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---
name: deployment-pipeline-design
description: Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.
---
# Deployment Pipeline Design
Architecture patterns for multi-stage CI/CD pipelines with approval gates and deployment strategies.
## Purpose
Design robust, secure deployment pipelines that balance speed with safety through proper stage organization and approval workflows.
## When to Use
- 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
```yaml
# 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
```yaml
# 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
```yaml
# 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
```yaml
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
```yaml
# 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
```yaml
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
```python
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
```yaml
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
steps:
- name: Deploy to staging
run: kubectl apply -f k8s/staging/
integration-test:
needs: deploy-staging
runs-on: ubuntu-latest
steps:
- name: Run E2E tests
run: npm run test:e2e
deploy-production:
needs: integration-test
runs-on: ubuntu-latest
environment:
name: production
steps:
- name: Canary deployment
run: |
kubectl apply -f k8s/production/
kubectl argo rollouts promote my-app
verify:
needs: deploy-production
runs-on: ubuntu-latest
steps:
- name: Health check
run: curl -f https://app.example.com/health
- name: Notify team
run: |
curl -X POST ${{ secrets.SLACK_WEBHOOK }} \
-d '{"text":"Production deployment successful!"}'
```
## Pipeline Best Practices
1. **Fail fast** - Run quick tests first
2. **Parallel execution** - Run independent jobs concurrently
3. **Caching** - Cache dependencies between runs
4. **Artifact management** - Store build artifacts
5. **Environment parity** - Keep environments consistent
6. **Secrets management** - Use secret stores (Vault, etc.)
7. **Deployment windows** - Schedule deployments appropriately
8. **Monitoring integration** - Track deployment metrics
9. **Rollback automation** - Auto-rollback on failures
10. **Documentation** - Document pipeline stages
## Rollback Strategies
### Automated Rollback
```yaml
deploy-and-verify:
steps:
- name: Deploy new version
run: kubectl apply -f k8s/
- name: Wait for rollout
run: kubectl rollout status deployment/my-app
- name: Health check
id: health
run: |
for i in {1..10}; do
if curl -sf https://app.example.com/health; then
exit 0
fi
sleep 10
done
exit 1
- name: Rollback on failure
if: failure()
run: kubectl rollout undo deployment/my-app
```
### Manual Rollback
```bash
# List revision history
kubectl rollout history deployment/my-app
# Rollback to previous version
kubectl rollout undo deployment/my-app
# Rollback to specific revision
kubectl rollout undo deployment/my-app --to-revision=3
```
## Monitoring and Metrics
### Key Pipeline Metrics
- **Deployment Frequency** - How often deployments occur
- **Lead Time** - Time from commit to production
- **Change Failure Rate** - Percentage of failed deployments
- **Mean Time to Recovery (MTTR)** - Time to recover from failure
- **Pipeline Success Rate** - Percentage of successful runs
- **Average Pipeline Duration** - Time to complete pipeline
### Integration with Monitoring
```yaml
- name: Post-deployment verification
run: |
# Wait for metrics stabilization
sleep 60
# Check error rate
ERROR_RATE=$(curl -s "$PROMETHEUS_URL/api/v1/query?query=rate(http_errors_total[5m])" | jq '.data.result[0].value[1]')
if (( $(echo "$ERROR_RATE > 0.01" | bc -l) )); then
echo "Error rate too high: $ERROR_RATE"
exit 1
fi
```
## Reference Files
- `references/pipeline-orchestration.md` - Complex pipeline patterns
- `assets/approval-gate-template.yml` - Approval workflow templates
## Related Skills
- `github-actions-templates` - For GitHub Actions implementation
- `gitlab-ci-patterns` - For GitLab CI implementation
- `secrets-management` - For secrets handling

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---
name: github-actions-templates
description: Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.
---
# GitHub Actions Templates
Production-ready GitHub Actions workflow patterns for testing, building, and deploying applications.
## Purpose
Create efficient, secure GitHub Actions workflows for continuous integration and deployment across various tech stacks.
## When to Use
- Automate testing and deployment
- Build Docker images and push to registries
- Deploy to Kubernetes clusters
- Run security scans
- Implement matrix builds for multiple environments
## Common Workflow Patterns
### Pattern 1: Test Workflow
```yaml
name: Test
on:
push:
branches: [ main, develop ]
pull_request:
branches: [ main ]
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
node-version: [18.x, 20.x]
steps:
- uses: actions/checkout@v4
- name: Use Node.js ${{ matrix.node-version }}
uses: actions/setup-node@v4
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
- name: Install dependencies
run: npm ci
- name: Run linter
run: npm run lint
- name: Run tests
run: npm test
- name: Upload coverage
uses: codecov/codecov-action@v3
with:
files: ./coverage/lcov.info
```
**Reference:** See `assets/test-workflow.yml`
### Pattern 2: Build and Push Docker Image
```yaml
name: Build and Push
on:
push:
branches: [ main ]
tags: [ 'v*' ]
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- uses: actions/checkout@v4
- name: Log in to Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=branch
type=ref,event=pr
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}
- name: Build and push
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
```
**Reference:** See `assets/deploy-workflow.yml`
### Pattern 3: Deploy to Kubernetes
```yaml
name: Deploy to Kubernetes
on:
push:
branches: [ main ]
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-west-2
- name: Update kubeconfig
run: |
aws eks update-kubeconfig --name production-cluster --region us-west-2
- name: Deploy to Kubernetes
run: |
kubectl apply -f k8s/
kubectl rollout status deployment/my-app -n production
kubectl get services -n production
- name: Verify deployment
run: |
kubectl get pods -n production
kubectl describe deployment my-app -n production
```
### Pattern 4: Matrix Build
```yaml
name: Matrix Build
on: [push, pull_request]
jobs:
build:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: ['3.9', '3.10', '3.11', '3.12']
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: Run tests
run: pytest
```
**Reference:** See `assets/matrix-build.yml`
## Workflow Best Practices
1. **Use specific action versions** (@v4, not @latest)
2. **Cache dependencies** to speed up builds
3. **Use secrets** for sensitive data
4. **Implement status checks** on PRs
5. **Use matrix builds** for multi-version testing
6. **Set appropriate permissions**
7. **Use reusable workflows** for common patterns
8. **Implement approval gates** for production
9. **Add notification steps** for failures
10. **Use self-hosted runners** for sensitive workloads
## Reusable Workflows
```yaml
# .github/workflows/reusable-test.yml
name: Reusable Test Workflow
on:
workflow_call:
inputs:
node-version:
required: true
type: string
secrets:
NPM_TOKEN:
required: true
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: ${{ inputs.node-version }}
- run: npm ci
- run: npm test
```
**Use reusable workflow:**
```yaml
jobs:
call-test:
uses: ./.github/workflows/reusable-test.yml
with:
node-version: '20.x'
secrets:
NPM_TOKEN: ${{ secrets.NPM_TOKEN }}
```
## Security Scanning
```yaml
name: Security Scan
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
jobs:
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
with:
scan-type: 'fs'
scan-ref: '.'
format: 'sarif'
output: 'trivy-results.sarif'
- name: Upload Trivy results to GitHub Security
uses: github/codeql-action/upload-sarif@v2
with:
sarif_file: 'trivy-results.sarif'
- name: Run Snyk Security Scan
uses: snyk/actions/node@master
env:
SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
```
## Deployment with Approvals
```yaml
name: Deploy to Production
on:
push:
tags: [ 'v*' ]
jobs:
deploy:
runs-on: ubuntu-latest
environment:
name: production
url: https://app.example.com
steps:
- uses: actions/checkout@v4
- name: Deploy application
run: |
echo "Deploying to production..."
# Deployment commands here
- name: Notify Slack
if: success()
uses: slackapi/slack-github-action@v1
with:
webhook-url: ${{ secrets.SLACK_WEBHOOK }}
payload: |
{
"text": "Deployment to production completed successfully!"
}
```
## Reference Files
- `assets/test-workflow.yml` - Testing workflow template
- `assets/deploy-workflow.yml` - Deployment workflow template
- `assets/matrix-build.yml` - Matrix build template
- `references/common-workflows.md` - Common workflow patterns
## Related Skills
- `gitlab-ci-patterns` - For GitLab CI workflows
- `deployment-pipeline-design` - For pipeline architecture
- `secrets-management` - For secrets handling

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---
name: gitlab-ci-patterns
description: Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.
---
# GitLab CI Patterns
Comprehensive GitLab CI/CD pipeline patterns for automated testing, building, and deployment.
## Purpose
Create efficient GitLab CI pipelines with proper stage organization, caching, and deployment strategies.
## When to Use
- Automate GitLab-based CI/CD
- Implement multi-stage pipelines
- Configure GitLab Runners
- Deploy to Kubernetes from GitLab
- Implement GitOps workflows
## Basic Pipeline Structure
```yaml
stages:
- build
- test
- deploy
variables:
DOCKER_DRIVER: overlay2
DOCKER_TLS_CERTDIR: "/certs"
build:
stage: build
image: node:20
script:
- npm ci
- npm run build
artifacts:
paths:
- dist/
expire_in: 1 hour
cache:
key: ${CI_COMMIT_REF_SLUG}
paths:
- node_modules/
test:
stage: test
image: node:20
script:
- npm ci
- npm run lint
- npm test
coverage: '/Lines\s*:\s*(\d+\.\d+)%/'
artifacts:
reports:
coverage_report:
coverage_format: cobertura
path: coverage/cobertura-coverage.xml
deploy:
stage: deploy
image: bitnami/kubectl:latest
script:
- kubectl apply -f k8s/
- kubectl rollout status deployment/my-app
only:
- main
environment:
name: production
url: https://app.example.com
```
## Docker Build and Push
```yaml
build-docker:
stage: build
image: docker:24
services:
- docker:24-dind
before_script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
script:
- docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
- docker build -t $CI_REGISTRY_IMAGE:latest .
- docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
- docker push $CI_REGISTRY_IMAGE:latest
only:
- main
- tags
```
## Multi-Environment Deployment
```yaml
.deploy_template: &deploy_template
image: bitnami/kubectl:latest
before_script:
- kubectl config set-cluster k8s --server="$KUBE_URL" --insecure-skip-tls-verify=true
- kubectl config set-credentials admin --token="$KUBE_TOKEN"
- kubectl config set-context default --cluster=k8s --user=admin
- kubectl config use-context default
deploy:staging:
<<: *deploy_template
stage: deploy
script:
- kubectl apply -f k8s/ -n staging
- kubectl rollout status deployment/my-app -n staging
environment:
name: staging
url: https://staging.example.com
only:
- develop
deploy:production:
<<: *deploy_template
stage: deploy
script:
- kubectl apply -f k8s/ -n production
- kubectl rollout status deployment/my-app -n production
environment:
name: production
url: https://app.example.com
when: manual
only:
- main
```
## Terraform Pipeline
```yaml
stages:
- validate
- plan
- apply
variables:
TF_ROOT: ${CI_PROJECT_DIR}/terraform
TF_VERSION: "1.6.0"
before_script:
- cd ${TF_ROOT}
- terraform --version
validate:
stage: validate
image: hashicorp/terraform:${TF_VERSION}
script:
- terraform init -backend=false
- terraform validate
- terraform fmt -check
plan:
stage: plan
image: hashicorp/terraform:${TF_VERSION}
script:
- terraform init
- terraform plan -out=tfplan
artifacts:
paths:
- ${TF_ROOT}/tfplan
expire_in: 1 day
apply:
stage: apply
image: hashicorp/terraform:${TF_VERSION}
script:
- terraform init
- terraform apply -auto-approve tfplan
dependencies:
- plan
when: manual
only:
- main
```
## Security Scanning
```yaml
include:
- template: Security/SAST.gitlab-ci.yml
- template: Security/Dependency-Scanning.gitlab-ci.yml
- template: Security/Container-Scanning.gitlab-ci.yml
trivy-scan:
stage: test
image: aquasec/trivy:latest
script:
- trivy image --exit-code 1 --severity HIGH,CRITICAL $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
allow_failure: true
```
## Caching Strategies
```yaml
# Cache node_modules
build:
cache:
key: ${CI_COMMIT_REF_SLUG}
paths:
- node_modules/
policy: pull-push
# Global cache
cache:
key: ${CI_COMMIT_REF_SLUG}
paths:
- .cache/
- vendor/
# Separate cache per job
job1:
cache:
key: job1-cache
paths:
- build/
job2:
cache:
key: job2-cache
paths:
- dist/
```
## Dynamic Child Pipelines
```yaml
generate-pipeline:
stage: build
script:
- python generate_pipeline.py > child-pipeline.yml
artifacts:
paths:
- child-pipeline.yml
trigger-child:
stage: deploy
trigger:
include:
- artifact: child-pipeline.yml
job: generate-pipeline
strategy: depend
```
## Reference Files
- `assets/gitlab-ci.yml.template` - Complete pipeline template
- `references/pipeline-stages.md` - Stage organization patterns
## Best Practices
1. **Use specific image tags** (node:20, not node:latest)
2. **Cache dependencies** appropriately
3. **Use artifacts** for build outputs
4. **Implement manual gates** for production
5. **Use environments** for deployment tracking
6. **Enable merge request pipelines**
7. **Use pipeline schedules** for recurring jobs
8. **Implement security scanning**
9. **Use CI/CD variables** for secrets
10. **Monitor pipeline performance**
## Related Skills
- `github-actions-templates` - For GitHub Actions
- `deployment-pipeline-design` - For architecture
- `secrets-management` - For secrets handling

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---
name: secrets-management
description: Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.
---
# Secrets Management
Secure secrets management practices for CI/CD pipelines using Vault, AWS Secrets Manager, and other tools.
## Purpose
Implement secure secrets management in CI/CD pipelines without hardcoding sensitive information.
## When to Use
- Store API keys and credentials
- Manage database passwords
- Handle TLS certificates
- Rotate secrets automatically
- Implement least-privilege access
## Secrets Management Tools
### HashiCorp Vault
- Centralized secrets management
- Dynamic secrets generation
- Secret rotation
- Audit logging
- Fine-grained access control
### AWS Secrets Manager
- AWS-native solution
- Automatic rotation
- Integration with RDS
- CloudFormation support
### Azure Key Vault
- Azure-native solution
- HSM-backed keys
- Certificate management
- RBAC integration
### Google Secret Manager
- GCP-native solution
- Versioning
- IAM integration
## HashiCorp Vault Integration
### Setup Vault
```bash
# Start Vault dev server
vault server -dev
# Set environment
export VAULT_ADDR='http://127.0.0.1:8200'
export VAULT_TOKEN='root'
# Enable secrets engine
vault secrets enable -path=secret kv-v2
# Store secret
vault kv put secret/database/config username=admin password=secret
```
### GitHub Actions with Vault
```yaml
name: Deploy with Vault Secrets
on: [push]
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Import Secrets from Vault
uses: hashicorp/vault-action@v2
with:
url: https://vault.example.com:8200
token: ${{ secrets.VAULT_TOKEN }}
secrets: |
secret/data/database username | DB_USERNAME ;
secret/data/database password | DB_PASSWORD ;
secret/data/api key | API_KEY
- name: Use secrets
run: |
echo "Connecting to database as $DB_USERNAME"
# Use $DB_PASSWORD, $API_KEY
```
### GitLab CI with Vault
```yaml
deploy:
image: vault:latest
before_script:
- export VAULT_ADDR=https://vault.example.com:8200
- export VAULT_TOKEN=$VAULT_TOKEN
- apk add curl jq
script:
- |
DB_PASSWORD=$(vault kv get -field=password secret/database/config)
API_KEY=$(vault kv get -field=key secret/api/credentials)
echo "Deploying with secrets..."
# Use $DB_PASSWORD, $API_KEY
```
**Reference:** See `references/vault-setup.md`
## AWS Secrets Manager
### Store Secret
```bash
aws secretsmanager create-secret \
--name production/database/password \
--secret-string "super-secret-password"
```
### Retrieve in GitHub Actions
```yaml
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-west-2
- name: Get secret from AWS
run: |
SECRET=$(aws secretsmanager get-secret-value \
--secret-id production/database/password \
--query SecretString \
--output text)
echo "::add-mask::$SECRET"
echo "DB_PASSWORD=$SECRET" >> $GITHUB_ENV
- name: Use secret
run: |
# Use $DB_PASSWORD
./deploy.sh
```
### Terraform with AWS Secrets Manager
```hcl
data "aws_secretsmanager_secret_version" "db_password" {
secret_id = "production/database/password"
}
resource "aws_db_instance" "main" {
allocated_storage = 100
engine = "postgres"
instance_class = "db.t3.large"
username = "admin"
password = jsondecode(data.aws_secretsmanager_secret_version.db_password.secret_string)["password"]
}
```
## GitHub Secrets
### Organization/Repository Secrets
```yaml
- name: Use GitHub secret
run: |
echo "API Key: ${{ secrets.API_KEY }}"
echo "Database URL: ${{ secrets.DATABASE_URL }}"
```
### Environment Secrets
```yaml
deploy:
runs-on: ubuntu-latest
environment: production
steps:
- name: Deploy
run: |
echo "Deploying with ${{ secrets.PROD_API_KEY }}"
```
**Reference:** See `references/github-secrets.md`
## GitLab CI/CD Variables
### Project Variables
```yaml
deploy:
script:
- echo "Deploying with $API_KEY"
- echo "Database: $DATABASE_URL"
```
### Protected and Masked Variables
- Protected: Only available in protected branches
- Masked: Hidden in job logs
- File type: Stored as file
## Best Practices
1. **Never commit secrets** to Git
2. **Use different secrets** per environment
3. **Rotate secrets regularly**
4. **Implement least-privilege access**
5. **Enable audit logging**
6. **Use secret scanning** (GitGuardian, TruffleHog)
7. **Mask secrets in logs**
8. **Encrypt secrets at rest**
9. **Use short-lived tokens** when possible
10. **Document secret requirements**
## Secret Rotation
### Automated Rotation with AWS
```python
import boto3
import json
def lambda_handler(event, context):
client = boto3.client('secretsmanager')
# Get current secret
response = client.get_secret_value(SecretId='my-secret')
current_secret = json.loads(response['SecretString'])
# Generate new password
new_password = generate_strong_password()
# Update database password
update_database_password(new_password)
# Update secret
client.put_secret_value(
SecretId='my-secret',
SecretString=json.dumps({
'username': current_secret['username'],
'password': new_password
})
)
return {'statusCode': 200}
```
### Manual Rotation Process
1. Generate new secret
2. Update secret in secret store
3. Update applications to use new secret
4. Verify functionality
5. Revoke old secret
## External Secrets Operator
### Kubernetes Integration
```yaml
apiVersion: external-secrets.io/v1beta1
kind: SecretStore
metadata:
name: vault-backend
namespace: production
spec:
provider:
vault:
server: "https://vault.example.com:8200"
path: "secret"
version: "v2"
auth:
kubernetes:
mountPath: "kubernetes"
role: "production"
---
apiVersion: external-secrets.io/v1beta1
kind: ExternalSecret
metadata:
name: database-credentials
namespace: production
spec:
refreshInterval: 1h
secretStoreRef:
name: vault-backend
kind: SecretStore
target:
name: database-credentials
creationPolicy: Owner
data:
- secretKey: username
remoteRef:
key: database/config
property: username
- secretKey: password
remoteRef:
key: database/config
property: password
```
## Secret Scanning
### Pre-commit Hook
```bash
#!/bin/bash
# .git/hooks/pre-commit
# Check for secrets with TruffleHog
docker run --rm -v "$(pwd):/repo" \
trufflesecurity/trufflehog:latest \
filesystem --directory=/repo
if [ $? -ne 0 ]; then
echo "❌ Secret detected! Commit blocked."
exit 1
fi
```
### CI/CD Secret Scanning
```yaml
secret-scan:
stage: security
image: trufflesecurity/trufflehog:latest
script:
- trufflehog filesystem .
allow_failure: false
```
## Reference Files
- `references/vault-setup.md` - HashiCorp Vault configuration
- `references/github-secrets.md` - GitHub Secrets best practices
## Related Skills
- `github-actions-templates` - For GitHub Actions integration
- `gitlab-ci-patterns` - For GitLab CI integration
- `deployment-pipeline-design` - For pipeline architecture