How to Prevent Memory Leaks in a Java 17 Spring Boot Application with Scheduled Tasks?
I'm deploying to production and I'm currently developing a Spring Boot application using Java 17, and I've implemented scheduled tasks using the `@Scheduled` annotation to perform background operations. However, I've noticed that as my application runs, it consumes an increasing amount of memory, leading to performance degradation over time. I suspect this might be related to how I'm managing resources within these scheduled tasks. Here's a simplified version of my code: ```java import org.springframework.scheduling.annotation.Scheduled; import org.springframework.stereotype.Component; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; @Component public class MyScheduledTasks { private final ExecutorService executorService = Executors.newFixedThreadPool(5); @Scheduled(fixedRate = 5000) public void performTask() { executorService.submit(() -> { try { // Simulated task processing Thread.sleep(3000); System.out.println("Task completed"); } catch (InterruptedException e) { Thread.currentThread().interrupt(); } }); } } ``` In this example, I am using an `ExecutorService` to handle the tasks. However, I noticed that the memory usage continues to grow even when the tasks complete. I've also tried calling `executorService.shutdown()` to release resources, but it seems that the threads are not being properly cleaned up, and I still experience memory leaks. I've considered using `ScheduledExecutorService`, but I'm unsure if it would help with the memory management of the scheduled tasks. Additionally, I want to ensure that I don’t lose scheduled tasks if the application restarts. Any advice or best practices on how to manage these scheduled tasks effectively without causing memory leaks would be greatly appreciated. I'm also interested in any tools or techniques for monitoring memory usage in a Spring Boot application to diagnose this issue further. My development environment is Linux. Any suggestions would be helpful. Has anyone else encountered this?