商用无服务器计算平台的特征
Characterizing Commodity Serverless Computing Platforms
摘要：
无服务器计算已经成为云计算的一个新的趋势范例，允许开发人员专注于核心应用逻辑的开发，并通过独立功能的组合快速构建原型。随着无服务器计算的发展和繁荣，各大云供应商纷纷推出其商用无服务器计算平台。然而，这些平台的特性还没有得到系统的研究。衡量这些特征可以帮助开发人员选择最合适的无服务器计算平台，并以正确的方式开发基于无服务器的应用程序。为了填补这一知识空白，我们对主流商品无服务器计算平台进行了全面的研究，包括AWS Lambda，Google Cloud Functions，Azure Functions和Alibaba Cloud Function Compute。具体而言，我们进行定性分析和定量分析。在定性分析中，我们从三个方面（即，开发、部署和运行时）基于其官方文档来构建特征分类法。在定量分析中，我们从多个维度分析这些平台的运行时性能，并设计了良好的基准测试。首先，我们分析了影响基于无服务器的应用程序启动延迟的三个关键因素。其次，我们用16个有代表性的基准比较了不同平台的资源效率。最后，我们测量了它们在处理不同并发请求时的性能差异，并以黑盒方式探索了潜在的原因。基于定性和定量分析的结果，我们得出了一系列的发现，并为开发人员和云供应商提供了有见地的影响。
英文摘要：
Serverless computing has become a new trending paradigm in cloud computing, allowing developers to focus on the development of core application logic and rapidly construct the prototype via the composition of independent functions. With the development and prosperity of serverless computing, major cloud vendors have successively rolled out their commodity serverless computing platforms. However, the characteristics of these platforms have not been systematically studied. Measuring these characteristics can help developers to select the most adequate serverless computing platform and develop their serverless-based applications in the right way. To fill this knowledge gap, we present a comprehensive study on characterizing mainstream commodity serverless computing platforms, including AWS Lambda, Google Cloud Functions, Azure Functions, and Alibaba Cloud Function Compute. Specifically, we conduct both qualitative analysis and quantitative analysis. In qualitative analysis, we compare these platforms from three aspects (i.e., development, deployment, and runtime) based on their official documentation to construct a taxonomy of characteristics. In quantitative analysis, we analyze the runtime performance of these platforms from multiple dimensions with well-designed benchmarks. First, we analyze three key factors that can influence the startup latency of serverless-based applications. Second, we compare the resource efficiency of different platforms with 16 representative benchmarks. Finally, we measure their performance difference when dealing with different concurrent requests, and explore the potential causes in a black-box fashion. Based on the results of both qualitative and quantitative analysis, we derive a series of findings and provide insightful implications for both developers and cloud vendors.
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。
