COMPARATIVE ANALYSIS OF SEQUENCE-BASED AND GRAPH-BASED DEEP LEARNING FOR ANOMALY DETECTION IN MICROSERVICE TRACES

The transition from monolithic to microservice architectures has significantly increased the complexity of system observability. Distributed tracing has emerged as a vital tool for monitoring inter-service interactions, yet traditional anomaly detection methods often fail to capture the intricate s...

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Autors principals:	Yesset Zhussupov, Ainur Zhumadillayeva, Shona Shinassylov, Ainur Amirtayeva
Format:	Artigo
Idioma:	Inglês
Publicat:	Al-Farabi Kazakh National University 2026-06-01
Col·lecció:	Journal of Problems in Computer Science and Information Technologies
Matèries:	microservice architecture anomaly detection graph neural networks LSTM distributed tracing deep learning
Accés en línia:	https://jpcsit.kaznu.kz/index.php/kaznu/article/view/304
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