I want to use kernel that’s spinned up on a server while using local jupyter.
I’ve seen solutions like ‘remote_ikernel’ and ‘ssh-ipykernel’, but they will require to jump into docker container (I should’ve mentioned that jupyter on server is running in a container).
Port forwarding is already working so I can work with remote jupyter.
But I want to use that kernel while working with local files (somewhat like what vscode does and pycharm prrofessional, but while still working in the same interrface)
Full remote kernel support is somewhat difficult to do quickly on your own as you’ve discovered. The jupyter_enterprise_gateway is another option that provides a way to achieve remote kernels but it sounds like overkill perhaps for what you’re doing (and has a learning curve). And it doesn’t solve the shared files problem you described inherently for you.
What it sounds like you may want/need is your working directory to use a mounted file system to share files across the network boundary.
Thanks for response.
Indeed, gateway is an overkill and probably won’t address the need to work on exactly one server of interest.
I’m trying to get away from folder syncing/mounting, other options also welcome