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Cache Eviction

Understand eviction policies when cache is full.

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Cache Eviction

When Cache Is Full

Cache: [A][B][C][D][E]  (full)
New item F arrives
Eviction needed → Remove one item to make room

Eviction Policies

Policy Description
LRU Least Recently Used
LFU Least Frequently Used
FIFO First In First Out
Random Random eviction

Key Points

  • Understanding Cache Eviction 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 Eviction 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

0/3solved
Implement Cache Eviction

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

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

public class CacheEviction {
    // Production-ready implementation
}
Cache Eviction Edge Cases

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

Write a testing strategy for Cache Eviction. 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. Most common eviction policy?

Question 1 options

2. LFU evicts?

Question 2 options

3. What is the primary purpose of Cache Eviction?

Question 3 options

4. What is a common mistake when implementing Cache Eviction?

Question 4 options

Flashcards

Question

Most common eviction?

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Answer

LRU (Least Recently Used)

Question

LFU evicts?

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Answer

Least frequently accessed

Question

What is Cache Eviction?

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Answer

Cache Eviction is a key concept in backend development.

Question

When to use Cache Eviction?

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Answer

Use Cache Eviction when building production systems that require reliability, scalability, and maintainability.

Question

Cache Eviction 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.Eviction: remove items when cache is full
  • 2.LRU: most common, evicts least recently used
  • 3.LFU: evicts least frequently used
  • 4.FIFO: evicts oldest

Interview Tips

  • •Know eviction policies
  • •Choose the right one

Cheat Sheet

Cache Eviction

  • LRU: least recently used (most common)
  • LFU: least frequently used
  • FIFO: first in first out
  • Random: random eviction