Function-as-a-Service (FaaS) is increasingly popular in the software industry due to the implied cost-savings in event-driven workloads and its synergy with DevOps. To size an on-premise FaaS platform, it is important to estimate the required CPU and memory capacity to serve the expected loads. Given the service-level agreements, it is however challenging to take the cold start issue into account during the sizing process. We have investigated the similarity of this problem with the hit rate improvement problem in TTL caches and concluded that solutions for TTL cache, although potentially applicable, lead to over-provisioning in FaaS. Thus, we propose a novel approach, COCOA, to solve this issue. COCOA uses a queueing-based approach to assess the effect of cold starts on FaaS response times. It also considers different memory consumption values depending on whether the function is idle or in execution. Using an event-driven FaaS simulator, FaasSim, we have developed, we show that COCOA can reduce over-provisioning by over 70% in some workloads, while satisfying the service-level agreements.

中文翻译：

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COCOA：功能即服务平台的冷启动感知容量规划

由于事件驱动的工作负载隐含的成本节约及其与 DevOps 的协同作用，功能即服务 (FaaS) 在软件行业中越来越受欢迎。要确定内部部署 FaaS 平台的规模，重要的是估计所需的 CPU 和内存容量来满足预期负载。然而，鉴于服务级别协议，在规模调整过程中考虑冷启动问题具有挑战性。我们研究了这个问题与 TTL 缓存中的命中率改进问题的相似性，并得出结论，TTL 缓存的解决方案虽然可能适用，但会导致 FaaS 中的过度配置。因此，我们提出了一种新方法 COCOA 来解决这个问题。COCOA 使用基于队列的方法来评估冷启动对 FaaS 响应时间的影响。它还根据函数是空闲还是正在执行来考虑不同的内存消耗值。使用我们开发的事件驱动的 FaaS 模拟器 FaasSim，我们表明 COCOA 可以在某些工作负载中减少 70% 以上的过度配置，同时满足服务级别协议。