  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.
