Git Repository Analytics
๐ Git Analytics Dashboard
Transform your git data into actionable insights for better team performance
Data-Driven Decisions
Make informed decisions about team capacity, workload distribution, and process improvements based on real commit data.
Team Health Monitoring
Track work-life balance, identify burnout risks, and ensure sustainable development practices across your team.
Delivery Optimization
Measure lead times, track feature vs bug ratios, and optimize your development workflow for faster delivery.
๐ฏ Why Use Git Analytics?
Identify Bottlenecks
Spot code review delays, long lead times, and uneven workload distribution before they impact delivery.
Improve Code Quality
Track test coverage, ensure proper peer reviews, and maintain quality standards across all features.
Support Your Team
Monitor after-hours work, balance review loads, and create a healthier development environment.
Plan Better Sprints
Use historical data to estimate capacity, plan realistic timelines, and set achievable goals.
Weekly Reviews
Monitor team health and after-hours work patterns
Monthly Analysis
Track delivery trends and adjust sprint planning
Quarterly Planning
Assess productivity and plan process improvements
Ready to Get Started?
Set up your dashboard in under 5 minutes and start gaining insights immediately.
๐ Monthly Activity
๐ฅ Total Lines by Developer
๐ What This Analysis Shows
- Monthly Activity: Tracks code contribution patterns and identifies peak productivity periods
- Developer Rankings: Shows relative productivity based on lines of code contributed (excluding merge commits)
- Workload Distribution: Reveals how development work is distributed across team members
- Productivity Trends: Identifies seasonal patterns, project phases, and individual performance cycles
- Team Capacity: Helps estimate team velocity and plan future sprint commitments
๐ก Recommendations
๐ Monthly Business Hours vs Non-Business Hours
๐ฅ Total Business Hours vs Non-Business Hours by Developer
๐ What This Analysis Shows
- Work-Life Balance: Tracks when developers are working outside standard business hours (8AM-5PM, Mon-Fri)
- Burnout Risk: High after-hours percentages may indicate excessive workload or poor time management
- Time Zone Patterns: Helps identify remote team members working in different time zones
- Project Urgency: Spikes in weekend/evening work often correlate with project deadlines
- Team Health: Sustainable development practices require balanced working hours
๐ก Recommendations
๐ Non-Business Hours Commits Reference
๐ Monthly Approvals
๐ Approvals Distribution
๐ What This Analysis Shows
- Code Review Distribution: Shows how review workload is distributed across team members
- Approval Patterns: Identifies who is reviewing what types of changes (features vs bugs)
- Review Process Health: Ensures no single person becomes a bottleneck in the review process
- Knowledge Sharing: Multiple reviewers indicate better knowledge distribution
- Quality Assurance: Consistent review patterns help maintain code quality standards
๐ก Recommendations
๐ซ Ticket Reference
๐ Monthly Features & Bug Fixes
๐ Features vs Bug Fixes Distribution
๐ What This Analysis Shows
- Feature vs Bug Ratio: Tracks the balance between new feature development and bug fixing work
- Development Focus: Shows whether the team is primarily building new functionality or maintaining existing code
- Quality Trends: High bug fix ratios may indicate technical debt or quality issues
- Developer Specialization: Identifies who focuses on features vs bug fixes and maintenance
- Sprint Planning: Helps estimate capacity allocation between new features and bug fixes
- Product Health: Balanced ratios suggest healthy development practices
๐ก Recommendations
๐ซ Feature & Bug Fix Reference
๐ Monthly Test Coverage
๐ Test Coverage Distribution
๐ What This Analysis Shows
- Test Coverage Gaps: Identifies tickets and commits that lack proper test coverage
- Quality Assurance Patterns: Shows which developers consistently include tests with their changes
- Risk Assessment: Highlights areas of the codebase that may be vulnerable due to insufficient testing
- Testing Culture: Reveals team commitment to test-driven development practices
- Technical Debt: Untested code represents potential future maintenance burden
- Release Confidence: Higher test coverage correlates with safer deployments
๐ก Recommendations
๐จ Tickets Without Tests
๐ Monthly Lead Time
๐ฅ Lead Time by Developer
โฑ๏ธ Lead Time Breakdown (Dev vs Review Days)
๐ Struggling Tickets Analysis
๐ What This Analysis Shows
- Development Velocity: Measures time from first commit to final merge, indicating team delivery speed
- Multiple Merge Detection: Identifies tickets requiring multiple merges, indicating potential quality issues or incomplete work
- Process Efficiency: Identifies bottlenecks in development workflow and review processes
- Rework Analysis: Tracks additional development time after initial merge attempts
- Quality vs Speed: Balances delivery velocity with code review thoroughness and rework patterns
- Predictability: Helps forecast delivery dates considering potential rework cycles
๐ก Recommendations
โฑ๏ธ Lead Time Details
๐ How to Read the Numbers
๐ง Knowledge Risk Analysis
Identify knowledge silos and bus factor risks in your codebase
๐ Analyze Module/Directory
๐ What This Analysis Shows
- Bus Factor: Number of people who need to leave before knowledge is lost
- Code Ownership: Who has made the most changes to this module
- Risk Level: HIGH if one person owns >70%, MEDIUM if >50%, LOW otherwise
- Knowledge Distribution: How evenly knowledge is spread across the team
๐ Developer Rankings
Top 10 developers across all repositories
โ๏ธ Dashboard Settings
Manage repositories and configure your analytics dashboard
Repository Management
Add, remove, and manage your git repositories. Generate analytics data for each repository.
Configuration Editor
Edit JIRA URLs, business hours, ticket patterns, and other dashboard configuration settings.
๐ Configured Repositories
โก Quick Actions
๐ Multi-Repository Analytics Setup
Dockerized dashboard for analyzing multiple git repositories
Start Dashboard
Run the Docker setup:
Opens at http://localhost:3000
Add Repositories
Click "โ๏ธ Manage Repos" and add your repositories:
- Enter full path (e.g., /Users/john/projects/my-repo)
- Give it a display name
- Click "Add Repository"
Generate Analytics
Generate data for each repository:
- Click "Generate Data" for each repo
- Or use "๐ Generate All Data"
- Select repository from dropdown to view
Add repositories via "Manage Repos", generate data, then select from dropdown to view analytics.
โ๏ธ Configuration Guide
๐ Organization Settings
๐ Business Hours
- START_HOUR: 8 (8 AM)
- END_HOUR: 17 (5 PM)
- DAYS: Monday(1) - Friday(5)
๐ฟ Branch Prefixes
- FEATURE: 'feature/'
- BUGFIX: 'bugfix/'
- HOTFIX: 'hotfix/'
๐ Analytics Reference
๐ฅ Contributors
Purpose: Track productivity patterns and workload distribution
Metrics: Lines of code, commits per month, developer rankings
Note: Excludes merge commits to avoid inflated statistics
๐ Working Hours
Purpose: Monitor work-life balance and identify burnout risks
Metrics: Business hours vs after-hours work patterns
Alert: High after-hours % may indicate workload issues
๐ Peer Review
Purpose: Ensure quality through proper review distribution
Source: "Approved-by" field from merge commits
Use: Review process optimization, knowledge sharing
๐ Features & Bugs
Purpose: Track business value delivery vs quality issues
Classification: Based on branch prefixes (feature/, bugfix/)
Use: Sprint planning, stakeholder reporting
๐งช Test Coverage
Purpose: Identify testing gaps and quality practices
Detection: Commit messages with test file references
Use: Quality assurance, technical debt tracking
โฑ๏ธ Lead Time
Purpose: Measure development velocity and bottlenecks
Formula: PR merge time โ first commit time
Use: Process optimization, delivery forecasting
๐ง Troubleshooting Guide
โ Common Issues
- "No repositories configured": Click "โ๏ธ Manage Repos" to add repositories
- "No data file found": Click "Generate Data" for the repository
- "Repository path does not exist": Verify the full absolute path
- No pull requests: Need "Approved-by:" in merge commits
๐ Data Requirements
- Peer Review: "Approved-by: Name" in merge commits
- Features/Bugs: Branch prefixes (feature/, bugfix/)
- Test Coverage: Test file mentions in commits
- Lead Time: Regular + merge commits with PR #
๐ Updating Data
To refresh with latest commits:
- Click "Generate Data" button for specific repository
- Or use "๐ Generate All Data" to update all repositories
- Data is automatically processed and stored
๐ง Technical Architecture
๐ณ Docker Infrastructure
- Containerized Node.js backend
- Automated git data processing
- Volume mounting for repository access
๐ Multi-Repository Support
- Centralized repository management
- Individual data file generation
- RESTful API for data operations
๐จ Frontend Features
- Interactive Chart.js visualizations
- Responsive design for all devices
- Real-time configuration editing
๐ฏ Best Practices & Guidelines
๐ Regular Usage
- Weekly: Monitor team health & after-hours work
- Monthly: Analyze delivery trends & adjust planning
- Quarterly: Assess productivity & process improvements
๐ฌ Data Interpretation
- Use metrics to start conversations, not make judgments
- Consider project phases & individual circumstances
- Focus on trends and patterns over absolute numbers
๐ Data Quality
- Maintain consistent commit message formats
- Use standardized branch naming conventions
- Regenerate repository data regularly for accuracy