A Study of Contributing Factors to Power Aware Vertical Scaling of Deadline Constrained Applications

Abstract

The adoption of virtualization technologies in datacenters has increased dramatically in the past decade. Clouds have pivoted from being just an infrastructure rental to offering platforms and solutions, made possible by having several layers of abstraction, providing internal and external users the ability to focus on core business logic. Efficient resource management has in turn become salient in ensuring operational efficiency. In this work, we study key factors that can influence vertical scaling decisions, propose a policy to vertically scale deadline constrained applications and surface our findings from experimentation. We observe that (a) the duration for which an application is profiled has an almost cyclic influence on the accuracy of behavior predictions and is inversely proportional to the time spent consuming backlog, (b) the duration for which an application is scaled can help achieve up to a 9.6% and 4.2% reduction in the 75th and 95th percentile of power usage respectively, (c) reducing the tolerance towards accrual of backlog influences the application execution time and can reduce the number of SLA violations by 50% or 100% at times and (d) increasing the time to deadline offers power saving opportunities and can help achieve a 9.3% improvement in the 75th percentile of power usage.