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Scenario #470
Scaling & Load
Kubernetes v1.23, AWS EKS
Slow Scaling Response Due to Insufficient Metrics Collection
The autoscaling mechanism responded slowly to traffic changes because of insufficient metrics collection.
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What Happened
The Horizontal Pod Autoscaler (HPA) failed to trigger scaling events quickly enough due to missing or outdated metrics, resulting in delayed scaling during traffic spikes.
Diagnosis Steps
- 1Checked HPA logs and observed that the scaling behavior was delayed, even though CPU and memory usage had surged.
- 2Discovered that custom metrics used by HPA were not being collected in real-time.
Root Cause
Missing or outdated custom metrics, which slowed down autoscaling.
Fix/Workaround
• Updated the metric collection to use real-time data, reducing the delay in scaling actions.
• Implemented a more frequent metric scraping interval to improve responsiveness.Lessons Learned
Autoscaling depends heavily on accurate and up-to-date metrics.
How to Avoid
- 1Ensure that all required metrics are collected in real-time for responsive scaling.
- 2Set up alerting for missing or outdated metrics.