Aglet

Learn from repeated partial-rollout divergence

Repeated cohort divergence usually exposes a weakness in rollout context or comparison design. Review prior episodes for the same boundary, dependency, data shape, or regional pattern. The lesson should improve how teams see exposure and decide before the next expansion.

Keep the lesson for the next incident

  1. Cluster by boundary

    Group previous episodes by region, tenant class, flag state, version pair, or dependency route. Record which dimensions repeated and which were incidental. Do not merge episodes solely because they happened during staged releases.

  2. Improve the control

    Document whether the unexposed cohort was truly comparable and what signal arrived too late. Choose one stronger control, such as a matched path or version marker, that can be captured without changing product behavior.

  3. Create a review memory

    Write the rollout checkpoint, evidence owner, and recurrence condition in the release record. Include the cohort query or stable identifiers so the next reviewer can recognize the pattern before exposure expands.

What to carry forward

The lesson is useful when it changes one repeatable comparison or decision point and names the signal that should reveal recurrence. Keep the boundary conditional until later rollout evidence confirms that the improved control is timely and comparable.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

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