The aim of this epic is to implement end-to-end automation for RHEL AI releases. The goal is to build a workflow that, given a RHEL AI drop, automatically generates a Merge Request with the corresponding release objects in https://gitlab.com/redhat/rhel-ai/ci-cd/aipcc-product-management-configs/.

Once the MR is created, it can be reviewed and validated through the standard GitLab workflow. After approval and merge, the release pipeline in Konflux will be triggered, allowing the team to monitor and verify the release process from there.

Ideally, this approach could establish a reusable pattern that other products can adopt, helping standardize release automation.

Automation worflow:

Workflow explanation

1. Trigger
   The process starts when a new RHEL AI drop is available.

1. Render manifests
   Automation generates the required release manifests and objects based on the drop. These manifests define the artifacts and metadata required for the release.

1. Validation layer (MR)
   The generated manifests are committed automatically as a Merge Request in the aipcc-product-management-configs repository. This acts as a validation and control layer where changes are visible and traceable.

1. Review
   Engineers review the generated MR to ensure the release configuration is correct. This step keeps a human approval gate while still automating the generation work.

1. CD pipeline
   Once the MR is approved and merged, the Continuous Delivery pipeline is triggered automatically.

1. Apply release
   The pipeline executes the release process in Konflux, where the release objects are applied and the release can be monitored.