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Spring Boot 4 Complete Guide · Lesson

Distributed Caching with Redis and TTLs

Share cache state across instances using Redis as a centralized cache backend with serialization control.

Why Distributed Caching?

Caffeine is a brilliant in-process cache: ultra-fast, but each application instance keeps its own private copy. The moment you scale horizontally to several pods, those copies drift apart.

  • Instance A evicts a user; instance B still serves the stale entry.
  • A cache warm-up on one node helps nobody else.
  • Total memory cost grows linearly with replica count.

A distributed cache solves this by putting cache state in a shared backend that every instance reads and writes. In Spring Boot, Redis is the most common choice for this role.

Adding the Redis Cache Starter

Spring Boot's caching abstraction is backend-agnostic. To swap Caffeine for Redis you mostly change dependencies and a property — your @Cacheable annotations stay the same.

Pull in the Redis starter and the cache abstraction:

  • spring-boot-starter-data-redis provides the connection and RedisCacheManager.
  • spring-boot-starter-cache enables the @Cacheable/@CacheEvict annotations.

Then declare Redis as the cache type so Boot auto-configures a RedisCacheManager instead of a simple map.

<!-- pom.xml -->
<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-data-redis</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-cache</artifactId>
    </dependency>
</dependencies>

All lessons in this course

  1. The Spring Cache Abstraction Fundamentals
  2. In-Memory Caching with Caffeine Tuning
  3. Distributed Caching with Redis and TTLs
  4. Cache Stampede, Invalidation, and Consistency
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