Robin Hyper-Converged Kubernetes Platform – the First Container Solution certified to run Hortonworks Data Platform (HDP)
On day two at Dataworks Summit 2018, Rebecca Knight and Jame Kobielus spoke with Partha Seetala, Chief Technology Officer (CTO), Robin Systems at theCUBE to discuss the first container solution certified to run Hortonworks Data Platform (HDP).
Tell us about Robin Systems
Robin Systems, a venture-backed company is headquartered in San Jose in the Silicon Valley. The focus is in allowing applications, such as big data, databases, NoSQL, and AI ML, to run within the Kubernetes platform. What we have built (the first container solution certified to run HDP) is a product that converges storage, complex 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. They can also do one click lifecycle management on these apps. Our thesis has initially been to actually look at it from the applications down and then say, “Let the applications drive the underlying infrastructure to meet the user’s requirements.”, instead of looking at this problem from an infrastructure up into the application.
Is this the differentiating factor for Robin Systems?
Yes, it is because most of the folks out there today are looking at is 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 talk to the operations folk they say that “You know what? Those are underlying problems but my challenge is more along the lines of when my CIO says the initiative is to make my applications mobile. The management wants to go across to different Clouds. That’s my challenge.” The line of business user says “I want to get a managed source experience.” Yes, storage is the thing that you want to manage underneath, but I want to go and click and create my, let’s say, an Oracle database or distributions log.
In terms of the developer experience here, from the application down, give us a sense for how Robin Systems tooling your product in a certain way enables that degree of specification of the application logic that will then get containerized within?
Absolutely, like I said, we want applications to drive the infrastructure. What it means is that Robin is a software platform – the first container solution certified by Hortonworks to run HDP. We layer ourselves on top of the machines that we sit on – whether it is bare metal machines on premises, on VMs, or even an Azure, Google Cloud as well as AWs. Then we make the underlying compute, storage, network resources almost invisible. We treat it as a pool of resources. Now once you have this pool of resources, they can be attached to the applications that are being deployed as can (3:10) inside containers. I mean, it’s a software plane installed 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.
So are these templates that the developer can then customize to their specific requirements? Or no?
Yes. Absolutely, we ship reference templates for pretty much a wide variety of the most popular big data, NoSQL, database, AI ML applications today. But again, as I said, it’s a reference implementation. Typically, customers take the reference recommendation 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 is that whatever the application might be, in fact, we keep saying that, if it runs somewhere else, it’s running on Robin. So the idea here is that you can bring any app or database, and with the flip of a switch, you can make it a 1-click deploy, 1-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? Are this ease and speed? Or what are some other things that are on their minds that you want to deliver?
So one click, of course, is a user experience part – but what is the real challenge? The real challenges are – there are a wide variety of tools being used by enterprises today. Even the data analytic pipeline, there’s a lot across the data store, processor pipeline. Users don’t want to deal with setting it up and keeping it up and running. They don’t want the management but they want to get the job done. Now when you only get the 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 it all one click because that is the experience that you get to hide the underlying complexity for these apps with the First Container Solution certified to run HDP.
Does your environment actually compile executable code based on that one click experience? Or where do the compilation and containerization actually happen in your distributed architecture?
Alright, so, I think the simplest to explain like this – You work on all the three big public clouds. Whether it is Azure, AWS or Google. Your entire application is containerized itself for deployment into these Clouds. So the idea here is let’s simplify it significantly. 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. Robin makes that possible.
But the Robin take is, just onboarding those applications on Kubernetes does not solve your CXO or your line of business user’s problems. You ought to manage the environment from an application point of view, not from a container management point of view. From an application point of view, management is a lot easier and that is where we create this one-click experience.
Give us a sense for how we’re here at DataWorks and it’s the Hortonworks show. Discuss with us your partnership with Hortonworks and you know, we’ve heard the announcement of HDP 3.0 and containerization support. Just give us a rough sense for how you align or partner with Hortonworks in this area.
Absolutely. 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. They actually were very skeptical, you know, “You guys are saying 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. They have certified us by running a wide variety of tests, which they call the Q80 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 Isilon.
So you’re in good company?
I think we are in great company.
Are you certified to work with HDP 3.0 or the prior version or both?
When we got certified we were still in the 2.X version of Hortonworks, HDP 3.0 is a more relatively newer version. But our plan is that we want to continue working with Hortonworks to get certified as they release the program and also help them because HDP 3.0 also has some container based orchestration and deployment. So we want to help them provide the underlying infrastructure so that it becomes easier for users 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. Hortonworks supports it in their data plane services portfolio. Does Robin Systems solutions portfolio tap into any of that, or do you provide your own layer of sort of security and metadata management so forth?
We don’t want to take away the security model that the application itself provides because the user might have step it up so that they are doing governance, it’s not just logging in and auto control and things like this. Some governance is built into. We don’t want to change that. We want to keep the same experience and the same workflow hat 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 where the security or the access into the application itself is left to the apps themselves. When I say apps, 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, as we know that companies are living with this deluge of data, how are you helping them manage it better?
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. It’s almost like follow the sun model, where you might have generated the data in one Cloud and at a different time, different time zone, you’ll basically want to keep the app as well as the data moving. 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. One of the challenges there, of course, you have great apps like TensorFlow or Theano or Caffe, these are very good AI ML toolkits but one of the challenges that people face, is they are buying this very expensive, let’s say NVIDIA DGX Box, this box costs about $150,000 each. How do you keep these boxes busy so that you’re getting a good return on investment? It will require you to better manage the resources offered with these boxes. We are also monitoring that space and we’re seeing that how can we take the Robin platform and how do you enable the better utilization of GPUs or the sharing of GPUs for running your AI ML kind of workload.
We’ll be discussing these trends at the next DataWorks Summit, I’m sure, at some other time in the future.
Learn more about Robin Hyper-Converged Kubernetes Platform – the First Container Solution Certified to run Hortonworks Data Platform (HDP) for big data, nosql databases and RDBMS applications.