Serverless Computing: An Investigation of Factors Influencing Microservice Performance
Serverless Computing: An Investigation of Factors Influencing Microservice Performance
复制标题
无服务器计算：影响微服务性能的因素调查
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
S. Pallickara
中科院分区：
文献类型：
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作者：
W. Lloyd;S. Ramesh;Swetha Chinthalapati;Lan Ly;S. Pallickara
无服务器计算平台为最终用户提供功能即服务（FaaS），同时承诺降低托管成本，高可用性，容错性和动态弹性，用于托管称为微服务的单个功能。无服务器计算环境与云结构即服务（IaaS）云平台不同，它抽象了基础设施管理，包括创建虚拟机（VM）、操作系统容器和请求用户负载平衡。为了节省云服务器的容量和能源，云提供商允许托管基础设施变冷，在服务需求较低时取消容器配置，从而释放基础设施供其他人利用。在本文中，我们提出了对影响无服务器计算提供的微服务性能的因素进行全面调查的结果。我们研究托管基础设施的弹性，负载平衡，供应变化，基础设施保留和内存预留大小相关的影响。我们确定了无服务器基础设施的四种状态，包括：提供商冷、VM冷、容器冷和热，并展示了微服务性能如何根据这些状态变化高达15倍。
Serverless computing platforms provide function(s)-as-a-Service (FaaS) to end users while promising reduced hosting costs, high availability, fault tolerance, and dynamic elasticity for hosting individual functions known as microservices. Serverless Computing environments, unlike Infrastructure-as-a-Service (IaaS) cloud platforms, abstract infrastructure management including creation of virtual machines (VMs), operating system containers, and request load balancing from users. To conserve cloud server capacity and energy, cloud providers allow hosting infrastructure to go COLD, deprovisioning containers when service demand is low freeing infrastructure to be harnessed by others. In this paper, we present results from our comprehensive investigation into the factors which influence microservice performance afforded by serverless computing. We examine hosting implications related to infrastructure elasticity, load balancing, provisioning variation, infrastructure retention, and memory reservation size. We identify four states of serverless infrastructure including: provider cold, VM cold, container cold, and warm and demonstrate how microservice performance varies up to 15x based on these states.