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beginner Phase · Backend Performance

Compression

Use gzip or brotli to reduce response payload size.

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Compression

Compression Benefits

Without: 1MB JSON response → 1MB transfer
With gzip: 1MB → ~200KB (80% reduction)

Enable in Spring Boot

server.compression.enabled=true
server.compression.mime-types=application/json,text/html
server.compression.min-response-size=1024

Nginx Compression

gzip on;
gzip_types application/json text/html;

Key Points

  • Understanding Compression is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Best Practices

Key Principles

  1. Follow SOLID principles
  2. Write clean, readable code
  3. Test thoroughly
  4. Document decisions
  5. Monitor in production

Implementation

  • Start simple, refactor as needed
  • Use established patterns
  • Consider trade-offs
  • Review with peers

Continuous Improvement

  • Learn from incidents
  • Update documentation
  • Share knowledge
  • Mentor others

Key Points

  • Understanding Compression is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0 / 3 solved
Implement Compression

Design and implement a solution for Compression in a backend system. Consider scalability, error handling, and production readiness.

Solution 
// Compression implementation
// Key aspects: validation, error handling, logging, testing

public class Compression {
    // Production-ready implementation
}
Compression Edge Cases

Identify and handle edge cases for Compression. What happens under high load, with invalid input, or during failures?

Solution 
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotency
Compression Testing Strategy

Write a testing strategy for Compression. Include unit tests, integration tests, and performance tests.

Solution 
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. Compression reduces?

Question 1 options

2. Typical JSON compression ratio?

Question 2 options

3. What is a common mistake when implementing Compression?

Question 3 options

Flashcards

Question

Compression reduces?

Click to reveal answer

Answer

Response body size

Question

JSON compression ratio?

Click to reveal answer

Answer

70-80% with gzip

Question

Compression best practices

Click to reveal answer

Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1. Compression reduces response size by 70-80%
  • 2. Enable in Spring Boot or Nginx
  • 3. Compress JSON, HTML, CSS, JS
  • 4. Trade: small CPU cost for large bandwidth savings

Interview Tips

  • • Enable compression
  • • Measure benefits

Cheat Sheet

Compression

  • Reduces response size 70-80%
  • Enable: server.compression.enabled=true
  • Trade: small CPU cost
  • Compress: JSON, HTML, CSS, JS