A Formal Methodology for Workload-Driven Comparative Evaluation of Cloud Infrastructure Architectures

Abstract

In this paper we propose a formal approach for workload-driven comparative evaluation of cloud infrastructure architectures that support objective architectural decision making in dynamic operating scenarios. The novelty of the work is an integrated framework, which combines cost modeling that is workload dependent, autoscaling behavior, dynamic pricing models and infrastructure as code (IaC)-based representations of architectures in one single evaluation methodology. Different to former approaches which employ pricing calculation tools that fix the prices, or report individual cost measures, or use expertise of humans, the proposed approach represents architectural candidates as scenario-dependent systems, which are able to provide accurate cost and performance estimation based on the intensity of workload and scaling dynamics. Real architectures instead of just infrastructure models can be evaluated by formally representing an IaC configuration in terms of the used analytic cost and performance models. We evaluate our methodology using production data of a real-world application and prove our model has a 94% accuracy in estimating costs and significantly reduce architectural design and evaluation time.