GitHub Metric
Engineering
Lead Time = Production Deployment Timestamp − Commit Timestamp
Lead Time for Changes measures the elapsed time from when a code change is committed to when it is successfully running in production. It is one of the four DORA metrics and a key indicator of delivery pipeline efficiency. Elite performers achieve lead times measured in hours rather than days or weeks.
Full guide: definition, formula, and benchmarksGitHubEngineeringLead Time for Changes
Lead Time for Changes measures the elapsed time from when a code change is committed to when it is successfully running in production. It is one of the four DORA metrics and a key indicator of delivery pipeline efficiency. Elite performers achieve lead times measured in hours rather than days or weeks.
How to calculate lead time for changes
Why lead time for changes matters for GitHub users
Short lead times mean that value reaches users quickly and that the cost of each change is low, encouraging experimentation and rapid iteration. Long lead times create pressure to batch changes, which increases risk and makes debugging harder.
For GitHub teams, lead time encompasses CI/CD pipeline speed, review wait time, and deployment automation. Reducing it requires investment across the entire delivery chain, and tracking it in a metric tree reveals which stage contributes the most delay.
Understand and act on lead time for changes with KPI Tree
Connect GitHub commit and deployment data via your warehouse and model lead time in KPI Tree. Position it as a DORA metric alongside deployment frequency, change failure rate, and MTTR in your engineering tree.
Assign RACI ownership to the platform team and decompose lead time into sub-metrics (CI time, review time, deploy time) to target specific improvements.
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Related GitHub metrics
Deployment Frequency
EngineeringMetric Definition
Deployment Frequency = Number of Deployments / Time Period
Deployment Frequency measures how often an organisation successfully releases to production. It is one of the four DORA metrics and a key indicator of delivery maturity. Elite teams deploy on demand, multiple times per day, while low performers deploy monthly or less frequently.
Feature Development Cycle Time
EngineeringMetric Definition
Cycle Time = Deployment Timestamp − First Feature Commit Timestamp
Feature Development Cycle Time measures the elapsed time from the first commit on a feature branch to successful deployment to production. It encompasses coding, review, testing, and release phases. Shorter cycle times enable faster user feedback and more responsive product development.
Code Review Velocity
EngineeringMetric Definition
Code Review Velocity = Median(First Review Timestamp − PR Ready Timestamp)
Code Review Velocity measures the elapsed time from when a pull request is opened or marked ready for review to when the first substantive review is submitted. It is a key driver of lead time for changes. Long review waits are one of the most common causes of developer context-switching.
DevOps Pipeline Efficiency
EngineeringMetric Definition
Pipeline Efficiency = Successful Pipeline Runs / Total Pipeline Runs × 100
DevOps Pipeline Efficiency measures the speed, reliability, and resource utilisation of CI/CD pipelines. It encompasses build duration, test execution time, pipeline success rate, and queue wait time. Efficient pipelines accelerate feedback loops and reduce developer idle time.
Explore lead time for changes across integrations
All GitHub metrics
Branch Lifecycle AnalysisBug Fix RateCode Churn RateCode Coverage TrendCode Quality Trend AnalysisCode Review Quality ScoreCode Review VelocityCommit FrequencyDeployment FrequencyDeveloper Contribution PatternsDeveloper Productivity ScoreDevOps Pipeline EfficiencyDiscussion Engagement RateFeature Development Cycle TimeIssue Resolution TimeOpen Source Contribution AnalysisPull Request Approval RatePull Request Bottleneck AnalysisRelease VelocityRepository Health ScoreSecurity Alert Resolution TimeSecurity Vulnerability TrendsSprint Velocity TrackingTeam Collaboration IndexTechnical Debt AccumulationEmpower your team to understand and act on GitHub data
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