45 citations · 86 across the 16 of their papers we have counts for
16 papers · 1 filter
From General Agents to RCA Experts: A Self-Evolving Harness for Root Cause Analysis
Haiyu Huang, Jiewei Lyu, Zhihan Jiang +5
Automated root cause analysis (RCA) with large language models (LLMs) has drawn growing attention. Today, SREs typically automate RCA with LLMs in one of two ways: directly using a…
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…
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…
KPIRoot+: An Efficient Integrated Framework for Anomaly Detection and Root Cause Analysis in Large-Scale Cloud Systems
Wenwei Gu, Renyi Zhong, Guangba Yu +8
To ensure the reliability of cloud systems, their performance is monitored using KPIs (key performance indicators). When issues arise, root cause localization identifies KPIs respo…
COCA: Generative Root Cause Analysis for Distributed Systems with Code Knowledge
Yichen Li, Yulun Wu, Jinyang Liu +4
Runtime failures are commonplace in modern distributed systems. When such issues arise, users often turn to platforms such as Github or JIRA to report them and request assistance.…
Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis
Junjie Huang, Zhihan Jiang, Jinyang Liu +7
Logs are imperative in the maintenance of online service systems, which often encompass important information for effective failure mitigation. While existing anomaly detection met…
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach
Jinxi Kuang, Jinyang Liu, Junjie Huang +6
Due to the scale and complexity of cloud systems, a system failure would trigger an "alert storm", i.e., massive correlated alerts. Although these alerts can be traced back to a fe…
FaultProfIT: Hierarchical Fault Profiling of Incident Tickets in Large-scale Cloud Systems
Junjie Huang, Jinyang Liu, Zhuangbin Chen +7
Postmortem analysis is essential in the management of incidents within cloud systems, which provides valuable insights to improve system's reliability and robustness. At CloudA, fa…
Go Static: Contextualized Logging Statement Generation
Yichen Li, Yintong Huo, Renyi Zhong +6
Logging practices have been extensively investigated to assist developers in writing appropriate logging statements for documenting software behaviors. Although numerous automatic…
MTAD: Tools and Benchmarks for Multivariate Time Series Anomaly Detection
Jinyang Liu, Wenwei Gu, Zhuangbin Chen +3
Key Performance Indicators (KPIs) are essential time-series metrics for ensuring the reliability and stability of many software systems. They faithfully record runtime states to fa…
LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
Zhihan Jiang, Jinyang Liu, Zhuangbin Chen +6
Log parsing transforms log messages into structured formats, serving as the prerequisite step for various log analysis tasks. Although a variety of log parsing approaches have been…
A Roadmap towards Intelligent Operations for Reliable Cloud Computing Systems
Yintong Huo, Cheryl Lee, Jinyang Liu +2
The increasing complexity and usage of cloud systems have made it challenging for service providers to ensure reliability. This paper highlights two main challenges, namely interna…
Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics
Jieming Zhu, Shilin He, Pinjia He +2
Logs have been widely adopted in software system development and maintenance because of the rich runtime information they record. In recent years, the increase of software size and…