BIAS Autoscaler: Leveraging Burstable Instances for Cost-Effective Autoscaling on Cloud Systems

Burstable instances have recently been introduced by cloud providers as a cost-efficient alternative to customers that do not require powerful machines for running their workloads. Unlike conventional instances, the CPU capacity of burstable instances is rate limited, but they can be boosted to their full capacity for small periods when needed. Currently, the majority of cloud providers offer this option as a cheaper solution for their clients. However, little research has been done on the practical usage of these CPU-limited instances. In this paper, we present a novel autoscaling solution that uses burstable instances along with regular instances to handle the queueing arising in traffic and flash crowds. We design BIAS Autoscaler, a state-of-the-art framework that leverages burstable and regular instances for cost-efficient autoscaling and evaluate it on the Google Cloud Platform. We apply our framework to a real-world microservice workload, and conduct extensive experimental evaluations using Google Compute Engines. Experimental results show that BIAS Autoscaler can reduce the overall cost up to 25% and increase resource efficiency by 42% while maintaining the same service quality observed when using conventional instances only.