[Feature flag] Enable auto_merge_process_worker_pipeline

Summary

This issue is to roll out the feature on production, that is currently behind the auto_merge_process_worker_pipeline feature flag.

Owners

Most appropriate Slack channel to reach out to: #g_ci-platform
Best individual to reach out to: @drew
Next best individual to reach out to: @patrickbajao

Expectations

What are we expecting to happen?

a 2-3x increase in the number of AutoMergeProcessWorker job executions
no increase or decrease in the number of merged MRs
no increase or decrease in the number of queries
When this and [Feature flag] Rollout of `auto_merge_process_w... (#496567) are both enabled, we expect to see a shift in SELECT * from merge_requests queries from the CI primary db to the CI replicas.

What can go wrong and how would we detect it?

Merge requests failing to merge
Extra database load somehow?

Grafana Verification Dashboard

This dashboard has primary + replica ops/s for both the main and CI database for PipelineProcessWorker and AutoMergeProcessWorker. The scale of the metrics are very different, so to produce aesthetically meaningful charts we'll probably have to look at just one of the workers at a time. But that link displaying both is a good place to start.

Rollout Steps

Note: Please make sure to run the chatops commands in the Slack channel that gets impacted by the command.

Rollout on non-production environments

Verify the MR with the feature flag is merged to master and has been deployed to non-production environments with /chatops run auto_deploy status <merge-commit-of-your-feature>

Deploy the feature flag at a percentage (recommended percentage: 50%) with /chatops run feature set auto_merge_process_worker_pipeline <rollout-percentage> --actors --dev --pre --staging --staging-ref
Monitor that the error rates did not increase (repeat with a different percentage as necessary).

Enable the feature globally on non-production environments with /chatops run feature set auto_merge_process_worker_pipeline true --dev --pre --staging --staging-ref
Verify that the feature works as expected. The best environment to validate the feature in is staging-canary as this is the first environment deployed to. Make sure you are configured to use canary.
If the feature flag causes end-to-end tests to fail, disable the feature flag on staging to avoid blocking deployments.
- See #e2e-run-staging Slack channel and look for the following messages:
  - test kicked off: Feature flag auto_merge_process_worker_pipeline has been set to true on **gstg**
  - test result: This pipeline was triggered due to toggling of auto_merge_process_worker_pipeline feature flag

For assistance with end-to-end test failures, please reach out via the #test-platform Slack channel. Note that end-to-end test failures on staging-ref don't block deployments.

Specific rollout on production

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

Ensure that the feature MRs have been deployed to both production and canary with /chatops run auto_deploy status <merge-commit-of-your-feature>
Depending on the type of actor you are using, pick one of these options:
- For project-actor: /chatops run feature set --project=gitlab-org/gitlab,gitlab-org/gitlab-foss,gitlab-com/www-gitlab-com auto_merge_process_worker_pipeline true
- For group-actor: /chatops run feature set --group=gitlab-org,gitlab-com auto_merge_process_worker_pipeline true
- For user-actor: /chatops run feature set --user=drew auto_merge_process_worker_pipeline true
- For all internal users: /chatops run feature set --feature-group=gitlab_team_members auto_merge_process_worker_pipeline true
Verify that the feature works for the specific actors.

Preparation before global rollout

Set a milestone to this rollout issue to signal for enabling and removing the feature flag when it is stable.
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 exists for the feature, and the version history text has been updated.
Ensure that any breaking changes have been announced following the release post process to ensure GitLab customers are aware.
Notify the #support_gitlab-com Slack channel 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 must be executed in the #production Slack channel and cross-posted (with the command results) to the responsible team's Slack channel.

Incrementally roll out the feature on production.
- Between every step wait for at least 15 minutes and monitor the appropriate graphs on https://dashboards.gitlab.net.
After the feature has been 100% enabled, wait for at least one day before releasing the feature.

(Optional) Release the feature with the feature flag

WARNING: This approach has the downside that it makes it difficult for us to clean up the flag. For example, on-premise users could disable the feature on their GitLab instance. But when you remove the flag at some point, they suddenly see the feature as enabled and they can't roll it back to the previous behavior. To avoid this potential breaking change, use this approach only for urgent matters.

See instructions if you're sure about enabling the feature globally through the feature flag definition

If you're still unsure whether the feature is deemed stable but want to release it in the current milestone, you can change the default state of the feature flag to be enabled. To do so, follow these steps:

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 the auto_merge_process_worker_pipeline feature flag. Ask for review/approval/merge as usual. The MR should include the following changes:
- Remove all references to the feature flag from the codebase.
- Remove the YAML definitions for the feature from the repository.
Ensure that the cleanup MR has been included in the release package. If the merge request was deployed before the monthly release was tagged, the feature can be officially announced in a release blog post: /chatops run release check https://gitlab.com/gitlab-org/gitlab/-/merge_requests/167095 17.5
Close [the feature issue][#483008 (closed)] to indicate the feature will be released in the current milestone.
Once the cleanup MR has been deployed to production, clean up the feature flag from all environments by running these chatops command in #production channel: /chatops run feature delete auto_merge_process_worker_pipeline --dev --pre --staging --staging-ref --production
Close this rollout issue.

Rollback Steps

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

/chatops run feature set auto_merge_process_worker_pipeline false

Disable the feature flag on non-production environments:

/chatops run feature set auto_merge_process_worker_pipeline false --dev --pre --staging --staging-ref

Delete feature flag from all environments:

/chatops run feature delete auto_merge_process_worker_pipeline --dev --pre --staging --staging-ref --production

Edited Oct 29, 2024 by drew stachon