Retiring an OpenStack project

As part of migrating Oslo Incubator code to graduated libraries I have come across several inactive OpenStack projects. (An inactivate project does not mean the project should be retired or removed). However in my case when consulting the mailing list , it was confirmed that the kite project met the criteria to proceed.

There are good procedures to Retiring a project in the Infra manual. In summary these steps are:

  • Inform the developer community via the mailing list of the intention to retire the project, confirming there are no unaware interested parties.
  • Submit an openstack-infra/project-config change to remove the zuul gate jobs that are run when reviews are submitted. This is needed as the subsequent review to remove code will fail if these checks are enabled..
  • Submit a project review that removes all code, and updates the README with a standard message “This project is no longer maintained. …” See Infra manual for full details. This change will have a Depends-On: for your project-config review. If this review is not yet merged, you should add a Needed-By: reference accordingly.
  • Following the approved review to remove the code from HEAD, a subsequent review to openstack-infra/project-config is needed to remove other infrastructure usage of the project and mark the project as read only.
  • Finally, a request to openstack/governance is made to propose removal of the repository from the governance.

As with good version control, the resulting code for the project is not actually removed.
As per the commit comment you simply git checkout HEAD^1 to access the project in question.

Tagged with: Cloud Computing OpenStack

Related Posts

My take on PyCon Australia 2026

PyCon AU 2026 held in Brisbane this week was a five day event for the Python community. With specialized tracks and dedicated tutorial and engineering days there was a wide variety of content available.

Read more

Fixing Old Software Bugs Without Thinking

I previously came across an issue in my benchmarking work where I relied on the Latency Histogram section of sysbench output. On Linux it worked fine — I generally ran my workload there, so it never mattered.

Read more

Curating DuckDB Datasets Leveraging AI

In Curated MySQL Data Sets for Realistic Testing I described datasets assembled the manual way — download, schema, load, validate, document — over hours or days per source. This post is the follow-up I promised: what changes when AI assists the same workflow, using DuckDB as the target engine and GeoNames as the first example.

Read more