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An Approach to Evolving Legacy Enterprise System to Microservice-Based Architecture through Feature-Driven Evolution Rules

Habibullah, Safa; Liu, Xiaodong; Tan, Zhiyuan

Authors

Safa Habibullah



Abstract

Evolving legacy enterprise systems into a lean system architecture has been on the agendas of many enterprises. Recent advance in legacy system evaluation is in favour of microservice technologies, which not only significantly reduce the complexity in deployment of enterprise systems but also enhance the availability of services to system users. However, there are technical challenges to overcome towards a successful transformation. Challenges, relating to information security, container optimisation, the performance of a new system and its deployment, are particularly under concern. To
cope with these technical challenges, a new approach is proposed
in this paper to govern the evolution of legacy systems into a
microservice-based and cloud-hosted architecture. This approach includes a detailed working process, a set of transformation rules towards microservices and their repositories. In addition, a conceptual framework is drawn to provide a comprehensive illustration to this evolution approach. Moreover, a case study is presented to demonstrate the application of the proposed approach on the evaluation of a chosen legacy system, as well as the procedure of system architecture optimisation.

Journal Article Type Article
Acceptance Date Nov 30, 2017
Publication Date 2018-10
Deposit Date Feb 5, 2018
Publicly Available Date Feb 6, 2018
Journal International Journal of Computer Theory and Engineering
Print ISSN 1793-8201
Publisher IACSIT Press
Peer Reviewed Peer Reviewed
Volume 10
Issue 5
Pages 164-169
DOI https://doi.org/10.7763/ijcte.2018.v10.1219
Keywords cloud computing, enterprise system, feature-driven evolution rules, microservices
Public URL http://researchrepository.napier.ac.uk/Output/1034494
Additional Information The paper was accepted by the 2018 the International Conference on Software and Services Engineering (ICSSE 2018), which provides two options for the publication source: in the conference proceedings or in the International Journal of Computer Theory and Engineering (IJCTE) (ISSN: 1793-8201). We selected the journal to publish it.
Contract Date Feb 5, 2018

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