Deployment rework rate
Target operating model — recommended contracts, not installed collection. All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
Prototype calculation — no live telemetry. The synthetic example calculates this metric; it has no network collectors.
Unplanned production deployment effects triggered by a production incident as a share of deployment effects.
| Contract | Definition |
|---|---|
| Numerator | Distinct incident-linked deployment_ids classified unplanned remediation |
| Denominator | All distinct production deployment_ids with production effect in window |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Production deployment effects in window with immutable planned/unplanned classification and incident linkage. |
| Exclusions | Nonproduction, no-effect retries and duplicates; do not exclude unclassified changes silently. |
| Events and source | deployment.completed; incident.linked; release intent classification |
| Owner / cadence | Platform & IT / Weekly |
| Missing evidence | Unknown classification stays denominator; observed numerator is lower bound until reconciliation; show classification coverage. |
| Gaming and limits | Call hotfixes planned; freeze reason and independently reconcile incident/deployment links. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Distinct from failure rate: one failed deployment can lead to multiple separate rework deployments. |
Read the shared collection and safeguards before collecting data; see the synthetic example and limits.
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