CN113570476A - Container service monitoring method of power grid monitoring system based on custom alarm rule - Google Patents
Container service monitoring method of power grid monitoring system based on custom alarm rule Download PDFInfo
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Abstract
The utility model relates to a self-defined warning rule for monitoring system container service of power grid, which comprises obtaining monitoring data of each node device from Prometheus Exporters module, using Prometheus Server module to pull measurement library from the monitoring data, using Prometheus Server module to convert the measurement library into warning message based on preset warning rule and push the warning message to Prometheus Alertmanager module, and using Prometheus Alertmanager module to visually display the warning message. According to the method, the monitoring data is automatically pulled, the alarm message is automatically converted and pushed, monitoring maintenance personnel are not required to participate in the whole process, the power grid monitoring method with high automation degree is realized, and the intelligence of power grid monitoring is greatly improved.
Description
Technical Field
The application relates to the technical field of power grid monitoring, in particular to a power grid monitoring system container server monitoring method based on a custom alarm rule.
Background
With the continuous development of social economy and the continuous progress of science and technology, social informatization is also continuously promoted, and for a large-scale data system, corresponding monitoring software is often needed to carry out data acquisition and monitoring scheduling processing on the large-scale data system.
However, for the conventional power grid monitoring system, from discovery, registration and configuration of a monitoring target to adjustment and optimization of monitoring parameters, a lot of monitoring maintenance personnel are required to participate and maintain, so that the automation degree of the monitoring process is low, and popularization and development of intelligent informatization are not facilitated.
Disclosure of Invention
Therefore, in order to solve the technical problems, a power grid monitoring system container server monitoring method, a device, computer equipment and a storage medium based on a custom alarm rule are provided, which can realize full-automatic monitoring in the field of power grid monitoring.
In a first aspect, a method for monitoring a container server of a power grid monitoring system based on a custom alarm rule includes:
acquiring monitoring data of each node device from a Prometous Exporters module;
using a Prometheus Server module to pull a measurement class library from the monitoring data;
converting the measurement class library into an alarm message by using the Prometheus Server module based on a preset alarm rule and pushing the alarm message to a Prometheus Alertmanager module;
and using the Prometheus Alertmanager module to visually display the alarm message.
In one embodiment, the method further comprises the following steps:
the metrics class library is stored using a Prometheus Server module.
In one embodiment, the method further comprises:
and scheduling the alarm message by using the Prometous Alertmanager module.
In one embodiment, before the obtaining the monitoring data of each node device from the Prometheus Exporters module, the method further includes:
the method comprises the steps of pulling monitoring data of each node device in a power grid monitoring system from a mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module.
In one embodiment, the extracting, from the mirror image warehouse, the monitoring data of each node device in the power grid monitoring system includes:
a container arrangement engine in the container cluster management system is used for pulling monitoring data of each node device in the power grid monitoring system from the mirror image warehouse;
the transmitting the monitoring data to the Prometheus Exporters module includes:
transmitting the monitoring data to the Prometheus Exporters module using the container orchestration engine.
In one embodiment, the container cluster management system is a kubernets container cluster management system.
In one embodiment, the mirror repository is a Harbor mirror repository.
In a second aspect, a device for monitoring a container service of a power grid monitoring system based on a customized alarm rule includes:
the acquisition module is used for acquiring the monitoring data of each node device from the Prometous Exporters module;
the first pulling module is used for pulling a metric class library from the monitoring data by using a Prometheus Server module;
the conversion module is used for converting the measurement class library into an alarm message based on a preset alarm rule by using the Prometheus Server module and pushing the alarm message to the Prometheus Alertmanager module;
and the display module is used for visually displaying the alarm message by using the Prometheus alert manager module.
In a third aspect, a computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method of the first aspect when executing the computer program.
In a fourth aspect, a computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of the first aspect described above.
According to the power grid monitoring system container service monitoring method and device based on the customized alarm rule, the monitoring data of each node device is obtained from the Prometheus Exporters module, the Prometheus Server module is used for pulling the measurement class library from the monitoring data, the Prometheus Server module is used for converting the measurement class library into the alarm message based on the preset alarm rule and pushing the alarm message to the Prometheus alert manager module, and then the Prometheus alert manager module is used for visually displaying the alarm message. According to the method, the monitoring data is automatically pulled, the alarm message is automatically converted and pushed, monitoring maintenance personnel are not required to participate in the whole process, the power grid monitoring method with high automation degree is realized, and the intelligence of power grid monitoring is greatly improved.
Drawings
FIG. 1 is a schematic diagram of a power grid monitoring system of a method for monitoring container services of the power grid monitoring system based on customized alarm rules in one embodiment;
FIG. 2 is a schematic flow chart illustrating a method for monitoring container services of a power grid monitoring system based on customized alarm rules in an embodiment;
FIG. 3 is a schematic flow chart illustrating a method for monitoring container services of a power grid monitoring system based on customized alarm rules in an embodiment;
FIG. 4 is a flowchart illustrating a method for monitoring container services of a power grid monitoring system based on customized alarm rules according to an embodiment;
FIG. 5 is a flowchart illustrating a method for monitoring container services for a grid monitoring system based on customized alarm rules according to an embodiment;
FIG. 6 is a flowchart illustrating a method for monitoring container services for a grid monitoring system based on customized alarm rules according to an embodiment;
FIG. 7 is a schematic structural diagram of a container service monitoring apparatus of a power grid monitoring system based on a customized alarm rule in an embodiment;
FIG. 8 is a schematic structural diagram of a container service monitoring apparatus of a power grid monitoring system based on customized alarm rules in an embodiment;
FIG. 9 is a schematic structural diagram of a container service monitoring apparatus of a power grid monitoring system based on a customized alarm rule in an embodiment;
FIG. 10 is a schematic structural diagram of a container service monitoring apparatus of a power grid monitoring system based on a customized alarm rule in an embodiment;
FIG. 11 is a diagram illustrating an internal structure of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The power grid monitoring system container server monitoring method based on the custom alarm rule can be applied to the power grid monitoring system shown in fig. 1. The power grid monitoring system can be a large power grid monitoring cluster, and comprises: the node devices 102 communicate with the grid monitoring platform 104 through a network, a Prometheus monitoring alarm system (Prometheus monitoring alarm frame) is installed on the grid monitoring platform 104, and monitoring data of each node device 102 can be monitored through the Prometheus monitoring alarm system on the grid monitoring platform 104. The node device 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the power grid monitoring platform 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, as shown in fig. 2, a method for monitoring container services of a power grid monitoring system based on a customized alarm rule is provided, which is described by taking the method as an example of being applied to the power grid monitoring platform in fig. 1, and includes the following steps:
s101, acquiring monitoring data of each node device from a Prometous Exporters module.
The Prometheus Exporters module is an interface module in the Prometheus monitoring alarm framework. The Prometheus monitoring alarm framework is an open-source system monitoring alarm framework, and Prometheus is a new-generation cloud native monitoring system, and has many advantages compared with a traditional monitoring system (such as a Nagios monitoring system or a Zabbix monitoring system). For example, the core part of the Prometheus monitoring alarm framework has only one single binary file and can directly work locally without relying on distributed storage. The Nagios monitoring system requires specialized personnel for installation, configuration and management, and is complicated. The Prometheus monitoring alarm framework is used for monitoring the running state of the service, and based on a Prometheus rich Client library, a user can easily add support for the Prometheus monitoring alarm framework in an application program, so that the user can obtain the service and the real running state in the application. Most of the monitoring capabilities of Nagios monitoring systems are marginal issues surrounding the system, mainly with respect to the status of system services and resources and the availability of applications. The Prometheus monitoring alarm framework can process millions of monitoring indexes and hundreds of thousands of data points per second, can be expanded by using a function partition and a federal cluster to form a logic cluster, and can provide client SDKs (software development kit) of multiple languages, and the SDKs can enable application programs to be quickly incorporated into the Prometheus monitoring alarm framework. The monitoring data may be performance state data during operation of a certain system, and the data represents the operation state of the system. The monitoring data may include abnormal alarm data of the system on each node device, normal operation data of the system, overhead data of the system, and other data related to each node device.
In this embodiment, a Prometheus monitoring alarm system (Prometheus monitoring alarm frame) may be installed in advance on the power grid monitoring platform. When the power grid monitoring platform wants to monitor each node device in the monitoring cluster in real time, each node device can upload the collected data to a Prometeus Exporters module in a Prometeus monitoring alarm system on the power grid monitoring platform, so that the power grid monitoring platform can obtain the data collected by each node device from the Prometeus Exporters module. Optionally, each node device may also upload respective data acquired in real time to a cloud database, so that a Prometheus Exporters module in a Prometheus monitoring alarm system on the power grid monitoring platform pulls the data acquired by each node device from the cloud database.
S102, using a Prometheus Server module to pull a measurement class library from the monitoring data.
The Prometheus Server module is a core part in a component of the Prometheus monitoring alarm framework and is responsible for acquiring, storing and inquiring monitoring data. The Prometeus Server can manage the monitoring targets through static configuration or dynamic management, and acquire data from the monitoring targets. When the Prometheus Server module needs to store the acquired data, the Prometheus Server module is a real-time database and stores the acquired monitoring data in a local disk in a time series manner. The Prometeus Server module provides self-defined PromQL for the outside, and the query and analysis of data are realized. Additionally, the federated cluster capability of the Prometheus Server module may enable it to obtain data from other Prometheus Server module instances. The metric class library is a basic unit in the Prometheus monitoring and warning system and can be an index (metric), and one metric corresponds to one record in a db table.
In this embodiment, when the power grid monitoring platform acquires the monitoring data of each node device based on the foregoing steps, the promemeus Server module may be called to convert the acquired monitoring data into the metric class library, so as to implement a pulling operation of the metric class library corresponding to the monitoring data; optionally, when the power grid monitoring platform acquires the monitoring data of each node device based on the foregoing steps, the power grid monitoring platform may also call the promemeus Server module to perform screening from the acquired monitoring data, screen out target data that needs to be monitored according to the requirements of maintenance personnel, and convert the screened target data into a measurement class library, so as to implement a pulling operation on the measurement class library corresponding to the screened target data.
Optionally, the protemeus Exporters module may expose an Endpoint (e.g., Endpoint) for collecting monitoring data to the protemeus Server module in the form of an HTTP service, and the protemeus Server module may obtain the monitoring data to be collected by accessing the Endpoint provided by the protemeus Exporters module.
S103, converting the measurement class library into an alarm message by using the Prometheus Server module based on a preset alarm rule and pushing the alarm message to the Prometheus Alertmanager module.
The preset alarm rule is a predefined alarm rule (for example, named alert.
In this embodiment, when the power grid monitoring platform obtains the measurement class library corresponding to the monitoring data, the Prometheus Server module may be called first to convert the measurement class library into an alarm message according to a preset alarm rule, and then the Prometheus Server module is called to push the alarm message to the Prometheus alert manager module for display, so that a maintainer may perform real-time monitoring on data on each node device. Optionally, when the power grid monitoring platform acquires the measurement class library corresponding to the monitoring data, processing work such as removing repeated data or grouping may be performed on the measurement class library, and then the processed measurement class library is converted into an alarm message according to a preset alarm rule to be pushed, and a specific pushing mode may be pushed in different modes such as an e-mail, a pager, a webhook, and the like.
S104, using a Prometous Alertmanager module to visually display the alarm message.
After the power grid monitoring platform pushes the alarm message to the Prometous Alertmanager module through the Prometous Server module, the Prometous Alertmanager module can be used for visually displaying the alarm message on a display interface, and during specific display, information such as generation time, generation reason, alarm type, identification, generation position and the like of each alarm message can be visually displayed, so that maintenance personnel can clearly learn the software and hardware running state and fault state of each node device, and timely find problems to monitor the maintenance and management of the cluster.
In the method for monitoring container service of a power grid monitoring system based on a customized alarm rule, monitoring data of each node device is obtained from a Prometheus Exporters module, a Prometheus Server module is used for pulling a measurement class library from the monitoring data, the measurement class library is converted into an alarm message based on a preset alarm rule by the Prometheus Server module and is pushed to a Prometheus Alertmanager module, and then the alarm message is visually displayed by the Prometheus Alertmanager module. According to the method, the monitoring data is automatically pulled, the alarm message is automatically converted and pushed, monitoring maintenance personnel are not required to participate in the whole process, the power grid monitoring method with high automation degree is realized, and the intelligence of power grid monitoring is greatly improved.
In an embodiment, when the power grid monitoring platform performs the step of S102, that is, the Prometheus Server module is used to obtain monitoring data from the Prometheus Exporters module, and convert the monitoring data into data of the metric class library, the Prometheus Server module may further store the converted metric class library, that is, after the power grid monitoring platform performs the step of S102, as shown in fig. 3, the method may further perform the steps of:
and S105, storing the measurement class library by using a Prometheus Server module.
Specifically, the Prometheus Server module is a real-time database, all the Prometheus Server modules can periodically pull the metric class library from the monitoring data collected from the Prometheus Exporters module, store the pulled metric class library, and specifically store the monitoring data in a local disk in a time series manner, so that the power grid monitoring platform can conveniently and directly acquire the metric class library from the Prometheus Server module for processing.
In practical applications, after the power grid monitoring platform performs the step S103, as shown in fig. 4, the following steps may be further performed:
s106, using a Prometous alert manager module to dispatch the alarm message.
After the power grid monitoring platform pushes the alarm message to the Prometous Alertmanager module through the Prometous Server module, a scheduling processing interface related to the alarm message can be provided for an operator on the display equipment, so that the operator can conveniently perform corresponding scheduling processing on the alarm message; optionally, the power grid monitoring platform may further determine a scheduling processing policy corresponding to the alarm message by analyzing the alarm message, analyzing information such as a generation reason, an alarm type, an identifier, and a generation location of the alarm message, and then automatically perform corresponding scheduling processing on the alarm message according to the scheduling processing policy.
When each device in the power grid monitoring system shown in fig. 1 operates, each node device may acquire operation data of each system in real time, including normal operation data and abnormal operation data, may also acquire abnormal alarm data of each system and overhead data of the system, and may also acquire operation state data of each system. After various types of monitoring data are collected by each node device, various corresponding mirror image files can be further generated according to the collected monitoring data, and the generated mirror image files are uploaded to a mirror image warehouse for storage. In the application scenario, when the power grid monitoring platform in the power grid monitoring system needs to monitor each node device, that is, before the step of S101 is executed, as shown in fig. 5, the following steps may also be executed:
s201, the monitoring data of each node device in the power grid monitoring system is pulled from the mirror image warehouse.
When a power grid monitoring platform in the power grid monitoring system needs to monitor each node device, image files corresponding to various stored monitoring data can be directly downloaded or pulled from an image warehouse, and the pulled or downloaded image files are analyzed into corresponding monitoring data.
S202, the monitoring data is transmitted to a Prometheus Exporters module.
When the power grid monitoring platform acquires the monitoring data from the mirror image warehouse, the monitoring data can be transmitted to the Prometeus Exporters module, so that the power grid monitoring platform can rapidly collect the monitoring data through the Prometeus Exporters module.
Further, when the power grid monitoring platform specifically executes the step S201, the following steps may be specifically executed: and a container arrangement engine in the container cluster management system is used for pulling the monitoring data of each node device in the power grid monitoring system from the mirror image warehouse.
Wherein the mirror repository is a management tool for storing and distributing container mirrors. The container cluster management system can be installed on the power grid monitoring platform in advance and used for achieving container management on the power grid monitoring platform. The container arrangement engine is used for downloading or pulling images or image files corresponding to various containers from the image warehouse.
Specifically, the container cluster management system may be a kubernets container cluster management system, and it should be noted that the kubernets container cluster management system may be a Google open-source container cluster management system, and a design target of the system is to provide a platform capable of automatic deployment, expansion, and application container operation among host clusters. The kubernets container cluster management system works by combining a Docker container tool and integrates a plurality of host clusters running Docker containers, and the kubernets not only supports Docker, but also supports socket, which is another container technology. In this embodiment, the mirror warehouse is a Harbor mirror warehouse. It should be noted that the Harbor mirror repository may be an open-source container mirror repository, and the Harbor mirror repository is correspondingly expanded at an enterprise level, and has new enterprise characteristics including: management user interface, role-based access control, AD/LDAP integration, audit logs, and the like.
In this embodiment, when the power grid monitoring platform in the power grid monitoring system needs to monitor each node device, the container arrangement engine in the container cluster management system may be directly used to quickly download or pull various images or various image files stored in the image warehouse from the image warehouse, and analyze the pulled or downloaded various image files into corresponding monitoring data of each node device.
Optionally, the container cluster management system may be further installed on a container management server, that is, the power grid monitoring system may further include a container management server, and when a power grid monitoring platform in the power grid monitoring system needs to monitor each node device, the container management server in the power grid monitoring system may use a container arrangement engine in the container cluster management system to quickly download or pull various images or various image files stored in the image warehouse from the image warehouse, analyze the pulled or downloaded various image files into monitoring data of each corresponding node device, and further send the monitoring data to the power grid monitoring platform, or the power grid monitoring platform actively reads the monitoring data from the container management server.
Correspondingly, when the power grid monitoring platform executes the step S202 "transmitting the monitoring data to the Prometheus Exporters module", the specific execution steps are as follows: the monitoring data is transmitted to the Prometheus Exporters module using the container orchestration engine.
When the power grid monitoring platform uses the container arrangement engine to pull the monitoring data from the mirror image warehouse, the container arrangement engine can be further used to transmit the monitoring data to the Prometeus Exporters module, so that the power grid monitoring platform can rapidly collect the monitoring data through the Prometeus Exporters module.
By combining all the above embodiments, the present application further provides a method for monitoring a container service of a power grid monitoring system based on a customized alarm rule, as shown in fig. 6, including:
s301, a container arrangement engine in the container cluster management system is used for pulling monitoring data of each node device in the power grid monitoring system from a mirror image warehouse.
S302, the container arrangement engine is used for transmitting the monitoring data to a Prometheus Exporters module.
S303, acquiring the monitoring data of each node device from the Prometheus Exporters module.
S304, using a Prometheus Server module to pull the measurement class library from the monitoring data and storing the measurement class library.
S305, the Prometheus Server module is used for converting the measurement class library into an alarm message based on a preset alarm rule and pushing the alarm message to the Prometheus Alertmanager module.
S306, using a Prometous Alertmanager module to visually display the alarm message.
S307, using a Prometous alert manager module to perform scheduling processing on the alarm message.
The above steps are described in the foregoing, and for details, refer to the foregoing description, which is not repeated herein.
It should be understood that although the various steps in the flow charts of fig. 2-6 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-6 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
In one embodiment, as shown in fig. 7, there is provided a power grid monitoring system container server monitoring apparatus based on a customized alarm rule, including:
an obtaining module 11, configured to obtain monitoring data of each node device from the Prometheus Exporters module.
A first pulling module 12, configured to pull the metric class library from the monitoring data using a promemeus Server module.
A conversion module 13, configured to use the Prometheus Server module to convert the metric class library into an alarm message based on a preset alarm rule, and push the alarm message to the Prometheus alert manager module.
And the display module 14 is configured to perform visual display on the alarm message by using the Prometheus alert manager module.
In one embodiment, as shown in fig. 8, the above apparatus further comprises:
and the storage module 15 is used for storing the measurement class library by using a Prometous Server module.
In one embodiment, as shown in fig. 9, the above apparatus further comprises:
and the scheduling module 16 is configured to perform scheduling processing on the alarm message by using the Prometheus alert manager module.
In one embodiment, as shown in fig. 10, the above apparatus further comprises:
and the second pulling module 17 is used for pulling the monitoring data of each node device in the power grid monitoring system from the mirror image warehouse.
A transmission module 18, configured to transmit the monitoring data to the Prometheus Exporters module.
In an embodiment, the second pulling module 17 is specifically configured to pull the monitoring data of each node device in the power grid monitoring system from the mirror warehouse by using a container arrangement engine in the container cluster management system.
Correspondingly, the transmitting module 18 is specifically configured to transmit the monitoring data to the Prometheus Exporters module by using the container arrangement engine.
In one embodiment, the container cluster management system is a kubernets container cluster management system.
In one embodiment, the mirror repository is a Harbor mirror repository.
For specific limitations of the monitoring apparatus for the container server of the power grid monitoring system based on the customized alarm rule, reference may be made to the above limitations of the monitoring method for the container server of the power grid monitoring system based on the customized alarm rule, which are not described herein again. All modules in the power grid monitoring system container server monitoring device based on the customized alarm rule can be completely or partially realized through software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 11. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to realize a monitoring method of a container server of the power grid monitoring system based on the customized alarm rule. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 11 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring monitoring data of each node device from a Prometous Exporters module;
using a Prometheus Server module to pull a measurement class library from the monitoring data;
converting the measurement class library into an alarm message by using the Prometheus Server module based on a preset alarm rule and pushing the alarm message to a Prometheus Alertmanager module;
and using the Prometheus Alertmanager module to visually display the alarm message.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the metrics class library is stored using a Prometheus Server module.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and scheduling the alarm message by using the Prometous Alertmanager module.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the method comprises the steps of pulling monitoring data of each node device in a power grid monitoring system from a mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
a container arrangement engine in the container cluster management system is used for pulling monitoring data of each node device in the power grid monitoring system from the mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module using the container orchestration engine.
The implementation principle and technical effect of the computer device provided by the above embodiment are similar to those of the above method embodiment, and are not described herein again.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring monitoring data of each node device from a Prometous Exporters module;
using a Prometheus Server module to pull a measurement class library from the monitoring data;
converting the measurement class library into an alarm message by using the Prometheus Server module based on a preset alarm rule and pushing the alarm message to a Prometheus Alertmanager module;
and using the Prometheus Alertmanager module to visually display the alarm message.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the metrics class library is stored using a Prometheus Server module.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and scheduling the alarm message by using the Prometous Alertmanager module.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the method comprises the steps of pulling monitoring data of each node device in a power grid monitoring system from a mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module.
In one embodiment, the computer program when executed by the processor further performs the steps of:
a container arrangement engine in the container cluster management system is used for pulling monitoring data of each node device in the power grid monitoring system from the mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module using the container orchestration engine.
The implementation principle and technical effect of the computer-readable storage medium provided by the above embodiments are similar to those of the above method embodiments, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A power grid monitoring system container service monitoring method based on a custom alarm rule is characterized by comprising the following steps:
acquiring monitoring data of each node device from a Prometous Exporters module;
using a Prometheus Server module to pull a measurement class library from the monitoring data;
converting the measurement class library into an alarm message by using the Prometheus Server module based on a preset alarm rule and pushing the alarm message to a Prometheus Alertmanager module;
and using the Prometheus Alertmanager module to visually display the alarm message.
2. The method of claim 1, further comprising:
the metrics class library is stored using a Prometheus Server module.
3. The method of claim 1, further comprising:
and scheduling the alarm message by using the Prometous Alertmanager module.
4. The method according to any one of claims 1-3, wherein before said obtaining monitoring data of each node device from Prometous Exporters module, the method further comprises:
the method comprises the steps of pulling monitoring data of each node device in a power grid monitoring system from a mirror image warehouse;
transmitting the monitoring data to the Prometheus Exporters module.
5. The method according to claim 4, wherein the extracting of the monitoring data of each node device in the power grid monitoring system from the mirror image warehouse comprises:
a container arrangement engine in the container cluster management system is used for pulling monitoring data of each node device in the power grid monitoring system from the mirror image warehouse;
the transmitting the monitoring data to the Prometheus Exporters module includes:
transmitting the monitoring data to the Prometheus Exporters module using the container orchestration engine.
6. The method of claim 5, wherein the container cluster management system is a kubernets container cluster management system.
7. The method of claim 4, wherein the mirror store is a Harbor mirror store.
8. A power grid monitoring system container service monitoring device based on custom alarm rules, the device comprising:
the acquisition module is used for acquiring the monitoring data of each node device from the Prometous Exporters module;
the first pulling module is used for pulling a metric class library from the monitoring data by using a Prometheus Server module;
the conversion module is used for converting the measurement class library into an alarm message based on a preset alarm rule by using the Prometheus Server module and pushing the alarm message to the Prometheus Alertmanager module;
and the display module is used for visually displaying the alarm message by using the Prometheus alert manager module.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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