Application program intelligent monitoring method, system and device, storage medium and product
Through the combination of intelligent application monitoring platform and AI model, the abnormal problems of application systems are automatically handled, which solves the problem of long exception handling time in the existing technology and improves the reliability and usability of the system.
Patent Information
- Application Number
- CN202411927817.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-25
- Publication Date
- 2025-04-18
AI Technical Summary
In the prior art, the application system exception handling time is long, resulting in poor reliability and availability of the application system.
Through the intelligent application monitoring platform, receive exception logs synchronized by the log platform, poll and scan to obtain exception information, and call AI models to provide solutions to achieve automated processing.
Quickly obtain exception information, automatically mobilize AI model acquisition solutions, save time in application system exception handling and improve the reliability and availability of application system.
Smart Images
Figure CN119847867A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of smart home technology, and in particular to an application program intelligent monitoring method, system, device, storage medium and product. Background Art
[0002] With the advancement of technology, the software industry is currently booming, and the stable operation of applications is the most basic guarantee. During the operation of applications, failures may occur, affecting the normal use of users. In order to improve the user experience, it is necessary to solve the failure problems in a timely manner to ensure the normal operation of the system.
[0003] In the existing technology, problems such as application failures or system anomalies need to be discovered manually and reported to the corresponding technical person in charge before they can be located and solved. For example, logs are collected through the monitoring platform, the information is classified, and saved in the database. When there is an abnormality in the system, the business user raises the problem, passes the problem description to the system person in charge, and then to the technical person in charge, who searches the logs according to the problem description information, locates the problem, and solves it.
[0004] In actual applications, the application scenarios of applications are diverse, and the problems that arise in applications are diverse. When a problem occurs, the technical person in charge cannot know all the answers, and solutions need to be tried. Therefore, the process is lengthy and highly dependent on the technical person in charge. Although the problem can also be solved, the processing process is too long and cannot be solved quickly, affecting system availability.
[0005] Therefore, in the prior art, the time required to process application system exceptions is relatively long, and the reliability and availability of the application system are relatively poor. Summary of the invention
[0006] The present application provides an application intelligent monitoring method, system, device, storage medium and product to solve the defects of the prior art that the application system exception handling time is long and the reliability and availability of the application system are poor. It can quickly obtain exception information and automatically mobilize AI models to obtain solutions, thereby saving the time of application system exception handling and improving the reliability and availability of the application system.
[0007] The present application provides an application intelligent monitoring method, which is applied to an application intelligent monitoring system. The application intelligent monitoring system includes a log platform, an intelligent application monitoring platform and an AI model; the method includes the following steps.
[0008] The intelligent application monitoring platform receives the abnormal logs of the application synchronized by the log platform.
[0009] The intelligent application monitoring platform performs polling scanning on the abnormal log to obtain abnormal information.
[0010] The intelligent application monitoring platform calls the application programming interface corresponding to the AI model and sends the exception information to the AI model, so that the AI model provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information.
[0011] The intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0012] The beneficial effects of the above steps are: being able to quickly obtain exception information, automatically mobilizing AI models to obtain solutions, saving time in application system exception handling, and improving the reliability and availability of the application system.
[0013] According to the application program intelligent monitoring method provided by the present application, the application program intelligent monitoring system includes multiple AI models; the intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the abnormal information to the AI model, so that the AI model provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information, specifically including: The intelligent application monitoring platform calls the application programming interface corresponding to each AI model respectively, and sends the exception information to each AI model, so that each AI model provides a solution corresponding to the exception problem corresponding to the exception information according to the exception information; The intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform, specifically including: The intelligent application monitoring platform receives the solution sent by each AI model calling the application programming interface of the intelligent application monitoring platform.
[0014] The beneficial effects of the above steps are: by integrating multiple AI models, not only the efficiency and accuracy of exception handling are improved, but also the flexibility, robustness and user experience of the system are enhanced.
[0015] According to an application intelligent monitoring method provided by the present application, after the intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform, the method also includes the following steps.
[0016] The intelligent application monitoring platform classifies and grades the abnormal problems corresponding to the abnormal information based on the abnormal information, and determines the category and level of the abnormal problem.
[0017] The intelligent application monitoring platform visualizes the abnormal information, the category of the abnormal problem, the level of the abnormal problem and the solution.
[0018] The beneficial effects of the above steps are: improving the efficiency and accuracy of abnormal problem handling, enhancing decision support, improving user experience, and providing a solid foundation for continuous improvement and optimization of the system.
[0019] According to the application, there is provided an application intelligent monitoring method, the method also includes: the intelligent application monitoring platform determines the person in charge according to the category and level of the abnormal problem, and sends a prompt message to the person in charge.
[0020] The beneficial effects of the above steps are: through the automation and intelligent problem handling process, the efficiency and accuracy of problem solving are improved, and the utilization of human resources can be optimized, providing support for continuous improvement.
[0021] According to the application program intelligent monitoring method provided by the present application, after the intelligent application monitoring platform visualizes the abnormal information, the category of the abnormal problem, the level of the abnormal problem and the solution, the method also includes the following steps.
[0022] The intelligent application monitoring platform executes a solution selected by the user in response to a solution selection instruction issued by the user, wherein the solution selection instruction represents the solution selected by the user.
[0023] The intelligent application monitoring platform responds to the re-acquisition solution instruction issued by the user, and returns to execute the step of the intelligent application monitoring platform calling the application programming interface corresponding to the AI model and sending the exception information to the AI model.
[0024] The beneficial effects of the above steps are: by providing a way for users to interact and select solutions, the efficiency and accuracy of problem solving are improved, the user experience is enhanced, and support is provided for the continuous improvement of the system.
[0025] According to a method for intelligent monitoring of an application provided by the present application, the method further includes: the intelligent application monitoring platform saving the exception information and the solution to an original error information table.
[0026] The beneficial effect of the above steps is: by saving the exception information and solutions to the original error information table, it is convenient for subsequent management personnel to view, and it can provide a reference for subsequent solutions to similar problems, thereby improving the efficiency of application system exception handling.
[0027] The present application also provides an application intelligent monitoring system, which includes: a log platform, an intelligent application monitoring platform and an AI model.
[0028] The intelligent application monitoring platform is used to receive the abnormal logs of the application programs synchronized by the log platform.
[0029] The intelligent application monitoring platform is also used to poll and scan the abnormal log to obtain abnormal information.
[0030] The intelligent application monitoring platform is also used to call the application programming interface corresponding to the AI model, and send the exception information to the AI model, so that the AI model provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information.
[0031] The intelligent application monitoring platform is also used to receive the solution sent by the AI model calling the application programming interface of the intelligent application monitoring platform.
[0032] The beneficial effects of the above system are: it can quickly obtain abnormal information, automatically mobilize AI models to obtain solutions, save the time of application system exception handling, and improve the reliability and availability of the application system.
[0033] The present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-mentioned application intelligent monitoring methods are implemented.
[0034] The present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any of the above-mentioned application intelligent monitoring methods are implemented.
[0035] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned application intelligent monitoring methods.
[0036] The application program intelligent monitoring method, system, device, storage medium and product provided by the present application, the intelligent application monitoring platform can obtain abnormal information in time by polling and scanning the received abnormal log, realize real-time and accurate positioning of abnormal problems, and improve the real-time performance of the application system; the intelligent application monitoring platform can obtain solutions corresponding to abnormal problems by calling AI models, saving the time of abnormal handling of application systems. Furthermore, the AI model can optimize its own performance by constantly learning new abnormal situations and solutions, which means that the platform can become more intelligent and efficient over time. It can be understood that a fast problem detection and resolution mechanism can save the processing time of abnormal problems, thereby improving the overall system availability and reliability. In summary, it can be seen that the solution of the present invention can quickly obtain abnormal information, automatically mobilize the AI model to obtain solutions, save the time of abnormal handling of application systems, and improve the reliability and availability of application systems. BRIEF DESCRIPTION OF THE DRAWINGS
[0037] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0038] Figure 1 It is a hardware environment diagram of an interaction method of a smart device according to an embodiment of the present application.
[0039] Figure 2 It is a flowchart of the application intelligent monitoring method provided by this application.
[0040] Figure 3 It is a schematic diagram of the architecture of the intelligent application monitoring platform provided by this application.
[0041] Figure 4 It is a structural diagram of the application intelligent monitoring system provided by this application.
[0042] Figure 5 It is a schematic diagram of the structure of the electronic device provided in this application. DETAILED DESCRIPTION
[0043] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0044] It should be noted that the terms "including" and "having" and any variations thereof in the specification of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0045] According to one aspect of the embodiment of the present application, a method for intelligent monitoring of an application is provided. The method for intelligent monitoring of an application is widely used in smart home, smart home, smart home device ecology, smart house ecology and other whole-house intelligent digital control application scenarios. Optionally, in this embodiment, the method for intelligent monitoring of an application can be applied to Figure 1 In the hardware environment composed of the terminal device 102 and the server 104 shown in FIG. Figure 1 As shown, the server 104 is connected to the terminal device 102 via a network, and can be used to provide services (such as application services, etc.) for the terminal or a client installed on the terminal. A database can be set on the server or independently of the server to provide data storage services for the server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data computing services for the server 104.
[0046] The network may include but is not limited to at least one of the following: wired network, wireless network. The wired network may include but is not limited to at least one of the following: wide area network, metropolitan area network, local area network, and the wireless network may include but is not limited to at least one of the following: WIFI (Wireless Fidelity), Bluetooth. The terminal device 102 may be but is not limited to a PC, a mobile phone, a tablet computer, a smart air conditioner, a smart range hood, a smart refrigerator, a smart oven, a smart stove, a smart washing machine, a smart water heater, a smart washing equipment, a smart dishwasher, a smart projection equipment, a smart TV, a smart clothes drying rack, a smart curtain, a smart audio and video, a smart socket, a smart speaker, a smart speaker, a smart fresh air equipment, a smart kitchen and bathroom equipment, a smart bathroom equipment, a smart sweeping robot, a smart window cleaning robot, a smart mopping robot, a smart air purification equipment, a smart steamer, a smart microwave oven, a smart kitchen treasure, a smart purifier, a smart water dispenser, a smart door lock, etc.
[0047] The following specific embodiments are used to describe in detail the technical solution of the present application and how the technical solution of the present application solves the above technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. Figure 2and Figure 3 Describe the application intelligent monitoring method of the present application.
[0048] In practical applications, the execution subject of the application intelligent monitoring method can be an intelligent application monitoring platform, which can be implemented in many ways, for example, through a computer program, such as application software, etc.; or, for example, a chip, etc. It can also be implemented as a medium storing relevant computer programs, such as a USB disk, a cloud disk, etc.; or, it can also be implemented through a physical device integrated or installed with relevant computer programs, such as a server, an intelligent device, etc.
[0049] The application intelligent monitoring method provided in this embodiment is applied to an application intelligent monitoring system, which includes a log platform, an intelligent application monitoring platform, and an AI model.
[0050] Figure 2 is a flowchart of the application program intelligent monitoring method provided by this application, such as Figure 2 As shown, the application intelligent monitoring method includes steps 201 to 204.
[0051] Step 201: The intelligent application monitoring platform receives the abnormal log of the application synchronized by the log platform.
[0052] Among them, the log platform is a platform for collecting, storing, managing and analyzing log data generated by applications, systems or network devices. Specifically, during the operation of the application, the application system (including application servers, databases, network devices, etc.) will generate log data, including exception logs. In actual applications, the log platform collects exception logs from the application system. For example, the log platform collects exception logs from the application system through a pre-set communication protocol. For example, the communication protocol can be Syslog, SNMP or other custom protocols.
[0053] Optionally, the intelligent application monitoring platform supports access to multiple types of log platforms. As an example, the log platform includes at least one of the following: a system log platform, an application log platform, and a database log platform.
[0054] Preferably, after the intelligent application monitoring platform receives the exception log of the application synchronized by the log platform, the intelligent application monitoring platform can pre-process the exception log, for example, perform data cleaning, formatting, deduplication, data enhancement, association, caching, etc. on the exception log.
[0055] Step 202: The intelligent application monitoring platform performs polling scanning on the exception log to obtain exception information.
[0056] In this embodiment, polling refers to the intelligent application monitoring platform regularly scanning the exception logs synchronized by the log platform to obtain exception information. In practical applications, the frequency of polling can be pre-set according to actual needs, that is, the interval at which the exception logs are scanned. Furthermore, when the scanning time arrives, the predefined rules or patterns are used to scan the exception logs and extract the exception information.
[0057] By way of example, the exception information includes timestamp, error level, error code, error message, stack trace, affected system component, system status, operation context, custom fields, etc.
[0058] Step 203: The intelligent application monitoring platform calls the application programming interface corresponding to the AI model and sends the exception information to the AI model, so that the AI model provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information.
[0059] The Application Programming Interface (API) corresponding to the AI model refers to the standardized interface for communication between the intelligent application monitoring platform and the AI model. The API corresponding to the AI model defines how to request services, pass data, and receive responses.
[0060] In actual applications, the intelligent application monitoring platform encapsulates the exception information extracted from the exception log into the format required for the API call. For example, the intelligent application monitoring platform converts the exception information into JSON, XML or other formats that can be processed by other AI models.
[0061] Furthermore, an HTTP request (such as a POST request) or other communication protocols is used to call an API and make a service call to send the exception information to the AI model.
[0062] Accordingly, after receiving the abnormal information, the AI model parses the abnormal information, uses machine learning algorithms to analyze the data, identifies the abnormal patterns and causes, and generates solutions. For example, the solutions include root cause analysis, repair suggestions, configuration optimization suggestions, recommended system updates or patches, resource adjustment suggestions, temporary mitigation measures, performance tuning suggestions, user operation guidance, system restart instructions, etc.
[0063] Step 204: The intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0064] Among them, data callback refers to a mechanism that allows the AI model to actively send these solutions back to the intelligent application monitoring platform after completing the analysis of abnormal information and generating solutions. In actual applications, after the AI model determines the solution corresponding to the abnormal problem, it calls the corresponding application programming interface (API) of the intelligent application monitoring platform and sends the solution to the intelligent application monitoring platform.
[0065] Preferably, during the callback process, an error handling mechanism is required to deal with possible communication failures, data format errors, or processing anomalies. Furthermore, when the intelligent application monitoring platform successfully receives and processes the callback data (solution), the intelligent application monitoring platform sends a confirmation response to the AI model to ensure that both parties are aware that the data has been processed correctly. Furthermore, the intelligent application monitoring platform and the AI model record detailed information on service calls and callback activities, including time, data content, and processing results, so that managers can conduct subsequent audits and problem tracking.
[0066] It is understandable that the intelligent application monitoring platform can obtain abnormal information in a timely manner by polling and scanning the received abnormal logs, realize real-time and accurate positioning of abnormal problems, and improve the real-time performance of the application system; the intelligent application monitoring platform can obtain solutions corresponding to abnormal problems by calling AI models, saving the time of application system abnormal processing. Furthermore, the AI model can optimize its own performance by constantly learning new abnormal situations and solutions, which means that the platform can become more intelligent and efficient over time. It is understandable that a fast problem detection and resolution mechanism can save the processing time of abnormal problems, thereby improving the overall system availability and reliability. In summary, it can be seen that the scheme of the embodiment can quickly obtain abnormal information, automatically mobilize the AI model to obtain solutions, save the time of application system abnormal processing, and improve the reliability and availability of the application system.
[0067] It should be noted that the solution of the present invention supports multiple AI models. As an example, in one possible implementation, the above-mentioned application intelligent monitoring system includes multiple AI models; the above-mentioned step 203 specifically includes: The intelligent application monitoring platform calls the application programming interface corresponding to each AI model respectively and sends the exception information to each AI model, so that each AI model provides a solution to the exception problem corresponding to the exception information based on the exception information.
[0068] The above step 204 specifically includes: The intelligent application monitoring platform receives the solution sent by each AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0069] In this embodiment, the above-mentioned application intelligent monitoring system includes multiple AI models, that is, the above-mentioned intelligent application monitoring platform supports access to multiple AI models. Specifically, the application intelligent monitoring system processes abnormal information and obtains solutions by integrating multiple AI models.
[0070] It can be understood that, on the one hand, by using multiple AI models, the system can obtain problem solutions from different angles and methods, increasing the diversity of solutions. For complex abnormal problems, multiple AI models can provide more comprehensive analysis and more comprehensive solutions. On the other hand, different AI models may focus on different fields or use different algorithms, which helps to improve the accuracy of problem diagnosis. On the other hand, users can get solutions to problems faster, which improves their satisfaction and trust in the monitoring system. On the other hand, if an AI model fails to provide a solution or the solution provided is unreliable, the solutions of other models can be used as a supplement, which enhances the robustness of the system, and multiple AI models can verify solutions with each other, reducing the risk of erroneous or malicious solutions. On the other hand, multiple AI models can work in parallel and process abnormal information at the same time, improving resource utilization efficiency and processing speed. On the other hand, the system can easily add or remove AI models as needed to adapt to different monitoring needs and environmental changes. On the other hand, in the distributed AI model architecture, the failure of a single model will not affect the operation of the entire system, which improves the fault tolerance of the system. On the other hand, if some AI models are heavily loaded, the system can intelligently assign tasks to models with lighter loads to achieve load balancing. On the other hand, multiple AI models can learn from each other and share knowledge, and over time, they can jointly improve their problem-solving capabilities. In summary, by integrating multiple AI models, this implementation not only improves the efficiency and accuracy of exception handling, but also enhances the flexibility, robustness and user experience of the system.
[0071] In addition, in a possible implementation manner, after the above step 204, the above method further includes: Based on the abnormal information, the intelligent application monitoring platform classifies and grades the abnormal problems corresponding to the abnormal information, and determines the category and level of the abnormal problem; The intelligent application monitoring platform visualizes abnormal information, categories of abnormal problems, levels of abnormal problems, and solutions.
[0072] In practical applications, by classifying and grading abnormal problems, the nature and severity of the problems can be more accurately identified, so that abnormal problems can be managed and responded to more effectively. Furthermore, clear categories and levels of abnormal problems help to reasonably allocate technical resources and give priority to high-level problems.
[0073] Furthermore, the intelligent application monitoring platform visualizes abnormal information, categories of abnormal problems, levels of abnormal problems, and solutions, which can help technical personnel quickly understand the problems and develop response strategies.
[0074] Therefore, the solution of this implementation improves the efficiency and accuracy of abnormal problem handling, enhances decision support, improves user experience, and provides a solid foundation for continuous improvement and optimization of the system.
[0075] Optionally, in a possible implementation manner, the above method further includes: The intelligent application monitoring platform determines the person in charge based on the category and level of the abnormal problem, and sends a prompt message to the person in charge.
[0076] For example, the prompt information includes abnormal information, the category of the abnormal problem, the level of the abnormal problem, the solution, the link to the intelligent application monitoring platform, etc.
[0077] It is understandable that by sending reminder information to the person in charge, the response speed to abnormal problems can be accelerated and the time to solve the problem can be reduced. Furthermore, by assigning the most appropriate person in charge according to the category and level of the problem, professional skills and resources can be used more effectively. Furthermore, automatically sending reminder information reduces errors and omissions in the manual notification process and improves the accuracy of the process.
[0078] Therefore, in this embodiment, the efficiency and accuracy of problem solving are improved through automated and intelligent problem handling processes, and the utilization rate of human resources can be optimized, providing support for continuous improvement.
[0079] Preferably, the application intelligent monitoring system also includes a user interaction interface. Specifically, the intelligent application monitoring platform visualizes the abnormal information, the category of abnormal problems, the level of abnormal problems and solutions on the user interaction interface. The interactive interface supports operations such as user selection of solutions, customization of solutions, and re-calling of AI models to obtain solutions.
[0080] For example, in a possible implementation, after the intelligent application monitoring platform visualizes the abnormal information, the category of the abnormal problem, the level of the abnormal problem and the solution, the method further includes: The intelligent application monitoring platform executes the solution selected by the user in response to the solution selection instruction issued by the user, and the solution selection instruction represents the solution selected by the user; In response to the re-acquisition solution instruction issued by the user, the intelligent application monitoring platform returns to the step of executing the intelligent application monitoring platform calling the application programming interface corresponding to the AI model and sending the exception information to the AI model.
[0081] In actual applications, users can directly participate in the problem-solving process, which improves the user's participation and satisfaction with the intelligent application monitoring platform. Specifically, users can choose the most appropriate solution based on actual conditions and business needs, which increases the adaptability and flexibility of the solution. Furthermore, after the user selects a solution, the solution is automatically executed, which can save time for application system exception handling and improve the reliability and availability of the application system. Furthermore, if the user is not satisfied with the solution provided by the AI model, he can get it again, which increases the flexibility of the system.
[0082] Therefore, the solution of this embodiment improves the efficiency and accuracy of problem solving by providing a way for users to interact and select solutions, enhances user experience, and provides support for continuous improvement of the system.
[0083] In addition, in a possible implementation manner, the above method further includes: The intelligent application monitoring platform saves the exception information and solutions to the original error information table.
[0084] In this implementation, by saving the exception information and the solution to the original error information table, it is convenient for subsequent management personnel to view, and can provide a reference for subsequent solutions to similar problems, thereby improving the efficiency of application system exception handling.
[0085] It should be noted that the above-mentioned various implementations can be implemented in combination or individually. As an example, Figure 3 This is a schematic diagram of the architecture of the intelligent application monitoring platform provided by this application. Figure 3 As shown, the intelligent application monitoring platform includes: front-end UI, display layer, business layer, data layer, database, operating environment, and log records. Among them, the front-end UI includes HTML, CSS, jQuery, and pictures; the display layer includes template engine rendering and Ajax interaction (Ajax interaction includes POST requests and GET requests); the business layer includes: system query, log query, AI suggestion, statistical report, system log, etc.; the data layer includes: stored procedures, data cache, custom functions, transactions, read and write databases, etc.; databases include: MS SQL, MY SQL, Oracle; the operating environment includes: Alibaba Cloud host, independent server, third-party virtual host; log records are distributed in the business layer and data layer.
[0086] Specifically, the front-end UI is the interface for users to interact with the intelligent application monitoring platform. It is responsible for displaying information and receiving user input. HTML is used to build the page structure, CSS is used for style design, jQuery is used to simplify HTML document traversal and event processing, and images are used to enhance visual effects. In practice, the front-end UI communicates with the presentation layer through Ajax interaction, sends requests and receives responses, and implements dynamic content updates.
[0087] Specifically, the presentation layer is responsible for processing requests from the front-end UI, rendering pages using the template engine, and exchanging data with the front-end UI through Ajax interactions. It handles POST requests (submitting data) and GET requests (requesting data). In practice, the presentation layer receives requests from the front-end UI, requests data or performs operations from the business layer, and then returns the results to the front-end UI.
[0088] Specifically, the business layer is the logical core of the intelligent application monitoring platform and is responsible for implementing specific business functions, such as system query, log query, AI suggestion, statistical report and system log processing. In practice, the business layer receives requests from the presentation layer, interacts with the data layer to obtain or store data, and returns the processing results to the presentation layer.
[0089] Specifically, the data layer is responsible for data persistence operations, including stored procedures, data caching, custom functions, transaction processing, and database read and write operations. The data layer provides data support for the business layer, executes data operation requests initiated by the business layer, and returns the results to the business layer.
[0090] Specifically, the database is where data is stored, and supports a variety of database systems, such as MS SQL, MySQL, and Oracle, to meet different data storage requirements. The database is closely connected to the data layer, which interacts with the database through SQL statements to perform CRUD (create, read, update, delete) operations.
[0091] Specifically, the operating environment provides the hardware and software environment required for the operation of the intelligent application monitoring platform, including Alibaba Cloud hosts, independent servers, and third-party virtual hosts. The operating environment hosts all levels of the entire system, from the front-end UI to the database, to ensure the stable operation of the intelligent application monitoring platform.
[0092] Specifically, log records are distributed in the business layer and data layer to record the system's operation history and abnormal information, which is convenient for problem tracking and system monitoring. Log records provide a data source for the monitoring system, and the intelligent application monitoring platform can analyze these logs to detect abnormalities and propose solutions.
[0093] In the application intelligent monitoring method provided in this embodiment, the intelligent application monitoring platform can obtain abnormal information in time by polling and scanning the received abnormal logs, realize real-time and accurate positioning of abnormal problems, and improve the real-time performance of the application system; the intelligent application monitoring platform can obtain solutions corresponding to abnormal problems by calling AI models, saving the time of application system exception handling. Furthermore, the AI model can optimize its own performance by constantly learning new abnormal situations and solutions, which means that the platform can become more intelligent and efficient over time. It can be understood that a fast problem detection and resolution mechanism can save the processing time of abnormal problems, thereby improving the overall system availability and reliability. In summary, it can be seen that the solution of this embodiment can quickly obtain abnormal information, automatically mobilize the AI model to obtain solutions, save the time of application system exception handling, and improve the reliability and availability of the application system.
[0094] The application intelligent monitoring system provided by the present application is described below. The application intelligent monitoring system described below and the application intelligent monitoring method described above can be referenced to each other.
[0095] Figure 4 It is a structural diagram of the application intelligent monitoring system provided by this application, such as Figure 4 As shown, the above-mentioned application intelligent monitoring system includes: a log platform 41, an intelligent application monitoring platform 42 and an AI model 43.
[0096] The intelligent application monitoring platform 42 is used to receive the abnormal logs of the application programs synchronized by the log platform 41 .
[0097] The intelligent application monitoring platform 42 is also used to poll and scan the exception log to obtain exception information.
[0098] The intelligent application monitoring platform 42 is also used to call the application programming interface corresponding to the AI model 43, and send the exception information to the AI model 43, so that the AI model 43 provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information.
[0099] The intelligent application monitoring platform 42 is also used to receive the solution sent by the AI model 43 calling the application programming interface of the intelligent application monitoring platform 42.
[0100] Among them, the log platform 41 is a platform for collecting, storing, managing and analyzing log data generated by applications, systems or network devices. Specifically, during the operation of the application, the application system (including application servers, databases, network devices, etc.) will generate log data, including exception logs. In actual applications, the log platform 41 collects exception logs from the application system. For example, the log platform 41 collects exception logs from the application system through a pre-set communication protocol. For example, the communication protocol can be Syslog, SNMP or other custom protocols.
[0101] Optionally, the intelligent application monitoring platform 42 supports access to multiple types of log platforms 41. As an example, the log platform 41 includes at least one of the following: a system log platform, an application log platform, and a database log platform.
[0102] Preferably, after the intelligent application monitoring platform 42 receives the exception log of the application synchronized by the log platform 41, the intelligent application monitoring platform 42 can pre-process the exception log, for example, perform data cleaning, formatting, deduplication, data enhancement, association, caching, etc. on the exception log.
[0103] In this embodiment, polling scanning refers to the intelligent application monitoring platform 42 regularly scanning the exception log synchronized by the log platform 41 to obtain exception information. In practical applications, the frequency of polling can be pre-set according to actual needs, that is, the interval at which the exception log is scanned. Further, when the scanning time arrives, a predefined rule or pattern is used to scan the exception log to extract the exception information.
[0104] The application programming interface (API) corresponding to the AI model 43 refers to a standardized interface for communication between the intelligent application monitoring platform 42 and the AI model 43. The application programming interface corresponding to the AI model 43 defines how to request services, transfer data, and receive responses.
[0105] In actual applications, the intelligent application monitoring platform 42 encapsulates the abnormal information extracted from the abnormal log into the format required for the API call. Further, the intelligent application monitoring platform 42 uses HTTP requests (such as POST requests) or other communication protocols to call the API and make a service call to send the abnormal information to the AI model.
[0106] Accordingly, after receiving the abnormal information, the AI model 43 parses the abnormal information, uses a machine learning algorithm to analyze the data, identifies the pattern and cause of the abnormality, and generates a solution.
[0107] Among them, data callback refers to a mechanism that allows the AI model 43 to actively send these solutions back to the intelligent application monitoring platform after completing the analysis of the abnormal information and generating solutions. In actual applications, after the AI model 43 determines the solution corresponding to the abnormal problem, it calls the application programming interface (API) corresponding to the intelligent application monitoring platform 42 and sends the solution to the intelligent application monitoring platform.
[0108] It is understandable that the intelligent application monitoring platform 42 can obtain abnormal information in a timely manner by polling and scanning the received abnormal logs, realize real-time and accurate positioning of abnormal problems, and improve the real-time performance of the application system; the intelligent application monitoring platform 42 can obtain solutions corresponding to abnormal problems by calling the AI model 43, saving the time of abnormal processing of the application system. Furthermore, the AI model 43 can optimize its own performance by constantly learning new abnormal situations and solutions, which means that the platform can become more intelligent and efficient over time. It is understandable that a fast problem detection and resolution mechanism can save the processing time of abnormal problems, thereby improving the overall system availability and reliability. In summary, it can be seen that the solution of the embodiment can quickly obtain abnormal information, automatically mobilize the AI model 43 to obtain solutions, save the time of abnormal processing of the application system, and improve the reliability and availability of the application system.
[0109] Further, in a possible implementation, the above-mentioned application intelligent monitoring system includes multiple AI models 43; the above-mentioned intelligent application monitoring platform 42 is used to call the application programming interface corresponding to the AI model 43, and send the abnormal information to the AI model 43, so that the AI model 43 provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information, specifically used for: The application programming interface corresponding to each AI model 43 is called respectively, and the exception information is sent to each AI model 43, so that each AI model 43 provides a solution corresponding to the exception problem corresponding to the exception information according to the exception information.
[0110] When the intelligent application monitoring platform 42 is used to receive the solution sent by the AI model 43 calling the application programming interface of the intelligent application monitoring platform 42, it is specifically used to: Receive the solution sent by each AI model 43 calling the application programming interface corresponding to the intelligent application monitoring platform.
[0111] In addition, in a possible implementation manner, the intelligent application monitoring platform 42 is further used for: Based on the abnormal information, classify and grade the abnormal problems corresponding to the abnormal information to determine the category and level of the abnormal problem; Visualize the abnormal information, abnormal problem categories, abnormal problem levels and solutions.
[0112] In addition, in a possible implementation manner, the intelligent application monitoring platform 42 is further used for: According to the category and level of the abnormal problem, the person in charge is determined and a prompt message is sent to the person in charge.
[0113] In addition, in a possible implementation manner, the intelligent application monitoring platform 42 is further used for: In response to a solution selection instruction issued by a user, executing a solution selected by the user, wherein the solution selection instruction represents the solution selected by the user; In response to the re-acquisition solution instruction issued by the user, the process returns to the step of executing the application programming interface corresponding to the AI model 43 and sending the exception information to the AI model 43 .
[0114] In addition, in a possible implementation manner, the intelligent application monitoring platform 42 is further used for: Save the exception information and solution to the original error information table.
[0115] In the application intelligent monitoring system provided by this embodiment, the intelligent application monitoring platform can obtain abnormal information in time by polling and scanning the received abnormal logs, realize real-time and accurate positioning of abnormal problems, and improve the real-time performance of the application system; the intelligent application monitoring platform can obtain solutions corresponding to abnormal problems by calling AI models, saving the time of application system exception handling. Furthermore, the AI model can optimize its own performance by constantly learning new abnormal situations and solutions, which means that the platform can become more intelligent and efficient over time. It can be understood that a fast problem detection and resolution mechanism can save the processing time of abnormal problems, thereby improving the overall system availability and reliability. In summary, it can be seen that the solution of this embodiment can quickly obtain abnormal information, automatically mobilize the AI model to obtain solutions, save the time of application system exception handling, and improve the reliability and availability of the application system.
[0116] Figure 5 is a schematic diagram of the structure of the electronic device provided by the present application, such as Figure 5As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute the application intelligent monitoring method, which includes: the intelligent application monitoring platform receives the abnormal log of the application synchronized by the log platform; the intelligent application monitoring platform performs polling scanning on the abnormal log to obtain abnormal information; the intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the abnormal information to the AI model, so that the AI model provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information; the intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0117] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.
[0118] On the other hand, the present application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the application intelligent monitoring method provided by the above methods, and the method includes: an intelligent application monitoring platform receives the exception log of the application synchronized by the log platform; the intelligent application monitoring platform polls and scans the exception log to obtain exception information; the intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the exception information to the AI model, so that the AI model provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information; the intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0119] On the other hand, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned application intelligent monitoring methods, the methods comprising: an intelligent application monitoring platform receives an exception log of an application synchronized by a log platform; the intelligent application monitoring platform polls and scans the exception log to obtain exception information; the intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the exception information to the AI model, so that the AI model provides a solution corresponding to the exception problem corresponding to the exception information based on the exception information; the intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
[0120] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.
[0121] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A method for intelligent monitoring of an application, characterized in that: Applied to an intelligent monitoring system, the intelligent monitoring system includes a log platform, an AI model, and an intelligent application monitoring platform; the method includes: The intelligent application monitoring platform receives the abnormal log of the application synchronized by the log platform; The intelligent application monitoring platform performs polling scanning on the abnormal log to obtain abnormal information; The intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the abnormal information to the AI model, so that the AI model provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information; The intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform.
2. The application intelligent monitoring method according to claim 1, characterized in that: The application intelligent monitoring system includes multiple AI models; the intelligent application monitoring platform calls the application programming interface corresponding to the AI model, and sends the abnormal information to the AI model, so that the AI model provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information, specifically including: The intelligent application monitoring platform calls the application programming interface corresponding to each AI model respectively, and sends the exception information to each AI model, so that each AI model provides a solution corresponding to the exception problem corresponding to the exception information according to the exception information; The intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform, specifically including: The intelligent application monitoring platform receives the solution sent by each AI model calling the application programming interface of the intelligent application monitoring platform.
3. The application intelligent monitoring method according to claim 1, characterized in that: After the intelligent application monitoring platform receives the solution sent by the AI model calling the application programming interface corresponding to the intelligent application monitoring platform, the method further includes: The intelligent application monitoring platform classifies and grades the abnormal problems corresponding to the abnormal information based on the abnormal information, and determines the category and grade of the abnormal problem; The intelligent application monitoring platform visualizes the abnormal information, the category of the abnormal problem, the level of the abnormal problem and the solution.
4. The application intelligent monitoring method according to claim 3, characterized in that: The method further comprises: The intelligent application monitoring platform determines a person in charge according to the category and level of the abnormal problem, and sends a prompt message to the person in charge.
5. The application intelligent monitoring method according to claim 3, characterized in that: After the intelligent application monitoring platform visually displays the abnormal information, the category of the abnormal problem, the level of the abnormal problem, and the solution, the method further includes: The intelligent application monitoring platform executes a solution selected by the user in response to a solution selection instruction issued by the user, wherein the solution selection instruction represents the solution selected by the user; The intelligent application monitoring platform responds to the re-acquisition solution instruction issued by the user, and returns to execute the step of the intelligent application monitoring platform calling the application programming interface corresponding to the AI model and sending the exception information to the AI model.
6. The application intelligent monitoring method according to any one of claims 1 to 5, characterized in that: The method further comprises: The intelligent application monitoring platform saves the exception information and the solution to the original error information table.
7. An application intelligent monitoring system, characterized in that: The application intelligent monitoring system includes: a log platform, an intelligent application monitoring platform and an AI model; The intelligent application monitoring platform is used to receive the abnormal logs of the application synchronized by the log platform; The intelligent application monitoring platform is also used to poll and scan the abnormal log to obtain abnormal information; The intelligent application monitoring platform is further used to call the application programming interface corresponding to the AI model, and send the abnormal information to the AI model, so that the AI model provides a solution corresponding to the abnormal problem corresponding to the abnormal information according to the abnormal information; The intelligent application monitoring platform is also used to receive the solution sent by the AI model calling the application programming interface of the intelligent application monitoring platform.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the application intelligent monitoring method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the application intelligent monitoring method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the application intelligent monitoring method according to any one of claims 1 to 6 are implemented.