Bursting with Possibilities -- An Empirical Study of Credit-Based Bursting Cloud Instance Types

Abstract

We study the performance and cost efficiency as perceived by the end user of a specific class of Infrastructure-as-a-Service (IaaS) cloud instances, namely credit-based bursting instances. This class of instance types has been introduced by Amazon EC2 in summer 2014, and behaves on a fundamental level differently than any other existing instance type, either from EC2 or other vendors. We introduce a basic formal model for fostering the understanding and analysis of these types, and empirically study their performance in practice. Further, we compare the performance of credit-based bursting cloud instance types to existing general-purpose types, and derive potential use cases for practitioners. Our results indicate that bursting instance types are cost-efficient for CPU-bound applications with an average utilization of less than 40%, as well as for non-critical IO-bound applications. Finally, we also discuss a simple boosting scheme that enables practitioners to improve the cost efficiency of their bursting instance usage under given constraints.