Cluster operation and maintenance state diagnosis method, operation and maintenance monitoring system, terminal and storage medium

Abstract

The invention discloses a cluster operation and maintenance state diagnosis method which comprises the steps: acquiring the current actual value of at least one piece of cluster operation and maintenance data, wherein the cluster operation and maintenance data comprises at least one piece of daily operation and maintenance data, cluster monitoring data, use specification data and cluster log data;obtaining the operation and maintenance data volume of the cluster according to the at least one piece of cluster data, and adjusting at least one preset threshold value and a preset repair suggestion according to the operation and maintenance data volume; obtaining a standard threshold range corresponding to each piece of cluster operation and maintenance data, and judging whether the current actual value of each piece of cluster operation and maintenance data exceeds the corresponding standard threshold range or not; if yes, obtaining a corresponding final repair suggestion according to thecurrent actual value; and displaying a diagnosis result, wherein the diagnosis result comprises the name and meaning of each piece of cluster operation and maintenance data, whether the name and meaning exceed a corresponding standard threshold range and / or repair suggestions. The invention further discloses an operation and maintenance monitoring system, a terminal and a storage medium. The cluster operation and maintenance efficiency can be improved, and the operation and maintenance risk is reduced.

Description

technical field [0001] The invention relates to the field of the Internet, in particular to a cluster operation and maintenance state diagnosis method, an operation and maintenance monitoring system, a terminal, and a storage medium. Background technique [0002] With the increasing use of commercial big data search scenarios, Elasticsearch has become the best choice among open source search engines with its excellent performance, rich functions, and complete ecosystem features. Therefore, the monitoring of the ES (Elasticsearch) cluster has become an important IT (Internet Technology, Internet technology) operation and maintenance work content to ensure the stable operation of the business. [0003] In conventional ES operation and maintenance, usually only the infrastructure layer monitoring indicators of the cluster are collected, such as CPU (central processing unit, central processing unit) usage, memory usage, disk IO (Input / Output, input / output) interface usage, etc. ...

AI Technical Summary

Problems solved by technology

Due to the complexity of the ES technology stack, the lack of monitoring indicators in a dedicated dimension will make it impossible to understand the health status of the cluster in time

At the same time, because common operation and maintenance personnel usually do not have an in-depth understanding of ES, they cannot know the optimal configuration for the current cluster, and often use the default configuration, which leads to the fact that the performance cluster cannot perform optimally in the actual environment, or even Unnecessary production accidents

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