[FF] Rollout the feature flag remove_limit_ci_job_token_scope
Summary
This issue is to roll out the feature on production,
that is currently behind the remove_limit_ci_job_token_scope
feature flag.
Owners
- Most appropriate Slack channel to reach out to:
#g_sscs_pipeline-security
- Best individual to reach out to: @jmallissery
Expectations
What are we expecting to happen?
What can go wrong and how would we detect it?
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 remove_limit_ci_job_token_scope <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 remove_limit_ci_job_token_scope 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 remove_limit_ci_job_token_scope has been set to true on **gstg**
- test result:
This pipeline was triggered due to toggling of remove_limit_ci_job_token_scope feature flag
- test kicked off:
- See
If you encounter end-to-end test failures and are unable to diagnose them, you may reach out to the #s_developer_experience
Slack channel for assistance. 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 remove_limit_ci_job_token_scope true
- For group-actor:
/chatops run feature set --group=gitlab-org,gitlab-com remove_limit_ci_job_token_scope true
- For user-actor:
/chatops run feature set --user=jmallissery remove_limit_ci_job_token_scope true
- For all internal users:
/chatops run feature set --feature-group=gitlab_team_members remove_limit_ci_job_token_scope 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. -
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. - Example:
/chatops run feature set remove_limit_ci_job_token_scope <rollout-percentage> --actors
. - Between every step wait for at least 15 minutes and monitor the appropriate graphs on https://dashboards.gitlab.net.
- Example:
-
After the feature has been 100% enabled, wait for at least one day before releasing the feature.
Cleanup
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 the remove_limit_ci_job_token_scope
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 <merge-request-url> 18.0
-
Close the feature issue 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 remove_limit_ci_job_token_scope --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 remove_limit_ci_job_token_scope false
-
Disable the feature flag on non-production environments:
/chatops run feature set remove_limit_ci_job_token_scope false --dev --pre --staging --staging-ref
-
Delete feature flag from all environments:
/chatops run feature delete remove_limit_ci_job_token_scope --dev --pre --staging --staging-ref --production