Data monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses a data monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of obtaining corresponding monitoring operation information in response to a data monitoring instruction, calling a first large model, and selecting a corresponding operation page; acquiring code data of an operation page, calling a second large model, identifying a target position in the code data, extracting an inspection parameter value from the monitoring operation information, updating the target position with the inspection parameter, and triggering an inspection instruction based on the updated code data; receiving an inspection result corresponding to the inspection instruction, calling the third model, identifying corresponding abnormal data from the inspection result, and generating a monitoring state corresponding to the monitoring index; and sending the abnormal data and the monitoring state. According to the embodiment, the problems that a data monitoring obtaining mode through a crawler technology needs to be high in cost, and especially when a monitoring platform changes, manual adjustment and even reconstruction are needed, and efficiency is low can be solved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a data monitoring method, device, electronic equipment and storage medium. Background Art

[0002] In various business processing scenarios, in order to ensure data security, data centers or systems usually set up visual monitoring platforms so that business personnel can monitor data through the monitoring platform. In related technologies, data monitoring can be achieved through crawler technology, that is, writing crawler code for pages in various business scenarios to obtain the required data, but this method is costly, especially when the monitoring platform changes, it needs to manually adjust the program or even reconstruct it, which is inefficient. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a data monitoring method, device, electronic device and storage medium, which can solve the problem that data monitoring obtained through crawler technology requires high costs, especially when the monitoring platform changes, manual adjustments or even reconstruction are required, and the efficiency is low.

[0004] To achieve the above objective, according to one aspect of an embodiment of the present invention, a method for data monitoring is provided.

[0005] A data monitoring method of an embodiment of the present invention includes: responding to a data monitoring instruction, obtaining corresponding monitoring operation information, calling a first large model to select a corresponding operation page; obtaining code data of the operation page, calling a second large model to identify a target position in the code data, extracting inspection parameter values ​​from the monitoring operation information to update the inspection parameters to the target position, and triggering an inspection instruction based on the updated code data; receiving an inspection result corresponding to the inspection instruction, calling a third large model to obtain a monitoring indicator, identifying corresponding abnormal data from the inspection result, and generating a monitoring status corresponding to the monitoring indicator; and sending the abnormal data and the monitoring status.

[0006] In one embodiment, inspection parameter values ​​are extracted from the monitoring operation information to update the inspection parameters to the target position, including: extracting the inspection type from the monitoring operation information, querying the inspection parameter sequence corresponding to the inspection type, extracting the parameter value of each inspection parameter in the inspection parameter sequence, and storing each parameter in a preset queue based on the inspection parameter sequence; and updating the target position corresponding to each parameter value according to the storage order of each parameter value in the preset queue.

[0007] In another embodiment, calling the second largest model to identify the target position in the code data includes: calling the second largest model to identify the page component set of the operation page, screening the inspection parameter input components to determine the corresponding code data, and determining the position of the parameters to be input in the code data as the target position.

[0008] In another embodiment, a page component set of the operation page is identified, and inspection parameter input components are screened, including: identifying the page layout of the operation page, extracting the component type of each page component, screening the pending component set, and obtaining input field information of each pending component in the pending component set; based on obtaining corresponding inspection parameters from the monitoring operation information to match the inspection parameters with the input fields, the pending component that has been successfully matched is determined as the inspection parameter input component.

[0009] In another embodiment, the inspection parameter value is extracted from the monitoring operation information to update the target position with the inspection parameter, including: extracting the inspection type from the monitoring operation information, querying the inspection parameter set corresponding to the inspection type, and identifying the parameter value of each inspection parameter in the inspection parameter set; based on the association between the inspection parameter and the target position, updating the target position with the inspection parameter.

[0010] In another embodiment, calling the first large model to select the corresponding operation page includes: calling the first large model, extracting each intention keyword from the monitoring operation information, clustering the intention keywords with each preset operation type, determining the number of intention keywords corresponding to each preset operation type, determining the target operation type according to the number, and selecting the operation page according to the target operation type.

[0011] To achieve the above objective, according to another aspect of an embodiment of the present invention, a data monitoring device is provided.

[0012] A data monitoring device according to an embodiment of the present invention includes: a selection unit, which is used to respond to a data monitoring instruction, obtain corresponding monitoring operation information, and call a first large model to select a corresponding operation page; an update unit, which is used to obtain code data of the operation page, call a second large model, identify a target position in the code data, extract an inspection parameter value from the monitoring operation information to update the inspection parameter to the target position, and trigger an inspection instruction based on the updated code data; a generation unit, which is used to receive an inspection result corresponding to the inspection instruction, call a third large model, obtain a monitoring indicator, identify corresponding abnormal data from the inspection result, and generate a monitoring status corresponding to the monitoring indicator; and a sending unit, which is used to send the abnormal data and the monitoring status.

[0013] In one embodiment, the update unit is specifically used to: extract the inspection type from the monitoring operation information, query the inspection parameter sequence corresponding to the inspection type, extract the parameter value of each inspection parameter in the inspection parameter sequence, and store each parameter in a preset queue based on the inspection parameter sequence; update each parameter value to a target position corresponding to the value according to the storage order of each parameter value in the preset queue.

[0014] In another embodiment, the update unit is specifically used to: call the second large model, identify the page component set of the operation page, screen the inspection parameter input component to determine the corresponding code data, and determine the position of the parameter to be input in the code data as the target position.

[0015] In another embodiment, the update unit is specifically used to: identify the page layout of the operation page, extract the component type of each page component, filter the set of pending components, and obtain the input field information of each pending component in the set of pending components; based on obtaining the corresponding inspection parameters from the monitoring operation information to match the inspection parameters with the input fields, the successfully matched pending component is determined as the inspection parameter input component.

[0016] In another embodiment, the updating unit is specifically used to: extract the inspection type from the monitoring operation information, query the inspection parameter set corresponding to the inspection type, and identify the parameter value of each inspection parameter in the inspection parameter set; based on the association between the inspection parameter and the target position, update the target position with the inspection parameter.

[0017] In another embodiment, the selection unit is specifically used to: call the first large model, extract each intention keyword from the monitoring operation information, cluster the intention keywords with each preset operation type, determine the number of intention keywords corresponding to each preset operation type, determine the target operation type according to the number, and select the operation page according to the target operation type.

[0018] To achieve the above objective, according to another aspect of an embodiment of the present invention, an electronic device is provided.

[0019] An electronic device according to an embodiment of the present invention includes: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the data monitoring method provided by the embodiment of the present invention.

[0020] To achieve the above objective, according to another aspect of an embodiment of the present invention, a computer readable medium is provided.

[0021] A computer-readable medium according to an embodiment of the present invention stores a computer program, and when the program is executed by a processor, the data monitoring method provided by the embodiment of the present invention is implemented.

[0022] To achieve the above objective, according to another aspect of an embodiment of the present invention, a computer program product is provided.

[0023] A computer program product according to an embodiment of the present invention includes a computer program, and when the program is executed by a processor, the data monitoring method provided by the embodiment of the present invention is implemented.

[0024] An embodiment of the above invention has the following advantages or beneficial effects: In the embodiment of the present invention, in response to the data monitoring instruction, the monitoring operation information can be input into the first large model, and the operation page of the data operation can be selected through the first large model; the second large model is called to identify the target position where the operation conditions need to be input from the code data of the operation page, and the inspection parameter value extracted from the monitoring operation information is input into the device target position to obtain the page code that can be operated, so as to trigger the inspection instruction based on this code data; after receiving the inspection result corresponding to the inspection instruction, the third large model can be called to identify the corresponding abnormal data from the inspection result according to the monitoring index, and generate the monitoring state corresponding to the monitoring index, and then send the abnormal data and the monitoring state. In the embodiment of the present invention, each large model is pre-trained, and when data monitoring is required, the operation page of the monitoring data is selected through each large model according to the input monitoring operation information, and the inspection parameter is input into the code of the operation page to perform data inspection, and then the inspection result can be obtained, and the result of data monitoring is obtained by analyzing the inspection result. In this way, automatic monitoring of data is realized through the large model, and there is no need to write the data monitoring code of each page. Even if the monitoring platform changes, there is no need to adjust the program, which improves the efficiency of data monitoring.

[0025] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention. Figure 1 is a schematic diagram of a main process of a data monitoring method according to an embodiment of the present invention; Figure 2 is a schematic diagram of another main process of the data monitoring method according to an embodiment of the present invention; Figure 3 is a schematic diagram of another main process of the data monitoring method according to an embodiment of the present invention; Figure 4is a schematic diagram of main units of a data monitoring device according to an embodiment of the present invention; Figure 5 is an exemplary system architecture diagram to which embodiments of the present invention may be applied; Figure 6 It is a schematic diagram of the structure of a computer system suitable for implementing the embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0028] It should be pointed out that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict. The acquisition, transmission, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. In the embodiments of this application, some existing solutions in the industry such as certain software, components, and models may be mentioned, which should be considered as exemplary. Their purpose is only to illustrate the feasibility of the implementation of the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0029] An embodiment of the present invention provides a data monitoring system, which can be used in scenarios of data monitoring, and specifically can be used in scenarios of data construction and abnormality analysis.

[0030] The embodiment of the present invention provides a data monitoring method, which can be executed by a data monitoring system. Figure 1 As shown, the method includes the following steps.

[0031] S101: In response to a data monitoring instruction, corresponding monitoring operation information is obtained, and a first large model is called to select a corresponding operation page.

[0032] The data monitoring instruction can be triggered automatically or sent by an external system. For example, a periodically triggered data monitoring instruction can be set. The data monitoring instruction can include monitoring operation information, which can include an operation description and operation conditions of the monitoring operation. The operation description indicates the intention of this monitoring, such as data query, that is, the query is the intention of this monitoring operation, and the operation condition user determines the data corresponding to this monitoring, such as querying the data of a certain day, and the time information of a certain day is the operation condition.

[0033] In an embodiment of the present invention, different operation pages can be set for different monitoring operations, so the first large model can be trained in advance in this step. After completing the training of the first large model, the corresponding monitoring operation information can be obtained in this step and then input into the first large model to select the corresponding operation page through the large model.

[0034] Specifically, selecting the corresponding operation page in this step can be executed as follows: calling the first large model, extracting each intent keyword from the monitoring operation information, clustering the intent keywords with each preset operation type, determining the number of intent keywords corresponding to each preset operation type, determining the target operation type based on the number, and selecting the operation page based on the target operation type.

[0035] The monitoring operation information includes the operation intention, so each intention keyword can be extracted from the monitoring operation information, and the extraction method can be unlimited. In the embodiment of the present invention, each operation page can be distinguished according to the operation type, so a correspondence can be established between each operation page and the operation type, and each operation type can be represented by a corresponding text, so the extracted intention keywords can be clustered with each preset operation type, that is, the preset operation type corresponding to each intention keyword is determined, so that the intention keyword corresponding to each preset operation type can be determined, and the preset operation type with the most corresponding intention keywords is determined as the preset operation type corresponding to this monitoring operation, and then the corresponding operation page can be selected.

[0036] It should be noted that, in the embodiment of the present invention, the selection of the corresponding operation page can also be directly achieved through the first large model, that is, by training the first large model, the corresponding operation page can be directly determined after the monitoring operation information is input into the first large model.

[0037] Before this step, operation pages of different preset operation types can be collected. Each operation page requires the input of one or more parameters. The first large model can identify the operation page that matches the input monitoring operation information based on the natural language inspection text. At the same time, model training can be completed through manual fine-tuning during the training process.

[0038] S102: Obtain the code data of the operation page, call the second largest model, identify the target position in the code data, extract the inspection parameter value from the monitoring operation information to update the inspection parameter to the target position, and trigger the inspection instruction based on the updated code data.

[0039] Among them, the code data of the operation page represents the source code for implementing the operation page. The second largest model is pre-trained, and through the second largest model, the target position in the code data can be identified. The target position represents the position where the operation conditions are input in the code data of the operation page. After the operation conditions are input into the code data, the operation of the data can be realized by running the code data. The inspection parameter value represents the parameter value corresponding to the preset inspection parameter, which represents the operation condition of this data monitoring. Therefore, after updating the inspection parameter to the target position, the code data with the operation condition added can be obtained, and then the inspection instruction can be triggered by triggering the running of this code data.

[0040] It should be noted that the operating conditions in the embodiment of the present invention can be implemented through multiple inspection parameters. For example, the operating condition is to query the order data from point 1 to point 2, and the inspection parameters may include point 1, point 2 and order data, so the target locations identified in this step may include multiple ones.

[0041] Specifically, the method for determining the target position can be executed as follows: calling the second largest model, identifying the page component set of the operation page, screening the inspection parameter input component to determine the corresponding code data, and determining the position of the parameter to be input in the code data as the target position.

[0042] In an embodiment of the present invention, the operation page can be implemented by page components, so the page component set of the operation page can be identified in this step, and the components used to input inspection parameters can be screened out from each page component, and then the code data corresponding to the component can be determined to determine the locations where the parameters need to be input from the code data, that is, the locations of the parameters to be input, and these locations can be determined as target locations.

[0043] In one embodiment, the method for filtering the inspection parameter input components in this step can be: identifying the page layout of the operation page, extracting the component type of each page component, filtering the pending component set, and obtaining the input field information of each pending component in the pending component set; based on obtaining the corresponding inspection parameters from the monitoring operation information, the inspection parameters and the input fields are matched, and the successfully matched pending components are determined as the inspection parameter input components.

[0044] The page layout may include the location information of each page component, so after determining the page layout, the included page components can be determined therefrom, and the component type of each page component can be extracted. Since the parameters for inputting inspection parameters need to be implemented by components that can input parameters, the pending component set can be screened according to the component type in this step. The pending component set represents the set of page components that need to input parameters, and then the inspection parameter input component can be determined from the pending component set. In this step, the input parameters of each pending component in the pending component set can be obtained to match it with the inspection parameters. A successful match indicates that this pending component is the component for inputting inspection parameters, that is, the inspection parameter input component.

[0045] It should be noted that, in the embodiments of the present invention, the inspection parameters can be obtained from the monitoring operation information, and the acquisition method is not limited, for example, it can be achieved through a preset recognition model.

[0046] In another embodiment, updating the inspection parameters to the target position in this step can be specifically performed as follows: extracting the inspection type from the monitoring operation information, querying the inspection parameter sequence corresponding to the inspection type, extracting the parameter value of each inspection parameter in the inspection parameter sequence, and storing each parameter in a preset queue based on the inspection parameter sequence; and updating the target position corresponding to each parameter value according to the storage order of each parameter value in the preset queue.

[0047] Since the number of inspection parameters and target positions is the same, the parameter values ​​can be updated in the value code data in the order of the corresponding target positions. Specifically, the inspection parameters can be pre-generated into an inspection parameter sequence in the order of the corresponding target positions, so that the parameter values ​​of each inspection parameter can be stored in the preset queue according to the arrangement order of the inspection parameters in the inspection parameter sequence, and then the target position corresponding to each parameter value can be updated according to the storage order of each parameter value in the preset queue. The inspection parameter sequence can be obtained by splicing each inspection parameter identifier in order.

[0048] In another embodiment, in an embodiment of the present invention, a corresponding identifier can be set at the target location to establish an association relationship with the inspection parameter through the identifier. Therefore, after obtaining the parameter value of the inspection parameter, the parameter value can be updated to the code data according to the association relationship. Therefore, it can be specifically known that the execution is: extracting the inspection type from the monitoring operation information, querying the inspection parameter set corresponding to the inspection type, identifying the parameter value of each inspection parameter in the inspection parameter set; based on the association relationship between the inspection parameter and the target location, updating the inspection parameter to the target location.

[0049] In another embodiment, the second large model can be trained in the embodiment of the present invention to obtain updated code data after the code data and inspection parameter values ​​of the page operation are input into the second large model. When the second large model is trained, a large number of operation page samples can be collected, including but not limited to different types of IT systems, diversified monitoring indicators and various query condition combinations. These samples are used to train and fine-tune the large model, so that the model learns how to recognize the structure of the operation page and the input of the inspection parameters, so as to implement the operation of this step after the training is completed.

[0050] S103: Receive the inspection result corresponding to the inspection instruction, call the third model, obtain the monitoring index, identify the corresponding abnormal data from the inspection result, and generate the monitoring status corresponding to the monitoring index.

[0051] Among them, the inspection result means the data obtained after running the operation page after inputting the parameter value, that is, the data to be monitored. After obtaining the inspection result, it can be analyzed and processed through the trained third model to identify the abnormal data therein, and the monitoring status corresponding to the monitoring indicator can also be generated. The monitoring status can include a normal state and an abnormal state. Under normal circumstances, if the corresponding abnormal data is identified for the monitoring indicator, the corresponding monitoring state can be determined to be an abnormal state; if the corresponding abnormal data is not identified for the monitoring indicator, the corresponding monitoring state can be determined to be a normal state.

[0052] In an embodiment of the present invention, abnormal data identification rules for each inspection indicator can be pre-set to achieve the identification of abnormal data. For example, it can include extracting key information from charts, logs or indicator lists, such as system load, response time, error rate, etc., to identify abnormal data through the rules.

[0053] S104: Send abnormal data and monitoring status.

[0054] After obtaining the abnormal data and monitoring status of the inspection indicators, a corresponding report can be generated and sent to the prompt end. Specifically, it can be sent to the operation and maintenance team through IM tools or emails, so that relevant personnel can obtain the results of the monitoring operation and related warning information in a timely manner.

[0055] In an embodiment of the present invention, each major model is pre-trained. When data monitoring is needed, the operation page of the monitoring data is selected through each major model according to the input monitoring operation information, and the data inspection is performed after the inspection parameters are input into the code of the operation page, so that the inspection result can be obtained, and the data monitoring result is obtained by analyzing the inspection result. In this way, automatic monitoring of data can be achieved through the large model, and there is no need to write data monitoring code. Even if the monitoring platform changes, there is no need to adjust the program, thereby improving the efficiency of data monitoring.

[0056] Combine the following Figure 1 The embodiment shown in the figure specifically describes the method for data monitoring in the embodiment of the present invention. Figure 2 As shown, the method includes the following steps.

[0057] S201: In response to a data monitoring instruction, corresponding monitoring operation information is obtained, and the first large model is called to select a corresponding operation page.

[0058] S202: calling the second largest model, identifying the page component set of the operation page, screening the inspection parameter input component to determine the corresponding code data, and determining the position of the parameter to be input in the code data as the target position.

[0059] S203: Obtain code data of the operation page, extract the inspection type from the monitoring operation information, query the inspection parameter sequence corresponding to the inspection type, extract the parameter value of each inspection parameter in the inspection parameter sequence, and store each parameter in a preset queue based on the inspection parameter sequence.

[0060] S204: updating the target position corresponding to each parameter value according to the storage order of each parameter value in the preset queue.

[0061] S205: Receive the inspection result corresponding to the inspection instruction, call the third model, obtain the monitoring index, identify the corresponding abnormal data from the inspection result, and generate the monitoring status corresponding to the monitoring index.

[0062] S206: Send abnormal data and monitoring status.

[0063] It should be noted that the data processing principle and Figure 1 The corresponding data processing principles in the illustrated embodiments are the same and will not be described in detail here.

[0064] Combine the following Figure 1 The embodiment shown in the figure specifically describes the method for data monitoring in the embodiment of the present invention. Figure 3 As shown, the method includes the following steps.

[0065] S301: In response to a data monitoring instruction, obtain corresponding monitoring operation information.

[0066] S302: Call the first large model, extract each intention keyword from the monitoring operation information, cluster the intention keywords with each preset operation type, and determine the number of intention keywords corresponding to each preset operation type.

[0067] S303: Determine the target operation type according to the quantity, and select an operation page according to the target operation type.

[0068] S304: Obtain the code data of the operation page, call the second largest model, identify the target position in the code data, extract the inspection type from the monitoring operation information, query the inspection parameter set corresponding to the inspection type, and identify the parameter value of each inspection parameter in the inspection parameter set.

[0069] S305: Based on the association between the inspection parameters and the target position, update the target position with the inspection parameters.

[0070] S306: Receive the inspection result corresponding to the inspection instruction, call the third model, obtain the monitoring index, identify the corresponding abnormal data from the inspection result, and generate the monitoring status corresponding to the monitoring index.

[0071] S307: Send abnormal data and monitoring status.

[0072] It should be noted that the data processing principle and Figure 1 The corresponding data processing principles in the illustrated embodiments are the same and will not be described in detail here.

[0073] In order to solve the problems existing in the prior art, an embodiment of the present invention provides a data monitoring device 400, such as Figure 4 As shown, the device 400 includes: a selection unit 401, which is used to respond to a data monitoring instruction, obtain corresponding monitoring operation information, and call the first large model to select a corresponding operation page; an update unit 402, which is used to obtain code data of the operation page, call the second large model, identify the target position in the code data, extract the inspection parameter value from the monitoring operation information to update the inspection parameter to the target position, and trigger the inspection instruction based on the updated code data; a generation unit 403, which is used to receive the inspection result corresponding to the inspection instruction, call the third large model, obtain the monitoring indicator, identify the corresponding abnormal data from the inspection result, and generate the monitoring status corresponding to the monitoring indicator; a sending unit 404, which is used to send the abnormal data and the monitoring status.

[0074] It should be understood that the manner of implementing the embodiments of the present invention is different from the Figure 1 The method of the illustrated embodiment is the same and will not be repeated here.

[0075] In one embodiment, the update unit 402 is specifically used to: extract the inspection type from the monitoring operation information, query the inspection parameter sequence corresponding to the inspection type, extract the parameter value of each inspection parameter in the inspection parameter sequence, and store each parameter in a preset queue based on the inspection parameter sequence; update each parameter value to a target position corresponding to the value according to the storage order of each parameter value in the preset queue.

[0076] In another embodiment, the update unit 402 is specifically used to: call the second large model, identify the page component set of the operation page, screen the inspection parameter input component to determine the corresponding code data, and determine the position of the parameter to be input in the code data as the target position.

[0077] In another embodiment, the update unit 402 is specifically used to: identify the page layout of the operation page, extract the component type of each page component, filter the set of pending components, and obtain the input field information of each pending component in the set of pending components; based on obtaining the corresponding inspection parameters from the monitoring operation information to match the inspection parameters with the input fields, the successfully matched pending component is determined as the inspection parameter input component.

[0078] In another embodiment, the update unit 402 is specifically used to: extract the inspection type from the monitoring operation information, query the inspection parameter set corresponding to the inspection type, and identify the parameter value of each inspection parameter in the inspection parameter set; based on the association between the inspection parameter and the target position, update the target position with the inspection parameter.

[0079] In another embodiment, the selection unit 401 is specifically used to: call the first large model, extract each intention keyword from the monitoring operation information, cluster the intention keywords with each preset operation type, determine the number of intention keywords corresponding to each preset operation type, determine the target operation type according to the number, and select the operation page according to the target operation type.

[0080] It should be understood that the manner of implementing the embodiments of the present invention is different from the Figure 1 , 2 , and 3 are the same as the embodiments shown in FIG. 3 and will not be described again here.

[0081] In an embodiment of the present invention, each major model is pre-trained. When data monitoring is needed, the operation page of the monitoring data is selected through each major model according to the input monitoring operation information, and the data inspection is performed after the inspection parameters are input into the code of the operation page, so that the inspection result can be obtained, and the data monitoring result is obtained by analyzing the inspection result. In this way, automatic monitoring of data can be achieved through the large model, and there is no need to write data monitoring code. Even if the monitoring platform changes, there is no need to adjust the program, thereby improving the efficiency of data monitoring.

[0082] According to an embodiment of the present invention, the embodiment of the present invention further provides an electronic device and a readable storage medium.

[0083] The electronic device of an embodiment of the present invention includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the data monitoring method provided by the embodiment of the present invention.

[0084] Figure 5 An exemplary system architecture 500 is shown to which the method for data monitoring or the apparatus for data monitoring according to the embodiment of the present invention may be applied.

[0085] like Figure 5 As shown, system architecture 500 may include terminal devices 501, 502, 503, a network 504 and a server 505. Network 504 is used to provide a medium for communication links between terminal devices 501, 502, 503 and server 505. Network 504 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0086] The user can use the terminal devices 501, 502, 503 to interact with the server 505 through the network 504 to receive or send messages, etc. Various client applications can be installed on the terminal devices 501, 502, 503.

[0087] The terminal devices 501 , 502 , and 503 may be, but are not limited to, smart phones, tablet computers, laptop computers, and desktop computers, etc.

[0088] The server 505 may be a server that provides various services. The server may analyze and process the received data such as the product information query request, and feed back the processing result (such as product information - just an example) to the terminal device.

[0089] It should be noted that the data comparison method provided in the embodiment of the present invention is generally executed by the server 505 , and accordingly, the data comparison device is generally set in the server 505 .

[0090] It should be understood that Figure 5 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0091] Reference below Figure 6 , which shows a schematic diagram of the structure of a computer system 600 suitable for implementing an embodiment of the present invention. Figure 6 The computer system shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0092] like Figure 6As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0093] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

[0094] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the system of the present invention are executed.

[0095] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0096] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a unit, a program segment, or a part of a code, and the above-mentioned unit, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0097] The units involved in the embodiments of the present invention may be implemented by software or hardware. The units described may also be set in a processor, for example, it may be described as: a processor includes a selection unit, an update unit, a generation unit, and a sending unit. The names of these units do not constitute limitations on the units themselves in some cases, for example, the selection unit may also be described as a "unit for selecting functions".

[0098] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device executes the data monitoring method provided by the present invention.

[0099] As another aspect, the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the data monitoring method provided in an embodiment of the present invention.

[0100] The above specific implementations do not constitute a limitation on the protection scope of the present invention. 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 modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data monitoring method, characterized in that: include: In response to the data monitoring instruction, corresponding monitoring operation information is obtained, and the first large model is called to select a corresponding operation page; Obtaining code data of the operation page, calling the second largest model, identifying a target position in the code data, extracting an inspection parameter value from the monitoring operation information to update the inspection parameter to the target position, and triggering an inspection instruction based on the updated code data; Receive the inspection result corresponding to the inspection instruction, call the third model, obtain the monitoring index, identify the corresponding abnormal data from the inspection result, and generate the monitoring status corresponding to the monitoring index; The abnormal data and the monitoring status are sent.

2. The method according to claim 1, characterized in that Extracting inspection parameter values ​​from the monitoring operation information to update the target position with the inspection parameters includes: Extracting the inspection type from the monitoring operation information, querying the inspection parameter sequence corresponding to the inspection type, extracting the parameter value of each inspection parameter in the inspection parameter sequence, and storing each of the parameters in a preset queue based on the inspection parameter sequence; According to the storage order of each parameter value in the preset queue, each parameter value is updated to a target position corresponding to the value.

3. The method according to claim 1, characterized in that The calling of the second largest model to identify the target position in the code data includes: The second largest model is called to identify the page component set of the operation page, screen the inspection parameter input component to determine the corresponding code data, and determine the position of the parameter to be input in the code data as the target position.

4. The method according to claim 3, characterized in that Identify the page component set of the operation page, and filter the inspection parameter input component, including: Identify the page layout of the operation page, extract the component type of each page component, filter the set of pending components, and obtain input field information of each pending component in the set of pending components; Based on obtaining corresponding inspection parameters from the monitoring operation information, the inspection parameters are matched with the input fields, and the undetermined component that is successfully matched is determined as the inspection parameter input component.

5. The method according to claim 1, characterized in that Extracting inspection parameter values ​​from the monitoring operation information to update the target position with the inspection parameters includes: Extracting an inspection type from the monitoring operation information, querying an inspection parameter set corresponding to the inspection type, and identifying a parameter value of each inspection parameter in the inspection parameter set; Based on the association between the inspection parameter and the target position, the target position is updated with the inspection parameter.

6. The method according to claim 1, characterized in that The calling of the first large model to select a corresponding operation page includes: Call the first large model, extract each intent keyword from the monitoring operation information, cluster the intent keywords with each preset operation type, determine the number of intent keywords corresponding to each preset operation type, determine the target operation type according to the number, and select the operation page according to the target operation type.

7. A data monitoring device, characterized in that: include: A selection unit, for obtaining corresponding monitoring operation information in response to a data monitoring instruction, and calling the first large model to select a corresponding operation page; An updating unit, configured to obtain code data of the operation page, call the second largest model, identify a target position in the code data, extract an inspection parameter value from the monitoring operation information, update the inspection parameter to the target position, and trigger an inspection instruction based on the updated code data; A generating unit, configured to receive an inspection result corresponding to the inspection instruction, call the third model, obtain a monitoring indicator, identify corresponding abnormal data from the inspection result, and generate a monitoring state corresponding to the monitoring indicator; A sending unit is used to send the abnormal data and the monitoring status.

8. The device according to claim 7, characterized in that The updating unit is specifically used for: Extracting the inspection type from the monitoring operation information, querying the inspection parameter sequence corresponding to the inspection type, extracting the parameter value of each inspection parameter in the inspection parameter sequence, and storing each of the parameters in a preset queue based on the inspection parameter sequence; According to the storage order of each parameter value in the preset queue, each parameter value is updated to a target position corresponding to the value.

9. The device according to claim 7, characterized in that The updating unit is specifically used for: The second largest model is called to identify the page component set of the operation page, screen the inspection parameter input component to determine the corresponding code data, and determine the position of the parameter to be input in the code data as the target position.

10. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

11. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

12. A computer program product, comprising a computer program, characterized in that When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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