Many processing platforms are measured and compared today using single socket or single system benchmarks focused primarily on performance. These numbers can be misleading because they do not consider what real workloads at scale will consume in space, power, and other data center resources—key factors in overall data center efficiency.

Since performance per rack incorporates inherent power and space constraints, it’s a more useful metric for data center operators, architects, and procurement analysts. The performance per rack metric details analysis at the rack level—including power consumption, rack density, and overall data center footprint. Ultimately, this kind of analysis yields more sustainable data center designs for the modern cloud era.

Since racks house servers, networking gear, and power delivery equipment, there is an overhead cost to adding racks to a data center. By reducing the number of racks needed to support a workload, Cloud Native Processors reduce this overhead—as well as required cooling—thereby magnifying their impact on data center efficiency by lowering power consumption. More significantly, delivering more performance per rack allows data center operators to reclaim part of their floorspace for future expansion.

“When looking at performance and power across the datacenter – especially for a workload that has consistent performance like cloud native – this rack level measurement is the best measurement. It allows a datacenter architect to quickly extrapolate compute capacity relative to needs at scale. It also enables a very quick and accurate measure of power consumption and power efficiency.”

Patrick Moorhead, Industry Analyst via Forbes