Orchestrator/shared/OrgMyLife/MIGRATION_TO_GITLAB.md

GitLab Migration Plan & Status

What has been done

• The scheduled GitHub workflows have been disabled (Collect AI Tasks, Sync Issues to File, Backup Dismissed Tasks) because of GitHub billing limits that were causing pipeline failures and costing money.
• This repository is being prepared for migration to GitLab.

What needs to be done

In order to get the CI/CD and automation processes running again on GitLab, the following tasks must be completed:

1. Import the repository to GitLab:

   • Migrate the source code.
   • Migrate GitHub Issues, labels, and Projects.

2. Translate GitHub Actions to GitLab CI/CD (.gitlab-ci.yml):

   • Backup Dismissed Tasks: Implement as a GitLab Scheduled Pipeline running every 6 hours.
   • Mark Issues for Review: Migrate to a standard GitLab CI pipeline triggered by pushes changing DONE_ISSUES.md.
   • Collect AI Tasks: Implement as a GitLab Scheduled Pipeline running every 30 minutes.
   • Update Task State on Issue Events: Create a GitLab webhook responding to issue events, or use GitLab CI pipelines with issue event triggers.
   • Deploy to VPS: Migrate to a GitLab CI pipeline triggered on branch pushes to main.
   • Sync Issues to File: Migrate to a GitLab Scheduled Pipeline (every 30 minutes) and/or use GitLab Webhooks for issue event triggers.
   • Sync OrgMyLife Plan to Projects Board: Migrate to a GitLab CI pipeline triggered by pushes to PLAN.md.

3. Configure CI/CD Variables:

   • Transfer any repository secrets or environment variables (such as deployment keys, SSH credentials, API tokens) into GitLab CI/CD Settings under Variables.

4. Runner Configuration:

   • Ensure the GitLab Runners have the necessary capabilities (e.g., Node.js environments) by utilizing standard Docker images in the .gitlab-ci.yml (e.g., image: node:20).

5. Optimize Pipeline Compute Efficiency:

   • Analyze and optimize the pipeline execution to drastically reduce compute time.
   • Context: The previous runner consumed ~2000 minutes of compute time in just 10 days, which is highly inefficient for a small application. Strategies like reducing cron frequencies, utilizing caching, and conditionally running jobs should be implemented.