Hi @<1618780810947596288:profile|ExuberantLion50>

I’m trying to containerize a task using clearml-agent build, following instructions from the docs online.

Do you mean to create a container with the Task's environment for debugging ?
If this is for running the Task there is no need to create a specific container for it, both code and python env are cached.

yes, specifically i'm following this: None

I'm getting lot of bizarre errors running without a docker image attached (still haven't gotten through all the issues in docker but i'm getting a lot further). For example, running the exact same pipeline in docker mode completes the first step fine but without docker i'm getting this:
virtualenv: error: argument dest: the destination . is not write-able at /home/david/.clearml/venvs-builds/3.10
SystemExit: 2
clearml_agent: ERROR: Command '['python3.10', '-m', 'virtualenv', '/home/david/.clearml/venvs-builds/3.10']' returned non-zero exit status 2.

I'm getting lot of bizarre errors running without a docker image attached

I think there is a mix in terminology
ClearML Agent can run in two different modes:

• virtual env - where it create a new venv for every Task executed
• docker mode- where it spins a docker as Base environment, then inside the docker (in real time) it will fetch the code, install missing python packages etc.There is no need to build a specific docker container, for example you can use the "python:3.10-bullseye" docker from dockerhub as a base docker for the Task (just set it in the Tasks execution section in the UI) , or from code via task.set_base_docker
  wdyt?