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arXiv 2301.06508cs.SE
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使用机器学习技术自动迁移到微服务架构

Automate migration to microservices architecture using Machine Learning techniques

Meryam Chaieb, Mohamed Aymen Saied

摘要:

微服务架构风格具有许多优点,例如可扩展性,可重用性和易于维护性。因此,微服务已成为开发新应用程序时的流行架构选择。获得这些好处需要重新设计单片应用程序,并将其迁移到基于微服务的架构。这个过程本身就很复杂,成本也很高,因此自动化这项任务至关重要。该项目提出了一种方法,通过该方法可以从给定的单片应用程序中识别潜在的微服务,同时将此问题视为集群主题。我们的方法将源应用程序的源代码作为输入,以便应用不同的方法将一个盒子应用程序设计到不同的微服务中。在本报告中,我们详细介绍了这些技术,同时完成了结果的讨论和比较。

英文摘要:

The microservice architectural style has many advantages such as scalability, reusability, and easy maintainability. Microservices have therefore become a popular architectural choice when developing new applications. Reaping these benefits requires redesigning the monolithic application and moving them to a microservices-based architecture. This process is inherently complex and costly, so automating this task is critical. This project proposes a method by which potential microservices can be identified from a given monolithic application while treating this problem as a clustering thematic. Our method takes as input the source code of the source application in order to apply different approaches to devise the one box application into its different microservices. In this report we detail each of these techniques while finishing with a discussion and comparison of the results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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