A5013595762- Software System Performance and Reliability
- Cloud Computing and Resource Management
- Software-Defined Networks and 5G
- Network Security and Intrusion Detection
- Advanced Text Analysis Techniques
- Topic Modeling
- Natural Language Processing Techniques
- Service-Oriented Architecture and Web Services
- Anomaly Detection Techniques and Applications
Nankai University
2023-2024
Automatic failure diagnosis is crucial for large microservice systems. Currently, most methods rely solely on single-modal data (i.e., using either metrics, logs, or traces). In this study, we conduct an empirical study real-world cases to show that combining these sources of (multimodal data) leads a more accurate diagnosis. However, effectively representing and addressing imbalanced failures remain challenging. To tackle issues, propose <italic...
Logs are one of the most valuable data to describe running state services. Failure diagnosis through logs is crucial for service reliability and security. The current automatic log failure methods cannot fully use multiple fields logs, which fail capture relation between them. In this article, we propose LogKG, a new framework diagnosing failures based on knowledge graphs (KG) logs. LogKG extracts entities relations from mine multi-field information their KG. To represented by KG,...
AIOps algorithms play a crucial role in the maintenance of microservice systems. Many previous benchmarks' performance leaderboard provides valuable guidance for selecting appropriate algorithms. However, existing benchmarks mainly utilize offline datasets to evaluate They cannot consistently using real-time datasets, and operation scenarios evaluation are static, which is insufficient effective algorithm selection. To address these issues, we propose an evaluation-consistent...
Automatic failure diagnosis is crucial for large microservice systems. Currently, most methods rely solely on single-modal data (i.e., using either metrics, logs, or traces). In this study, we conduct an empirical study real-world cases to show that combining these sources of (multimodal data) leads a more accurate diagnosis. However, effectively representing and addressing imbalanced failures remain challenging. To tackle issues, propose DiagFusion, robust approach uses multimodal data. It...