Right now archiving of the completed release is based on elapsed time that is set after which the completed release is automatically archived.
In order to clean up the completed release that takes up space and has bad data or executed in error, there is no option to archive such released except to wait for certain number of days before it is systematically archived.
We should have an option to select and archived any release at anytime.
by: Shad W. | 7 months ago | Templates & Releases
Comments
Thank you for the suggestion.
Regarding the cleanup of unnecessary releases, we propose an automatic approach, particularly when dealing with high release volumes where manual cleanup might not be practical.
In situations where there are numerous releases in a failed state, users with dedicated Abort permissions can manually terminate such releases from the Release Flow page. These aborted releases could be filtered out from the Releases list to declutter the view.
We seek a deeper understanding of your use case:
- What is the typical daily and weekly count of releases categorized as "completed releases occupying space with erroneous data or executed in error"?
- How are releases terminated when they fail due to execution errors? Is it through automation, such as a dedicated script, or a manual process where the team aborts them?
- Are there specific releases defined by some criteria, that you prefer to delete, skipping the archiving?
Linking additional request for archiving: https://ideas.digital.ai/devops/Idea/Detail/4054
While the feature of automatic archiving based on a set of parameters is useful, I am asking for an additional feature for selective archiving. The reason is that there could be specific releases that may be in failed/passed/incomplete state that may be needed for archiving - for cleaning the release lists, weed out unique runs that could skew the dashboard, etc. In such scenario we don't want to archive the entire batch based on when the release was executed but remove a few selected ones.
Linking similar request: https://ideas.digital.ai/devops/Idea/Detail/4479