SeBS

Marcin Copik, Grzegorz Kwaśniewski, Maciej Besta, Michał Podstawski, Torsten Hoefler

2021 · 111 citations · 28 references

Concepts

TL;DR

Function‑as‑a‑Service is a promising cloud paradigm, yet its rapid evolution and absence of a standardized benchmark hinder reproducibility and comparison across studies. This work introduces the Serverless Benchmark Suite, the first systematic benchmark for FaaS that spans diverse cloud resources and applications. The suite comprises representative workload specifications, implementation and evaluation infrastructure, and a reproducible methodology that enables interpretable performance assessment. Our abstract execution model applies to AWS, Azure, and Google Cloud, and the benchmark provides a reliable, evolving framework for evaluating FaaS platforms’ performance, efficiency, scalability, and reliability.

Abstract

Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for building scalable and cost-efficient microservices and appli cations. However, the quickly moving technology hinders reproducibility, and the lack of a standardized benchmarking suite leads to ad-hoc solutions and microbenchmarks being used in serverless research, further complicating meta-analysis and comparison of research solutions. To address this challenge, we propose the Serverless Benchmark Suite: the first benchmark for FaaS computing that systematically covers a wide spectrum of cloud resources and applications. Our benchmark consists of the specification of representative workloads, the accompanying implementation and evaluation infrastructure, and the evaluation methodology that facilitates reproducibility and enables interpretability. We demonstrate that the abstract model of a FaaS execution environment ensures the applicability of our benchmark to multiple commercial providers such as AWS, Azure, and Google Cloud. Our work facilitates experimental evaluation of serverless systems, and delivers a standardized, reliable and evolving evaluation methodology of performance, efficiency, scalability and reliability of middleware FaaS platforms.

References

28