DevOps

CALMS Framework
• Culture: shared responsibility, blameless post-mortems, psychological safety
• Automation: eliminate manual, repetitive steps
• Lean: minimize waste, work in small batches
• Measurement: data-driven decisions (DORA metrics)
• Sharing: knowledge, tools, and on-call responsibilities

DORA Metrics (measuring DevOps performance)
• Deployment Frequency: how often you ship
• Lead Time for Changes: commit to production time
• Change Failure Rate: % of deployments causing incidents
• MTTR (Mean Time to Restore): how fast you recover from failures

Continuous Integration (CI) Every code commit triggers automated build and test execution.

# GitHub Actions example
name: CI Pipeline
on: [push, pull_request]

jobs: build-test: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - name: Setup Node.js uses: actions/setup-node@v3 with: node-version: '20' - run: npm ci - run: npm run lint - run: npm test -- --coverage - name: Security Scan run: npm audit --audit-level=high ```

Continuous Delivery (CD) Every passing build is deployable to production (human approval gate).

Continuous Deployment Every passing build automatically deploys to production (no human gate).

Pipeline Stages 1. Source (commit trigger) 2. Build (compile, bundle) 3. Test (unit, integration, E2E) 4. Security Scan (SAST, dependency audit) 5. Staging Deploy 6. Smoke Tests 7. Production Deploy (blue/green or canary)

Docker ```dockerfile FROM node:20-alpine

WORKDIR /app COPY package*.json ./ RUN npm ci --production COPY . .

EXPOSE 3000 USER node CMD ["node", "server.js"] ```

Docker Compose (multi-container local dev) ``yaml version: '3.8' services: app: build: . ports: ["3000:3000"] environment: - DATABASE_URL=postgres://db:5432/mydb depends_on: [db] db: image: postgres:15 volumes: - pgdata:/var/lib/postgresql/data volumes: pgdata: ``

Kubernetes Key Concepts
• Pod: smallest unit, one or more containers
• Deployment: manages pod replicas and rolling updates
• Service: stable network endpoint for pods
• Ingress: HTTP routing rules into the cluster
• ConfigMap / Secret: externalize configuration
• HPA (Horizontal Pod Autoscaler): scale based on CPU/memory

Terraform Declarative IaC for any cloud provider. ```hcl provider "aws" { region = "us-east-1" }

resource "aws_s3_bucket" "data" { bucket = "my-data-lake-bucket"

tags = { Environment = "production" Team = "data-engineering" } }

resource "aws_s3_bucket_versioning" "data" { bucket = aws_s3_bucket.data.id versioning_configuration { status = "Enabled" } } ```

GitOps Git as single source of truth for infrastructure state. ArgoCD / Flux watch Git and sync cluster state.

Observability Stack
• Metrics: Prometheus + Grafana
• Logs: ELK Stack (Elasticsearch, Logstash, Kibana) or Loki
• Traces: Jaeger / Zipkin / OpenTelemetry
• Alerts: PagerDuty, OpsGenie

# .github/workflows/deploy.yml
name: Deploy

on: push: branches: [main]

jobs: test: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: { node-version: 20, cache: npm } - run: npm ci && npm test

build: needs: test runs-on: ubuntu-latest outputs: image-tag: ${{ steps.meta.outputs.tags }} steps: - uses: actions/checkout@v4 - name: Set up Docker Buildx uses: docker/setup-buildx-action@v3 - name: Log in to ECR uses: aws-actions/amazon-ecr-login@v2 - name: Build and push id: meta uses: docker/build-push-action@v5 with: push: true tags: ${{ env.ECR_REGISTRY }}/app:${{ github.sha }} cache-from: type=gha cache-to: type=gha,mode=max

deploy: needs: build runs-on: ubuntu-latest environment: production # requires manual approval steps: - name: Deploy to ECS run: | aws ecs update-service \ --cluster prod \ --service api \ --force-new-deployment - name: Verify deployment run: | aws ecs wait services-stable \ --cluster prod \ --services api

notify: needs: [deploy] if: always() runs-on: ubuntu-latest steps: - uses: slackapi/slack-github-action@v1 with: payload: '{"status":"${{ needs.deploy.result }}"}' env: SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK }} ```