Abnormity analysis method and device based on operation and maintenance atlas, electronic equipment, medium and product

Abstract

The invention discloses an exception analysis method and device based on an operation and maintenance atlas, electronic equipment, a storage medium and a computer program product, and relates to the technical field of application operation and maintenance, and the method comprises the steps: collecting application information from a preset operation and maintenance project development platform, importing the application information into a preset graphic database, and generating an application relation atlas and a redisk summary atlas; under the condition that the preset operation and maintenance project has an abnormal problem, searching an abnormal node corresponding to the abnormal problem in the application relation graph and the redisk summary graph; and determining an association node related to the abnormal node, and outputting the association node, the association node including a reference solution of the abnormal problem. The technical problem that the efficiency is low when the abnormal problem is solved in the current monitoring operation and maintenance process is solved.

Description

Technical Field

[0001] The present application relates to the field of application operation and maintenance technology, and in particular to an abnormality analysis method, device, electronic device, storage medium and computer program product based on an operation and maintenance graph. Background Art

[0002] In the software development process, a complete life cycle should include three stages: coding development - application deployment and operation - review and summary. The current monitoring and operation process mainly focuses on the application deployment and operation stage, lacking the monitoring and correlation analysis capabilities of the coding development and review and summary stages, resulting in difficulty in early warning of potential problems in the coding stage, and lack of data support during the review and summary, forming a monitoring blind spot. Once an abnormality occurs in the system, due to the lack of full-process monitoring and correlation analysis capabilities, solving the problem is like looking for a needle in a haystack, which is inefficient and costly. Therefore, the current monitoring and operation process has the problem of low efficiency in solving abnormal problems. Summary of the invention

[0003] The main purpose of this application is to provide an abnormality analysis method, device, electronic device, storage medium and computer program product based on an operation and maintenance map, aiming to solve the technical problem of low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process.

[0004] To achieve the above objectives, the present application proposes an abnormality analysis method based on an operation and maintenance graph, and the abnormality analysis method based on an operation and maintenance graph includes:

[0005] Collect application information from a preset operation and maintenance project development platform, import the application information into a preset graphic database, and generate an application relationship map and a review summary map;

[0006] When an abnormal problem occurs in the preset operation and maintenance project, an abnormal node corresponding to the abnormal problem is retrieved in the application relationship map and the replay summary map;

[0007] Determine a related node related to the abnormal node and output the related node, wherein the related node includes a reference solution to the abnormal problem.

[0008] In one embodiment, the application information includes application code data, code submission record data, application organizational structure data, code review data and production accident data, the preset operation and maintenance project development platform includes a code hosting platform, a development and operation and maintenance pipeline platform, a configuration management database platform and a knowledge platform, and the step of collecting application information from the preset operation and maintenance project development platform includes:

[0009] Collecting the application code data on the code hosting platform according to a first preset scheduled task mode;

[0010] Collecting the code submission record data on the development and operation pipeline platform according to a preset event-driven mode;

[0011] Collecting the application organizational structure data on the configuration management database platform according to a second preset scheduled task mode;

[0012] The code review data is collected on the knowledge platform according to the third preset scheduled task mode, and the production accident data is collected according to the fourth preset scheduled task mode.

[0013] In one embodiment, the abnormal node includes an abnormal application node in the application relationship graph and an abnormal keyword node in the replay summary graph, the associated node includes a first associated node and a second associated node, and the step of determining an associated node related to the abnormal node includes:

[0014] The node connected to the abnormal application node in the application relationship graph is used as the first associated node, wherein the first associated node includes an associated application node, an associated storage node and an associated user node, wherein the associated application node and the associated storage node are used to determine the impact scope of the abnormal problem, and the associated user node is a precise alarm object for the abnormal problem;

[0015] The node connected to the abnormal keyword node in the review summary graph is used as the second associated node, and the second associated node includes an abnormal reference document node. The abnormal reference document node is associated with a solution document node, an abnormal reference document encoder node and a solution document encoder node. The solution document node and the solution document encoder node are used to determine the reference solution.

[0016] In one embodiment, the application relationship map includes a system architecture map, and the abnormality analysis method based on the operation and maintenance map further includes:

[0017] Determine, based on the application information, call information between application programs in the preset operation and maintenance project;

[0018] Based on the call information, generate a system architecture diagram corresponding to the preset operation and maintenance project;

[0019] In the application relationship map, the system architecture diagram is displayed according to the front-end application layer, the authentication and authorization gateway layer, the back-end business application layer and the storage medium layer.

[0020] In one embodiment, the application code data of the application information includes a configuration file, and the step of determining the call information between the application programs in the preset operation and maintenance project according to the application information includes:

[0021] Parsing the configuration file, and obtaining an abstract syntax tree through lexical analysis and grammatical analysis;

[0022] Traversing the abstract syntax tree and extracting method call nodes in the abstract syntax tree;

[0023] According to the node information of the node called by the method, the calling information between the application programs in the preset operation and maintenance project is obtained.

[0024] In one embodiment, the step of importing the application information into a preset graphic database includes:

[0025] Based on a preset data migration tool, migrating the application information to the preset graphic database in parallel;

[0026] In the case where a migration failure is detected, the migration task of the application information is transferred from the faulty component with the migration failure to the standby component through an adaptive failover mechanism, and the migration task is continued to be executed on the standby component.

[0027] In addition, to achieve the above purpose, the present application also proposes an abnormality analysis device based on an operation and maintenance map, and the abnormality analysis device based on an operation and maintenance map includes:

[0028] A graph generation module is used to collect application information from a preset operation and maintenance project development platform, import the application information into a preset graph database, and generate an application relationship graph and a review summary graph;

[0029] An abnormality search module is used to retrieve an abnormal node corresponding to the abnormal problem in the application relationship map and the replay summary map when an abnormal problem occurs in the preset operation and maintenance project;

[0030] The graph output module is used to determine the associated nodes related to the abnormal node and output the associated nodes, wherein the associated nodes include reference solutions to the abnormal problem.

[0031] In addition, to achieve the above-mentioned purpose, the present application also proposes an electronic device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the anomaly analysis method based on the operation and maintenance map as described above.

[0032] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the anomaly analysis method based on the operation and maintenance map as described above are implemented.

[0033] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the anomaly analysis method based on the operation and maintenance map as described above.

[0034] The present application provides an abnormality analysis method based on an operation and maintenance map, and the abnormality analysis method based on the operation and maintenance map includes: collecting application information from a preset operation and maintenance project development platform, importing the application information into a preset graphic database, and generating an application relationship map and a review summary map; when an abnormal problem occurs in a preset operation and maintenance project, retrieving abnormal nodes corresponding to the abnormal problem in the application relationship map and the review summary map; determining associated nodes related to the abnormal nodes, and outputting the associated nodes, wherein the associated nodes include reference solutions to the abnormal problems.

[0035] This application collects application information of preset operation and maintenance projects. This application information is closely related to the key links in the entire life cycle of software coding development, providing basic support for quickly locating the root cause of the problem. By importing the application information into a preset graphic database, an application relationship map and a review summary map are generated, and complex application relationships, code change history and accident records are converted into an intuitive map form. When an abnormal problem occurs in the preset operation and maintenance project, the system can quickly search the application relationship map and the review summary map, quickly locate the abnormal node corresponding to the abnormal problem, and further analyze the abnormal node and its related nodes to reveal the root cause of the problem and provide a reference solution. Compared with related solutions that focus on the application deployment and operation stages, they lack the monitoring and correlation analysis capabilities of the coding development and review and summary stages, making it difficult to quickly determine the dependencies between services and the abnormal propagation paths, resulting in delayed responses. This application improves the visualization of operation and maintenance work by importing application information in the entire application development process into a preset graphic database and generating an application relationship map and a review and summary map. When an abnormal problem occurs, the system can automatically retrieve abnormal nodes in the application relationship map and the review and summary map, and further determine the associated nodes containing the reference solution, thereby achieving accurate positioning and efficient resolution of abnormal problems, effectively shortening problem resolution time, reducing operation and maintenance costs, and significantly improving the efficiency of resolving abnormal problems in the operation and maintenance process. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 A flowchart of the first embodiment of the abnormal analysis method based on the operation and maintenance map of the present application is provided;

[0039] Figure 2 A schematic diagram of a scenario for abnormal impact range analysis and precise alarm provided in Example 1 of the abnormal analysis method based on the operation and maintenance map of this application;

[0040] Figure 3 A schematic diagram of a scenario for knowledge precipitation provided in Example 1 of the abnormal analysis method based on the operation and maintenance graph of this application;

[0041] Figure 4 A schematic diagram of a scenario for intelligent decision-making provided in Embodiment 1 of the abnormal analysis method based on the operation and maintenance graph of this application;

[0042] Figure 5 A flow chart of the second embodiment of the abnormal analysis method based on the operation and maintenance map of the present application;

[0043] Figure 6 A schematic diagram of a service governance scenario provided in Embodiment 1 of the abnormality analysis method based on the operation and maintenance graph of this application;

[0044] Figure 7 This is a schematic diagram of the module structure of an abnormality analysis device based on an operation and maintenance graph according to an embodiment of the present application;

[0045] Figure 8 Schematic diagram of the device structure of the hardware operating environment involved in the abnormal analysis method based on the operation and maintenance map in the embodiment of the present application.

[0046] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0048] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0049] The main solution of the embodiment of the present application is: collecting application information from a preset operation and maintenance project development platform, importing the application information into a preset graphic database, generating an application relationship map and a review summary map; when an abnormal problem occurs in the preset operation and maintenance project, retrieving the abnormal node corresponding to the abnormal problem in the application relationship map and the review summary map; determining the associated nodes related to the abnormal nodes, and outputting the associated nodes, wherein the associated nodes contain a reference solution to the abnormal problem.

[0050] In this embodiment, for ease of description, the operation and maintenance monitoring system is used as the execution entity for explanation below.

[0051] In the software development process, the current monitoring and operation system mainly focuses on the application deployment and operation stages, ignoring the key monitoring and in-depth analysis capabilities in the coding development and review and summary stages. As a result, potential errors and hidden dangers in the coding stage are difficult to be discovered and warned in a timely manner, making problem location complex and difficult, which is not only inefficient but also accompanied by high resolution costs.

[0052] The present application provides a solution, which generates an application relationship map and a review summary map by collecting application information closely related to the preset operation and maintenance project, and importing the collected application information into a preset graphic database, so as to present the intricate dependencies and data flows between applications in the form of intuitive and easy-to-understand maps. When an abnormal problem occurs in the preset operation and maintenance project, the system can quickly perform intelligent retrieval in the application relationship map and the review summary map, determine the abnormal node corresponding to the abnormal problem, and deeply analyze the abnormal node and its related nodes, revealing the potential root cause of the problem and intelligently recommending reference solutions for the abnormal problem, thereby providing a powerful support tool for quickly responding to and resolving system abnormalities.

[0053] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, an operation and maintenance monitoring system, etc. The following takes the operation and maintenance monitoring system as an example to illustrate this embodiment and the following embodiments.

[0054] Based on this, the embodiment of the present application provides an abnormal analysis method based on the operation and maintenance map, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the abnormality analysis method based on the operation and maintenance map of the present application.

[0055] In this embodiment, the abnormality analysis method based on the operation and maintenance map includes steps S01 to S03:

[0056] Step S01, collecting application information from a preset operation and maintenance project development platform, importing the application information into a preset graphic database, and generating an application relationship map and a review summary map;

[0057] It should be noted that the preset operation and maintenance project refers to a specific IT system or software project that needs to be monitored and maintained. The preset operation and maintenance project development platform is a series of platforms that support the development, deployment, monitoring and other functions of the preset operation and maintenance project. Application information refers to all application-related data in the preset operation and maintenance project development platform. The preset graph database refers to a database system used to store and query graph structured data, such as Neo4j, ArangoDB, Amazon Neptune, etc. The application relationship map is a map that graphically displays the call relationship between applications. The review summary map is used to represent the complex relationship between code review results, production accidents and their solutions.

[0058] In addition, it should be noted that application information is automatically collected from the preset operation and maintenance project development platform, imported into the preset graph database, and the graph processing capabilities of the graph database are used to construct an application relationship graph and a review summary graph. These two graphs respectively describe the dependencies and interaction patterns between applications, as well as the relationships between code changes, production accidents and solutions.

[0059] It is understandable that since traditional operation and maintenance monitoring relies on log analysis and alarm systems, it is difficult to fully display the complexity and internal connections of the system. Therefore, step S01 is performed to build a graph to achieve a visual presentation of the system structure and operation and maintenance knowledge, which facilitates an in-depth understanding of system behavior and significantly improves the analysis efficiency of system complexity, providing a solid data foundation for the subsequent service governance, abnormal impact range analysis and other functions.

[0060] Step S02: when an abnormal problem occurs in a preset operation and maintenance project, an abnormal node corresponding to the abnormal problem is retrieved in the application relationship map and the replay summary map;

[0061] It should be noted that abnormal problems refer to problems or failures that affect the normal operation of the system during the operation and maintenance of the preset operation and maintenance project. When an abnormal problem is detected in the preset operation and maintenance project, the system will automatically search for abnormal nodes related to the abnormal problem in the application relationship map and the review summary map. Abnormal nodes refer to nodes that are directly related to the abnormal problem in the application relationship map and the review summary map.

[0062] It is understandable that in traditional operation and maintenance monitoring systems, operation and maintenance personnel often need to manually analyze a large amount of logs and monitoring data, which is time-consuming and error-prone. Therefore, step S02 is performed. When an abnormal problem occurs, through automated retrieval and analysis, the abnormal node can be quickly located in the graph, which significantly shortens the time for problem location and resolution and improves the response speed and accuracy of the operation and maintenance process.

[0063] Step S03, determining associated nodes related to the abnormal node, and outputting the associated nodes, wherein the associated nodes include reference solutions to the abnormal problems.

[0064] It should be noted that an associated node refers to a node that has a direct or indirect relationship with an abnormal node, and contains applications or storage related to the abnormal problem and solution information to the abnormal problem. The associated nodes analyzed in step S02 are output. These associated nodes contain reference solutions to the abnormal problem. The reference solution refers to recommended information provided for solving abnormal problems based on historical experience or best practices.

[0065] It is understandable that due to the low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process, step S03 is performed to output the retrieved associated nodes and the reference solutions they contain to the operation and maintenance personnel. These solutions may be derived from the experience in handling historical problems, which provides a direct reference for solving the current abnormal problems, improves the efficiency and quality of problem solving, and reduces the time and cost waste caused by manual search and trial and error.

[0066] In a feasible implementation, the application information includes application code data, code submission record data, application organizational structure data, code review data and production accident data. The preset operation and maintenance project development platform includes a code hosting platform, a development and operation and maintenance pipeline platform, a configuration management database platform and a knowledge platform. In step S01, the step of collecting application information from the preset operation and maintenance project development platform includes steps A01 to A04:

[0067] Step A01, collecting application code data on a code hosting platform according to a first preset scheduled task mode;

[0068] It should be noted that the code hosting platform refers to a platform used to store and manage application source code of preset operation and maintenance projects, such as GitHub, GitLab, Bitbucket, etc. The first preset scheduled task mode refers to an application code data collection task that is automatically executed on the code hosting platform at preset time intervals and / or specific time points. Application code data refers to all files and data in the preset operation and maintenance project development platform, including code written in programming language, configuration files, resource files, etc.

[0069] In addition, it should be noted that a first preset scheduled task is set in the system, which specifies the first time point (such as 1 a.m.) and the first frequency for collecting application code data. When the first time point is reached, the system automatically triggers the first preset scheduled task. Through the API or direct access interface, the system connects to the code hosting platform, retrieves the latest application code data from the code hosting platform, and stores the collected application code data in the local database.

[0070] The system is connected to the code hosting platform and performs data collection tasks according to a pre-set first preset scheduled task mode. The task mode defines the cycle and time point of data collection to ensure that the system can automatically collect the latest application code data from the code hosting platform on a regular basis.

[0071] Step A02, collecting code submission record data in the development and operation pipeline platform according to the preset event-driven mode;

[0072] It should be noted that the development and operation pipeline platform refers to a platform that supports automated processes such as code building, testing, deployment and monitoring, such as Jenkins, GitLab CI / CD, Azure DevOps, etc. The preset event-driven mode triggers task execution when specific events occur. These events can be code submission, service failure, performance threshold triggering, etc. The code submission record data records the historical information of the developer's changes to all files and data in the preset operation and maintenance project development platform, including the author, time, submission instructions and specific content of each submission.

[0073] In addition, it should be noted that in the development and operation pipeline platform, an event listener is set up to capture driver events (such as code merging, pushing to a specific branch, etc.). When the system detects the occurrence of a driver event, it automatically triggers the data collection process, and collects code submission record data related to the event from the development and operation pipeline platform through an API or internal interface, and stores the collected code submission record data in the local database.

[0074] In the development and operation pipeline platform, the system uses a preset event-driven mode to collect code submission record data. This mode relies on the occurrence of specific events, such as code being merged into the main branch, passing the testing phase, etc. When the system detects these events, it executes data collection tasks to collect relevant code submission records, including information such as the submitter, submission time, submission content, and associated work orders or issues.

[0075] Step A03, collecting application organizational structure data in the configuration management database platform according to the second preset scheduled task mode;

[0076] It should be noted that the configuration management database platform (CMDB) is used to store and manage configuration information of IT infrastructure, including hardware, software, services, network equipment, etc. The second preset scheduled task mode is similar to the first preset scheduled task mode, but is applied to the configuration management database platform. It refers to the application organization architecture data collection task that is automatically executed at preset time intervals and / or specific time points. The application organization architecture data describes the composition structure of all applications in the preset operation and maintenance project development platform, the relationship between components, and how they work together, including dependencies between services, network topology, data flow, etc.

[0077] In addition, it should be noted that, similar to step A01, for the configuration management database platform, a second preset scheduled task is set in the task scheduler, specifying a second frequency and a second time point for collecting application organizational structure data. When the second time point is reached, the system automatically executes the second scheduled task, connects to the configuration management database platform through an API or a direct access interface, retrieves application organizational structure data from the configuration management database platform, including server configuration, network topology and other information, and stores the collected application organizational structure data in a data warehouse or database.

[0078] Step A04, collecting code inspection data according to the third preset scheduled task mode on the knowledge platform, and collecting production accident data according to the fourth preset scheduled task mode.

[0079] It should be noted that the knowledge platform refers to a platform used to store and share knowledge, documents, experience and other information within an organization, such as Confluence, Jira, Wiki, etc. The third preset scheduled task mode is used to collect code review data on the knowledge platform, which is the same as the first preset scheduled task mode and the second preset scheduled task mode, and refers to data collection tasks that are automatically executed at preset time intervals and / or specific time points. Code review data refers to data generated during the code review process, including reviewers' comments, suggestions, approval or rejection decisions, etc. The fourth preset scheduled task mode is similar to the third preset scheduled task mode and will not be elaborated here. The production accident data records any events that occur in the production environment that affect the normal operation of the application, including failures, performance issues, security vulnerabilities, etc.

[0080] In addition, it should be noted that, for the knowledge platform, a third scheduled task is set in the task scheduler, and a third frequency and a third time point for collecting code review data are specified. When the third time point is reached, the system automatically executes the third scheduled task, and connects to the knowledge platform containing the code review data through an API or access interface, and retrieves the latest code review data from the knowledge platform, including issues and suggestions in code review, etc.; similarly, a fourth scheduled task is set in the task scheduler, but a fourth frequency and a fourth time point for collecting production accident data are specified. When the fourth time point is reached, the system executes the fourth scheduled task, connects to the knowledge platform containing production accident data, and retrieves the latest production accident data from the knowledge platform, including accident description, scope of impact, handling measures, etc.

[0081] In this implementation, automated data collection reduces manual intervention, improves the timeliness and accuracy of data updates, and speeds up the exception handling process. Multi-source data collection ensures the comprehensiveness of information, helps operation and maintenance personnel understand the application status from multiple dimensions, and improves monitoring results.

[0082] In a feasible implementation, the abnormal node includes an abnormal application node in the application relationship graph and an abnormal keyword node in the review summary graph, and the associated node includes a first associated node and a second associated node. In step S03, the step of outputting the associated node includes steps A11 to A12:

[0083] Step A11, taking the node connected to the abnormal application node in the application relationship graph as the first associated node, the first associated node includes an associated application node, an associated storage node and an associated user node, wherein the associated application node and the associated storage node are used to determine the impact scope of the abnormal problem, and the associated user node is a precise alarm object for the abnormal problem;

[0084] It should be noted that an abnormal application node refers to an application that is marked as abnormal in the application relationship graph due to anomalies (such as crashes, performance degradation, etc.); an abnormal keyword node refers to a keyword or phrase closely related to the current abnormal problem extracted from code review data and production accident data in the monitoring and operation process; an associated application node refers to an application or service related to the abnormal problem; an associated storage node refers to a storage medium or resource related to the abnormal problem; an associated user node refers to a user who has a code submission record or operation and maintenance responsibility for the abnormal application node; the impact scope of the abnormal problem refers to the scope of direct or indirect impact of the abnormal problem on the system, including affected applications, storage, users, etc.; precise alarm objects refer to users or teams that are directly related to the abnormal problem and need to be notified and intervened in a timely manner.

[0085] In addition, it should be noted that the word segmenter function is implemented through a dynamic programming algorithm (such as the Viterbi algorithm), the text in the code review data and production accident data is segmented, and a dictionary dedicated to operation and maintenance is maintained, which contains common operation and maintenance terms, code keywords, etc., to improve the accuracy and efficiency of word segmentation, and keywords are extracted from the segmented text through a graph-based sorting algorithm (such as the TextRank algorithm). In the application relationship graph, according to the monitored abnormal problems, the abnormal application nodes corresponding to the abnormal problems are quickly located, and the associated nodes of the abnormal application nodes in the application relationship graph are analyzed. The associated application nodes and associated storage nodes in the associated nodes are directly related to the abnormal problems, indicating the impact range of the abnormal problems. The associated user nodes are determined as precise alarm objects so that the relevant responsible persons can be notified in time when the abnormality occurs.

[0086] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 2 , Figure 2 A scenario diagram for abnormal impact range analysis and precise alarm is provided. The preset graphic database page is divided into 7 modules. In module M1, "Type" is used to distinguish between application relationship graphs and review summary graphs, and "Scenario" is used to explain the corresponding function of this graph. Here, it represents the abnormal impact range analysis function. The nodes and relationships displayed in the diagram of module M6 are counted in module M5. "APPLICATION5" means that there are 5 applications in module M6: C1, C2, C3, C4, and C5. Similarly, "REDIS1" means that there is a Redis database B1, "MYSQL1" means that there is a Mysql database B2, and "DEVELOPER3" means that there are 3 developers A1, A2, and A3. In module M6, "CALL" means the call between applications, and "CODE" means the developer's coding of the application. Select the node in module M6. After C1, module M2 will display the type and name of node C1 accordingly. If any node in module M6 is selected again, the corresponding type and name of the node selected later will be displayed in module M3. At the same time, the relationship between the two selected nodes is displayed in module M4, including the relationship type and relationship depth. The user can choose whether to turn on the "distinguish direction" function to display the calling relationship between the two selected nodes (who calls whom), and stipulates the maximum number of displayed nodes in module M6, which is 500 here. The information of the selected node in module M6 is displayed in module M7, including the unique identifier (id), application name (Application_name), application display name (Display_name), product number (Product_id), preset graphic database identifier (Unique_code), and storage path (Url).

[0087] In the abnormal impact range analysis scenario in the application relationship graph, when an abnormal problem occurs in the system and it is determined that the abnormal application node corresponding to the abnormal problem is C1, a series of nodes associated with the program node C1 may be affected by the abnormal problem, which represents the abnormal impact range (C2, C3, C5, B1, B2). After determining the abnormal impact range, the application relationship graph can be used to intuitively find the developer nodes A1 and A2 that have code submission records for the abnormal application node, so that accurate alarms can be issued to them, notifying them to deal with the abnormal problem in time.

[0088] Step A12, the node connected to the abnormal keyword node in the review summary graph is used as the second associated node, the second associated node includes the abnormal reference document node, the abnormal reference document node is associated with the solution document node, the abnormal reference document encoder node and the solution document encoder node, the solution document and the solution document encoder are used to determine the reference solution.

[0089] It should be noted that the abnormal reference document node refers to the node associated with all abnormal keywords in the review summary map, indicating that the abnormal reference document it contains is the same or similar to the abnormal problem, and records the detailed information of the abnormal problems that have occurred in the historical operation and maintenance records, including problem description, occurrence time, etc. The solution document node records the solution process, final solution, implementation effect and other information of the abnormal problem in the abnormal reference document. The abnormal reference document encoder node represents the user or team who wrote the abnormal reference document, and the solution document encoder node represents the user or team who wrote the solution document.

[0090] In addition, it should be noted that in the review summary map, the system records specific events and solutions, effectively precipitates knowledge in the operation and maintenance process such as code review and production accidents, and forms a closed-loop knowledge management system. Operation and maintenance personnel can view the history of a developer or an application to understand its performance and potential problems, thereby continuously improving and optimizing the operation and maintenance process. When an abnormal problem occurs, the system will retrieve and associate the abnormal reference document node containing all abnormal keywords based on the abnormal keyword node of the abnormal problem, and find its associated solution document node, abnormal reference document coder node and solution document coder node. Through the abnormal reference documents that are the same or similar to the abnormal problem, it provides references for operation and maintenance personnel, and by analyzing the solution documents and solution document coders associated with the abnormal reference documents, it helps to find solutions and solvers that can solve similar abnormal problems, and realize intelligent decision-making.

[0091] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 3 and Figure 4 , Figure 3 Provides a schematic diagram of the knowledge accumulation scenario. Figure 4Provides a scenario diagram of intelligent decision-making, which is consistent with the above Figure 2 For the same or similar content, please refer to the above introduction and will not be repeated later. Figure 3 In the review summary graph, the knowledge precipitation scenario includes project node P1, abnormal reference document nodes D1, D2, D3, solution document node S1, abnormal reference document coder node A4, solution document coder node A5, keyword nodes K1, K2, K3, "CONTAINS" indicates the inclusion relationship between abnormal reference documents and abnormal keywords, "HAS" indicates that the project contains abnormal reference documents, "SOLVE" indicates the solution document published by the solution document coder, "PLAN" indicates that the abnormal reference document can be solved by the solution document, and "CREATE" indicates that the abnormal reference document coder created the abnormal reference document. In the summary graph, the abnormal problem corresponds to the abnormal reference document node D2. Through the solution document node S1, solution document encoder A5, and keyword node K3 associated with the abnormal reference document node D2, it can be ensured that when similar abnormal problems occur again in the system in the future, the solution corresponding to the solution document and the person who can solve this abnormal problem can be found by querying the review summary graph. At the same time, according to the project P1 where the abnormal reference document node D2 is located and the abnormal reference document encoder A4, it is possible to exclude the same or similar abnormal problems in the applications or storages associated with the project P1 and the abnormal reference document encoder A4, thereby reducing the possibility of similar abnormal problems occurring.

[0092] Figure 4 In the intelligent decision-making scenario in the review summary map, including abnormal reference document nodes D4, D5, D6, solution document node S2, keyword nodes K4, K5, K6, K7, K8, abnormal reference document encoder node and solution document encoder node A6, when an abnormal problem occurs in the system and it is determined that the abnormal keyword nodes corresponding to the abnormal problem are K4 and K5, the node D4 containing the abnormal keyword nodes K4 and K5 is determined to be an abnormal reference document that is the same or similar to the abnormal problem, and the solution document node S2 and solution document encoder node A8 associated with the abnormal reference document node are recommended as solutions and personnel for solving the abnormal problem, so as to help operation and maintenance personnel quickly solve the abnormal problem.

[0093] In this implementation, by accumulating code review and production accident data, operation and maintenance personnel can quickly identify and solve problems in the system by querying the review summary map, which significantly improves the operation and maintenance efficiency. The map-associated node method enables the operation and maintenance knowledge to be effectively accumulated and inherited, providing strong support for system operation and maintenance. Through automation and intelligent methods, the time cycle from the discovery to the resolution of abnormal problems is shortened. The precise alarm function ensures that abnormal information can be conveyed to the relevant responsible persons in a timely and accurate manner, avoiding omissions and delays in information. The intelligent decision-making function provides operation and maintenance personnel with rich historical experience and professional advice, enhancing their ability to deal with complex problems and improving operation and maintenance efficiency.

[0094] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 5 , the application relationship map includes a system architecture map, and the abnormality analysis method based on the operation and maintenance map also includes steps S11 to S13:

[0095] Step S11, determining the calling information between the application programs in the preset operation and maintenance project according to the application information;

[0096] It should be noted that the system collects and analyzes information about each application in the preset operation and maintenance project, including but not limited to application name, function description, interface definition, etc. Based on the collected information, the calling relationship between applications is determined, including which applications call which interfaces, as well as key indicators such as calling frequency and response time. Call information refers to the calling relationship information between functions, methods or procedures in the application.

[0097] Step S12, generating a system architecture diagram corresponding to the preset operation and maintenance project based on the call information;

[0098] It should be noted that the calling relationship determined in step S11 is converted into a visual system architecture diagram. The system architecture diagram refers to a diagram that graphically displays the components of the system and their relationships. In the system architecture diagram, each application is represented as a node, and the lines between the nodes represent the calling relationship. At the same time, additional information can be added to the nodes and lines as needed, such as application name, interface description, calling frequency, etc.

[0099] Step S13, in the application relationship map, the system architecture diagram is displayed according to the front-end application layer, the authentication and authorization gateway layer, the back-end business application layer and the storage medium layer.

[0100] It should be noted that the front-end application layer is the direct interface for users to interact with the system. It is responsible for receiving user input and displaying data and information to users in the form of graphics, text or other forms. The authentication and authorization gateway layer is located between the front-end application layer and the back-end business application layer, and is responsible for processing user authentication and authorization requests. The back-end business application layer is the core logic processing part of the system, responsible for processing business logic and data operations. The storage medium layer is the part of the system used to store data, which can be a database, file system, cache system, etc.

[0101] In addition, it should be noted that in the application relationship map, the complex system architecture is divided into four levels: front-end application layer (front-end Bff application), authentication and authorization gateway layer (back-end gateway + authentication and authorization service), back-end business application layer and storage medium layer. Through layered display, operation and maintenance personnel can quickly identify bottlenecks, redundancies or potential risk points in the system, and then take corresponding optimization measures, such as load balancing adjustment, service splitting and merging, data access optimization, etc., to achieve service governance.

[0102] For example, to help understand the technical concept or technical principle of this application, please refer to Figure 6 , Figure 6 Provides a scenario diagram of service governance, which is similar to the above Figure 2 For the same or similar content, please refer to the above introduction, which will not be repeated later. In module M6, the system architecture diagram is divided into 4 layers from top to bottom. The first layer is the front-end application layer, which includes node C6, the second layer is the authentication and authorization gateway layer, which includes nodes C7 and C8, the third layer is the back-end business application layer, which includes nodes C9, C10, and C11, and the fourth layer is the storage medium layer, which includes nodes B1 and B2. Through the graphical system architecture diagram, operation and maintenance personnel can quickly understand the system architecture, analyze the system complexity, and thus perform service governance.

[0103] In this implementation, by automatically determining the call information based on the application information, the accuracy and completeness of the call information are ensured, providing a solid data foundation for the subsequent generation of the system architecture diagram. By generating the system architecture diagram based on the call information, an intuitive system structure view is provided to the operation and maintenance personnel, so that the operation and maintenance personnel can see the call relationship and dependency between applications at a glance, providing strong support for problem location and solution design. The layered system architecture diagram not only reduces the complexity of the system architecture, but also facilitates users to analyze the complexity of the system, thereby making it easier to identify potential problems and optimization points, and formulate more scientific and reasonable optimization plans, significantly improving the operation and maintenance efficiency.

[0104] In a feasible implementation manner, the application code data of the application information includes a configuration file. In step S11, the step of determining the call information between application programs in the preset operation and maintenance project according to the application information includes steps E01 to E03:

[0105] Step E01, parsing the configuration file, and obtaining an abstract syntax tree through lexical analysis and grammatical analysis;

[0106] It should be noted that the configuration file refers to a file that stores the configuration information required for the operation of the preset operation and maintenance project, such as Yml, Properties, etc. Lexical analysis is the process of decomposing source code or text strings into meaningful lexical units (such as keywords, identifiers, literals, etc.). Syntax analysis is the process of constructing the results of lexical analysis (a series of lexical units) into a grammatical structure (such as an abstract syntax tree) according to the grammatical rules of the language. The abstract syntax tree (AST) refers to the tree representation of the grammatical structure of the source code.

[0107] In addition, it should be noted that the Yml and Properties files in the preset operation and maintenance project are read, and the contents of the read configuration files are converted into Java objects or Map structures through the API provided by the built-in jackson package of SpringBoot. The java.compiler and jdk.compiler modules in the Javac source code are extracted to implement a castrated Java parser, and com.sun.tools.java.parser.Lexer (based on the finite automaton algorithm) is used to perform lexical analysis on the Java source code of the preset operation and maintenance project, splitting it into a series of lexical units, and com.sun.tools.java.parser.Parser (based on a top-down recursive descent algorithm) is used for syntax analysis to construct an abstract syntax tree for the preset operation and maintenance project.

[0108] Step E02, traversing the abstract syntax tree, extracting method call nodes in the abstract syntax tree;

[0109] It should be noted that the abstract syntax tree is traversed to extract key node information such as classes, methods, and fields. Among them, special attention is paid to method call nodes, which represent the calling operation of a function or method, including the caller, the called method name, parameters and other information.

[0110] Step E03, obtaining the calling information between the application programs in the preset operation and maintenance project according to the node information of the method calling node.

[0111] It should be noted that the method call node information extracted in step E02 is used to construct or update a model representing the calling relationship between applications (such as a call graph or call chain). This model records which applications call which programs or methods, and how these calls are related to each other.

[0112] In this implementation, by parsing the configuration file of the preset operation and maintenance project, its content is converted into a data structure for programmable operations, providing an accurate application configuration and call relationship basis for subsequent analysis. Through a castrated version of the Java parser, based on lexical analysis and syntax analysis, an abstract syntax tree of the preset operation and maintenance project is quickly generated, and then the call information between applications is obtained, greatly improving the accuracy and efficiency of information extraction.

[0113] In a feasible implementation manner, in step S01, the step of importing application information into a preset graphic database includes steps E11 to E12:

[0114] Step E11, based on a preset data migration tool, migrating application information to a preset graphic database in parallel;

[0115] It should be noted that the preset data migration tool refers to a pre-configured data migration solution for a specific migration task. Here it specifically refers to the independently developed DataX Neo4j Writer. DataX is an open source offline synchronization tool for heterogeneous data sources, and Neo4j Writer is a component based on the DataX framework extension that is specifically used to import application information from the local database into the preset graph database. The underlying layer of DataX Neo4j Writer relies on APOC migration functions and implements parallel processing through the ForkJoin framework to accelerate the migration process of application information to the preset graph database.

[0116] In addition, it should be noted that during the migration process, the system dynamically adjusts the page cache size of the preset graph database, temporarily increases the page cache size of the preset graph database or operating system according to the available memory of the system, and cleans or reduces the cache priority of non-critical data or services before the import begins to ensure that the batch imported application information can occupy more cache resources. The page cache is a cache mechanism used in database management systems to store recently accessed database pages (such as data pages, index pages, etc.). At the same time, the transaction log retention policy is adjusted as needed. The resource management policy, namely the transaction log retention mechanism, is a mechanism used by the preset graph database to ensure data consistency and recovery capabilities. By reducing the number of times the log is written to disk in real time, using a more relaxed write strategy (such as asynchronous write, batch write) to reduce the impact on disk I / O, and using the minimum log mode during batch import to reduce the number of log records, performance is improved, resource usage and import efficiency are optimized.

[0117] Step E12: when a migration failure is detected, the migration task of the application information is transferred from the faulty component with the migration failure to the standby component through an adaptive failover mechanism, and the migration task is continued on the standby component.

[0118] It should be noted that migration failure refers to any problem encountered during the parallel migration of application information that causes the migration task to be interrupted or failed, including but not limited to network interruption, insufficient disk space, database performance bottleneck, defects in the migration tool itself, etc. The adaptive failover mechanism is a mechanism that can automatically transfer the migration task from the faulty component to the backup component for continued execution when a migration failure is detected. The migration task refers to the specific work unit of migrating data from one system or database to another system or database. The backup component refers to the backup system or component that can take over the migration task and continue execution when the main migration task component fails.

[0119] In addition, it should be noted that the consistency probe is used to monitor the various performance indicators of the migration task in real time during the migration process. The consistency probe is a mechanism for detecting data consistency problems in distributed systems. Once a migration failure is detected (such as component failure, network interruption, etc.), the adaptive failover mechanism is immediately triggered to seamlessly switch the current migration task to the pre-prepared backup component for continued execution.

[0120] In this implementation, through parallel migration and dynamic adjustment mechanisms, the problem of low migration efficiency caused by database performance bottlenecks during large-scale data migration is solved, ensuring the efficient use of system resources, avoiding migration delays caused by resource limitations, significantly improving the speed and efficiency of data migration, and reducing the risk of migration interruption due to performance problems. At the same time, the stability and responsiveness of the database are guaranteed. When a migration failure occurs, the continuity and stability of the migration process are achieved through an automated fault detection and transfer mechanism, significantly improving the fault response speed and the reliability of the migration task, reducing the downtime and data loss risk caused by failures, and reducing operation and maintenance costs.

[0121] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the abnormality analysis method based on the operation and maintenance map of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0122] This application also provides an abnormal analysis device based on operation and maintenance graphs, please refer to Figure 7 , the abnormal analysis device based on the operation and maintenance map includes:

[0123] A graph generation module 10 is used to collect application information from a preset operation and maintenance project development platform, import the application information into a preset graph database, and generate an application relationship graph and a review summary graph;

[0124] The abnormality search module 20 is used to search for abnormal problems in the application relationship map and the review summary map when abnormal problems occur in the preset operation and maintenance project;

[0125] The graph output module 30 determines the associated nodes related to the abnormal node and outputs the associated nodes, wherein the associated nodes include reference solutions to the abnormal problem.

[0126] Optionally, the application information includes application code data, code submission record data, application organizational structure data, code review data and production accident data, the preset operation and maintenance project development platform includes a code hosting platform, a development and operation and maintenance pipeline platform, a configuration management database platform and a knowledge platform, and the graph generation module 10 is also used for:

[0127] Collect application code data on the code hosting platform according to a first preset scheduled task mode;

[0128] Collect code submission and record data in the development and operation pipeline platform according to the preset event-driven mode;

[0129] Collect application organizational structure data on the configuration management database platform according to a second preset scheduled task mode;

[0130] On the knowledge platform, code review data is collected according to the third preset scheduled task mode, and production accident data is collected according to the fourth preset scheduled task mode.

[0131] Optionally, the abnormal node includes an abnormal application node in the application relationship graph and an abnormal keyword node in the review summary graph, and the associated node includes a first associated node and a second associated node. The graph output module 30 is further used to:

[0132] The node connected to the abnormal application node in the application relationship graph is used as the first associated node, and the first associated node includes an associated application node, an associated storage node and an associated user node, wherein the associated application node and the associated storage node are used to determine the impact scope of the abnormal problem, and the associated user node is a precise alarm object for the abnormal problem;

[0133] The node connected to the abnormal keyword node in the review summary graph is used as the second associated node, and the second associated node includes an abnormal reference document node. The abnormal reference document node is associated with a solution document node, an abnormal reference document encoder node and a solution document encoder node. The solution document and the solution document encoder are used to determine the reference solution.

[0134] Optionally, the application relationship map includes a system architecture map, and the abnormality analysis device based on the operation and maintenance map further includes an architecture display module 40, and the architecture display module 40 is further used to:

[0135] Determine the calling information between applications in the preset operation and maintenance project based on the application information;

[0136] Generate a system architecture diagram corresponding to the preset operation and maintenance project based on the call information;

[0137] In the application relationship diagram, the system architecture diagram is displayed according to the front-end application layer, authentication and authorization gateway layer, back-end business application layer and storage medium layer.

[0138] Optionally, the application code data of the application information includes a configuration file, and the architecture display module 40 is further used to:

[0139] Parse the configuration file and obtain the abstract syntax tree through lexical analysis and syntax analysis;

[0140] Traverse the abstract syntax tree and extract the method call nodes in the abstract syntax tree;

[0141] According to the node information of the method call node, the call information between applications in the preset operation and maintenance project is obtained.

[0142] Optionally, the graph generation module 10 is further used for:

[0143] Based on the preset data migration tool, application information is migrated to the preset graphic database in parallel;

[0144] In the case where a migration failure is detected, the migration task of the application information is transferred from the faulty component with the migration failure to the standby component through an adaptive failover mechanism, and the migration task is continued on the standby component.

[0145] The abnormal analysis device based on the operation and maintenance map provided by the present application adopts the abnormal analysis method based on the operation and maintenance map in the above embodiment, which can solve the technical problem of low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process. Compared with the prior art, the beneficial effects of the abnormal analysis device based on the operation and maintenance map provided by the present application are the same as the beneficial effects of the abnormal analysis method based on the operation and maintenance map provided by the above embodiment, and the other technical features of the abnormal analysis device based on the operation and maintenance map are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0146] The present application provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the anomaly analysis method based on the operation and maintenance map in the above-mentioned embodiment 1.

[0147] Reference below Figure 8 , which shows a schematic diagram of the structure of an electronic device suitable for implementing an embodiment of the present application. The electronic device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, notebook computers, PADs (Portable Application Description: tablet computers), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 8 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0148] like Figure 8 As shown, the electronic device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the electronic device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a microphone, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a hard disk; and a communication device 1009. The communication device 1009 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although the electronic device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have instead.

[0149] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0150] The electronic device provided by the present application adopts the abnormal analysis method based on the operation and maintenance map in the above embodiment, which can solve the technical problem of low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process. Compared with the prior art, the beneficial effects of the electronic device provided by the present application are the same as the beneficial effects of the abnormal analysis method based on the operation and maintenance map provided in the above embodiment, and the other technical features in the electronic device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0151] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0152] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0153] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the anomaly analysis method based on the operation and maintenance graph in the above-mentioned embodiment.

[0154] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0155] The computer-readable storage medium may be included in the electronic device, or may exist independently without being installed in the electronic device.

[0156] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by an electronic device, the electronic device: collects application information from a preset operation and maintenance project development platform, imports the application information into a preset graphic database, and generates an application relationship map and a review summary map; when an abnormal problem occurs in the preset operation and maintenance project, retrieves the abnormal node corresponding to the abnormal problem in the application relationship map and the review summary map; determines the associated nodes related to the abnormal nodes, and outputs the associated nodes, wherein the associated nodes contain reference solutions to the abnormal problems.

[0157] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0158] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0159] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0160] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned abnormal analysis method based on the operation and maintenance map, and can solve the technical problem of low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the abnormal analysis method based on the operation and maintenance map provided by the above-mentioned embodiment, and will not be repeated here.

[0161] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned anomaly analysis method based on operation and maintenance graph when executed by a processor.

[0162] The computer program product provided by the present application can solve the technical problem of low efficiency in solving abnormal problems in the current monitoring and operation and maintenance process. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the abnormal analysis method based on the operation and maintenance map provided in the above embodiment, which will not be repeated here.

[0163] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. An abnormality analysis method based on operation and maintenance graph, characterized in that: The abnormality analysis method based on the operation and maintenance graph includes: Collect application information from a preset operation and maintenance project development platform, import the application information into a preset graphic database, and generate an application relationship map and a review summary map; When an abnormal problem occurs in the preset operation and maintenance project, an abnormal node corresponding to the abnormal problem is retrieved in the application relationship map and the replay summary map; Determine a related node related to the abnormal node and output the related node, wherein the related node includes a reference solution to the abnormal problem.

2. The abnormality analysis method based on the operation and maintenance graph according to claim 1, characterized in that: The application information includes application code data, code submission record data, application organizational structure data, code review data and production accident data. The preset operation and maintenance project development platform includes a code hosting platform, a development and operation and maintenance pipeline platform, a configuration management database platform and a knowledge platform. The step of collecting application information from the preset operation and maintenance project development platform includes: Collecting the application code data on the code hosting platform according to a first preset scheduled task mode; Collecting the code submission record data on the development and operation pipeline platform according to a preset event-driven mode; Collecting the application organizational structure data on the configuration management database platform according to a second preset scheduled task mode; The code review data is collected on the knowledge platform according to the third preset scheduled task mode, and the production accident data is collected according to the fourth preset scheduled task mode.

3. The abnormality analysis method based on the operation and maintenance map according to claim 2 is characterized in that: The abnormal node includes an abnormal application node in the application relationship graph and an abnormal keyword node in the review summary graph, the associated node includes a first associated node and a second associated node, and the step of determining an associated node related to the abnormal node includes: The node connected to the abnormal application node in the application relationship graph is used as the first associated node, wherein the first associated node includes an associated application node, an associated storage node and an associated user node, wherein the associated application node and the associated storage node are used to determine the impact scope of the abnormal problem, and the associated user node is a precise alarm object for the abnormal problem; The node connected to the abnormal keyword node in the review summary graph is used as the second associated node, and the second associated node includes an abnormal reference document node. The abnormal reference document node is associated with a solution document node, an abnormal reference document encoder node and a solution document encoder node. The solution document node and the solution document encoder node are used to determine the reference solution.

4. The abnormality analysis method based on the operation and maintenance graph according to claim 1, characterized in that: The application relationship map includes a system architecture diagram, and the abnormality analysis method based on the operation and maintenance map also includes: Determine, based on the application information, call information between application programs in the preset operation and maintenance project; Based on the call information, generate a system architecture diagram corresponding to the preset operation and maintenance project; In the application relationship map, the system architecture diagram is displayed according to the front-end application layer, the authentication and authorization gateway layer, the back-end business application layer and the storage medium layer.

5. The abnormality analysis method based on the operation and maintenance graph according to claim 4, characterized in that: The application code data of the application information includes a configuration file, and the step of determining the calling information between the application programs in the preset operation and maintenance project according to the application information includes: Parsing the configuration file, and obtaining an abstract syntax tree through lexical analysis and grammatical analysis; Traversing the abstract syntax tree and extracting method call nodes in the abstract syntax tree; According to the node information of the node called by the method, the calling information between the application programs in the preset operation and maintenance project is obtained.

6. The abnormality analysis method based on the operation and maintenance graph according to claim 1, characterized in that: The step of importing the application information into a preset graphic database comprises: Based on a preset data migration tool, migrating the application information to the preset graphic database in parallel; In the case where a migration failure is detected, the migration task of the application information is transferred from the faulty component with the migration failure to the standby component through an adaptive failover mechanism, and the migration task is continued to be executed on the standby component.

7. An abnormality analysis device based on operation and maintenance graph, characterized in that: The abnormality analysis device based on the operation and maintenance graph includes: A graph generation module is used to collect application information from a preset operation and maintenance project development platform, import the application information into a preset graph database, and generate an application relationship graph and a review summary graph; An abnormality search module is used to retrieve an abnormal node corresponding to the abnormal problem in the application relationship map and the replay summary map when an abnormal problem occurs in the preset operation and maintenance project; The graph output module is used to determine the associated nodes related to the abnormal node and output the associated nodes, wherein the associated nodes include reference solutions to the abnormal problem.

8. An electronic device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the abnormality analysis method based on the operation and maintenance graph as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the abnormality analysis method based on the operation and maintenance map as described in any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the abnormality analysis method based on the operation and maintenance map as described in any one of claims 1 to 6 are implemented.

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