Q&A on Machine Learning and Kubernetes with David Aronchick of Google from Kubecon 2017
At the recently concluded Kubecon in Austin, TX, attended by over 4000 engineers, Kubernetes was front, left and center. Due to the nature of workloads and typical heavy compute requirements in training algorithms, Machine Learning topics and its synergy with Kubernetes was discussed in many sessions.
Kubeflow is a platform for making Machine Learning on Kubernetes easy, portable and scalable by providing manifests for creating:
- A JupyterHub to create and manage Jupyter notebooks
- A Tensorflow training controller to adapt for both CPUs and GPUs, and
- A Tensorflow serving container
Read more at InfoQ