> ## Documentation Index > Fetch the complete documentation index at: https://docs.devhelm.io/llms.txt > Use this file to discover all available pages before exploring further. # DORA Metrics > How DORA metrics measure software delivery performance and operational reliability The four DORA metrics — deployment frequency, lead time for changes, change failure rate, and time to restore service — measure engineering team performance across both velocity and stability. ## The four metrics ### 1. Deployment frequency How often your team deploys to production. | Performance | Frequency | | - | - | | Elite | On-demand (multiple times per day) | | High | Weekly to monthly | | Medium | Monthly to every six months | | Low | Less than once every six months | ### 2. Lead time for changes Time from code commit to running in production. | Performance | Lead time | | - | - | | Elite | Less than one day | | High | One day to one week | | Medium | One week to one month | | Low | More than six months | ### 3. Change failure rate Percentage of deployments that cause a failure requiring remediation (rollback, hotfix, or patch). | Performance | Failure rate | | - | - | | Elite | 0–15% | | High | 16–30% | | Medium | 16–30% | | Low | 46–60% | ### 4. Time to restore service (MTTR) How long it takes to recover from a failure in production. | Performance | Recovery time | | - | - | | Elite | Less than one hour | | High | Less than one day | | Medium | One day to one week | | Low | More than six months | ## Why DORA matters DORA research (now part of Google Cloud) demonstrated that these four metrics predict both software delivery performance and organizational performance. Teams that excel on all four metrics: * Deploy more frequently with fewer failures * Recover faster when things break * Have higher employee satisfaction * Deliver more business value The key insight: **velocity and stability are not tradeoffs**. Elite teams are both fast and reliable. ## How monitoring helps Uptime monitoring directly impacts two DORA metrics: ### Change failure rate Monitoring immediately tells you whether a deployment caused a failure. Without monitoring, failed deployments can go undetected for hours, distorting your metrics. ### Time to restore service Faster detection (MTTD) means faster restoration (MTTR). Automated monitoring with clear alerting is the foundation of rapid recovery. ## Improving DORA metrics | Metric | Improvement strategy | | - | - | | Deployment frequency | Smaller PRs, CI/CD automation, feature flags | | Lead time | Automated testing, trunk-based development, fast CI | | Change failure rate | Better testing, canary deploys, monitoring-gated rollouts | | Time to restore | Automated rollback, playbooks, alerting with context | ## Monitoring as Code and DORA Monitoring as Code specifically improves DORA metrics by: * **Deployment frequency** — monitoring config deploys alongside code changes * **Lead time** — automated validation catches issues in CI, not production * **Change failure rate** — monitoring changes are reviewed in PRs like code * **MTTR** — consistent monitoring setup across environments speeds diagnosis The incident metrics that feed into DORA's MTTR. Automate monitoring deploys to improve all four metrics. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.