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Object-Aware identification of microservices

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

45 Scopus citations

Abstract

Microservices is an architectural style inspired by service-oriented computing that structures an application as a collection of cohesive and loosely coupled components, which implement business capabilities. One of today's problems in designing microservice architectures is to decompose a system into cohesive, loosely coupled, and fine-grained microservices. Identification of microservices is usually performed intuitively, based on the experience of the system designers, however, if the functionalities of a system are highly interconnected, it is a challenging task to decompose the system into appropriate microservices. To tackle this challenge, we present a microservice identification method that decomposes a system using clustering technique. To this end, we model a system as a set of business processes and take two aspects of structural dependency and data object dependency of functionalities into account. Furthermore, we conduct a study to evaluate the effect of process characteristics on the accuracy of identification approaches.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages253-256
Number of pages4
ISBN (Print)9781538672501
DOIs
StatePublished - Sep 5 2018
Event2018 IEEE International Conference on Services Computing, SCC 2018 - San Francisco, United States
Duration: Jul 2 2018Jul 7 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services

Conference

Conference2018 IEEE International Conference on Services Computing, SCC 2018
Country/TerritoryUnited States
CitySan Francisco
Period07/2/1807/7/18

Keywords

  • Business Process
  • Clustering
  • Identification
  • Microservice

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