I successfully built a custom docker image for the Standard runtime following the steps described on the page Customize containers with Databricks Container Services and based on the image databricksruntime/standard:11.3-LTS. However, I cannot find an appropriate base image for an ML runtime.
The only thing I can come up with is to export the list of all Python packages via pip freeze from a notebook in a running ML cluster and build the Docker image based on that list, but that seems tedious.
Also I'm not sure even that could work with the base image for the Standard runtime. There might be other dependencies missing apart from Python packages.
Has anyone an idea how this could be achieved?