Semi-Supervised and Disentangled Causal Discovery for Analyzing Fault Propagation in Microservices

While troubleshooting fault propagation in a microservice-based system is labor-intensive for operators, it is critical to their decision-making process for maintaining availability and reliability. Efficient troubleshooting can significantly accelerate fault recovery and help strengthen preventive...

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Bibliografische Detailangaben

Hauptverfasser:	Nobukazu Fukuda, Haruhisa Nozue, Haruo Oishi, Chao Wu, Shingo Horiuchi, Kenichi Tayama
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2026-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	AIOps microservice systems causal structure learning semi-supervised learning disentanglement learning
Online-Zugang:	https://ieeexplore.ieee.org/document/11408137/
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