Data monitoring method and device, computer equipment and storage medium

Abstract

The invention relates to the technical field of cloud monitoring, and provides a data monitoring method and a device, computer equipment and a storage medium, and the method comprises the steps: obtaining a plurality of function points reported by a business system, and initializing a plurality of monitoring rules for each function point; hanging a plurality of monitoring rules corresponding to each function point on a hanging node corresponding to each function point; generating a check chain according to the plurality of monitoring rules on each hanging node; in response to received first burying point data on a first function point triggered by a service system, determining a first hanging node corresponding to the first function point, and calling a check chain on the first hanging point to monitor the first burying point data to obtain a first monitoring result; and packaging the first monitoring result and returning the first monitoring result to the service system. According tothe invention, personalized and directional monitoring can be carried out on a plurality of function points of a plurality of service systems through one monitoring system, and the monitoring qualityis high. In addition, the invention also relates to the technical field of the blockchain, and the first monitoring result can be stored in the blockchain.

Description

technical field [0001] The invention relates to the technical field of cloud monitoring, in particular to a data monitoring method, device, computer equipment and storage medium. Background technique [0002] Pre-risk control is an indispensable part of the field of capital payment, which is conducive to protecting the safety and integrity of enterprise assets, and is conducive to the realization of the business objectives of enterprises and projects. It is of great significance to enterprises and projects. [0003] The monitoring data and risk levels faced by traditional risk control systems are relatively single. For example, it is basically impossible for financial risk control systems to be used for risk control of engineering construction. Each risk control system has its own customization and irreversibility. In terms of usability, it is often necessary to prepare different risk control systems for different projects or fields within an enterprise. For example, the ris...

AI Technical Summary

Problems solved by technology

[0003] The monitoring data and risk levels faced by traditional risk control systems are relatively single. For example, it is basically impossible for financial risk control systems to be used for risk control of engineering construction. Each risk control system has its own customization and irreversibility. In terms of usability, it is often necessary to prepare different risk control systems for different projects or fields within an enterprise. For example, the risk monitoring rules for fund payment and asset management are different, and the monitoring points for direct payment and authorized payment in fund payment are also different. , so when it is necessary to monitor these data at the same time, either customize different monitoring systems, or mix all the monitoring together. Every time a new monitoring item is added, targeted customized development is required, which increases the complexity and usability of the risk control system , resulting in lower risk control quality

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