容器和功能即服务架构中的微服务性能

C. Canali, R. Lancellotti, Pietro Pedroni
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引用次数: 1

摘要

功能即服务(FaaS)是一种新的基于云的计算模型,它承诺相对于容器即服务(CaaS)等其他云范式而言,微服务的部署更具成本效益。但是,在FaaS方法下服务的请求通常会遇到冷启动条件,这种情况发生在第一次执行非活动功能并且必须重新设置容器环境时。在这种情况下,性能会下降,响应时间会增加。本文针对两个单独提供的微服务,对功能即服务模型的性能进行了分析。具体来说,我们对通过OpenWhisk实现的功能即服务模型进行了性能评估,并将其作为基准与使用Docker实现的容器即服务方法进行了比较。我们的分析侧重于与响应时间和主要服务器资源(如CPU和内存)使用情况相关的指标。为了进行性能比较,我们分别利用了基于人脸识别和图像转换的两种不同的微服务,以评估人工智能和多媒体应用中流行和现代服务的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microservice Performance in Container- and Function-as-a-Service Architectures
Function-as-a-Service (FaaS) is a new cloud-based computing model that promises a more cost-efficient deployment of microservices with respect to other cloud paradigms, like Container-as-a-Service (CaaS). However, requests served under a FaaS approach often experience a cold start condition, that occurs when the execution of an inactive function occurs for the first time and a container environment has to be set up afresh. In such cases, performance deteriorates and response times increase. This paper proposes an analysis of the performance of the Function-as-a-Service model for two single offered microservices. Specifically, we carry out a performance evaluation of the Function-as-a-Service model, implemented through OpenWhisk, using as a baseline for comparison the Container-as-a-Service approach, implemented with Docker. Our analysis focuses on metrics related to the response time and to the usage of main server resources such as CPU and memory. For the performance comparison, we exploited two different microservices based on face recognition and image conversion, respectively, in order to evaluate the performance over popular and modern kinds of services included in artificial intelligence and multimedia applications.
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