Power Provisioning for Diverse Datacenter Workloads

The workloads hosted in a datacenter share more than just servers; they also share electrical circuits. Datacenter managers provision the power capacity of these circuits to hosted workloads, often based on peak power needs. In this work, we studied the typical (mode) and peak power needs of 3 real datacenters, using 1) data from hardware manufacturers and 2) past traces of observed power needs. We found that typical power needs were nonmonotonic relative to peak needs. That is, some applications with low typical power needs had large peak needs—stemming from the diverse power utilization of datacenter workloads. Such diversity caused surprising order inversions where workloads with relatively small peak power had relatively large typical needs. Based on these results, we propose a power provisioning approach that considers powerutilization diversity. Our approach provides 1) predictable monotonic results as power capacity increases and 2) performs better than approaches commonly used