K8S Memory Tune

What This Skill Does

The K8s Memory Tune skill is a diagnostic and configuration optimization utility designed to resolve persistent OOMKilled errors in Kubernetes-based Java applications. Many JVM-based applications running inside containers suffer from memory exhaustion because the JVM fails to correctly calculate its maximum heap size relative to the container's memory limits, leading to scenarios where the container is killed by the K8s OOMKiller despite the heap appearing to have room. This skill provides a structured approach to applying JVM-specific ergonomics by utilizing MaxRAMPercentage, ensuring the heap footprint dynamically scales with the container's cgroup memory boundaries.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/2233admin/k8s-memory-tune

Use Cases

• OOMKilled Troubleshooting: Automatically diagnose why specific pods are crashing during peak traffic loads.
• Production Tuning: Standardize JVM heap settings across microservices to ensure stability.
• Cloud Cost Optimization: Fine-tune resource requests and limits by aligning JVM memory consumption with actual workload behavior.
• Performance Engineering: Implement container-aware monitoring to identify memory leaks versus misconfigured heap settings.

Example Prompts

1. "My Java microservice keeps getting OOMKilled on K8s, can you help me tune the JVM heap settings?"
2. "Analyze the current pod memory_limit and suggest the correct -XX:MaxRAMPercentage for my container."
3. "The JVM heap is not respecting container memory constraints; apply the recommended k8s memory tune configuration."

Tips & Limitations

• Safety First: Before applying these flags, ensure you have verified your baseline memory usage; setting MaxRAMPercentage too high can still trigger the OOMKiller if native memory (metaspace, code cache, stack) plus heap exceeds the limit.
• Version Check: Ensure your JVM version supports the modern container-aware memory flags; older versions of Java 8 may require specific minor versions or patches.
• Monitoring: Always accompany these changes with Prometheus or Grafana dashboards to track the actual Resident Set Size (RSS) versus the JVM heap usage to prevent 'ghost' OOMKilled events where non-heap memory is the culprit.