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[Feature flag] Enable GitLab Duo breadcrumbs entry point

Summary

This issue is to rollout the GitLab Duo breadcrumbs entry point on production, that is currently behind the tanuki_bot_breadcrumbs_entry_point feature flag.

The breadcrumbs entry point refers to a button that is visible on every page of GitLab (to users with the appropriate tier & correct settings) in the top-right:

image

Why are we enabling this feature flag?

We have quite low usage of the GitLab Duo Chat as the chat is intentionally not very discoverable. We know from internal testing that the accuracy of the AI is lower than we would like. (Scroll to bottom of page: User satisfaction..).

The chat was developed in the typical GitLab product development process - meaning we did not have a specific user problem to solve, and instead made some guesses about customer problems. We need to refine our product direction by learning from users and iterating.

We have learned about trends of what users are using the chat for via internal testing, but ultimately we are basing those trends on low usage (about 150 questions).

By promoting the feature more prominently, we intend to get more usage to further understand how users are using the chat, how accurate the chat is, UX feedback etc.

How we will measure success

Initially we plan to enable this feature flag for 5% of eligible users, which we estimate to be 1050 users. There is a concern that 5% is too low of a number to have any meaningful impact on statistical metrics.

How will learn from additional users

Rollout criteria

The purpose of enabling this feature flag is to learn from our users, refine our product direction, and improve UX.

The criteria to rollout to 100% is tied to answer quality:

We can role out to 100% once we have achieved >80% good and excellent answers and <5% terrible answers. Until then we‘ll leave it a 5% (if that results in too little usage, we can add another 5%).

https://gitlab.com/gitlab-org/gitlab/-/issues/425954#note_1613417716

We measure answer quality via UXR bashes and (eventually) the test framework.

We will initially roll this feature flag out to 5%. If we do not get the usage data and UX research participants we need, we may choose to roll out to an additional 5%.

Rollout plan (written 2023-10-25)

  • Today we are not ready with the test framework, so accuracy is measured by UX bashes.
  • It's unclear (technically/privacy/legal-wise) if we will be able to recruit users for the UX bash based on their usage of this feature. If not, recruitment will take longer.

Estimated timeframes

  • 1 - 3 weeks user recruitment & scheduling
  • 1 week: give participants time to complete the UX bash
  • 2 - 3 days analysis of UX bash:
    • Categorizing questions
    • Add latest accuracy scoring to Sisense dashboard
    • Create data visualizations
  • Present findings to the team and determine on next steps, e.g.:
    • Do we see trends in what users are asking that we do not support? If so, does that impact any of our plans?
    • Evaluate accuracy score over time - are there particular questions or topics we need to focus on?

Rollout percentage

It is estimated that 21,000 users have the appropriate tier and settings to access the chat. We intended to target the first enablement of this feature flag to 5% of those users (approx. 1000 users). However, we cannot target a feature flag for such a specific subset of users.

Possible solutions:

Owners

  • Team: groupai framework
  • Most appropriate slack channel to reach out to: #g_ai_framework
  • Best individual to reach out to: @oregand
  • PM: NAME

Stakeholders

Expectations

What are we expecting to happen?

When is the feature viable?

What might happen if this goes wrong?

What can we monitor to detect problems with this?

Consider mentioning checks for 5xx errors or other anomalies like an increase in redirects (302 HTTP response status)

What can we check for monitoring production after rollouts?

Consider adding links to check for Sentry errors, Production logs for 5xx, 302s, etc.

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.
  • Verify that the feature MRs have been deployed to non-production environments with:
    • /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 --staging --staging-ref
    • If the feature flag causes QA end-to-end tests to fail:
      • Disable the feature flag on staging to avoid blocking deployments.
  • Verify that the feature works as expected. Posting the QA result in this issue is preferable. The best environment to validate the feature in is staging-canary as this is the first environment deployed to. Note you will need to make sure you are configured to use canary as outlined here when accessing the staging environment in order to make sure you are testing appropriately.

For assistance with QA end-to-end test failures, please reach out via the #quality Slack channel. Note that QA 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 (#g_TEAM_NAME).

  • Ensure that the feature MRs have been deployed to both production and canary.
    • /chatops run auto_deploy status <merge-commit-of-your-feature>
  • Depending on the type of actor you are using, pick one of these options:
    • If you're using project-actor, you must enable the feature on these entries:
      • /chatops run feature set --project=gitlab-org/gitlab,gitlab-org/gitlab-foss,gitlab-com/www-gitlab-com <feature-flag-name> true
    • If you're using group-actor, you must enable the feature on these entries:
      • /chatops run feature set --group=gitlab-org,gitlab-com <feature-flag-name> true
    • If you're using user-actor, you must enable the feature on these entries:
      • /chatops run feature set --user=<your-username> <feature-flag-name> true
  • Verify that the feature works on the specific entries. Posting the QA result in this issue is preferable.

Preparation before global rollout

  • Set a milestone to the 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 has been updated (More info).
  • 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 #support_gitlab-com 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_TEAM_NAME).

  • Incrementally roll out the feature.
    • Between every step wait for at least 15 minutes and monitor the appropriate graphs on https://dashboards.gitlab.net.
    • 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> --random
    • Enable the feature globally on production environment.
      • /chatops run feature set <feature-flag-name> true
  • Observe appropriate graphs on https://dashboards.gitlab.net and verify that services are not affected.
  • Leave a comment on the feature 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

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.
  • 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> <milestone>
  • 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 <feature-flag-name> --dev --staging --staging-ref --production
  • Close the feature 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 <feature-flag-name>".
    • 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.

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.

The follow-up issue, handling the release of the feature: Removal of the tanuki_bot_breadcrumbs_entry_poi... (#454095 - closed)

Rollback Steps

  • This feature can be disabled by running the following Chatops command:
/chatops run feature set <feature-flag-name> false
Edited by Denys Mishunov