In order to offer you and other users a good user experience with Jupyter, the resources per JupyterLab Docker container are limited. This also allows us to ensure the proper operation of Jupyter.
| Resource | Limitation |
|---|---|
| Memory | 32 GB |
| Processor | 4 cores (vCPU) |
| Maximum number of processes (PIDs) | 1024 |
Maximum number of open files (ulimits -n)
|
1024 |
| Storage space (home directory) | 5 GB (soft limit) |
| Maximum runtime | 12h |
The limitation of your storage space does not take effect immediately if it is exceeded. This allows you to temporarily store larger amounts of data, for example for interim results. If you exceed the limit for a longer period of time, we will block your access and/or permanently delete your data.
The use of the graphics card is based on the Fair Use Policy. This resource is shared by all JupyterLab instances and cannot be reserved per user. To enable other users to use the scarce resource, please release the video RAM (vRAM) promptly. If you block the graphics card for a longer period of time, we will block your access.
Please note that inactive instances are automatically terminated in order to conserve resources. Instances are terminated after 12 hours at the latest, regardless of their activity.