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Conference Papers Year : 2021

Automated performance prediction of microservice applications using simulation

Abstract

Microservices transform monolithic applications into simple, scalable, and interacting services. It allows for faster development and fine-grained deployments. However, the cooperation of several services leads to intricate dependencies, hindering the detection of performance bottlenecks. Current microservice performance analysis methods require real deployments, a costly process both in time and resources, while performance prediction through simulation relies on models that are complex to develop and instantiate. In this paper, we propose a microservice performance analysis approach based on simulation. Our contribution first introduces a microservice performance model requiring few instantiation parameters. We then propose a methodology to automatically derive model instantiation values from a single execution trace. We evaluate this methodology on two benchmarks from the literature. Our approach accurately predicts the deployment performance of large-scale microservice applications in various configurations from a single execution trace. This provides valuable insights on the performance of an application prior to its deployment on real platform.
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Dates and versions

hal-03389508 , version 1 (21-10-2021)

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Clément Courageux-Sudan, Anne-Cécile Orgerie, Martin Quinson. Automated performance prediction of microservice applications using simulation. MASCOTS 2021 - International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Nov 2021, virtually, France. pp.1-8, ⟨10.1109/MASCOTS53633.2021.9614260⟩. ⟨hal-03389508⟩
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