A deployment scorecard without an individual league table
A fictional service records two hundred production deployments during a quarter. Twelve require immediate remediation after causing a production failure. The team also records eight unplanned deployments that were made because of incidents; the supplied definitions and denominators are fixed for this exercise, and these two counts need not describe the same events. A sponsor wants to compare the service directly with an unrelated safety-critical system and publish an individual engineer ranking based on deployment volume. The team instead proposes a shared service-level review alongside customer impact and recovery evidence. It must calculate the two given rates while explaining the limits of a count. Current DORA terminology is used in this case rather than assuming the old four-key set is complete.
1. Calculate the supplied change fail rate and deployment rework rate.
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Change fail rate is 12/200 =6%. Deployment rework rate is 8/200 =4% under the supplied definitions. One counts deployments requiring remediation; the other counts unplanned incident-driven deployments, so the measures should not be assumed identical.
2. Explain a useful comparison and an inappropriate inference.
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Use the service’s own comparable trend and investigate causes with customer and reliability context. Do not infer individual productivity or blame from deployment count, or rank fundamentally different services without understanding their constraints and definitions.