As always, the server log ( trains-apiserver for start) and more details from the browser's developer tools Network section would be appreciated 🙂

And the trains-elasticsearch log?

btw, there are "[2020-09-02 15:15:40,331] [9] [WARNING] [urllib3.connectionpool] Connection pool is full, discarding connection: elasticsearch" in the apiserver logs again

0.16.1

btw, are there any examples of exporting metrics using Python client? I could only find last_metrics attribute of the task

Hi DilapidatedDucks58 , I am trying to reproduce the "Connection is full warning". Do you override any apiserver environment variables is docker compose? If yes then can you share your version of docker-compose? Do you provide a configuration file for gunicorn? Can you please share it?

This shouldn't be an issue, since the server should reuse connections, but perhaps the max connections limit on your server os relatively low?

we do log a lot of the different metrics, maybe this can be part of the problem

Is it possible to get a longer log file for the apiserver? From what I see, there's some kind of a connection pool issue

Great! What error do you still see in UI when comparing more than 20 experiments? At the time of error do you see any error response from the apiserver (in the browser network tab)? When the call to compare of 20+ task metrics succeed how much time does it usually takes in your environment?

Error
Failed to get Scalar Charts

I'll try to check it out and get back to you, seems very strange

tail of the api server log

I'll think about it and get back to you - it might be interesting to understand what causes this when comparing >20 experiments...

OK, on first glance ES doesn't seem to have any issue

Also, what's the Trains Server version?

Can you please check the max connections setting in your OS?

Do you see any error in the browser network tab?

nope, the only changes to config that we made are adding web-auth and non-responsive tasks watchdog

just in case, this warning disappeared after I https://stackoverflow.com/questions/49638699/docker-compose-restart-connection-pool-full

Yeah, connections keep getting dropped since the pool is full

m5.xlarge EC2 instance (4 vCPUs, 16 GB RAM), 100GB disk

okay, give me a sec

What is your server machine profile/spec?

some of the POST requests "tasks.get_all_ex" fail as far as I can see

thanks!

Well, server seems OK, disk size might be a little on the low-end (just to be safe)

any suggestions on how to fix it?

network logs

running
docker network prunebefore starting the containers kind of helped. I still see an error when I'm comparing > 20 experiments, but at least trains works okay after that, and there are no connection pool limit errors in the logs

Can you share all the error info that you get in the network tab?