For large-scale distributed systems, it is crucial to efficiently diagnose the root causes of
incidents to maintain high system availability. The recent development of microservice …

Availability issues of industrial microservice systems (eg, drop of successfully placed orders
and processed transactions) directly affect the running of the business. These issues are …

In microservice systems, the identification of root causes of anomalies is imperative for
service reliability and business impact. This process is typically divided into two phases:(i) …

The complexity and dynamism of microservices pose significant challenges to system
reliability, and thereby, automated troubleshooting is crucial. Effective root cause localization …

Incidents in online service systems could incur poor user experience and tremendous
economic loss. To reduce the influence of incidents and guarantee service reliability, it is …

An increasing number of Internet applications are applying microservice architecture due to
its flexibility and clear logic. The stability of microservice is thus vitally important for these …

This paper presents a self-adaptive root cause diagnosis framework, named MS-Rank, to
analyze multiple metrics collected from micro-service architecture. MS-Rank decomposes …

Microservice architecture is applied by an increasing number of systems because of its
benefits on delivery, scalability, and autonomy. It is essential but challenging to localize root …

As online service systems continue to grow in terms of complexity and volume, how service
incidents are managed will significantly impact company revenue and user trust. Due to the …

Causal inference (CI) is one of the popular performance diagnosis methods, which infers the
anomaly propagation from the observed data for locating the root causes. Although some …