ACMES team

Samovar lab

Automated performance prediction of microservice applications using simulation

Reading group: Henrique Medeiros presented "Automated performance prediction of microservice applications using simulation" (MASCOTS'21) at 1A330 the 15/12/2023 at 10h25.


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.