CN114968717A - Data acquisition method and device, electronic equipment and storage medium - Google Patents

Abstract

The present disclosure provides a data collection method, device, electronic device and storage medium, which relate to the technical field of computers, and in particular, to the technical field of the Internet of Things and edge computing. The specific implementation scheme includes: determining the edge operation mode of the edge end; obtaining a data collection application adapted to the edge operation mode, and installing and deploying the data collection application; The preset indicator data at the edge is collected. The disclosed solution achieves the effect of collecting index data for each edge end in different edge operation modes.

Description

A data acquisition method, device, electronic device and storage medium

technical field

The present disclosure relates to the field of computer technology, in particular to the field of Internet of Things and edge computing technology, and in particular to a data collection method, apparatus, electronic device, storage medium and computer program product.

Background technique

Edge computing refers to the use of an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of objects or data to provide the most recent services nearby. With the development of the Internet of Things, edge computing is gradually being valued by more and more industries.

SUMMARY OF THE INVENTION

The present disclosure provides a data acquisition method, apparatus, electronic device, storage medium and computer program product.

According to an aspect of the present disclosure, a data collection method is provided, comprising:

Determine the edge operating mode at the edge side;

Obtain data collection applications that are compatible with the edge operating mode, and install and deploy the data collection applications;

The preset indicator data at the edge is collected through the installed data collection application.

According to an aspect of the present disclosure, a data acquisition device is provided, comprising:

The mode determination module is used to determine the edge operation mode of the edge end;

The application acquisition and deployment module is used to acquire data collection applications that are compatible with the edge operation mode, and to install and deploy the data collection applications;

The data collection module is used to collect the preset index data of the edge end through the installed data collection application.

According to another aspect of the present disclosure, there is provided an electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the data collection method of any embodiment of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the data acquisition method of any embodiment of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product including a computer program that, when executed by a processor, implements the data acquisition method of any embodiment of the present disclosure.

According to the technology of the present disclosure, the effect of collecting index data for each edge end in different edge operation modes is achieved.

It should be understood that what is described in this section is not intended to identify key or critical features of embodiments of the disclosure, nor is it intended to limit the scope of the disclosure. Other features of the present disclosure will become readily understood from the following description.

Description of drawings

The accompanying drawings are used for better understanding of the present solution, and do not constitute a limitation to the present disclosure. in:

1 is a schematic flowchart of a data collection method provided by an embodiment of the present disclosure;

2 is a schematic flowchart of another data collection method provided by an embodiment of the present disclosure;

3 is a schematic flowchart of another data collection method provided by an embodiment of the present disclosure;

4 is a schematic structural diagram of a data acquisition device provided by an embodiment of the present disclosure;

FIG. 5 is a block diagram of an electronic device used to implement the data collection method of an embodiment of the present disclosure.

Detailed ways

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

FIG. 1 is a schematic flowchart of a data collection method according to an embodiment of the present disclosure. This embodiment can be applied to a situation in which preset index data at an edge is collected in an Internet of Things or edge computing scenario. The method can be performed by a data acquisition device, which is implemented in software and/or hardware and integrated on an electronic device, for example, an edge device.

Specifically, referring to Figure 1, the data collection method is as follows:

S101. Determine the edge operation mode of the edge end.

In this embodiment of the present disclosure, the edge terminal may be any edge device that can be networked in an edge scenario. For example, the edge terminal may be a server device, a smart meter in daily life, or a roadside at a road intersection. smart devices, etc. Due to the different performance of different edge terminals, different edge operation modes are derived. Among them, the edge operation modes of the edge terminal can be divided into two types: container mode and process mode. Optionally, the container mode can be used for the edge end with strong performance, so as to execute more specialized services; while the edge end with relatively low performance and single service can adopt the process mode. It should be noted that the container mode means that edge-side applications (such as business applications or system applications) are implemented and run through containers; and the process mode means that edge-side applications are run through edge-side system processes. In the solution of the present disclosure, when the edge operation mode of the edge end is determined, it may be determined according to the configuration file of the edge end, or may be determined by other methods, which are not specifically limited herein.

S102: Acquire a data collection application that is compatible with the edge operation mode, and install and deploy the data collection application.

In the embodiment of the present disclosure, in the cloud connected to each edge terminal, different data collection applications may be preconfigured for different edge operation modes, so that after determining the edge operation mode of each edge terminal in the edge scene through S101, you can directly According to the determined edge operation mode, the data collection application adapted to it is obtained from the cloud, and the data collection application is installed and deployed. It should be noted here that because the preset indicator data to be collected is different in different edge operation modes, if the edge operation mode of the edge end is not considered, all the edge ends use the same data collection application to obtain the preset indicator data, which will lead to The problem of incomplete collection of indicator data. For example, some indicator data can be collected in container mode, but cannot be collected in process mode. This solution deploys different data collection applications for different edge operation modes, which can just avoid this problem.

In the embodiment of the present disclosure, the data collection application adapted to the edge operation mode may also be integrated into the system application at the edge, and is deployed along with the installation of the system application.

S103: Collect preset index data at the edge end through the installed data collection application.

In the embodiment of the present disclosure, after the data collection application is installed through the step of S102, the preset index data of the edge end is collected in combination with the edge operation mode of the edge end. Wherein, the preset index data includes at least one of edge-end host state index data, edge-end application state index data, and edge-end component state index data. Exemplarily, the edge-side host status indicator data includes but is not limited to host CPU usage information, memory usage information, disk, network information, etc.; edge-side application status indicator data includes but is not limited to application CPU usage information, memory usage information, running Status, etc.; edge component status indicator data includes, but is not limited to, the temperature, power consumption, computing power usage, and video memory usage of common accelerator cards or graphics cards. In this way, by collecting the above-mentioned preset indicator data, a guarantee is provided for the subsequent monitoring of the state of the edge terminal.

In the embodiments of the present disclosure, different data collection applications are installed to collect data according to different edge operation modes, so as to achieve the purpose of collecting index data for each edge terminal under different edge operation modes, and avoid the occurrence of parts due to different edge operation modes. The problem that the indicator data cannot be collected.

Further, through the index data collected in S103, the working status of the edge terminal can be effectively obtained, so that the abnormality of the edge terminal can be detected in time and an alarm notification can be performed. The specific process of realizing the alarm is as follows: After the data collection application collects the preset indicator data, it reports it to the cloud, and the cloud stores the received preset indicator data, for example, the indicator data reported by the edge is stored in the preset database. In the example, the preset indicator data is stored in the MySql database. Further, the cloud also provides a data exposure function, which is mainly responsible for obtaining the preset indicator data reported by the edge from the database, and reorganizing the preset indicator data with a general specification (ie, the preset data processing specification), and then through the preset indicator data. Set a service port (such as a network port) for exposure; it should be noted that the reason for reorganizing and standardizing the preset indicator data is that the collected preset indicator data is usually stored according to a custom data structure, in order to be able to connect to the open source alarm system , the data format of the collected preset indicator data needs to be converted into a general data format. Further, in order to distinguish the data of each preset indicator from different edge terminals and different applications of the same edge terminal, when organizing the preset indicator data, each indicator data will be labeled, that is, by specifying the preset indicator data. The method of adding source labels to the data distinguishes the sources of the data of each preset indicator. Further, the alarm system connected to the cloud can regularly pull preset indicator data according to the ports exposed in the cloud, and then store it in the time series database, which is convenient for subsequent viewing of historical indicator data and visual display. Further, the visual front-end console of the alarm system can directly obtain the stored preset indicator data from the time series database, and filter the data according to the tags in the preset indicator data, so as to automatically distinguish the data belonging to different edge terminals or different edge applications. Default indicator data. Further, the alarm system can determine the alarm rules, alarm notification destinations and alarm notification types (such as SMS, email, etc.) set by the user for different preset indicators of the edge terminal according to the user's configuration data. When an indicator triggers an alarm event, , it will trigger the corresponding alarm and notify the specified destination. In this way, an edge-side alarm scheme that supports multiple edge operation modes is realized.

FIG. 2 is a schematic flowchart of yet another data collection method according to an embodiment of the present disclosure. Referring to Figure 2, the data collection method is as follows:

S201. Determine an edge operation mode of an edge end; wherein, the edge operation mode of the edge end is a container mode or a process mode.

S202: Acquire a data collection application that is compatible with the edge operation mode, and install and deploy the data collection application.

For the specific description of S201-S202, reference may be made to the foregoing embodiments, which will not be repeated here. In the embodiment of the present disclosure, since the edge operation mode of the edge end can be either a container mode or a process mode, and in different edge operation modes, the specific process of collecting preset indicator data is also different. Specifically, if the edge operation mode is the container mode, data collection is performed according to the steps of S203; if the edge operation mode is the process mode, data collection is performed according to the steps of S204-S205. The preset index data to be collected in the disclosed solution is as follows: edge-end host state index data, edge-end application state index data, and edge-end component state index data. Among them, the edge-side host status indicator data includes but is not limited to host CPU usage information, memory usage information, disk, network information, etc.; edge-side application status indicator data includes but is not limited to application CPU usage information, memory usage information, running status, etc. ; The status indicator data of components on the edge includes but not limited to the temperature, power consumption, computing power usage, and video memory usage of common accelerator cards or graphics cards.

S203. In the container mode, the data collection application connects to the data aggregation service through a preset container interface, and obtains the preset indicator data of the edge end from the data aggregation service; and, the data collection application obtains the edge data through the built-in component identification and collection service. Default indicator data.

In the embodiment of the present disclosure, when the edge operation mode of the edge end is the container mode, the data aggregation service is a service provided by the container orchestration management tool kubernetes, which is used to monitor and aggregate the edge end host state indicator data and application state indicator data , so that after the data collection application connects to the data aggregation service through the preset container interface, it can directly obtain preset indicator data such as edge host status indicator data and application status indicator data from the data aggregation service.

In addition, for the collection of edge device status indicator data in container mode, the data collection application also integrates the component identification and collection service. The component identification and collection service will identify the components that make up the edge. For example, the edge can be identified. At the same time, the associated data of the identified components will be collected, so as to realize the temperature, power consumption, computing power utilization, and video memory utilization of the edge components such as the acceleration card or graphics card. collection of information.

S204. In the process mode, determine the system architecture of the edge terminal.

In the process mode, to collect indicator data, it is necessary to first determine the system architecture of the edge, for example, it can be determined directly from the system configuration file. Exemplarily, the system architecture of the edge end may be any one of a Linux system, an Android system, a Windows system, and a darwin system.

S205 , the data collection application is connected to the system index collection instruction or system file according to the system architecture of the edge end, so as to collect the preset index data of the edge end.

For different system architectures, the data collection application can adaptively connect to different system files or index collection instructions to collect the required index data information. Exemplarily, in the process mode, if the system architecture of the edge is a linux system, the data collection application collects kernel system information by connecting to the system, such as obtaining cpu information from the /proc/cpuinfo directory, and obtaining the cpu information from the /proc/meminfo directory. Obtain memory information, etc.; if the system architecture of the edge is a Windows system, the information such as the CPU and memory of the Windows system will be obtained through the docking system plug-in.

In the embodiments of the present disclosure, not only the effect of collecting index data for each edge terminal in different edge operation modes is achieved, but also in the process mode, the purpose of obtaining index data under different system architectures is achieved. That is, the data collection solution of the present disclosure supports multi-edge operation modes and multi-system architectures, and has strong versatility.

FIG. 3 is a schematic flowchart of yet another data collection method according to an embodiment of the present disclosure. Referring to Figure 3, the data collection method is as follows:

S301. In response to an edge node installation instruction sent by the cloud, install an edge node on an edge terminal.

Wherein, the edge node installation instruction at least includes the node operation mode.

S302. Use the node operation mode as the edge operation mode of the edge end.

In the edge scenario, in order to realize the communication management between the cloud and the edge, first create an edge node in the cloud and determine the operation mode of the edge node, and then install the corresponding edge node on the edge that needs to be managed. Specifically, after receiving the edge node installation instruction sent by the cloud, the edge terminal performs an operation of installing the edge node on the edge terminal. On this basis, the node operation mode can be directly used as the edge operation mode of the edge. Among them, the edge running mode of the edge is the container mode or the process mode.

S303: Acquire a data collection application that is compatible with the edge operation mode, and install and deploy the data collection application.

In the embodiment of the present disclosure, if the edge operation mode of the edge terminal is the container mode, the cloud sends the data collection application adapted to the container mode to the edge terminal for installation and deployment; otherwise, if the edge operation mode of the edge terminal is the process mode, The cloud sends the data collection application that matches the process mode to the edge for installation and deployment. In this way, data collection can be ensured for the edge ends of different edge operation modes.

S304 , collect the preset index data of the edge terminal through the installed data collection application.

Optionally, in the container mode, the data collection application connects to the data aggregation service through a preset container interface, and obtains the preset indicator data at the edge from the data aggregation service; and, the data collection application obtains through the built-in component identification and collection service Preset indicator data at the edge. In the process mode, the system architecture of the edge end is determined; the data collection application connects to the system index collection instruction or system file according to the system architecture of the edge end to collect the preset index data of the edge end.

In the embodiment of the present disclosure, the node operation mode included in the installation instruction of the edge node is used as the edge operation mode of the edge end, so that the edge operation mode of the edge end can be quickly determined; and then the edge end index data is collected through a data collection application adapted to the edge operation mode , to achieve the data collection effect that supports the multi-edge operation mode.

FIG. 4 is a schematic structural diagram of a data collection apparatus according to an embodiment of the present disclosure. This embodiment may be applicable to the case of collecting preset index data at the edge in an Internet of Things or edge computing scenario. See Figure 4, including:

a mode determination module 401, configured to determine the edge operation mode of the edge end;

An application acquisition and deployment module 402, configured to acquire a data collection application adapted to the edge operation mode, and to install and deploy the data collection application;

The data collection module 403 is configured to collect the preset index data of the edge end through the installed data collection application.

On the basis of the foregoing embodiment, optionally, the edge running mode of the edge terminal is a container mode or a process mode.

On the basis of the above embodiment, optionally, the data acquisition module is also used for:

In the container mode, the data collection application connects to the data aggregation service through the preset container interface, and obtains the preset indicator data of the edge side from the data aggregation service; and, the data collection application obtains the preset index data of the edge side through the built-in component identification and collection service indicator data.

On the basis of the above embodiment, optionally, the data acquisition module is also used for:

In process mode, determine the system architecture of the edge;

According to the system architecture of the edge end, the data collection application connects to the system index collection instruction or system file to collect the preset index data of the edge end.

On the basis of the foregoing embodiment, optionally, the mode determination module is further configured to:

In response to the edge node installation instruction sent by the cloud, the edge node is installed on the edge terminal; wherein the edge node installation instruction at least includes the node operation mode;

Use the node operating mode as the edge operating mode on the edge side.

On the basis of the foregoing embodiment, optionally, the preset indicator data includes at least one of edge-end host state index data, edge-end application state index data, and edge-end component state index data.

On the basis of the above-mentioned embodiment, optional, also includes:

The data reporting module is used to report the collected preset indicator data to the cloud, so that the cloud can process the preset indicator data as follows:

Store the received preset indicator data;

Based on the preset data processing specification, organize the stored preset indicator data, and add source tags to the preset indicator data;

The pre-organized preset indicator data is exposed through the preset service port, so that the alarm system connected to the cloud can issue an alarm according to the preset indicator data exposed in the cloud and combined with the preset alarm parameters; wherein, the alarm parameters include alarm rules and alarms. Destination and alert notification type.

The data collection device provided by the embodiment of the present disclosure can execute the data collection method provided by any embodiment of the present disclosure, and has functional modules and beneficial effects corresponding to the execution method. For the content not described in detail in this embodiment, reference may be made to the description in any method embodiment of the present disclosure.

In the technical solution of the present disclosure, the acquisition, storage and application of the user's personal information involved are all in compliance with the provisions of relevant laws and regulations, and do not violate public order and good customs.

According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

5 shows a schematic block diagram of an example electronic device 500 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.

As shown in FIG. 5 , the device 500 includes a computing unit 501 that can be executed according to a computer program stored in a read only memory (ROM) 502 or loaded from a storage unit 508 into a random access memory (RAM) 503 Various appropriate actions and handling. In the RAM 503, various programs and data necessary for the operation of the device 500 can also be stored. The computing unit 501 , the ROM 502 , and the RAM 503 are connected to each other through a bus 504 . An input/output (I/O) interface 505 is also connected to bus 504 .

Various components in the device 500 are connected to the I/O interface 505, including: an input unit 506, such as a keyboard, mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, an optical disk, etc. ; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks.

Computing unit 501 may be various general-purpose and/or special-purpose processing components with processing and computing capabilities. Some examples of computing units 501 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various specialized artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as data acquisition methods. For example, in some embodiments, the data acquisition method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 508 . In some embodiments, part or all of the computer program may be loaded and/or installed on device 500 via ROM 502 and/or communication unit 509 . When a computer program is loaded into RAM 503 and executed by computing unit 501, one or more steps of the data acquisition method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the data acquisition method by any other suitable means (eg, by means of firmware).

Various implementations of the systems and techniques described herein above can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips system (SOC), complex programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpretable on a programmable system including at least one programmable processor that The processor, which may be a special purpose or general-purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device an output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, performs the functions/functions specified in the flowcharts and/or block diagrams. Action is implemented. The program code may execute entirely on the machine, partly on the machine, partly on the machine and partly on a remote machine as a stand-alone software package or entirely on the remote machine or server.

In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with the instruction execution system, apparatus or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media may include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), fiber optics, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and can be in any form (including acoustic input, voice input, or tactile input) to receive input from the user.

The systems and techniques described herein may be implemented on a computing system that includes back-end components (eg, as a data server), or a computing system that includes middleware components (eg, an application server), or a computing system that includes front-end components (eg, a user's computer having a graphical user interface or web browser through which a user may interact with implementations of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

A computer system can include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a distributed system server, or a server combined with blockchain.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present disclosure can be executed in parallel, sequentially, or in different orders. As long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, there is no limitation herein.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present disclosure should be included within the protection scope of the present disclosure.

Claims (17)

1. A data collection method, comprising: Determine the edge operating mode at the edge side; acquiring a data collection application that is compatible with the edge operation mode, and installing and deploying the data collection application; The preset index data of the edge terminal is collected through the installed data collection application. 2. The method according to claim 1, wherein the edge operation mode of the edge terminal is a container mode or a process mode. 3. The method according to claim 2, wherein the preset indicator data of the edge terminal is collected by the installed data collection application, comprising: In the container mode, the data collection application connects to the data aggregation service through a preset container interface, and obtains the preset indicator data of the edge end from the data aggregation service; and, the data collection application uses the built-in The component identification and collection service obtains the preset index data of the edge. 4. The method according to claim 2, wherein the preset indicator data of the edge terminal is collected by the data collection application after installation, comprising: In the process mode, determine the system architecture of the edge; The data collection application is connected to a system indicator collection instruction or a system file according to the system architecture of the edge end, so as to collect preset indicator data of the edge end. 5. The method of claim 1, wherein determining the edge operating mode of the edge comprises: In response to an edge node installation instruction sent by the cloud, an edge node is installed on the edge terminal; wherein the edge node installation instruction at least includes a node operation mode; The node operation mode is used as the edge operation mode of the edge end. 6 . The method according to claim 1 , wherein the preset indicator data comprises at least one of edge-end host state index data, edge-end application state index data, and edge-end component state index data. 7 . 7. The method of claim 1, further comprising: The collected preset indicator data is reported to the cloud, so that the cloud performs the following processing on the preset indicator data: storing the received preset indicator data; Organizing the stored preset indicator data based on the preset data processing specification, and adding a source tag to the preset indicator data; The pre-organized preset indicator data is exposed through the preset service port, so that the alarm system connected to the cloud can issue an alarm according to the preset indicator data exposed by the cloud and combined with preset alarm parameters; wherein, the alarm Parameters include alert rule, alert destination, and alert notification type. 8. A data acquisition device, comprising: The mode determination module is used to determine the edge operation mode of the edge end; an application acquisition and deployment module, configured to acquire a data acquisition application adapted to the edge operation mode, and to install and deploy the data acquisition application; The data collection module is used to collect the preset index data of the edge end through the installed data collection application. 9. The apparatus according to claim 8, wherein the edge operation mode of the edge terminal is a container mode or a process mode. 10. The apparatus of claim 9, wherein the data acquisition module is further configured to: In the container mode, the data collection application connects to the data aggregation service through a preset container interface, and obtains the preset indicator data of the edge end from the data aggregation service; and, the data collection application uses the built-in The component identification and collection service obtains the preset index data of the edge. 11. The apparatus of claim 9, wherein the data acquisition module is further configured to: In the process mode, determine the system architecture of the edge; The data collection application is connected to a system indicator collection instruction or a system file according to the system architecture of the edge end, so as to collect preset indicator data of the edge end. 12. The apparatus of claim 8, wherein the mode determination module is further configured to: In response to an edge node installation instruction sent by the cloud, an edge node is installed on the edge terminal; wherein the edge node installation instruction at least includes a node operation mode; The node operation mode is used as the edge operation mode of the edge end. 13. The apparatus according to claim 8, wherein the preset indicator data comprises at least one of edge-end host state index data, edge-end application state index data, and edge-end component state index data. 14. The apparatus of claim 8, further comprising: A data reporting module, configured to report the collected preset indicator data to the cloud, so that the cloud performs the following processing on the preset indicator data: storing the received preset indicator data; Organizing the stored preset indicator data based on the preset data processing specification, and adding a source tag to the preset indicator data; The pre-organized preset indicator data is exposed through the preset service port, so that the alarm system connected to the cloud can issue an alarm according to the preset indicator data exposed by the cloud and combined with preset alarm parameters; wherein, the alarm Parameters include alert rule, alert destination, and alert notification type. 15. An electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the execution of any of claims 1-7 Methods. 16. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any of claims 1-7. 17. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-7.

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