Improving QoS of Microservices Architecture Using Machine Learning Techniques

被引：0
|
作者：
Kaushik, Neha [1 ]
机构：
[1] JC Bose Univ Sci & Technol, Faridabad, India
来源：
SOFTWARE ARCHITECTURE, ECSA 2024 TRACKS AND WORKSHOPS | 2024年 / 14937卷
关键词：
Microservices architecture (MSA); Quality of Service (QoS); Performance; Reliability;
D O I：
10.1007/978-3-031-71246-3_9
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Microservices architecture has gained significant popularity in the development of modern software applications due to its scalability, flexibility, and modularity. However, ensuring high-quality service delivery while maintaining the agility and responsiveness of microservices poses several challenges. This paper introduces an innovative method aimed at enhancing the Quality of Service (QoS) in microservices architecture-driven applications through the utilization of machine learning techniques. Initially, the primary factors contributing to the overall quality of microservices applications are identified. Subsequently, a machine learning-based framework is proposed for enhancing the QoS of such applications. To validate this framework, experimental assessments are conducted using sample microservices applications as case studies. The outcomes of these experiments demonstrate a significant enhancement in the overall QoS of the microservices application facilitated by the proposed framework.
引用
收藏
页码：72 / 79
页数：8
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