Operation and maintenance management method, system and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to an operation and maintenance management method, system and device, computer equipment, a readable storage medium and a program product. The method comprises the steps of obtaining historical job information of a job dependent file from a database under the condition that the job dependent file updated by a user is received; performing server attribution analysis on the historical job information, and determining a target edge server matched with the job dependent file from a plurality of edge servers; and sending an update instruction for the job-dependent file to a proxy node associated with the target edge server, so that the proxy node obtains the job-dependent file by responding to the update instruction, and performs file update on the target edge server based on the obtained job-dependent file. By adopting the method, the operation and maintenance management effect can be improved.

Description

Technical Field

[0001] This application relates to the field of cloud computing technology, and in particular to an operation and maintenance management method, system, device, computer equipment, readable storage medium, and program product. Background Technology

[0002] With the rapid development of cloud computing technology, distributed computing architectures are increasingly widely used in the field of operation and maintenance management. Edge computing, by pushing computing resources down to network edge nodes, significantly reduces data transmission latency and improves service response efficiency, making it particularly suitable for job processing scenarios with high real-time requirements.

[0003] However, the management of job-dependent files in a distributed architecture faces new challenges: due to the large number and dispersed deployment of edge servers, the traditional centralized file update method requires the central node to issue update instructions level by level, resulting in high update latency and large bandwidth consumption, thus causing low operation and maintenance efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide an operation and maintenance management method, device, computer equipment, computer-readable storage medium, and computer program product that can improve the efficiency of operation and maintenance management in response to the above-mentioned technical problems.

[0005] Firstly, this application provides an operation and maintenance management method, including:

[0006] Upon receiving an updated job dependency file from the user, retrieve the historical job information of the job dependency file from the database;

[0007] The historical job information is analyzed for server affiliation, and the target edge server that matches the job dependency file is determined from multiple edge servers.

[0008] An update instruction for job dependency files is sent to the proxy node associated with the target edge server, so that the proxy node obtains the job dependency files by responding to the update instruction and updates the files of the target edge server based on the obtained job dependency files.

[0009] In one embodiment, sending the update instruction for the job dependency file to the proxy node associated with the target edge server includes:

[0010] In the case where the job dependency file matches multiple target edge servers, the proxy nodes managed by each of the target edge servers are determined.

[0011] For each of the aforementioned proxy nodes, the priority of the proxy node is determined based on the number of target edge servers associated with the proxy node; the priority is positively correlated with the number of servers.

[0012] According to the priority of each agent node, update instructions for job dependency files are sent to the agent nodes in sequence.

[0013] In one embodiment, the method further includes:

[0014] Based on the number of agent nodes, create a corresponding number of replica files for the job dependency files;

[0015] In response to file retrieval requests sent by each of the agent nodes, the copy file is distributed to each of the agent nodes.

[0016] In one embodiment, the step of performing server attribution analysis on the historical job information to determine the target edge server matching the job dependency file from multiple edge servers includes:

[0017] Perform server attribution analysis on the historical job information to determine the server identifier to which the job dependency file belonged before it was updated;

[0018] Based on the server attributes represented by the server identifier, a target edge server matching the server attributes is determined from a plurality of edge servers.

[0019] In one embodiment, the method further includes:

[0020] Retrieve user-submitted information query requests;

[0021] The system retrieves target information matching the information query request from the database and returns the target information to the user in a structured format.

[0022] Secondly, this application also provides an operation and maintenance management system, including a central server, agent nodes, and edge servers:

[0023] The central server is used to retrieve historical job information of the job dependency file from the database when it receives an updated job dependency file from the user.

[0024] The historical job information is analyzed for server affiliation, and the target edge server that matches the job dependency file is determined from multiple edge servers.

[0025] Send update instructions for job dependency files to the proxy node associated with the target edge server;

[0026] The proxy node is used to respond to the update instruction to obtain the job dependency file, and to update the target edge server based on the obtained job dependency file.

[0027] In one embodiment, the proxy node is specifically used for:

[0028] In response to the update command, query the local storage space for the version of the file associated with the update command;

[0029] If the version of the associated file matches the version of the job dependency file, the job dependency file corresponding to the associated file is retrieved from the local storage space.

[0030] If the version of the associated file does not match the version of the job dependency file, a file retrieval request is sent to the central server to obtain the job dependency file.

[0031] In one embodiment, the proxy node is further configured to:

[0032] For each edge server associated with the agent node, once the edge server completes the file update, the completed job result information and job log are saved to the local storage space.

[0033] If the edge server file update fails, the failure log will be sent to the central server.

[0034] In one embodiment, the central server is further configured to:

[0035] The edge server was given a file cleanup command.

[0036] The edge server is also used for:

[0037] Upon receiving the file cleanup command, the system periodically scans the job result information and job logs stored in the local storage space and deletes expired or useless job result information or job logs according to preset rules.

[0038] In one embodiment, the proxy node is further configured to:

[0039] According to a set time period, the central server obtains the server resource information of each edge server associated with the proxy node.

[0040] The server resource information is saved to an embedded relational database in the local storage space;

[0041] The system receives user service requests from the central server, queries available server resources from the embedded relational database, and schedules the corresponding edge servers to respond to the user service requests according to the server resources.

[0042] Thirdly, this application also provides an operation and maintenance management device, including:

[0043] The historical job information acquisition module is used to retrieve the historical job information of the job dependency file from the database when the user updates the job dependency file.

[0044] The server attribution analysis module is used to perform server attribution analysis on the historical job information and determine the target edge server that matches the job dependency file from multiple edge servers.

[0045] The update instruction sending module is used to send an update instruction for the job dependency file to the agent node associated with the target edge server, so that the agent node can obtain the job dependency file by responding to the update instruction and update the file of the target edge server based on the obtained job dependency file.

[0046] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0047] Fifthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0048] Sixthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described above.

[0049] The aforementioned operation and maintenance management methods, systems, devices, computer equipment, readable storage media, and program products first obtain historical job information of job dependency files from the database, using historical data to provide a data foundation for subsequent analysis and avoiding blind updates due to a lack of historical references. Second, by performing server affiliation analysis on historical job information, the target edge server matching the job dependency files can be accurately identified from multiple edge servers, significantly improving resource utilization efficiency and update accuracy compared to traditional static rule matching methods. Finally, by sending update commands to the agent nodes associated with the target edge server, the file update is automated and distributed, improving operation and maintenance management efficiency. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is an application environment diagram of the operation and maintenance management method in one embodiment;

[0052] Figure 2 This is a flowchart illustrating an operation and maintenance management method in one embodiment;

[0053] Figure 3 This is a sequence diagram of the server resource information update steps in one embodiment;

[0054] Figure 4 This is a flow sequence diagram of the job dependency file update step in one embodiment;

[0055] Figure 5 This is a flowchart illustrating the operation and maintenance management method in another embodiment;

[0056] Figure 6 This is a structural block diagram of the operation and maintenance management device in one embodiment;

[0057] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0059] The operation and maintenance management method provided in this application embodiment can be applied to, for example, Figure 1In the application environment shown, the central server 102 communicates with agent nodes 104 deployed on edge servers via a network. The central server 102 is the core control unit of the entire system, typically deployed in a data center or cloud, responsible for overall management, coordination, and decision-making. Agent nodes 104 are software applications deployed on edge servers, acting as an "intermediate layer" between the central server and edge servers. They are responsible for executing specific tasks locally, managing edge resources, and acting as agents for instructions from the central server. Specifically, during operation and maintenance management, when the central server 102 receives an updated job dependency file from a user, it retrieves historical job information for the job dependency file from the database; it performs server attribution analysis on the historical job information, determining the target edge server matching the job dependency file from multiple edge servers; and it sends an update instruction for the job dependency file to the agent node 104 associated with the target edge server. This allows the agent node 104 to retrieve the job dependency file in response to the update instruction and update the target edge server based on the retrieved job dependency file.

[0060] In one exemplary embodiment, such as Figure 2 As shown, an operation and maintenance management method is provided, which is applied to... Figure 1 Taking the central server 102 as an example, the explanation is as follows:

[0061] Step S202: Upon receiving an updated job dependency file from the user, retrieve historical job information of the job dependency file from the database.

[0062] Job dependency files refer to external files that the program needs to run or the task needs to execute, such as algorithm models, configuration files, data scripts, and dynamic link libraries. These files typically contain key parameters or logic required for task execution; version inconsistencies may lead to incorrect calculation results or service anomalies. For example, in this embodiment, job dependency files may be different versions of script files. Historical job information records relevant data about job dependency files during past task executions, including but not limited to: which edge servers used the file, the usage time, the task type, resource consumption (such as memory usage), and the execution results. This information is stored in a database for analyzing the correlation between files and edge servers.

[0063] Specifically, upon receiving an updated job dependency file from a user, a data query process is first triggered. The central server connects to a pre-configured database and retrieves historical job information based on the unique identifier of the job dependency file. This information may include, for example, which edge servers have accessed the file in the past 30 days, the frequency of access, the type of task accessed, the execution time of the task, the peak resource consumption, and whether the task was successfully completed. For instance, if a file is primarily used for real-time fault detection in industrial equipment, historical information might show that it is accessed 5 times per week by the edge server of factory A, with memory consumption consistently below 200MB per access. By collecting this data, the system can gain a comprehensive understanding of the file's past usage patterns, providing a basis for subsequent server matching.

[0064] Step S204: Perform server attribution analysis on historical job information, and determine the target edge server that matches the job dependency file from multiple edge servers.

[0065] Edge servers are servers deployed at the network edge (such as in corporate parks, factories, base stations, etc.), close to the data source and end users, and are responsible for localized computing, storage, and data processing to reduce latency and bandwidth consumption.

[0066] Specifically, after collecting historical task information, the central server can perform server attribution analysis on the historical task information, prioritizing the edge server that best matches the historical usage scenario of the file. For example, the central server can count the number of times each edge server called the file in the history, filtering out the top N edge servers with the highest call frequency. If multiple edge servers have similar call frequencies, their task execution success rate and resource stability are further compared. If a unique determination still cannot be made, task type matching is considered. For instance, if historical information shows that a file was executed 100 times on edge server X with a 95% success rate, while it was executed 80 times on edge server Y with only an 80% success rate, then edge server X will be prioritized as the target edge server.

[0067] Furthermore, the central server can directly determine the target edge server matching the job dependency file from multiple edge servers based on the server identifier to which the job dependency file belonged before the update in the historical job information. Alternatively, the central server can determine the target edge server matching the server attributes represented by the server identifier from multiple edge servers.

[0068] Step S206: Send an update instruction for the job dependency file to the agent node associated with the target edge server, so that the agent node can obtain the job dependency file by responding to the update instruction, and update the target edge server based on the obtained job dependency file.

[0069] The proxy node is a software module running on the edge server. It acts as an intermediary between the central server and the edge server, and is responsible for receiving instructions from the central server (such as file updates and task scheduling), and performing specific operations locally (such as downloading files, replacing old versions, and restarting services), while also providing feedback on the execution results.

[0070] Specifically, after identifying the target edge server, the central server sends an update command to the agent node associated with the target edge server. This update command may include, for example, the storage path of the job's dependent files, the file version number, verification information, and update requirements. Upon receiving the command, the agent node first parses the command content, then downloads the updated file from the specified location according to the file path, replaces the old file according to preset rules, and records metadata such as the update time and the operator. Finally, the agent node restarts the services that depend on the file to ensure the new file takes effect, and returns the update result to the central server. This process achieves a fully automated closed loop from command issuance to file update, ensuring that the edge server always runs the latest version of the job's dependent files.

[0071] Optionally, if the job dependency file matches multiple target edge servers, the agent node managed by each target edge server is determined, and an update instruction for the job dependency file is sent to the agent node.

[0072] Optionally, when the job dependency file matches multiple target edge servers, the central server can also determine the agent nodes managed by each target edge server. For each agent node, the priority of the agent node is determined based on the number of target edge servers associated with the agent node. The priority is positively correlated with the number of servers. According to the priority of each agent node, update instructions for the job dependency file are sent to the agent nodes in sequence.

[0073] The aforementioned operation and maintenance management methods provide a data foundation, avoiding blind updates due to a lack of historical references. Secondly, by analyzing the server affiliation of historical job information, the target edge server matching the job's dependent files can be accurately identified from multiple edge servers. Compared with the traditional static rule matching method, this significantly improves resource utilization efficiency and update accuracy. Finally, by sending update commands to the agent nodes associated with the target edge server, the automation and distributed execution of file updates are achieved, improving operation and maintenance management efficiency.

[0074] In an exemplary embodiment, sending an update instruction for a job dependency file to a proxy node associated with a target edge server includes: determining the proxy node managed by each target edge server when the job dependency file matches multiple target edge servers; determining the priority of each proxy node based on the number of servers of the target edge servers associated with the proxy node; and sending the update instruction for the job dependency file to the proxy node sequentially according to the priority of each proxy node.

[0075] Priority is positively correlated with the number of servers. The number of servers refers to the total number of servers actually deployed, and its scale directly affects the choice of priority scheduling strategy. Priority is a weight value assigned to a server or task based on dimensions such as business needs, resource consumption, and urgency, used to guide resource allocation and execution order.

[0076] Specifically, when a job's dependency files need to be updated to multiple target edge servers, the central server first queries the database to find the agent nodes associated with each target edge server (e.g., Server A → Agent-A, Server B → Agent-B, Server C → Agent-C). Then, it counts the number of edge servers associated with each agent node (e.g., Agent-A associated with 1, Agent-B with 2, Agent-C with 3), prioritizing them based on quantity (higher quantity, higher priority). Finally, the central server sends update commands sequentially from highest to lowest priority (Agent-C → Agent-B → Agent-A), ensuring that high-priority nodes are processed first.

[0077] In this embodiment, priority scheduling based on the number of servers avoids resource contention caused by simultaneous updates of multiple nodes, thereby improving update efficiency and system stability. This is especially suitable for large-scale heterogeneous edge environments.

[0078] In an exemplary embodiment, the operation and maintenance management method further includes: creating a corresponding number of replica files for job dependency files according to the number of agent nodes; and distributing replica files to each agent node in response to a file retrieval request sent by each agent node.

[0079] Among them, the copy file is a set of multiple identical copies of the file that the same job depends on, which are generated to improve file distribution efficiency and are used to distribute the file to multiple agent nodes in parallel to avoid single point of transmission bottleneck.

[0080] Specifically, the central server can create N copies of the job dependency files based on the number of agent nodes. Each copy contains the same file content and version information. When an agent node sends a file retrieval request, the central server allocates an unused copy from the copy pool to that node and marks it as "allocated". If all copies are allocated, new copies are dynamically generated to meet the demand.

[0081] In this embodiment, parallel distribution of replica files reduces the pressure on single-point transmission, improves the speed and reliability of large-scale node updates, and reduces the load on the central server.

[0082] In an exemplary embodiment, server attribution analysis is performed on historical job information to determine a target edge server that matches the job dependency file from multiple edge servers. This includes: performing server attribution analysis on historical job information to determine the server identifier to which the job dependency file belonged before it was updated in the historical job information; and determining a target edge server that matches the server attributes represented by the server identifier from multiple edge servers.

[0083] Among these, the server identifier is information that uniquely identifies the edge server, such as an IP address (Internet Protocol Address), device serial number, or custom identifier, used to distinguish different server instances. Server attributes are the edge server's hardware configuration, software environment, or business tags.

[0084] Specifically, the central server can analyze the server identifiers of the dependent files in historical job information before they were updated, and further extract the attributes of that server. Then, it filters servers with matching attributes from all edge servers as targets. For example, if a file was historically run on a server with a certain architecture, the central server will prioritize edge servers with the same architecture to avoid update failures due to architecture incompatibility.

[0085] In this embodiment, by combining server attribute matching, update failures caused by environment incompatibility are reduced, the success rate of task execution is improved, and operation and maintenance costs are reduced.

[0086] In one exemplary embodiment, the operation and maintenance management method further includes: obtaining an information query request submitted by a user; retrieving target information matching the information query request from the database; and feeding back the target information to the user in a structured format.

[0087] An information query request refers to a user's request to an information provider to obtain specific information in order to satisfy their information needs. The target information is the specific information content that the user hopes to obtain through the information query request.

[0088] Specifically, after a user submits a structured query request, the central server parses the key fields in the request, retrieves matching target information from the database, and returns the information in the format specified by the user. For example, if a user queries the historical update records of a file, the central server returns a table containing the update time "2024-01-01 10:00", the operator "Admin", the version change "v1.0→v2.0", and the change description "optimized algorithm accuracy". This function allows operations and maintenance personnel to quickly locate problems and improve troubleshooting efficiency.

[0089] In this embodiment, structured information feedback and flexible query methods simplify user operation processes, improve operational transparency, and support data-driven decision-making.

[0090] In one exemplary embodiment, an operation and maintenance management system is also provided, including a central server, agent nodes, and edge servers: the central server is used to, upon receiving a user-updated job dependency file, retrieve historical job information of the job dependency file from a database; perform server affiliation analysis on the historical job information, and determine a target edge server matching the job dependency file from multiple edge servers; send an update instruction for the job dependency file to the agent node associated with the target edge server; the agent node is used to respond to the update instruction, retrieve the job dependency file, and update the target edge server based on the retrieved job dependency file.

[0091] The aforementioned operation and maintenance management system first retrieves historical job information of job dependency files from the database, using historical data to provide a data foundation for subsequent analysis and avoiding blind updates due to a lack of historical reference. Second, by performing server affiliation analysis on historical job information, it can accurately identify the target edge server matching the job dependency files from multiple edge servers, significantly improving resource utilization efficiency and update accuracy compared to traditional static rule matching methods. Finally, by sending update commands to the proxy nodes associated with the target edge server, it achieves automated and distributed execution of file updates, improving operation and maintenance management efficiency.

[0092] In an exemplary embodiment, the proxy node is specifically configured to: respond to an update instruction and query the associated file version of the update instruction from the local storage space; if the associated file version matches the file version of the job dependency file, obtain the job dependency file corresponding to the associated file from the local storage space; if the associated file version does not match the file version of the job dependency file, send a file retrieval request to the central server to obtain the job dependency file.

[0093] The update command, generated by the central server, instructs the agent nodes to update job dependency files. Local storage is the storage device provided by the agent node itself, used to store data such as associated file versions, job dependency files, job result information, job logs, and server resource information. Associated file versions are file version information stored in the local storage space that is related to the job dependency files, used for comparison with the versions of the job dependency files.

[0094] Specifically, upon receiving an update command, the proxy node immediately initiates a response process. First, it performs a detailed query in its local storage space to find the file version information associated with the update command. This process requires the proxy node to traverse and compare files in its local storage space to ensure accurate identification of the associated file version. Once the associated file version is successfully found, the proxy node compares it in detail with the file versions of the job's dependent files. If the versions match perfectly, it means that the required job dependent file is already stored locally, and the proxy node can directly retrieve the corresponding job dependent file from its local storage space, saving network transmission time and resources. However, if the associated file version does not match the job dependent file version, it indicates that the locally stored job dependent file is not the latest version or does not meet the requirements. In this case, the proxy node quickly sends a file retrieval request to the central server, explicitly informing the central server of the required job dependent file information, so that the correct job dependent file can be retrieved from the central server, ensuring that the edge servers can use the latest file to execute the job.

[0095] In this embodiment, by processing update commands through proxy nodes, matching files can be directly obtained locally when they are available, reducing network transmission and improving file update efficiency; when no matching files are available locally, they can be obtained from the central server in a timely manner, ensuring the accuracy and timeliness of job-dependent files and ensuring that edge servers can execute jobs normally.

[0096] In an exemplary embodiment, the proxy node is also configured to: for each edge server associated with the proxy node, if the edge server completes the file update, save the completed job result information and job log to the local storage space; if the edge server file update fails, send the failure log to the central server.

[0097] The job result information refers to the result data generated by the edge server after completing the job, including relevant output content of the job execution. The job log records detailed information during the edge server's job execution process, including operation steps, time, status, etc., for troubleshooting and auditing.

[0098] Specifically, each proxy node has a comprehensive management mechanism for each associated edge server. When an edge server completes a file update operation, the proxy node promptly intervenes, collecting the job results and logs from that edge server and saving them to local storage. This process requires establishing a stable data transmission channel between the proxy node and the edge server to ensure the accurate transmission of job results and logs to local storage. Simultaneously, the proxy node categorizes and stores this information for later retrieval and use. When an edge server file update fails, the proxy node immediately sends the failure log to the central server. During the submission of the failure log, the proxy node performs formatting and encapsulation to ensure the central server can accurately parse and understand the cause of the failure. Upon receiving the failure log, the central server can troubleshoot and repair the issue based on the log information, promptly resolving edge server file update failures and ensuring stable system operation.

[0099] Furthermore, job results can be stored in a database bound to the central server. Users can directly access the job results in the database by writing SQL (Structured Query Language) queries, generating customized analysis charts to help operations and maintenance personnel better understand system operation status and optimize job processes. In this embodiment, the database can be a Duckdb columnar database.

[0100] In this embodiment, the agent node's management of edge server job result information and logs facilitates data storage and retrieval, and makes subsequent analysis and auditing easier; at the same time, sending file update failure logs to the central server helps to troubleshoot and resolve faults in a timely manner, improving the stability and reliability of the system.

[0101] In an exemplary embodiment, the central server is further configured to: issue file cleanup instructions to the edge server; the edge server is further configured to: receive the file cleanup instructions, periodically scan the job result information and job logs stored in the local storage space, and delete expired or useless job result information or job logs according to preset rules.

[0102] The file cleanup command is issued by the central server and instructs the edge servers to clean up the job results information and job logs stored in their local storage space. Preset rules are pre-defined criteria used to determine whether job results information and job logs are expired or useless, such as based on time, file size, or business requirements.

[0103] Specifically, the central server periodically sends file cleanup commands to the edge servers to control the usage of their local storage space. Upon receiving the command, the edge server initiates a periodic scan of its local storage space. During the scan, the edge server checks each stored job result and log file according to preset rules. These preset rules can be flexibly configured based on actual business needs. For example, they can set a retention period for job results and log files, deeming those exceeding the period expired; or they can delete useless files based on their size and importance. Through this periodic scanning and deletion based on preset rules, the edge server can promptly clean up expired or useless data in its local storage space, freeing up storage space, improving storage efficiency, and also contributing to improved overall system performance.

[0104] In this embodiment, the central server issues a file cleanup command, and the edge server cleans up the local storage space according to preset rules. This can effectively release storage space, improve storage efficiency, avoid system performance degradation caused by insufficient storage space, and ensure the long-term stable operation of the system.

[0105] In an exemplary embodiment, the proxy node is further configured to: obtain server resource information of each edge server associated with the proxy node from the central server according to a set time period; save the server resource information to an embedded relational database in the local storage space; receive user service requests issued by the central server, query available server resources from the embedded relational database, and schedule the corresponding edge server to respond to the user service request according to the server resource scheduler.

[0106] The server resource information includes hardware resource information such as the edge server's memory capacity, disk space, and network bandwidth, as well as its current resource usage. The embedded relational database is a lightweight relational database deployed in the local storage space of the proxy node to store and manage server resource information, supporting fast querying and retrieval. In this embodiment, the embedded relational database can be, for example, SQLite. It does not require a separate server process or system administrator privileges; instead, it is directly linked to the application as a library, allowing the application to directly control the database's management and operation. User service requests are requests initiated by users to the system, requesting specific services. The proxy node schedules appropriate edge servers to respond to these requests based on the server resource information.

[0107] Specifically, the proxy nodes proactively retrieve server resource information from their associated edge servers through the central server at set time intervals. This process requires a stable communication connection between the proxy nodes and the central server to ensure timely and accurate acquisition of server resource information. After acquiring the information, the proxy nodes save this server resource information to an embedded relational database in their local storage space. The embedded relational database is efficient and stable, enabling rapid data storage and retrieval, facilitating subsequent management and querying of server resource information by the proxy nodes. When a proxy node receives a user service request from the central server, it immediately queries the embedded relational database for available server resources. During the query process, the proxy node filters out server resources that meet the specific requirements of the user service request and selects the corresponding edge server to respond to the user service request according to the server resource scheduling strategy. This ensures that user service requests are processed promptly and effectively, improving user satisfaction.

[0108] In this embodiment, the proxy node periodically acquires and stores server resource information, enabling it to quickly query available resources and schedule appropriate edge servers when it receives user service requests. This improves the response speed and processing efficiency of user service requests and enhances the user experience.

[0109] In a specific embodiment, such as Figure 3 As shown, after a user updates server resource information, the central server can send an update command to the proxy nodes. The proxy nodes can then request server resource information from the central server. After the central server returns the server resource information to the proxy nodes, the proxy nodes can use local storage (SQLite database) to save the server resource information, ensuring that they can obtain the latest server resource information even when the network is unstable or offline. Furthermore, the proxy nodes can periodically send resource information to the central server to ensure the real-time nature of information updates.

[0110] In addition, such as Figure 4 As shown, after a user updates the job dependency file, the central server can retrieve historical job information from the database. After the database returns the historical job information, the central server can perform server attribution analysis on the historical job information, determine the target edge server that matches the job dependency file from multiple edge servers, and send an update instruction for the job dependency file to the agent node associated with the target edge server. The agent node requests the job dependency file from the central server, retrieves the job dependency file from the database bound to the central server, and saves it to the agent node's local storage space.

[0111] In one embodiment, such as Figure 5As shown, an operation and maintenance management method is also provided, including:

[0112] Step S501: Upon receiving an updated job dependency file from the user, retrieve historical job information of the job dependency file from the database;

[0113] Step S502: Perform server attribution analysis on historical job information to determine the server identifier to which the job dependency files in the historical job information belonged before they were updated.

[0114] Step S503: Based on the server attributes represented by the server identifier, determine the target edge server that matches the server attributes from multiple edge servers.

[0115] Step S504: If the job dependency file matches multiple target edge servers, determine the proxy nodes managed by each target edge server.

[0116] Step S505: For each proxy node, determine the priority of the proxy node based on the number of servers of the target edge server associated with the proxy node.

[0117] The priority is positively correlated with the number of servers.

[0118] Step S506: According to the priority of each agent node, update instructions for job dependency files are sent to the agent nodes in sequence, so that the agent nodes can obtain job dependency files by responding to the update instructions and update the target edge server based on the obtained job dependency files.

[0119] Step S507: Create a corresponding number of replica files for the job dependency files according to the number of agent nodes;

[0120] Step S508: In response to the file retrieval requests sent by each agent node, distribute the copy file to each agent node;

[0121] Step S509: Obtain the information query request submitted by the user;

[0122] Step S510: Retrieve target information matching the information query request from the database and return the target information to the user in a structured format.

[0123] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0124] Based on the same inventive concept, this application also provides an operation and maintenance management device for implementing the operation and maintenance management method described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more operation and maintenance management device embodiments provided below can be found in the limitations of the operation and maintenance management method above, and will not be repeated here.

[0125] In one exemplary embodiment, such as Figure 6 As shown, an operation and maintenance management device 600 is provided, including: a historical job information acquisition module 602, a server ownership analysis module 604, and an update instruction sending module 606, wherein:

[0126] The historical job information acquisition module 602 is used to acquire historical job information of the job dependency file from the database when the user updates the job dependency file.

[0127] The server affiliation analysis module 604 is used to perform server affiliation analysis on the historical job information and determine the target edge server that matches the job dependency file from multiple edge servers.

[0128] The update instruction sending module 606 is used to send an update instruction for the job dependency file to the agent node associated with the target edge server, so that the agent node can obtain the job dependency file by responding to the update instruction and update the file of the target edge server based on the obtained job dependency file.

[0129] In an exemplary embodiment, the update instruction sending module 606 is specifically used for:

[0130] In the case where the job dependency file matches multiple target edge servers, the proxy nodes managed by each of the target edge servers are determined.

[0131] For each of the aforementioned proxy nodes, the priority of the proxy node is determined based on the number of target edge servers associated with the proxy node; the priority is positively correlated with the number of servers.

[0132] According to the priority of each agent node, update instructions for job dependency files are sent to the agent nodes in sequence.

[0133] In an exemplary embodiment, the operation and maintenance management device 600 further includes a copy file distribution module, specifically used for:

[0134] Based on the number of agent nodes, create a corresponding number of replica files for the job dependency files;

[0135] In response to file retrieval requests sent by each of the agent nodes, the copy file is distributed to each of the agent nodes.

[0136] In one exemplary embodiment, the server attribution analysis module 604 is specifically used for:

[0137] Perform server attribution analysis on the historical job information to determine the server identifier to which the job dependency file belonged before it was updated;

[0138] Based on the server attributes represented by the server identifier, a target edge server matching the server attributes is determined from a plurality of edge servers.

[0139] In an exemplary embodiment, the operation and maintenance management device 600 further includes an information feedback module, specifically used for:

[0140] Retrieve user-submitted information query requests;

[0141] The system retrieves target information matching the information query request from the database and returns the target information to the user in a structured format.

[0142] Each module in the aforementioned operation and maintenance management device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0143] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements an operation and maintenance management method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0144] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0145] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0146] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0147] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0148] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0149] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0150] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0151] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. An operation and maintenance management method, characterized in that, include: Upon receiving an updated job dependency file from the user, retrieve the historical job information of the job dependency file from the database; The historical job information is analyzed for server affiliation, and the target edge server that matches the job dependency file is determined from multiple edge servers. An update instruction for job dependency files is sent to the proxy node associated with the target edge server, so that the proxy node obtains the job dependency files by responding to the update instruction and updates the files of the target edge server based on the obtained job dependency files.

2. The method according to claim 1, characterized in that, Sending update instructions for job dependency files to the proxy node associated with the target edge server includes: In the case where the job dependency file matches multiple target edge servers, the proxy nodes managed by each of the target edge servers are determined. For each of the aforementioned proxy nodes, the priority of the proxy node is determined based on the number of target edge servers associated with the proxy node; the priority is positively correlated with the number of servers. According to the priority of each agent node, update instructions for job dependency files are sent to the agent nodes in sequence.

3. The method according to claim 2, characterized in that, The method further includes: Based on the number of agent nodes, create a corresponding number of replica files for the job dependency files; In response to file retrieval requests sent by each of the agent nodes, the copy file is distributed to each of the agent nodes.

4. The method according to claim 1, characterized in that, The step of performing server attribution analysis on the historical job information to determine the target edge server matching the job dependency file from multiple edge servers includes: Perform server attribution analysis on the historical job information to determine the server identifier to which the job dependency file belonged before it was updated; Based on the server attributes represented by the server identifier, a target edge server matching the server attributes is determined from a plurality of edge servers.

5. The method according to claim 1, characterized in that, The method further includes: Retrieve user-submitted information query requests; The system retrieves target information matching the information query request from the database and returns the target information to the user in a structured format.

6. An operation and maintenance management system, characterized in that, This includes central servers, proxy nodes, and edge servers: The central server is used to retrieve historical job information of the job dependency file from the database when it receives an updated job dependency file from the user. The historical job information is analyzed for server affiliation, and the target edge server that matches the job dependency file is determined from multiple edge servers. Send update instructions for job dependency files to the proxy node associated with the target edge server; The proxy node is used to respond to the update instruction to obtain the job dependency file, and to update the target edge server based on the obtained job dependency file.

7. The system according to claim 6, characterized in that, The proxy node is specifically used for: In response to the update command, query the local storage space for the version of the file associated with the update command; If the version of the associated file matches the version of the job dependency file, the job dependency file corresponding to the associated file is retrieved from the local storage space. If the version of the associated file does not match the version of the job dependency file, a file retrieval request is sent to the central server to obtain the job dependency file.

8. The system according to claim 6, characterized in that, The proxy node is also used for: For each edge server associated with the agent node, once the edge server completes the file update, the completed job result information and job log are saved to the local storage space. If the edge server file update fails, the failure log will be sent to the central server.

9. The system according to claim 8, characterized in that, The central server is also used for: The edge server was given a file cleanup command. The edge server is also used for: Upon receiving the file cleanup command, the system periodically scans the job result information and job logs stored in the local storage space and deletes expired or useless job result information or job logs according to preset rules.

10. The system according to claim 6, characterized in that, The proxy node is also used for: According to a set time period, the central server obtains the server resource information of each edge server associated with the proxy node. The server resource information is saved to an embedded relational database in the local storage space; The system receives user service requests from the central server, queries available server resources from the embedded relational database, and schedules the corresponding edge servers to respond to the user service requests according to the server resources.

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