[Feature flag] Rollout of `load_balancing_for_web_hook_worker`

Summary

Roll out load balancing for the web hooks worker on production, which is currently behind the load_balancing_for_web_hook_worker feature flag.

Owners

• Team: groupmemory
• Most appropriate slack channel to reach out to: #g_memory
• Best individual to reach out to: @mkaeppler
• PM: @fzimmer

Stakeholders

• ~"group::ecosystem"
• EM: @arturoherrero

The Rollout Plan

• Enable on staging
• Percentage Rollout on GitLab.com until we get a clear signal
• Rollout Feature for everyone as soon as it's ready

Expectations

What are we expecting to happen?

DB traffic should shift completely from primary to replicas.

What might happen if this goes wrong?

If the shift doesn't happen, and it still goes to primary, this should not result in any changes compared to the FF not being active. Otherwise, unknown.

What can we monitor to detect problems with this?

• Kibana worker logs
• Thanos dashboard with primary vs replica query counts
• Sidekiq Queue Detail
• Sidekiq Worker Detail
• Replica pool saturation

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 <feature-flag-name> true --dev
  • /chatops run feature set <feature-flag-name> true --staging
• Verify that the feature works as expected. Posting the QA result in this issue is preferable.

Preparation before production rollout

• Ensure that the feature MRs have been deployed to both production and canary.
  • /chatops run auto_deploy status <merge-commit-of-your-feature>
• 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.
• If the feature flag in code has an actor, enable it on GitLab.com for testing groups/projects.
  • /chatops run feature set --<actor-type>=<actor> <feature-flag-name> true
• Verify that the feature works as expected. Posting the QA result in this issue is preferable.

Global rollout on production

• Incrementally roll out the feature.
  • If the feature flag in code has an actor, perform actor-based rollout.
    • /chatops run feature set <feature-flag-name> <rollout-percentage> --actors
  • If the feature flag in code does NOT have an actor, perform time-based rollout (random rollout).
    • /chatops run feature set <feature-flag-name> <rollout-percentage>
  • Enable the feature globally on production environment.
    • /chatops run feature set <feature-flag-name> true
• Announce on the feature issue that the feature has been globally enabled.
• Cross-post chatops slack command to #support_gitlab-com. (more guidance when this is necessary in the dev docs) and in your team channel
• Wait for at least one day for the verification term.

(Optional) Release the feature with the feature flag

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:

• Create a merge request with the following changes. Ask for review and merge it.
  • Set the default_enabled attribute in the feature flag definition to true.
  • Create a changelog entry.
• Ensure that the above 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>
• Close the feature issue to indicate the feature will be released in the current milestone.

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.

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.

• Create a merge request to remove <feature-flag-name> 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 above 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>
• 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 <feature-flag-name> --dev
  • /chatops run feature delete <feature-flag-name> --staging
  • /chatops run feature delete <feature-flag-name>
• Close this rollout issue.

Rollback Steps

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

/chatops run feature set <feature-flag-name> false