Operation and maintenance job task monitoring method and device, equipment, storage medium and product

Abstract

The invention discloses an operation and maintenance job task monitoring method, device and equipment, a storage medium and a product, which can be applied to the financial science and technology field, and the method comprises the steps: carrying out the machine operation state detection of at least one operation and maintenance production machine in the operation and maintenance job task execution process, and obtaining the machine operation state data; determining the operation and maintenance task interruption probability of each operation and maintenance production machine in a preset second time period according to the machine operation state data in the preset first time period; according to the operation and maintenance task interruption probability of each operation and maintenance production machine, if it is determined that a target production machine meeting a preset interruption decision judgment condition exists, generating a target machine execution strategy according to the operation and maintenance task interruption probability of the target production machine, and issuing the target machine execution strategy to the target production machine, and executing the target machine execution strategy by the target production machine. According to the technical scheme, risks such as interruption or abnormity in the operation and maintenance task execution process are monitored and evaluated in advance.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a method, device, equipment, storage medium and product for monitoring operation and maintenance tasks. Background Art

[0002] During the operation and maintenance of IT (Information Technology) infrastructure in the banking industry, it is necessary to conduct security monitoring on production machines during the operation and maintenance process to avoid business losses caused by abnormal operation and maintenance operations.

[0003] In existing operation and maintenance task monitoring solutions, anomaly monitoring is usually performed directly on the logs generated by the operation and maintenance tasks. However, this method can often only be monitored after the anomaly has occurred, making it impossible to identify potential task interruption risks in advance and lacking real-time prediction capabilities. Summary of the Invention

[0004] The present invention provides a method, device, equipment, storage medium and product for monitoring operation and maintenance tasks, so as to realize the pre-monitoring and assessment of risks such as interruption or abnormality during the execution of operation and maintenance tasks, and improve the real-time prediction capability during the monitoring process of operation and maintenance tasks.

[0005] According to one aspect of the present invention, a method for monitoring operation and maintenance tasks is provided, the method comprising:

[0006] Performing machine operation status detection on at least one operation and maintenance production machine during the execution of the operation and maintenance task to obtain machine operation status data;

[0007] Determining, based on the machine operating status data within a preset first time period, a probability of interruption of the operation and maintenance tasks of each of the operation and maintenance production machines within a preset second time period;

[0008] Determining whether there is a target production machine that meets a preset interruption decision judgment condition based on the interruption probability of the operation and maintenance task of each of the operation and maintenance production machines;

[0009] If so, a target machine execution policy is generated according to the operation and maintenance task interruption probability of the target production machine, and the target machine execution policy is sent to the target production machine, and the target production machine executes the target machine execution policy.

[0010] According to another aspect of the present invention, there is provided an operation and maintenance task monitoring device, the device comprising:

[0011] An operation status detection module is used to detect the operation status of at least one operation and maintenance production machine in the process of performing an operation and maintenance task, and obtain machine operation status data;

[0012] An interruption probability determination module, configured to determine an interruption probability of the operation and maintenance task of each of the operation and maintenance production machines within a preset second time period based on the machine operation status data within a preset first time period;

[0013] A target machine determination module is used to determine whether there is a target production machine that meets a preset interruption decision judgment condition based on the operation and maintenance task interruption probability of each of the operation and maintenance production machines;

[0014] The execution strategy sending module is used to generate a target machine execution strategy based on the operation and maintenance task interruption probability of the target production machine if it is determined that there is a target production machine that meets the preset interruption decision judgment conditions, and send the target machine execution strategy to the target production machine, so that the target production machine executes the target machine execution strategy.

[0015] According to another aspect of the present invention, an electronic device is provided, comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the operation and maintenance task monitoring method described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the operation and maintenance task monitoring method described in any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the operation and maintenance task monitoring method according to any embodiment of the present invention is implemented.

[0021] The technical solution of the embodiment of the present invention obtains machine operating status data by detecting the machine operating status of at least one operation and maintenance production machine in the process of executing an operation and maintenance task. Based on the machine operating status data in a preset first time period, the operation and maintenance task interruption probability of each operation and maintenance production machine in a preset second time period is determined. Based on the operation and maintenance task interruption probability of each operation and maintenance production machine, when it is determined that there is a target production machine that meets the preset interruption decision judgment condition, the target machine execution strategy is generated based on the operation and maintenance task interruption probability of the target production machine, and the target machine execution strategy is sent to the target production machine. The above technical solution realizes the automated monitoring of the production machine in the process of executing the operation and maintenance task, so that the task interruption risk of the production machine in the future time period can be monitored in advance, and the risk of interruption or abnormality in the execution of the operation and maintenance task can be pre-monitored and evaluated, thereby improving the real-time prediction capability in the monitoring process of the operation and maintenance task.

[0022] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a flowchart of a method for monitoring operation and maintenance tasks according to the first embodiment of the present invention;

[0025] Figure 2 This is a flowchart of a method for monitoring operation and maintenance tasks according to the second embodiment of the present invention;

[0026] Figure 3 This is a flowchart of a method for monitoring operation and maintenance tasks provided according to the third embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram of the structure of an operation and maintenance task monitoring device provided according to a fourth embodiment of the present invention;

[0028] Figure 5 It is a structural diagram of an electronic device for implementing the operation and maintenance task monitoring method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Example 1

[0032] Figure 1 This is a flow chart of a method for monitoring an operation and maintenance task provided in the first embodiment of the present invention. This embodiment is applicable to the case of automated operation and maintenance of bank-related systems or service applications and abnormal monitoring of the operation and maintenance task execution process. The method can be executed by an operation and maintenance task monitoring device, which can be implemented in the form of hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110: Perform machine operation status detection on at least one operation and maintenance production machine in the process of executing the operation and maintenance task to obtain machine operation status data.

[0034] S120: Determine, based on the machine operation status data within the preset first time period, the probability of interruption of the operation and maintenance tasks of each operation and maintenance production machine within the preset second time period.

[0035] S130 : Determine whether there is a target production machine that meets a preset interruption decision judgment condition based on the operation and maintenance task interruption probability of each operation and maintenance production machine.

[0036] S140 , if yes, then generate a target machine execution policy based on the operation and maintenance task interruption probability of the target production machine, and send the target machine execution policy to the target production machine, so that the target production machine executes the target machine execution policy.

[0037] The operation and maintenance production machine may be a device that performs operation and maintenance tasks, such as a server, etc. The operation and maintenance tasks may be the management and maintenance of service systems and / or service applications on the operation and maintenance production machine, such as software installation, configuration updates, and troubleshooting.

[0038] Among them, machine operation status data may include CPU (Central Processing Unit) load, memory usage, disk IO (Input / Output) and service application response time, etc. Machine operation status data is used to describe the performance status of the machine during the execution of operation and maintenance tasks.

[0039] The preset first time period is earlier than the preset second time period. The preset first time period may be a historical time period, and the preset second time period may be a future time period. For example, if the current time is 2025 / 06 / 02 / 09:00, the preset first time period may be 2025 / 06 / 02 / 08:00 to 2025 / 06 / 02 / 08:59, and the preset second time period may be 2025 / 06 / 02 / 09:01 to 2025 / 06 / 02 / 10:00.

[0040] The interruption probability of an operation and maintenance task describes the probability that an operation and maintenance task will be interrupted due to various factors while the operation and maintenance production machine is executing the operation and maintenance task. When the interruption probability is high, it can be considered that the operation and maintenance task is likely to be interrupted within the preset second time period, and preemptive warning or preemptive interruption measures are required. When the interruption probability is low, it can be considered that the interruption probability is low within the preset second time period, and no intervention is required for the operation and maintenance task, which can continue to execute.

[0041] Specifically, for any operation and maintenance production machine, the machine operation status data generated by the operation and maintenance production machine during the execution of the operation and maintenance task within a preset first time period is obtained; the obtained machine operation status data is compared with the normal operation status data under the preset normal execution state, and the data deviation between the machine operation status data within the first preset time period and the preset normal operation status data is determined; based on the data deviation, the probability of operation and maintenance task interruption of the operation and maintenance production machine is determined.

[0042] For example, taking the machine operation status data as CPU load, if the operation and maintenance production machine is a 4-core CPU, the normal operation status data under the set normal execution state, that is, the normal CPU load is 2.0~4.0, if the CPU load obtained in the first time period is 6.0, then the data deviation between the machine operation status data in the first preset time period and the preset normal operation status data is 2.0, then the operation and maintenance task interruption probability can be (2.0 / 6.0*100%*2)66.6%.

[0043] In order to further improve the accuracy of determining the probability of operation and maintenance task interruption of operation and maintenance production machines, in an optional embodiment, the machine operation status data includes central processing unit load, memory occupancy, disk input / output and service application response time; accordingly, based on the machine operation status data within a preset first time period, the operation and maintenance task interruption probability of each operation and maintenance production machine within a preset second time period is determined, including: inputting the central processing unit load, memory occupancy, disk input / output and service application response time of the corresponding operation and maintenance production machine within the preset first time period into a pre-trained operation and maintenance task interruption probability prediction model, and obtaining the operation and maintenance task interruption probability of each operation and maintenance production machine output by the model; wherein, the operation and maintenance task interruption probability prediction model is obtained by pre-training a preset network model based on the historical operation status data of the operation and maintenance production machine in the historical time period and its corresponding probability label data.

[0044] Among them, the operation and maintenance task interruption probability prediction model is used to predict the task interruption probability of the operation and maintenance production machine that performs the operation and maintenance task.

[0045] The training method for the operation and maintenance task interruption probability prediction model can be as follows: historical operating status data of operation and maintenance production machines over a historical time period is obtained, and each historical operating status data is labeled. Specifically, the probability value of the operation and maintenance task interruption corresponding to the historical operating status data is labeled and used as the probability label data for the data itself. For example, the probability label value corresponding to historical operating status data A is 90%, and the probability label value corresponding to historical operating status data B is 80%, and so on. Each historical operating status data and its corresponding probability label data are used as the sample training data set for the model. The historical operating status data includes historical CPU load, historical memory usage, historical disk I / O, and historical service application response time.

[0046] Input a sample training data set with probability label data into a pre-built network model, wherein the preset network model can be a neural network model or a machine learning model, for example, a recurrent neural network or a logistic regression model. Obtain the predicted probability value output by the network model; determine the current loss value in the current iteration cycle based on the probability label value and the predicted probability value and the preset loss function; perform model training on the preset network model according to the current loss value until the preset model training end condition is met, and obtain an operation and maintenance task interruption probability prediction model. The model training end condition can be that the current loss value reaches a set loss threshold, or that the current loss value tends to be stable, or that the current number of iterations reaches a set number threshold, etc. This embodiment does not impose any restrictions on this.

[0047] For any operation and maintenance production machine, the CPU load, memory usage, disk I / O and service application response time of the operation and maintenance production machine within a preset first time period are input into the pre-trained operation and maintenance task interruption probability prediction model to obtain the operation and maintenance task interruption probability of the operation and maintenance production machine output by the model.

[0048] The above technical solution inputs the CPU load, memory usage, disk I / O and service application response time of the corresponding operation and maintenance production machine within a preset first time period into a pre-trained operation and maintenance task interruption probability prediction model, and obtains the operation and maintenance task interruption probability of each operation and maintenance production machine output by the model. By using the pre-trained operation and maintenance task interruption probability prediction model to predict the operation and maintenance task interruption probability of the operation and maintenance production machine, the prediction accuracy of the operation and maintenance task interruption probability is improved, thereby improving the accuracy of selecting subsequent target production machines, and then improving the accurate issuance of execution strategies, thereby realizing accurate abnormal monitoring and control of the operation and maintenance tasks of the production machines.

[0049] Based on the operation and maintenance task interruption probability of each operation and maintenance production machine, it is determined whether there is a target production machine that meets the preset interruption decision judgment criteria. The preset interruption decision judgment criteria can be pre-set by relevant technical personnel based on actual needs. For example, the preset interruption decision judgment criteria can be that the operation and maintenance task interruption probability is greater than a preset task interruption probability threshold. The preset task interruption probability threshold can be pre-set by relevant technical personnel based on actual experience or experimental values. For example, the preset task interruption probability threshold can be set to 60%.

[0050] Specifically, for any operation and maintenance production machine, if the operation and maintenance task interruption probability of the operation and maintenance production machine is greater than a preset task interruption probability threshold, the operation and maintenance production machine is determined as a target production machine.

[0051] If a target production machine meets the requirements among all the production machines, a target machine execution policy is generated based on the target machine's operation and maintenance task interruption probability. It should be noted that different operation and maintenance task interruption probabilities correspond to different abnormality levels. For example, a smaller operation and maintenance task interruption probability corresponds to a lower abnormality level, while a larger operation and maintenance task interruption probability corresponds to a higher abnormality level. Therefore, different target machine execution policies can be generated based on the target machine's operation and maintenance task interruption probability.

[0052] Specifically, when the operation and maintenance task interruption probability of the target production machine is within a first interruption probability range, a first machine execution policy is generated, and the first machine execution policy is used as the target machine execution policy. For example, if the first interruption probability range is set to [80%, 100%], the corresponding first machine execution policy can be set to suspend the operation and interrupt the execution of the current operation and maintenance task. When the operation and maintenance task interruption probability of the target production machine is within the second interruption probability range, a second machine execution policy is generated and used as the target machine execution policy. For example, if the second interruption probability range is set to [70%, 80%], the corresponding second machine execution policy can be set to generate an early warning report or early warning log, displaying the real-time operating status data of the risky production machine, the operation and maintenance task interruption probability, and processing suggestions on the front-end interface, such as a recommendation to expand the CPU load limit. When the operation and maintenance task interruption probability of the target production machine is within the third interruption probability range, a third machine execution policy is generated and used as the target machine execution policy. For example, if the third interruption probability range is set to [60%, 70%], the corresponding third machine execution policy can be manually intervened, triggering the relevant operation and maintenance personnel to manually intervene through message notifications, such as emails, to determine whether to continue the operation and maintenance task or other adjustment strategies, such as replacing production machines or optimizing resource allocation.

[0053] The target machine execution policy is sent to the corresponding target machine production machine, so that the target production machine executes the corresponding target machine execution policy.

[0054] The technical solution of the embodiment of the present invention obtains machine operating status data by detecting the machine operating status of at least one operation and maintenance production machine in the process of executing an operation and maintenance task. Based on the machine operating status data in a preset first time period, the operation and maintenance task interruption probability of each operation and maintenance production machine in a preset second time period is determined. Based on the operation and maintenance task interruption probability of each operation and maintenance production machine, when it is determined that there is a target production machine that meets the preset interruption decision judgment condition, the target machine execution strategy is generated based on the operation and maintenance task interruption probability of the target production machine, and the target machine execution strategy is sent to the target production machine. The above technical solution realizes the automated monitoring of the production machine in the process of executing the operation and maintenance task, so that the task interruption risk of the production machine in the future time period can be monitored in advance, and the risk of interruption or abnormality in the execution of the operation and maintenance task can be pre-monitored and evaluated, thereby improving the real-time prediction capability in the monitoring process of the operation and maintenance task.

[0055] Furthermore, in the process of detecting the machine operating status of the operation and maintenance production machine that performs the operation and maintenance task, there may be a situation where an abnormality has occurred in the operation and maintenance production machine. Therefore, in order to further ensure the normal operation of the operation and maintenance task, it is necessary to promptly detect the abnormal operation and maintenance production machine and take corresponding processing measures for the abnormal operation and maintenance production machine in a timely manner to ensure the safe execution of the operation and maintenance task.

[0056] In an optional embodiment, after performing a machine operation status detection on at least one operation and maintenance production machine in the process of executing an operation and maintenance task, it also includes: obtaining the task execution log of each operation and maintenance production machine in the process of executing the operation and maintenance task; performing keyword extraction on the task execution log to obtain reference log keywords; determining whether there is an abnormal production machine with abnormal operation and maintenance task execution based on the reference log keywords and preset abnormal log keywords; if so, generating an operation and maintenance task interruption strategy, and sending the operation and maintenance task interruption strategy to the abnormal production machine, and the abnormal production machine executes the operation and maintenance task interruption strategy.

[0057] The task execution log records the operation data generated by each service application or system in the operation and maintenance production machine during the execution of the operation and maintenance task.

[0058] Before extracting keywords from task execution logs, the logs can be cleaned up, such as removing irrelevant information like timestamps, removing special symbols, and performing word segmentation. When extracting keywords from task execution logs, a word frequency inverse document frequency method or a deep learning-based keyword extraction method can be used to obtain reference log keywords.

[0059] Exception log keywords can be pre-set by relevant technical personnel based on the abnormal operation and maintenance task scenario. For example, exception log keywords may include "ERROR," "FAULT," and "WARNING." The extracted reference log keywords are matched with the preset exception log keywords. If a matching keyword is found, the operation and maintenance production machine is identified as the abnormal production machine that caused the abnormal operation and maintenance task execution.

[0060] Specifically, the keyword matching process can be based on a preset similarity matching algorithm. When the matching result between the reference log keyword and the abnormal log keyword reaches the set similarity threshold, the two are considered to be consistent. For example, the similarity threshold can be set to 98%. If there is an abnormal production machine that performs abnormal operation and maintenance tasks, an operation and maintenance task interruption strategy is generated. Among them, the operation and maintenance task interruption strategy can be pre-set by relevant technical personnel according to actual needs. For example, the operation and maintenance task interruption strategy can be to suspend the operation and maintenance operation, generate an early warning log, or manually intervene. The operation and maintenance task interruption strategy is sent to the abnormal production machine, and the abnormal production machine executes the operation and maintenance task interruption strategy.

[0061] The above technical solution obtains the task execution log during the operation and maintenance task process, extracts keywords from the task execution log, obtains reference log keywords, and generates an operation and maintenance task interruption strategy when it is determined that there is an abnormal production machine with abnormal operation and maintenance task execution based on the reference log keywords and the preset abnormal log keywords. The operation and maintenance task interruption strategy is then sent to the abnormal production machine, thereby realizing timely detection and timely repair of abnormal operation and maintenance operations of abnormal production machines, improving the safety and reliability of the operation and maintenance task execution process, and avoiding the situation where continuous abnormalities during the operation and maintenance task process lead to low efficiency of operation and maintenance task execution.

[0062] Example 2

[0063] Figure 2 This is a flow chart of a method for monitoring operation and maintenance tasks provided in the second embodiment of the present invention. This embodiment is optimized and improved on the basis of the above technical solutions.

[0064] Furthermore, before the step of "performing a machine operation status detection on at least one operation and maintenance production machine in the process of executing the operation and maintenance task to obtain machine operation status data", add the step of "obtaining the operation and maintenance operation parameters input by the user based on the operation and maintenance management interface; the operation and maintenance operation parameters include the application name, the production machine ID and the operation and maintenance operation task name; obtaining the operation and maintenance operation task according to the operation and maintenance operation task name, and determining the target service application according to the application name, and determining the operation and maintenance production machine according to the machine ID; sending the operation and maintenance operation task to the operation and maintenance production machine, and having the operation and maintenance production machine execute the operation and maintenance operation task." to improve the automated deployment method of the operation and maintenance operation tasks.

[0065] It should be noted that for the parts not described in detail in the embodiments of the present invention, reference can be made to the descriptions of other embodiments. Figure 2 As shown, the method includes the following specific steps:

[0066] S210: Acquire operation and maintenance parameters input by the user based on the operation and maintenance management interface; the operation and maintenance parameters include application name, production machine identifier, and operation and maintenance task name.

[0067] S220: Acquire the operation and maintenance task according to the operation and maintenance task name, determine the target service application according to the application name, and determine the operation and maintenance production machine according to the machine identifier.

[0068] S230: Send the operation and maintenance task to the operation and maintenance production machine, and let the target service application of the operation and maintenance production machine execute the operation and maintenance task.

[0069] S240: Perform machine operation status detection on at least one operation and maintenance production machine in the process of executing the operation and maintenance task to obtain machine operation status data.

[0070] S250: Determine, based on the machine operation status data within the preset first time period, the probability of interruption of the operation and maintenance tasks of each operation and maintenance production machine within the preset second time period.

[0071] S260: Determine whether there is a target production machine that meets a preset interruption decision judgment condition based on the operation and maintenance task interruption probability of each operation and maintenance production machine.

[0072] S270: If so, generate a target machine execution policy based on the operation and maintenance task interruption probability of the target production machine, and send the target machine execution policy to the target production machine, so that the target production machine executes the target machine execution policy.

[0073] It should be noted that during the operation and maintenance of systems or service applications on production machines, the traditional manual operation method requires operation and maintenance personnel to directly log in to the production machines in the production environment, such as physical machines, virtual machines, servers, or network devices such as switches, and perform operation and maintenance management operations such as installation or configuration on each machine through a command line or graphical interface. This manual operation method results in low deployment efficiency of operation and maintenance tasks, and reliance on personal experience may lead to the possibility of operational errors during the deployment process. Therefore, this embodiment provides an automated deployment method for operation and maintenance tasks to improve the deployment efficiency and deployment accuracy of operation and maintenance tasks.

[0074] The operation and maintenance management interface can be a front-end interface that can be deployed with control components and selection components that can control user clicks or inputs. Users can select or enter corresponding operation and maintenance parameters based on the corresponding components. Operation and maintenance parameters can include application names, production machine identifiers, and operation and maintenance task names.

[0075] In this operation and maintenance management interface, users can select automated operation and maintenance tools for configuration management, service application deployment and task orchestration, and enter the corresponding operation and maintenance job parameters. When there are multiple operation and maintenance task tasks, the number of automated operation and maintenance tools selected can be multiple, and the operation and maintenance job parameters required by the automated operation and maintenance tools can be entered separately.

[0076] Before executing an operation task, the operation script can be pre-compiled by relevant technicians and copied or stored in a preset entry directory. Different operation scripts are corresponding to different service applications. Each operation folder has a different name and contains a standardized startup script of the same name provided by the developer. This script is responsible for launching the entire operation and passing the necessary operation parameters, such as the target production machine group, login password, and environment variables used in the script.

[0077] Based on the operation and maintenance job name, the operation and maintenance job folder is retrieved from the portal directory. The script file for the operation and maintenance task and related script files required to execute the operation and maintenance task are retrieved from the retrieved operation and maintenance job folder. The target application service for the operation and maintenance task is determined based on the application name. The operation and maintenance production machine that executes the operation and maintenance task is determined based on the machine ID. The operation and maintenance task is then distributed to the operation and maintenance production machine, which executes the task to implement operation and maintenance management for the target service application.

[0078] The technical solution of the embodiment of the present invention obtains the operation and maintenance job parameters input by the user based on the operation and maintenance management interface, obtains the operation and maintenance job task according to the operation and maintenance job task name, determines the target service application according to the application name, and determines the operation and maintenance production machine according to the machine identifier, and sends the operation and maintenance job task to the operation and maintenance production machine, and the target service application of the operation and maintenance production machine executes the operation and maintenance job task, thereby realizing the automated deployment of the operation and maintenance job task, improving the deployment efficiency and deployment accuracy of the operation and maintenance job task, ensuring the execution consistency of each operation and maintenance job task, and reducing the errors and risks caused by manual operations.

[0079] It is understandable that, when deploying operation and maintenance tasks, in order to improve the efficiency of operation and maintenance task deployment, multiple operation and maintenance tasks can be deployed in the same time period. In an optional embodiment, after obtaining the operation and maintenance task according to the operation and maintenance task name, determining the target service application according to the application name, and determining the operation and maintenance production machine according to the machine identifier, it also includes: if there are multiple operation and maintenance tasks for the operation and maintenance production machine, obtaining the machine performance data of the operation and maintenance production machine; judging whether the operation and maintenance production machine is executing multiple operation and maintenance tasks simultaneously based on the machine performance data; if so, sending multiple operation and maintenance tasks to the operation and maintenance production machine at the same time, and having the operation and maintenance production machine execute multiple operation and maintenance tasks in parallel.

[0080] Among them, machine performance data may include at least one or more of CPU usage, CPU load, CPU temperature, memory usage, disk usage, I / O throughput, I / O latency, bandwidth usage, service response time, log error rate, and number of container restarts.

[0081] For any operation and maintenance production machine, if the operation and maintenance production machine has multiple operation and maintenance tasks at the same time, then based on the machine performance data of the operation and maintenance production machine, it is determined whether the operation and maintenance production machine is executing multiple operation and maintenance tasks at the same time. For example, if the CPU utilization, CPU load, CPU temperature, memory utilization, disk utilization, I / O throughput, I / O latency, and broadband utilization are all low, the service response time is short, the log error rate is low, and the number of container restarts is small, it can be evaluated to determine that the operation and maintenance production machine can execute at least two operation and maintenance tasks at the same time, and the number of operation and maintenance tasks that can be executed at the same time can be further evaluated based on the specific values ​​of the specific machine performance data. According to the number of operation and maintenance tasks obtained by the evaluation, the corresponding number of operation and maintenance tasks are simultaneously sent to the operation and maintenance production machine, and the operation and maintenance production machine executes multiple operation and maintenance tasks in parallel.

[0082] The above technical solution obtains the machine performance data of the operation and maintenance production machine when there are multiple operation and maintenance tasks for the operation and maintenance production machine, and determines based on the machine performance data that the operation and maintenance production machine executes multiple operation and maintenance tasks at the same time, and then sends multiple operation and maintenance tasks to the operation and maintenance production machine at the same time. The operation and maintenance production machine executes multiple operation and maintenance tasks in parallel, thereby realizing resource utilization of the operation and maintenance production machine, improving the execution efficiency of multiple operation and maintenance tasks, avoiding resource waste, and achieving improved operation and maintenance efficiency while improving resource utilization.

[0083] In an optional embodiment, after determining whether the operation and maintenance production machine executes multiple operation and maintenance tasks simultaneously based on the machine performance data, it also includes: if it is determined that the operation and maintenance production machine does not execute multiple operation and maintenance tasks simultaneously, determining the task attribute information corresponding to the multiple operation and maintenance tasks respectively; determining the task priorities corresponding to the multiple operation and maintenance tasks respectively based on the task attribute information corresponding to the multiple operation and maintenance tasks; and issuing the operation and maintenance tasks to the operation and maintenance production machine in sequence based on the task priorities corresponding to the multiple operation and maintenance tasks, and having the operation and maintenance production machine execute each operation and maintenance task in sequence.

[0084] If the machine performance data of the operation and maintenance production machine determines that the operation and maintenance production machine is unable to execute multiple production job tasks, such as high CPU usage, CPU load, CPU temperature, memory usage, disk usage, I / O throughput, I / O latency, and broadband usage, long service response time, high log error rate, and high number of container restarts, then it can be considered that the operation and maintenance production machine is unable to execute multiple production job tasks simultaneously.

[0085] When it is determined that the operation and maintenance production machine does not execute multiple operation and maintenance tasks simultaneously, task attribute information corresponding to each of the multiple operation and maintenance tasks is determined. The task attribute information may include the task type and the business or service to which the task belongs. For banking services, some task types and businesses or services have a higher degree of urgency. For example, payment or clearing services have a higher degree of urgency, while batch report tasks have a lower degree of urgency. Therefore, based on the task attribute information corresponding to each operation and maintenance task, the task priority corresponding to each operation and maintenance task can be determined. Operation and maintenance tasks with a higher degree of urgency are assigned a higher task priority, while operation and maintenance tasks with a lower degree of urgency are assigned a lower task priority.

[0086] According to the task priorities corresponding to each operation and maintenance task, the operation and maintenance task is sent to the operation and maintenance production machine in sequence. For example, the operation and maintenance task with a higher task priority is sent first and executed by the operation and maintenance production machine first. The operation and maintenance task with the lowest task priority is sent last and executed by the operation and maintenance production machine last.

[0087] The above technical solution determines the task attribute information corresponding to the multiple operation and maintenance tasks respectively when it is determined that the operation and maintenance production machine cannot execute multiple operation and maintenance tasks at the same time, and determines the task priorities corresponding to the multiple operation and maintenance tasks respectively based on the task attribute information corresponding to the multiple operation and maintenance tasks. According to the task priorities corresponding to the multiple operation and maintenance tasks, the operation and maintenance tasks are sent to the operation and maintenance production machine in sequence, thereby realizing the priority execution of urgent tasks when resources are tight, ensuring the execution efficiency of the operation and maintenance tasks with the greatest safety or impact value, and improving the stability and reliability of the operation and maintenance task execution process.

[0088] Example 3

[0089] Figure 3 This is a flow chart of a method for monitoring operation and maintenance tasks provided by embodiment 3 of the present invention. This embodiment provides a preferred example based on the above embodiments.

[0090] like Figure 3 As shown, the method includes the following specific steps:

[0091] S301. Acquire operation and maintenance parameters input by the user based on the operation and maintenance management interface; the operation and maintenance parameters include application name, production machine identifier, and operation and maintenance task name.

[0092] S302: Acquire the operation and maintenance task according to the operation and maintenance task name, determine the target service application according to the application name, and determine the operation and maintenance production machine according to the machine identifier.

[0093] S303: If there are multiple operation and maintenance tasks for the operation and maintenance production machine, obtain machine performance data of the operation and maintenance production machine.

[0094] S304. Determine, based on the machine performance data, whether the operation and maintenance production machine is executing multiple operation and maintenance tasks simultaneously; if so, execute S305A; if not, execute S305B-S305C.

[0095] S305A: Send multiple operation and maintenance tasks to the operation and maintenance production machine at the same time, and have the operation and maintenance production machine execute the multiple operation and maintenance tasks in parallel.

[0096] S305B, determining task attribute information corresponding to the plurality of operation and maintenance tasks, and determining task priorities corresponding to the plurality of operation and maintenance tasks according to the task attribute information corresponding to the plurality of operation and maintenance tasks;

[0097] S305C: According to the task priorities corresponding to the multiple operation and maintenance tasks, the operation and maintenance tasks are sequentially issued to the operation and maintenance production machine, and the operation and maintenance production machine executes each operation and maintenance task in sequence.

[0098] S306: Perform machine operation status detection on at least one operation and maintenance production machine in the process of executing the operation and maintenance task to obtain machine operation status data.

[0099] S307. Input the CPU load, memory usage, disk I / O and service application response time of the corresponding operation and maintenance production machine within the preset first time period into the pre-trained operation and maintenance task interruption probability prediction model to obtain the operation and maintenance task interruption probability of each operation and maintenance production machine output by the model.

[0100] S308: Based on the interruption probability of the operation and maintenance tasks of each operation and maintenance production machine, determine whether there is a target production machine that meets the preset interruption decision judgment condition. If so, execute S309A; if not, execute S309B.

[0101] S309A: Generate a target machine execution policy based on the operation and maintenance task interruption probability of the target production machine, and send the target machine execution policy to the target production machine, so that the target production machine executes the target machine execution policy.

[0102] S309B: Do not generate a machine execution policy.

[0103] Optionally, during the execution of operation and maintenance tasks, obtain the task execution logs of each operation and maintenance production machine during the execution of operation and maintenance tasks; perform keyword extraction on the task execution logs to obtain reference log keywords; determine whether there are abnormal production machines with abnormal operation and maintenance task execution based on the reference log keywords and preset abnormal log keywords; if so, generate an operation and maintenance task interruption strategy, and send the operation and maintenance task interruption strategy to the abnormal production machine, and the abnormal production machine executes the operation and maintenance task interruption strategy.

[0104] Example 4

[0105] Figure 4 This is a schematic diagram of the structure of an operation and maintenance task monitoring device provided in the fourth embodiment of the present invention. The operation and maintenance task monitoring device provided in the embodiment of the present invention can be applied to the situation where the bank-related system or service application performs automated operation and maintenance and abnormal monitoring of the operation and maintenance task execution process. The operation and maintenance task monitoring device can be implemented in the form of hardware and / or software, such as Figure 4 As shown, the device includes: an operation status detection module 401, an interruption probability determination module 402, a target machine judgment module 403 and an execution strategy delivery module 404.

[0106] The operation status detection module 401 is used to detect the operation status of at least one operation and maintenance production machine in the process of performing the operation and maintenance task, and obtain machine operation status data;

[0107] An interruption probability determination module 402 is configured to determine an interruption probability of the operation and maintenance task of each of the operation and maintenance production machines within a preset second time period based on the machine operation status data within a preset first time period;

[0108] The target machine determination module 403 is configured to determine whether there is a target production machine that meets a preset interruption decision judgment condition based on the operation and maintenance task interruption probability of each of the operation and maintenance production machines;

[0109] The execution strategy sending module 404 is used to generate a target machine execution strategy based on the operation and maintenance task interruption probability of the target production machine if it is determined that there is a target production machine that meets the preset interruption decision judgment conditions, and send the target machine execution strategy to the target production machine, so that the target production machine executes the target machine execution strategy.

[0110] The technical solution of the embodiment of the present invention obtains machine operating status data by detecting the machine operating status of at least one operation and maintenance production machine in the process of executing an operation and maintenance task. Based on the machine operating status data in a preset first time period, the operation and maintenance task interruption probability of each operation and maintenance production machine in a preset second time period is determined. Based on the operation and maintenance task interruption probability of each operation and maintenance production machine, when it is determined that there is a target production machine that meets the preset interruption decision judgment condition, the target machine execution strategy is generated based on the operation and maintenance task interruption probability of the target production machine, and the target machine execution strategy is sent to the target production machine. The above technical solution realizes the automated monitoring of the production machine in the process of executing the operation and maintenance task, so that the task interruption risk of the production machine in the future time period can be monitored in advance, and the risk of interruption or abnormality in the execution of the operation and maintenance task can be pre-monitored and evaluated, thereby improving the real-time prediction capability in the monitoring process of the operation and maintenance task.

[0111] Optionally, the machine operation status data includes central processing unit load, memory usage, disk input / output, and service application response time; accordingly, the interruption probability determination module 402 is specifically configured to:

[0112] Inputting the CPU load, memory usage, disk input / output, and service application response time of the corresponding operation and maintenance production machine within a preset first time period into a pre-trained operation and maintenance task interruption probability prediction model, and obtaining the operation and maintenance task interruption probability of each operation and maintenance production machine as output by the model;

[0113] The operation and maintenance task interruption probability prediction model is obtained by pre-training a preset network model based on the historical operating status data of the operation and maintenance production machine in the historical time period and its corresponding probability label data.

[0114] Optionally, the device further includes:

[0115] An execution log acquisition module is configured to acquire a task execution log of each operation and maintenance production machine in the process of executing the operation and maintenance task after detecting the machine operation status of at least one operation and maintenance production machine in the process of executing the operation and maintenance task;

[0116] A keyword extraction module, configured to extract keywords from the task execution log to obtain reference log keywords;

[0117] An abnormality judgment module is used to determine whether there is an abnormal production machine that performs an abnormal operation and maintenance task based on the reference log keywords and preset abnormality log keywords;

[0118] The interruption strategy generation module is used to generate an operation and maintenance task interruption strategy if it is determined that there is an abnormal production machine that performs an operation and maintenance task abnormally, and send the operation and maintenance task interruption strategy to the abnormal production machine, so that the abnormal production machine executes the operation and maintenance task interruption strategy.

[0119] Optionally, the device further includes:

[0120] An operation parameter acquisition module is configured to acquire operation and maintenance operation parameters input by a user based on an operation and maintenance management interface before performing machine operation status detection on at least one operation and maintenance production machine in the process of executing the operation and maintenance task and obtaining machine operation status data; the operation and maintenance operation parameters include an application name, a production machine identifier, and an operation and maintenance task name;

[0121] a target application determination module, configured to obtain an operation and maintenance task according to the operation and maintenance task name, determine a target service application according to the application name, and determine an operation and maintenance production machine according to the machine identifier;

[0122] The task issuing module is used to issue the operation and maintenance task to the operation and maintenance production machine, so that the target service application of the operation and maintenance production machine executes the operation and maintenance task.

[0123] Optionally, the device further includes:

[0124] a performance data acquisition module configured to, after acquiring the operation and maintenance task according to the operation and maintenance task name, determining the target service application according to the application name, and determining the operation and maintenance production machine according to the machine identifier, acquire machine performance data of the operation and maintenance production machine if there are multiple operation and maintenance tasks for the operation and maintenance production machine;

[0125] An operation and maintenance task determination module, configured to determine, based on the machine performance data, whether the operation and maintenance production machine is performing multiple operation and maintenance tasks simultaneously;

[0126] The multi-task sending module is used to send multiple operation and maintenance tasks to the operation and maintenance production machine at the same time if the operation and maintenance production machine executes multiple operation and maintenance tasks at the same time, and the operation and maintenance production machine executes multiple operation and maintenance tasks in parallel.

[0127] Optionally, the device further includes:

[0128] a task attribute determination module configured to, after determining whether the operation and maintenance production machine is simultaneously executing multiple operation and maintenance tasks based on the machine performance data, determine task attribute information corresponding to each of the multiple operation and maintenance tasks if it is determined that the operation and maintenance production machine is not simultaneously executing multiple operation and maintenance tasks;

[0129] A task priority determination module is used to determine the task priorities corresponding to the multiple operation and maintenance tasks according to the task attribute information corresponding to the multiple operation and maintenance tasks;

[0130] The task dispatching module is used to dispatch the operation and maintenance tasks to the operation and maintenance production machine in sequence according to the task priorities corresponding to multiple operation and maintenance tasks, and the operation and maintenance production machine executes each operation and maintenance task in sequence.

[0131] The operation and maintenance task monitoring device provided in the embodiment of the present invention can execute the operation and maintenance task monitoring method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0132] Example 5

[0133] Figure 5 A schematic diagram of the structure of an electronic device 50 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0134] like Figure 5As shown, the electronic device 50 includes at least one processor 51 and a memory, such as a read-only memory (ROM) 52, a random access memory (RAM) 53, etc., which is communicatively connected to the at least one processor 51. The memory stores a computer program that can be executed by the at least one processor. The processor 51 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 52 or the computer program loaded from the storage unit 58 into the random access memory (RAM) 53. Various programs and data required for the operation of the electronic device 50 can also be stored in the RAM 53. The processor 51, ROM 52, and RAM 53 are connected to each other via a bus 54. An input / output (I / O) interface 55 is also connected to the bus 54.

[0135] Multiple components in the electronic device 50 are connected to the I / O interface 55, including an input unit 56, such as a keyboard, a mouse, etc.; an output unit 57, such as various types of displays, speakers, etc.; a storage unit 58, such as a magnetic disk, an optical disk, etc.; and a communication unit 59, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 59 allows the electronic device 50 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0136] The processor 51 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 51 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors that run machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 51 executes the various methods and processes described above, such as the operation and maintenance task monitoring method.

[0137] In some embodiments, the operation and maintenance task monitoring method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 58. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 50 via the ROM 52 and / or the communication unit 59. When the computer program is loaded into the RAM 53 and executed by the processor 51, one or more steps of the operation and maintenance task monitoring method described above can be performed. Alternatively, in other embodiments, the processor 51 can be configured to execute the operation and maintenance task monitoring method in any other appropriate manner (for example, by means of firmware).

[0138] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0139] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0140] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0141] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0142] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0143] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0144] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0145] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for monitoring operation and maintenance tasks, characterized in that: include: Performing machine operation status detection on at least one operation and maintenance production machine during the execution of the operation and maintenance task to obtain machine operation status data; Determining, based on the machine operating status data within a preset first time period, a probability of interruption of the operation and maintenance tasks of each of the operation and maintenance production machines within a preset second time period; Determining whether there is a target production machine that meets a preset interruption decision judgment condition based on the interruption probability of the operation and maintenance task of each of the operation and maintenance production machines; If so, a target machine execution policy is generated according to the operation and maintenance task interruption probability of the target production machine, and the target machine execution policy is sent to the target production machine, and the target production machine executes the target machine execution policy.

2. The method according to claim 1, characterized in that The machine operation status data includes central processing unit load, memory usage, disk input / output, and service application response time; accordingly, determining the operation and maintenance task interruption probability of each of the operation and maintenance production machines within a preset second time period based on the machine operation status data within a preset first time period includes: Inputting the CPU load, memory usage, disk input / output, and service application response time of the corresponding operation and maintenance production machine within a preset first time period into a pre-trained operation and maintenance task interruption probability prediction model, and obtaining the operation and maintenance task interruption probability of each operation and maintenance production machine as output by the model; The operation and maintenance task interruption probability prediction model is obtained by pre-training a preset network model based on the historical operating status data of the operation and maintenance production machine in the historical time period and its corresponding probability label data.

3. The method according to claim 1, characterized in that After detecting the machine operating status of at least one operation and maintenance production machine in the process of performing the operation and maintenance task, the method further includes: Obtaining task execution logs of each of the operation and maintenance production machines during the execution of the operation and maintenance task; Extracting keywords from the task execution log to obtain reference log keywords; Determine whether there is an abnormal production machine that performs an abnormal operation and maintenance task based on the reference log keywords and the preset abnormal log keywords; If so, an operation and maintenance task interruption strategy is generated and sent to the abnormal production machine, so that the abnormal production machine executes the operation and maintenance task interruption strategy.

4. The method according to claim 1, wherein Before detecting the operation status of at least one operation and maintenance production machine in the process of performing the operation and maintenance task to obtain the machine operation status data, the method further includes: Obtaining operation and maintenance parameters input by the user based on the operation and maintenance management interface; the operation and maintenance parameters include application name, production machine identifier and operation and maintenance task name; Acquire the operation and maintenance task according to the operation and maintenance task name, determine the target service application according to the application name, and determine the operation and maintenance production machine according to the machine identifier; The operation and maintenance task is sent to the operation and maintenance production machine, and the target service application of the operation and maintenance production machine executes the operation and maintenance task.

5. The method according to claim 4, characterized in that After acquiring the operation and maintenance task according to the operation and maintenance task name, determining the target service application according to the application name, and determining the operation and maintenance production machine according to the machine identifier, the method further includes: If there are multiple operation and maintenance tasks for the operation and maintenance production machine, obtaining machine performance data of the operation and maintenance production machine; Determining, based on the machine performance data, whether the operation and maintenance production machine is performing multiple operation and maintenance tasks simultaneously; If so, multiple operation and maintenance tasks are sent to the operation and maintenance production machine at the same time, and the operation and maintenance production machine executes the multiple operation and maintenance tasks in parallel.

6. The method according to claim 5, characterized in that After determining, based on the machine performance data, whether the operation and maintenance production machine is simultaneously executing multiple operation and maintenance tasks, the method further includes: If it is determined that the operation and maintenance production machine does not execute multiple operation and maintenance tasks simultaneously, then determining the task attribute information corresponding to the multiple operation and maintenance tasks respectively; Determine the task priorities corresponding to the multiple operation and maintenance tasks according to the task attribute information corresponding to the multiple operation and maintenance tasks; According to the task priorities corresponding to the multiple operation and maintenance tasks, the operation and maintenance tasks are sent to the operation and maintenance production machine in sequence, and the operation and maintenance production machine executes each operation and maintenance task in sequence.

7. An operation and maintenance task monitoring device, characterized in that: include: An operation status detection module is used to detect the operation status of at least one operation and maintenance production machine in the process of performing an operation and maintenance task, and obtain machine operation status data; An interruption probability determination module, configured to determine an interruption probability of the operation and maintenance task of each of the operation and maintenance production machines within a preset second time period based on the machine operation status data within a preset first time period; A target machine determination module is used to determine whether there is a target production machine that meets a preset interruption decision judgment condition based on the operation and maintenance task interruption probability of each of the operation and maintenance production machines; The execution strategy sending module is used to generate a target machine execution strategy based on the operation and maintenance task interruption probability of the target production machine if it is determined that there is a target production machine that meets the preset interruption decision judgment conditions, and send the target machine execution strategy to the target production machine, so that the target production machine executes the target machine execution strategy.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the operation and maintenance task monitoring method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the operation and maintenance task monitoring method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the operation and maintenance task monitoring method according to any one of claims 1 to 6.

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