Detecting out-of-memory errors in a Boomi application is crucial to prevent crashes, maintain stability, optimize resource usage, and improve user experience. Early identification enables proactive issue resolution, enhances performance, ensures scalability, and facilitates troubleshooting. Efficient memory management is essential for application reliability, availability, and cost optimization in cloud environments. Today we are going to detect OOM errors within a Boomi process.
What causes OutOfMemoryError?
Out of Memory Errors in Java applications usually occur when the Java Virtual Machine (JVM) exhausts its allocated heap space or runs out of memory in other areas. Some common reasons that often cause this condition are:
1. Memory Leaks: One of the most common reasons is memory leaks. Objects that are no longer needed by the application but are still referenced are not garbage collected, leading to a gradual increase in memory usage.
2. Inefficient Data Structures: The use of inefficient data structures or holding onto objects unnecessarily can cause the heap to fill up quickly. For example, using a large collection when a smaller one would suffice.
3. Large Objects: The creation of very large objects, such as arrays or collections, can quickly consume available heap space. If these objects are not properly managed, they can lead to Out of Memory Errors.
4. Improper Thread Management: Incorrect management of threads, such as creating too many threads or not properly releasing resources associated with threads, can lead to excessive memory usage.
5. Infinite Loops or Recursion: Infinite loops or recursive calls that do not have proper exit conditions can lead to a continuous increase in the stack space, eventually resulting in a stack overflow error.
6. Classloader Memory Leaks: In certain scenarios, memory leaks can occur due to improper handling of classloaders, especially in environments where dynamic class loading and unloading are performed.
7. Too Many Finalizers: Finalizer methods can prevent objects from being garbage collected promptly. If there are too many objects with finalizers, it can lead to memory exhaustion.
8. Memory Fragmentation: Over time, memory fragmentation can occur, especially in long-running applications. This can make it challenging for the garbage collector to find contiguous blocks of memory, even though the overall heap size may appear sufficient.
9. Insufficient Heap Size: If the allocated heap size is too small for the application’s memory requirements, the JVM may run out of memory. Adjusting the heap size using the -Xmx and -Xms JVM options can help in such cases.
10. Native Memory Leaks: Issues related to native libraries or components can also contribute to memory leaks. For example, not releasing resources acquired through native calls.
Boomi OutOfMemoryError Simulation
The buggyApp project (available on GitHub) demonstrates a common memory management issue by simulating a scenario where a thread continuously consumes memory, leading to a memory leak. This is achieved through the ThreadMemoryLeakDemo class, which creates an ever-growing HashMap. As the map keeps expanding without bounds, it eventually exhausts the heap space, illustrating how thread-related memory leaks can lead to application crashes or performance degradation.
The following is the code from the buggyApp which will simulate the OutOfMemoryError:
package com.buggyapp.memoryleakthread;
/**
*
* @author Ram Lakshmanan
*/
public class ThreadMemoryLeakDemo {
public static void start() {
Object1 object1 = new Object1();
object1.grow();
}
}
package com.buggyapp.memoryleakthread;
public class Object1 {
public void grow() {
Object2 object2 = new Object2();
object2.grow();
}
}
public class Object2 {
public void grow() {
Object3 object3 = new Object3();
object3.grow();
}
}
public class Object3 {
public void grow() {
MapManager mapManager = new MapManager();
mapManager.grow();
}
}
/**
*
* @author Ram Lakshmanan
*/
public class MapManager {
//private static final Logger s_logger = LogManager.getLogger(MapManager.class);
HashMap<Object, Object> myMap = new HashMap<>();
public void grow() {
long counter = 0;
while (true) {
if (counter % 1000 == 0) {
System.out.println("Inserted 1000 Records to map!");
//s_logger.info("Inserted 1000 Records to map!");
}
try {
//Thread.sleep(1);
} catch (Exception e) {
}
myMap.put("key" + counter, "Large stringgggggggggggggggggggggggggggg"
+ "ggggggggggggggggggggggggggggggggggggggggggggggggggggg" + counter);
++counter;
}
}
}
The provided code demonstrates a potential memory leak scenario in a Java application by continuously creating and storing large objects in a HashMap without releasing them. It consists of multiple classes (ThreadMemoryLeakDemo, Object1, Object2, Object3, and MapManager), where the start method in ThreadMemoryLeakDemo initiates a chain of method calls that ultimately leads to the grow method in the MapManager class. This method enters an infinite loop that repeatedly adds entries to a HashMap, each containing a large string, while printing a message every 1000 insertions. As the loop runs indefinitely, memory consumption increases, which can lead to an OutOfMemoryError if not managed properly, illustrating how unbounded resource usage can occur in a threaded environment.
The code to invoke the memory leak scenario from a boomi is below, note that dataContext is an object provided by the Boomi runtime environment:
import java.util.Properties;
import java.io.InputStream;
import com.buggyapp.memoryleakthread.ThreadMemoryLeakDemo;
for( int i = 0; i < dataContext.getDataCount(); i++ ) {
InputStream is = dataContext.getStream(i);
Properties props = dataContext.getProperties(i);
ThreadMemoryLeakDemo.start()
dataContext.storeStream(is, props);
}
To implement this in Boomi we need to create a process with three shapes/steps. The first step is a start shape with no other significance than the start of the process. The next shape is a data process shape which holds the reference to the custom groovy script above, to invoke the buggyApp. The last shape is a stop shape which terminates the process successfully.
Fig: Boomi Process Creation – OOM Exception
Boomi Process Execution
I executed the process and Boomi failed the process due to lack of heap space.
Fig: Boomi Process Reporting – OOM Exception
Boomi Triage and Troubleshooting
The Boomi container log caught the heap space failure:
Jan 4, 2024 5:57:47 PM EST SEVERE [com.boomi.process.ProcessExecution handleProcessFailure] Unexpected error executing process: java.lang.OutOfMemoryError: Java heap space
java.lang.OutOfMemoryError: Java heap space
I also noticed that the atom JVM process rebooted itself after detecting the OOM failure.
Jan 4, 2024 5:58:27 PM EST SEVERE [com.boomi.util.LogUtil doLog] OutOfMemoryError detected: the atom is restarting…
yCrash Troubleshooting
yCrash caught the incident with the tag “Out of Memory”. Below is the incident page generated by yCrash. It also indicated that less than 5% of total system memory is available.
Fig: yCrash Incident Summary Screen for Boomi Process Generated by OOM
The report can be reviewed here: https://www.ycrash.io/yc-report.jsp?ou=REVuMm56ODZqOHBCbDh3QjdYMW5lUT09&de=192.168.1.162&app=yc&ts=2024-04-27T19-51-03&srId=VysyL2ErSjJzRnB0OWNxYk52Mm1qZz09
Interestingly, the Out of Memory error was identified in the Application Logs module. You can clearly see the java “Out of Memory” signature errors from over allocating the heap.
Conclusion
Identifying and resolving out-of-memory errors in Java applications, like those in Boomi processes, is crucial for system stability and performance. By recognizing common causes such as memory leaks and inefficient data structures, developers can preemptively address issues. Tools like yCrash provide valuable diagnostics for streamlined troubleshooting, improving memory management and application reliability. With proactive monitoring and optimization, organizations can ensure smooth operations and enhance user experience in their Boomi setups.
Share your Thoughts!