Now I would like to deploy on CDMS (after #48), the main issue is that scaling up is very slow, it takes about 20 min to get another node up.
1) So to maximize savings we could just keep the master running which supports 1 user (with 5 GB memory), a second concurrent user trying to connect will have to wait 20 min for their session to start
2) We keep master + 1 node always running, so only after those are full (or someone asks for a full node) we trigger autoscaling
@pibion what do you think? We could also try a couple of weeks with 1 and then decide.
I would like to set this up only after the redeploy (#48), so there is lots of time to discuss this.
Autoscaling support for our deployment from the official project is still very far away, see https://github.com/zonca/jupyterhub-deploy-kubernetes-jetstream/issues/34
So I implemented a hacked-up script myself, see https://zonca.dev/2021/01/autoscaling_script_kubespray_jupyterhub.html, I tested on a sample deployment and worked just fine.
Now I would like to deploy on CDMS (after #48), the main issue is that scaling up is very slow, it takes about 20 min to get another node up.
1) So to maximize savings we could just keep the
masterrunning which supports 1 user (with 5 GB memory), a second concurrent user trying to connect will have to wait 20 min for their session to start 2) We keep master + 1 node always running, so only after those are full (or someone asks for a full node) we trigger autoscaling@pibion what do you think? We could also try a couple of weeks with 1 and then decide. I would like to set this up only after the redeploy (#48), so there is lots of time to discuss this.