Root cause analysis (RCA) in large-scale microservice systems is a critical and challenging
task. To understand and localize root causes of unexpected faults, modern observability …

Widely adopted for their scalability and flexibility, modern microservice systems present
unique failure diagnosis challenges due to their independent deployment and dynamic …

Effective root cause analysis (RCA) is vital for swiftly restoring services, minimizing losses,
and ensuring the smooth operation and management of complex systems. Previous data …

Automatic failure diagnosis is crucial for large microservice systems. Currently, most failure
diagnosis methods rely solely on single-modal data (ie, using either metrics, logs, or traces) …

Accurate and efficient localization of root cause instances in large-scale microservice
systems is of paramount importance. Unfortunately, prevailing methods face several …

Microservices architecture improves software scalability, resilience, and agility but also
poses significant challenges to system reliability due to their complexity and dynamic nature …

Automated incident management is critical for large-scale microservice systems, including
tasks such as anomaly detection (AD), failure triage (FT), and root cause localization (RCL) …

Although dedicated efforts have been devoted to ensuring the service quality of online
service systems, these systems are still suffering from incidents due to various causes, which …

Anomaly detection is an essential activity for identifying abnormal behaviours in
microservice-based systems. A common approach is to model the system behaviour during …

This paper presents Chain-of-Event (CoE), an interpretable model for root cause analysis in
microservice systems that analyzes causal relationships of events transformed from multi …