GitHub Metric
Engineering
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.
Full guide: definition, formula, and benchmarksGitHubEngineeringDeployment Frequency
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.
How to calculate deployment frequency
Why deployment frequency matters for GitHub users
Higher deployment frequency enables faster feedback from users, smaller blast radius per release, and quicker time-to-value for new features. It is strongly correlated with organisational performance in software delivery.
For GitHub-based teams, deployment frequency reflects the effectiveness of your CI/CD pipeline, branching strategy, and release process. Tracking it over time reveals whether infrastructure investments are translating into faster delivery.
Understand and act on deployment frequency with KPI Tree
Sync deployment events from GitHub Actions or release tags into your warehouse and model deployment frequency in KPI Tree. Position it as a top-level DORA metric in your engineering tree alongside lead time, change failure rate, and MTTR.
Assign RACI ownership to the platform team and configure alerts when frequency drops below your target cadence.
Get started with your GitHub data
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Connect your existing warehouse where GitHub data already lands.
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Related GitHub metrics
Lead Time for Changes
EngineeringMetric Definition
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.
Release Velocity
EngineeringMetric Definition
Release Velocity = Number of Releases / Time Period
Release Velocity measures the frequency and speed at which new versions are tagged and published via GitHub Releases or deployment workflows. It encompasses the cadence of releases, the volume of changes per release, and the time between successive releases. Healthy velocity balances speed with stability.
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.
Commit Frequency
EngineeringMetric Definition
Commit Frequency = Total Commits / Time Period
Commit Frequency measures the number of commits pushed to a repository or across an organisation within a given time period. It serves as a high-level activity indicator and a proxy for continuous integration discipline. Consistently low frequency may indicate large, risky batch commits.
Explore deployment frequency across integrations
All GitHub metrics
Branch Lifecycle AnalysisBug Fix RateCode Churn RateCode Coverage TrendCode Quality Trend AnalysisCode Review Quality ScoreCode Review VelocityCommit FrequencyDeveloper Contribution PatternsDeveloper Productivity ScoreDevOps Pipeline EfficiencyDiscussion Engagement RateFeature Development Cycle TimeIssue Resolution TimeLead Time for ChangesOpen 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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