Overhead Measurement Noise in Different Runtime Environments

TL;DR

This paper evaluates how different runtime environments, especially cloud versus bare-metal, affect overhead measurements of observability tools, highlighting the impact of environment noise on performance detection accuracy.

Contribution

It compares the suitability of cloud and bare-metal environments for benchmarking observability overhead using MooBench, providing insights into environment-induced measurement variability.

Findings

Bare metal servers have lower runtime and standard deviation for MooBench.

Performance changes up to 4.41% are detectable in cloud environments with sequential workloads.

Cloud environments introduce more noise, affecting measurement precision.

Abstract

In order to detect performance changes, measurements are performed with the same execution environment. In cloud environments, the noise from different processes running on the same cluster nodes might change measurement results and thereby make performance changes hard to measure. The benchmark MooBench determines the overhead of different observability tools and is executed continuously. In this study, we compare the suitability of different execution environments to benchmark the observability overhead using MooBench. To do so, we compare the execution times and standard deviation of MooBench in a cloud execution environment to three bare-metal execution environments. We find that bare metal servers have lower runtime and standard deviation for multi-threaded MooBench execution. Nevertheless, we see that performance changes up to 4.41% are detectable by GitHub actions, as long as only sequential workloads are examined.