Git Notes

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CI/CD with GitHub Actions

Continuous Integration and Continuous Deployment (CI/CD) is the backbone of modern software delivery. CI ensures that every code change is automatically...

Continuous Integration and Continuous Deployment (CI/CD) is the backbone of modern software delivery. CI ensures that every code change is automatically tested and validated, while CD automates the deployment of validated code to production. GitHub Actions provides a native, powerful CI/CD platform built directly into your repository — no external tools needed.

Understanding CI/CD

Continuous Integration (CI) is the practice of frequently merging developer code into a shared repository, with each merge triggering automated builds and tests. The goal is to catch integration problems early when they are cheap to fix.

Continuous Deployment (CD) takes validated code and automatically deploys it to production. Every change that passes CI goes live without manual intervention.

Continuous Delivery (also CD) is the middle ground — code is automatically prepared for deployment but requires manual approval to go live.

Developer Push → Build → Test → Deploy to Staging → Approve → Deploy to Production ↑ ↑ └─── Continuous Integration ───┘ └── Continuous Deployment ──┘

Building a Complete CI/CD Pipeline

Example

name: CI/CD Pipeline on: push: branches: [main] pull_request: branches: [main] jobs: # Stage 1: Quality Checks lint: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: node-version: '20' cache: 'npm' - run: npm ci - run: npm run lint - run: npm run type-check # Stage 2: Testing test: needs: lint runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: node-version: '20' cache: 'npm' - run: npm ci - run: npm test -- --coverage - uses: codecov/codecov-action@v4 # Stage 3: Build build: needs: test runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: node-version: '20' cache: 'npm' - run: npm ci - run: npm run build - uses: actions/upload-artifact@v4 with: name: build-output path: dist/ # Stage 4: Deploy (only on main branch push) deploy: needs: build if: github.ref == 'refs/heads/main' && github.event_name == 'push' runs-on: ubuntu-latest environment: production steps: - uses: actions/download-artifact@v4 with: name: build-output path: dist/ - name: Deploy to production run: | echo "Deploying to production server..." # Your deployment commands here

Pipeline Stages Explained

Stage 1: Code Quality

Before running expensive tests, verify code quality:

Linting catches style violations and potential bugs
Type checking (TypeScript) catches type errors at build time
Formatting ensures consistent code style

If linting fails, the pipeline stops immediately — no point testing code that does not meet standards.

Stage 2: Testing

Run your test suite at various levels:

Unit tests (fastest, most numerous)
Integration tests (moderate speed)
End-to-end tests (slowest, fewest)

Stage 3: Build

Compile the application into deployment artifacts:

Bundle JavaScript/TypeScript
Optimize assets (images, CSS)
Generate static pages
Create Docker images

Stage 4: Deploy

Place the built artifacts on servers:

Upload to cloud hosting (Vercel, Netlify, AWS)
Push Docker images to registries
Update Kubernetes deployments
Trigger serverless function updates

Environment Protection

GitHub Actions environments add safety to deployments:

yaml example

deploy:
  environment:
    name: production
    url: https://myapp.com

Configure environment protection rules:

Required reviewers — Someone must approve before deployment
Wait timer — Delay deployment by N minutes (cancel window)
Branch restrictions — Only deploy from specific branches

Secrets Management

Store sensitive values securely:

yaml example

steps:
  - name: Deploy
    env:
      AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
      AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
      DATABASE_URL: ${{ secrets.DATABASE_URL }}
    run: npm run deploy

Secrets are encrypted, never exposed in logs, and can be scoped to specific environments.

Parallel vs Sequential Jobs

Run independent jobs simultaneously to save time:

Example

jobs: lint: # Runs immediately test-unit: # Runs immediately (parallel with lint) test-e2e: # Runs immediately (parallel with lint and test-unit) build: needs: [lint, test-unit, test-e2e] # Waits for all three deploy: needs: build # Waits for build

Monitoring and Notifications

Alert the team when pipelines fail:

yaml example

- name: Notify on failure
  if: failure()
  uses: slackapi/slack-github-action@v1
  with:
    payload: |
      {"text": "CI/CD failed on ${{ github.ref }}"}
  env:
    SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK }}

Rollback Strategy

Include rollback capability in your pipeline:

yaml example

rollback:
  if: failure() && needs.deploy.result == 'failure'
  needs: deploy
  runs-on: ubuntu-latest
  steps:
    - name: Rollback to previous version
      run: |
        # Revert to the last known good deployment
        aws ecs update-service --desired-count 0 --service new-version
        aws ecs update-service --desired-count 2 --service stable-version

Key Takeaways

CI/CD with GitHub Actions automates the entire path from code commit to production deployment. Structure your pipeline in stages — quality checks, testing, building, and deploying — with each stage acting as a gate. Use environments for deployment protection, secrets for sensitive configuration, and parallel jobs for speed. A well-designed pipeline gives teams confidence to deploy frequently, knowing that automation catches problems before users encounter them.

Exam Focus

Revise definitions, diagrams, examples, and short-answer points for CI/CD with GitHub Actions.

Interview Use

Prepare one clear explanation, one practical example, and one common mistake for this Git & GitHub topic.

Search Terms

git-github, git & github, git, github, actions, with, ci/cd with github actions

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Git Notes

CI/CD with GitHub Actions

Continuous Integration and Continuous Deployment (CI/CD) is the backbone of modern software delivery. CI ensures that every code change is automatically...

Understanding CI/CD

Continuous Deployment (CD) takes validated code and automatically deploys it to production. Every change that passes CI goes live without manual intervention.

Continuous Delivery (also CD) is the middle ground — code is automatically prepared for deployment but requires manual approval to go live.

Developer Push → Build → Test → Deploy to Staging → Approve → Deploy to Production ↑ ↑ └─── Continuous Integration ───┘ └── Continuous Deployment ──┘

Building a Complete CI/CD Pipeline

Example

Pipeline Stages Explained

Stage 1: Code Quality

Before running expensive tests, verify code quality:

Linting catches style violations and potential bugs
Type checking (TypeScript) catches type errors at build time
Formatting ensures consistent code style

If linting fails, the pipeline stops immediately — no point testing code that does not meet standards.

Stage 2: Testing

Run your test suite at various levels:

Unit tests (fastest, most numerous)
Integration tests (moderate speed)
End-to-end tests (slowest, fewest)

Stage 3: Build

Compile the application into deployment artifacts:

Bundle JavaScript/TypeScript
Optimize assets (images, CSS)
Generate static pages
Create Docker images

Stage 4: Deploy

Place the built artifacts on servers:

Upload to cloud hosting (Vercel, Netlify, AWS)
Push Docker images to registries
Update Kubernetes deployments
Trigger serverless function updates

Environment Protection

GitHub Actions environments add safety to deployments:

yaml example

deploy:
  environment:
    name: production
    url: https://myapp.com

Configure environment protection rules:

Required reviewers — Someone must approve before deployment
Wait timer — Delay deployment by N minutes (cancel window)
Branch restrictions — Only deploy from specific branches

Secrets Management

Store sensitive values securely:

yaml example

steps:
  - name: Deploy
    env:
      AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
      AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
      DATABASE_URL: ${{ secrets.DATABASE_URL }}
    run: npm run deploy

Secrets are encrypted, never exposed in logs, and can be scoped to specific environments.

Parallel vs Sequential Jobs

Run independent jobs simultaneously to save time:

Example

Monitoring and Notifications

Alert the team when pipelines fail:

yaml example

- name: Notify on failure
  if: failure()
  uses: slackapi/slack-github-action@v1
  with:
    payload: |
      {"text": "CI/CD failed on ${{ github.ref }}"}
  env:
    SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK }}

Rollback Strategy

Include rollback capability in your pipeline:

yaml example

rollback:
  if: failure() && needs.deploy.result == 'failure'
  needs: deploy
  runs-on: ubuntu-latest
  steps:
    - name: Rollback to previous version
      run: |
        # Revert to the last known good deployment
        aws ecs update-service --desired-count 0 --service new-version
        aws ecs update-service --desired-count 2 --service stable-version

Key Takeaways

Exam Focus

Revise definitions, diagrams, examples, and short-answer points for CI/CD with GitHub Actions.

Interview Use

Prepare one clear explanation, one practical example, and one common mistake for this Git & GitHub topic.

Search Terms

git-github, git & github, git, github, actions, with, ci/cd with github actions

Related Git & GitHub Topics

Continue learning this concept

PreviousAutomated Testing with GitHub Actions NextDeployment Automation with GitHub Actions