Intermediate Node.js Development Courseware (NJS200)

Module 1: Advanced Asynchronous Programming & Performance

1.1. Understanding Node.js architecture and the event loop
1.2. Event loop phases and execution order
1.3. Microtasks vs macrotasks (process.nextTick, Promises, setImmediate)
1.4. Performance best practices and avoiding event loop blocking
1.5. Profiling tools overview (Chrome DevTools, Performance API)

Lab 1: Async Iterators and Generators
- Building efficient async data pipelines
- Processing large datasets with lazy evaluation
- Memory-friendly streaming patterns
- Practical file processing examples

1.6. Async iterators and generators for data processing
1.7. When to use async iterators vs traditional approaches
1.8. Worker threads for CPU-intensive operations
1.9. Worker thread patterns (task queue, pipeline, pool)
1.10. Choosing between async iterators, worker threads, and child processes

Lab 2: Worker Threads Implementation
- Creating and managing worker threads
- Building a reusable worker pool
- Performance comparison: main thread vs workers
- Handling CPU-intensive calculations without blocking

Module 2: Authentication, Security & Database Integration

2.1. Authentication vs authorization concepts
2.2. Session-based authentication (traditional approach)
2.3. Token-based authentication with JWT
2.4. JWT structure, claims, and security best practices
2.5. OAuth2 flow and social authentication integration
2.6. Multi-factor authentication considerations

Lab 3: JWT Authentication System
- Implementing JWT-based authentication
- Creating login and registration endpoints
- Token refresh strategies
- Protected routes and middleware

2.7. Role-based access control (RBAC) implementation
2.8. Common security vulnerabilities (OWASP Top 10)
2.9. Injection prevention (SQL, NoSQL, command injection)
2.10. XSS and CSRF protection strategies
2.11. Security middleware (Helmet, rate limiting, input validation)
2.12. Environment and secrets management

Lab 4: MongoDB Transactions and Data Integrity
- Advanced MongoDB operations with transactions
- Implementing ACID transactions in NoSQL
- Connection pooling and performance optimization
- Data validation and error handling

Module 3: State Management, Caching & Real-Time Communication

3.1. Why caching matters for performance
3.2. Common caching patterns (cache-aside, write-through, write-behind)
3.3. Cache hierarchy (browser, CDN, application, database)
3.4. Redis data types and use cases
3.5. Implementing cache-aside pattern with Redis
3.6. Cache invalidation strategies

Lab 5: Redis Caching Implementation
- Setting up Redis for caching
- Implementing cache-aside pattern
- Performance testing with and without caching
- Cache expiration and invalidation strategies

Lab 6: Advanced Redis Usage
- Redis pub/sub for real-time features
- Sorted sets for leaderboards
- Lists for queues and activity feeds
- Advanced Redis patterns and use cases

3.7. Session management in distributed systems
3.8. Distributed session storage options
3.9. WebSockets vs HTTP polling
3.10. Real-time use cases (chat, notifications, dashboards)
3.11. Socket.io benefits and features
3.12. Room-based communication and broadcasting
3.13. Scaling WebSocket applications with Redis adapter

Lab 7: Real-Time Chat Application
- Building a Socket.io-based chat system
- Implementing rooms and private messaging
- User authentication with WebSockets
- Scaling with Redis pub/sub adapter

Module 4: Performance, Scalability & Testing

4.1. Performance goals and metrics
4.2. Profiling tools (Chrome DevTools, Clinic.js, 0x)
4.3. CPU profiling and flame graphs
4.4. Memory analysis and leak detection
4.5. Memory optimization patterns
4.6. Database query optimization (N+1 queries, indexing, connection pooling)

Lab 8: Application Performance Analysis & Optimization
- Establishing performance baselines
- CPU and memory profiling
- Identifying and fixing bottlenecks
- Implementing caching and optimization strategies
- Load testing and performance comparison

4.7. Why testing matters (ROI, confidence, documentation)
4.8. Testing pyramid (unit, integration, E2E)
4.9. Test-driven development (TDD) cycle
4.10. Testing best practices (AAA pattern, independence, repeatability)
4.11. Unit testing with Jest
4.12. API testing with Supertest
4.13. Testing async code and mocking external services
4.14. Test coverage goals and interpretation

Lab 9: Comprehensive Testing Suite
- Writing unit tests for business logic
- Integration tests for API endpoints
- Testing async operations and error handling
- Achieving meaningful test coverage
- TDD workflow implementation

Module 5: Deployment, DevOps & Production Monitoring

5.1. Modern deployment strategies (blue-green, canary, rolling)
5.2. Docker benefits and use cases
5.3. Docker vs VMs comparison
5.4. Writing production-ready Dockerfiles
5.5. Multi-stage builds for optimization
5.6. Docker security best practices
5.7. CI/CD pipeline fundamentals
5.8. GitHub Actions workflow implementation

Lab 10: Docker Deployment
- Creating optimized Dockerfiles
- Multi-stage build optimization
- Docker Compose for local development
- Container health checks and logging
- Deploying to cloud platforms (AWS ECS)

5.9. The three pillars of observability (metrics, logs, traces)
5.10. Logging best practices and log levels
5.11. Structured logging with Winston
5.12. Essential application metrics (RED and USE methods)
5.13. Health check endpoints (liveness, readiness)
5.14. Error tracking and alerting strategies
5.15. APM tools overview (New Relic, DataDog, Sentry)
5.16. Incident response and debugging production issues

Lab 11: Logging and Monitoring System
- Implementing structured logging
- Creating comprehensive health check endpoints
- Setting up Prometheus metrics collection
- Visualizing metrics with Grafana
- Error tracking and alerting
- Production debugging strategies