Abstract:An increased adoption of cloud computing has lead to a greater concentration of hardware in massive named datacenters.It is essential for these datacenters to be energy efficient not only to cut down on electricity costs but also to be in compliance with environmental regulations.The author implemented an enhanced version of Hadoop YARN framework that utilizes RAPL's power capping feature to mitigate computational imbalances in an application and to reduce CPU power consumption, named Phadoop. The purpose of the experiment is investgating whether it is beneficial to use RAPL interfaces to conserve the energy consumption of a CPU in a cloud-based workload without significant loss of performance. Experimental results indicate a reduction in energy consumption of Phadoop up to 34% compared to Hadoop.