9 citations · 14 across the 6 of their papers we have counts for
6 papers
A Scenario-Oriented Benchmark for Assessing AIOps Algorithms in Microservice Management
Yongqian Sun, Jiaju Wang, Zhengdan Li +9
AIOps algorithms play a crucial role in the maintenance of microservice systems. Many previous benchmarks' performance leaderboard provides valuable guidance for selecting appropri…
LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysis
Tianyu Cui, Shiyu Ma, Ziang Chen +10
Log analysis is crucial for ensuring the orderly and stable operation of information systems, particularly in the field of Artificial Intelligence for IT Operations (AIOps). Large…
Robust Multimodal Failure Detection for Microservice Systems
Chenyu Zhao, Minghua Ma, Zhenyu Zhong +10
Proactive failure detection of instances is vitally essential to microservice systems because an instance failure can propagate to the whole system and degrade the system's perform…
Generic and Robust Root Cause Localization for Multi-Dimensional Data in Online Service Systems
Zeyan Li, Junjie Chen, Yihao Chen +9
Localizing root causes for multi-dimensional data is critical to ensure online service systems' reliability. When a fault occurs, only the measure values within specific attribute…
Robust Failure Diagnosis of Microservice System through Multimodal Data
Shenglin Zhang, Pengxiang Jin, Zihan Lin +10
Automatic failure diagnosis is crucial for large microservice systems. Currently, most failure diagnosis methods rely solely on single-modal data (i.e., using either metrics, logs,…
Constructing Large-Scale Real-World Benchmark Datasets for AIOps
Zeyan Li, Nengwen Zhao, Shenglin Zhang +5
Recently, AIOps (Artificial Intelligence for IT Operations) has been well studied in academia and industry to enable automated and effective software service management. Plenty of…