January 19, 2020

359 words 2 mins read

Progress for big data in Kubernetes

Progress for big data in Kubernetes

Stateful containers are a well-known anti-pattern, but the standard solutionmanaging state in a separate storage tieris costly and complex. Recent developments have changed things dramatically for the better. In particular, you can now manage a high-performance software-defined-storage tier entirely in Kubernetes. Ted Dunning describes what's new and how it makes big data easier on Kubernetes.

Talk Title Progress for big data in Kubernetes
Speakers Ted Dunning (MapR, now part of HPE)
Conference Strata Data Conference
Conf Tag Make Data Work
Location New York, New York
Date September 11-13, 2018
URL Talk Page
Slides Talk Slides
Video

The folk wisdom has always been that when running stateful applications inside containers, the only viable choice is to externalize the state so that the containers themselves are stateless or nearly so. Keeping large amounts of state inside containers is possible, but it’s considered a problem because stateful containers generally can’t preserve that state across restarts. In practice, this complicates the management of large-scale Kubernetes-based infrastructure because these high-performance storage systems require separate management. In terms of overall system management, it would be ideal if we could run a software-defined storage system directly in containers managed by Kubernetes, but that has been hampered by lack of direct device access and difficult questions about what happens to the state on container restarts. Ted Dunning describes recent developments that make it possible for Kubernetes to manage both compute and storage tiers in the same cluster. Container restarts can be handled gracefully without loss of data or a requirement to rebuild storage structures and access to storage from compute containers is extremely fast. In some environments, it’s even possible to implement elastic storage frameworks that can fold data onto just a few containers during quiescent periods or explode it in just a few seconds across a large number of machines when higher speed access is required. The benefits of systems like this extend beyond management simplicity, because applications can be more Agile precisely because the storage layer is more stable and can be uniformly accessed from any container host. Even better, it makes it a snap to configure and deploy a full-scale compute and storage infrastructure.

comments powered by Disqus