Are you running into scaling issues because all students are on a single box? I think the JupyterHub proxying service should be able to handle way more than 70 users, but I could see 70 users on a single machine being problematic. I'm doing a lot of work around JupyterHub - happy to help out if I can, I can be reached at hugo@saturncloud.io
Well, it's a virtual server, so I'm not sure how that plays with things. I supposed getting more servers in play would help, but that feels more like throwing hardware at a software problem. It doesn't feel like JH should have this much overhead - is the kernel really doing so much work?
Depends on what your students are doing right? Also I'd bet your running out of ram before CPU. You should try doing the same workload without JH involved - I'd bet you'd still run out of ram. Also - I'd throw hardware at software problems all day long if I could. Hardware is cheap compared to developer time
