Journal
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
Volume 19, Issue 5, Pages 3087-3100Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2021.3083671
Keywords
Computer architecture; Measurement; Cloud computing; Monitoring; Topology; Throughput; Heuristic algorithms; Microservice architecture; root cause; anomaly propagation; impact graph; cloud computing
Categories
Funding
- National Key R&D Program of China [2017YFB1200700]
- National Natural Science Foundation of China [62072006]
- Science and Technology on Communication Networks Laboratory [6142104200103]
- National Key Laboratory of Science and Technology on Reliability and Environmental Engineering [6142004180403]
- IBM Shared University Research Project
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This article discusses the challenges and implications of diagnosing root causes of anomalies in large-scale microservice architecture in the cloud. It proposes a novel framework called ServiceRank, which detects anomalies and identifies their root causes in a fast and accurate manner. ServiceRank includes an anomaly detector, a root cause analysis module, and various mechanisms to eliminate the impacts of cloud design patterns on anomaly diagnosis.
Nowadays, increasing business applications running in the cloud are embracing the microservice architecture. This article presents the challenges and implications of diagnosing root causes of anomalies in large-scale microservice architecture using real incidents in IBM Bluemix. We propose ServiceRank, a novel framework for anomaly detection and root cause identification in the microservice architecture to tackle these challenges. ServiceRank introduces an anomaly detector followed by a root cause analysis module, which detects the suspected abnormal service without pre-defined thresholds. To generalize our approach, we design a causal relationship extraction approach to construct impact graphs for root cause investigation according to specific anomalies. To eliminate cloud design-patterns' impact on anomaly diagnosis, we propose a correlation calibration mechanism in ServiceRank and present a calibration algorithm for the circuit breaker - A typical protection pattern in the microservice architecture. Finally, we design a heuristic investigation algorithm based on the second-order random walk to identify the anomaly's root cause. Experimental results in a simulated environment and the IBM Bluemix platform show that ServiceRank outperforms selected approaches in accuracy and offers fast identification of root cause service when an anomaly occurs. Moreover, we can deploy ServiceRank rapidly and easily in various systems without any pre-defined knowledge.
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