CN-121996716-A - Data monitoring method, device, equipment and medium

CN121996716ACN 121996716 ACN121996716 ACN 121996716ACN-121996716-A

Abstract

The invention discloses a data monitoring method, a device, equipment and a medium, which comprise the steps of collecting running state data of each monitored equipment according to a preset data collecting mode corresponding to each monitored equipment, collecting basic environment data of each monitored equipment according to an environment data collecting method corresponding to each monitored equipment, integrating data sources of the basic environment data and the running state data corresponding to each monitored equipment respectively to obtain monitoring fusion data, and visually displaying the monitoring fusion data. The invention can realize intelligent operation and maintenance monitoring of the monitored equipment of the cloud platform, so as to discover the abnormal working state of the monitored equipment in time, help an administrator to respond and process more quickly, and improve the stability and safety of the system.

Inventors

LI YUXIN
LI HUAFENG
XIA WEIHONG
LI JIANWEI
ZHANG YIPING
ZHAO FENGKUN
YANG XIAOYI
ZHANG YUE
RAO YU
WANG CAN
Mou xuan

Assignees

中国石油天然气股份有限公司
中石油煤层气有限责任公司
中联煤层气国家工程研究中心有限责任公司

Dates

Publication Date: 20260508
Application Date: 20241104

Claims (10)

1. The data monitoring method is characterized by being applied to a cloud system, wherein the cloud system is communicated with different kinds of monitored equipment, and the method comprises the following steps: Collecting running state data of each monitored device according to a preset data collecting mode corresponding to each monitored device, wherein each monitored device comprises network equipment, storage equipment, server equipment, a middleware database, a big data cluster and a container cluster; according to the corresponding environmental data acquisition method of each monitored device, acquiring the basic environmental data of each monitored device; and carrying out data source integration on the basic environment data and the running state data corresponding to each monitored device respectively to obtain monitoring fusion data, and carrying out visual display on the monitoring fusion data.
2. The method of claim 1, wherein the collecting the operation state data of each monitored device according to the preset data collection mode corresponding to each monitored device includes: Controlling the distributed acquisition servers corresponding to the monitored devices respectively, and acquiring the running state data of the monitored devices corresponding to the distributed acquisition servers according to the preset data acquisition modes corresponding to the monitored devices; and receiving the running state data of the monitored equipment corresponding to each distributed acquisition server from the distributed acquisition servers corresponding to each monitored equipment.
3. The method according to claim 2, wherein the controlling the distributed collection server corresponding to each monitored device to collect the operation state data of the monitored device corresponding to each distributed collection server according to the preset data collection mode corresponding to the monitored device corresponding to each monitored device includes: When the computing capacities of the distributed acquisition servers corresponding to the monitored devices are changed, controlling the distributed acquisition servers corresponding to the monitored devices, and readjusting the monitoring corresponding relation between the distributed acquisition servers and the monitored devices according to a preset automatic adjustment mechanism; And controlling the distributed acquisition servers corresponding to the monitored equipment respectively based on the adjusted monitoring corresponding relation, and acquiring the running state data of the monitored equipment corresponding to each distributed acquisition server according to the preset data acquisition mode corresponding to the monitored equipment corresponding to each distributed acquisition server.
4. The method of claim 1, wherein the cloud comprises two console servers in communication with each other, the method further comprising: When the main control console servers in the two control console servers are abnormal, controlling the auxiliary control console servers in the two control console servers to execute the step of collecting the running state data of each monitored device according to the preset data collecting mode corresponding to each monitored device.
5. The method of claim 1, wherein the method further comprises: receiving alarm information sent by each monitored device respectively to obtain an alarm information cluster; Combining and compressing the alarm information in the alarm information cluster according to the alarm object, the alarm type, the alarm level and the rule description attribute to obtain a simplified alarm cluster; and carrying out alarm processing on the alarm information existing in the simplified alarm cluster.
6. The method of claim 1, wherein after collecting the operational status data of each of the monitored devices and collecting the base environment data of each of the monitored devices, the method further comprises: and determining whether the target monitored equipment is abnormal or not according to the first time sequence of the port outlet flow and the second time sequence of the port inlet flow in the running state data corresponding to the target monitored equipment aiming at any one target monitored equipment in the monitored equipment.
7. The method of claim 6, wherein the determining whether the target monitored device is abnormal based on the first time series of port outgoing traffic and the second time series of port incoming traffic in the operational status data corresponding to the target monitored device comprises: Performing time sequence mode feature extraction on the first time sequence and the second time sequence, and performing semantic enhancement processing on the first time sequence and the second time sequence to obtain a first enhanced port feature vector and a second enhanced port feature vector; respectively determining average value feature vectors of the first enhanced port feature vector and the second enhanced port feature vector, and determining a first association feature vector and a second association feature vector; Determining a port access interaction vector according to the first association feature vector and the second association feature vector; and determining whether the target monitored equipment is abnormal or not according to the port access interaction vector.
8. A data monitoring device, characterized in that is applied to a cloud system, the cloud system communicates with different kinds of monitored equipment, the device includes: The data acquisition module is used for acquiring the running state data of each monitored device according to a preset data acquisition mode corresponding to each monitored device, wherein each monitored device comprises a network device, a storage device, a server device, a middleware database, a big data cluster and a container cluster; The data acquisition module is used for acquiring basic environment data of each monitored device according to an environment data acquisition method corresponding to each monitored device; And the fusion display module is used for carrying out data source integration on the basic environment data and the running state data corresponding to each monitored device respectively to obtain monitoring fusion data, and carrying out visual display on the monitoring fusion data.
9. An electronic device, comprising: A processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute to implement a data monitoring method as claimed in any one of claims 1 to 7.
10. A non-transitory computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform a data monitoring method implementing any of claims 1 to 7.

Description

Data monitoring method, device, equipment and medium Technical Field The present invention relates to the field of big data monitoring technologies, and in particular, to a data monitoring method, device, equipment, and medium. Background Exploration and development of unconventional natural gas refers to the exploration and development of natural gas that has significant differences in subsurface occurrence and aggregation patterns from conventional natural gas reservoirs. In the exploration and development process, a large amount of data needs to be collected and subjected to professional processing analysis, and related technologies mainly rely on a cloud platform to share resources. However, since these data originate from different kinds of specialized software and from different computer terminals, these data cannot be effectively monitored. Therefore, how to effectively monitor the data of different professional software and different computer terminals is a problem that needs to be solved currently. Disclosure of Invention The embodiment of the application solves the technical problem that the data from different types of professional software and different computer terminals cannot be effectively monitored in the prior art by providing the data monitoring method, the device, the equipment and the medium, and achieves the technical effect of effectively monitoring the data of different professional software and different computer terminals. In a first aspect, the present application provides a data monitoring method applied to a cloud system, where the cloud system communicates with different kinds of monitored devices, the method includes: The method comprises the steps of collecting running state data of each monitored device according to a preset data collecting mode corresponding to each monitored device, wherein each monitored device comprises network equipment, storage equipment, server equipment, a middleware database, a big data cluster and a container cluster; According to the corresponding environmental data acquisition method of each monitored device, acquiring the basic environmental data of each monitored device; and carrying out data source integration on the basic environment data and the running state data corresponding to each monitored device respectively to obtain monitoring fusion data, and carrying out visual display on the monitoring fusion data. In a second aspect, the present application provides a data monitoring apparatus applied to a cloud system, where the cloud system communicates with different kinds of monitored devices, the apparatus includes: the system comprises a data acquisition module, a data storage module and a data storage module, wherein the data acquisition module is used for acquiring the running state data of each monitored device according to a preset data acquisition mode corresponding to each monitored device; The data acquisition module is used for acquiring basic environment data of each monitored device according to an environment data acquisition method corresponding to each monitored device; And the fusion display module is used for carrying out data source integration on the basic environment data and the running state data corresponding to each monitored device respectively to obtain monitoring fusion data, and carrying out visual display on the monitoring fusion data. In a third aspect, the present application provides an electronic device, comprising: A processor; A memory for storing processor-executable instructions; wherein the processor is configured to execute to implement a data monitoring method as provided in the first aspect. In a fourth aspect, the present application provides a non-transitory computer readable storage medium, which when executed by a processor of an electronic device, enables the electronic device to perform a method of implementing data monitoring as provided in the first aspect. One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages: According to the embodiment of the application, the port outlet flow and port inlet flow data of the monitored equipment are collected through real-time monitoring, and the time sequence collaborative analysis and dynamic interaction association of the port outlet flow and port inlet flow data of the monitored equipment are carried out by introducing an artificial intelligence and deep learning-based data processing and analysis algorithm at the rear end, so that the working state of the monitored equipment is monitored in real time and abnormal detection is carried out. Therefore, intelligent operation and maintenance monitoring of the monitored equipment of the cloud platform can be realized, so that the abnormal working state of the monitored equipment can be found in time, an administrator can be helped to respond and process more quickly, and the stability and the safety of the system are i