English

Enhancing Trace Visualizations for Microservices Performance Analysis

Software Engineering 2023-02-27 v1 Human-Computer Interaction Performance

Abstract

Performance analysis of microservices can be a challenging task, as a typical request to these systems involves multiple Remote Procedure Calls (RPC) spanning across independent services and machines. Practitioners primarily rely on distributed tracing tools to closely monitor microservices performance. These tools enable practitioners to trace, collect, and visualize RPC workflows and associated events in the context of individual end-to-end requests. While effective for analyzing individual end-to-end requests, current distributed tracing visualizations often fall short in providing a comprehensive understanding of the system's overall performance. To address this limitation, we propose a novel visualization approach that enables aggregate performance analysis of multiple end-to-end requests. Our approach builds on a previously developed technique for comparing structural differences of request pairs and extends it for aggregate performance analysis of sets of requests. This paper presents our proposal and discusses our preliminary ongoing progress in developing this innovative approach.

Keywords

Cite

@article{arxiv.2302.12734,
  title  = {Enhancing Trace Visualizations for Microservices Performance Analysis},
  author = {Jessica Leone and Luca Traini},
  journal= {arXiv preprint arXiv:2302.12734},
  year   = {2023}
}

Comments

Accepted for publication in the 6th Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2023)