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devops-deploy

tranhieutt/software_development_department/.claude/skills/devops-deploy/SKILL.md

Skill71 starsChanged 5 months ago
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What's in it

  1. DevOps Deploy
  2. Production checklist (always verify)
  3. Docker: multi-stage Python
  4. Docker Compose (local dev)
  5. SAM template (Lambda + DynamoDB)
  6. GitHub Actions: test + security + deploy
  7. Health check endpoint (FastAPI)
  8. Pipeline Design
  9. Standard Pipeline Stages
  10. Deployment Strategy Selection
  11. GitOps Repository Structure
  12. Security Scanning in Pipeline
  13. DORA Metrics to Track
  14. Deployment Runbook Principles
  15. Platform Selection
  16. 5-Phase Deployment Process
  17. Verification Window
  18. Rollback Decision
  19. Anti-Patterns
  20. CloudWatch alarm (Python)
---
name: devops-deploy
type: workflow
description: "Designs and executes CI/CD pipelines, GitOps workflows, deployment automation, and cloud infrastructure deployment including Docker, AWS Lambda, SAM, Terraform, and GitHub Actions. Use when building or improving CI/CD pipelines, containerizing applications, creating deployment runbooks, or deploying to cloud infrastructure."
paths: ["**/Dockerfile*", "**/k8s/**", "**/infra/**", "**/.github/workflows/**", "**/template.yaml", "**/deploy/**"]
effort: 3
argument-hint: "[target: docker|lambda|k8s|terraform|github-actions|pipeline|runbook]"
user-invocable: true
when_to_use: "When dockerizing applications, configuring CI/CD pipelines, deploying to AWS, setting up infrastructure as code, designing GitOps workflows, or creating deployment runbooks"
allowed-tools: Read, Glob, Grep, Write, Edit, Bash
---

# DevOps Deploy

## Production checklist (always verify)

- [ ] Env vars via Secrets Manager — never hardcoded
- [ ] Health check endpoint responding
- [ ] Structured JSON logs with `request_id`
- [ ] Rate limiting configured
- [ ] CORS restricted to authorized domains
- [ ] Lambda timeout appropriate (10–30s)
- [ ] CloudWatch alarms for errors and latency
- [ ] Rollback plan documented
- [ ] Load test before launch

## Docker: multi-stage Python

```dockerfile
FROM python:3.11-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir --user -r requirements.txt

FROM python:3.11-slim
WORKDIR /app
COPY --from=builder /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
HEALTHCHECK --interval=30s --timeout=3s CMD curl -f http://localhost:8000/health || exit 1
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
```

## Docker Compose (local dev)

```yaml
services:
  app:
    build: .
    ports: ["8000:8000"]
    environment:
      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
    volumes:
      - .:/app
    depends_on: [db, redis]
  db:
    image: postgres:15
    environment:
      POSTGRES_DB: app
      POSTGRES_USER: app
      POSTGRES_PASSWORD: ${DB_PASSWORD}
    volumes:
      - pgdata:/var/lib/postgresql/data
  redis:
    image: redis:7-alpine
volumes:
  pgdata:
```

## SAM template (Lambda + DynamoDB)

```yaml
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Globals:
  Function:
    Timeout: 30
    Runtime: python3.11
    Environment:
      Variables:
        DYNAMODB_TABLE: !Ref AppTable

Resources:
  AppFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: src/
      Handler: lambda_function.handler
      MemorySize: 512
      Policies:
        - DynamoDBCrudPolicy:
            TableName: !Ref AppTable

  AppTable:
    Type: AWS::DynamoDB::Table
    Properties:
      BillingMode: PAY_PER_REQUEST
      AttributeDefinitions:
        - AttributeName: userId
          AttributeType: S
      KeySchema:
        - AttributeName: userId
          KeyType: HASH
      TimeToLiveSpecification:
        AttributeName: ttl
        Enabled: true
```

```bash
# SAM commands
sam build
sam deploy --guided          # first time (creates samconfig.toml)
sam deploy                   # subsequent
sam deploy --no-confirm-changeset --no-fail-on-empty-changeset
sam logs -n AppFunction --tail
```

## GitHub Actions: test + security + deploy

```yaml
name: Deploy
on:
  push:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with: { python-version: "3.11" }
      - run: pip install -r requirements.txt
      - run: pytest tests/ -v --cov=src --cov-report=xml

  security:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: pip install bandit safety
      - run: bandit -r src/ -ll
      - run: safety check -r requirements.txt

  deploy:
    needs: [test, security]
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: aws-actions/setup-sam@v2
      - 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-east-1
      - run: sam build
      - run: sam deploy --no-confirm-changeset
```

## Health check endpoint (FastAPI)

```python
import time, os
from fastapi import FastAPI

app = FastAPI()
START_TIME = time.time()

@app.get("/health")
async def health():
    return {
        "status": "healthy",
        "uptime_seconds": time.time() - START_TIME,
        "version": os.environ.get("APP_VERSION", "unknown"),
    }
```

## Pipeline Design

### Standard Pipeline Stages

```
[Build] -> [Test] -> [Security Scan] -> [Package] -> [Deploy Staging] -> [Integration Test] -> [Approval] -> [Deploy Prod] -> [Verify]
```

| Stage | Actions | Failure Policy |
|-------|---------|----------------|
| Build | Compile, lint, type-check | Block |
| Test | Unit + integration tests | Block |
| Security | SAST, dependency scan, container scan | Block on Critical/High |
| Package | Docker build, push to registry, sign image | Block |
| Deploy Staging | Apply manifests/Helm, run smoke tests | Block |
| Approval | Manual gate for production | Require approval |
| Deploy Prod | Progressive rollout | Auto-rollback on failure |
| Verify | Health checks, metrics validation | Auto-rollback |

### Deployment Strategy Selection

| Strategy | Zero-downtime | Rollback Speed | Resource Cost | Use When |
|----------|---------------|----------------|---------------|----------|
| Rolling Update | Yes | Slow (redeploy) | Low | Default for most services |
| Blue/Green | Yes | Instant (switch) | 2x | Critical services, DB-independent |
| Canary | Yes | Fast (shift) | 1.1x | High-traffic, need real-user validation |

### GitOps Repository Structure

```
app-repo/           # Application source code + Dockerfile
env-repo/           # Environment configs
  base/             # Base manifests
  overlays/
    dev/
    staging/
    prod/
```

Tools: ArgoCD or Flux v2 · Kustomize or Helm · External Secrets Operator

### Security Scanning in Pipeline

- SAST: CodeQL, Semgrep, SonarQube
- Dependency: Snyk, Dependabot, npm audit
- Container: Trivy, Grype
- Secrets: GitLeaks, TruffleHog
- SBOM: Syft · Image signing: Cosign

### DORA Metrics to Track

- Deployment frequency
- Lead time for changes
- Change failure rate
- Mean time to recovery (MTTR)

---

## Deployment Runbook Principles

### Platform Selection

```
What are you deploying?
├── Static site → Vercel, Netlify, Cloudflare Pages
├── Simple web app → Railway, Render, Fly.io / VPS + PM2
├── Microservices → Container orchestration
└── Serverless → Edge functions, Lambda
```

| Platform | Deployment Method | Rollback |
|----------|------------------|---------|
| Vercel/Netlify | Git push, auto-deploy | Redeploy previous commit |
| Railway/Render | Git push or CLI | Dashboard rollback |
| VPS + PM2 | SSH + manual steps | Restore backup, restart |
| Docker | Image push + orchestration | Previous image tag |
| Kubernetes | kubectl apply | kubectl rollout undo |

### 5-Phase Deployment Process

```
1. PREPARE  → Verify code, build, env vars
2. BACKUP   → Save current state before changing
3. DEPLOY   → Execute with monitoring open
4. VERIFY   → Health check, logs, key flows
5. CONFIRM or ROLLBACK
```

### Verification Window

- First 5 min: Active monitoring
- 15 min: Confirm stable
- 1 hour: Final verification
- Next day: Review metrics

### Rollback Decision

| Symptom | Action |
|---------|--------|
| Service down | Rollback immediately |
| Critical errors | Rollback |
| Performance >50% degraded | Consider rollback |
| Minor issues | Fix forward if quick |

Rollback principles: Speed over perfection → Communicate → Post-mortem after stable.

### Anti-Patterns

| ❌ Don't | ✅ Do |
|----------|-------|
| Deploy on Friday | Deploy early in week |
| Skip staging | Always test first |
| Deploy without backup | Backup before deploy |
| Walk away after deploy | Monitor for 15+ min |
| Multiple changes at once | One change at a time |

---

## CloudWatch alarm (Python)

```python
import boto3

def create_error_alarm(function_name: str, sns_topic_arn: str):
    cw = boto3.client("cloudwatch")
    cw.put_metric_alarm(
        AlarmName=f"{function_name}-errors",
        MetricName="Errors",
        Namespace="AWS/Lambda",
        Dimensions=[{"Name": "FunctionName", "Value": function_name}],
        Period=300, EvaluationPeriods=1, Threshold=5,
        ComparisonOperator="GreaterThanThreshold",
        AlarmActions=[sns_topic_arn],
        TreatMissingData="notBreaching",
    )
```

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