Persistent storage for Kubernetes and containerized


In this brief video, Jack Norris, SVP Data & Applications helps us understand how their new MapR-XD converged platform enables containers to run and provides persistent storage for containers as well, including Kubernetes.

Mike Matchett:                  Hi, I'm Mike Matchett. I'm here today with Jack Norris, from MapR. And we're going to talk a little bit about their latest announcement providing storage for containers in a really big way. Hi Jack. How are you doing today?

Jack Norris:                           Good. Hi Mike. How are you?

Mike Matchett:                  Good. So, we've talked a lot before about what MapR offers in the converged analytics space and as a platform. But what you guys are doing right now is kind of exciting, 'cause it goes away from that pure data science category people kind of might shoebox MapR into, and is saying, "Here's a way to use the MapR-XD, the converged data platform, to not only run containers, but now get to that nirvana of persistent storage for containers, and using that MapR storage, right?

Jack Norris:                           Mm-hmm (affirmative). Yep. Yep.

Mike Matchett:                  Could you tell me a little bit about what that storage solution actually provides to someone who is running Kubernetes, for example.

Jack Norris:                           So, when you're running Kubernetes, when you're thinking of containerizing applications, most organizations have to subset and containerize just the lightweight, the ephemeral applications. Because, once you try to tackle stateful applications, that require shared data, it becomes much more complicated.

                                                      Well, our announcement is basically, our data fabric is now available to support Kubernetes environments in a native access. So, from the developers, from the administrators, it looks like accessing storage locally. When containers spin up or spin down, they pick up where they left off, as they move across locations, they access it the same way, so it dramatically simplifies the support of stateful applications in a Kubernetes environment. So, it's the power of our data fabric, plus the management flexibility and ease of use of Kubernetes.

Mike Matchett:                  And that data fabric, if I'm trying to remember, gives you HA, gives you scalability, gives you a couple other things. What else am I missing here?

Jack Norris:                           Yeah, I mean, if you think of it, well really, it's a huge paradigm shift. So, you've got centralized security. You've got a highly scalable fabric. Not only within a data center, but can burst, and include, and stretch to the cloud and across cloud. So, all of the data protection, the sophisticated restart, the synchronization across location. All of that is part of the fabric.

                                                      So, the developer doesn't need to think about it, and the complexity of pulling disparate data sets and doing really sophisticated operations, it's just a simple access. It looks like it's local storage for them, for the administrator, it really simplifies. They don't have to understand the details of individual containers and what they're accessing. They're a centralized location to make sure it's secure as possible, even though you've got different people with different access permissions that are only allowed for the access to the data that they're allowed to see.

Mike Matchett:                  Just to recap, so, I can go to a MapR-XD platform, with my Kubernetes, either on a platform or next to it, and from within my containers, mount volumes out of your data fabric, off that MapR-XD platform. And from a container perspective, it just looks like that native local container storage. Right? That-

Jack Norris:                           Absolutely. Yep.

Mike Matchett:                  So, if I'm a DevOps or ApDev guy, I'm getting the benefit of that huge, big data platform and all the stored greatness you guys have built in to that thing, and it's just invisible to me. I think what struck me as we walked through it was, you guys have this huge scalable platform already. So, when we talk about not just thousands of containers, but hundreds of thousands of containers, and I have talked to normal storage guys, you know, they kind of go, "Oh. Well, we support containers, but only up to the first hundred or so." Right? And if I would guess, because of the scalability you baked in there, that's not the problem that you're going to have at all. You're going to actually be able to provide for those hundreds of thousands of containers, all with persistent storage.

Jack Norris:                           Trillions of file, you know, petabytes of data, from anywhere. Even at a conference location where I'm talking to you now. Probably see the people in the background. So, my container, I can access here on the laptop, regardless of where the data is located.

Mike Matchett:                  Awesome. Awesome. Where can someone come to find a little bit more information about this?

Jack Norris:                           We've got information on our website, so, They can come in, they can see information there. They can easily see a demo or try it for themselves.

Mike Matchett:                  All right. So, this is going to be available now? Is it something I can get-

Jack Norris:                           Yes.

Mike Matchett:                  All right. Awesome.

Jack Norris:                           Shipping and available.

Mike Matchett:                  Awesome. Awesome. Thank you very much, Jack. Again, this is Mike Matchett from Small World Big Data, and we're talking with Jack Norris from MapR. Well, thanks and good luck, and we hope to see more of you guys in terms of what you can do for this big data and container space.

Jack Norris:                           Thanks so much, Mike.

Mike Matchett:                  All right. Take care.