Caching REST Services with Redis

Author: Brian Sam-Bodden


Learn how easy it is to use Redis as a cache in your Spring applications


In this lesson, students will learn:

  • The basics of Caching RESTful Services
  • How to configure the Spring Data Redis RedisCacheManager using RedisCacheConfiguration
  • How to use the @Cacheable annotation to mark a REST controller response as cacheable If you get stuck:
  • The progress made in this lesson is available on the redi2read github repository at

Spring-Redis Caching Recipe#

To implement caching in our Spring Boot application:

  • Configure the Redis cache manager
  • Enable application-wide caching with the @EnableCaching annotation

In the main application file (src/main/java/com/redislabs/edu/redi2read/, add the cacheManager method as shown:

public class Redi2readApplication {
// ...
public RedisCacheManager cacheManager(RedisConnectionFactory connectionFactory) {
RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig() //
.prefixCacheNameWith(this.getClass().getPackageName() + ".") //
.entryTtl(Duration.ofHours(1)) //
return RedisCacheManager.builder(connectionFactory) //
.cacheDefaults(config) //
// ...

The cacheManager method takes an instance of the RedisConnectionFactory. In it we will configure our cache to use a Redis key prefix equals to our application’s main package plus a period, that is We also set the TTL or “Time to Live” of our cache entries to 1 hour and make sure that we don’t cache nulls. At the class level, we also use the annotation @EnableCaching to globally enable caching for our applications. The changes above will need the import statements shown below:

import org.springframework.cache.annotation.EnableCaching;
import java.time.Duration;

Using the @Cacheable annotation#

In the context of a RESTful service, caching makes sense at the handoff between the application and the HTTP protocol. It seems almost silly to think about caching anything in an application powered by Redis, but complex business logic touching many data repositories and performing intense calculations can add to your response’s latency. The ideal place to perform this caching is at the controller level. For example, let’s say that we wanted to cache the responses of our book searches in the BookController. We could simple add the @Cacheable annotation as follows:

public SearchResults<String,String> search(@RequestParam(name="q")String query) {
RediSearchCommands<String, String> commands = searchConnection.sync();
SearchResults<String, String> results =, query);
return results;

Spring will now use Redis to create keys under the prefix to store cache entries for the search method. There is no need to perform cache maintenance yourself. Spring will intercept the request and check the cache; in the case of a cache hit, it will return its value. Otherwise, in case of a miss, it will store the cache’s search method’s return value, allowing the method to execute as if there was no cache at all. If we try the request http://localhost:8080/api/books/search?q=java:

curl --location --request GET 'http://localhost:8080/api/books/search?q=java'

On the first request we get a 28 ms response time:

PostMan Request 1

Subsequent responses return in the range of 8 ms to 10 ms consistently:

PostMan Request 2