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
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- 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
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- Documentation: Keep docs updated with code changes
Practice Problems
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
}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, idempotencyWrite 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 injectionQuiz
1. Cache invalidation removes?
2. TTL-based invalidation does?
3. What is the primary purpose of Cache Invalidation?
4. What is a common mistake when implementing Cache Invalidation?
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
What is Cache Invalidation?
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Answer
Cache Invalidation is a key concept in backend development.
Question
When to use Cache Invalidation?
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Answer
Use Cache Invalidation when building production systems that require reliability, scalability, and maintainability.
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