ISSN 2587-814X (print), Russian version: ISSN 1998-0663 (print), |
Alexey Doljenko 1, Irina Shpolianskaya1, Sergey Glushenko1Fuzzy production network model for quality assessment of an information system based on microservices
2020.
No. 4 Vol.14.
P. 36–46
[issue contents]
This article describes the analysis of the quality of microservice architectures, which are one of the main approaches to the creation and maintenance of modern information systems capable of quickly respond to changes in business demands. The implementation of continuous delivery of software components for dynamic business processes of information systems can be carried out by various sets of microservices, the optimal choice of which is a complex multi-alternative task. The paper presents a review of existing approaches to solving the problem, which showed that the development of models for assessing the quality of microservices of information systems requires further elaboration in terms of accounting for uncertainty in the initial data and modes of operation. The authors have proposed an approach to solving the problem of analyzing the quality of a microservice architecture which is implemented on the basis of a fuzzy production network model. The model allows for comprehensive accounting of various parameters (qualitative and quantitative).The article shows the implementation process of the fuzzy production network that was developed to analyze the functional quality of the microservice architecture for processing customer orders using fuzzy modeling software.The results of the analysis will allow managers and system architects to make an informed choice of the microservice architecture of the information system, as well as use it in their reports when arguing the need for scaling the system and increasing the availability of microservices.
Citation:
Doljenko A.I., Shpolianskaya I.Yu., Glushenko S.A. (2020) Fuzzy production network model for quality assessment of an information system based on microservices. Business Informatics, vol. 14, no 4, pp. 36–46. DOI: 10.17323/2587-814X.2020.4.36.46
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