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intermediate Phase · Backend Performance

Caching for Performance

Use caching to eliminate redundant database queries.

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Cache Performance

Cache Metrics

Metric Target
Hit rate > 80%
Miss rate < 20%
Eviction rate Low
Memory usage < 80%

Improving Hit Rate

  • Right TTL (not too short)
  • Right key design
  • Pre-warm cache
  • Cache frequent queries

Key Points

  • Understanding Caching Performance 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

Performance Optimization

Areas

  • Database: Indexes, queries, connection pooling
  • Caching: Multi-level, appropriate TTL
  • Network: Compression, CDN, HTTP/2
  • Code: Profiling, async, batch

Measurement

  • Load testing
  • Profiling
  • APM tools
  • Real user monitoring

Best Practices

  • Set performance budgets
  • Monitor in production
  • Optimize hot paths
  • Use appropriate data structures

Key Points

  • Understanding Caching Performance 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 / 2 solved
Caching Performance Edge Cases

Identify and handle edge cases for Caching Performance. 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
Caching Performance Testing Strategy

Write a testing strategy for Caching Performance. 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. Good cache hit rate?

Question 1 options

2. Low hit rate fix?

Question 2 options

3. What is a common mistake when implementing Caching Performance?

Question 3 options

Flashcards

Question

Target hit rate?

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Answer

> 80%

Question

Low hit rate fixes?

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Answer

Adjust TTL, pre-warm, optimize keys

Question

Caching Performance 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. Target > 80% hit rate
  • 2. Monitor: hit rate, miss rate, eviction rate
  • 3. Improve: right TTL, pre-warm, key design

Interview Tips

  • • Measure cache performance
  • • Improve hit rate

Cheat Sheet

Cache Performance

  • Hit rate: > 80%
  • Monitor: hit, miss, eviction rates
  • Improve: TTL, pre-warm, key design