Deployment Pipeline Design

# 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: 'team-leads@example.com'
              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