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The Cure for Kubernetes Storage Headaches: Break Your Data Free Posted on : May 20 - 2020

If you’re using Kubernetes, there’s likely a simple reason why: Because it makes your life easier. That is, after all, the whole premise behind container-based orchestration. Infrastructure becomes disposable. Spin it up when you need it, throw it away when you’re done, and let Kubernetes worry about the underlying infrastructure, so you don’t have to think too much about it.

At least, that’s how things are supposed to work. As you know if you’ve actually set up workloads that depend on persistent data, there’s one big asterisk – storage.

As great as Kubernetes is at abstracting away compute and networking infrastructure, it just doesn’t work that way for storage when your apps are stateful and data is persistent. Your application still must know all about the underlying storage infrastructure to find its way to the data you need. And not just the location of that data, but all the other fine-grained considerations (performance, protection, resiliency, data governance, and cost) that come with different kinds of storage infrastructure, that most data scientists don’t want to think about.

Why, in a cloud-native world where we’ve automated away the management of so much underlying hardware complexity, is storage still so painful? Two words: data silos.

As long as we continue to manage data via the different infrastructures it lives on, rather than focusing on the data itself, we’ll inevitably end up juggling islands of storage, with all the headaches that come with them. Fortunately, this is not an intractable problem. By changing the way we think about data management, from an infrastructure-centric to a data-centric approach, we can use Kubernetes to give us what was promised in the first place: making storage SEP (Someone Else’s Problem). View More