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Scalability Assessment of Microservice Architecture Deployment Configurations: A Domain-based Approach Leveraging Operational Profiles and Load Tests
Journal of Systems and Software ( IF 3.7 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.jss.2020.110564
Alberto Avritzer , Vincenzo Ferme , Andrea Janes , Barbara Russo , André van Hoorn , Henning Schulz , Daniel Menasché , Vilc Rufino

Abstract Microservices have emerged as an architectural style for developing distributed applications. Assessing the performance of architecture deployment configurations — e.g., with respect to deployment alternatives — is challenging and must be aligned with the system usage in the production environment. In this paper, we introduce an approach for using operational profiles to generate load tests to automatically assess scalability pass/fail criteria of microservice configuration alternatives. The approach provides a Domain-based metric for each alternative that can, for instance, be applied to make informed decisions about the selection of alternatives and to conduct production monitoring regarding performance-related system properties, e.g., anomaly detection. We have evaluated our approach using extensive experiments in a large bare metal host environment and a virtualized environment. First, the data presented in this paper supports the need to carefully evaluate the impact of increasing the level of computing resources on performance. Specifically, for the experiments presented in this paper, we observed that the evaluated Domain-based metric is a non-increasing function of the number of CPU resources for one of the environments under study. In a subsequent series of experiments, we investigate the application of the approach to assess the impact of security attacks on the performance of architecture deployment configurations.

中文翻译:

微服务架构部署配置的可扩展性评估:利用操作配置文件和负载测试的基于域的方法

摘要 微服务已成为开发分布式应用程序的一种架构风格。评估架构部署配置的性能——例如,关于部署备选方案——具有挑战性,必须与生产环境中的系统使用保持一致。在本文中,我们介绍了一种使用操作配置文件生成负载测试的方法,以自动评估微服务配置替代方案的可扩展性通过/失败标准。该方法为每个备选方案提供了一个基于域的度量,例如,可以应用该指标做出关于备选方案选择的明智决定,并针对与性能相关的系统属性进行生产监控,例如异常检测。我们在大型裸机主机环境和虚拟化环境中使用大量实验评估了我们的方法。首先,本文提供的数据支持仔细评估提高计算资源水平对性能的影响的需要。具体而言,对于本文中介绍的实验,我们观察到评估的基于域的指标是所研究环境之一的 CPU 资源数量的非递增函数。在随后的一系列实验中,我们研究了该方法的应用,以评估安全攻击对架构部署配置性能的影响。本文中提供的数据支持仔细评估提高计算资源水平对性能的影响的必要性。具体而言,对于本文中介绍的实验,我们观察到评估的基于域的指标是所研究环境之一的 CPU 资源数量的非递增函数。在随后的一系列实验中,我们研究了该方法的应用,以评估安全攻击对架构部署配置性能的影响。本文中提供的数据支持仔细评估提高计算资源水平对性能的影响的必要性。具体而言,对于本文中介绍的实验,我们观察到评估的基于域的指标是所研究环境之一的 CPU 资源数量的非递增函数。在随后的一系列实验中,我们研究了该方法的应用,以评估安全攻击对架构部署配置性能的影响。
更新日期:2020-07-01
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