Analysis of the impact of using containerization techniques on application performance in Python

Abstract

This article comprehensively evaluates the impact of two containerization environments, Docker and Podman, on the performance of Python applications. The paper characterizes the two tools and presents the differences in their architectures. The scope of the study covers three aspects. The first is a comparison of resource usage, such as CPU usage, RAM usage and execution time, during the calculation of the number π. The next step is to analyse the resource usage when sorting an ordered list. The final aspect of the research is a comparison of the start-up time of the container in both environments. The tests carried out allow the presence of a performance overhead in both containerization environments, with an average of 8%. In addition, it can be seen that there is better resource management in the case of the Podman tool and a more dynamic environment in the case of the Docker tool.