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A Causality Mining and Knowledge Graph Based Method of Root Cause Diagnosis for Performance Anomaly in Cloud Applications

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School of Software Engineering, Tongji University, Shanghai 201804, China
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Donald Bren School of Information and Computer Sciences, University of California, Irvine 6210 Donald Bren Hall, Irvine, CA 92697-3425, USA
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Authors to whom correspondence should be addressed.
Appl. Sci. 2020, 10(6), 2166; https://doi.org/10.3390/app10062166
Received: 23 February 2020 / Revised: 11 March 2020 / Accepted: 16 March 2020 / Published: 22 March 2020
With the development of cloud computing technology, the microservice architecture (MSA) has become a prevailing application architecture in cloud-native applications. Many user-oriented services are supported by many microservices, and the dependencies between services are more complicated than those of a traditional monolithic architecture application. In such a situation, if an anomalous change happens in the performance metric of a microservice, it will cause other related services to be downgraded or even to fail, which would probably cause large losses to dependent businesses. Therefore, in the operation and maintenance job of cloud applications, it is critical to mine the causality of the problem and find its root cause as soon as possible. In this paper, we propose an approach for mining causality and diagnosing the root cause that uses knowledge graph technology and a causal search algorithm. We verified the proposed method on a classic cloud-native application and found that the method is effective. After applying our method on most of the services of a cloud-native application, both precision and recall were over 80%. View Full-Text
Keywords: causality graph; knowledge graph; microservice system; operation and maintenance (O&M); root cause diagnosis causality graph; knowledge graph; microservice system; operation and maintenance (O&M); root cause diagnosis
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MDPI and ACS Style

Qiu, J.; Du, Q.; Yin, K.; Zhang, S.-L.; Qian, C. A Causality Mining and Knowledge Graph Based Method of Root Cause Diagnosis for Performance Anomaly in Cloud Applications. Appl. Sci. 2020, 10, 2166.

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