research-article

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

Authors:

Mario Cardarelli,

Ludovico Iovino,

Paolo Di Francesco,

Amleto Di Salle,

Ivano Malavolta,

Patricia LagoAuthors Info & Claims

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

Pages 1225 - 1234

https://doi.org/10.1145/3297280.3297400

Published: 08 April 2019 Publication History

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.

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Cited By

Li ZSaldías-Vallejos NSeco DRodríguez MRanjan R(2024)Long Live the Image: On Enabling Resilient Production Database Containers for Microservice ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2024.343662350:9(2363-2378)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3436623
Yılmaz RBuzluca F(2024)A fuzzy logic-based quality model for identifying microservices with low maintainabilityJournal of Systems and Software10.1016/j.jss.2024.112143216:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.112143
Bajaj DBharti UGupta IGupta PYadav A(2024)GTMicro—microservice identification approach based on deep NLP transformer model for greenfield developmentsInternational Journal of Information Technology10.1007/s41870-024-01766-516:5(2751-2761)Online publication date: 8-Mar-2024
https://doi.org/10.1007/s41870-024-01766-5
Show More Cited By

Index Terms

An extensible data-driven approach for evaluating the quality of microservice architectures
1. Applied computing
  1. Enterprise computing
    1. Service-oriented architectures
2. Software and its engineering
  1. Software notations and tools
    1. Context specific languages
      1. Domain specific languages
    2. Software maintenance tools

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cover image ACM Conferences

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

April 2019

2682 pages

ISBN:9781450359337

DOI:10.1145/3297280

Conference Chairs:
Chih-Cheng Hung
Kennesaw State University, Marietta, Georgia
,
George A. Papadopoulos
University of Cyprus, Nicosia, Cyprus

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGAPP: ACM Special Interest Group on Applied Computing

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Published: 08 April 2019

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SAC '19: The 34th ACM/SIGAPP Symposium on Applied Computing

April 8 - 12, 2019

Limassol, Cyprus

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Li ZSaldías-Vallejos NSeco DRodríguez MRanjan R(2024)Long Live the Image: On Enabling Resilient Production Database Containers for Microservice ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2024.343662350:9(2363-2378)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3436623
Yılmaz RBuzluca F(2024)A fuzzy logic-based quality model for identifying microservices with low maintainabilityJournal of Systems and Software10.1016/j.jss.2024.112143216:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.112143
Bajaj DBharti UGupta IGupta PYadav A(2024)GTMicro—microservice identification approach based on deep NLP transformer model for greenfield developmentsInternational Journal of Information Technology10.1007/s41870-024-01766-516:5(2751-2761)Online publication date: 8-Mar-2024
https://doi.org/10.1007/s41870-024-01766-5
Driessen FFerreira Pires LMoreira JVerhoeven Pvan den Bosch S(2024)A Quantitative Assessment Method for Microservices Granularity to Improve MaintainabilityEnterprise Design, Operations, and Computing. EDOC 2023 Workshops10.1007/978-3-031-54712-6_13(211-226)Online publication date: 2-Mar-2024
https://doi.org/10.1007/978-3-031-54712-6_13
Salii SAjdari JZenuni X(2023)Migrating to a microservice architecture: benefits and challenges2023 46th MIPRO ICT and Electronics Convention (MIPRO)10.23919/MIPRO57284.2023.10159894(1670-1677)Online publication date: 22-May-2023
https://doi.org/10.23919/MIPRO57284.2023.10159894
Tapia VGaona C(2023)Research Opportunities in Microservices Quality Assessment: A Systematic Literature ReviewJournal of Advances in Information Technology10.12720/jait.14.5.991-100214:5(991-1002)Online publication date: 2023
https://doi.org/10.12720/jait.14.5.991-1002
Silva STuyishime ASantilli TPelliccione PIovino L(2023)Quality Metrics in Software Architecture2023 IEEE 20th International Conference on Software Architecture (ICSA)10.1109/ICSA56044.2023.00014(58-69)Online publication date: Mar-2023
https://doi.org/10.1109/ICSA56044.2023.00014
Rosa TGuerra ECorreia FGoldman A(2023)CharM — Evaluating a model for characterizing service-based architecturesJournal of Systems and Software10.1016/j.jss.2023.111826206:COnline publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111826
Milić MMakajić-Nikolić D(2022)Development of a Quality-Based Model for Software Architecture Optimization: A Case Study of Monolith and Microservice ArchitecturesSymmetry10.3390/sym1409182414:9(1824)Online publication date: 2-Sep-2022
https://doi.org/10.3390/sym14091824
Peng XZhang CZhao ZIsami AGuo XCui YRoychoudhury ACadar CKim M(2022)Trace analysis based microservice architecture measurementProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558951(1589-1599)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3540250.3558951
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