How Uber is Running Ray on Kubernetes

Companies are in a bind over whether to use or ditch Kubernetes. While some companies decided to completely move away from it, many have now been moving their workloads back to Kubernetes after trying and testing monolithic architectures. Unfortunately, both approaches have their pain points, and no single perfect solution exists.  Last year, ride-hailing logistics firm Uber decided to upgrade its machine learning platform and shift its ML workloads to Kubernetes. And, in typical Uber fashion, it didn’t just migrate but also built some of its own tools along the way to make everything run smoothly. In a recent blog, the Uber tech team explained this transition and the motivation behind it. ML pipelines deal with huge volumes of data, especially during model training. These are