While there has been a variety of Kubernetes Enhancement Proposals (KEPs) to improve its scheduler plugins for a range of resource and node allocation requirements, unfortunately, we find there hasn't been a focus on sustainability. Towards this, we propose a new scheduler - PEAKS (Power Efficiency Aware Kubernetes Scheduler) that can factor in sustainability goals such as power utilization and carbon footprint. PEAKS leverages the Kepler (Kubernetes-based Efficient Power Level Exporter) project, which uses eBPF to probe system wide utilization (i.e. power, memory, CPU, etc) and dynamically expose these metrics via Prometheus. Given these metrics, PEAKS makes dynamic decisions to recommend nodes for pod scheduling, addressing power inefficiencies on underutilized nodes. In this talk, I will present on-going work from collaborators at Boston University, Red Hat, and IBM in deploying PEAKS in a variety of experimental scenarios that range from synthetic to more realistic microservices-based deployments.