[Feature flag] Rollout of `update_all_mirrors_job_tracker`

Summary

This issue is to rollout Use ProjectImportScheduleWorker's processing count in UpdateAllMirrorsWorker on production, that is currently behind the update_all_mirrors_job_tracker feature flag.

This flag should be rollout after project_import_schedule_worker_job_tracker flag is rolled out and runs stable.

In the MR, we use JobTracker to track for the current number of processing jobs of ProjectImportScheduleWorker. This number is used in UpdateAllMirrorsWorker to account for capacity management. We hid this tracking behind this feature flag to prevent an unexpected effect on mirroring feature.

Owners

• Team: Scalablity Team
• Most appropriate slack channel to reach out to: #g_scalability
• Best individual to reach out to: @qmnguyen0711

Expectations

What are we expecting to happen?

After this flag is on, the number of requests to Redis-sidekiq should not stay the same, or slightly increases. This flag is used in a worker belong to Mirror logic. So, the mirroring feature should work as expected.

What might happen if this goes wrong?

There are two possibilities if something goes wrong:

• The mirror feature is broken
• Redis-sidekiq receives an unexpected peak

What can we monitor to detect problems with this?

• All operating metrics of the following workers are normal:
  • ProjectImportScheduleWorker: https://dashboards.gitlab.net/d/sidekiq-worker-detail/sidekiq-worker-detail?orgId=1&var-PROMETHEUS_DS=Global&var-environment=gprd&var-stage=main&var-worker=ProjectImportScheduleWorker
  • UpdateAllMirrorsWorker: https://dashboards.gitlab.net/d/sidekiq-worker-detail/sidekiq-worker-detail?orgId=1&var-PROMETHEUS_DS=Global&var-environment=gstg&var-stage=main&var-worker=UpdateAllMirrorsWorker
• All operating metrics of redis-sidekiq is normal: https://dashboards.gitlab.net/d/redis-sidekiq-main/redis-sidekiq-overview?orgId=1

Rollout Steps

Rollout on non-production environments

• Ensure that the feature MRs have been deployed to non-production environments.
  • /chatops run auto_deploy status <merge-commit-of-your-feature>
• Enable the feature globally on non-production environments.
  • /chatops run feature set update_all_mirrors_job_tracker true --dev
  • /chatops run feature set update_all_mirrors_job_tracker true --staging
• Verify that the feature works as expected. Posting the QA result in this issue is preferable.

Preparation before global rollout

• Check if the feature flag change needs to be accompanied with a change management issue. Cross link the issue here if it does.
• Ensure that you or a representative in development can be available for at least 2 hours after feature flag updates in production. If a different developer will be covering, or an exception is needed, please inform the oncall SRE by using the @sre-oncall Slack alias.
• Ensure that documentation has been updated (More info).
• Announce on the feature issue an estimated time this will be enabled on GitLab.com.
• Notify #support_gitlab-com and your team channel (more guidance when this is necessary in the dev docs).

Global rollout on production

For visibility, all /chatops commands that target production should be executed in the #production slack channel and cross-posted (with the command results) to the responsible team's slack channel (#g_TEAM_NAME).

• Incrementally roll out the feature.
  • Enable the feature globally on production environment.
    • /chatops run feature set update_all_mirrors_job_tracker true
• Announce on the feature issue that the feature has been globally enabled.
• Wait for at least one day for the verification term.

Release the feature

After the feature has been deemed stable, the clean up should be done as soon as possible to permanently enable the feature and reduce complexity in the codebase.

You can either create a follow-up issue for Feature Flag Cleanup or use the checklist below in this same issue.

• Create a merge request to remove update_all_mirrors_job_tracker feature flag. Ask for review and merge it.
  • Remove all references to the feature flag from the codebase.
  • Remove the YAML definitions for the feature from the repository.
  • Create a changelog entry.
• Ensure that the cleanup MR has been deployed to both production and canary. If the merge request was deployed before the code cutoff, the feature can be officially announced in a release blog post.
  • /chatops run auto_deploy status <merge-commit-of-cleanup-mr>
• Close the feature issue to indicate the feature will be released in the current milestone.
• Clean up the feature flag from all environments by running these chatops command in #production channel:
  • /chatops run feature delete update_all_mirrors_job_tracker --dev
  • /chatops run feature delete update_all_mirrors_job_tracker --staging
  • /chatops run feature delete update_all_mirrors_job_tracker
• Close this rollout issue.

Rollback Steps

• This feature can be disabled by running the following Chatops command:

/chatops run feature set update_all_mirrors_job_tracker false