Abstract

Many researchers reported considerable delay of up to a few seconds when invoking serverless functions for the first time. This phenomenon, which is known as a cold start, affects even more when users are running multiple serverless functions orchestrated in a workflow. However, in many cases users need to instantly spawn numerous serverless functions, usually as a part of parallel loops. In this paper, we introduce the spawn start and analyze the behavior of three Function-as-a-Service (FaaS) providers AWS Lambda, Google Cloud Functions, and IBM Cloud Functions when running parallel loops, both as warm and cold starts. We conducted a series of experiments and observed three insights that are beneficial for the research community. Firstly, cold start on IBM Cloud Functions, which is up to 2s delay compared to the warm start, is negligible compared to the spawn start because the latter generates additional 20s delay. Secondly, Google Cloud Functions' cold start is "warmer" than the warm start of the same serverless function. Finally, while Google Cloud Functions and IBM Cloud Functions run the same serverless function with low concurrency faster than AWS Lambda, the spawn start effect on Google Cloud Functions and IBM Cloud Functions makes AWS the preferred provider when spawning numerous serverless functions.

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