Basically two options, spin the clearml-k8s-glue, as a k8s service.
This service takes clearml jobs and creates k8s job on your cluster.
The second option is to spin agents inside pods statically, then inside the pods the agent work in venv model.
I know the enterprise edition has more sophisticated k8s integration where the glue also retains the clearml scheduling capabilities.
From the documentation https://github.com/allegroai/clearml-agent :
` Two K8s integration flavours
Spin ClearML-Agent as a long-lasting service pod
use clearml-agent docker image
map docker socket into the pod (soon replaced by podman)
allow the clearml-agent to manage sibling dockers
benefits: full use of the ClearML scheduling, no need to worry about wrong container images / lost pods etc.
downside: Sibling containers `