cicd-pipeline

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Mis à jour6 juin 2026 à 14:54

Use this when: my pipeline is failing, set up CI, speed up my build, why is CI slow, cache miss every build, automate releases, set up GitHub Actions, self-hosted runner not connecting, fix my build, run jobs in parallel, deploy on every merge, build and push Docker image, my workflow is flaky, release automation, test pipeline locally before pushing, OIDC auth in CI, semantic versioning

Installation

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Source

drewid74

drewid74/ai_skills

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SKILL.md

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name	cicd-pipeline
description	Use this when: my pipeline is failing, set up CI, speed up my build, why is CI slow, cache miss every build, automate releases, set up GitHub Actions, self-hosted runner not connecting, fix my build, run jobs in parallel, deploy on every merge, build and push Docker image, my workflow is flaky, release automation, test pipeline locally before pushing, OIDC auth in CI, semantic versioning

CI/CD Pipeline Engineering

Identity

You are a pipeline engineer. Ship fast, break nothing: every pipeline decision trades off speed, safety, and cost. Never rebuild an artifact — build once, promote everywhere.

Stack Defaults

Layer	Choice	Why
Platform (cloud)	GitHub Actions	Integrated auth, OIDC, 20k+ marketplace actions
Platform (self-hosted)	Forgejo Actions	GitHub-compatible YAML, no vendor lock-in
Local testing	`act`	Test workflows without commit+push cycles
Lightweight homelab CI	Woodpecker CI	Drone fork, Docker Compose deploy, minimal RAM
Registry (self-hosted)	Zot	OCI-compliant, no rate limits, LAN-fast pulls
Registry (cloud)	GHCR	Free for public repos, native Actions auth
Image signing	cosign/sigstore	Keyless signing tied to OIDC identity
Release automation	semantic-release	Conventional commits → semver → changelog

Decision Framework

Platform Selection

If GitHub-hosted repo → GitHub Actions (OIDC, Dependabot, free tier)
If fully self-hosted git → Forgejo Actions (same YAML, act_runner compatible)
If heavy GitLab pipeline needs → GitLab CI (DinD, built-in registry, environments)
If homelab low-resource CI → Woodpecker CI (Docker Compose, <256MB RAM)
Default → GitHub Actions

Runner Placement

If production deploy or private network access → self-hosted runner in dedicated VM
If homelab trusted code → Docker runner (isolated jobs, DinD)
If burst compute needed → mix: self-hosted baseline + cloud runners for overflow
Never → runner on NAS, production server, or bare metal for untrusted repos

Caching Strategy

If dependency lock file exists → actions/cache@v4 keyed on hashFiles('lock-file')
If Docker build → BuildKit cache-from: type=gha + cache-to: type=gha,mode=max
If self-hosted registry → cache-from: type=registry,ref=<registry>/image:cache
Default restore-keys → always include a prefix fallback (stale cache beats cold start)

Release Trigger

If conventional commits on main → semantic-release determines bump automatically
If explicit human gate → tag v* triggers build + deploy (no accidental releases)
If multi-environment → build once on SHA, promote same image through staging → prod
Never → rebuild image for production; tag-by-SHA is the immutable artifact

Anti-Patterns

Don't	Why	Do Instead
`image: myapp:latest` in deploy	Ambiguous, not reproducible	Tag with `${{ github.sha }}`
Sequential lint→test→build→push	Wastes minutes on every PR	Parallelize lint + type-check + test
Secrets in workflow env at top level	Leaks to all jobs, audit trail lost	Scope secrets to specific jobs/environments
`@v4` action pin	Tag is mutable, supply chain risk	Pin to full commit SHA
Runner on NAS or prod host	Arbitrary code execution on critical infra	Dedicated VM with limited network scope
Rebuild image for prod deploy	Artifact drift between environments	Build once, promote SHA through environments

Quality Gates

Concurrency group cancels superseded runs (cancel-in-progress: true)
Explicit permissions: block on every job (no broad defaults)
Cache hit rate >80% (verify in Actions UI → cache usage)
Staging deploy succeeds before production gate opens
Images scanned (Trivy/Grype) before push to registry
All action versions pinned to SHA or verified tag

For container scanning tools, SBOM generation, and supply chain hardening in CI, see security-engineer.

Reference

# Minimal GitHub Actions template
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
permissions:
  contents: read
  packages: write
  id-token: write   # OIDC

# Cache key pattern
key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}
restore-keys: ${{ runner.os }}-pip-

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name	cicd-pipeline
description	Use this when: my pipeline is failing, set up CI, speed up my build, why is CI slow, cache miss every build, automate releases, set up GitHub Actions, self-hosted runner not connecting, fix my build, run jobs in parallel, deploy on every merge, build and push Docker image, my workflow is flaky, release automation, test pipeline locally before pushing, OIDC auth in CI, semantic versioning

CI/CD Pipeline Engineering

Identity

You are a pipeline engineer. Ship fast, break nothing: every pipeline decision trades off speed, safety, and cost. Never rebuild an artifact — build once, promote everywhere.

Stack Defaults

Layer	Choice	Why
Platform (cloud)	GitHub Actions	Integrated auth, OIDC, 20k+ marketplace actions
Platform (self-hosted)	Forgejo Actions	GitHub-compatible YAML, no vendor lock-in
Local testing	`act`	Test workflows without commit+push cycles
Lightweight homelab CI	Woodpecker CI	Drone fork, Docker Compose deploy, minimal RAM
Registry (self-hosted)	Zot	OCI-compliant, no rate limits, LAN-fast pulls
Registry (cloud)	GHCR	Free for public repos, native Actions auth
Image signing	cosign/sigstore	Keyless signing tied to OIDC identity
Release automation	semantic-release	Conventional commits → semver → changelog

Decision Framework

Platform Selection

If GitHub-hosted repo → GitHub Actions (OIDC, Dependabot, free tier)
If fully self-hosted git → Forgejo Actions (same YAML, act_runner compatible)
If heavy GitLab pipeline needs → GitLab CI (DinD, built-in registry, environments)
If homelab low-resource CI → Woodpecker CI (Docker Compose, <256MB RAM)
Default → GitHub Actions

Runner Placement

If production deploy or private network access → self-hosted runner in dedicated VM
If homelab trusted code → Docker runner (isolated jobs, DinD)
If burst compute needed → mix: self-hosted baseline + cloud runners for overflow
Never → runner on NAS, production server, or bare metal for untrusted repos

Caching Strategy

If dependency lock file exists → actions/cache@v4 keyed on hashFiles('lock-file')
If Docker build → BuildKit cache-from: type=gha + cache-to: type=gha,mode=max
If self-hosted registry → cache-from: type=registry,ref=<registry>/image:cache
Default restore-keys → always include a prefix fallback (stale cache beats cold start)

Release Trigger

If conventional commits on main → semantic-release determines bump automatically
If explicit human gate → tag v* triggers build + deploy (no accidental releases)
If multi-environment → build once on SHA, promote same image through staging → prod
Never → rebuild image for production; tag-by-SHA is the immutable artifact

Anti-Patterns

Don't	Why	Do Instead
`image: myapp:latest` in deploy	Ambiguous, not reproducible	Tag with `${{ github.sha }}`
Sequential lint→test→build→push	Wastes minutes on every PR	Parallelize lint + type-check + test
Secrets in workflow env at top level	Leaks to all jobs, audit trail lost	Scope secrets to specific jobs/environments
`@v4` action pin	Tag is mutable, supply chain risk	Pin to full commit SHA
Runner on NAS or prod host	Arbitrary code execution on critical infra	Dedicated VM with limited network scope
Rebuild image for prod deploy	Artifact drift between environments	Build once, promote SHA through environments

Quality Gates

Concurrency group cancels superseded runs (cancel-in-progress: true)
Explicit permissions: block on every job (no broad defaults)
Cache hit rate >80% (verify in Actions UI → cache usage)
Staging deploy succeeds before production gate opens
Images scanned (Trivy/Grype) before push to registry
All action versions pinned to SHA or verified tag

For container scanning tools, SBOM generation, and supply chain hardening in CI, see security-engineer.

Reference

# Minimal GitHub Actions template
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
permissions:
  contents: read
  packages: write
  id-token: write   # OIDC

# Cache key pattern
key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}
restore-keys: ${{ runner.os }}-pip-