To address the issue of JupyterHub Helm deploys showing changes in Ansible due to regenerated elements like checksums and secrets, you can use specific annotations and strategies to ignore these changes. Here's a potential solution:

Patch Helm Hooks: Modify the Helm templates to include annotations that make certain elements immutable unless truly necessary. For example:

yaml code
annotations:

"helm.sh/hook": pre-install,pre-upgrade
"helm.sh/hook-delete-policy": before-hook-creation,hook-succeeded

Customize Ansible Tasks: Adjust your Ansible playbooks to exclude specific tasks or resources that frequently change and do not impact the actual deployment.

Use Helm Secrets Plugin: Consider using the Helm secrets plugin to manage sensitive data outside of the main deployment process, which can help reduce unnecessary changes.

Helm Post-Render Hook: Implement a Helm post-render hook to filter out non-critical changes before Ansible checks for differences. Check with these above mentioned steps.

I agree, that the checksums and secrets could be stored as annotations. Though the image puller job would be more difficult to manage in a similar fashion. And in this case, the thing being deployed is the main part of the project, so not reporting changes isn't ideal. Leaving it as always showing changed, may be the better option.

To manage JupyterHub Helm deploys with Ansible, where certain elements always show as changed (like image puller job and secret annotations), here’s an effective strategy:

Accept Routine Changes: Document in your Ansible playbook or runbook that specific components (checksums, secrets, image puller jobs) will consistently show changes. This sets clear expectations for those managing the deployments.

Add Comments: In your automation scripts, include comments explaining why these components change frequently. This helps anyone reviewing the scripts understand that these changes are normal and expected.

In your Ansible playbook:

yaml code

• name: Deploy JupyterHub with Helm helm: name: jupyterhub chart: jupyterhub/jupyterhub values: values.yaml register: helm_deploy

• name: Annotate routine changes debug: msg: "Note: Checksum, secrets, and image puller jobs will always show changes. This is expected behavior." when: helm_deploy.changed

By documenting and commenting on these routine changes, you maintain transparency and clarity without suppressing important updates. This approach ensures that your deployment process is both accurate and understandable.