| name | spring-boot-cache |
| description | Provides patterns for implementing Spring Boot caching: configures Redis/Caffeine/EhCache providers with TTL and eviction policies, applies @Cacheable/@CacheEvict/@CachePut annotations, validates cache hit/miss behavior, and exposes metrics via Actuator. Use when adding caching to Spring Boot services, configuring cache expiration, evicting stale data, or diagnosing cache misses. |
| allowed-tools | Read, Write, Bash |
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
-
Add dependencies — spring-boot-starter-cache plus a provider:
- Caffeine:
caffeine starter
- Redis:
spring-boot-starter-data-redis
- Ehcache:
ehcache starter
-
Enable caching — annotate a @Configuration class with @EnableCaching
and define a CacheManager bean.
-
Annotate methods — @Cacheable for reads, @CachePut for writes,
@CacheEvict for deletions.
-
Configure TTL/eviction — set spring.cache.caffeine.spec,
spring.cache.redis.time-to-live, or spring.cache.ehcache.config.
-
Shape keys — use SpEL in key attributes; guard with
condition/unless for selective caching.
-
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) { ... }
Example 3: Cache Eviction
@CacheEvict(value = "users", key = "#id")
public void deleteUser(Long id) { ... }
For progressive scenarios (basic product cache, multilevel eviction, Redis
integration), load references/cache-examples.md.
Advanced Options
- Use JCache annotations (
@CacheResult, @CacheRemove) for providers favoring
JSR-107 interoperability; avoid mixing with Spring annotations on the same method.
- Cache reactive return types (
Mono, Flux) or CompletableFuture values.
- Apply HTTP
CacheControl headers when exposing cached responses via REST.
- Schedule periodic eviction with
@Scheduled for time-bound caches.
- Create a
CacheManagementService for programmatic cacheManager.getCache(name).
Troubleshooting
If cache misses persist after adding @Cacheable:
- Verify
@EnableCaching is present on a @Configuration class.
- Confirm the method is public and called from outside the class (Spring uses
proxies; self-invocation bypasses the cache).
- Validate SpEL key expressions resolve correctly.
- Confirm the cache manager bean is registered as
cacheManager or explicitly
referenced via cacheManager = "myCacheManager".
References
Best Practices
- Prefer constructor injection and immutable DTOs for cache entries.
- Separate cache names per aggregate (
users, orders) to simplify eviction.
- Log cache hits/misses only at debug; push metrics via Micrometer.
- Tune TTLs based on data staleness tolerance; document rationale in code.
- Guard caches storing PII or credentials with encryption or avoid caching.
- Align cache eviction with transactional boundaries to prevent dirty reads.
Constraints and Warnings
- Avoid caching mutable entities that depend on open persistence contexts.
- Do not mix Spring cache annotations with JCache annotations on the same method.
- Validate serialization compatibility when caching across service instances.
- Monitor memory footprint to prevent OOM with in-memory stores.
- Caffeine + Redis multi-level caches require publish/subscribe invalidation channels.
Related Skills