Autoscaling Kubernetes well is less about clever algorithms and more about disciplined capacity planning. In this post we walk through how our platform team sizes node pools, sets resource requests correctly, and uses predictive scaling to handle traffic spikes without over-provisioning spend. We also cover common pitfalls like ignoring pod disruption budgets, setting requests too low, and forgetting to test scale-down behavior before an incident actually happens.
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