Towards Carbon-aware: Power Monitoring in Cloud Computing

Abstract

The escalating adoption of cloud computing has not only bring significant values in terms of technology, but also sparked critical concerns regarding its environmental footprint. Together with the advantages cloud services provide, there exist issues from the energy consumption management and its impacts on the planet. The vast data centers required to support cloud services consume significant amounts of energy, much of which is derived from non-renewable sources, contributing to greenhouse effect. Additionally, the manufacturing, operation, and disposal of hardware result in substantial ecological impacts, including resource depletion and electronic waste.

The thesis delves into to the energy efficiency and sustainability of cloud computing environments by analyzing data collected from monitoring tools deployed in customized cluster, aiming to examine the role of monitoring tools in managing computing systems.

The research centers on comprehending the functionality of monitoring tools and assessing their performance within this context. By scrutinizing key metrics such as CPU time, CPU cycles, and energy consumption patterns, the study provides insights into the factors that influence overall system performance and costs.

The findings underscore the potential of monitoring tools such as Kepler to optimize resource allocation and enhance energy efficiency. The study also identifies limitations in the current state of monitoring tools and emphasizes the necessity for further development to capture a more representative set of system metrics. The analysis highlights the significance of exploring innovative approaches to sustainable cloud computing, such as developing and committing to energy-efficient architectures, optimizing cooling systems, and implementing effective methods to achieve the sustainability.