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If your Jupyter server will not start or you are greeted with a blank page after logging in, it most like likely means that your Jupyter server has crashed or has otherwise stopped working. In most of the cases the simplest fix is to restart the server. You can do this by browsing to the address https://jupyterhub.apps.stack.it.ntnu.no/hub/home (or {coursecode}.apps.stack.it.ntnu.no/hub/home for specific courses), and clicking the "Stop My Server" button and trying again.
Kernel
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crashing
If a kernel is constantly crashing when running a specific notebook, it usually means that the kernel is trying to use more memory than the system has access to. If applicable, you can try to verify this by running the same code with fewer datapoints. We can increase the amount of allocated memory for very special cases, however please be aware it is often likely that your use-case will not fit into that category. That is not to say the specific use-case is not important, but but those special cases are very rare. We have limited resources available, and the goal of the hub is to serve as many users as possible.
Unauthorized error
If you are met with a '403 Unauthorized' error after logging into a hub, that means that you are not a member of the required access group(s) for the hub.
https://jupyterhub.apps.stack.it.ntnu.no is open (only) to everyone at NTNU.
Access to the course specific hubs is often limited to a group for students taking the course(s) and another specific access group for everyone else. You can see your group memberships at https://innsyn.feide.no/groups. The student groups for courses are managed automatically by Felles Studentsystem (FS) - we do not have the possibility to include students in them. Please note that there can be a significant delay (from a few hours to a few days) between signing up to a course and being registered for the course on FS.
If you think you should have access to a specific hub but are still seeing the error, check with the course staff for an invitation to the access group.
File size too large
If you encounter an error with the error code 413 (example shown below), it almost always means that the file that you are working on is too large. The error can occur both when uploading files and/or when saving files within the Jupyter interface. The default file size limit is very strict, and it is strict for a reason. However, it is possible for us to increase the limit - but only for a very good reason.
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