Machine Learning on Kubernetes

With the rise of containers, the problems of orchestration became more relevant. Over the last few years, various projects and have companies tried to address the challenge — but Kubernetes came out as a strong and dominant platform to run containers. Today, most companies are running (or are planning to move to) Kubernetes as a platform for running various workloads — be it stateless microservices, cron jobs, or stateful workloads such as databases (though these workloads only represent a small portion of computing workloads in the real world. For example, there are workloads which need specialized hardware like GPU. The resource management working group exactly focuses on this area and work towards aligning project and technologies so that more diverse kind of workloads run on Kubernetes platform.

Image source