Association for Computing Machinery
Peak power management of datacenters has tremendous cost implications. While numerous mechanisms have been proposed to cap power consumption, real datacenter power consumption data is scarce. To address this gap, the authors collect power demands at multiple spatial and fine-grained temporal resolutions from the load of geo-distributed datacenters of Microsoft over 6 months. They conduct aggregate analysis of this data, to study its statistical properties. With work-load characterization a key ingredient for systems design and evaluation, they note the importance of better abstractions for capturing power demands, in the form of peaks and valleys.