How to Diagnose Synchronization Overhead in Java Services on ServiceNow MID server

Is your ServiceNow MID Server experiencing slow performance due to synchronization overhead in Java services? 🤔 The issue might be related to inefficient synchronization mechanisms. In this article, we’ll guide you through diagnosing synchronization overhead and how it affects your ServiceNow environment. Discover effective methods to enhance performance and reliability. Ready to get started? Let’s dive in!

Addressing Synchronization Overhead in Java Services for Improved Performance

Synchronization overhead in Java services occurs when multiple threads need to coordinate access to shared resources, leading to delays. This overhead arises because threads often have to wait for locks to be released before they can proceed, which slows down the execution. Inefficient or excessive synchronization can cause significant performance bottlenecks, as threads spend more time waiting than performing useful work. This wait time can lead to increased CPU utilization and reduce the overall throughput of applications. Additionally, poor synchronization practices can result in deadlocks, where threads get stuck waiting indefinitely. Addressing these issues typically involves optimizing the use of locks and minimizing the critical sections where synchronization is necessary.

How Synchronization Overhead affects Your ServiceNow MID Server

1. Degraded Performance: Synchronization overhead can significantly degrade MID Server performance. Excessive locking mechanisms cause the JVM to spend more time managing threads, resulting in slower operations.
2. Frequent Freezes and Timeouts: With heavy synchronization, the MID Server is more prone to application freezes and timeouts. This leads to delayed responses and potential missed requests, impacting service reliability.
3. Extended Response Times: As synchronization overhead increases, the time it takes for your MID Server to process requests also increases. This results in a slower user experience and delays in executing critical tasks.
4. Increased Resource Consumption: Synchronization overhead leads to higher CPU usage as threads compete for locks. The JVM must work harder to manage thread contention, putting an additional load on the system.
5. Challenging Diagnostics: Identifying and troubleshooting synchronization issues can be difficult without detailed logs and in-depth analysis. These issues often remain hidden until significant performance degradation occurs.
6. Scalability Constraints: Poor management of synchronization overhead hinders your application’s ability to scale effectively. Handling more requests or larger data volumes becomes increasingly challenging.

Diagnosing Synchronization Overhead in Java Services on ServiceNow

This program defines two shared resources and two tasks that attempt to lock these resources in different orders. It starts two threads, each running one of the tasks. Each task includes a delay to simulate processing time while holding a resource lock. This setup induces a deadlock situation where each thread waits for a resource locked by the other thread. Consequently, the program demonstrates synchronization overhead due to deadlocked threads waiting indefinitely.

public class SynchronizationOverheadSimulator {

    // Resources
    private static final Object resource1 = new Object();
    private static final Object resource2 = new Object();

    public static void main(String[] args) {
        // Thread 1
        Thread thread1 = new Thread(new Task1());
        // Thread 2
        Thread thread2 = new Thread(new Task2());

        // Start the threads
        thread1.start();
        thread2.start();
    }

    static class Task1 implements Runnable {
        @Override
        public void run() {
            synchronized (resource1) {
                System.out.println("Task1 locked resource1");

                try {
                    Thread.sleep(100); // Simulate some work with resource1
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                }

                System.out.println("Task1 waiting to lock resource2");
                synchronized (resource2) {
                    // This block will never be reached because of deadlock
                    System.out.println("Task1 locked resource2");
                }
            }
        }
    }

    static class Task2 implements Runnable {
        @Override
        public void run() {
            synchronized (resource2) {
                System.out.println("Task2 locked resource2");

                try {
                    Thread.sleep(100); // Simulate some work with resource2
                } catch (InterruptedException e) {
                    Thread.currentThread().interrupt();
                }

                System.out.println("Task2 waiting to lock resource1");
                synchronized (resource1) {
                    // This block will never be reached because of deadlock
                    System.out.println("Task2 locked resource1");
                }
            }
        }
    }
}

Here’s our observation: 

1. The program defines two shared resources, resource1 and resource2.
2. It creates two tasks, Task1 and Task2, where each task tries to lock one resource first and the other one next.
3. The tasks are run in separate threads, thread1 and thread2.
4. Each task includes a Thread.sleep(100) call to simulate processing time while holding a lock.
5. This induces a deadlock scenario where Task1 locks resource1 and waits for resource2, while Task2 locks resource2 and waits for resource1.
6. The deadlock results in synchronization overhead, as both threads wait indefinitely, unable to proceed.

Simulation of Synchronization Overhead in Java Services on ServiceNow MID server

Let’s run our application on the ServiceNow MID Server and see how Synchronization Overhead in Java Services on ServiceNow MID server problems look. First, create a JAR file from the program using the command:

javac SynchronizationOverheadSimulator.java

jar cf SynchronizationOverheadSimulator.jar SynchronizationOverheadSimulator.class

Once a JAR file is created, let’s upload and run this program in the ServiceNow MID Server as documented in the MID Server setup guide. This guide provides a detailed walkthrough on how to run a custom Java application in the ServiceNow MID Server infrastructure. It walkthrough following steps:

1. Creating a ServiceNow application
2. Installing MID Server in AWS EC2 instance
3. Configuring MID Server
4. Installing Java application within MID Server
5. Running Java application from MID server

We strongly encourage you to check out the guide if you are not sure on how to run custom Java applications in ServiceNow MID server infrastructure.

yCrash’s Diagnosing Synchronization Overhead in Java Services on ServiceNow MID server

Fig: yCrash Issues in the Application view

The yCrash report indicates that the application is experiencing unresponsiveness due to a detected deadlock. The identified problem is caused by certain threads that are stuck in a deadlock situation. This issue results in those threads being unable to proceed, causing the overall application to hang.

Fig: yCrash Thread view

The summary provides an overview of the state of all threads in the application at the time of the report, highlighting a total of 20 threads. Out of these, 15 threads are in the RUNNABLE state, actively executing tasks. Two threads are in the WAITING state, paused and waiting for other threads to signal them. Another two threads are BLOCKED, unable to proceed because they are waiting to acquire locks held by other threads. The last thread is in a TIMED_WAITING state, waiting for a specified period of time to elapse or for another thread to signal a condition. This breakdown helps in understanding the distribution of thread states, which is crucial for diagnosing performance issues and deadlocks.

Fig: yCrash Dead Lock view

The yCrash report details a deadlock situation in the application, where threads Thread-0 and Thread-1 are waiting indefinitely for each other to release locks on resources. Thread-0 is blocked, waiting to lock a resource held by Thread-1, and Thread-1 is similarly blocked, waiting on a resource held by Thread-0. This has caused the application to become unresponsive, as indicated by their BLOCKED states in the stack traces.

Analyzing this deadlock with yCrash helps diagnose synchronization overhead in Java services on a ServiceNow MID server by pinpointing the exact threads and resources causing the deadlock. This allows developers to identify inefficient synchronization mechanisms and redesign critical sections of the code to avoid such deadlocks, improving performance and reliability of the service. You can see the detailed report here.

Conclusion

yCrash is a tool that helps diagnose performance issues and deadlocks in Java applications by providing detailed thread and system state information. Our current problem involves a deadlock in a ServiceNow MID server, where specific threads are stuck waiting on each other, causing the application to become unresponsive. Synchronization overhead, where threads spend excessive time waiting for resource locks, has directly caused this deadlock. The yCrash report identifies the problematic threads and their respective states, offering insights into the causes of the deadlock. By analyzing this data, we can pinpoint synchronization issues and inefficient code sections. This helps us redesign these parts to improve the performance and reliability of the MID server. Overall, yCrash facilitates quicker identification and resolution of complex issues in Java services.

If you want to diagnose and resolve synchronization overhead in your ServiceNow MID Server using yCrash, you may register here.