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intermediate Phase · Backend Performance

Throughput

Maximize requests per second while maintaining correctness.

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Throughput

What Is Throughput?

Requests or data processed per unit time.

Throughput = Total Requests / Time
Example: 10,000 requests / 1 second = 10,000 RPS

Throughput vs Latency

Metric Measures
Latency Speed of one request
Throughput Volume of requests

Both matter: low latency + high throughput = ideal.

Key Points

  • Understanding Throughput 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 Throughput 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 Throughput

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

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

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

Identify and handle edge cases for Throughput. 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
Throughput Testing Strategy

Write a testing strategy for Throughput. 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. Throughput is?

Question 1 options

2. Low latency + high throughput =?

Question 2 options

3. What is a common mistake when implementing Throughput?

Question 3 options

Flashcards

Question

Throughput?

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Answer

Requests per second

Question

Ideal?

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Answer

Low latency + high throughput

Question

Throughput best practices

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Answer

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

Revision Notes

Key Takeaways

  • 1. Throughput = requests per second
  • 2. Latency and throughput are both important
  • 3. Improve throughput: parallel processing, caching

Interview Tips

  • • Measure throughput
  • • Know the difference from latency

Cheat Sheet

Throughput

  • Requests per second
  • vs Latency: volume vs speed
  • Ideal: low latency + high throughput