DoraPulse Composite Action

Reusable GitHub Composite Action to calculate DORA metrics and upload CSV artifacts.

Understanding DORA Metrics

DoraPulse calculates the four key metrics defined by the DORA (DevOps Research and Assessment) team.

Deployment Frequency

• How often an organization successfully releases to production
• Elite performers: Multiple deployments per day
• Metric shows: Release cadence and batch size

Lead Time for Changes

• Time taken from code commit to code running in production
• Elite performers: Less than one hour
• Metric shows: Process efficiency and deployment pipeline health

Mean Time to Recovery (MTTR)

• How long it takes to restore service after an incident
• Elite performers: Less than one hour
• Metric shows: Incident response effectiveness

Change Failure Rate

• Percentage of changes that lead to degraded service
• Elite performers: 0-15%
• Metric shows: Quality of testing and review processes

References

• Official DORA Research Program
• Google Cloud's DORA Metrics
• DORA's State of DevOps Reports
• DORA Metrics in GitHub
• Accelerate: The Science of Lean Software - The book that introduced DORA metrics

Outputs

• dora_metrics.csv: per-repository metrics
• dora_metrics_summary.csv: aggregate summary

Inputs

• token (required): GitHub token with read access to target repositories
• owner (optional): repository owner for single repository mode, or optional owner/org filter in topic mode
• repo (optional): repository name for single repository mode
• topic (optional): GitHub topic for discovery mode
• days (optional, default 30)
• artifact_name (optional, default dora-metrics-csv)

Provide either:

• owner + repo (single repository mode), or
• topic (topic mode, optional owner filter)

DORA Calculation Logic

Metrics are calculated from closed pull requests with merged_at inside the selected rolling window (days).

• Deployment Frequency: merged_prs_in_window / days
• Lead Time for Changes (hours): Average of (merged_at - created_at) for merged PRs in window
• MTTR (hours): Average of (merged_at - created_at) only for merged PRs whose title/body contains recovery keywords: fix, hotfix, revert, rollback
• Change Failure Rate (%): (failed_prs / merged_prs_in_window) * 100 A PR is treated as failed if title/body contains any failure keyword: fix, hotfix, revert, rollback, emergency

CSV files:

• dora_metrics.csv: One row per repository with columns: repository, period_days, merged_prs, failed_prs, deployment_frequency_per_day, lead_time_hours, mttr_hours, change_failure_rate_pct
• dora_metrics_summary.csv: Columns: repositories_analyzed, period_days, total_merged_prs, total_failed_prs, avg_deployment_frequency_per_day, avg_lead_time_hours, avg_mttr_hours Weighted failure rate formula: weighted_change_failure_rate_pct = (total_failed_prs / total_merged_prs) * 100

Notes:

• Unmerged PRs are ignored for all four metrics.
• If no merged PRs are found in window, rate/time metrics are emitted as 0.0.

Usage (Single Repo)

name: DORA Metrics

on:
  workflow_dispatch:

jobs:
  dora:
    runs-on: ubuntu-latest
    steps:
      - name: Run DoraPulse
        uses: chandanrattan/DoraPulse@v1
        with:
          token: ${{ secrets.TOKEN }}
          owner: my-org
          repo: my-service
          days: 30
          artifact_name: my-service-dora

Usage (Topic Mode)

name: DORA Topic Metrics

on:
  workflow_dispatch:

jobs:
  dora-topic:
    runs-on: ubuntu-latest
    steps:
      - name: Run DoraPulse
        uses: chandanrattan/DoraPulse@v1
        with:
          token: ${{ secrets.TOKEN }}
          topic: microservice
          owner: my-org
          days: 30

Local Script

The action uses scripts/dora_metrics_csv.py.

Run Locally

1. Install dependencies:

pip install .

2. Copy env template and set values:

cp .env.example .env

3. Edit .env and choose one mode:

• Single repository mode: set TOKEN, DORA_OWNER, DORA_REPO and keep DORA_TOPIC empty
• Topic mode: set TOKEN, DORA_TOPIC and optionally DORA_OWNER as filter; keep DORA_REPO empty

4. Run:

python scripts/dora_metrics_csv.py

Optional examples:

# Estimate only (no CSV generation)
python scripts/dora_metrics_csv.py --estimate-only

# CLI override example
python scripts/dora_metrics_csv.py --owner my-org --repo my-service --token <token>

Install with dev tooling:

pip install ".[dev]"

For local execution:

python scripts/dora_metrics_csv.py

Use .env / .env.example variables:

• TOKEN
• DORA_OWNER + DORA_REPO, or DORA_TOPIC
• DORA_DAYS
• DORA_OUT_DIR