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Deployment Pipeline Design

deployment-pipeline-design

Architecture patterns for multi-stage CI/CD pipelines with approval gates and deployment strategies.

SKILL.md

Full skill instructions

Deployment Pipeline Design

Architecture patterns for multi-stage CI/​CD pipelines with approval gates and deployment strategies.

Do not use this skill when

  • The task is unrelated to deployment pipeline design
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/​implementation-playbook.md.

Purpose

Design robust, secure deployment pipelines that balance speed with safety through proper stage organization and approval workflows.

Use this skill when

  • Design CI/​CD architecture
  • Implement deployment gates
  • Configure multi-environment pipelines
  • Establish deployment best practices
  • Implement progressive delivery

Pipeline Stages

Standard Pipeline Flow

┌─────────┐   ┌──────┐   ┌─────────┐   ┌────────┐   ┌──────────┐
│  Build  │ → │ Test │ → │ Staging │ → │ Approve│ → │Production│
└─────────┘   └──────┘   └─────────┘   └────────┘   └──────────┘

Detailed Stage Breakdown

  1. Source - Code checkout
  2. Build - Compile, package, containerize
  3. Test - Unit, integration, security scans
  4. Staging Deploy - Deploy to staging environment
  5. Integration Tests - E2E, smoke tests
  6. Approval Gate - Manual approval required
  7. Production Deploy - Canary, blue-green, rolling
  8. Verification - Health checks, monitoring
  9. Rollback - Automated rollback on failure

Approval Gate Patterns

Pattern 1: Manual Approval

# GitHub Actions
production-deploy:
  needs: staging-deploy
  environment:
    name: production
    url: https://app.example.com
  runs-on: ubuntu-latest
  steps:
    - name: Deploy to production
      run: |
        # Deployment commands

Pattern 2: Time-Based Approval

# GitLab CI
deploy:production:
  stage: deploy
  script:
    - deploy.sh production
  environment:
    name: production
  when: delayed
  start_in: 30 minutes
  only:
    - main

Pattern 3: Multi-Approver

# Azure Pipelines
stages:
- stage: Production
  dependsOn: Staging
  jobs:
  - deployment: Deploy
    environment:
      name: production
      resourceType: Kubernetes
    strategy:
      runOnce:
        preDeploy:
          steps:
          - task: ManualValidation@0
            inputs:
              notifyUsers: '[email protected]'
              instructions: 'Review staging metrics before approving'

Reference: See assets/​approval-gate-template.yml

Deployment Strategies

1. Rolling Deployment

apiVersion: apps/​v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 10
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 2
      maxUnavailable: 1

Characteristics:

  • Gradual rollout
  • Zero downtime
  • Easy rollback
  • Best for most applications

2. Blue-Green Deployment

# Blue (current)
kubectl apply -f blue-deployment.yaml
kubectl label service my-app version=blue

# Green (new)
kubectl apply -f green-deployment.yaml
# Test green environment
kubectl label service my-app version=green

# Rollback if needed
kubectl label service my-app version=blue

Characteristics:

  • Instant switchover
  • Easy rollback
  • Doubles infrastructure cost temporarily
  • Good for high-risk deployments

3. Canary Deployment

apiVersion: argoproj.io/​v1alpha1
kind: Rollout
metadata:
  name: my-app
spec:
  replicas: 10
  strategy:
    canary:
      steps:
      - setWeight: 10
      - pause: {duration: 5m}
      - setWeight: 25
      - pause: {duration: 5m}
      - setWeight: 50
      - pause: {duration: 5m}
      - setWeight: 100

Characteristics:

  • Gradual traffic shift
  • Risk mitigation
  • Real user testing
  • Requires service mesh or similar

4. Feature Flags

from flagsmith import Flagsmith

flagsmith = Flagsmith(environment_key="API_KEY")

if flagsmith.has_feature("new_checkout_flow"):
    # New code path
    process_checkout_v2()
else:
    # Existing code path
    process_checkout_v1()

Characteristics:

  • Deploy without releasing
  • A/​B testing
  • Instant rollback
  • Granular control

Pipeline Orchestration

Multi-Stage Pipeline Example

name: Production Pipeline

on:
  push:
    branches: [ main ]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/​checkout@v4
      - name: Build application
        run: make build
      - name: Build Docker image
        run: docker build -t myapp:${{ github.sha }} .
      - name: Push to registry
        run: docker push myapp:${{ github.sha }}

  test:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - name: Unit tests
        run: make test
      - name: Security scan
        run: trivy image myapp:${{ github.sha }}

  deploy-staging:
    needs: test
    runs-on: ubuntu-latest
    environment:
      name: staging

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