We address the problem of improving the energy efficiency of servers that provide web-based services, including services provided through clouds. We propose an automated technique for allocating workload to servers to operate the fewest number of servers that are needed to cope with the instantaneous workload, leaving some headroom for workload surges. The technique requires no a priori knowledge about individual workloads and manages the server states explicitly. We use synthetic scripts, a

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... ll server setup and actual energy consumption measurements to show that the proposed system achieves non-trivial energy savings at typical operating regions of traditional server configurations.