Hi Jupyter experts, My team and I are working to bring JupyterLab in a multi-tenant environment (Kubernetes) where each member of a particular tenant has a dedicated JupyterLab client.
The following are critical features that we require: 1. Mounting Persistent Volumes onto remote kernel pods - Is this a spec that can be passed? 2. Lifecycle management of remote kernels - Is this available? If not, what is the current behaviour of the remote kernels? 3. Dependency management - For dependencies that have been dynamically installed within a remote kernel pod, is there any way that these dependencies be restored in the next session where a different pod is spun up? 4. Configuring kernel pod resource specs - If I'm not wrong JKG 2.2.0 should have already implemented this? Thank you! -- You received this message because you are subscribed to the Google Groups "Project Jupyter" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/jupyter/3c356e77-6eeb-4043-b9d7-e320872ffd32%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
