Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1050
Title: A Network Science-Based Approach for an Optimal Microservice Governance
Authors: Siriwardhana, G. S
De Silva, N
Jayasinghe, L. S
Vithanage, L
Kasthurirathna, D
Keywords: Network Science-Based
Science-Based Approach
Optimal Microservice
Governance
Issue Date: 10-Dec-2020
Publisher: IEEE
Citation: G. S. Siriwardhana, N. De Silva, L. S. Jayasinghe, L. Vithanage and D. Kasthurirathna, "A Network Science-Based Approach for an Optimal Microservice Governance," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 357-362, doi: 10.1109/ICAC51239.2020.9357232.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Vol 1 Pages 357-362
Abstract: In today's world of software application development, Kubernetes has emerged as one of the most effective microservice deployment technologies presently available due to its exceptional ability to deploy and orchestrate containerized microservices. However, a common issue faced in such orchestration technologies is the employment of vast arrays of disjoint monitoring solutions that fail to portray a holistic perspective on the state of microservice deployments, which consequently inhibit the creation of more optimized deployment policies. In response to this issue, this publication proposes the use of a network science-based approach to facilitate the creation of a microservice governance model that incorporates the use of dependency analysis, load prediction, centrality analysis, and resilience evaluation to effectively construct a more holistic perspective on a given microservice deployment. Furthermore, through analysis of the factors mentioned above, the research conducted, then proceeds to create an optimized deployment strategy for the deployment with the aid of a developed optimization algorithm. Analysis of results revealed the developed governance model aided through the utilization of the developed optimization algorithm proposed in this publication, proved to be quite effective in the generation of optimized microservice deployment policies.
URI: http://rda.sliit.lk/handle/123456789/1050
ISBN: 978-1-7281-8412-8
Appears in Collections:Department of Computer Science and Software Engineering-Scopes
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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