Existing Kubernetes schedulers prioritize resource allocation over varying node power efficiencies. PEAKS (Power Efficiency Aware Kubernetes Scheduler) targets aggregate power optimization during scheduling. Using ML models considering Node Utilization vs Power Consumption, PEAKS recommends nodes for pod scheduling, addressing power inefficiencies on underutilized nodes. This dynamic approach aligns nodes along the utilization-power curve, significantly reducing power compared to default schedulers. Emphasizing multi-objective optimization and power efficiency, PEAKS innovates cloud-native system management. Kepler facilitates energy metrics collection from cluster nodes, enhancing power-aware scheduling. The discussion explores diverse pod placement strategies based on node utilization-power relations, enriching Kubernetes' energy optimization.