Autoscaling Failed During Peak Traffic Periods

Autoscaling was ineffective during peak traffic periods, leading to degraded performance.

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What Happened

Although traffic spikes were detected, the Horizontal Pod Autoscaler (HPA) failed to scale up the required number of pods in time.

Diagnosis Steps

1Analyzed HPA metrics and scaling logs, which revealed that the scaling trigger was set with a high threshold.
2Traffic metrics indicated that the spike was gradual but persistent, triggering a delayed scaling response.

Root Cause

Autoscaling thresholds were not sensitive enough to handle gradual, persistent traffic spikes.

Fix/Workaround

• Lowered the scaling thresholds to respond more quickly to persistent traffic increases.
• Implemented more granular scaling rules based on time-based patterns.

Lessons Learned

Autoscaling policies need to be tuned to handle gradual traffic increases, not just sudden bursts.

How to Avoid

1Implement time-based or persistent traffic-based autoscaling rules.
2Regularly monitor and adjust scaling thresholds based on actual traffic patterns.

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