Article 16: Performance & Caching in Spring Boot

1. Introduction

As applications grow, performance becomes critical.

Without caching:

• Same data is fetched repeatedly
• Databases get overloaded
• APIs become slow

Caching helps you:

• Improve response time
• Reduce database load
• Scale efficiently

Spring Boot provides simple yet powerful caching support.

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2. What Is Caching?

Caching means:

Storing frequently accessed data temporarily so it can be reused quickly.

Instead of:

Request → DB → Response

You get:

Request → Cache → Response

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3. When Should You Use Caching?

Use caching when:

• Data is read frequently
• Data changes infrequently
• Performance is critical

Avoid caching when:

• Data changes constantly
• Strong consistency is required

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4. Enabling Caching in Spring Boot

Add dependency:

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-cache</artifactId>
</dependency>

Enable caching:

@SpringBootApplication
@EnableCaching
public class DemoApplication {
}

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5. Using @Cacheable

@Service
public class UserService {

    @Cacheable("users")
    public User getUserById(Long id) {
        simulateSlowService();
        return userRepository.findById(id)
                .orElseThrow(() -> new RuntimeException("User not found"));
    }
}

First call → slow
Next calls → fast

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6. Cache Key Behavior

Default key:

• Method parameters

Example:

getUserById(1)

Cache key = 1

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7. Using @CacheEvict

When data changes, cache must be cleared.

@CacheEvict(value = "users", key = "#id")
public void deleteUser(Long id) {
    userRepository.deleteById(id);
}

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8. Using @CachePut

@CachePut(value = "users", key = "#user.id")
public User updateUser(User user) {
    return userRepository.save(user);
}

Updates cache without skipping method execution.

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9. Cache Providers

Spring Boot supports multiple cache providers:

Provider	Use Case
ConcurrentMap	Default (simple)
Caffeine	High performance
Redis	Distributed cache
EhCache	Legacy

For learning: ✔ Default cache is enough

For production: ✔ Redis / Caffeine

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10. Configuring Cache Provider (Example: Caffeine)

<dependency>
    <groupId>com.github.ben-manes.caffeine</groupId>
    <artifactId>caffeine</artifactId>
</dependency>

spring.cache.type=caffeine

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11. Common Caching Mistakes

❌ Forgetting to evict cache
❌ Caching mutable data
❌ Over-caching everything
❌ Ignoring TTL (time-to-live)

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12. Best Practices

✔ Cache at service layer
✔ Keep TTL reasonable
✔ Monitor cache hits/misses
✔ Combine caching with DB indexing

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13. What You Should Understand Before Moving On

You should now know:

• Why caching improves performance
• How @Cacheable works
• How to evict and update cache
• Which cache provider to choose

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14. What’s Next?

➡ Article 17: Testing Spring Boot Applications

• Unit tests
• Integration tests
• MockMvc & Mockito

Type Next when you’re ready.