Identifying JupyterHub api performance bottleneck

[mriedem]

@minrk

Thanks for investigating! My guess is that it’s the activity tracking that’s bogging it down. Every authenticated request is performing a write to the database to update the activity counter for the authenticated user/token. That’s probably not good! We should probably throttle this so we don’t record activity for a given user more often than every ~30 seconds or so. I’ve added config to do this: https://github.com/jupyterhub/jupyterhub/pull/2605

I’m digging into profiling and performance scale/load testing our hub and came across this older thread. I just wanted to say that earlier in the year when we had some load issues on the hub API during a large user event that config was the thing we found and tuned to ease the pressure so definitely thanks for adding that. We actually bumped that up from the default (30 seconds) to 6000 seconds.

While this is fresh in mind and I’ve been poking around docs looking at performance tuning, would it be worthwhile to mention that config option here [1]?

[1] Optimizations — Zero to JupyterHub with Kubernetes documentation