Introduction

Spring Boot simplifies application development, but improper dependency injection, excessive singleton bean retention, unoptimized JDBC connections, and thread pool mismanagement can lead to severe performance issues. Common pitfalls include keeping unnecessary stateful singleton beans, failing to close database connections, using default thread pool settings that cannot handle high loads, and failing to monitor application memory usage. These issues become especially problematic in high-traffic applications where efficiency and scalability are critical. This article explores Spring Boot performance bottlenecks, debugging techniques, and best practices for optimization.

Common Causes of Memory Leaks and Performance Issues in Spring Boot

1. Singleton Bean Mismanagement Leading to Memory Leaks

Using stateful singleton beans causes memory retention issues.

Problematic Scenario

@Component
public class StatefulBean {
    private List cache = new ArrayList<>();
    
    public void addData(String data) {
        cache.add(data);
    }
}

The list keeps accumulating data, leading to memory leaks.

Solution: Use `@Scope("prototype")` for Stateful Beans

@Component
@Scope("prototype")
public class StatefulBean {
    private List cache = new ArrayList<>();
}

Using `prototype` scope ensures new instances are created per request.

2. Inefficient Database Connection Handling Causing Performance Bottlenecks

Failing to properly close database connections leads to connection pool exhaustion.

Problematic Scenario

@Service
public class UserService {
    @Autowired
    private DataSource dataSource;
    
    public void fetchUsers() throws SQLException {
        Connection conn = dataSource.getConnection();
        Statement stmt = conn.createStatement();
        ResultSet rs = stmt.executeQuery("SELECT * FROM users");
    }
}

The connection is never closed, leading to resource exhaustion.

Solution: Use Try-With-Resources for Connection Management

public void fetchUsers() throws SQLException {
    try (Connection conn = dataSource.getConnection();
         Statement stmt = conn.createStatement();
         ResultSet rs = stmt.executeQuery("SELECT * FROM users")) {
        while (rs.next()) {
            System.out.println(rs.getString("name"));
        }
    }
}

Using try-with-resources ensures connections are automatically closed.

3. Unoptimized Thread Pool Leading to High Latency

Spring Boot’s default thread pool settings may not handle high request loads efficiently.

Problematic Scenario

@Bean
public Executor taskExecutor() {
    return Executors.newFixedThreadPool(5);
}

A fixed pool of 5 threads may become overloaded under high traffic.

Solution: Configure an Optimized Thread Pool

@Bean
public TaskExecutor taskExecutor() {
    ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
    executor.setCorePoolSize(10);
    executor.setMaxPoolSize(50);
    executor.setQueueCapacity(100);
    executor.initialize();
    return executor;
}

Configuring an appropriate thread pool improves performance under high load.

4. Excessive Hibernate Cache Retention Causing High Memory Usage

Improper caching configuration leads to excessive object retention in memory.

Problematic Scenario

spring.jpa.properties.hibernate.cache.use_second_level_cache=true

Using the second-level cache without expiration can lead to excessive memory usage.

Solution: Configure Cache Expiration Policies

spring.jpa.properties.hibernate.cache.use_second_level_cache=true
spring.jpa.properties.hibernate.cache.region.factory_class=org.hibernate.cache.jcache.JCacheRegionFactory
spring.jpa.properties.hibernate.javax.cache.provider=org.ehcache.jsr107.EhcacheCachingProvider

Using proper caching mechanisms prevents unnecessary memory retention.

5. Improperly Configured Garbage Collection Causing Application Pauses

Using default JVM GC settings may lead to inefficient memory management.

Problematic Scenario

java -Xms512m -Xmx512m -jar app.jar

Low heap allocation can cause frequent GC pauses.

Solution: Optimize JVM Garbage Collection

java -Xms2g -Xmx4g -XX:+UseG1GC -jar app.jar

Using G1GC optimizes memory management for large-scale applications.

Best Practices for Optimizing Spring Boot Performance

1. Use `@Scope("prototype")` for Stateful Beans

Prevent memory leaks by avoiding long-lived singleton beans with mutable state.

2. Use Try-With-Resources for Database Connections

Ensure database connections are closed to prevent connection pool exhaustion.

3. Optimize Thread Pool Settings

Use `ThreadPoolTaskExecutor` to fine-tune concurrency management.

4. Configure Hibernate Caching Properly

Limit cache size and implement expiration policies to avoid excessive memory usage.

5. Tune JVM Garbage Collection

Use G1GC and allocate sufficient heap memory for optimal performance.

Conclusion

Spring Boot applications can suffer from memory leaks and performance bottlenecks due to improper bean management, inefficient database connections, unoptimized thread pools, and poor garbage collection settings. By using `@Scope("prototype")` for stateful beans, properly managing database connections, fine-tuning thread pools, configuring Hibernate caching, and optimizing JVM settings, developers can significantly improve Spring Boot application performance. Regular monitoring with Spring Boot Actuator and profiling tools like VisualVM helps detect and resolve performance issues proactively.