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Awesome! I wonder if I can use this to replace jupyterhub for my small data science team. The jhub kubernetes architecture is (roughly) - Proxy —> hub —> spawn
by scrappyjoe 4y ago
Awesome! I wonder if I can use this to replace jupyterhub for my small data science team. The jhub kubernetes architecture is (roughly) -
Proxy —> hub —> spawner based on selected image —> container with /user persistent PV
But the image needs to be spawnable by jhub (i/e it needs to have some variant of jupyter-server-proxy installed), and currently that limits you to JupyterLab, RStudio and openrefine.
If you can port-forward with containerssh you could bypass the whole jhub proxy / hub / spawner rigmarole and simply
Select image -> containerssh w/port forward -> start the desired dev environment from inside the container -> get to work.
Then you’re not limited to jhub-compatible environments, and you don’t have to manage the complexity of jhub.
- janosdebugs 4y agoYes you can and you wouldn't be the only person doing this. However, port forwarding is only supported in the in-development version, so you have to build your own binary for that.
- urcyanide 4y agoRecently, I found another tool built for machine learning environment: https://github.com/tensorchord/envd https://github.com/tensorchord/envd. It integrates with buildkit and can share the config like Python functions cross the team. This can reduce a lot complexity for data scientists.
- paulgb 4y agoFor the “jhub but for any container that speaks HTTP” use case, you might find our Spawner project interesting: https://github.com/drifting-in-space/spawner https://github.com/drifting-in-space/spawner We don’t have support for volumes yet, but I’m open to ideas.