is, really modernizing your applications, extending with innovation. But as Ginni 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 can 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 there 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 a customer to run production-ready workloads, we have security, compliance, reliability, these kinds of things, the same principles apply back to the platform that they're 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 and 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 that 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. Like, when we talk about Watson Studio, what Ginni 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 that 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, it's fully embraced all the agile DevOps capabilities, it's all developed on a cloud environment, we actually use ICP in our development of our IBM Cloud 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. >> So 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 that they're consuming? What are they like? What do they want? What are they asking you for? >> So we did what we consider a soft launch in June, where wanted to get some experience and feedback from users and operations. And what we actually did, is opened a open-select 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, we did a major launch with all the middleware capabilities, that content on the platform, it just took off. Since that time, we have upwards of 150 global accounts picked up IBM Cloud Private and started and going through the deployment, some are 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 into 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 micro-services for refactoring or even adding Watson Artificial Intelligence Services into the environment. >> Ajay, I started off asking you, sort of, where you got the motivation, a good starting point, your answer was outside in. You started with the customers, looked at use cases. Having said that, you're trying to replicate, mimic, to the greatest degree possible, the public cloud experience, so there's a reference model there. So when you think about what's next, do you, sort of, pop 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, road map 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 dimension. Customers, of course, is one of the important ones. Having a consistent story between IBM Public Cloud and IBM Cloud Private, is an absolute key principle for us. It's not just a requirement, but it's not just about keeping them functionally consistent, keeping them expedience-wise consistent, but making sure that when customers embark on the journey of hybrid deployment, be it, in terms of doing my dev test in public and then moving to IBM Cloud Private for production, or be a bursting scenario, these kind of things. Customers, not only want to run their application seamlessly, they want performance, they want network connectivity, they want secure connectivity, these kind of things. So that becomes another angle, in terms of how we are growing this, we have public, we have private, we can build a seamless hybrid storage today, but how do we evolve that hybrid storage to make sure that we can give them the same qualities of service? Just because you move your application from private to public, if the data stays on private, the performance is going to really impact, it'll 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 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, right? They will always have multiple clusters, geographically distributed. How do we manage their entire footprint and give them the right views for deployment, management, accountability, these kinds of things, across that entire real estate, right? 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've got a got 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, what would you say? >> Accelerate your transformation with cloud. That's what I would say. Leverage the technologies across IOT, public, private cloud, AI, block chain, and accelerate the transformation. >> Ajay, Dave, thanks very much for coming to the Cube. Good to see you again. >> Thank you. >> Alright, keep it right there, buddy. We'll be right back with our next guest. You're watching the Cube, we're live from Think 2018. (techno music)