An experimental methodology to evaluate energy efficiency and performance in an enterprise virtualized environment

Computing servers generally have a narrow dynamic power range. For instance, even completely idle servers consume between 50% and 70% of their peak power. Since the us- age rate of the server has the main in uence on its power consumption, energy-e ciency is achieved whenever the uti- lization of the servers that are powered on reaches its peak. For this purpose, enterprises generally adopt the following technique: consolidate as many workloads as possible via virtualization in a minimum amount of servers (i.e. maxi- mize utilization) and power down the ones that remain idle (i.e. reduce power consumption). However, such approach can severely impact servers' performance and reliability. In this paper, we propose a methodology to determine the ideal values for power consumption and utilization for a server without performance degradation. We accomplish this through a series of experiments using two typical types of workloads commonly found in enterprises: TPC-H and SPECpower ssj2008 benchmarks. We use the rst to mea- sure the amount of queries responded successfully per hour for di erent numbers of users (i.e. Throughput@Size) in the VM. Moreover, we use the latter to measure the power con- sumption and number of operations successfully handled by a VM at di erent target loads. We conducted experiments varying the utilization level and number of users for di er- ent VMs and the results show that it is possible to reach the maximum value of power consumption for a server, without experiencing performance degradations when running indi- vidual, or mixing workloads.