Application server monitoring method, system and equipment based on event triggering and medium

Abstract

The invention discloses an application server monitoring method, system and device based on event triggering and a medium, and the method comprises the steps: monitoring the state data of a plurality of application servers in real time; the state data is obtained based on a preset monitoring index; monitoring abnormal events of the plurality of application servers according to the state data; marking an application server corresponding to the abnormal event as a potential fault application server, and collecting operation data of the potential fault application server; and analyzing and diagnosing the operation data through a preset analysis algorithm to obtain a solution and a diagnosis result of the potential fault application server. Thus, in combination with a monitoring mechanism triggered by an event, collection and diagnosis are triggered only when an abnormal event occurs, rapid response to the abnormal event is realized, problems are rapidly analyzed, a solution is provided, the problems of data redundancy and untimely response caused by frequent timing polling are avoided, and the accuracy of data processing is improved. The application server can be monitored and diagnosed efficiently in real time.

Description

Technical Field

[0001] The present application relates to the technical field of application servers, and in particular to an event-triggered application server monitoring method, system, device and medium. Background Art

[0002] Application server monitoring refers to the process of real-time monitoring and recording of the application server's operating status, performance indicators, resource usage, etc. Through monitoring, potential problems can be discovered and resolved in a timely manner to ensure stable operation and efficient performance of the application.

[0003] At present, application server monitoring technology is to achieve monitoring by periodically collecting performance indicators through timers, such as CPU usage, memory consumption, etc. Although the above-mentioned method of achieving monitoring through timed collection is simple, when the application server has an instantaneous load peak or anomaly, the timed collection method cannot obtain data in time and may miss key performance indicators. In other words, the current application server monitoring technology has a monitoring lag, which makes the reliability and security of the application server low. Summary of the invention

[0004] The present application provides an event-triggered application server monitoring method, system, device and medium, which can realize timely monitoring and improve the reliability and security of the application server.

[0005] In a first aspect, the present application provides an application server monitoring method based on event triggering, the method comprising:

[0006] Real-time monitoring of status data of multiple application servers; the status data is obtained based on preset monitoring indicators;

[0007] Monitoring abnormal events of a plurality of the application servers according to the status data;

[0008] Marking the application server corresponding to the abnormal event as a potential faulty application server, and collecting operation data of the potential faulty application server;

[0009] The operation data is analyzed and diagnosed by a preset analysis algorithm to obtain a solution and a diagnosis result of the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnosis result represents the operation status of the potential faulty application server.

[0010] Optionally, the status data includes operation status data and performance status data, wherein the operation status data is used to indicate whether the application server is in a normal operation state; and the performance status data is used to measure the operation efficiency of the application server.

[0011] Optionally, monitoring abnormal events of the plurality of application servers according to the status data includes:

[0012] If the running status data indicates that the application server is in an abnormal running state, it is determined that the abnormal event is monitored.

[0013] Optionally, monitoring abnormal events of the plurality of application servers according to the status data includes:

[0014] If the performance status data exceeds a preset threshold, it is determined that the abnormal event is monitored.

[0015] Optionally, the analyzing and diagnosing the operating data by using a preset analysis algorithm to obtain a solution and a diagnosis result for the potential faulty application server includes:

[0016] The operation data is analyzed and diagnosed through a machine learning method or a rule matching method to obtain a solution and a diagnosis result for the potential faulty application server.

[0017] Optionally, the multiple application servers are in a multi-stage link, and the real-time monitoring of status data of the multiple application servers includes:

[0018] The multiple application servers are tracked through a cross-service call chain, and the status data of the multiple application servers are monitored in real time.

[0019] Optionally, the method further comprises:

[0020] According to the diagnosis result, the diagnosis result is sent through a preset notification method.

[0021] Optionally, the preset monitoring indicators include central processing unit CPU usage, memory usage, network response time or application anomaly indicators.

[0022] Optionally, the operation data includes logs, process status and thread stacks.

[0023] In a second aspect, the present application also provides an application server monitoring system based on event triggering, the system comprising an event monitoring module and a diagnosis module:

[0024] The event monitoring module is used to monitor the status data of multiple application servers in real time; the status data is obtained based on preset monitoring indicators;

[0025] The event monitoring module is further used to monitor abnormal events of the plurality of application servers according to the status data;

[0026] The event monitoring module is further used to mark the application server corresponding to the abnormal event as a potential fault application server and collect the operation data of the potential fault application server;

[0027] The diagnostic module is used to analyze and diagnose the operating data through a preset analysis algorithm to obtain a solution and a diagnostic result for the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnostic result represents the operating status of the potential faulty application server.

[0028] Optionally, the status data includes operation status data and performance status data, wherein the operation status data is used to indicate whether the application server is in a normal operation state; and the performance status data is used to measure the operation efficiency of the application server.

[0029] Optionally, the event monitoring module is specifically used to:

[0030] If the running status data indicates that the application server is in an abnormal running state, it is determined that the abnormal event is monitored.

[0031] Optionally, the event monitoring module is specifically used to:

[0032] If the performance status data exceeds a preset threshold, it is determined that the abnormal event is monitored.

[0033] Optionally, the diagnosis module is specifically used to:

[0034] The operation data is analyzed and diagnosed through a machine learning method or a rule matching method to obtain a solution and a diagnosis result for the potential faulty application server.

[0035] Optionally, the plurality of application servers are in a multi-stage link, and the event monitoring module is specifically used to:

[0036] The multiple application servers are tracked through a cross-service call chain, and the status data of the multiple application servers are monitored in real time.

[0037] Optionally, the system further comprises a notification module;

[0038] The notification module is used to send the diagnosis result in a preset notification manner according to the diagnosis result.

[0039] Optionally, the preset monitoring indicators include central processing unit CPU usage, memory usage, network response time or application anomaly indicators.

[0040] Optionally, the operation data includes logs, process status and thread stacks.

[0041] In a third aspect, the present application further provides an electronic device, the electronic device comprising a processor and a memory:

[0042] The memory is used to store computer programs;

[0043] The processor is used to execute the method provided in the first aspect according to the computer program.

[0044] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method provided in the first aspect above.

[0045] It can be seen that this application has the following beneficial effects:

[0046] The present application provides an application server monitoring method, system, device and medium based on event triggering, in which the status data of multiple application servers are monitored in real time; the status data is obtained based on preset monitoring indicators; according to the status data, abnormal events of multiple application servers are monitored; the application server corresponding to the abnormal event is marked as a potential fault application server, and the operation data of the potential fault application server is collected; through a preset analysis algorithm, the operation data is analyzed and diagnosed to obtain a solution and a diagnosis result of the potential fault application server, the solution is used to indicate the solution to the abnormal event, and the diagnosis result represents the operation status of the potential fault application server. In this way, combined with the monitoring mechanism triggered by the event, the collection and diagnosis are triggered only when an abnormal event occurs, so as to achieve a rapid response to the abnormal event, so as to quickly analyze the problem and provide a solution, avoid the data redundancy and untimely response problems caused by frequent timed polling, and can monitor and diagnose the application server in real time and efficiently. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0048] Figure 1 This is a flow chart of an application server monitoring method based on event triggering in an embodiment of the present application;

[0049] Figure 2 A schematic diagram of the structure of an application server monitoring system 200 based on event triggering provided in an embodiment of the present application;

[0050] Figure 3 This is a flow chart of an embodiment of an application server monitoring method based on event triggering in an embodiment of the present application;

[0051] Figure 4 A schematic diagram of the structure of an electronic device 400 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] The multiple involved in the embodiments of the present application means greater than or equal to two. It should be noted that in the description of the embodiments of the present application, the words "first", "second", etc. are only used for the purpose of distinguishing the description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying an order.

[0053] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the embodiments of the present application are further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It is understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. In addition, it should be noted that, for ease of description, only the parts related to the present application are shown in the accompanying drawings, not all structures.

[0054] At present, the application server monitoring technology is to monitor performance indicators periodically through timers, such as CPU usage, memory consumption, etc. Although the above-mentioned method of monitoring by timed collection is simple, when the application server has an instantaneous load peak or anomaly, the timed collection method cannot obtain data in time, and may miss key performance indicators. That is, the current application server monitoring technology has monitoring lag, which makes the reliability and security of the application server low. In addition, because the existing technology uses the operation log of the application server as a data source for offline analysis to identify potential performance bottlenecks and abnormal events, it lacks real-time performance and cannot respond to emergencies in time.

[0055] Based on this, an embodiment of the present application provides an event-triggered application server monitoring method, system, device and medium, in which the status data of multiple application servers are monitored in real time; the status data is obtained based on preset monitoring indicators; according to the status data, abnormal events of multiple application servers are monitored; the application servers corresponding to the abnormal events are marked as potential faulty application servers, and the operating data of the potential faulty application servers are collected; the operating data is analyzed and diagnosed through a preset analysis algorithm to obtain a solution and a diagnosis result for the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnosis result represents the operating status of the potential faulty application server.

[0056] In this way, combined with the event-triggered monitoring mechanism, collection and diagnosis are triggered only when an abnormal event occurs, so as to achieve a rapid response to abnormal events, quickly analyze problems and provide solutions, avoid data redundancy and untimely response problems caused by frequent scheduled polling, and enable real-time and efficient monitoring and diagnosis of application servers.

[0057] To facilitate understanding of the specific implementation of the event-triggered application server monitoring method provided in the embodiment of the present application, it will be described below with reference to the accompanying drawings.

[0058] It should be noted that the subject implementing the event-triggered application server monitoring method can be the event-triggered application server monitoring system provided in the embodiment of the present application, and the event-triggered application server monitoring system can be carried in an electronic device or a functional module of an electronic device. The electronic device in the embodiment of the present application can be any device capable of implementing the event-triggered application server monitoring method in the embodiment of the present application, for example, it can be an Internet of Things (IoT) device.

[0059] Figure 1 The flow chart of the event-triggered application server monitoring method provided in the embodiment of the present application is as follows. The method can be applied to an event-triggered application server monitoring system, which can be, for example, Figure 2 The event-triggered application server monitoring system 200 shown in FIG. 1 may also be integrated into the event-triggered application server monitoring method. Figure 4 Functional modules in the electronic device 400 are shown.

[0060] like Figure 1 As shown, the method may include, for example:

[0061] S1, real-time monitoring of status data of multiple application servers.

[0062] It should be noted that the status data is obtained based on preset monitoring indicators, which may include central processing unit (CPU) utilization, memory utilization, network response time or application abnormality indicators. Of course, the preset monitoring indicators are not limited to the above indicators, but may also include other indicators, such as input / output (I / O) indicators, and may also be divided according to the type of indicators to monitor the internal and external indicators of the application server. The embodiments of the present application do not limit the specific content of the preset monitoring indicators.

[0063] It should be noted that an event listener may be integrated into the application server of the embodiment of the present application, so as to realize real-time monitoring of status data of multiple application servers.

[0064] Among them, the event listener includes event listening mechanism and event filtering mechanism. By introducing an event-triggered monitoring mechanism, it can capture abnormal events of the server in real time and diagnose them, thereby reducing data redundancy and significantly improving the response speed to potential faults.

[0065] In a possible implementation, multiple application servers are in a multi-level link, and S1 may include: tracking multiple application servers through a cross-service call chain, and monitoring status data of the multiple application servers in real time.

[0066] It should be noted that the multi-level link in the embodiment of the present application generally refers to a hierarchical data transmission path formed by multiple application servers in a network environment. This link design is intended to improve network reliability, bandwidth utilization, and data transmission efficiency. The method provided in the embodiment of the present application supports the diagnosis of multi-level links, monitors the execution status of client requests in different application servers through cross-service call chain tracking, and monitors the status data of multiple application servers in real time.

[0067] S2, monitors abnormal events of multiple application servers according to the status data.

[0068] The status data may include operation status data and performance status data. The operation status data is used to indicate whether the application server is in a normal operation state; the performance status data is used to measure the operation efficiency of the application server.

[0069] In a possible implementation, S2 may include: if the running status data indicates that the application server is in an abnormal running state, determining that an abnormal event is monitored. The running status data is based on a value corresponding to an application abnormality indicator, and the abnormal running state may include, for example, a request timeout, a service crash, etc.

[0070] In another possible implementation, S2 may include: if the performance status data exceeds a preset threshold, determining that an abnormal event is monitored. The performance status data is a value corresponding to a preset monitoring indicator that characterizes the performance status, and the preset monitoring indicator that characterizes the performance status may be, for example, CPU usage, memory usage, and network response time.

[0071] Then, when the CPU usage exceeds the preset threshold of 90%, it is judged that an abnormal event is monitored; when the memory usage exceeds the preset threshold of 80%, it is judged that an abnormal event is monitored; when the network response time exceeds the preset threshold of 5s, it is judged that an abnormal event is monitored. It should be noted that the preset threshold is not limited in the embodiment of the present application, and technical personnel in this field can make corresponding settings according to actual conditions.

[0072] S3, marking the application server corresponding to the abnormal event as a potential faulty application server, and collecting the operation data of the potential faulty application server.

[0073] Among them, the running data may include logs, process status and thread stacks. Of course, the embodiments of the present application do not limit the running data.

[0074] In the embodiment of the present application, after an abnormal event is captured, the operation data of the potential faulty application server is automatically collected so that the operation data can be subsequently analyzed by a preset analysis algorithm.

[0075] It should be noted that the monitoring method in the prior art generates a large amount of irrelevant duplicate data through timed collection, especially when the system load is stable, which increases the burden of storage and analysis and reduces unnecessary detection. In the embodiment of the present application, the relevant operation data is collected only after the abnormal event is triggered, which greatly reduces data redundancy.

[0076] S4, analyzes and diagnoses the operation data through a preset analysis algorithm to obtain solutions and diagnostic results for potential faulty application servers.

[0077] The solution is used to indicate the solution to the abnormal event, and the diagnosis result represents the operating status of the potential faulty application server.

[0078] In a possible implementation, S4 provided in the embodiment of the present application may include: analyzing and diagnosing the operating data through a machine learning method or a rule matching method to obtain a solution and a diagnosis result for a potential faulty application server.

[0079] It should be noted that, compared with the prior art which only provides a method of data collection, in the embodiments of the present application, a preset intelligent analysis algorithm such as a machine learning method or a rule matching method is used to perform real-time analysis on the collected operating data to identify potential root causes of faults, thereby achieving active prediction or response to potential risks.

[0080] On the basis of the above embodiments, the method provided in the embodiments of the present application may further include:

[0081] S5, sending the diagnosis result through a preset notification method according to the diagnosis result.

[0082] Among them, the preset notification method may include email notification method, SMS notification method or system push method. Of course, the embodiment of the present application does not specifically limit the preset notification method. Technical personnel in this field can set it according to actual needs to ensure that the diagnosis results can be communicated to the staff in a timely and accurate manner.

[0083] In this way, through the method provided in the embodiment of the present application, it is possible to quickly locate which level of application server has a problem through the topological structure of the link, and the method provided in the embodiment of the present application, combined with the event-triggered monitoring mechanism, provides a detailed diagnostic report, that is, collection and diagnosis are triggered only when an abnormal event occurs, so as to achieve a rapid response to abnormal events, so as to quickly analyze the problem and provide a solution, and communicate it to relevant personnel in a timely and accurate manner, avoiding the data redundancy and untimely response problems caused by frequent timed polling. Through the method provided in the embodiment of the present application, the application server can be monitored and diagnosed in real time and efficiently.

[0084] See also Figure 2 The embodiment of the present application provides an application server monitoring system 200 based on event triggering. The application server monitoring system 200 based on event triggering includes an event monitoring module 201 and a diagnosis module 202:

[0085] The event monitoring module 201 is used to monitor the status data of multiple application servers in real time; the status data is obtained based on preset monitoring indicators;

[0086] The event monitoring module 201 is further used to monitor abnormal events of the plurality of application servers according to the status data;

[0087] The event monitoring module 201 is further used to mark the application server corresponding to the abnormal event as a potential fault application server and collect the operation data of the potential fault application server;

[0088] The diagnostic module 202 is used to analyze and diagnose the operating data through a preset analysis algorithm to obtain a solution and a diagnostic result for the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnostic result represents the operating status of the potential faulty application server.

[0089] It should be noted that the status data includes running status data and performance status data. The running status data is used to indicate whether the application server is in a normal operating state; the performance status data is used to measure the operating efficiency of the application server. The running log of the application server is used as a data source for offline analysis to identify potential performance bottlenecks and abnormal events. This method lacks real-time performance and cannot respond to emergencies in a timely manner. The running data includes logs, process status, and thread stacks.

[0090] In a possible implementation, the event monitoring module 201 is specifically configured to: if the running status data indicates that the application server is in an abnormal running state, determine that the abnormal event is monitored.

[0091] In another possible implementation, the event monitoring module 201 is specifically configured to: if the performance status data exceeds a preset threshold, determine that the abnormal event is monitored.

[0092] In a possible implementation, the diagnosis module 202 is specifically used to analyze and diagnose the operation data through a machine learning method or a rule matching method to obtain a solution and a diagnosis result for the potential faulty application server.

[0093] In a possible implementation, the multiple application servers are in a multi-level link, and the event monitoring module 201 is specifically used to: track the multiple application servers through a cross-service call chain, and monitor the status data of the multiple application servers in real time.

[0094] In a possible implementation, the event-triggered application server monitoring system 200 provided in the embodiment of the present application may further include a notification module 203; the notification module 203 is used to send the diagnosis result through a preset notification method according to the diagnosis result.

[0095] In order to understand the monitoring mechanism of the application server monitoring system 200 based on event triggering, Figure 4 Provide explanation.

[0096] See also Figure 4 , is a flow chart of an embodiment of an event-triggered application server monitoring system 200 implementing an event-triggered application server monitoring method, Figure 4 In the example, after the application server monitoring system 200 based on event triggering is started, the event monitoring module 201 starts to monitor the operation data of the application server in real time, and monitors the abnormal events of the application server according to the operation data. If an abnormal event is monitored, the system 200 will trigger the diagnosis module 202 for analysis, and notify the relevant personnel or system according to the diagnosis result, and record the event and the processing result. If no abnormal event is monitored, the application server monitoring system 200 based on event triggering will continue to monitor, and the whole process is a cycle until the cycle is stopped, and the process ends.

[0097] In this way, the overall architecture of the event-triggered application server monitoring system 200 in the embodiment of the present application is composed of an event monitoring module 201, a diagnosis module 202, and a notification module 203. The collaborative work between the modules enables the event-triggered application server monitoring system to monitor and diagnose the application server in real time and efficiently.

[0098] In addition, the present application embodiment also provides an electronic device 400, such as Figure 4 As shown, the electronic device 400 includes a processor 401 and a memory 402:

[0099] The memory 402 is used to store computer programs;

[0100] The processor 401 is used to execute according to the computer program Figure 1 The method provided.

[0101] In addition, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method provided by the embodiment of the present application.

[0102] Through the description of the above implementation methods, it can be known that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a general hardware platform. Based on such an understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a storage medium, such as a read-only memory (ROM) / RAM, a magnetic 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 communication device such as a router) to execute the methods described in each embodiment of the present application or some parts of the embodiments.

[0103] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is only schematic, in which the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the goals of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0104] The above is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. It should be noted that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the present application, and these improvements and modifications should also be regarded as the protection scope of the present application.

Claims

1. An application server monitoring method based on event triggering, characterized in that: The method comprises: Real-time monitoring of status data of multiple application servers; the status data is obtained based on preset monitoring indicators; Monitoring abnormal events of a plurality of the application servers according to the status data; Marking the application server corresponding to the abnormal event as a potential faulty application server, and collecting operation data of the potential faulty application server; The operation data is analyzed and diagnosed by a preset analysis algorithm to obtain a solution and a diagnosis result of the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnosis result represents the operation status of the potential faulty application server.

2. The method according to claim 1, characterized in that The status data includes operation status data and performance status data. The operation status data is used to indicate whether the application server is in a normal operation state; and the performance status data is used to measure the operation efficiency of the application server.

3. The method according to claim 2, characterized in that The monitoring of abnormal events of the plurality of application servers according to the status data includes: If the running status data indicates that the application server is in an abnormal running state, it is determined that the abnormal event is monitored.

4. The method according to claim 2, characterized in that: The monitoring of abnormal events of the plurality of application servers according to the status data includes: If the performance status data exceeds a preset threshold, it is determined that the abnormal event is monitored.

5. The method according to claim 1, characterized in that The method of analyzing and diagnosing the operation data by using a preset analysis algorithm to obtain a solution and a diagnosis result for the potential faulty application server includes: The operation data is analyzed and diagnosed through a machine learning method or a rule matching method to obtain a solution and a diagnosis result for the potential faulty application server.

6. The method according to claim 1, characterized in that The multiple application servers are in a multi-level link, and the real-time monitoring of the status data of the multiple application servers includes: The multiple application servers are tracked through a cross-service call chain, and the status data of the multiple application servers are monitored in real time.

7. The method according to claim 1, characterized in that The method further comprises: According to the diagnosis result, the diagnosis result is sent through a preset notification method.

8. An application server monitoring system based on event triggering, characterized in that: The system includes an event monitoring module and a diagnosis module: The event monitoring module is used to monitor the status data of multiple application servers in real time; the status data is obtained based on preset monitoring indicators; The event monitoring module is further used to monitor abnormal events of the plurality of application servers according to the status data; The event monitoring module is further used to mark the application server corresponding to the abnormal event as a potential fault application server and collect the operation data of the potential fault application server; The diagnostic module is used to analyze and diagnose the operating data through a preset analysis algorithm to obtain a solution and a diagnostic result for the potential faulty application server, wherein the solution is used to indicate a solution to the abnormal event, and the diagnostic result represents the operating status of the potential faulty application server.

9. An electronic device, characterized in that: The electronic device comprises a processor and a memory: The memory is used to store computer programs; The processor is configured to execute the method according to any one of claims 1 to 7 according to the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

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