论文标题
野外无服务器：在大云提供商处表征和优化无服务器的工作负载
Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider
论文作者
论文摘要
作为服务（FAAS）的功能一直在越来越受欢迎，以作为将计算的一种方式部署到云中的无服务器后端。这种范式将分配和供应资源的复杂性转移到云提供商上，这必须以最低的可能资源成本提供始终可用资源的幻想（即，没有冷启动的快速功能调用）。这样做需要提供商深入了解FAA工作量的特征。不幸的是，几乎没有关于这些特征的公众信息。因此，在本文中，我们首先表征了Azure功能的整个生产FAA工作量。例如，我们表明大多数函数很少被调用，但是有8阶的调用频率范围。利用我们从表征的观察结果，我们提出了一项实用的资源管理政策，该政策大大减少了功能冷门的数量，而花费的时间比实践策略少。
Function as a Service (FaaS) has been gaining popularity as a way to deploy computations to serverless backends in the cloud. This paradigm shifts the complexity of allocating and provisioning resources to the cloud provider, which has to provide the illusion of always-available resources (i.e., fast function invocations without cold starts) at the lowest possible resource cost. Doing so requires the provider to deeply understand the characteristics of the FaaS workload. Unfortunately, there has been little to no public information on these characteristics. Thus, in this paper, we first characterize the entire production FaaS workload of Azure Functions. We show for example that most functions are invoked very infrequently, but there is an 8-order-of-magnitude range of invocation frequencies. Using observations from our characterization, we then propose a practical resource management policy that significantly reduces the number of function coldstarts,while spending fewerresources than state-of-the-practice policies.
