I want to switch my notebook easily between different kernels. One use case is to quickly test a piece of code in tensorflow 2, 2.2, 2.3, and there are many similar use cases. However I prefer to define my environments as dockers these days, rather than as different (conda) environments.
Now I know that you can start jupyter in a container, but that it not what I want. I would like to just click Kernel > use kernel > TF 2.2 (docker), and let jupyter connect to a kernel running in this container.
Is something like that around? I have used livy to connect to remote spark kernels via ssh, so it feels like this should be possible.