Kubernetes at its’ core is a container orchestration system. But simply running containers for their own sake has little purpose, at the end of the day what really matters are applications.
Among the most interesting and often challenges types of application workloads are machine learning, which can often be difficult to deploy and operate. On Dec. 21 the Kubeflow project was officially announced by Google engineers as a new stack to easily deploy and run machine learning workloads.
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