Application-Agnostic Power Monitoring in Virtualized Environments

Abstract

Many servers use technologies such as virtualization or containerization to improve server utilization. These technologies pose challenges for power monitoring since it is not possible to directly measure the power use of an abstraction such as a virtual machine. Much work has been done in modeling the power use of CPUs, virtual machines and entire servers, however, there is a scarcity of work in building lightweight power monitoring middleware that can be deployed across a range of systems. In this paper, we present cWatts+ as a prototype lightweight software-based virtual power meter. Utilizing a simple but powerful application-agnostic power model, it offers comparable performance to existing more complex and heavier-weight power models. It uses a small number of widely available CPU event counters and the Performance Application Programming Interface Library to estimate power usage on a per-thread basis. It has minimal overhead and is portable across a variety of systems. It can be used in containerized or virtualized environments. We evaluate the estimation performance of cWatts+ for a variety of real-world benchmarks that are relevant to large distributed systems. Also, we examine the importance of including CPU core temperature data in the power model. We demonstrate that our power model has an average error of less than 5%. This result compares favorably with existing state-of-the-art power models and is achieved using a relatively simple power model that exhibits minimal power consumption (overhead). Consequently, our power monitoring middleware is viable for use in real-world applications such as power estimation for energy-aware scheduling.