An extensible data-driven approach for evaluating the quality of microservice architectures

Mario Cardarelli, Amleto Di Salle, Ludovico Iovino, Ivano Malavolta, Paolo Di Francesco, Patricia Lago

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Microservice architecture (MSA) is defined as an architectural style where the software system is developed as a suite of small services, each running in its own process and communicating with lightweight mechanisms. The benefits of MSA are many, ranging from an increase in development productivity, to better business-IT alignment, agility, scalability, and technology flexibility. The high degree of microservices distribution and decoupling is, however, imposing a number of relevant challenges from an architectural perspective. In this context, measuring, controlling, and keeping a satisfactory level of quality of the system architecture is of paramount importance. In this paper we propose an approach for the specification, aggregation, and evaluation of software quality attributes for the architecture of microservice-based systems. The proposed approach allows developers to (i) produce architecture models of the system, either manually or automatically via recovering techniques, (ii) contribute to an ecosystem of well-specified and automatically-computable software quality attributes for MSAs, and (iii) continuously measure and evaluate the architecture of their systems by (re-)using the software quality attributes defined in the ecosystem. The approach is implemented by using Model-Driven Engineering techniques. The current implementation of the approach has been validated by assessing the maintainability of a third-party, publicly available benchmark system.

LanguageEnglish
Title of host publicationProceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019
Place of PublicationLimassol
PublisherACM
Pages1225-1234
Number of pages10
ISBN (Print)9781450359337
DOIs
Publication statusPublished - 8 Apr 2019
Event34th Annual ACM Symposium on Applied Computing, SAC 2019 - Limassol, Cyprus
Duration: 8 Apr 201912 Apr 2019

Conference

Conference34th Annual ACM Symposium on Applied Computing, SAC 2019
CountryCyprus
CityLimassol
Period8/04/1912/04/19

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Ecosystems
Maintainability
Scalability
Agglomeration
Productivity
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Keywords

  • Architecture recovery
  • Microservices
  • Model-Driven
  • Software quality

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Cite this

Cardarelli, M., Di Salle, A., Iovino, L., Malavolta, I., Di Francesco, P., & Lago, P. (2019). An extensible data-driven approach for evaluating the quality of microservice architectures. In Proceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019 (pp. 1225-1234). Limassol: ACM. https://doi.org/10.1145/3297280.3297400
Cardarelli, Mario ; Di Salle, Amleto ; Iovino, Ludovico ; Malavolta, Ivano ; Di Francesco, Paolo ; Lago, Patricia. / An extensible data-driven approach for evaluating the quality of microservice architectures. Proceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019. Limassol : ACM, 2019. pp. 1225-1234
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Cardarelli, M, Di Salle, A, Iovino, L, Malavolta, I, Di Francesco, P & Lago, P 2019, An extensible data-driven approach for evaluating the quality of microservice architectures. in Proceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019. ACM, Limassol, pp. 1225-1234, 34th Annual ACM Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, 8/04/19. https://doi.org/10.1145/3297280.3297400

An extensible data-driven approach for evaluating the quality of microservice architectures. / Cardarelli, Mario; Di Salle, Amleto; Iovino, Ludovico; Malavolta, Ivano; Di Francesco, Paolo; Lago, Patricia.

Proceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019. Limassol : ACM, 2019. p. 1225-1234.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Cardarelli M, Di Salle A, Iovino L, Malavolta I, Di Francesco P, Lago P. An extensible data-driven approach for evaluating the quality of microservice architectures. In Proceedings of the 34th Annual ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 08-12, 2019. Limassol: ACM. 2019. p. 1225-1234 https://doi.org/10.1145/3297280.3297400