A Modular Approach to Calculate Service-Based Maintainability Metrics from Runtime Data of Microservices

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Abstract

While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice-based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.

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Bogner, J., Schlinger, S., Wagner, S., & Zimmermann, A. (2019). A Modular Approach to Calculate Service-Based Maintainability Metrics from Runtime Data of Microservices. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11915 LNCS, pp. 489–496). Springer. https://doi.org/10.1007/978-3-030-35333-9_34

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