I've talked about Docker a couple of times in the Roundup before. Containers are a very useful tool for data scientists, and you should really be able to get up and running with Docker for your personal use after a couple of hours with the docs. Not too bad.
Kubernetes (K8S) is an altogether different animal. If you're not familiar, Kubernetes is a way to run clusters of Docker containers and allow them to do special things like fail over to each other and transparently add and subtract workers automatically.
Let me just say: Kubernetes is hard. Managing a K8S cluster is cutting edge devops work, and I didn't include this post because I think you should march out and try to set one up. I do, however, think that it's important for data scientists to understand the technology: it's beginning to invade data science products left and right.
If you're not familiar with K8S, this post will give you a sense for what's involved in going end-to-end: from cluster creation to app deployment.Read more...