# Epic 20: CI/CD Quality Pipeline

**Goal**: Implement comprehensive CI/CD pipeline with automated testing, security scanning, performance benchmarks, and semantic release process.

**Value**: Ensures every release is high quality, catches issues before production, automates release process, and maintains project health over time.

**Priority**: High (Project sustainability)

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## Story 20.1: GitHub Actions Workflow Orchestration

As a maintainer,
I want automated CI/CD workflows for every commit and release,
So that quality gates are enforced consistently and releases are reliable.

**Acceptance Criteria:**

**Given** GitHub repository with Actions enabled
**When** code is pushed or PR opened
**Then** CI workflow runs: lint checks (ruff, mypy), unit tests (pytest), integration tests (pytest with Docker), coverage report (pytest-cov), security scan (bandit)

**And** workflows triggered by: push to main, PR to main, tag push (v*), scheduled (nightly)

**And** workflow stages: setup (checkout, Python setup, dependency install), test (parallel test jobs), build (package build), deploy (PyPI publish on tag)

**And** parallel execution: unit tests, integration tests, security scans run in parallel (faster CI)

**And** caching: pip cache, Docker layers cached for speed

**And** workflow status: badges in README show build status, test coverage

**And** workflow artifacts: test reports, coverage reports, built packages uploaded

**And** workflow notifications: Slack/Discord notifications on failure, success on main

**Prerequisites:** Epic 6 complete (testing), Story 8.10 (release process)

**Technical Notes:**
- GitHub Actions workflows: .github/workflows/ci.yml, release.yml, nightly.yml
- Parallel jobs: strategy.matrix for multiple Python versions (3.12, 3.13)
- Caching: actions/cache for pip, actions/setup-python with cache: pip
- Docker: use service containers for RabbitMQ in integration tests
- Artifacts: actions/upload-artifact for reports, actions/download-artifact for consumption
- Notifications: use GitHub Actions Slack/Discord integration or webhooks
- Quality gates: require CI pass before merge (branch protection rules)

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## Story 20.2: Semantic Release Automation

As a maintainer,
I want automated semantic versioning and release generation,
So that releases are consistent and changelogs are accurate.

**Acceptance Criteria:**

**Given** commits following conventional commits format
**When** release workflow runs
**Then** version is automatically determined: MAJOR (breaking: feat!), MINOR (new feat), PATCH (fix)

**And** changelog is auto-generated from commit messages: grouped by type (Features, Fixes, Breaking Changes)

**And** Git tag is created: v{version} with changelog as tag message

**And** GitHub Release is created: release notes from changelog, built packages attached

**And** PyPI publish: package uploaded automatically on release

**And** conventional commit enforcement: PR checks verify commit format (feat:, fix:, docs:, etc.)

**And** release workflow triggered: on push to main (if releasable commits), manually (workflow_dispatch)

**And** pre-release support: alpha/beta tags (v1.0.0-alpha.1)

**Prerequisites:** Story 8.6 (changelog), Story 8.10 (release process)

**Technical Notes:**
- Use python-semantic-release or semantic-release (JS): analyzes commits, determines version
- Conventional commits: feat: (minor), fix: (patch), feat!: or BREAKING CHANGE: (major)
- Commit linting: use commitlint in pre-commit hooks or GitHub Actions
- Changelog generation: semantic-release auto-generates from commit history
- PyPI publish: use trusted publisher (OIDC) for secure PyPI authentication (no API tokens)
- Workflow: .github/workflows/release.yml triggered on main push
- Pre-release: use --prerelease flag for alpha/beta versions

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## Story 20.3: Quality Dashboard & Metrics Tracking

As a project maintainer,
I want a dashboard showing project health metrics over time,
So that I can identify trends, regressions, and areas needing improvement.

**Acceptance Criteria:**

**Given** quality metrics collected from CI/CD
**When** I view dashboard
**Then** dashboard shows: test coverage (trend over time), build success rate, test execution time, security vulnerabilities (count, severity), performance benchmarks (latency percentiles over versions), code quality scores (maintainability index)

**And** dashboard is: web-based (SonarCloud, Codecov, custom), updated automatically (on every CI run), publicly accessible (README badge links)

**And** alerts configured: coverage drops below 80%, build failures exceed 10%, critical vulnerabilities detected

**And** historical data retained: 1 year of metrics for trend analysis

**And** comparison view: compare current vs previous release, identify regressions

**And** dashboard integrations: GitHub commit status checks, PR comments with quality report

**And** dashboard URL linked from README with badge

**Prerequisites:** Story 6.7 (coverage reporting), Story 15.3 (security testing)

**Technical Notes:**
- Use SonarCloud: code quality, coverage, security issues (free for open source)
- Codecov: test coverage tracking with graphs, trends, PR comments
- Custom dashboard: Grafana + InfluxDB for metrics (CI pushes metrics to InfluxDB)
- Metrics collection: CI extracts metrics from test reports, pushes to dashboard
- Badges: ![Coverage](https://codecov.io/.../badge.svg), ![Quality](https://sonarcloud.io/.../badge.svg)
- Alerts: Codecov/SonarCloud have built-in alerting, configure thresholds
- Historical data: SonarCloud/Codecov retain automatically, custom needs database

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