Inconsistent Scaling Due to Misconfigured Horizontal Pod Autoscaler

Horizontal Pod Autoscaler (HPA) inconsistently scaled pods based on incorrect metric definitions.

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What Happened

HPA failed to scale up correctly because it was configured to trigger based on custom metrics, but the metric source was unreliable.

Diagnosis Steps

1Reviewed HPA configuration and identified incorrect metric configuration.
2Logs showed HPA was relying on a custom metric, which sometimes reported outdated or missing data.

Root Cause

Misconfigured custom metrics in the HPA setup, leading to inconsistent scaling decisions.

Fix/Workaround

• Switched to using Kubernetes-native CPU and memory metrics for autoscaling.
• Improved the reliability of the custom metrics system by implementing fallback mechanisms.

Lessons Learned

Custom metrics should be tested for reliability before being used in autoscaling decisions.

How to Avoid

1Regularly monitor and validate the health of custom metrics.
2Use native Kubernetes metrics for critical scaling decisions when possible.

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