Skip to main content
Stanford
Research Computing Nero GCP

Frequently Asked Questions & Troubleshooting

Useful resources

Where applicable, <sunetid> should be replaced with your own SUNet ID, and <pi-sunetid> should be replaced by your pi’s SUNet ID.

Common JupyterLab Error Messages and Pitfalls

Q: I am trying to connect to JupyterLab, but I am getting a “504 Gateway Time-out” error.

If you are unable to access JupyterLab, you can restart your JupyterLab server by going to https://<pi-sunetid>.compute.stanford.edu/hub/home and clicking on “Stop my server”, followed by “Start my server”.

Q: I am getting the error “Spawn Failed> Server at [address] didn’t respond in 30 seconds”.

This is a generic error message. Here are the usual culprits:

  • You are using a custom Conda environment and an error is preventing it from loading.

    If you are running a custom environment, this is the first thing to check.

    Using an ssh client, ssh to your Nero GCP project.

    $ ssh <sunetid>@<pi-sunetid>.compute.stanford.edu

    If you know the name/location of your custom environment conf file, you can skip this step. If you followed our Custom Environment tutorial, you may have a file called override in ~/.srcc/jupyter, so check there first.

      $ ls -la ~/.srcc/jupyter/

    You are looking for a file that contains something like

    export _CONDA_ROOT=~/envs/custom-jupyter

    Once you have located your file, move it to a backup so it will not execute. Swap in your own file path/name instead of override if it is different.

    $ mv ~/.srcc/jupyter/override ~/.srcc/jupyter/override.bak

    Try to open your environment again. If it works, then you know the problem was in your custom environment. Make a new custom environment or consult the Anaconda documentation to try to fix the old one.

  • The maximum storage quota has been reached on one of the directories you have access to.

When a home or PI directory is over its storage quota

This means that this directory has reached its storage quota. As a reminder, home directories are allocated 10GB of storage, while PI directories are allocated at least 1TB of data. You can try to ssh into Nero by opening a terminal and typing:
$ ssh <your-sunet>@nero.compute.stanford.edu
From the Nero login node, you can move or delete some files in the directory that is full. You can check the storage quota of a directory by typing:
$ cd /path/to/directory
$ df . -h

Q: I restarted my server, but I am now getting an error that says “Please use a different workspace. This workspace is already in use in another JupyterLab window. Please enter another workspace name.”

This simply means that you have an existing tab with another Nero session open in your browser. If you are unable to access JupyterLab, you can restart your JupyterLab server by going to https://<pi-sunetid>.compute.stanford.edu/hub/home and clicking on “Stop my server”, followed by “Start my server”.

Q: I see an error “Error Invalid response: 403” when I try to launch a Jupyter Notebook.

When you launch JupyterLab for the first time, make sure that you navigate to a directory in which you have read/write privileges before you try creating a Notebook. These directories are:

  • /home/
  • /share/pi/

Q: My JupyterLab session freezes. My browser eventually produces an error.

You probably have too many tabs in your Nero JupyterLab session opened. This also happens if you try to preview a csv file within the Nero JupyterLab environment. We recommend that you avoid opening too many tabs on Nero JupyterLab, and that you use a programming language to import your CSV file, and preview the data (e.g: using the df.head() command in Python).

Installing Python Modules

Q: How do I install a Python module on Nero?

The short answer is: Open a Terminal on Nero and type:
$ pip install --user <module-name>
For more instructions on how to install a Python package in your own conda environment, please visit our Anaconda documentation.

RStudio/R

Q: I use RStudio and I am getting a “500 error” when I try to connect to my session.

There could be a variety of things going on but here are a few commands to try.
On a Nero terminal, you can delete old R sessions by typing:
$ rm -rf ~/.rstudio/sessions/*
Restart your JupyerHub session by clicking on “Hub” > “Control Panel” > “Stop my server”, then “Start my server”.

Q: How do I install an R package on Nero?

Whether you are using RStudio or the R kernel on a Jupyter notebook, the short answer is: Open a Terminal on Nero Type the following commands:
$ module load r
$ R
$ install.packages(“package-name”)
# Accept the suggested settings (type “Yes)
# When prompted to select a CRAN mirror, choose “USA (OR)”. To choose this you would type the number to the left of “USA (OR)”

For github R packages you will want to clone the repo locally, then install in R.

Data Transfer

Q: I am trying to use an API to download data onto Nero. However, I am getting a time-out error.

Nero is an environment for high-risk data. As such, it only enables API calls to websites that have been whitelisted by the Nero team. The error you are seeing is actually by design.

On This Page

See Also