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Experiment Rollout: `promote_ultimate_features`

Summary

This issue tracks the rollout and status of an experiment through to removal.

  1. Feature flag name: promote_ultimate_features
  2. Epic or issue link: &11792

This is an experiment rollout issue using the scoped experiment label. As well as defining the experiment rollout and cleanup, this issue incorporates the relevant Feature Flag Roll Out steps.

Owners

Stakeholders

Expectations

What are we expecting to happen?

This will reveal the alternative promotion of paid features on Learn GitLab

What might happen if this goes wrong?

What can we monitor to detect problems with this?

QA

  • PM (@p_cordero) to tick this off when all QA has been completed and passed

Confirm experiment on STAGING

  1. Go to https://staging.gitlab.com/-/trial_registrations/new and go through trial registration

Assignment

Confirm that assignment events are populating on STAGING https://app.periscopedata.com/app/gitlab/1120337/Growth-Experiment-Event-Validation

Control / Candidate experience

Does the control & candidate user experience work as expected? Does it match designs? Discover potential edge cases?

Control

  • Confirm that 'Included in Trial' appears

Candidate

  • Confirm that the 'Ultimate' badge appears and the tool tip loads

  • Confirm that a free user does not see this

  • Confirm that a free user directed to trial sees this

Tracked data

https://app.periscopedata.com/app/gitlab/1120337/Growth-Experiment-Event-Validation

Note: you can use the CXL calculator to determine if your experiment has reached significance. The calculator includes an estimate for how much longer an experiment must run for before reaching significance.

Rollout plan

  • Runtime in days, or until we expect to reach statistical significance: We will monitor impact to 2nd user adds for minimum 1 month.
  • We will roll this out behind a feature flag and expose this to 30% of actors to start then ramp it up from there.

/chatops run feature set <feature-flag-name> <rollout-percentage> --actors

Status

Preferred workflow

The issue should be assigned to the Product manager (PM) or Engineer (Eng) as follows:

  1. PM determines and manages the status of the experiment (assign this issue to the PM)
  2. PM asks for initial rollout on production, or changes to the status (assign to an Eng)
  3. Eng changes the status using chatops (reassign to the PM)
  4. When concluded, PM updates the 'Roll Out Steps' and adds a milestone (assigns to an Eng)

The current status and history can be viewed using the:

In this rollout issue, ensure the scoped experiment:: label is kept accurate.

Experiment Results

Roll Out Steps

  • Confirm that end-to-end tests pass with the feature flag enabled. If there are failing tests, contact the relevant stable counterpart in the Quality department to collaborate in updating the tests or confirming that the failing tests are not caused by the changes behind the enabled feature flag.
  • Enable on staging (/chatops run feature set promote_ultimate_features true --staging)
  • Test on staging
  • Ensure that documentation has been updated
  • Enable on GitLab.com for individual groups/projects listed above and verify behaviour (/chatops run feature set --project=gitlab-org/gitlab ultimate_trial_benefit_modal true)
  • Coordinate a time to enable the flag with the SRE oncall and release managers
    • In #production mention @sre-oncall and @release-managers. Once an SRE on call and Release Manager on call confirm, you can proceed with the rollout
  • Announce on the issue an estimated time this will be enabled on GitLab.com
  • Enable on GitLab.com by running chatops command in #production (/chatops run feature set <feature-flag-name> true)
  • Cross post chatops Slack command to #support_gitlab-com (more guidance when this is necessary in the dev docs) and in your team channel
  • Announce on the issue that the flag has been enabled
  • Remove experiment code and feature flag and add changelog entry - a separate cleanup issue might be required
  • After the flag removal is deployed, clean up the feature flag by running chatops command in #production channel
  • Assign to the product manager to update the knowledge base (if applicable)

Rollback Steps

  • This feature can be disabled by running the following Chatops command:
/chatops run feature set promote_ultimate_features false

Experiment Successful Cleanup Concerns

Items to be considered if candidate experience is to become a permanent part of GitLab

Edited by Paige Cordero