In this episode, Lucas and Luna dig into a surprisingly common Kubernetes failure mode: when Pod PriorityClasses and preemption interact badly with cluster autoscaling, nodes get drained, workloads get killed, and the cluster autoscaler ends up fighting itself. They walk through a real-world scenario where a high-priority batch job preempts a low-priority web service, the node autoscaler scales down the now-idle node, and the preempted pods can't reschedule because the cluster is too small — creating a deadlock. Lucas explains how preemption is designed to work, why the autoscaler's node utilization threshold can trigger a scale-down right after preemption, and what signals you can look for in events and metrics to catch this before it bites. They also discuss practical mitigations: using PodDisruptionBudgets with preemption, tuning the autoscaler's scale-down utilization threshold, and considering whether preemption is even the right tool for your workload. If you run a cluster with mixed priorities and autoscaling, this episode gives you a concrete failure pattern to recognise and avoid.