Job log monitoring method and device, computer equipment and storage medium

Abstract

The invention relates to a job log monitoring method and device, computer equipment and a storage medium. The method comprises the steps of obtaining to-be-analyzed job log data of a job log center; the to-be-analyzed job log data is data obtained by processing log data generated during operation of the target job; inputting the to-be-analyzed job log data into a log analysis model to obtain a job log data analysis result, and judging whether the target job is interrupted or not based on the job log data analysis result to obtain a first judgment result; the log analysis model is a bidirectional gating circulation unit network with a multilayer structure; if the first judgment result is that the target job is not interrupted, inputting the to-be-analyzed job log data into an alarm tracking model to obtain a second judgment result corresponding to an uninterrupted job log data analysis result; and if the second judgment result is abnormal alarm, outputting abnormal operation data for the target operation. By adopting the method, the monitoring efficiency can be improved, and the identification error rate is reduced.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular, to a method, device, computer equipment and storage medium for monitoring job logs. Background technique [0002] With the development of artificial intelligence technology, cloud technology has emerged. This technology can unify a series of resources such as hardware, software, and network in a wide area network or a local area network, and realize a hosting technology for data computing, storage, processing and sharing. [0003] In traditional technologies, the traditional manual and semi-automatic operation and maintenance methods are increasingly unable to meet the demand as the amount of data increases. Most of the existing log monitoring and analysis of large batches of logs are still in passive and time-consuming operation and maintenance methods such as monitoring error reporting and keyword retrieval, resulting in low monitoring efficiency and...

AI Technical Summary

Problems solved by technology

[0003] In traditional technology, relying on manual and semi-automatic traditional operation and maintenance methods, as the amount of data increases, it is increasingly unable to meet the demand

When the existing log monitoring and analysis of a large number of logs, most of them still stay in passive and time-consuming operation and maintenance methods such as monitoring error reporting and keyword retrieval, resulting in low monitoring efficiency and high identification error rate

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