Intelligent operation and maintenance method, device and equipment based on expert knowledge base and storage medium

Abstract

The embodiment of the invention provides an intelligent operation and maintenance method and device, equipment and a storage medium. In some embodiments of the invention, the method comprises the following steps: obtaining application fault alarm data; the application fault alarm data is matched with expert databases in an expert knowledge database, a target expert database is obtained, each expert database corresponds to at least one scene, and each scene corresponds to at least one script; according to a target scene associated with the target expert database and a target script associated with the target scene, selecting a target execution script from the target script; executing the target execution script to perform operation and maintenance operation on the application fault to obtain an execution result; according to the application fault operation and maintenance method and device, fault positioning is rapidly carried out on the basis of searching the similar fault cases in the expert database, checking the script execution function, searching the similar fault cases in the expert database and checking the script execution function, the intelligent degree of application fault operation and maintenance is improved, and the application fault operation and maintenance efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of operation and maintenance technology, and in particular to an intelligent operation and maintenance method, device, equipment and storage medium. Background Art

[0002] The core advantage of the current knowledge base application in the field of operation and maintenance lies in the construction of a multifunctional document management system as a centralized storage and sharing hub for operation and maintenance wisdom. Existing technologies focus on refined document classification, intelligent search tools, and secure permission control mechanisms, so that the knowledge base itself has perfect document management capabilities, ensuring that every operation and maintenance personnel can quickly access accurate and up-to-date knowledge resources, thereby showing a strong support role in solving complex operation and maintenance problems, optimizing system performance, and ensuring system security.

[0003] The current application of knowledge bases in the field of operation and maintenance is mainly based on the knowledge base's ability to provide various types of document management capabilities, making it a platform for centralized storage and sharing of operation and maintenance knowledge. However, this platform is still insufficient in directly supporting problem troubleshooting, script execution, and event recording process automation.

[0004] Currently, the intelligence level of application fault operation and maintenance is low and the efficiency is low. Summary of the invention

[0005] The present disclosure provides an intelligent operation and maintenance method, apparatus, device and storage medium to at least solve the problem of low intelligence and low efficiency of existing application fault operation and maintenance.

[0006] The technical solution of the present disclosure is as follows:

[0007] The present disclosure provides an intelligent operation and maintenance method, including:

[0008] Obtain application failure alarm data;

[0009] Match the alarm label with the alarm label that can be identified by the expert library to obtain the target expert library, wherein each of the expert libraries corresponds to at least one scenario, and each of the scenarios corresponds to at least one script, wherein the alarm label is a label generated by labeling the application fault alarm data;

[0010] According to the target scenario associated with the target expert library and the target script associated with the target scenario, a target execution script is selected from the target scripts;

[0011] Execute the target execution script to perform operation and maintenance operations on the application failure and obtain an execution result.

[0012] Optionally, after obtaining the application failure alarm data, the method further includes:

[0013] Displaying the application failure alarm data;

[0014] In response to the alarm level selection operation, an alarm level corresponding to the application failure alarm data is determined.

[0015] Optionally, matching the warning label with the warning label that can be identified by the expert database to obtain the target expert database includes:

[0016] Matching the alarm label with an expert library label in an expert library to obtain a matching weight and a matching type, wherein the expert library label is an alarm label that can be recognized by the expert library;

[0017] The target expert database is selected from the expert database according to the matching weight and the matching type.

[0018] Optionally, the matching type includes: perfect matching, inclusive matching and non-inclusive matching, the perfect matching has a higher priority than inclusive matching, and the inclusive matching has a higher priority than non-inclusive matching; the selecting the target expert database from the expert database according to the matching weight and the matching type includes:

[0019] The target expert database is selected from the expert database according to the matching weight, the matching type and the priority of the matching type.

[0020] Optionally, selecting a target execution script from the target scripts according to the target scenario associated with the target expert library and the target script associated with the target scenario includes:

[0021] In response to a scene display operation, displaying a target scene associated with the target expert library;

[0022] In response to the script display operation, display the target script associated with the target scene;

[0023] In response to the script selection operation, a target execution script is selected from the target scripts.

[0024] Optionally, the method further comprises:

[0025] Query script execution records based on the alarm data dimension and expert library dimension.

[0026] Optionally, the scenario includes at least one of the following: application error, application performance, application OOM and application suspended animation.

[0027] The present disclosure also provides an intelligent operation and maintenance device based on an expert knowledge base, including:

[0028] An acquisition module is used to obtain application fault alarm data;

[0029] A matching module, used for matching the alarm label with the alarm label that can be identified by the expert library to obtain a target expert library, wherein each of the expert libraries corresponds to at least one scenario, and each of the scenarios corresponds to at least one script, wherein the alarm label is a label generated by labeling the application fault alarm data;

[0030] A selection module, configured to select a target execution script from the target scripts according to a target scenario associated with the target expert library and a target script associated with the target scenario;

[0031] The execution module is used to execute the target execution script to perform operation and maintenance operations on the application failure and obtain an execution result.

[0032] The present disclosure also provides an electronic device, including:

[0033] processor;

[0034] a memory for storing instructions executable by the processor;

[0035] The processor is configured to execute the instructions to implement each step in the above method.

[0036] The embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, each step in the above method is implemented.

[0037] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0038] In some embodiments of the present disclosure, application fault alarm data is obtained; the alarm label is matched with the alarm label that can be recognized by the expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script; according to the target scenario associated with the target expert library and the target script associated with the target scenario, a target execution script is selected from the target script; the target execution script is executed to perform operation and maintenance operations on the application fault to obtain an execution result; the present disclosure is based on retrieving similar fault cases in the expert library and troubleshooting the script execution function, retrieving similar fault cases in the expert library and troubleshooting the script execution function, quickly locating the fault, improving the intelligence level of application fault operation and maintenance, and improving the efficiency of application fault operation and maintenance.

[0039] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0041] Figure 1 A flowchart of an intelligent operation and maintenance method based on an expert knowledge base provided for an exemplary embodiment of the present disclosure;

[0042] Figure 2 A system schematic diagram of an intelligent operation and maintenance system based on an expert knowledge base provided for an exemplary embodiment of the present disclosure;

[0043] Figure 3 A schematic diagram of the structure of an intelligent operation and maintenance device based on an expert knowledge base provided for an exemplary embodiment of the present disclosure;

[0044] Figure 4 A schematic structural diagram of an electronic device provided by an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0045] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0046] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure.

[0047] It should be noted that the user information involved in this disclosure includes but is not limited to: user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure comply with the relevant laws and regulations and do not violate public order and good morals.

[0048] In response to the above technical problems, in some embodiments of the present disclosure, application fault alarm data is obtained; the alarm label is matched with the alarm label that can be recognized by the expert library to obtain a target expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script; according to the target scenario associated with the target expert library and the target script associated with the target scenario, a target execution script is selected from the target script; the target execution script is executed to perform operation and maintenance operations on the application fault to obtain an execution result; the present disclosure is based on retrieving similar fault cases in the expert library and troubleshooting the script execution function, retrieving similar fault cases in the expert library and troubleshooting the script execution function, quickly locating the fault, improving the intelligence level of application fault operation and maintenance, and improving the efficiency of application fault operation and maintenance.

[0049] The technical solutions provided by various embodiments of the present disclosure are described in detail below in conjunction with the accompanying drawings.

[0050] Figure 1 The following is a flow chart of an intelligent operation and maintenance method based on an expert knowledge base provided by an exemplary embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0051] S101: Obtain application failure alarm data;

[0052] S102: Match the alarm label with the alarm label that can be identified by the expert library to obtain a target expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script, wherein the alarm label is a label generated by labeling the application fault alarm data;

[0053] S103: selecting a target execution script from the target scripts according to the target scenario associated with the target expert database and the target script associated with the target scenario;

[0054] S104: Execute the target execution script to perform operation and maintenance operations on the application failure and obtain an execution result.

[0055] In this embodiment, the execution subject of the above method may be a terminal device or a server.

[0056] Among them, the terminal device includes but is not limited to a mobile station (MS), a mobile terminal, a mobile phone, a handset and a portable equipment, etc. The terminal device can communicate with one or more core networks via a radio access network (RAN). For example, the terminal device can be a mobile phone (or a "cellular" phone), a computer with a wireless communication function, etc. The terminal device can also be a computer with a wireless transceiver function, a virtual reality (VR) terminal device, an AR terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc., and the operating system installed on the terminal device includes but is not limited to: IOS, Android, windows, linux, Mac OS and other operating systems. In different networks, the terminal may be called different names, such as user equipment, mobile station, subscriber unit, station, cellular phone, personal digital assistant, wireless modem, wireless communication device, handheld device, laptop computer, cordless phone, wireless local loop station, television, etc. For the convenience of description, it is referred to as terminal equipment in this embodiment.

[0057] In this embodiment, the implementation form of the server is not limited. For example, the server can be a conventional server, a cloud server, a cloud host, a virtual center, or other server devices. The server mainly includes a processor, a hard disk, a memory, a system bus, etc., and a general computer architecture type.

[0058] In this embodiment, application fault alarm data is obtained; the alarm label is matched with the alarm label that can be recognized by the expert library to obtain a target expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script; according to the target scenario associated with the target expert library and the target script associated with the target scenario, a target execution script is selected from the target script; the target execution script is executed to perform operation and maintenance operations on the application fault to obtain an execution result; the present disclosure is based on retrieving similar fault cases in the expert library and troubleshooting the script execution function, retrieving similar fault cases in the expert library and troubleshooting the script execution function, quickly locating the fault, improving the intelligence level of application fault operation and maintenance, and improving the efficiency of application fault operation and maintenance.

[0059] Specifically, the present disclosure focuses on improving the speed and efficiency of operation and maintenance response, and aims to intelligently match system alarms, seamlessly connect the rich historical case library, established solutions and troubleshooting strategies in the expert knowledge base, and build an efficient and intelligent integrated operation and maintenance analysis ecosystem by integrating system alarm management, expert knowledge base wisdom and automated operation and maintenance tools. The present disclosure can quickly retrieve and analyze similar fault cases in the expert knowledge base, and automatically recommend relevant solutions and troubleshooting ideas. At the same time, the integrated troubleshooting script execution function enables operation and maintenance personnel to obtain professional guidance while triggering predefined scripts with one click to implement accurate root cause troubleshooting. This process not only greatly shortens the fault location time, but also realizes the automation of the entire chain from system alarm triggering to problem root cause analysis to solution execution, opening up all aspects of operation and maintenance work.

[0060] It should be noted that the expert knowledge database stores multiple expert libraries, each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script.

[0061] Figure 2 An expert library structure relationship is provided for an exemplary embodiment of the present disclosure. Figure 2 As shown in the figure, each expert library information consists of multiple scenarios, and each scenario is divided into multiple executable scripts. The scripts are independent of each other. The expert library is recommended according to the alarm label algorithm, and the corresponding scenario is determined according to the content and then the executable script is selected. The whole process is clear and helps operation and maintenance to quickly locate anomalies and troubleshoot faults after the alarm is generated.

[0062] In some embodiments of the present disclosure, the alarm analysis center monitors application fault information and generates application fault alarm data. The application fault alarm data is displayed; in response to the alarm level selection operation, the alarm level corresponding to the application fault alarm data is determined. For example, in response to the application fault alarm data opening operation, the application fault alarm data can be displayed on an electronic display screen; the user divides the application fault alarm data into five levels: notification, minor, general, severe, and emergency according to the degree of business impact; in response to the alarm level selection operation, the corresponding alarm level is added to the application fault alarm data, and the corresponding color is marked to classify the application fault alarm data.

[0063] It should be noted that application fault alarm data includes: alarm labels. Match types include: perfect match, inclusive match, and non-inclusive match. Perfect match has a higher priority than inclusive match, and inclusive match has a higher priority than non-inclusive match.

[0064] In some embodiments of the present disclosure, the alarm label is matched with the alarm label that the expert library can identify to obtain the target expert library. Among them, the expert library label is the alarm label that the expert library can identify. One achievable way is to match the alarm label with the expert library label in the expert library to obtain the matching weight and matching type; according to the matching weight and matching type, the target expert library is selected from the expert library. The present disclosure quickly selects the target expert library by matching the alarm label in the fault alarm data with the expert library label in the expert library. Among them, perfect match: when the alarm label is completely equal to the expert library label in the expert knowledge database (the number of labels is the same and the label content is consistent), it is a perfect match with a weight of 100%; inclusion match: when the alarm label is smaller than the expert library label, the weight is the alarm label accounting for the expert library label, weight = (the number of expert library labels hit / the total number of expert library labels) * 100%; non-inclusion match: when the alarm label is larger than the expert library label, the weight is the expert library label accounting for the alarm label, weight = (the number of expert library labels hit / the total number of expert library labels) * 100%.

[0065] For example, as shown by the warning labels 1001, 1002 and 1003, the corresponding labels pushed by the expert database are shown in Table 1 below.

[0066]

[0067] Table 1

[0068] In the above embodiment of the present disclosure, a target expert library is selected from the expert library according to the matching weight and the matching type. One achievable method is to select the target expert library from the expert library according to the matching weight, the matching type and the priority of the matching type. It should be noted that when the expert library is recommended to the alarm system according to the weight, if there is a situation where the weight is the same, the priority of the inclusion match is higher than that of the non-inclusion match.

[0069] It should be noted that common fault scenarios include: application error, application performance, application OOM, and application pseudo-death. Through long-term accumulation, the scenario system is gradually expanded. The ultimate goal is that each alarm will be matched with the corresponding scenario in the expert knowledge base, so as to obtain the alarm elimination solution. Each scenario consists of two parts of functions, which can be used to assist each other, or only one part can be used. One part of the function is a text summary. This function records the common coping methods for such scenarios in the form of text. For example, for application performance, follow the peripheral system troubleshooting, component troubleshooting, database troubleshooting, and network troubleshooting to step by step. The other part of the function is to associate and execute scripts. The response relationship between the scenario and the script is M:N. Multiple executable scripts can be associated and configured in the scenario. By adjusting the script execution order and binding and unbinding operations, the external output capability of this scenario can be improved. Among them, application OOM refers to an application requesting resources that exceed the available memory during execution, causing it to fail to run normally or crash. When an application encounters OOM, the system may throw an exception or error message, indicating that more memory cannot be allocated to the application.

[0070] It should be noted that scripts can be divided into two types according to their content: scripts without parameters and scripts with parameters. Scripts without parameters are based on the common operation and maintenance situations in the production environment, and frequently used shell scripts are pre-entered, such as top, free, iostat, telnet, jstack, jmap, and jstat. Scripts with parameters are a basic scenario for using scripts. The parameters plus the script content construct the logic to be executed to obtain the corresponding results.

[0071] In some embodiments of the present disclosure, a target execution script is selected from the target script according to the target scene associated with the target expert library and the target script associated with the target scene. One achievable method is to display the target scene associated with the target expert library in response to a scene display operation; display the target script associated with the target scene in response to a script display operation; and select the target execution script from the target script in response to a script selection operation. Among them, the scene and the script are displayed, and the user can select the target execution script according to the script execution record, etc.

[0072] In some disclosed embodiments, the present disclosure can perform record backtracking from multiple dimensions. One achievable method is to query script execution records based on the alarm data dimension and the expert library dimension.

[0073] In order to facilitate the operation and maintenance operators to screen scenarios, perform operations, and the operation and maintenance administrators to maintain the expert database data, the script execution records are divided into multiple dimension records. Statistics are made based on the alarm data dimension. This dimension facilitates the management and summary of existing scripts. By adjusting the script and scenario content, the coverage of the expert knowledge base is further expanded. Statistics based on the expert database dimension serve as a reference for the operation and maintenance operators when selecting scenarios and scripts.

[0074] In some embodiments of the present disclosure, in order to continuously expand the coverage of the expert database and improve the speed of abnormal closed loop, operation and maintenance personnel need to be divided into operators and administrators according to their roles. Operators collect alarm data, locate problems, and troubleshoot faults on a daily basis, while administrators regularly summarize and manage the background data of the expert knowledge base.

[0075] Figure 2 The following is a schematic diagram of an intelligent operation and maintenance system based on an expert knowledge base provided by an exemplary embodiment of the present disclosure. Figure 2 As shown in the figure, the intelligent operation and maintenance system includes an alarm platform, an expert knowledge database and a cloud platform. The alarm platform generates alarm data, performs alarm classification and marks alarm tags; matches alarm tags with expert library tags in the expert library, then selects scenarios and target execution scripts, and executes the target execution scripts. The cloud platform performs virtual machine execution and generates execution results; the expert knowledge database retains the results and notifies the alarm platform to close the alarm.

[0076] Figure 3 FIG. 1 is a schematic diagram of a structure of an intelligent operation and maintenance device 30 based on an expert knowledge base provided by an exemplary embodiment of the present disclosure. Figure 3 As shown, the intelligent operation and maintenance device 30 includes: an acquisition module 31, a matching module 32, a selection module 33 and an execution module 34.

[0077] Wherein, the acquisition module 31 is used to obtain application fault alarm data;

[0078] A matching module 32, used to match the alarm tag with the alarm tag that can be identified by the expert library to obtain a target expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script;

[0079] A selection module 33, configured to select a target execution script from the target scripts according to the target scenario associated with the target expert library and the target script associated with the target scenario, wherein the alarm label is a label generated by labeling the application fault alarm data;

[0080] The execution module 34 is used to execute the target execution script to perform operation and maintenance operations on the application failure and obtain the execution result.

[0081] Optionally, after acquiring the application fault alarm data, the acquisition module 31 may also be used to:

[0082] Display application failure alarm data;

[0083] In response to the alarm level selection operation, an alarm level corresponding to the application failure alarm data is determined.

[0084] Optionally, when the matching module 32 matches the warning label with the warning label that can be identified by the expert database to obtain the target expert database, it is used to:

[0085] Matching the alarm label with the expert library label in the expert library to obtain a matching weight and a matching type, wherein the expert library label is an alarm label that can be recognized by the expert library;

[0086] According to the matching weight and matching type, a target expert database is selected from the expert database.

[0087] Optionally, the matching types include: perfect matching, inclusive matching and non-inclusive matching, wherein the priority of perfect matching is higher than that of inclusive matching, and the priority of inclusive matching is higher than that of non-inclusive matching; when the selection module 33 selects the target expert library from the expert library according to the matching weight and the matching type, it is used to:

[0088] A target expert database is selected from the expert database according to the matching weight, the matching type and the priority of the matching type.

[0089] Optionally, when selecting a target execution script from the target scripts according to the target scenario associated with the target expert library and the target script associated with the target scenario, the selection module 33 is used to:

[0090] In response to the scene display operation, display the target scene associated with the target expert library;

[0091] In response to the script display operation, displaying a target script associated with the target scene;

[0092] In response to the script selection operation, a target execution script is selected from the target scripts.

[0093] Optionally, the execution module 34 may also be used to:

[0094] Query script execution records based on the alarm data dimension and expert library dimension.

[0095] Optionally, the scenario includes at least one of the following: application error, application performance, application OOM, and application suspended animation.

[0096] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0097] Figure 4FIG. 1 is a schematic diagram of a structure of an electronic device provided by an exemplary embodiment of the present disclosure. Figure 4 As shown, the electronic device includes: a memory 41 and a processor 42. In addition, the electronic device also includes a power supply component 43 and a communication component 44.

[0098] The memory 41 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application program or method operating on the electronic device.

[0099] The memory 41 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0100] The communication component 44 is used for data transmission with other devices.

[0101] The processor 42 can execute computer instructions stored in the memory 41 to: obtain application fault alarm data; match the alarm label with the alarm label that can be recognized by the expert library to obtain a target expert library, wherein each expert library corresponds to at least one scenario, and each scenario corresponds to at least one script; select a target execution script from the target script according to the target scenario associated with the target expert library and the target script associated with the target scenario; execute the target execution script to perform operation and maintenance operations on the application fault and obtain an execution result.

[0102] Optionally, after acquiring the application fault alarm data, the processor 42 may also be used to:

[0103] Display application failure alarm data;

[0104] In response to the alarm level selection operation, an alarm level corresponding to the application failure alarm data is determined.

[0105] Optionally, when the processor 42 matches the alarm tag with the alarm tag that can be identified by the expert database to obtain the target expert database, it is configured to:

[0106] Match the alarm label with the expert library label in the expert library to obtain the matching weight and matching type;

[0107] According to the matching weight and matching type, a target expert database is selected from the expert database.

[0108] Optionally, the matching type includes: perfect matching, inclusive matching and non-inclusive matching, the priority of perfect matching is higher than that of inclusive matching, and the priority of inclusive matching is higher than that of non-inclusive matching; when the processor 42 selects the target expert library from the expert library according to the matching weight and the matching type, it is used to:

[0109] A target expert database is selected from the expert database according to the matching weight, the matching type and the priority of the matching type.

[0110] Optionally, when the processor 42 selects a target execution script from the target scripts according to the target scenario associated with the target expert library and the target script associated with the target scenario, it is configured to:

[0111] In response to the scene display operation, display the target scene associated with the target expert library;

[0112] In response to the script display operation, displaying a target script associated with the target scene;

[0113] In response to the script selection operation, a target execution script is selected from the target scripts.

[0114] Optionally, the processor 42 may also be configured to:

[0115] Query script execution records based on the alarm data dimension and expert library dimension.

[0116] Optionally, the scenario includes at least one of the following: application error, application performance, application OOM, and application suspended animation.

[0117] Accordingly, the present disclosure also provides a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores the computer program and the computer program is executed by one or more processors, the one or more processors execute Figure 1 Each step in the method embodiment.

[0118] Accordingly, the present disclosure also provides a computer program product, the computer program product includes a computer program / instruction, the computer program / instruction is executed by a processor Figure 1 Each step in the method embodiment.

[0119] Above Figure 4The communication component in is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0120] Above Figure 4 The power supply component in the device provides power to various components of the device where the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device where the power supply component is located.

[0121] The electronic device also includes a display screen and an audio component.

[0122] The display screen includes a screen, and the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0123] The audio component may be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC), and when the device where the audio component is located is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal may be further stored in a memory or sent via a communication component. In some embodiments, the audio component also includes a speaker for outputting an audio signal.

[0124] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0125] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0126] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0129] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0130] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0131] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0132] The above are only specific embodiments of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent operation and maintenance method based on an expert knowledge base, characterized in that: include: Obtain application failure alarm data; Match the alarm label with the alarm label that can be identified by the expert library to obtain the target expert library, wherein each of the expert libraries corresponds to at least one scenario, and each of the scenarios corresponds to at least one script, wherein the alarm label is a label generated by labeling the application fault alarm data; According to the target scenario associated with the target expert library and the target script associated with the target scenario, a target execution script is selected from the target scripts; Execute the target execution script to perform operation and maintenance operations on the application failure and obtain an execution result.

2. The method according to claim 1, characterized in that After obtaining the application fault alarm data, the method further includes: Displaying the application failure alarm data; In response to the alarm level selection operation, an alarm level corresponding to the application failure alarm data is determined.

3. The method according to claim 1, characterized in that The step of matching the warning label with the warning label that can be identified by the expert database to obtain the target expert database includes: Matching the alarm label with an expert library label in an expert library to obtain a matching weight and a matching type, wherein the expert library label is an alarm label that can be recognized by the expert library; The target expert database is selected from the expert database according to the matching weight and the matching type.

4. The method according to claim 3, characterized in that The matching types include: perfect matching, inclusive matching and non-inclusive matching, wherein the priority of the perfect matching is higher than that of the inclusive matching, and the priority of the inclusive matching is higher than that of the non-inclusive matching; the selecting the target expert database from the expert database according to the matching weight and the matching type includes: The target expert database is selected from the expert database according to the matching weight, the matching type and the priority of the matching type.

5. The method according to claim 1, characterized in that The step of selecting a target execution script from the target scripts according to the target scenario associated with the target expert library and the target script associated with the target scenario includes: In response to a scene display operation, displaying a target scene associated with the target expert library; In response to the script display operation, display the target script associated with the target scene; In response to the script selection operation, a target execution script is selected from the target scripts.

6. The method according to claim 1, characterized in that The method further comprises: Query script execution records based on the alarm data dimension and expert library dimension.

7. The method according to claim 1, characterized in that The scenario includes at least one of the following: application error, application performance, application OOM and application suspended state.

8. An intelligent operation and maintenance device based on an expert knowledge base, characterized in that: include: An acquisition module is used to obtain application fault alarm data; A matching module, used for matching the application fault alarm data with an expert library in an expert knowledge database to obtain a target expert library, wherein each of the expert libraries corresponds to at least one scenario, and each of the scenarios corresponds to at least one script; A selection module, configured to select a target execution script from the target scripts according to a target scenario associated with the target expert library and a target script associated with the target scenario; The execution module is used to execute the target execution script to perform operation and maintenance operations on the application failure and obtain an execution result.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement each step in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, each step of the method according to any one of claims 1 to 7 is implemented.

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