Part 5: Automated Tools and CI/CD Integration

Series Navigation: ← Part 4: Testing During Refactoring | Back to Series Overview β†’

Introduction

After covering principles, processes, techniques, and testing in Parts 1-4, it's time to automate. Manual code review and refactoring are essential, but automation ensures consistency and catches issues before they reach reviewers.

In my TypeScript microservices, we process 50-100 pull requests weekly. Without automation, maintaining code quality at this scale would be impossible. Our CI/CD pipeline catches formatting issues, linting errors, type problems, test failures, and security vulnerabilities automaticallyβ€”freeing reviewers to focus on architecture and logic rather than syntax.

This part covers the actual tools and configurations I use daily.

The Tool Stack

Our Complete Setup

Development Phase:
β”œβ”€β”€ ESLint          β†’ Code linting and style
β”œβ”€β”€ Prettier        β†’ Code formatting
β”œβ”€β”€ TypeScript      β†’ Type checking
β”œβ”€β”€ Jest            β†’ Testing
└── Husky           β†’ Pre-commit hooks

CI/CD Phase:
β”œβ”€β”€ GitHub Actions  β†’ Automated workflows
β”œβ”€β”€ SonarQube       β†’ Code quality analysis
β”œβ”€β”€ Snyk            β†’ Security scanning
└── Codecov         β†’ Coverage tracking

ESLint Configuration

My Production Configuration

Custom Rules for Our Domain

Prettier Configuration

Integration with ESLint

This prevents ESLint and Prettier from conflicting.

TypeScript Configuration

Strict Mode Configuration

This catches countless type errors during development.

Pre-commit Hooks with Husky

Setup

Configuration

Husky Hook

This runs automatically before every commit, ensuring:

  • Code is formatted

  • Linting passes

  • Related tests pass

GitHub Actions CI/CD

Main Workflow

Package Scripts

SonarQube Configuration

Quality Gate

Custom Quality Profile

In SonarQube UI, I configure:

  • Reliability: 0 bugs allowed

  • Security: 0 vulnerabilities (high/critical)

  • Maintainability: <5% code duplication

  • Coverage: >80% overall, >90% for critical paths

  • Complexity: Max cyclomatic complexity 10

Automated Dependency Updates

Dependabot Configuration

Code Quality Dashboard

Our Metrics

I track these in our team dashboard:

Weekly Report

We generate automated weekly reports:

Custom Git Hooks

Additional Local Checks

Automated Code Review Comments

Custom GitHub Action

Integration with IDEs

VS Code Configuration

Performance Optimization

Caching in CI

Parallel Test Execution

Monitoring and Alerting

Slack Integration

Conclusion

Automation is essential for maintaining code quality at scale. Key takeaways:

  1. ESLint + Prettier: Enforce consistent style and catch common errors

  2. TypeScript Strict Mode: Catch type errors early

  3. Pre-commit Hooks: Prevent bad code from being committed

  4. CI/CD Pipeline: Automated testing, linting, and security scanning

  5. Code Quality Metrics: Track and improve over time

  6. Custom Automation: Build tools specific to your needs

  1. Week 1: Set up ESLint + Prettier

  2. Week 2: Enable TypeScript strict mode (fix errors incrementally)

  3. Week 3: Add Jest tests for critical paths

  4. Week 4: Set up GitHub Actions CI

  5. Week 5: Add pre-commit hooks

  6. Week 6: Integrate SonarQube

  7. Week 7: Add security scanning

  8. Week 8: Set up metrics dashboard

Resources

This completes our Code Review and Refactoring 101 series. You now have the principles, processes, techniques, testing strategies, and automation tools to build and maintain high-quality TypeScript microservices.

Series Navigation: ← Part 4: Testing During Refactoring | Back to Series Overview β†’

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