从单体到微服务的自动性能监控和回归测试

Andrea Janes, B. Russo
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引用次数: 15

摘要

从单体到微服务的转变带来了一些挑战,比如如何在不同的微服务上重新分配系统的特性。在转换期间,开发人员还可能重新设计或重新考虑系统服务,这可能对最终系统的各个质量方面产生强烈的影响。因此,新系统的性能好坏取决于开发人员设计微服务的能力和微服务架构表示系统的能力。总的来说,过渡到微服务可能会也可能不会得到相同或更好的系统。控制向微服务迁移的一种方法是通过持续收集性能数据并将结果数据分析反馈到转换过程中来持续监控系统。在DevOps中,这种持续的反馈可以用来重新调整系统构建的开发和部署。在本文中,我们介绍了PPTAM+,这是一个在向微服务过渡期间持续评估系统退化的工具。在生产系统中,该工具可以持续监控每个微服务,并提供性能损失和整体退化的指示。该系统旨在集成在DevOps流程中。该工具自动化了整个过程,从为构建参考操作概要文件收集数据到简化性能数据,并根据从前一个构建的测试中获得的分析反馈自动调整和回归每个构建的性能测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Performance Monitoring and Regression Testing During the Transition from Monolith to Microservices
The transition from monolith to microservices poses several challenges, like how to redistribute the features of system over different microservices. During the transition, developers may also redesign or rethink system services significantly, which can have a strong impact on various quality aspects of the resulting system. Thus, the new system may be more or less performing depending on the ability of the developers to design microservices and the capability of the microservice architecture to represent the system. Overall, a transition to microservices may or may not end up with the same or a better performing system. One way to control the migration to microservices is to continuously monitor a system by continuously collecting performance data and feeding the resulting data analysis back in the transition process. In DevOps, such continuous feedback can be exploited to re-tune the development and deployment of system's builds. In this paper, we present PPTAM+, a tool to continuously assess the degradation of a system during a transition to microservices. In an in-production system, the tool can continuously monitor each microservice and provide indications of lost performance and overall degradation. The system is designed to be integrated in a DevOps process. The tool automates the whole process from collecting data for building the reference operational profile to streamline performance data and automatically adapt and regress performance tests on each build based the analysis' feedback obtained from tests of the previous build.
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