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DevOps

Change Failure Rate

DORA stability metric

IntermediateConcept10.8K learners

Change failure rate is a DORA metric measuring the percentage of deployments to production that result in a degraded service, requiring a hotfix, rollback, or remediation.

Definition

Change failure rate is a DORA metric measuring the percentage of deployments to production that result in a degraded service, requiring a hotfix, rollback, or remediation.

Overview

Change failure rate answers the question: of everything a team ships, how much of it breaks something? It is expressed as a percentage — deployments causing an incident divided by total deployments — and is one of the four DORA metrics used to characterize both delivery speed and software stability together. What counts as a "failure" varies by organization, but common definitions include any deployment that triggers a rollback, a hotfix, a page to on-call, or a documented incident. The metric is deliberately paired with deployment frequency and lead time for changes because those speed metrics can be gamed by shipping carelessly; change failure rate acts as a check, showing whether high velocity is coming at the cost of stability. DORA's research consistently finds that elite performers do not trade stability for speed — they achieve both a high deployment frequency and a low change failure rate (commonly cited in the 0-15% range for elite teams), because practices like automated testing, small batch sizes, and progressive delivery reduce risk on every axis simultaneously. Low performers, by contrast, often show both slow delivery and high failure rates, since infrequent, large releases are inherently harder to reason about and test thoroughly. Teams typically calculate change failure rate from data in their incident management and deployment tools, tagging incidents to the deployments that caused them. Because the definition of "failure" is somewhat subjective, the trend over time within an organization is usually more valuable than comparing raw percentages across companies with different incident-tagging conventions.

Key Concepts

  • Percentage of deployments causing a production incident or requiring rollback
  • One of the four core DORA metrics
  • Acts as a stability check against speed-only metrics
  • Elite teams combine high deployment frequency with low failure rates
  • Calculated from incident management and deployment tool data
  • Definition of 'failure' varies and should be standardized per organization
  • Most useful tracked as an internal trend over time

Use Cases

Evaluating whether faster releases are introducing more instability
Justifying investment in automated testing and progressive delivery
Setting quality gates for release approval processes
Comparing stability trends before and after a process change
Feeding into postmortem and root-cause analysis programs

Frequently Asked Questions

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