Jay Vyas is a Kubernetes Engineer at Platform9, a Kubernetes core contributor, and ASF member and commiter. Dynamic Provisioning in Kubernetes, and How It’s Different As Kubernetes matures - developers increasingly expect it to also be able to support transactional workloads like PostgreSQL, backups, recycling, and high-performance workloads (for example, in the AI arena).Īlthough we won’t solve this problem today for you, we will put you in a position where you can begin to effectively model your storage policies and experiment with emerging storage APIs before provisioning a full-blown production cluster. Rarely will an enterprise be able to survive with only a single type of default storage volume. Therefore, it is critically important to estimate what your storage needs are based on your applications workload type. The cost of using the Postgres solution for your cloud storage volumes could easily waste hundreds of thousands of dollars at data center scale. Now, let’s take into account the fact that a single storage array with 100s of Terabytes can be tens of thousands of dollars. Infinite (assume that over time the amount of storage increases indefinitely) Consider the following table of storage requirements for different workloads:ĪI Workloads with model or training caches And for a data center with 100s of applications, “picking one that just works,” is almost never an option. In conceptualizing your storage model - you’ll need a firm understanding of how basic Kubernetes components interact, in a storage-agnostic manner, detached from vendor-specific buzzwords, Ansible scripts, or RAID jargon. I believe that once you’ve looked at it a bit deeper, you’ll likely agree that the need for distributed storage in any cloud environment (Kubernetes or otherwise) is deceptively complex. Part 1: Kubernetes Storage Deep-Dive: The Economics of Heterogeneous, Dynamic Storageįirst, let’s review why there’s no out-of-the-box storage model in Kubernetes. A simple, private sandbox where experiments could be run in a reproducible way on the Kubernetes storage API.Shared conceptual model for reasoning about Kubernetes storage paradigms in a Production data center.These basic questions could easily be answered - if only there was a: In countless customer experiences - I can honestly say that majority of customer questions and issues around Kubernetes storage are often rather elementary, and roughly half of them are somehow related to persistent storage models. Storage in Kubernetes can really frustrate customers and newcomers to the blossoming cloud native universe. In the next part of this series, to run on Wednesday, we’ll turn to see how we can observe the inner-workings of Kubernetes storage and tweak those in a sandbox environment, using minikube.

In this two-part article, Platform9 Kubernetes engineer Jay Vyas introduces the key concepts and components in the Kubernetes storage architecture, to build up a conceptual storage model which is technology agnostic.

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