论文标题
可可：功能与服务平台的冷启动意识能力计划
COCOA: Cold Start Aware Capacity Planning for Function-as-a-Service Platforms
论文作者
论文摘要
由于事件驱动的工作负载中隐含的成本节省及其与DevOps的协同作用，因此功能-AS-AS-A-Service（FAAS）在软件行业越来越受欢迎。要大小一个本地FAAS平台，重要的是要估计服务期望负载所需的CPU和内存能力。鉴于服务级别的协议，在尺码过程中考虑冷启动问题是一项挑战。我们已经研究了此问题与TTL缓存中的命中率提高问题的相似性，并得出结论，TTL缓存的解决方案虽然可能适用，但导致FAAS中的过度提供。因此，我们提出了一种新颖的方法可可，以解决这个问题。可可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执行，考虑了不同的内存消耗值。使用事件驱动的FAAS模拟器Faassim，我们已经开发了，我们表明可可在某些工作负载中可以将过度提供的超过70％减少，同时满足服务级别的协议。
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.
