Automated QoS-oriented cloud resource optimization using containers

Yu Sun, Jules White, Bo Li, Michael Walker, Hamilton A. Turner

Abstract: Optimizing the deployment of software in a cloud environment is one approach for maximizing system Quality-of-Service (QoS) and minimizing total cost. A traditional challenge to this optimization is the large amount of benchmarking required to optimize even simplistic cloud systems. This paper introduces $$\hbox {C}^2$$ C 2 RAM, an new approach to enable rapid, optimized deployment of software onto a cloud environment by substantially reducing the number of benchmarks required. $$\hbox {C}^2$$ C 2 RAM continues to perform some benchmarking, and therefore its predictions of application QoS metrics, such as throughput and latency, are very accurate. Our results show a maximum difference of 1.06 % between $$\hbox {C}^2$$ C 2 RAM predicted QoS and empirically measured QoS. Moreover, $$\hbox {C}^2$$ C 2 RAM can be provided with QoS requirements for each software in the system, and will ensure that each requirement is met before presenting a deployment plan.