Autoscaling Policy Calibrator

Platform engineers and SREs managing Kubernetes workloads with HPA, VPA, or KEDA need to calibrate autoscaling policies based on observed traffic patterns to avoid both over-provisioning waste and under-scaling failures during load spikes. Default autoscaling settings are almost never optimal for real workload shapes.