Feature Experiment Analysis Cleanup: Archive Notebooks After Decisions Ship

Feature Experiment Analysis Cleanup: Archive Notebooks After Decisions Ship starts with experiment analysis left scattered after the decision shipped. The analysis notebook may look quiet, but quiet is not the same as unused. It can still support a rare workflow, a contract, a rollback path, or an owner who no longer sits near the team doing the cleanup.

Use this note when you need to reduce stale software surface area without turning deletion into the first real test. The useful result is a small decision record: current owner, current purpose, evidence reviewed, reversible first step, caveats, and the rule that prevents the same analysis notebook from returning.

What makes this cleanup risky

The risk is not age. The risk is losing a dependency that is visible only during unusual conditions. In feature experiment analysis cleanup, the review should start by naming the exact behavior the analysis notebook still enables and the exact behavior that has replaced it.

Review area	What to inspect	Cleanup signal
Current owner	Team, service, data owner, or support path	Someone can approve a keep or remove decision
Runtime evidence	launch state, primary metric query, guardrail metrics, scheduled dashboards, roadmap links, and readout owner	Recent use is absent or explained
Replacement path	final experiment decision record	The new path handles the same real cases
Rollback or history	Backup, audit, archive, or recreation plan	A wrong decision is recoverable
Creation path	How new items are created	A prevention rule can stop recurrence

A cleanup candidate with no owner should not be treated as safe. It should be treated as an ownership bug that must be resolved before the final removal.

Evidence checks that fit the subject

Collect several signals before acting:

• Inspect launch state, primary metric query, guardrail metrics, scheduled dashboards, roadmap links, and readout owner.
• Confirm the replacement path, not just the absence of recent edits.
• Review the longest business, reporting, incident, or customer cycle that could still use the analysis notebook.
• Ask the owner to choose keep, narrow, archive, disable, remove, or investigate.

A focused review sample can keep the conversation concrete:

decision: ship variant B
primary_metric: activated_accounts
guardrail: support_contact_rate
archive: experiment-2026-04-checkout-copy

Treat the output as a candidate list, not a deletion command. It proves one slice of behavior and must be paired with ownership, dependency review, and a rollback plan.

Prefer a reversible first move

Good cleanup usually happens in stages. First stop creating new analysis notebook records or references. Then narrow the scope, disable the stale path, or archive the visible surface while watching for unexpected use. Remove only after the waiting window matches how the system is actually used.

Do not rush when the analysis notebook touches security response, customer commitments, billing, compliance, incident recovery, or low-frequency operational work. Also slow down when the replacement changed semantics rather than only names; similar labels can hide different behavior.

Prevention rule

experiments should start with one decision page and expiration dates for temporary dashboards. Add the rule where the analysis notebook is created, not only in a cleanup spreadsheet. The next cleanup should begin with owner and sunset context already attached.

Key takeaways

• Stale analysis notebook cleanup needs evidence about use, ownership, replacement, and reversibility.
• Recent silence is helpful, but it is not enough by itself.
• The best first move is usually narrowing, disabling, or archiving before final removal.
• Prevention belongs in the creation path so the same stale item does not return.