Automated fault localization in large-scale cloud-based applications is challenging because
it involves mining multivariate time series data from large volumes of operational monitoring …

Cloud services are omnipresent and critical cloud service failure is a fact of life. In order to
retain customers and prevent revenue loss, it is important to provide high reliability …

The task of root cause analysis (RCA) is to identify the root causes of system faults/failures
by analyzing system monitoring data. Efficient RCA can greatly accelerate system failure …

Due to the complexity of microservice architecture, it is difficult to accomplish efficient
microservice anomaly detection and localization tasks and achieve the target of high system …

Identifying root causes for unexpected or undesirable behavior in complex systems is a
prevalent challenge. This issue becomes especially crucial in modern cloud applications …

This paper describes the development of a causal diagnosis approach for troubleshooting
an industrial environment on the basis of the technical language expressed in Return on …

Recent work conceptualized root cause analysis (RCA) of anomalies via quantitative
contribution analysis using causal counterfactuals in structural causal models (SCMs). The …

Microservice architecture has been widely adopted by large-scale applications. Due to the
huge amount of data and complex microservice dependency, it also poses new challenges …

Runtime failure and performance degradation is commonplace in modern cloud systems.
For cloud providers, automatically determining the root cause of incidents is paramount to …

Under a distributed information system, the scale of various operational components such as
applications, operating systems, databases, servers, and networks is immense, with intricate …