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Microservice fault prediction method based on log mining

A log, fault technique, used in error detection/correction, instrumentation, electrical digital data processing, etc.

Pending Publication Date: 2022-04-22
DIGITAL CHINA INFORMATION SYST
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing methods use logs to detect anomalies or predict failures based on cloud systems. These logs are generated by basic software such as operating systems, distributed file systems, and container orchestration systems, so they can only detect cloud infrastructure that occurs on computing or storage nodes. Anomalies or failures in

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  • Microservice fault prediction method based on log mining

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Embodiment Construction

[0013] Below in conjunction with specific embodiment and accompanying drawing, the present invention is described in detail, as figure 1 As shown, the method flow of the embodiment of the present invention:

[0014] The method includes an offline training phase and an online prediction phase. In the offline training phase, the target application is executed in the test environment, and the prediction model is trained based on the collected trace logs. The trace logs of successful execution and error execution are required. Use the fault injection strategy to obtain the wrong version of the application, and use the automated test cases to execute the application and its wrong version to generate trace logs. The test case simulates the user request from the customer and generates a microservice call chain. The test process runs in a controlled deployment environment, so that the application is executed under different configurations. Then, collect and analyze the trace logs ge...

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Abstract

The invention relates to a micro-service fault prediction method based on log mining. According to functions defined on the system tracking logs, automatically executing original and error injection target programs, obtaining corresponding system tracking logs, and training a fault prediction model on the system tracking log and micro-service levels based on machine learning. The predictive model is applied to the production environment to predict potential errors at runtime, detect faulty microservices, and analyze fault types.

Description

technical field [0001] The invention relates to a microservice fault prediction method based on log mining, which belongs to the field of software technology. Background technique [0002] Microservice applications usually have multiple microservices running on a large number of servers, and infrastructure or application errors in the production environment often cause microservice failures, so diagnosing microservice application failures in a test environment is challenging. At the cloud infrastructure layer, faults can be handled through technical means such as fault prediction, virtual machine allocation and migration (Jawwad Ahmed, et al. Online Approach to Performance Fault Localization for Cloud and Datacenter Services. In Proc. IFIP / IEEE Symposium on Integrated Network and Service Management . 873–874.). At the software application layer, faults rely on developers to fix faults through code review, testing, and debugging (Elton Alves, et al. 2011. Fault Localization ...

Claims

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Application Information

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IPC IPC(8): G06F11/30
CPCG06F11/3065
Inventor 李扬陈杉杉张鼎
Owner DIGITAL CHINA INFORMATION SYST
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