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advanced Phase · Caching

Cache Invalidation

The hardest problem in computer science - when and how to invalidate cache.

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Cache Invalidation

Why Invalidate?

Stale data scenario:
1. Product price = $100 (cached)
2. Price updated to $150 in DB
3. Cache still shows $100 (stale!)
4. Must invalidate cache

Invalidation Strategies

Strategy Description
TTL Auto-expire after time
Event-driven Invalidate on DB change
Manual Explicit delete
Version Include version in key

Key Points

  • Understanding Cache Invalidation 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

Cache Best Practices

Strategies

  • Cache-Aside: Application manages cache
  • Write-Through: Sync write to cache and DB
  • Write-Behind: Async write to DB
  • Read-Through: Cache loads from DB

Invalidation

  • Time-based TTL
  • Event-based invalidation
  • Version-based keys
  • Tag-based grouping

Monitoring

  • Hit rate > 80% is good
  • Monitor eviction rates
  • Track cache size
  • Alert on anomalies

Key Points

  • Understanding Cache Invalidation 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 Cache Invalidation

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

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

public class CacheInvalidation {
    // Production-ready implementation
}
Cache Invalidation Edge Cases

Identify and handle edge cases for Cache Invalidation. 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
Cache Invalidation Testing Strategy

Write a testing strategy for Cache Invalidation. 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. Cache invalidation removes?

Question 1 options

2. TTL-based invalidation does?

Question 2 options

3. What is a common mistake when implementing Cache Invalidation?

Question 3 options

Flashcards

Question

Cache invalidation purpose?

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Answer

Remove stale entries

Question

TTL-based?

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Answer

Auto-expires entries after time

Question

Cache Invalidation 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. Cache invalidation prevents stale data
  • 2. TTL: auto-expire after time
  • 3. Event-driven: invalidate on DB change
  • 4. One of the two hard problems in CS

Interview Tips

  • • Know invalidation strategies
  • • Handle stale data

Cheat Sheet

Cache Invalidation

  • TTL: auto-expire
  • Event-driven: on DB change
  • Manual: explicit delete
  • One of CS hardest problems