10 citations · 47 across the 19 of their papers we have counts for
19 papers
Which Types of Heterogeneity Matter for Root Cause Localization in Microservice Systems ?
Runzhou Wang, Shenglin Zhang, Wenwei Gu +5
Microservice root cause localization is fundamentally challenged by the inherent heterogeneity of cloud-native systems, which encompasses diverse observability data and multiple sy…
LogPurge: Log Data Purification for Anomaly Detection via Rule-Enhanced Filtering
Shenglin Zhang, Ziang Chen, Zijing Que +5
Log anomaly detection, which is critical for identifying system failures and preempting security breaches, detects irregular patterns within large volumes of log data, and impacts…
RationAnomaly: Log Anomaly Detection with Rationality via Chain-of-Thought and Reinforcement Learning
Song Xu, Yilun Liu, Minggui He +10
Logs constitute a form of evidence signaling the operational status of software systems. Automated log anomaly detection is crucial for ensuring the reliability of modern software…
Enhancing Interpretability in Software Change Management with Chain-of-Thought Reasoning
Yongqian Sun, Weihua Kuang, Chao Shen +6
In modern online services, frequent software changes introduce significant risks. To tackle this challenge, we propose SCELM (Software Change Evaluation and Lifecycle Management),…
LogLM: From Task-based to Instruction-based Automated Log Analysis
Yilun Liu, Yuhe Ji, Shimin Tao +7
Automatic log analysis is essential for the efficient Operation and Maintenance (O&M) of software systems, providing critical insights into system behaviors. However, existing appr…
Enhanced Fine-Tuning of Lightweight Domain-Specific Q&A Model Based on Large Language Models
Shenglin Zhang, Pengtian Zhu, Minghua Ma +8
Large language models (LLMs) excel at general question-answering (Q&A) but often fall short in specialized domains due to a lack of domain-specific knowledge. Commercial companies…
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…
Failure Diagnosis in Microservice Systems: A Comprehensive Survey and Analysis
Shenglin Zhang, Sibo Xia, Wenzhao Fan +6
Widely adopted for their scalability and flexibility, modern microservice systems present unique failure diagnosis challenges due to their independent deployment and dynamic intera…
TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Models
Haotian Si, Jianhui Li, Changhua Pei +9
Time series anomaly detection (TSAD) has gained significant attention due to its real-world applications to improve the stability of modern software systems. However, there is no e…
OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models
Yuhe Liu, Changhua Pei, Longlong Xu +13
Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of e…
A Survey of Time Series Anomaly Detection Methods in the AIOps Domain
Zhenyu Zhong, Qiliang Fan, Jiacheng Zhang +6
Internet-based services have seen remarkable success, generating vast amounts of monitored key performance indicators (KPIs) as univariate or multivariate time series. Monitoring a…
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…
Assess and Summarize: Improve Outage Understanding with Large Language Models
Pengxiang Jin, Shenglin Zhang, Minghua Ma +13
Cloud systems have become increasingly popular in recent years due to their flexibility and scalability. Each time cloud computing applications and services hosted on the cloud are…
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…
GenAD: General Representations of Multivariate Time Seriesfor Anomaly Detection
Xiaolei Hua, Lin Zhu, Shenglin Zhang +5
The reliability of wireless base stations in China Mobile is of vital importance, because the cell phone users are connected to the stations and the behaviors of the stations are d…
UniLog: Deploy One Model and Specialize it for All Log Analysis Tasks
Yichen Zhu, Weibin Meng, Ying Liu +4
UniLog: Deploy One Model and Specialize it for All Log Analysis Tasks
Summarizing Unstructured Logs in Online Services
Weibin Meng, Federico Zaiter, Yuheng Huang +10
Logs are one of the most valuable data sources for managing large-scale online services. After a failure is detected/diagnosed/predicted, operators still have to inspect the raw lo…