9 papers
LogNLQ: Natural-Language Log Querying with Parser-Induced and Semantically Grounded Schemas
Juepeng Wang, Jinyang Liu, Zhuangbin Chen +1
Logs are essential for system monitoring and failure diagnoses in modern software systems, yet querying them through natural language remains an open challenge. Existing approaches…
KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction
Lei Ma, Jinyang Liu, Tieying Zhang +5
Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions with clear boundaries, this structure i…
LogPrism: Unifying Structure and Variable Encoding for Effective Log Compression
Yang Liu, Kaiming Zhang, Zhuangbin Chen +1
In the field of log compression, the prevailing "parse-then-compress" paradigm fundamentally limits effectiveness by treating log parsing and compression as isolated objectives. Wh…
CodeAD: Synthesize Code of Rules for Log-based Anomaly Detection with LLMs
Junjie Huang, Minghua He, Jinyang Liu +3
Log-based anomaly detection (LogAD) is critical for maintaining the reliability and availability of large-scale online service systems. While machine learning, deep learning, and l…
ErrorPrism: Reconstructing Error Propagation Paths in Cloud Service Systems
Junsong Pu, Yichen Li, Zhuangbin Chen +6
Reliability management in cloud service systems is challenging due to the cascading effect of failures. Error wrapping, a practice prevalent in modern microservice development, enr…
LogPilot: Intent-aware and Scalable Alert Diagnosis for Large-scale Online Service Systems
Zhihan Jiang, Jinyang Liu, Yichen Li +7
Effective alert diagnosis is essential for ensuring the reliability of large-scale online service systems. However, on-call engineers are often burdened with manually inspecting ma…