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intermediatePhase ·

Cache-Aside

The most common caching pattern: application manages cache explicitly.

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Cache-Aside

Cache-Aside Flow

1. Check cache for key
2. If HIT → return cached value
3. If MISS → query DB, store in cache, return
4. On write → invalidate cache

Implementation

public Product getProduct(Long id) {
    String key = "product:" + id;
    Product cached = redis.get(key, Product.class);
    if (cached != null) return cached;

    Product product = productRepository.findById(id).orElseThrow();
    redis.set(key, product, Duration.ofMinutes(30));
    return product;
}

Invalidation

public void updateProduct(Long id, UpdateRequest req) {
    Product product = productRepository.save(...);
    redis.delete("product:" + id);  // Invalidate
}

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-Aside Pattern 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-Aside Pattern

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

Solution
// Cache-Aside Pattern implementation
// Key aspects: validation, error handling, logging, testing

public class CacheAsidePattern {
    // Production-ready implementation
}
Cache-Aside Pattern Edge Cases

Identify and handle edge cases for Cache-Aside Pattern. 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-Aside Pattern Testing Strategy

Write a testing strategy for Cache-Aside Pattern. 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-aside on write does what?

Question 1 options

2. Cache-aside flow for read?

Question 2 options

3. What is the primary purpose of Cache-Aside Pattern?

Question 3 options

4. What is a common mistake when implementing Cache-Aside Pattern?

Question 4 options

Flashcards

Question

Cache-aside write action?

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Answer

Invalidate (delete) cache entry

Question

Cache-aside read flow?

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Answer

Check cache → miss → query DB → cache result

Question

What is Cache-Aside Pattern?

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Answer

Cache-Aside Pattern is a key concept in backend development.

Question

When to use Cache-Aside Pattern?

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Answer

Use Cache-Aside Pattern when building production systems that require reliability, scalability, and maintainability.

Question

Cache-Aside Pattern 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-Aside: check cache, miss → DB → cache
  • 2.Invalidate cache on write
  • 3.Most common caching pattern
  • 4.Simple to implement

Interview Tips

  • •Implement cache-aside
  • •Know invalidation strategies

Cheat Sheet

Cache-Aside

  • Read: cache → miss → DB → cache
  • Write: invalidate cache
  • Most common pattern
  • Simple, effective