Yeah, another thing you can do is offer Labs as a service (Jupyter Hub) to a group of users and then you can do things across the org like preinstalled requirements, shared or persistent storage, federated users, etc. If you run this on kubernetes it'll spawn up and down labs as people login/out and let you manage lab lifecycles, proxying, etc. We bundle Hub with our AI product at $work to give our users a packaged experience.

https://jupyter.org/hub