Sorry but no, i already have clearml agent running as a pod. My question is how to use it to manage my experiments (docker containers). Simply put, let's say:
I have an an experiment ( some code in Tensorflow) I containerized my code inside a docker container -inside the container already set the credentials to my clearml server (i can see logs, plots artifacts etc etc)
Now i am using Tfjobs to run my experiment in the cluster ( https://www.kubeflow.org/docs/components/training/tftraining/ ) My question is how can i make use of clearml agent in this situation to schedule these experiments using queues etc, because we have hundreds of experiments from different teams and have multiple resources (CPUs, DGX A100, MIGs etc). I want to use clearml agent to manage all of that if possible. But i couldn't really understand how to do it.