Newest papers

CloudIR-Bench: A Benchmark for Root Cause Analysis and Mitigation of Cloud Incidents

Hoang Tran, Huong Ha, Tri Dang, Jeffrey Chan, Hongyu Zhang · 2026 · arXiv

DOI: 10.48550/arXiv.2610.29185 · open-access PDF

Portuguese

A análise de causa raiz (RCA) e a previsão de mitigação são essenciais para a gestão de incidentes, permitindo a identificação das causas subjacentes de falhas e assegurando a confiabilidade de sistemas baseados em nuvem complexos. Com o aumento do volume de incidentes e da complexidade do sistema, os relatórios de incidentes se tornaram um recurso valioso para essas tarefas. Estudos recentes mostraram resultados promissores usando modelos de grande linguagem (LLMs) para prever causas raiz e ações de mitigação a partir de descrições textuais em relatórios de incidentes.

Machine translation (Meta M2M100); the English original follows.

Abstract

Root cause analysis (RCA) and mitigation prediction are essential for incident management, enabling the identification of underlying causes of failures and ensuring the reliability of complex cloud-based systems. With rising incident volume and system complexity, incident reports have become a valuable resource for these tasks. Recent studies have shown promising results using Large Language Models (LLMs) to predict root causes and mitigation actions from textual descriptions in incident reports. Despite these advances, further progress is hindered by the lack of publicly available datasets; e

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