Serverless computing is increasingly popular because of its lower cost and easier deployment. Several cloud service providers (CSPs) offer serverless computing on their public clouds, but it may bring the vendor lock-in risk. To avoid this limitation, many open-source serverless platforms come out to allow developers to freely deploy and manage functions on self-hosted clouds. However, building effective functions requires much expertise and thorough comprehension of platform frameworks and features that affect performance. It is a challenge for a service developer to differentiate and select the appropriate serverless platform for different demands and scenarios. Thus, we elaborate the frameworks and event processing models of four popular open-source serverless platforms and identify their salient idiosyncrasies. We analyze the root causes of performance differences between different service exporting and auto-scaling modes on those platforms. Further, we provide several insights for future work, such as auto-scaling and metric collection.
翻译:无服务器的计算由于成本较低,部署更方便,因此越来越受欢迎。一些云服务供应商(CSPs)在其公共云层上提供无服务器的计算,但可能会带来供应商锁定风险。为了避免这一限制,许多开放源码服务器的平台出现,让开发商能够自由部署和管理自载云层的功能。然而,建设有效功能需要大量专业知识,需要透彻理解影响绩效的平台框架和特征。对于服务开发商来说,为不同需求和情景区分和选择适当的无服务器平台是一项挑战。因此,我们详细设计了四个广受欢迎的开放源服务器平台的框架和事件处理模式,并确定了其突出的特异性。我们分析了不同服务输出和自动缩放模式之间绩效差异的根源。此外,我们为未来工作提供了一些见解,如自动缩放和指标收集。