spring-boot-cache

Spring Boot Cache Abstraction

Overview

6-step workflow for enabling cache abstraction, configuring providers (Caffeine, Redis, Ehcache), annotating service methods, and validating behavior in Spring Boot 3.5+ applications. Apply @Cacheable for reads, @CachePut for writes, @CacheEvict for deletions. Configure TTL/eviction policies and expose metrics via Actuator.

When to Use

• Add @Cacheable, @CachePut, or @CacheEvict to service methods.
• Configure Caffeine, Redis, or Ehcache with TTL and capacity policies.
• Implement eviction strategies for stale data.
• Diagnose cache misses or invalidation issues.
• Expose hit/miss metrics via Actuator or Micrometer.

Instructions

1. Add dependencies — spring-boot-starter-cache plus a provider:

   • Caffeine: caffeine starter
   • Redis: spring-boot-starter-data-redis
   • Ehcache: ehcache starter

2. Enable caching — annotate a @Configuration class with @EnableCaching and define a CacheManager bean.

3. Annotate methods — @Cacheable for reads, @CachePut for writes, @CacheEvict for deletions.

4. Configure TTL/eviction — set spring.cache.caffeine.spec, spring.cache.redis.time-to-live, or spring.cache.ehcache.config.

5. Shape keys — use SpEL in key attributes; guard with condition/unless for selective caching.

6. Validate setup — run integration test to confirm cache hit on second call; check GET /actuator/caches to verify cache manager registration; query GET /actuator/metrics/cache.gets for hit/miss ratios.

Examples

Example 1: Basic @Cacheable Usage

@Service
@CacheConfig(cacheNames = "users")
class UserService {

    @Cacheable(key = "#id", unless = "#result == null")
    User findUser(Long id) { ... }
}

First call → cache miss, repository invoked
Second call → cache hit, repository skipped

Example 2: Conditional Caching with SpEL

@Cacheable(value = "products", key = "#id", condition = "#price > 100")
public Product getProduct(Long id, BigDecimal price) { ... }

// Only expensive products are cached