Memory Leaks and OOM (Out of Memory) Errors

You can detect memory leaks and Out of Memory errors in Apinizer, optimize JVM heap settings, manage cache configuration, and adjust connection pool settings.

Problem Symptoms

Memory leaks and OOM errors usually manifest themselves with the following symptoms:

• Pods continuously restarting
• OutOfMemoryError log records
• Slowly increasing memory usage
• Decrease in system performance
• Pods transitioning to OOMKilled state in Kubernetes

Problem Causes

Memory leaks and OOM errors can usually be caused by the following factors:

• Insufficient Heap Settings: JVM heap size may be insufficient
• Memory Leaks: Unused objects not being cleaned by garbage collection
• Large Data Processing: Processing large message bodies
• Cache Sizes: Cache growing unlimited
• Connection Pool Issues: Connections not being closed
• Thread Pool Issues: Threads not being properly cleaned

Detection Methods

1. Log Analysis

Search for OOM errors in log files:

kubectl logs <pod-name> | grep -i "OutOfMemoryError"
kubectl logs <pod-name> | grep -i "java.lang.OutOfMemoryError"

2. Monitoring Memory Metrics

Monitor memory usage with Prometheus metrics:

• jvm_memory_used_bytes
• jvm_memory_max_bytes
• container_memory_usage_bytes

3. Heap Dump Analysis

1. Take Heap Dump

   Detect memory leaks by taking heap dump:

   # Taking heap dump
   kubectl exec <pod-name> -- jmap -dump:format=b,file=/tmp/heapdump.hprof <pid>
   
   # Copying heap dump from pod
   kubectl cp <namespace>/<pod-name>:/tmp/heapdump.hprof ./heapdump.hprof
   

Solution Recommendations

1. Optimizing JVM Heap Settings

Set JVM parameters in Pod deployment:

env:
  - name: JAVA_OPTS
    value: "-Xms2g -Xmx4g -XX:+UseG1GC -XX:MaxGCPauseMillis=200"

Recommendations:

• Apinizer’s automatic memory profile selects the appropriate GC and heap percentage based on container memory (Serial GC at ≤768 MB, G1GC at 769-1536 MB, ZGC at >1536 MB)
• For containers with more than 1536 MB, ZGC is auto-selected with 70% heap — providing sub-millisecond GC pauses
• If you prefer manual configuration, use G1GC with MaxGCPauseMillis for predictable pause times
• See JVM Garbage Collector Tuning for detailed GC configuration options

2. Increasing Memory Limits

Increase memory limits in Kubernetes deployment:

resources:
  limits:
    memory: "4Gi"
  requests:
    memory: "2Gi"

3. Optimizing Cache Configuration

Set cache TTL and size limits:

• Optimize cache TTL values
• Determine cache size limits
• Clean unnecessary cache entries

4. Optimizing Connection Pool Settings

Check connection pool settings:

• Limit maximum connection count
• Set connection timeout values
• Regularly clean idle connections

5. Thread Pool Management

Optimize thread pool settings:

• Limit maximum thread count
• Set thread timeout values
• Ensure threads are properly cleaned

6. Optimizing Large Message Processing

When processing large message bodies:

• Use streaming
• Determine message size limits
• Avoid unnecessary data copying

Preventive Measures

1. Regular Monitoring

• Regularly monitor memory usage
• Get early warning by setting up alerts
• Detect problems in advance by performing trend analysis

2. Load Testing

• Perform regular load tests
• Detect memory leaks early
• Perform capacity planning

3. Code Review

• Review code that may cause memory leaks
• Check resource management
• Follow best practices

Related Resources

• JVM Tuning
• Performance Tuning
• Log Analysis