Mean Time to Failure (MTTF): Formula, Examples & DevOps Use
Blog post from Harness
Mean Time to Failure (MTTF) is a crucial metric in assessing the reliability of non-repairable components, such as Kubernetes pods and CI/CD runners, by measuring the average operational time before failure. It is distinguished from Mean Time to Repair (MTTR) and Mean Time Between Failures (MTBF), which focus on repairable systems and uptime between failures, respectively. MTTF serves as a decision-making tool rather than a mere dashboard statistic, aiding platform teams in planning capacity, setting realistic Service Level Objectives (SLOs), and reducing developer workload by identifying and prioritizing components that frequently fail. The text underscores the importance of using MTTF to forecast incidents, prioritize components based on operational cost, and enhance business outcomes by integrating it with SLOs, error budgets, and AI-powered automation to improve reliability and reduce toil. Practical ways to improve MTTF include stabilizing CI pipelines, employing progressive delivery and rollback strategies, enforcing pipeline governance, and validating resilience through chaos engineering.