[BUG] Available envs for dashboards is incorrect

OS system and architecture in which you are running QHub

GCP

Expected behavior

• all the envs should show up as options for deploying dashboards.

Actual behavior

I have a group env on https://quansight-beta.qhub.dev/ that I want to use as my dashboard env, but its not showing up in the list of available envs on the Create a new dashboard page. The environment does show up under store https://quansight-beta.qhub.dev/conda-store/environment/analyst/water_dashboards/

This is the same env that I have on https://quansight.qhub.dev/ as a user env and on that deployment, it does show up in the list of available envs when creating a new dashboard.

How to Reproduce the problem?

- conda-forge
dependencies:
- python
- pip
- jupyterlab
- pandas
- holoviews
- geopandas
- geoviews
- param
- panel
- rich
- cdsdashboards-singleuser >=0.5.6
- jupyter_bokeh
- pip:
  - noaa-coops
- ipykernel
name: water_dashboards
prefix: null

Command output

No response

Versions and dependencies used.

https://quansight-beta.qhub.dev/ - QHub v0.4.1 according to the screen https://quansight.qhub.dev/ - v0.0.1 according to the screen

Compute environment

No response

Integrations

No response

Anything else?

No response

[rsignell-usgs]

Also, while the environments show up in jupyterlab as users-pangeo (e.g. with the namespace), they don’t show up that way in the dashboard gui, and they don’t show up that way if you open a terminal. You just see the environment names without namespaces:

rsignell-usgs@jupyter-rsignell-2dusgs:~$ conda info -e

# conda environments:
#
dask2                    /home/conda/filesystem/envs/dask2
bitinfo                  /home/conda/users/envs/bitinfo
pangeo                   /home/conda/users/envs/pangeo
seppo                    /home/conda/users/envs/seppo
base                  *  /opt/conda
default                  /opt/conda/envs/default

This is all super confusing to me and likely other users.

[costrouc]

See https://github.com/Quansight/qhub/pull/1358 working on a fix. Currently my dilemma is the correct way to do this. Do I mount the pvc for conda-store or use the latest conda-store which does all of this with an api call.