Gremlin Scenario: Kubernetes CPU scalability

How it works

How this Scenario works

This Scenario progressively consumes CPU within your Kubernetes pods in three stages: 50%, 75%, and 90%. This simulates CPU pressure from traffic spikes or resource-intensive workloads, testing your HPA configuration, pod resource limits, and cluster autoscaler.

Use cases

Why run this Scenario?

Validate that the Horizontal Pod Autoscaler (HPA) triggers at the correct CPU thresholds and scales pods effectively.
Verify that pod CPU resource requests and limits are tuned for both performance and cost efficiency.
Test cluster autoscaler behavior when node-level CPU capacity is exhausted.
Ensure that Kubernetes pod priorities correctly manage resources when CPU is scarce across the cluster.

Result

What to expect when you run it

As CPU usage increases in Kubernetes pods, the Horizontal Pod Autoscaler (HPA) scales the workload to maintain performance within your defined thresholds.

Keep going

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Kubernetes CPU scalability