Anomaly Detection for Partially Observable Container Systems Based on Architecture Profiling

Isidora Erakovic, Claus Pahl

2025

Abstract

Managing and diagnosing faults in microservices architectures is a challenge, especially in a service provider environment that hosts third-party services. Solutions such as anomaly detection can help, as anomalies often indicate underlying problems that can lead to system failures. We develop an integrated solution that extracts microservice architecture knowledge and detects anomalies using the architecture knowledge to provide context for these anomalies. Our approach combines the use of latency thresholds with temporal distribution of latency anomalies to determine normal behavior of a system and detect deviations that point to faults. The solution proposed was validated using data from an Internet Service Provider’s microservices system. We were able to identify critical components as key points of failure during fault conditions. The combined use of architecture mining and anomaly detection enabled us to analyse anomalies in depth.

Paper Citation

in Harvard Style

Erakovic I. and Pahl C. (2025). Anomaly Detection for Partially Observable Container Systems 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 127-135. DOI: 10.5220/0013224900003950

in Bibtex Style

@conference{closer25,
author={Isidora Erakovic and Claus Pahl},
title={Anomaly Detection for Partially Observable Container Systems Based on Architecture Profiling},
booktitle={Proceedings of the 15th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER},
year={2025},
pages={127-135},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013224900003950},
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 - Anomaly Detection for Partially Observable Container Systems Based on Architecture Profiling
SN - 978-989-758-747-4
AU - Erakovic I.
AU - Pahl C.
PY - 2025
SP - 127
EP - 135
DO - 10.5220/0013224900003950
PB - SciTePress