first stab at mkdocs migration

refactor CSCS and Meg content

add merlin6 quick start

update merlin6 nomachine docs

give the userdoc its own color scheme

we use the Materials default one

refactored slurm general docs merlin6

add merlin6 JB docs

add software support m6 docs

add all files to nav

vibed changes #1

add missing pages

further vibing #2

vibe #3

further fixes
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# Jupyterhub Troubleshooting
In case of problems or requests, please either submit a **[PSI Service
Now](https://psi.service-now.com/psisp)** incident containing *"Merlin
Jupyterhub"* as part of the subject, or contact us by mail through
<merlin-admins@lists.psi.ch>.
## General steps for troubleshooting
### Investigate the Slurm output file
Your jupyterhub session runs as a normal batch job on the cluster, and each
launch will create a slurm output file in your *home* directory named like
`jupyterhub_batchspawner_{$JOBID}.log`, where the `$JOBID` part is the slurm job
ID of your job. After a failed launch, investigate the contents of that file.
An error message will usually be found towards the end of the file, often
including a python backtrace.
### Investigate python environment interferences
Jupyterhub just runs a jupyter notebook executable as your user inside the
batch job. A frequent source of errors consists of a user's local python
environment definitions getting mixed up with the environment that jupyter
needs to launch.
- setting PYTHONPATH inside of the ~/.bash_profile or any other startup script
- having installed packages to your local user area (e.g. using `pip install
--user <some-package>`). Such installation will interfere with the
environment offered by the `module` system on our cluster (based on
anaconda). You can list such packages by executing `pip list user`.
They are usually located in `~/.local/lib/pythonX.Y/...`.
You can investigate the launching of a notebook interactively, by logging in to
Merlin6 and running a jupyter command in the correct environment.
```bash
module use unstable
module load anaconda/2019.07
conda activate jupyterhub-1.0.0_py36
jupyter --paths
```
## Known Problems and workarounds
### Spawner times out
If the cluster is very full, it may be difficult to launch a session. We always
reserve some slots for interactive Jupyterhub use, but it may be that these
slots have been taken or that the resources you requested are currently not
available.
Inside of a Merlin6 terminal shell, you can run the standard commands like
`sinfo` and `squeue` to get an overview of how full the cluster is.
### Your user environment is not among the kernels offered for choice
Refer to our documentation about [using your own custom made
environments with jupyterhub](jupyterhub.md).
### Cannot save notebook - *xsrf argument missing*
You cannot save your notebook anymore and you get this error:
```text
'_xsrf' argument missing from POST
```
This issue occurs very seldomly. There exists the following workaround:
Go to the jupyterhub file browsing window and just open another
notebook using the same kernel in another browser window. The issue
should then go away. For more information refer to [this github
thread](https://github.com/nteract/hydrogen/issues/922#issuecomment-405456346)
<!-- ## Error HTTP 500 when starting the spawner -->
<!-- The spawner screen shows after launching an error message like the following: -->
<!-- `Internal server error (Spawner failed to start [status=..]. The logs may contain details)` -->