Epic Goal

• Upgrade the exisitng single test pipeline to make it stable and reliable to run single e2e tests. 
• Network connection issues
• Upstream using resources (e.g go version, helm chart) instead pulling from resources, we add our image , permission to run script, download.
• Manually clean up after pipeline finished.

Why is this important?

• It is not possilbe for all QE folk to execute single e2e tests locally and therefor a reliable, stable pipeline is needed. Spefically during release-testing cycles for failure investigation or verifying test-flakes etc. 
• Currently the pipeline is unstable, unreliable and is not repeatable (on same cluster). 

Scenarios

• Specific improvents required are **
  • Less relicance on upstream. Upgrage out TEST_IMAGE with necessary resrouces that we have full control over.
  • Improve robustness and error handling - 
  • Perform verifications of argcocd status  (scale up and sacle down) and availablity during execute to further enure reliabily. 
  • Improve logs and logging for better debugging. 
  • Comprehensive clean up - ensure cluster is restored to a 'before test' state with suitable scale-up. 

Other Considerations

• This does not include specific test failure investifations. 

Definition of Ready

• The epic has been broken down into stories.
• Stories have been scoped.
• The epic has been stack ranked.

Definition of Done

• Code Complete:
  • All code has been written, reviewed, and approved.
• Tested:
  • Unit tests have been written and passed.
  • Integration tests have been completed.
  • System tests have been conducted, and all critical bugs have been fixed.
  • Tested on OpenShift either upstream or downstream on a local build.
• Documentation:
  • User documentation or release notes have been written.
• Build:
  • Code has been successfully built and integrated into the main repository / project.
• Review:
  • Code has been peer-reviewed and meets coding standards.
  • All acceptance criteria defined in the user story have been met.
  • Tested by reviewer on OpenShift.
• Deployment:
  • The feature has been deployed on OpenShift cluster for testing.
• Acceptance:
  • Product Manager or stakeholder has reviewed and accepted the work.