[Feature flag] Rollout of `respawn_assign_resource_worker`
Summary
This issue is to roll out the feature on production,
that is currently behind the respawn_assign_resource_worker
feature flag.
Owners
- Most appropriate Slack channel to reach out to:
#g_environments
- Best individual to reach out to: @partiaga
Expectations
What are we expecting to happen?
We have an issue where GitLab Pipelines where some jobs have a Resource Group sometimes gets stuck due to a race condition caused by Sidekiq worker deduplication.
When this feature is enabled, we expect that pipelines will no longer run into this race condition and will not get stuck.
What can go wrong and how would we detect it?
While we can't foresee anything going drastically wrong, we could observe the following areas:
Sentry
Observe AssignResourceFromResourceGroupWorker
in Sentry for error events
Elastic Search
In ElasticSearch, look up logs for the AssignResourceFromResourceGroupWorker:
- source:
pubsub-sidekiq-inf-gprd
- filter:
json.class = Ci::ResourceGroups::AssignResourceFromResourceGroupWorker
You can also filter further on the following fields:
-
json.job_status
= possible values:start|done|failed
-
json.meta.project
= the full path to the project
The main to watch out for are the number of jobs with status start
and failed
, comparing the numbers before and after the Feature Flag is enabled.
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 have 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 respawn_assign_resource_worker <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 respawn_assign_resource_worker 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
#qa-staging
Slack channel and look for the following messages:- test kicked off:
Feature flag respawn_assign_resource_worker has been set to true on **gstg**
- test result:
This pipeline was triggered due to toggling of respawn_assign_resource_worker feature flag
- test kicked off:
- See
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 should 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 respawn_assign_resource_worker true
- For group-actor:
/chatops run feature set --group=gitlab-org,gitlab-com respawn_assign_resource_worker true
- For user-actor:
/chatops run feature set --user=partiaga respawn_assign_resource_worker true
- For project-actor:
-
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. -
Leave a comment on the feature issue announcing estimated time when this feature flag will be enabled on GitLab.com. -
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). -
Ensure that the feature flag rollout plan is reviewed by another developer familiar with the domain.
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_environments
).
-
(Optional) Incrementally roll out the feature on production environment. - Between every step wait for at least 15 minutes and monitor the appropriate graphs on https://dashboards.gitlab.net.
- Perform actor-based rollout:
/chatops run feature set respawn_assign_resource_worker <rollout-percentage> --actors
-
Enable the feature globally on production environment: /chatops run feature set respawn_assign_resource_worker true
-
Observe appropriate graphs on https://dashboards.gitlab.net and verify that services are not affected. -
Leave a comment on [the feature issue][main-issue] announcing that the feature has been globally enabled. -
Wait for at least one day for the verification term.
(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:
-
Create a merge request with the following changes. Ask for review and merge it. -
If feature was enabled for various actors, ensure the feature has been enabled globally on production /chatops run feature get respawn_assign_resource_worker
. If the feature has not been globally enabled then enable the feature globally using:/chatops run feature set respawn_assign_resource_worker true
-
Set the default_enabled
attribute in the feature flag definition totrue
. -
Decide which changelog entry is needed.
-
-
Ensure that the default-enabling 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 <merge-request-url> 16.10
-
Consider cleaning up the feature flag from all environments by running these chatops command in #production
channel. Otherwise these settings may override the default enabled:/chatops run feature delete respawn_assign_resource_worker --dev --pre --staging --staging-ref --production
-
Close [the feature issue][main-issue] to indicate the feature will be released in the current milestone. -
Set the next milestone to this rollout issue for scheduling the flag removal. -
(Optional) You can create a separate issue for scheduling the steps below to Release the feature. -
Set the title to "[Feature flag] Cleanup respawn_assign_resource_worker
". -
Execute the /copy_metadata <this-rollout-issue-link>
quick action to copy the labels from this rollout issue. -
Link this rollout issue as a related issue. -
Close this rollout issue.
-
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 respawn_assign_resource_worker
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.
- Create a changelog entry.
-
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 <merge-request-url> 16.10
-
Close [the feature issue][main-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 respawn_assign_resource_worker --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 respawn_assign_resource_worker false
-
Disable the feature flag on non-production environments:
/chatops run feature set respawn_assign_resource_worker false --dev --pre --staging --staging-ref
-
Delete feature flag from all environments:
/chatops run feature delete respawn_assign_resource_worker --dev --pre --staging --staging-ref --production