Function-as-a-Service (FaaS) is one form of the serverless cloud computing paradigm and is defined through FaaS platforms (e.g., AWS Lambda) executing event-triggered code snippets (i.e., functions). Many studies that empirically evaluate the performance of such FaaS platforms have started to appear but we are currently lacking a comprehensive understanding of the overall domain. To address this gap, we conducted a multivocal literature review (MLR) covering 112 studies from academic (51) and grey (61) literature. We find that existing work mainly studies the AWS Lambda platform and focuses on micro-benchmarks using simple functions to measure CPU speed and FaaS platform overhead (i.e., container cold starts). Further, we discover a mismatch between academic and industrial sources on tested platform configurations, find that function triggers remain insufficiently studied, and identify HTTP API gateways and cloud storages as the most used external service integrations. Following existing guidelines on experimentation in cloud systems, we discover many flaws threatening the reproducibility of experiments presented in the surveyed studies. We conclude with a discussion of gaps in literature and highlight methodological suggestions that may serve to improve future FaaS performance evaluation studies.

中文翻译：

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功能即服务性能评估：多语种文献综述

功能即服务 (FaaS) 是无服务器云计算范式的一种形式，通过 FaaS 平台（例如 AWS Lambda）执行事件触发的代码片段（即函数）来定义。许多实证评估此类 FaaS 平台性能的研究已经开始出现，但我们目前缺乏对整个领域的全面了解。为了弥补这一差距，我们进行了一项多语文献综述 (MLR)，涵盖来自学术 (51) 和灰色 (61) 文献的 112 项研究。我们发现现有的工作主要研究 AWS Lambda 平台，并专注于使用简单函数来衡量 CPU 速度和 FaaS 平台开销（即容器冷启动）的微基准测试。此外，我们发现学术和工业来源在测试平台配置上不匹配，发现函数触发器仍然没有得到充分研究，并将 HTTP API 网关和云存储确定为最常用的外部服务集成。遵循现有的云系统实验指南，我们发现了许多威胁调查研究中提出的实验可重复性的缺陷。我们最后讨论了文献中的差距，并强调了可能有助于改进未来 FaaS 性能评估研究的方法论建议。