As a cloud user, how do you avoid the pull of data gravity of one provider or another? How can you get the flexibility and tooling to migrate your infrastructure and applications as your needs change? How do you get to the future of storage federation as data agility?

In this blog we cover the primary motivations and considerations that drive the enablement of flexible, scalable, and agile data management. Our subsequent blogs cover practical use cases and concrete solutions for our 6 federated storage patterns. 

All of this is grounded in Red Hat’s work to take a lead in multi-cluster enablement and hybrid cloud capabilities. Our work is focused on leading and moving forward projects that lay the groundwork for this vision in OpenShift, driven via the Kubernetes project KubeFed.

It’s no secret that if you want to run containerized applications in a distributed way, then Kubernetes is the platform for you. Kubernetes’ role as an orchestration platform for containers has taken center stage to become a main player for automating deployment, scaling, and management of applications within containers. Red Hat’s own OpenShift Container Platform is a Kubernetes distribution that uses Kubernetes optimized for enterprises.

Storage has been one of the areas of potential optimization. Many containers, by their very nature, are usually small enough to be easily distributed and managed. Containers hold applications, but the data those applications use needs to be held somewhere else, for a number of reasons. Of particular interest in this post, we want to avoid the containers themselves becoming too large and unwieldy to be effectively managed.