PluginBench
Skill
Review
Audit score 70

spring-boot-cache

giuseppe-trisciuoglio/developer-kit

Configure Spring Boot caching with Redis/Caffeine/EhCache, TTL policies, and @Cacheable/@CacheEvict annotations.

What is spring-boot-cache?

Implements cache abstraction patterns for Spring Boot 3.5+ services using configurable providers (Caffeine, Redis, Ehcache) with TTL and eviction policies. Use when adding caching to reduce database load, configuring cache expiration, evicting stale data, or diagnosing cache behavior via Actuator metrics.

  • Configure Caffeine, Redis, or Ehcache cache managers with TTL and capacity policies
  • Apply @Cacheable, @CachePut, and @CacheEvict annotations to service methods
  • Shape cache keys using SpEL expressions with conditional caching via condition/unless
  • Validate cache hits and misses through integration tests and Actuator endpoints
  • Expose cache metrics (hit/miss ratios) via /actuator/caches and /actuator/metrics/cache.gets
  • Implement eviction strategies and programmatic cache management

How to install spring-boot-cache

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill spring-boot-cache
Prerequisites
  • Spring Boot 3.5 or later
  • spring-boot-starter-cache dependency
  • One cache provider: caffeine, spring-boot-starter-data-redis, or ehcache starter
  • Spring Actuator (optional, for metrics exposure)
Claude Code
Cursor
Windsurf
Cline

How to use spring-boot-cache

  1. 1.Add spring-boot-starter-cache and your chosen provider (Caffeine/Redis/Ehcache) to pom.xml or build.gradle
  2. 2.Create a @Configuration class annotated with @EnableCaching and define a CacheManager bean
  3. 3.Annotate service methods with @Cacheable (reads), @CachePut (writes), or @CacheEvict (deletions)
  4. 4.Configure TTL and eviction policies via spring.cache.caffeine.spec, spring.cache.redis.time-to-live, or spring.cache.ehcache.config
  5. 5.Use SpEL in key attributes and condition/unless parameters to shape cache behavior
  6. 6.Run integration tests to verify cache hits on repeated calls and check /actuator/caches and /actuator/metrics/cache.gets endpoints

Use cases

Good for
  • Add caching to frequently-accessed data (users, products) to reduce database queries
  • Configure multi-level caching (Caffeine + Redis) for distributed Spring Boot services
  • Implement selective caching based on data attributes (e.g., cache only expensive products)
  • Diagnose cache misses and validate cache invalidation during updates or deletes
  • Monitor cache performance and memory usage in production via Actuator metrics
Who it's for
  • Spring Boot backend developers building high-throughput services
  • Architects designing caching strategies for microservices
  • DevOps engineers tuning cache configuration and monitoring metrics
  • QA engineers validating cache behavior in integration tests

spring-boot-cache FAQ

What's the difference between @Cacheable, @CachePut, and @CacheEvict?

@Cacheable checks cache first and only invokes the method on miss; @CachePut always invokes the method and updates the cache; @CacheEvict removes entries from the cache.

Why is my cache not working even though I added @Cacheable?

Ensure @EnableCaching is on a @Configuration class, the method is public, and it's called from outside the class (Spring uses proxies; self-invocation bypasses caching). Verify the cache manager bean is registered as 'cacheManager'.

Can I cache reactive types like Mono or Flux?

Yes, Spring Boot cache abstraction supports caching reactive return types and CompletableFuture values.

How do I monitor cache performance in production?

Enable Spring Actuator and query /actuator/caches for cache manager registration and /actuator/metrics/cache.gets for hit/miss ratios; push metrics via Micrometer.

Should I mix Spring cache annotations with JCache (@CacheResult)?

No, avoid mixing Spring and JCache annotations on the same method; choose one approach per method for clarity and compatibility.

Full instructions (SKILL.md)

Source of truth, from giuseppe-trisciuoglio/developer-kit.


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

  1. Add dependenciesspring-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

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:

  1. Verify @EnableCaching is present on a @Configuration class.
  2. Confirm the method is public and called from outside the class (Spring uses proxies; self-invocation bypasses the cache).
  3. Validate SpEL key expressions resolve correctly.
  4. 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

  • ../spring-boot-rest-api-standards
  • ../spring-boot-test-patterns
  • ../unit-test-caching