ElastiBench: Scalable Continuous Benchmarking on Cloud FaaS Platforms

TL;DR

ElastiBench leverages cloud FaaS platforms to significantly reduce microbenchmarking time and cost, enabling scalable, reliable performance testing during development.

Contribution

This paper introduces a novel architecture for scalable microbenchmarking on FaaS platforms, addressing performance variability and control issues.

Findings

Achieves ~95% accuracy in detecting performance changes

Reduces benchmarking time from ~4 hours to <=15 minutes

Lowers cost per benchmark run compared to VMs

Abstract

Running microbenchmark suites often and early in the development process enables developers to identify performance issues in their application. Microbenchmark suites of complex applications can comprise hundreds of individual benchmarks and take multiple hours to evaluate meaningfully, making running those benchmarks as part of CI/CD pipelines infeasible. In this paper, we reduce the total execution time of microbenchmark suites by leveraging the massive scalability and elasticity of FaaS (Function-as-a-Service) platforms. While using FaaS enables users to quickly scale up to thousands of parallel function instances to speed up microbenchmarking, the performance variation and low control over the underlying computing resources complicate reliable benchmarking. We demonstrate an architecture for executing microbenchmark suites on cloud FaaS platforms and evaluate it on code changes from an open-source time series database. Our evaluation shows that our prototype can produce reliable results (~95% of performance changes accurately detected) in a quarter of the time (<=15min vs.~4h) and at lower cost ($0.49 vs. ~$1.18) compared to cloud-based virtual machines.