OutOfMemoryError GC Overhead Limit Exceeded in Jenkins: Root Causes, Diagnostics & Production Fixes

Jenkins – popular CI/CD pipeline is used for several critical operations in the organization such as building applications, conducting automated tests, deployments in pre-prod and prod environments, … If Jenkins is down, engineers’ productivity will be severely hampered. Thus, extra care is given to major organizations to keep them up 24 x 7. 

While Java has 9 types of OutOfMemoryError, Jenkins is susceptible to 8 of them. In this blog series, we systematically walk through each of those 8 types, helping you identify, diagnose, and fix them. This post covers one of them.

Occasionally it can experience java.lang.OutOfMemoryError: GC Overhead Limit Exceeded, which would disrupt entire Jenkins availability. In this post let’s discuss what does ‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ mean, how to isolate the root cause of it quickly, what are its temporary and permanent fixes, and even better, how to prevent them from happening.

Immediate Stabilization Steps – OutOfMemoryError GC Overhead Limit Exceeded in Jenkins

When Jenkins experience ‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ here are the options one can take to stabilize the Jenkins immediately (basically first-aid):

1. Restart the JVM: When ‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ happens in Jenkins, it will put JVM into an unstable state. It’s dangerous to run Jenkins in this setting, as it can result in erroneous behavior. Thus, it’s highly recommended to restart the JVM, so that it will come back in a clean slate.

2. Increase Heap size: ‘java.lang.OutOfMemoryError: Java heap space’ happens in Jenkins due to lack of space in the heap region of the JVM Memory. Thus increase the heap memory region size. You can increase the heap memory region by passing following arguments to your JVM: 

-Xmx<size> Sets the upper limit for heap size 

Why OutOfMemoryError GC Overhead Limit Exceeded Happens in Jenkins?

To better understand OutOfMemoryError GC Overhead Limit Exceeded, we first need to understand different JVM Memory regions. Here is a video clip that gives a good introduction about different JVM memory regions. But in nutshell, JVM has following memory regions:

Fig: JVM Memory Regions

1. Young Generation: Newly created application objects are stored in this region.
2. Old Generation: Application objects that are living for longer duration are promoted from the Young Generation to the Old Generation. Basically this region holds long lived objects.
3. Metaspace: Class definitions, method definitions and other metadata that are required to execute your program are stored in the Metaspace region. This region was added in Java 8. Before that metadata definitions were stored in the PermGen. Since Java 8, PermGen was replaced by Metaspace.
4. Threads: Each application thread requires a thread stack. Space allocated for thread stacks, which contain method call information and local variables are stored in this region.
5. Code Cache: Memory areas where compiled native code (machine code) of methods is stored for efficient execution are stored in this region.
6. Direct Buffer: ByteBuffer objects are used by modern framework (i.e. Spring WebClient) for efficient I/O operations. They are stored in this region.
7. GC (Garbage Collection): Memory required for automatic garbage collection to work is stored in this region. 
8. JNI (Java Native Interface): Memory for interacting with native libraries and code written in other languages are stored in this region.
9. misc: There are areas specific to certain JVM implementations or configurations, such as the internal JVM structures or reserved memory spaces, they are classified as ‘misc’ regions.

Fig: ‘java.lang.OutOfMemoryError: GC overhead limit exceeded’

When Jenkins’ JVM is spending more than 98% of its time doing garbage collection but recovering less than 2% of the heap, across 5 consecutive GC cycles, the JVM gives up and throws java.lang.OutOfMemoryError: GC overhead limit exceeded. This is Jenkins signaling that it is exhausting nearly all of its processing effort just trying to free memory, yet making almost no progress.

Note: When the above program is executed multiple times, sometimes it may throw ‘java.lang.OutOfMemoryError:Java heap space’ and sometimes it may throw ‘java.lang.OutOfMemoryError:GC overhead limit exceeded’. Depending on how a Jenkins build or pipeline pushes memory, the JVM may throw either one interchangeably. Both point to the same underlying pressure: Jenkins has more live objects than the heap can comfortably sustain. 

This video covers OutOfMemoryError: GC Overhead Limit Exceeded from a Java perspective, the same underlying concept that applies to Jenkins.

Root Causes of OutOfMemoryError GC Overhead Limit Exceeded in Jenkins

‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ in Jenkins is potentially caused because of the following reasons:

1. Increase in Traffic Volume: When there is a spike in the traffic volume, more objects will be created in the memory. When more objects are created than the allocated Memory limit, Jenkins JVM will throw ‘GC Overhead Limit Exceeded’.
2. Memory Leak due to Buggy Code: Due to the bug in the Jenkins plugin, or  Jenkins application can inadvertently retain references to objects that are no longer needed, it can lead to buildup of unused objects in memory, eventually exhausting the available heap space, resulting in OutOfMemoryError.
3. Container OOMKill vs. JVM OutOfMemoryError (Kubernetes): These two look similar but are fundamentally different. A JVM OutOfMemoryError is thrown by the JVM itself when the heap is exhausted, the application logs it and may try to recover. An OOMKill is the Linux kernel silently terminating your pod the moment it breaches its memory: limit, with zero JVM warning, you’ll only know it happened via OOMKilled in kubectl describe pod. The fixes don’t overlap: heap tuning or leak fixes for JVM OOM; bumping the pod memory limit or lowering -Xmx for OOMKill.

How to Diagnose the OutOfMemoryError GC Overhead Limit Exceeded Problem in Jenkins (Step-by-Step)

To diagnose OutOfMemoryError: GC Overhead Limit Exceeded in Jenkins, the process involves two steps: capturing a heap dump and analyzing it. 

1. Capture Heap Dump: You need to capture heap dump from the application, right before JVM throws OutOfMemoryError. In this post, 8 options to capture the heap dump are discussed. You might choose the option that fits your needs. My favorite option is to pass the -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=<FILE_PATH_LOCATION> JVM arguments to your application at the time of startup. Example:

-XX:+HeapDumpOnOutOfMemoryError 
-XX:HeapDumpPath=/opt/tmp/heapdump.bin

When you pass the above arguments, JVM will generate a heap dump and write it to ‘/opt/tmp/heapdump.bin’ whenever OutOfMemoryError is thrown. 

What is Heap Dump?

A heap dump is a frozen snapshot of everything Jenkins had in memory at that moment — every object, every reference chain, every piece of build data, plugin state, and pipeline context. 

2. Analyze Heap Dump: Once the heap dump is captured from Jenkins, load it into a tool like HeapHero, JHat, or Eclipse MAT to analyze it. These tools will surface the heaviest memory consumers and help pinpoint whether the leak originates from a Jenkins plugin, a runaway build process, or accumulated pipeline data that was never released.

Solutions for OutOfMemoryError GC Overhead Limit Exceeded in Jenkins

Here are the potential solutions to address java.lang.OutOfMemoryError: GC Overhead Limit Exceeded in Jenkins:

1. Identify & Fix the Memory Leak in Jenkins: Using the diagnostic steps described in the above section find the leaking objects in the memory and fix it.
2. Remove the recently added Plugins: Whenever you add new plugins, it will occupy space in the Metaspace. Sometimes you might end up adding poorly implemented, memory-inefficient plugins. Remove the recently added plugins and restart the JVM and see whether Jenkins stabilizes. 
3. Revert to Previous Jenkins Installation: If you have recently upgraded to the latestversion of Jenkins installation and GC Overhead Limit Exceeded OutOfMemoryError started to surface after it, consider reverting to previous Jenkins installation.
4. Increase Heap size: ‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ happens in Jenkins due to lack of space in the heap region of the JVM Memory. Thus increase the heap memory region size. You can increase the heap memory region by passing following arguments to your JVM: 
   
   -Xmx<size> Sets the upper limit for heap size 

How to Prevent OutOfMemoryError GC Overhead Limit Exceeded in Jenkins

Before you upgrade to new release of Jenkins or install a new Jenkins plugin in the production environment, you might be studying following key metrics in your performance lab:

• CPU Utilization
• Memory Utilization
• Response Time of key transactions

These are wonderful metrics that highlight the performance characteristics of the new release. However, several performance problems slowly build over the period of time, for example for most applications, OutOfMemoryError happens only if it runs for more than 1 week. In the performance lab, we don’t run such long endurance tests. 

Above mentioned metrics are more reactive indicators that don’t indicate the silently lurking problem in the environment. We recommend studying below mentioned Micro-metrics along with above reactive indicators in the performance lab and certify the release. These Micro-Metrics are good at predicting/forecasting performance problems even if they act at acute scale.

• GC Behavior Pattern: Detects memory leaks, poor GC configuration, or excessive object promotion causing GC pauses.
• Object Creation Rate: Identifies allocation surges that can trigger frequent GCs or memory pressure.
• GC Throughput: Highlights apps spending too much time in GC instead of work—can lead to CPU spikes or slowdowns.
• GC Pause Time: Surfaces stop-the-world GC events affecting responsiveness or causing thread backlogs.
• Thread Patterns: Flags CPU spikes, thread starvation, bursty load, and thread buildup from backend slowness.
• Thread States: Detects BLOCKED, DEADLOCKED, or WAITING threads due to DB chattiness, config limits, or locking.
• Thread Pool Behavior: Identifies thread exhaustion, request rejections, or poor pooling thresholds in backend services.
• TCP/IP Connection Count & States: Catches backend connection leaks, TIME_WAIT surges, or slow/unresponsive downstream services.
• Error Trends in Application Logs: Detects hidden runtime errors, JDBC leaks, logging misconfigurations, or disk issues.

yCrash tool facilitates you reporting these Micro-Metrics which will unearth several performance problems well in advance, before they silently surface in production. You can find the details on how to source and study these Micro-Metrics through yCrash from here. 

Business Impact & ROI

Isolating and fixing OutOfMemoryError in Jenkins will have considerable business impact to your organization:

1. Engineering Time Savings: yCrash dramatically reduces the time engineers spend analyzing Heap Dumps and pinpointing root causes in complex, multi-threaded applications.
   • Suppose your organization is analyzing 10 incidents per month & each analysis traditionally will take around 40 hours. 
   • With a Performance Engineer’s hourly rate at USD $100, yCrash can save approximately $480,000 annually (10 incidents x 40 hours/dump x $100/hour x 12 months) by automating root cause analysis and reducing troubleshooting time.

2. Rapid Deployments & Increased Productivity: yCrash minimizes prolonged downtime of Jenkins that can lead to delayed deployment, degeneration of engineers productivity and reputational damage of the organization. By quickly diagnosing issues, yCrash helps to prevent such large-scale impacts, protecting revenue and brand reputation.

3. Protection from Escalated Operational Consequences: Certain Jenkins outages can have severe repercussions, including escalated consequences like organizational changes or job losses. yCrash’s rapid problem isolation capabilities prevent such disruptions, allowing teams to resolve issues before they escalate to crisis levels. By maintaining operational continuity and team stability, yCrash supports a steady, resilient organizational environment and protects against the high stakes impacts that can result from unmanaged production outages.

Conclusion

Jenkins is the backbone of your organization’s CI/CD pipeline. Keeping it stable is not optional, it’s rather essential. Even though ‘java.lang.OutOfMemoryError: GC Overhead Limit Exceeded’ is not a common error, it can hurt your entire Jenkins platform availability, when it surfaces. Hopefully this post has given you enough light on how to troubleshoot this problem effectively & efficiently.