Scalability Assessment of Microservice Architecture Deployment Configurations: A Domain-based Approach Leveraging Operational Profiles and Load Tests

•Scalability testing approach for microservices based on operational profiles.•Domain-based metric for comparing scalability of architecture deployment alternatives.•PPTAM framework implementing the approach and the metric for production environments.•Lab experiments to analyze the sensitivity of th...

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Veröffentlicht in:The Journal of systems and software 2020-07, Vol.165, p.110564, Article 110564
Hauptverfasser: Avritzer, Alberto, Ferme, Vincenzo, Janes, Andrea, Russo, Barbara, Hoorn, André van, Schulz, Henning, Menasché, Daniel, Rufino, Vilc
Format: Artikel
Sprache:eng
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Zusammenfassung:•Scalability testing approach for microservices based on operational profiles.•Domain-based metric for comparing scalability of architecture deployment alternatives.•PPTAM framework implementing the approach and the metric for production environments.•Lab experiments to analyze the sensitivity of the Domain-based metric.•Application of the approach and metric for scalability and security assessment. Microservices have emerged as an architectural style for developing distributed applications. Assessing the performance of architecture deployment configurations — e.g., with respect to deployment alternatives — is challenging and must be aligned with the system usage in the production environment. In this paper, we introduce an approach for using operational profiles to generate load tests to automatically assess scalability pass/fail criteria of microservice configuration alternatives. The approach provides a Domain-based metric for each alternative that can, for instance, be applied to make informed decisions about the selection of alternatives and to conduct production monitoring regarding performance-related system properties, e.g., anomaly detection. We have evaluated our approach using extensive experiments in a large bare metal host environment and a virtualized environment. First, the data presented in this paper supports the need to carefully evaluate the impact of increasing the level of computing resources on performance. Specifically, for the experiments presented in this paper, we observed that the evaluated Domain-based metric is a non-increasing function of the number of CPU resources for one of the environments under study. In a subsequent series of experiments, we investigate the application of the approach to assess the impact of security attacks on the performance of architecture deployment configurations.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2020.110564