Spring Cache with Claude Code: Faster Dev Cycles

Ever find yourself repeatedly hitting the database or making slow external API calls during development, even for data that shouldn’t change often? This is a classic scenario where Spring’s caching abstraction shines. However, configuring and tuning these caches can sometimes feel like a black box. How do you quickly experiment with different caching strategies or verify if your cache is being hit as expected without lengthy redeployments or complex debugging setups?

Claude Code can be an invaluable partner here. Imagine you’re working on a Spring Boot application using Spring Cache and you want to understand the nuances of a particular @Cacheable annotation. You can ask Claude Code to generate example configurations, explain the behavior of different cache providers (like Caffeine or Redis), or even help you write unit tests to verify cache hits and misses. This allows for rapid iteration and learning, directly impacting your development velocity.

Let’s say you’ve just added a @Cacheable annotation to a service method and want to quickly generate a JUnit test that verifies it’s working. You can provide Claude Code with your service class and the specific method, and it can help generate the necessary @SpringBootTest setup, mock CacheManager, and assertions. This eliminates the boilerplate and lets you focus on the caching logic itself.

// Assume this is your service class with a @Cacheable annotation
// @Cacheable("myCache")
// public MyData findDataById(String id) { ... }

// Prompt to Claude Code:
// "Generate a JUnit test for a Spring Boot service that uses @Cacheable('myCache').
// The test should verify that the underlying method is called only once when the data is requested multiple times."

// Claude Code might respond with something like this (adapted for demonstration):
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.cache.CacheManager;
import org.springframework.cache.annotation.EnableCaching;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.stereotype.Service;

import static org.mockito.Mockito.*;

@SpringBootTest(classes = {MyServiceTest.TestConfig.class, MyService.class})
public class MyServiceTest {

    @Autowired
    private MyService myService;

    @Autowired
    private CacheManager cacheManager; // Auto-configured or from TestConfig

    @Test
    void testCacheableAnnotation() {
        String dataId = "test-123";
        MyData data1 = myService.findDataById(dataId);
        MyData data2 = myService.findDataById(dataId); // Should be served from cache

        // Verify the underlying method was called only once
        // For this, we'd typically mock the actual data retrieval logic
        // For simplicity, let's assume findDataById's internal logic can be spied on.
        // A more robust test would involve mocking the repository.

        // Example assertion (requires spying on the service or mocking repository)
        // If spying on myService, you'd check if findDataById was called exactly once.
        // If mocking the repository, you'd check if repository.findById was called exactly once.

        // A simpler check: verify data consistency
        assertNotNull(data1);
        assertNotNull(data2);
        assertEquals(data1.getId(), data2.getId());

        // Verify cache hit (specific to cache implementation and testing setup)
        // For Caffeine, you might check stats if configured for it.
        // For a generic check, observe behavior.
    }

    @Configuration
    @EnableCaching
    static class TestConfig {
        // Configure a simple cache manager for testing if not auto-configured appropriately
        // e.g., using Caffeine or ConcurrentMapCacheManager
        @Bean
        public org.springframework.cache.CacheManager cacheManager() {
            return new org.springframework.cache.concurrent.ConcurrentMapCacheManager("myCache");
        }

        @Service
        public static class MyService {
            private int callCount = 0; // To demonstrate method call counting

            // Simulate data retrieval
            public MyData findDataById(String id) {
                callCount++;
                System.out.println(">>> findDataById called: " + callCount + " times for id: " + id);
                return new MyData(id, "Some Data");
            }

            public int getCallCount() {
                return callCount;
            }
        }

        public static class MyData {
            private String id;
            private String value;

            public MyData(String id, String value) {
                this.id = id;
                this.value = value;
            }

            public String getId() { return id; }
            public String getValue() { return value; }
        }
    }
}

Try it: Paste the prompt asking for a JUnit test for a @Cacheable method into Claude Code and adapt the generated code to your specific service and cache configuration.

By integrating Claude Code into your daily workflow for Spring Cache, you can dramatically reduce the time spent on understanding, configuring, and testing caching strategies. This allows you to build more performant applications faster, focusing on the core business logic rather than getting bogged down in intricate infrastructure details.