Detecting thread leakage in a Boomi process is paramount to ensuring optimal software performance and maintaining the stability of the environment. Thread leakage occurs when a process creates threads that are not properly terminated or managed, leading to an accumulation of inactive or blocked threads over time. This can severely degrade system performance, as the growing number of threads consumes valuable system resources such as memory and CPU, ultimately leading to slowdowns, resource exhaustion, and even complete system crashes. In a production environment where seamless and efficient data integration is critical, such performance degradation can have far-reaching impacts on business operations, user experience, and overall productivity.

Effective thread management is essential for maintaining the reliability and responsiveness of Boomi processes. When thread leakage is not detected and addressed, it can cause significant disruptions to business processes by overwhelming the runtime environment. This results in increased latency, delayed data processing, and potential data loss or corruption. Additionally, unhandled thread leaks can lead to unpredictable behavior, making it difficult to troubleshoot and resolve issues quickly. Ensuring that threads are properly managed and terminated helps maintain a stable environment, enabling consistent and reliable execution of integration tasks.

Simulating Thread Leakage Natively in Boomi

Using the below code, the program effectively spawns up to 10000 threads and the threads sleep infinitely forever. The threads do not exit and persist past the execution of the Boomi process.

import java.util.Properties;
import java.io.InputStream;

// Function to simulate work by creating a new thread
def createLeakingThread() {
    new Thread({
        while (true) {
            // Simulate some work by sleeping for a short period
            Thread.sleep(1000)
        }
    }).start()
}

for( int i = 0; i < dataContext.getDataCount(); i++ ) {
    InputStream is = dataContext.getStream(i);
    Properties props = dataContext.getProperties(i);

    // Number of threads to create (this value can be adjusted)
    def threadCount = 10000

    // Create the specified number of leaking threads
    for (int j = 0; j < threadCount; j++) {
        createLeakingThread()
        println("Created thread #" + (j + 1))
        // Delay between thread creations to simulate a slow leak
        Thread.sleep(10)
    }

    println("Simulated thread leakage completed. Threads will stop eventually.")

    dataContext.storeStream(is, props);
}

This Groovy script is designed to simulate thread leakage within a Boomi process. It first defines a function, createLeakingThread(), which creates and starts a new thread. Each of these threads runs an infinite loop where it sleeps for one second repeatedly, simulating ongoing work without termination. The main part of the script iterates over the data available in the dataContext. For each piece of data, it retrieves the input stream and properties. Then, it creates a specified number of threads (threadCount set to 10,000) by calling the createLeakingThread() function in a loop. After each thread is created, the script pauses for 10 milliseconds to simulate a gradual leak. The threads created continue to run indefinitely, consuming system resources. Finally, the script stores the input stream and properties back into the dataContext. This simulation helps illustrate the potential impact of thread leakage by creating a large number of long-running threads that can lead to resource exhaustion and degraded system performance.

yCrash Monitoring for Boomi

In order to monitor the performance of the application, I have selected yCrash to help. The yCrash agent must be installed in order to report back performance metrics to the yCrash receiver/dashboard. To install the yCrash agent, follow these instructions. 

Boomi Thread Leakage Scenario

The process used to test thread leakage exists in an error state with “unable to create native thread: possibly out of memory or process/resource limits reached”. The process logs capture the thread leakage scenario due to the resource consumption of spawning numerous threads. 

Jun 9, 2024 11:15:53 AM EDT SEVERE  [com.boomi.process.ProcessExecution handleProcessFailure] Unexpected error executing process: java.lang.OutOfMemoryError: unable to create native thread: possibly out of memory or process/resource limits reached

java.lang.OutOfMemoryError: unable to create native thread: possibly out of memory or process/resource limits reached

Fig: Boomi Process Reporting – Failed Process: [Java] Native Thread Leakage

yCrash Diagnostics – Native Thread Leakage

As expected, yCrash identifies the thread leakage incident and raises an Incident Summary.

Fig: yCrash Boomi Incident Summary – OutOfMemoryError

You can check out the Incident Report here.

It looks like yCrash identified the resource consumption scenario by monitoring the Application logs.

Fig: yCrash Detailed Incident Summary View – Application Logs

This tells me that the process that we created consumed many resources as we spawned threads, to the point it started to cause instability within the processes that are running on the Atom. As those other processes began to fail (scheduler, atom-queue runner, homebase callbacks, etc…), they generated OutOfMemoryError exceptions which yCrash is on top of. 

Conclusion

Preventing thread leakage in custom Groovy scripting within Boomi is crucial due to the significant performance issues it can cause. Thread leakage occurs when threads are created but not properly managed or terminated, leading to an accumulation of inactive or blocked threads that consume system resources. In a Boomi environment, where efficient data integration and processing are vital, such leakage can result in degraded performance, increased latency, and even system crashes. Proper thread management practices, such as ensuring threads are terminated correctly and avoiding unnecessary thread creation, are essential to maintain the stability and efficiency of the integration processes. By proactively addressing thread leakage, organizations can safeguard their Boomi environments from resource exhaustion, ensuring reliable and high-performing integration solutions that support business continuity and operational excellence.