功能即服务性能评估：一个多域的文献综述
Function-as-a-Service Performance Evaluation: A Multivocal Literature Review
摘要：
功能即服务（FaaS）是无服务器云计算范例的一种形式，并且通过FaaS平台（例如，AWS Lambda）执行事件触发的代码片段（即，职能）。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。为了解决这一差距，我们进行了一项多目标文献综述（MLR），涵盖了来自学术（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测量CPU速度和FaaS平台开销的微基准测试（即，容器冷启动）。此外，我们发现在测试平台配置上学术和工业来源之间存在不匹配，发现功能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。根据现有的云系统实验指南，我们发现许多缺陷威胁到调查研究中提出的实验的可重复性。最后，我们讨论了文献中的差距，并强调了可能有助于改善未来FaaS性能评估研究的方法建议。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
