Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for building scalable and cost-efficient microservices and applications. However, the quickly moving technology hinders reproducibility, and the lack of a standardized benchmarking suite leads to ad-hoc solutions and microbenchmarks being used in serverless research, further complicating metaanalysis and comparison of research solutions. To address this challenge, we propose the Serverless Benchmark Suite: the first benchmark for FaaS computing that systematically covers a wide spectrum of cloud resources and applications. Our benchmark consists of the specification of representative workloads, the accompanying implementation and evaluation infrastructure, and the evaluation methodology that facilitates reproducibility and enables interpretability. We demonstrate that the abstract model of a FaaS execution environment ensures the applicability of our benchmark to multiple commercial providers such as AWS, Azure, and Google Cloud. Our work facilities experimental evaluation of serverless systems, and delivers a standardized, reliable and evolving evaluation methodology of performance, efficiency, scalability and reliability of middleware FaaS platforms.
翻译:功能-服务(Faas-as-Service)是未来云服务最有希望的方向之一,没有服务器的功能立即成为建设可扩缩和具有成本效益的微服务和应用程序的新的中间工具,然而,快速移动的技术阻碍可复制,缺乏标准化的基准套件导致在无服务器的研究中使用了临时热解和微型基准,进一步使元分析和研究解决办法的比较复杂化。为了应对这一挑战,我们提议了无服务器基准套件:FaaS计算的第一个基准,它系统地涵盖广泛的云资源和应用程序。我们的基准包括有代表性的工作量、配套的执行和评价基础设施以及有助于可复制和可解释的评价方法。我们证明,FaS执行环境的抽象模型确保了我们的基准适用于多种商业供应商,如AWS、Azure和Googlod。我们的工作设施对没有服务器的系统进行了实验性评估,并提供了一种标准化、可靠和不断发展的FaaAS中软件平台绩效、效率、可缩放性和可靠性的评价方法。