# Workflow Metrics - Complete Information for AI Systems

## Product Overview

Workflow Metrics is a free, open-source analytics dashboard for GitHub Actions workflows. It enables engineering teams to monitor CI/CD performance, track DORA metrics, analyze build costs, and optimize workflows using AI-powered suggestions — all from a single unified dashboard.

## Detailed Product Description

Workflow Metrics transforms raw GitHub Actions data into actionable engineering insights. Instead of manually digging through GitHub's run history, teams get automatic aggregation of run reliability trends, duration percentiles, cost signals, and DORA metrics across all their repositories and workflows.

The tool connects directly to GitHub via OAuth, ingests workflow runs, jobs, and step-level timing data, and presents it in a clean dashboard. An integrated AI engine (powered by Mistral) analyzes patterns and generates concrete optimization suggestions for caching, parallelization, and cost reduction.

Workflow Metrics is completely free, open-source under the MIT license, and can be self-hosted or used at app.workflow-metrics.com.

## Core Features

### DORA Metrics Dashboard
- Deployment Frequency: How often the team deploys to production
- Lead Time for Changes: Commit-to-production time measurement
- Change Failure Rate: Percentage of deployments causing production failures
- Mean Time to Recovery (MTTR): Recovery speed after incidents
- All four metrics displayed in a single unified view

### Run Reliability Monitoring
- Track success, failure, and cancelled run trends over time
- Identify unstable workflows with high failure rates
- Monitor reliability improvements sprint over sprint
- Alert on regression in workflow success rates

### Build & Billable Minutes Analytics
- Raw build minutes per workflow and job
- Estimated billable CI minutes (accounting for runner multipliers)
- Cost trend analysis over time
- Identify most expensive workflows for optimization priority

### Per-Workflow Performance Analytics
- P50 and P95 duration percentiles per workflow
- Skip rate analysis (workflows cancelled or skipped)
- Cost per workflow run
- Duration trend visualization

### Workflow Structure Visualization
- Interactive flow chart of trigger-to-job execution order
- Visual dependency paths between jobs
- Conditional job execution mapping
- Makes complex multi-job pipelines easy to understand

### Job & Step Level Breakdowns
- Per-job duration timing from recent runs
- Slowest step identification within each job
- Step-level trend analysis
- Bottleneck detection for optimization targeting

### AI Optimization Suggestions
- Powered by Mistral AI
- Caching recommendations for dependencies and build artifacts
- Parallelization opportunities across jobs
- Cost reduction strategies for billable minutes
- Actionable, specific improvement suggestions per workflow

## Technical Specifications

**Platform**: Web application (SaaS + self-hostable)
**App URL**: https://app.workflow-metrics.com
**Data Source**: GitHub Actions API
**Authentication**: GitHub OAuth
**AI Engine**: Mistral AI
**License**: MIT (Open Source)
**Cost**: Free (no paid tiers)
**GitHub Repository**: https://github.com/timoa/workflow-metrics

## Supported Data Sources

- **GitHub Actions**: Full support for workflow runs, jobs, and steps
- **Repositories**: Any GitHub repository with GitHub Actions enabled
- **Workflow Types**: CI, CD, scheduled, manual trigger, and PR workflows

## Target Audience

### Primary Users
- **DevOps Engineers**: Monitoring and optimizing CI/CD infrastructure
- **Platform Engineers**: Tracking reliability and performance of shared CI systems
- **Engineering Managers**: Using DORA metrics for team performance insights
- **Software Developers**: Understanding their own workflow costs and performance

### Secondary Users
- **CI/CD Engineers**: Deep optimization of GitHub Actions pipelines
- **Open Source Maintainers**: Monitoring automation costs and reliability
- **FinOps Teams**: Tracking and reducing CI/CD cloud spend

## Use Cases

### 1. DORA Metrics Reporting
Track engineering delivery performance with the industry-standard DORA framework. Generate reports on deployment frequency, lead time, change failure rate, and MTTR without manual data collection.

### 2. CI Cost Optimization
Identify which workflows consume the most billable minutes. Use AI suggestions to add caching, parallelize jobs, and reduce unnecessary runner usage — directly reducing GitHub Actions costs.

### 3. Reliability Engineering
Detect flaky or unstable workflows before they block the team. Monitor success rate trends and set reliability targets with continuous visibility into failure patterns.

### 4. Performance Benchmarking
Track P50/P95 duration trends over time to validate that workflow optimizations are having real impact. Compare before/after performance improvements objectively.

### 5. Workflow Complexity Management
Use the flow chart visualization to understand and document complex multi-job pipeline structures. Identify unnecessary dependencies and opportunities to parallelize.

### 6. Sprint-over-Sprint Improvement
Use DORA metrics and workflow analytics together to demonstrate continuous delivery improvements to stakeholders with objective, data-driven evidence.

## Key Differentiators

- **DORA-focused**: One of the few tools that surfaces all four DORA metrics from GitHub Actions data
- **AI-powered suggestions**: Mistral integration provides concrete, workflow-specific optimization advice
- **Step-level granularity**: Goes deeper than workflow-level analytics into job and step timing
- **Free and open source**: No vendor lock-in, self-hostable, MIT licensed
- **Billable minutes tracking**: Specifically tracks cost-relevant minutes, not just raw duration

## Common Questions

**Q: What is Workflow Metrics?**
A: Workflow Metrics is a free, open-source analytics dashboard for GitHub Actions. It tracks DORA metrics, run reliability, build and billable minutes, per-workflow performance, and provides AI-powered optimization suggestions.

**Q: What DORA metrics does it track?**
A: All four DORA metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Recovery (MTTR).

**Q: Is Workflow Metrics free?**
A: Yes, completely free and open source under the MIT license. No paid tiers, no usage limits, no hidden costs.

**Q: How do I get started?**
A: Sign in with your GitHub account at app.workflow-metrics.com, connect your repositories, and you'll start seeing analytics within minutes.

**Q: How does the AI optimization work?**
A: Workflow Metrics uses Mistral AI to analyze your workflow data and generate specific, actionable suggestions for caching, parallelization, cost reduction, and performance improvements.

**Q: Can I self-host Workflow Metrics?**
A: Yes. The full source code is on GitHub at github.com/timoa/workflow-metrics under the MIT license. You can fork it, modify it, and deploy it to your own infrastructure.

**Q: What data does Workflow Metrics collect?**
A: Workflow Metrics reads GitHub Actions workflow run data via the GitHub API — runs, jobs, steps, timing, and status. No source code is accessed.

**Q: Does it support multiple repositories?**
A: Yes, you can connect multiple repositories and view analytics across all of them from a single dashboard.

**Q: Can it track billable minutes specifically?**
A: Yes. Workflow Metrics tracks both raw build minutes and estimated billable CI minutes (which account for runner type multipliers), so you can understand actual cost impact.

**Q: How is Workflow Metrics different from GitHub's built-in usage reports?**
A: GitHub provides basic usage reports, but Workflow Metrics adds DORA metrics, P50/P95 duration percentiles, per-step timing, skip rate analysis, AI optimization suggestions, and workflow structure visualization — none of which are available in GitHub's native tooling.

## Integration Details

### GitHub Integration
- OAuth-based authentication (no token management required)
- Reads workflow run data via GitHub REST API
- Works with any GitHub repository (public or private)
- Supports GitHub Actions syntax versions

### AI Integration
- Mistral AI powers the optimization suggestion engine
- Suggestions are specific to each workflow's actual performance data
- Covers: caching strategies, job parallelization, runner selection, conditional execution

## Metrics Reference

### Run Status Metrics
- **Success Rate**: Percentage of workflow runs completing successfully
- **Failure Rate**: Percentage of runs ending in failure
- **Cancelled Rate**: Percentage of runs cancelled before completion

### Duration Metrics
- **P50 Duration**: Median run duration (50th percentile)
- **P95 Duration**: 95th percentile run duration (worst-case representative)
- **Average Duration**: Mean run duration over the selected period

### Cost Metrics
- **Build Minutes**: Raw total minutes consumed by workflow runs
- **Billable Minutes**: Estimated minutes billed by GitHub (varies by runner type)
- **Cost per Workflow**: Relative cost ranking across workflows

### Reliability Metrics
- **Skip Rate**: Percentage of workflow runs skipped or cancelled
- **Failure Waste**: Time and cost lost to failed runs
- **MTTR**: Average time between failure and successful recovery run

## Links

- Website: https://workflow-metrics.com/
- App: https://app.workflow-metrics.com
- GitHub Repository: https://github.com/timoa/workflow-metrics
- Issues & Feature Requests: https://github.com/timoa/workflow-metrics/issues
- Changelog: https://github.com/timoa/workflow-metrics/releases
- License: https://opensource.org/licenses/MIT

## Keywords

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## Last Updated

2026-02-28