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

COCOA: Cold Start Aware Capacity Planning for Function-as-a-Service Platforms