Multi-zone jupyterhub in GKE


Past few weeks we have been running into scaling issues for a couple 5-15 node single-zone autoscaling GKE clusters running jupyterhub v0.8.0. In both cases we see autoscaling getting triggered when expected but occasionally failing with ZONE_RESOURCE_POOL_EXHAUSTED, which I gather means the zone we are running in is out of compute for us. Of course these are times mid-day when the cluster is acutely needed. It’s relatively straight-forward to get new nodes in a different zone, but the persistent storage volumes are locked to the current zone as far as I can tell.


  • anyone else run into this?
  • is there a way to have user volumes float across a region though configuration to gcloud / jupyterhub’s helm config?
  • is there a sane way to take what we have and make it multi-zonal without tearing everything down?

I could be wrong but I think this message is in regards to a resource quota you may have exceeded. I have run into these in the past and have requested to increase the quota without a hassle.

Pretty sure this isn’t the case, as the cluster sizes have been larger both before and after these events. My understanding is that the quotas are static unless you explicitly ask for them to be changed.