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/nw-cicd-and-deployment

CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.

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$ npx -y skills add nWave-ai/nWave --skill nw-cicd-and-deployment --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/nw-cicd-and-deployment

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The summary Claude sees to decide when to auto-load this skill.

CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.

SKILL.md

nw-cicd-and-deployment.SKILL.md
name: nw-cicd-and-deployment
description: CI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.
user-invocable: false
disable-model-invocation: true

CI/CD Pipeline Design and Deployment Strategies

Local Quality Gates

Catch issues at the developer's machine before they reach CI. Local gates mirror the remote commit stage for fast feedback (seconds vs minutes).

Gate Taxonomy

| Gate | Trigger | Checks | Tools | |------|---------|--------|-------| | Pre-commit | `git commit` | Formatting, linting, unit tests, secrets scan | pre-commit, husky, lefthook | | Pre-push | `git push` | Integration tests, acceptance tests, coverage threshold | pre-commit (push stage), git hooks | | Local CI | Manual | Full pipeline locally | act (GitHub Actions), gitlab-runner exec |

Design Principles

  • **Mirror, not duplicate**: local gates run the same checks as the remote commit stage, not additional ones. Keeps developer experience consistent with CI.
  • **Fast by default**: pre-commit gates target < 30 seconds. Move slow checks (integration, acceptance) to pre-push.
  • **Escapable with audit trail**: allow `--no-verify` for emergencies but log skips. CI remains the authoritative gate.
  • **Framework selection**: prefer `pre-commit` (Python ecosystem) or `lefthook` (polyglot, fast parallel execution) over raw git hooks. Husky for JS/TS-heavy projects.

Hook Stage Assignment

pre-commit (< 30s):     formatting | linting | unit tests (fast subset) | secrets scan
pre-push   (< 5 min):   full unit suite | integration tests | coverage check | type checking

Pipeline Stages

Commit Stage (target: < 10 minutes)

Compile/build | Run unit tests (fast, isolated) | Static code analysis (linting, formatting) | Security scanning (SAST, secrets detection) | Generate build artifacts. Quality gates: build success | 100% unit test pass rate | coverage threshold (e.g., > 80%) | no critical vulnerabilities | no secrets in code.

Acceptance Stage (target: < 30 minutes)

Deploy to test environment | Run acceptance/integration/contract tests | Security scanning (DAST). Quality gates: 100% acceptance/integration pass rate | no high/critical security findings | API contracts validated.

Capacity Stage (target: < 60 minutes, can run parallel)

Performance, load, and stress testing | Chaos engineering experiments. Quality gates: performance within SLO thresholds | load test pass (expected traffic + margin) | resilience under failure.

Production Stage

Progressive deployment (canary/blue-green) | Health checks and smoke tests | SLO monitoring during rollout | Automatic rollback on degradation. Quality gates: health checks pass | SLOs maintained | no error rate increase | latency within bounds.

Quality Gate Classification

Every quality gate has a category (where it runs), a type (what happens on failure), and a scope (what it protects).

Gate Taxonomy

| Category | Stage | Type | Examples | |----------|-------|------|----------| | Local | Pre-commit, pre-push | Blocking (developer) | Format, lint, unit tests, secrets scan | | PR | Pull request | Blocking (merge) | Status checks, review approvals, coverage diff | | CI | Commit stage | Blocking (pipeline) | Build, unit tests, SAST, coverage threshold | | CI | Acceptance stage | Blocking (pipeline) | Integration, acceptance, contract tests, DAST | | Deploy | Environment promotion | Blocking (approval) | Manual approval, change advisory board | | Deploy | Canary/progressive | Automatic (rollback) | Error rate, latency, SLO breach | | Production | Post-deploy | Advisory (monitoring) | Smoke tests, SLO monitoring window, business metrics |

Gate Types

  • **Blocking**: pipeline halts on failure. Merge/deploy/promotion is prevented until resolved.
  • **Automatic (rollback)**: no human intervention -- system rolls back on threshold breach. Requires pre-defined thresholds and rollback automation.
  • **Advisory**: failure is reported but does not block. Used for post-deploy monitoring where rollback is a separate decision.

Design Checklist

When designing quality gates for a pipeline, verify: 1. Every remote CI gate has a local equivalent (pre-commit or pre-push) 2. PR gates include both automated checks (status checks) and human review (approvals) 3. Deployment gates distinguish blocking (promotion) from automatic (canary rollback) 4. Post-deploy gates have clear escalation paths (advisory -> manual rollback decision) 5. Gate thresholds are documented and versioned (not hardcoded in pipeline YAML)

GitHub Actions Patterns

Workflow Structure

Triggers: push to main/develop | pull_request | release tags | manual workflow_dispatch. Jobs flow: build -> security -> deploy_staging -> deploy_production. Each with appropriate `needs` dependencies and environment gates.

Quality Gate Pattern

- name: Quality Gate
  run: |
    COVERAGE=$(jq '.totals.percent_covered' coverage.json)
    if (( $(echo "$COVERAGE < 80" | bc -l) )); then
      echo "Coverage $COVERAGE% is below 80% threshold"
      exit 1
    fi

Caching Pattern

- uses: actions/cache@v4
  with:
    path: ~/.cache/pip
    key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
    restore-keys: |
      ${{ runner.os }}-pip-

Matrix Testing Pattern

strategy:
  matrix:
    python-version: ['3.10', '3.11', '3.12']
    os: [ubuntu-latest, macos-latest]

Deployment Strategies

Rolling Deployment

Gradual replacement of instances. Kubernetes config: `type: RollingUpdate`, `maxSurge: 25%`, `maxUnavailable: 0`.

  • Pros: zero downtime | simple | efficient resources
  • Cons: slow rollback | mixed versions during deployment
  • Use when: stateless services | no breaking API changes | low-risk changes

Blue-Green Deployment

Two identical environments, instant switch: Blue (current) serves traffic -> Deploy new t

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AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).

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