Redis Caching in Spring Boot

A local cache is fast but isolated — each instance holds its own copy, and evictions on one node do not reach the others. Redis solves this by giving every instance a single shared cache with server-side expiry.

Wire up Redis as the cache manager

Add spring-boot-starter-data-redis and configure a RedisCacheManager. Setting a default TTL means entries expire even if you forget to evict them.

@Configuration
@EnableCaching
public class RedisCacheConfig {
 
    @Bean
    public RedisCacheManager cacheManager(RedisConnectionFactory factory) {
        RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
            .entryTtl(Duration.ofMinutes(15))
            .serializeValuesWith(SerializationPair.fromSerializer(
                new GenericJackson2JsonRedisSerializer()));
 
        return RedisCacheManager.builder(factory)
            .cacheDefaults(config)
            .build();
    }
}

The annotations don't change

The beauty of the cache abstraction is that switching backends is a config change. Your service code stays identical to a local cache setup.

@Service
public class CatalogService {
 
    @Cacheable(value = "catalog", key = "#category")
    public List<Product> byCategory(String category) {
        return repository.findByCategory(category);
    }
}

Point Spring at your Redis

spring.data.redis.host=localhost
spring.data.redis.port=6379
spring.data.redis.timeout=2s

Takeaways

• Redis turns caching from per-instance to cluster-wide.
• Always set a default TTL as a safety net against stale data.
• Use a JSON serializer so cached values stay human-readable and portable.

Watch your serialization format: changing a DTO shape can make old cached entries fail to deserialize, so version your keys when models evolve.