Change as Metrics: Measuring System Reliability Through Change Delivery Signals

System changes cause 60-80% of production incidents, making change observability a first-class reliability concern. A proposed metrics framework defines three business-level indicators: Change Lead Time (CLT), Change Success Rate (CSR), and Incident Leakage Rate (ILR), complemented by technical control metrics covering approval rates, progressive rollout adoption, and monitoring windows. The framework adapts and extends DORA metrics for large-scale, multi-platform environments. To collect this data reliably across heterogeneous systems, an event-centric data warehouse architecture is recommended, using a centralized message queue and batch analytics pipelines to normalize and analyze change events platform-agnostically. A risk-based tiering model (L1/L2/L3) aligns metric targets and governance controls with business criticality, allowing high-impact services to enforce stricter safeguards while lower-risk domains retain delivery agility.