 Live from San Jose, in the heart of Silicon Valley. It's theCUBE, covering DataWorks Summit 2018. Brought to you by Hortonworks. Welcome back everyone. You are watching day two of theCUBE's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight. I'm coming at you with my co-host, James Kobielus. We're joined by Partha Sitala. He is the Chief Technology Officer at Robin Systems. Thanks so much for coming on theCUBE. You're a first-timer, so we promise we don't bite. Actually, I'm not. I was on theCUBE at DockerCon in 2016. Oh, well, excellent. Okay, so now you're a veteran. Right. So, Robin Systems, before the cameras were rolling, we were talking about it. It's about four years old, based here in San Jose. Venture-backed company. Tell us a little bit more about the company and what you do. Absolutely. First of all, thanks for hosting me here. So, like I said, Robin is a Silicon Valley-based company. Our focus is in allowing applications such as Big Data, Databases, NoSQL, and AIML to run within the Kubernetes platform. And what we have built is a product that converges storage, components like storage, networking, application workflow management, along with Kubernetes to create a one-click experience where users can get managed services kind of feel when they're deploying these applications. And they can also do one-click lifecycle management on these apps. So, our thesis has essentially been to, instead of looking at this problem from an infrastructure up into application, to actually look at it from the applications down, and then say, let the applications drive them underlying infrastructure to meet the user's requirements. And is that your differentiating factor, would you say? Yeah, I think it is, because most of the folks out there today are looking at it as if it's a component-based play. It's like they want to bring storage to Kubernetes or networking to Kubernetes. But the challenges are not really around storage and networking. If you look at, if you talk to the operations folks, they say that, you know what, yeah, those are underlying problems, but my challenge is more along the lines of, okay, my CIO says the initiative is to make my applications mobile. They want to go across different clouds. That's my challenge. The line of business user says that I want to get a managed service experience. Yes, storage is a thing that you want to manage underneath, but I want to go and click and create my, let's say an Oracle database or an Hadoop distribution and so on. In terms of the developer experience here, what's sort of, you know, from the application down, give us a sense for how Robin's systems tooling your product enables that degree of, you know, specification of the application logic that will then get containerized within the... Absolutely. So like I said, we want applications to drive the infrastructure. What it means is that we, Robin is a software platform. We layer ourselves on top of the machines that we sit on, whether it is bare metal machines, on-premises or VMs, or even an Azure Google Cloud as well as AWS. Then we make the underlying compute storage network resources almost invisible. We just treat it as a pool of resources. Now, once you have this pool of resources, they can be attached to the applications that have been deployed as inside containers. Now, so that is the software play. Install on machines. Once it's installed, the experience now moves away from infrastructure into applications. You log in, you can see a portal. You have a lot of applications in that portal. We ship support for about 25 applications or some such. So these are templates that they develop and then customize to their specific requirements? Or no? Absolutely. We ship reference templates for pretty much a wide variety of the most popular big data, no SQL database, AI ML work applications today. But they are, again, as I said, it's a reference implementation. Typically, customers take their reference implementation and they enhance it, or they use that to onboard their custom apps, for example, or the apps that we don't ship out of the box. So it's a very open, extensible platform. But the goal being that, whatever the application might be, in fact, we keep saying that if it runs on Linux, it runs on Dragon, right? So the idea here is that you can bring anything and we just flip over a switch. You can make it one click deploy, one click manage, one click mobile across clouds. You keep mentioning this one click and this idea of it being so easy, so convenient, so seamless, is that what you say is the biggest concern of your customers? Is this ease and speed, or what are some other things that are on their minds that you want to deliver? Right, so one click, of course, is a user experience part, but what is the real challenge? The real challenge is there are a wide variety of tools being used by enterprises today. Even the data analytic pipeline has a lot across the ingest or process of pipeline. Users don't want to deal with setting it up and keeping it up and running. They just don't want that. They want to get their job done, right? Now when you want to get their job done, you really want to hide the underlying details of those platforms. And the best way to convey that, the best way to give that experience is to make it a single click experience from the UI. So I keep calling about one click because that is the experience that you get to hide the underlying complexity for these apps. So does your environment actually compile executable code based on that one click experience, or where does the compilation and containerization actually happen in your distributed architecture? All right, so, I think the simplest way of doing it- You're a print-based offering, right? You're not in the cloud yourself. No, we are. So we work in all the three public clouds, whether it is Azure, AWS, or Google. So your entire application suite is containerized itself for deployment of these clouds? Yes, it is. So the idea here is let's simplify it significantly, right? You have Kubernetes today, it can run anywhere, on-premises, in the public cloud, and so on. Kubernetes is a great platform for orchestrating containers. But it is largely inaccessible to a certain class of data-centric applications. We make that possible. But our take is just onboarding these applications on Kubernetes does not solve your CXO or your line of business users problems. You have to make the management from an application point of view, not from a container management point of view, but an application point of view, a lot easier. And that is where we kind of create this experience that I talked about, one-click experience. Give us a sense for how, we're here at DataWorks, and it's the Hortonworks show. To discuss with us your partnership with Hortonworks, and, you know, we've heard the announcement of HTTP 3.0 and containerization support. Just give us a rough sense for how you align or partner with Hortonworks in this area. Absolutely. So, it's kind of interesting because Hortonworks is a data management platform, if you think about it from that point of view. And when we engaged with them first, so some of our customers have been using the product, Hortonworks on top of Robin, so orchestrating Hortonworks, making it a lot easier to use. One of the requirements was, are you certified with Hortonworks? And the challenge that Hortonworks also had is they had never certified a container-based deployment of Hortonworks before. And they actually was very skeptical that, you guys are seeing all these things. Can you actually containerize and run Hortonworks? So, we worked with Hortonworks, and we are, I mean, if you go to the Hortonworks website, you'll see that we are the first in the entire industry who have been certified as a container-based play that can actually deploy and manage Hortonworks. So, they have certified us by running a wide variety of tests, which they call the QATS test suite. And when we got certified, the only other players in the market that got that stamp of approval was Microsoft, in Azure, and EMC with Icelon. So, you're in good company. Yeah, I think you're in great company. So, you're certified to work with HTTP 3.0, or the prior version, or both? So, when you got certified, we are still in the 2.x version of Hortonworks. HTTP 3.0 is more relatively newer version. But our plan is that we want to continue working with Hortonworks to get certified as they release their product. And also, help them, because HTTP 3.0 also has some container-based orchestration and deployment. So, you want to help them provide the underlying infrastructure so that it becomes easy for Deion to spin up more containers. The higher-level security and governance and all these things you're describing, they have to be over the Kubernetes layer. You know, Hortonworks supports it in their data plane services portfolio. Does your, does Robin's system solution portfolio tap into any of that, or do you provide your own layer of security and metadata management and so forth? Yeah, so we don't want to take- The context of what you offer. Right, so we don't want to take away the security model that the application itself provides, because people might have set it up so that they're doing governance. It's not just logging in and audit control and things like that. There's some governance built into it. We don't want to, we don't want to change that. We want to keep the same experience and the same workflow that customers have. So we just integrate with whatever security that the application has. We, of course, provide security in terms of isolating these different apps that are running on the Robin platform. But the security or the access into the application itself is left to the apps themselves. When I say I have, I'm talking about Hortonworks or any other databases. Moving forward, as you think about ways you're going to augment and enhance and alter the Robin platform, what are some of the biggest trends that are driving your decision making around that? In the sense of, you know, as we know that companies are living with this deluge of data, how are you helping them manage it better? Sure, I think there are a few trends that we are closely watching. One is around cloud mobility. CIOs want their applications along with their data to be available where their end users are. So almost like follow the sun model where you might have generated the data in one cloud and at a different time zone, you basically want to keep the app as well as data. So we are following that very closely. How we can enable the mobility of data and apps a lot easier in that world. The other one is around the general AI ML workflow. So one of the challenges there, of course, you have great apps like TensorFlow or Tiano or Cafe. These are very good AI ML toolkits. But one of the challenges that people face is they're buying this very expensive, let's say an NVIDIA DGX box. These box costs about 150 grand each. How do you keep these boxes busy so that you're actually getting a good return on investment will require you to better manage the resources offered with these boxes. So we are also monitoring that space and we're saying that how can we take the Robin platform and how do you enable the better utilization of GPUs but a sharing of GPUs for running your AI MLDL kind of workloads. So those are the two key trends that we are closely watching. We'll be discussing those at the next DataWorks Summit, I'm sure, at some other time in the future. Absolutely. Thank you so much for coming on the Q part, Tom. Thank you, my pleasure. Thanks. I'm Rebecca Knight for James Kobielus. We will have more from DataWorks coming up in just a little bit.