OutOfMemoryError is one of the most disruptive failures that a Java application can encounter. These errors can cause the application to slow down, crash and sometimes even cause restart loops that is totally chaotic. This is where the famous proverb makes sense: Prevention is better than cure. Honestly, I kind of agree with it too.
In the past we have discussed in detail, what a Java OutOfMemoryError is, what are it’s types, and we have even listed each of those types with possible ways to troubleshoot and fix those errors. This means we have already equipped you with the information that you need to handle when you face OutOfMemoryError issues. Now, we are going to give you some tips that can prevent it from happening.
1. Size the Java Heap Properly
One of the most common causes of memory failures is simply improper heap sizing. If the heap is too small relative to the allocation rate, the JVM eventually runs out of memory. Now, this will lead to Java heap space OutOfMemoryError, and we havee outlined what are the causes, possible solutions in the blog already. The things you need to be vigilant about are as follows:
- Proper -Xms and -Xmx Configuration
- Monitor Heap Utilization
- Understand Object Allocation Rate
- Avoid Excessive Object Retention
2. Prevent Garbage Collection Pressure
Similarly, when objects are allocated faster than the garbage collector can reclaim them, the JVM starts spending an excessive amount of time performing garbage collection instead of executing application logic. Over time, this can lead to the GC Overhead Limit Exceeded error, where the JVM determines that too much CPU time is being spent on GC with very little memory being reclaimed. This is again discussed in detail in our earlier blog, and here’s what you need to prevent it from happening:
- Monitor GC behavior
- Reduce unnecessary object creation
3. Control Thread Creation
This is specific to applications that create too many threads may eventually exhaust the available native memory required for thread stacks. When the system cannot allocate memory for new threads, the JVM throws the Unable to Create New Native Thread error. To prevent this you have to be vigilant about are as follows:
- Limit Thread Creation
- Use bounded thread pools
4. Manage Class Metadata
Modern JVMs store class metadata in Metaspace, which resides outside the Java heap. Excessive dynamic class loading, proxy generation, or classloader leaks can cause Metaspace usage to grow uncontrollably and eventually trigger a Metaspace OutOfMemoryError. To stop this from happening the only thing you need to do is control Class Metadata Growth.
5. Monitor Off-Heap Memory
Java applications can allocate memory outside the Java heap using mechanisms such as NIO direct buffers. While this improves performance in many cases, excessive off-heap allocations may lead to the Direct Buffer Memory OutOfMemoryError. The prevention measure we’d suggest here is to manage oof-heap or the direct memory carefully. If you do that, then you should be safe.
6. Configure Container Memory Correctly
In containerized environments such as Docker or Kubernetes, memory limits are enforced by the operating system rather than the JVM. If the application exceeds the container’s memory limit, the operating system may terminate the process, resulting in a Kill Process OutOfMemoryError. If you configure the container memory correctly, then this crisis is averted as well.
7. Monitor Native Memory Usage
Not all memory used by a Java application comes from the heap. Soma also somes from Native memory which can be consumed by JNI libraries, system resources, or other native components, and excessive usage may lead to OutOfMemoryError messages referencing native methods. We have already discussed the causes and possible solutions for such scenarios in our blog. Investigating the native memory usage would be the best approach to avoid this from happening.
8. Avoid Excessive Array Allocations
Sometimes applications attempt to allocate arrays that are larger than what the JVM can support. This typically occurs due to programming errors, incorrect size calculations, or unvalidated input data, which can lead to the Requested Array Size Exceeds VM Limit error. So what can we do to prevent this from happening? It’s simple. Make sure you validate the inputs and avoid allocating extremely large arrays.
9. Upgrade Legacy JVM Configurations
Now, this is crucial. Some of the enterprises that we know still use the legacy environments in production, which means they use old version of Java. If that is the case, then there is a high chance that a certain type of OutOfMemoryError happens. Because Older versions of Java used PermGen to store class metadata, and applications running on legacy JVMs may encounter the PermGen Space OutOfMemoryError when this area becomes full. Modern JVMs have replaced PermGen with Metaspace, but legacy systems may still face this issue. There are two steps to prevent this from happening:
- Upgrade to newer JVM versions
- Monitor class metadata usage
Quick Summary Table
Let me quickly summarize the above sections in the table:
| OutOfMemoryError Type | Common Cause | Prevention Strategy |
| Java Heap Space | Heap exhaustion | Proper heap sizing and memory monitoring |
| GC Overhead Limit Exceeded | Excessive garbage collection | Reduce allocation rate |
| Unable to Create New Native Thread | Too many threads | Use bounded thread pools |
| Metaspace | Excessive class metadata | Control class loading |
| Direct Buffer Memory | Off-heap allocations | Monitor direct memory usage |
| Kill Process | Container memory limits | Configure container memory properly |
| Native Method | Native memory usage | Monitor JNI/native allocations |
| Requested Array Size | Oversized arrays | Validate input and allocation size |
| PermGen Space | Legacy JVM metadata limits | Upgrade JVM versions |
Recommended Tools for Prevention
Since many of the prevention practices discussed above involve monitoring memory behavior, it is important to use the right tools to observe JVM memory usage and detect anomalies early. Even with proper configuration and coding practices, memory usage patterns can change over time due to traffic growth, increasing data volumes, or new features being introduced into the system. Monitoring tools help identify these patterns before they escalate into OutOfMemoryError failures.
Some of the commonly used tools include:
1. HeapHero: Analyzes Java heap dumps and helps identify memory leaks, excessive object retention, and inefficient memory usage patterns that may eventually lead to OutOfMemoryError.
2. GCeasy: Analyzes JVM garbage collection logs and provides insights into GC behavior, memory allocation rates, pause times, and GC efficiency.
3. fastThread: Analyzes thread dumps and helps detect thread leaks, blocked threads, and excessive thread creation that may contribute to native memory exhaustion.
4. Java Mission Control (JMC): A powerful JVM monitoring and profiling tool that provides real-time insights into memory usage, garbage collection activity, and application performance.
5. VisualVM: To monitor heap usage, thread activity, and CPU consumption, and also capture heap dumps for deeper analysis.
6. Prometheus + Grafana: In modern production environments, Prometheus combined with Grafana is commonly used to monitor JVM metrics such as heap usage, GC activity, thread counts, and container memory consumption.
Conclusion
That said, you should now have a clear understanding of how to diagnose, troubleshoot, and fix OutOfMemoryError issues, as well as the best practices to prevent them from occurring in the first place.
OutOfMemoryError failures rarely appear without warning. In most cases, they are the result of gradual memory pressure caused by inefficient memory usage, excessive resource consumption, or improper JVM configuration. By following the preventive practices discussed in this article, you can significantly reduce, even stop, the likelihood of encountering memory-related failures in production.
Proactive monitoring and early diagnosis remain the most effective ways to ensure long-term memory stability in Java applications.
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