Performance Evaluation of an API Stock Exchange Web System on Cloud Docker Containers

Abstract

This study aims to identify the most effective input parameters for performance modelling of container-based web systems. We introduce a method using queueing Petri nets to model web system performance for containerized structures, leveraging prior measurement data for resource demand estimation. This approach eliminates intrusive interventions in the production system. Our research evaluates the accuracy of various formal estimation methods, pinpointing the most suitable for container environments. With the use of a stock exchange web system benchmark for data collection and simulation verification, our findings reveal that the proposed method ensures precise response time parameter accuracy for such architectural configurations.