Would that mean if you are running 2-3 clearml agents for 2-3 projects that their environment has to be such that they could run each of the 3 projects (each having different requirements)?

What is the pattern to start an agent within the project specific docker container based on the task? Would that be handled via the service queue? Or can you already configure that on a task level providing a docker file?

Do we support GPUs in a) docker mode b) k8s glue?

So on the ec2 instance (with the agent running), just install prior to running the agent:
apt-get install poppler-utils

I am not running in Docker mode

I guess this is a advantage with docker mode. Will try that out as well sometime.

In the docker bash startup script
apt-get install poppler-utils

This Docker Mode - https://allegro.ai/clearml/docs/docs/use_cases/clearml_agent_use_case_examples.html#docker-mode

Hi JealousParrot68
spinning the clearml-agent with docker support (i.e. each experiment is running inside its own container):
https://clear.ml/docs/latest/docs/clearml_agent#docker-mode
Basically you can specify a default docker to use (per agent) and a specific docker container to use per Task (configured in the UI under execution at the bottom)

Is there a good reference to get started with k8s glue?

All right, that’s the only way? 🙂

Basic question - i am running clearml agent in a ubuntu ec2 machine. Does it use docker by default? I thought it uses docker only if I add the --docker flag?

Do we support GPUs in a) docker mode b) k8s glue?

yes on both

Is there a good reference to get started with k8s glue?

A few folks here already set it up, do you have a k8s cluster with GPU support ?