Manage AMD EPYC™ CPU Power at Scale

See how Kubernetes Power Manager enhances the energy efficiency of AMD EPYC™ CPUs for lower costs and a sustainable cloud infrastructure

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Fine-Tune AMD EPYC™ CPU Power at Scale

More efficient and sustainable AMD EPYC™ CPUs with Kubernetes Power Manager

As global data center energy consumption surges toward 1000 TWh by 2026, optimizing power usage across cloud infrastructure has become essential. High-performance workloads, particularly in telco and edge environments, demand smarter resource orchestration that balances efficiency with performance.

This white paper is your guide to unlocking energy optimization for AMD EPYC™ CPUs in Kubernetes environments, covering:

Workload-aware tuning: Tailoring CPU performance using PowerProfiles and CPU ScalingProfiles.
Dynamic CPU scaling: Using real-time telemetry and utilization metrics to intelligently adjust core frequencies and power states in KPM.
Sustainability at scale: Reducing idle power waste across cloud and edge deployments.
Multi-cluster orchestration: See how KPM integrates into distributed cloud environments for broader control and geographic load balancing.

Whether you're running a small Kubernetes cluster or managing infrastructure at scale, this white paper equips you with actionable tools to drive smarter, greener cloud operations.

This White paper Unlocks

Smarter CPU Resource Control

Learn how to dynamically tune AMD cores for better efficiency and performance.

Energy Savings at Scale

Discover strategies to cut idle power use across clusters and edge nodes.

Ready for Real-World Deployment

Get practical steps for deploying KPM using automated provisioning tools.

Get the AMD EPYC™ CPU Efficiency guide

Learn how to reduce power waste, enhance performance, and scale sustainability using Kubernetes Power Manager for AMD EPYC™ CPUs.