Hybrid Root Cause Analysis for Partially Observable Microservices Based on Architecture Profiling

Isidora Erakovic, Claus Pahl

2025

Abstract

Managing and diagnosing faults in microservices architectures is a challenge. Solutions such as anomaly detection and root cause analysis (RCA) can help, as anomalies often indicate underlying problems that can lead to system failures. This investigation provides an integrated solution that extracts microservice architecture knowledge, detects anomalies, and identifies their root causes. Our approach combines the use of latency thresholds with other techniques to learn the normal behavior of the system and detect deviations that point to faults. Once deviations are identified, a hybrid RCA method is applied that integrates empirical data analysis with an understanding of the system’s architecture to accurately trace the root causes of these anomalies. The solution was validated using trace log data from an Internet Service Provider’s (ISP) microservices system.

Paper Citation

in Harvard Style

Erakovic I. and Pahl C. (2025). Hybrid Root Cause Analysis for Partially Observable Microservices Based on Architecture Profiling. In Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER; ISBN 978-989-758-747-4, SciTePress, pages 255-263. DOI: 10.5220/0013453600003950

in Bibtex Style

@conference{closer25,
author={Isidora Erakovic and Claus Pahl},
title={Hybrid Root Cause Analysis for Partially Observable Microservices Based on Architecture Profiling},
booktitle={Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER},
year={2025},
pages={255-263},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013453600003950},
isbn={978-989-758-747-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER
TI - Hybrid Root Cause Analysis for Partially Observable Microservices Based on Architecture Profiling
SN - 978-989-758-747-4
AU - Erakovic I.
AU - Pahl C.
PY - 2025
SP - 255
EP - 263
DO - 10.5220/0013453600003950
PB - SciTePress