Developing accurate and extendable performance models for serverless platforms, aka Function-as-a-Service (FaaS) platforms, is a very challenging task. Also, implementation and experimentation on real serverless platforms is both costly and time-consuming. However, at the moment, there is no comprehensive simulation tool or framework to be used instead of the real platform. As a result, in this paper, we fill this gap by proposing a simulation platform, called SimFaaS, which assists serverless application developers to develop optimized Function-as-a-Service applications in terms of cost and performance.
In this work, we propose an analytical performance model that is capable of predicting several key performance metrics for serverless workloads using only their average response time for warm and cold requests. The introduced model uses realistic assumptions, which makes it suitable for online analysis of real-world platforms. We validate the proposed model through extensive experimentation on AWS Lambda.