Conda kernels not showing on a remote jupyter server, within remote-ssh session

[xroi]

Applies To

• Notebooks (.ipynb files)
• Interactive Window and/or Cell Scripts (.py files with #%% markers)

What happened?

I'm using remote-ssh to connect to host1, but I want to run the Jupyter cluster on host2, which is mounted on the same file system as host1. However, when trying to select a kernel in Jupyter, I can only see the default system-wide python installation.

Here are the exact steps I'm taking:

1. SSH into host1 using remote-ssh.
2. In the terminal on host1, SSH into host2, activate the desired conda environment, and launch the Jupyter server.
3. Open the Jupyter notebook on host1.
4. Switch the kernel by selecting "Existing Jupyter Server."
5. Enter the Jupyter server address on host2 and successfully connect.
6. The only available kernel in the dropdown list is the system-wide kernel, not the one from the activated conda environment or any others

Note: host1,2 are on Debian 12
Other Note: I can't remote-ssh directly to host2, nor connect to it's jupyter server directly

VS Code Version

Version: 1.97.2 (user setup) Commit: e54c774e0add60467559eb0d1e229c6452cf8447 Date: 2025-02-12T23:20:35.343Z Electron: 32.2.7 ElectronBuildId: 10982180 Chromium: 128.0.6613.186 Node.js: 20.18.1 V8: 12.8.374.38-electron.0 OS: Windows_NT x64 10.0.22631

Jupyter Extension Version

2025.1.2025013001

Jupyter logs

Coding Language and Runtime Version

No response

Language Extension Version (if applicable)

No response

Anaconda Version (if applicable)

conda 24.7.1

Running Jupyter locally or remotely?

Remote

[xroi]

A solution was to run
path\to\miniconda\envs\<env_name>\bin\ipython kernel install --user
on each of the environments.
this is a little weird since when running the notebooks "locally" on the ssh'd host I didn't need to do that