Prearranged processing method, prearranged processing device, electronic equipment and readable storage medium

Abstract

The application discloses a preplan processing method, a preplan processing device, an electronic device and a readable storage medium. The method comprises the following steps: in the case that a target preplan meets a drill condition, controlling a target system to execute an operation in the target preplan to perform a current round of drill of the target preplan; after the target system executes the operation in the target preplan, obtaining drill related data corresponding to the target preplan; and based on the drill related data, evaluating the drill effect of the target preplan in the current round to obtain a drill evaluation result of the target preplan in the current round. In this way, the application can realize automatic and intelligent closed-loop processing of the complete process of preplan drill, from triggering, execution, data collection to effect evaluation, thereby ensuring the execution efficiency of preplan drill processing. Compared with the traditional manual mode, the operation and maintenance personnel do not need to intervene in the starting, execution, data collection and evaluation of the drill, thereby improving the execution efficiency of the preplan drill.

Description

Technical Field

[0001] This application relates to the field of software system contingency plan management technology, specifically to a contingency plan processing method, contingency plan processing device, electronic device, and computer-readable storage medium. Background Technology

[0002] The relevant plan requires staff to manually conduct drills of the contingency plan and evaluate its effectiveness. However, since the drills need to be manually triggered and executed step by step, the whole process is inefficient and it is difficult to complete the drills within a limited time. As a result, the effectiveness of the contingency plan cannot be verified and guaranteed in a timely manner. Consequently, when an actual fault occurs, the system's ability to respond to the actual fault is affected because the contingency plan has not been fully drilled. Summary of the Invention

[0003] This application provides a contingency plan processing method, contingency plan processing device, electronic device, and computer-readable storage medium. Under the condition of meeting the preset exercise conditions, the current round of exercise of the target contingency plan is automatically triggered, and exercise-related data is collected after the exercise is executed. The exercise effect is evaluated based on the exercise-related data, thereby realizing the automated initiation and quantitative evaluation of the effect of the contingency plan exercise.

[0004] On the one hand, embodiments of this application provide a contingency plan processing method, the method comprising:

[0005] In response to meeting the exercise conditions of the target plan, the target system is controlled to execute the operation in the target plan to conduct the current round of exercise of the target plan, wherein the exercise conditions include the time difference from the previous round of the current round being greater than or equal to the exercise time interval corresponding to the target plan;

[0006] After the target system executes the operation in the target plan, exercise-related data corresponding to the target plan is obtained. The exercise-related data includes first related data, second related data, and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running according to the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round.

[0007] Based on the exercise-related data, the effectiveness of the target plan in the current round of exercises is evaluated, and the evaluation result of the target plan in the current round of exercises is obtained.

[0008] On the other hand, embodiments of this application provide a plan processing device, the device comprising:

[0009] The control module is used to control the target system to execute the operation in the target plan in response to the exercise conditions of the target plan, so as to carry out the current round of exercise of the target plan, wherein the exercise conditions include the time difference from the previous round to the current round being greater than or equal to the exercise time interval corresponding to the target plan.

[0010] The acquisition module is used to acquire exercise-related data corresponding to the target plan after the target system executes the operation in the target plan. The exercise-related data includes first related data, second related data, and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round.

[0011] The evaluation module is used to evaluate the effectiveness of the target plan in the current round of the exercise based on the exercise-related data, and obtain the exercise evaluation result of the target plan in the current round.

[0012] On the other hand, embodiments of this application provide an electronic device, which includes a processor and a memory. The memory stores a computer program, and the processor executes the pre-processing method as described in any of the above embodiments by calling the computer program stored in the memory.

[0013] On the other hand, embodiments of this application provide a computer-readable storage medium storing a computer program adapted for loading by a processor to execute the pre-processing method as described in any of the above embodiments.

[0014] On the other hand, embodiments of this application provide a computer program product, including computer instructions, which, when executed by a processor, implement the pre-processing method as described in any of the above embodiments.

[0015] The contingency plan processing method, device, computer-readable storage medium, electronic device, and computer program product provided in this application can automatically control the target system to execute operations in the target contingency plan to conduct the current round of exercise in response to the exercise conditions of the target contingency plan. After the exercise is completed, it automatically acquires exercise-related data, including first relevant data indicating the current round of operation status of the target system, second relevant data indicating the target system's operating environment, and historical exercise evaluation results including past exercise situations. Based on the exercise-related data, it evaluates the exercise effect of the current round and obtains the exercise evaluation result corresponding to the target contingency plan. This realizes the automated and intelligent closed-loop processing of the entire process of contingency plan exercise from triggering, execution, data collection to effect evaluation, thereby ensuring the execution efficiency of contingency plan exercise processing. Moreover, compared with the traditional method of relying on manual judgment of exercise timing, manual execution of exercise steps, and collection of scattered data afterward and subjective judgment based on experience, it eliminates the need for operation and maintenance personnel to intervene in the initiation, execution, data collection, and evaluation of the exercise, thereby improving the execution efficiency of contingency plan exercise to a certain extent. Furthermore, evaluating the effectiveness of the exercise based on relevant data ensures that the evaluation results are well-supported by data, avoiding biases caused by subjective human judgment and improving the credibility and objectivity of the evaluation results to a certain extent. In addition, the automated and intelligent closed-loop processing of the contingency plan exercises allows for timely verification of the adaptability and effectiveness of the target contingency plan, providing a reliable basis for subsequent optimization and adjustment of the plan. This, to a certain extent, improves the stability and fault recovery capabilities of the software system, thereby ensuring the plan's ability to respond to actual faults. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the pre-processing method provided in the embodiments of this application.

[0018] Figure 2 This is a flowchart illustrating the pre-processing method provided in the embodiments of this application.

[0019] Figure 3 This is a schematic diagram illustrating the entire process of automated evaluation and triggering of contingency plan exercises provided in the embodiments of this application.

[0020] Figure 4(a) is a schematic diagram of the entire process of the pre-plan processing method provided in the embodiment of this application.

[0021] Figure 4(b) is a schematic diagram of the entire process of the pre-plan processing method provided in the embodiment of this application.

[0022] Figure 5 This is a schematic diagram of the effectiveness scoring data of the contingency plan provided in the embodiments of this application.

[0023] Figure 6 This is a schematic diagram of the pre-processing device provided in an embodiment of this application.

[0024] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] This application provides a contingency plan processing method, a contingency plan processing device, an electronic device, and a computer-readable storage medium. Specifically, the contingency plan processing method of this application can be executed by an electronic device, which can be a terminal or a server. The terminal can be a smartphone, tablet, laptop, smart TV, wearable smart device, smart vehicle terminal, etc. The terminal can also include a client, which can be a browser client, instant messaging client, or mini-program, etc. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery network (CDN), and big data and artificial intelligence platforms.

[0027] It should be noted that, in this embodiment of the application, the executing entity of the contingency plan processing method can be a terminal device or a server. The terminal device can be a local terminal device or a client device in a cloud platform. This embodiment of the application does not limit the type of executing entity.

[0028] For example, when this pre-programmed processing method is run on a terminal device, the terminal device may include a display screen and a processor. The display screen is used to present a graphical user interface (GUI) and receive instructions generated by the user interacting with the GUI. The processor is used to store applications, generate the GUI, respond to instructions, and control the display of the GUI on the display screen. When the user operates the GUI through the display screen, the GUI can control the local content of the terminal device in response to the received operation instructions. The terminal device can provide the GUI to the user in various ways, such as rendering it on the terminal device's display screen or presenting the GUI through holographic projection.

[0029] For example, when the contingency plan processing method runs on a server, it can be implemented and executed based on a cloud system. The cloud system includes servers and client devices. The application's runtime and the graphical user interface (GUI) presentation are separate. The storage and execution of the contingency plan processing method are completed on the server, while the GUI presentation is completed on the client. The client is mainly used for data reception, transmission, and GUI presentation. For example, the client can be a display device with data transmission capabilities located close to the user, such as a mobile terminal, television, computer, PDA, personal digital assistant, or head-mounted display device. However, the terminal device for data processing is the server in the cloud. During execution, the user operates the client to send instructions to the server. The server executes the instructions, encodes and compresses the GUI data, returns it to the client via the network, and finally, the client decodes and outputs the GUI.

[0030] It should be noted that, in this embodiment, the executing entity of the contingency plan processing method can be a terminal device or a server. The terminal device can be a local terminal device or a client device in the aforementioned cloud system. This embodiment does not limit the type of executing entity.

[0031] The technical solution of this application will be described in detail below through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0032] As software systems grow in scale and business logic becomes increasingly complex, the risks of failures during software system operation also gradually increase. For example, service interruptions, data delays, and interface anomalies can all affect the stable operation of the software system.

[0033] Contingency plans, as fault response schemes planned in advance by technical personnel, can guide the software system to return to normal when a fault occurs. Therefore, effective management and regular drills of contingency plans are important aspects of software system operation and maintenance.

[0034] Some solutions utilize a contingency plan management platform to manage basic technical contingency plans. This platform involves manual contingency plan drills, with the results recorded on the platform for both drill and tracking. However, this reliance on manual drills and updates makes it difficult to guarantee the timeliness of drills. Furthermore, some contingency plans may become unsuitable for dynamic changes in the system environment due to a lack of long-term drills, thus failing to fulfill their intended purpose when actual faults occur.

[0035] Furthermore, during the contingency plan drills, maintenance personnel need to carry out the drill operations one by one, which requires them to spend a lot of time and energy to complete the drill tasks. This makes it impossible to fully verify the effectiveness of all contingency plans, make it difficult to grasp the actual status of each contingency plan in a timely manner, and affect the overall efficiency of contingency plan management.

[0036] In addition, manual recording of exercise results is prone to problems such as data omissions and recording errors, resulting in a lack of accurate data support for tracking and evaluating the exercise effect. This affects the pertinence and effectiveness of plan optimization, makes it impossible to meet the needs of large-scale plan corruption control, and makes it difficult to guarantee the software system's ability to cope with failure scenarios.

[0037] For the above issues, please refer to Figure 1 , Figure 1 This is a flowchart illustrating the pre-processing method provided in an embodiment of this application. It should be noted that the steps shown may be executed in a logical order different from that shown in the flowchart. The method includes:

[0038] 110: Under the condition that the exercise conditions of the target plan are met, control the target system to execute the operation in the target plan in order to carry out the current round of exercise of the target plan. The exercise conditions include that the time difference between the current round and the previous round is greater than or equal to the exercise time interval corresponding to the target plan.

[0039] 120: After the target system executes the operation in the target plan, acquire the exercise-related data corresponding to the target plan. The exercise-related data includes first related data, second related data, and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running according to the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round.

[0040] 130: Based on the relevant data from the exercise, evaluate the effectiveness of the target plan in the current round of the exercise and obtain the evaluation results of the target plan in the current round of the exercise.

[0041] Specifically, in contingency plan drills, the reliance on manual decisions regarding drill time and selection of drill plans lacks an automated triggering mechanism. This results in extremely low efficiency for manual execution when large-scale drills are required, making it difficult to quickly complete the verification of all plans. Furthermore, the lack of a standardized evaluation process for drill effectiveness makes it impossible to accurately assess the effectiveness of the plans, thereby affecting the software system's ability to respond to actual failures. Based on the above problems, this application provides a contingency plan processing method that can automatically trigger the current round of drills for a target contingency plan in response to the fulfillment of the drill conditions. After the drill is executed, relevant data is collected, and the drill effectiveness is evaluated based on the relevant data, thereby achieving automated initiation and quantitative evaluation of the effectiveness of contingency plan drills.

[0042] In some embodiments, a target contingency plan can be understood as a standardized handling plan developed in advance by maintenance personnel in a software system to address various potential faults in the software system, guiding the response actions when a software system fault occurs. Examples include adjusting application service configurations through a configuration center or adjusting service channels through a gateway.

[0043] In some embodiments, the operations in the target plan can be understood as a series of specific technical actions and execution steps that are pre-planned in the target plan and can be automatically executed by the target system in response to potential problems specific to the software system.

[0044] In some examples, the actions in the target contingency plan include adjusting application service configuration. Specifically, when performance bottlenecks or service call failures occur in the target system due to unreasonable initial configuration parameters of application services, such as an excessively small connection pool or too short a timeout, the application service configuration can be adjusted. This can be done by modifying the core configuration parameters of the target application service, such as the database connection pool size, API call timeout, and system concurrency threshold.

[0045] In some examples, the operations in the target contingency plan include adjusting the service channel configuration of the service gateway. Specifically, when a service channel in the target system fails to access services due to node failure or network fluctuations, the service gateway can adjust the service channel configuration. For example, the service gateway component can route access requests for the target service from the failed / offline channel to a backup healthy channel, or adjust the traffic allocation ratio of each channel according to the contingency plan requirements, or temporarily close the access entry of the failed channel, thereby achieving dynamic adjustment of the service channel.

[0046] In one example, the operations in the target contingency plan include a core database master-slave switchover operation. Specifically, when the target system experiences hardware failure, service downtime, or abnormal data read / write operations on the database master node, a core database master-slave switchover operation can be performed. This involves seamlessly switching the target system's data read / write operations from the failed master node to the standby slave node, synchronously updating the database connection configurations of all related application services, and verifying the consistency and normality of data read / write operations after the switchover, thereby ensuring the normal response of the database node.

[0047] In some embodiments, a target system can be understood as a software system that has deployed a target contingency plan and needs to verify the effectiveness of the plan through drills.

[0048] In some embodiments, the current round of drills can be understood as a drill process initiated after the preset drill conditions are met, targeting a contingency plan.

[0049] In some embodiments, the previous round can be understood as the most recent exercise of the target plan that has been fully executed before the current round of exercise.

[0050] In some embodiments, the exercise time interval can be understood as the time span between two adjacent effective exercises, pre-set for the target plan. The setting of the exercise time interval can take into account factors such as the importance of the target plan, the applicable scenarios, and the frequency of changes.

[0051] In some embodiments, exercise-related data can be understood as a collection of various data collected by electronic devices during and after the exercise to evaluate the effectiveness of the exercise.

[0052] In some embodiments, the first relevant data can be understood as various types of information that can reflect the operating status of the target system during the current round of exercises, including operation execution status, system response parameters, etc.

[0053] In some embodiments, the second relevant data can be understood as information about the operating environment in which the target system operates under the target plan, including hardware configuration, software version, network status, etc.

[0054] In some embodiments, historical exercise evaluation results can be understood as comprehensive evaluation results and data records formed after at least one target plan exercise prior to the current round of exercise, including information such as exercise scores and problem records from previous rounds.

[0055] In some embodiments, the exercise evaluation result can be understood as a comprehensive evaluation of the effectiveness of the current round of exercises based on the collected exercise-related data and through a preset evaluation logic.

[0056] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0057] The electronic equipment will continuously monitor the exercise status of the target plan, calculate the time difference between the current time and the completion time of the previous round of exercise in real time, and compare it with the preset exercise time interval.

[0058] When the detected time difference is greater than or equal to the exercise time interval, i.e. the exercise conditions are met, the electronic equipment can respond to the satisfaction of the exercise conditions, automatically start the current round of exercise process, send an exercise execution signal to the target system, and control the target system to execute various operations step by step according to the preset operation steps, execution order and related parameters in the target plan, simulating the application process of the plan in actual fault scenarios.

[0059] After the target system has completed all the operations in the target plan, the electronic equipment automatically acquires the exercise-related data corresponding to the target plan.

[0060] Subsequently, the electronic equipment will comprehensively evaluate the effectiveness of the target plan in the current round of exercise based on the collected first relevant data, second relevant data, and historical exercise evaluation results, using a preset evaluation algorithm. The final exercise evaluation result reflects the performance of the target plan in the current round of exercise and the effectiveness of the plan itself.

[0061] Thus, in this embodiment, in response to meeting the exercise conditions of the target plan, the target system can be automatically controlled to execute the operations in the target plan to carry out the current round of exercise. After the exercise is completed, the system automatically acquires exercise-related data, including first relevant data indicating the current round's operating status of the target system, second relevant data indicating the target system's operating environment, and historical exercise evaluation results including past exercise situations. Based on the exercise-related data, the exercise effect of the current round is evaluated to obtain the exercise evaluation result corresponding to the target plan. This achieves automated and intelligent closed-loop processing of the entire process of the contingency plan exercise from triggering, execution, data collection to effect evaluation, thereby ensuring the execution efficiency of the contingency plan exercise processing. Moreover, compared with the traditional method of relying on manual judgment of exercise timing, manual execution of exercise steps, and collection of scattered data afterward and subjective judgment based on experience, this method eliminates the need for operation and maintenance personnel to intervene in the initiation, execution, data collection, and evaluation of the exercise, thereby improving the execution efficiency of the contingency plan exercise to a certain extent. Furthermore, evaluating the effectiveness of the exercise based on relevant data ensures that the evaluation results are well-supported by data, avoiding biases caused by subjective human judgment and improving the credibility and objectivity of the evaluation results to a certain extent. In addition, the automated and intelligent closed-loop processing of the contingency plan exercises allows for timely verification of the adaptability and effectiveness of the target contingency plan, providing a reliable basis for subsequent optimization and adjustment of the plan. This, to a certain extent, improves the stability and fault recovery capabilities of the software system, thereby ensuring the plan's ability to respond to actual faults.

[0062] In some embodiments provided in this application, the target plan is one of a plurality of executable plans, each executable plan corresponding to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable plan corresponding to the fault type of the detected fault. Therefore, step 110 above includes:

[0063] Under the condition that the exercise conditions of the target plan are met, the target system is subjected to fault injection processing according to the fault type corresponding to the target plan. After the fault injection processing is performed on the target system, the target system detects the fault type corresponding to the target plan.

[0064] Specifically, during contingency plan drills, the drill scenarios lack correlation with actual fault scenarios. Simply executing the contingency plan operations cannot realistically simulate the system state when an actual fault occurs, resulting in the drill's effectiveness failing to accurately reflect the contingency plan's response capability in practical applications, and the plan's practicality cannot be effectively verified. Based on the above problems, in some embodiments provided in this application, each executable contingency plan is associated with a specific fault type. When the drill is triggered based on the drill conditions, fault injection processing is performed on the target system according to the fault type corresponding to the target contingency plan. This allows the target system to detect the corresponding fault type, simulating a real fault scenario for the drill, thus improving the realism and relevance of the drill.

[0065] In some embodiments, an executable contingency plan can be understood as a set of contingency plans pre-configured in the software system that can cope with different fault scenarios, and each executable contingency plan corresponds to at least one type of fault that may occur in the target system.

[0066] In some embodiments, fault types can be understood as various categories of problems that cause abnormal operation of the target system, including service interruption, data delay, interface response timeout, database connection failure, excessive resource consumption, and other problems that may affect the stable operation of the system. Each fault type has clear manifestation characteristics and scope of impact.

[0067] In some embodiments, fault injection processing can be understood as using professional technical means to simulate and generate fault phenomena of the fault type corresponding to the target plan in the target system, so that the target system presents the abnormal state corresponding to the fault type of the target plan, thereby simulating the operation of real fault scenarios.

[0068] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0069] Electronic devices store multiple executable plans, each of which is associated with at least one type of fault through preset rules. These preset rules can be determined based on the technical characteristics, scope of impact, and response logic of the fault, thereby improving the matching degree between the fault and the plan to a certain extent.

[0070] During the operation of the target system, the system's operating status is monitored in real time. When a certain type of fault is detected, the system will automatically call and execute the operation in the executable plan corresponding to the fault type to eliminate the impact of the fault and restore the normal operation of the system.

[0071] If the conditions for the exercise are met, the electronic equipment first queries and determines the specific fault type corresponding to the target plan, and determines the fault category and characteristics targeted by the target plan.

[0072] Subsequently, based on the technical manifestations and impact mechanisms of the fault type, the electronic device uses appropriate fault injection techniques to simulate faults in the target system. For example, if the fault type is data delay, the target system can be made to exhibit an abnormal state of slow data transmission by adding delay nodes to the data transmission link or limiting data transmission bandwidth. If the fault type is interface response timeout, the fault scenario can be simulated by blocking the interface service process or simulating interface server crashes.

[0073] Through fault injection processing, the target system can accurately detect the fault type corresponding to the target contingency plan, and at this time the state of the target system is consistent with that when the actual fault occurs.

[0074] Then, the electronic equipment controls the target system to perform various operations according to the preset operation steps, execution sequence and parameter requirements in the target plan, fully simulating the execution process of the plan under real fault scenarios, and ensuring that the exercise process is highly consistent with the actual fault handling process.

[0075] Thus, in this embodiment, when the exercise conditions are met, the target system is first injected with faults according to the fault type corresponding to the target plan. After the target system detects the fault type, it is then controlled to execute the operations in the target plan to carry out the current round of exercise. This achieves automated exercise of the plan under real fault scenarios. Compared with the exercise method that only controls the target system to execute the plan operations without building a real fault environment, the exercise scenario is consistent with the system state when the actual fault occurs. This allows for a more realistic test of the execution effect and adaptability of the plan in actual application. To a certain extent, it avoids problems such as the mismatch between the plan and the fault type and the incompatibility of the operation steps that cannot be detected in the exercise in the fault-free scenario. Moreover, the exercise based on the real fault scenario can obtain more realistic exercise data, providing a more reliable basis for the subsequent exercise effect evaluation. This makes the evaluation results more reflective of the real effectiveness of the plan, and to a certain extent, it provides a clear direction for the optimization and adjustment of the plan, improving the reliability and practicality of the plan in actual fault handling.

[0076] In some embodiments provided in this application, the target plan includes at least one operation, and the method further includes:

[0077] After the target system executes each operation in the target plan, the target system is subjected to fault recovery processing according to the fault type corresponding to the target plan. After the target system is subjected to fault recovery processing, the target system cannot detect the fault type corresponding to the target plan.

[0078] Specifically, after the exercise of the target plan is completed, the injected fault may still remain in the target system, which will continue to affect the normal operation of the target system, and may even prevent other subsequent exercises from being carried out normally, or affect the actual business processing of the target system, reducing the security and flexibility of the exercise. Based on the above problems, in some embodiments provided in this application, after the target system has executed each operation in the target plan, the target system is subjected to fault recovery processing according to the fault type corresponding to the target plan, the injected fault is eliminated, and the target system is restored to normal state.

[0079] In some embodiments, fault recovery processing can be understood as the reverse operation corresponding to fault injection processing. It refers to the process of eliminating the fault previously injected into the target system by using specific technical means after the target system has completed a certain operation in the plan, so as to restore the target system to a normal state.

[0080] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0081] The target contingency plan, as a solution to deal with a specific type of failure, includes at least one logically coherent and progressively stepping operation, which together constitute a complete failure handling process.

[0082] If the fault injection process has been completed according to the fault type corresponding to the target plan, and the target system has successfully detected the corresponding fault type, the electronic device controls the target system to perform the first operation in the order preset by the target plan.

[0083] After the first operation is completed, the electronic device immediately uses the opposite technical logic to eliminate the fault. For example, if the injected fault is a service interruption, the fault recovery restores the service to normal by restarting the service process and restoring the network connection. If the injected fault is a data delay, the fault recovery eliminates the delay by clearing the delay nodes in the data transmission link and restoring normal bandwidth.

[0084] After the fault recovery process is completed, the electronic equipment will detect the status of the target system and confirm that the target system can no longer detect the fault type corresponding to the target plan, ensuring that the fault impact caused by the current operation has been eliminated.

[0085] Subsequently, the electronic device controls the target system to execute the next operation in the plan. After the operation is completed, the above fault recovery process is repeated until all operations in the target plan have been executed.

[0086] Thus, in this embodiment of the application, after the target system executes each operation in the target plan, the target system is subjected to fault recovery processing according to the fault type corresponding to the target plan. This achieves independent drills and fault clearing loops for each operation link. Compared with the mode where faults persist until the end of the drill after injection, it can effectively isolate fault interference between each operation step, avoid the impact of residual faults from previous operations on the execution effect of subsequent operations, and to a certain extent ensure the safety and controllability of the drill process.

[0087] Furthermore, the effective recovery of faults after each operation allows the execution effect of each operation to be evaluated independently, which to some extent avoids the distortion of exercise results caused by the superposition of faults. This enables the exercise data to reflect the real performance of individual operations, providing a reliable basis for optimizing specific operation steps in the contingency plan. In turn, this improves the overall executability and effectiveness of the contingency plan to a certain extent, ensuring that each operation step of the target system can play its expected role in actual fault handling.

[0088] In some embodiments provided in this application, the method further includes:

[0089] Update or maintain the exercise interval based on the exercise evaluation results.

[0090] Specifically, during contingency plan drills, the drill intervals are fixed and cannot be dynamically adjusted based on the actual drill results. However, for contingency plans with good drill results and high stability, fixed intervals may lead to over-drilling and wasted resources. For contingency plans with poor drill results and problems, fixed intervals may lead to untimely drills, making it impossible to identify and resolve problems in a timely manner, thus affecting the effectiveness of the contingency plan. Based on the above problems, in some embodiments provided in this application, the evaluation results of the current round of drills are correlated with the drill intervals. The original drill intervals are dynamically updated or maintained based on the drill evaluation results, so that the drill cycle matches the actual effect of the contingency plan, thereby improving the flexibility of contingency plan management and resource utilization.

[0091] In some embodiments, an update can be understood as adjusting the original exercise time interval based on the exercise evaluation results, including increasing or decreasing the time span.

[0092] In some embodiments, "maintain" can be understood as keeping the original exercise time interval unchanged if the exercise evaluation results meet expectations.

[0093] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0094] After obtaining the evaluation results of the current round of exercises, the electronic equipment analyzes the evaluation results of the current round of exercises, determines the current effectiveness of the contingency plan, and adjusts the exercise time interval of the contingency plan.

[0095] For example, if the evaluation results show that the contingency plan drills are effective and the plan is highly effective and stable, the electronic equipment will automatically increase the drill interval of the target plan and reduce the drill frequency to avoid wasting resources. If the evaluation results are basically in line with the preset standards, it indicates that the plan is stable, and the electronic equipment will maintain the original drill interval of the target plan. If the evaluation results show that the plan has problems such as execution lag, inadequate fault response, and insufficient adaptability, it indicates that the plan needs to be further verified. The electronic equipment will automatically reduce the drill interval of the target plan and increase the drill frequency in order to promptly identify problems in the plan and make optimizations and adjustments.

[0096] Thus, in this embodiment of the application, the exercise time interval corresponding to the target plan is updated or maintained according to the exercise evaluation results, thereby realizing the dynamic adaptation of the exercise time interval. Compared with the exercise mode where the exercise time interval is fixed, the exercise time interval can match the actual effectiveness of the target plan, which improves the pertinence and effectiveness of the exercise to a certain extent, and allows exercise resources to be tilted towards high-demand plans, thereby improving resource utilization efficiency.

[0097] In some embodiments provided in this application, the exercise evaluation result is one of several preset evaluation results. Updating or maintaining the exercise time interval based on the exercise evaluation result includes one of the following steps:

[0098] When the exercise evaluation result is the first preset evaluation result among multiple preset evaluation results, increase the exercise time interval;

[0099] When the exercise evaluation result is the second preset evaluation result among multiple preset evaluation results, the exercise time interval remains unchanged;

[0100] When the exercise evaluation result is the third preset evaluation result among multiple preset evaluation results, reduce the exercise time interval.

[0101] Specifically, when adjusting the exercise time interval, there is a lack of unified adjustment rules and standards, and the adjustment methods corresponding to different exercise evaluation results are unclear. This leads to strong subjectivity in the adjustment operation, making it difficult to ensure the consistency and rationality of the adjustment, and making it impossible to accurately match the exercise time interval with the contingency plan effect. Based on the above problems, in some embodiments provided in this application, multiple evaluation result categories are preset, and the exercise time interval adjustment strategy corresponding to each evaluation result category is determined, making the adjustment operation more standardized and operable.

[0102] In some embodiments, multiple preset evaluation results can be understood as several fixed evaluation categories pre-divided according to the quality of the exercise effect, used to distinguish different levels of exercise performance and provide a basis for adjusting the exercise time interval.

[0103] In some embodiments, the first preset evaluation result can be understood as the evaluation category with the best corresponding exercise effect among multiple preset evaluation results, indicating that the target plan is executed smoothly, the fault response efficiency is high, and the adaptability is excellent.

[0104] In some embodiments, the second preset evaluation result can be understood as the evaluation category in which the corresponding exercise effect meets expectations, indicating that the performance of the target plan meets the standards and there are no obvious defects.

[0105] In some embodiments, the third preset evaluation result can be understood as the evaluation category corresponding to poor exercise performance, indicating that the target plan has execution problems, insufficient adaptability, or failure response capability does not meet the standard.

[0106] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0107] After generating the exercise evaluation results for the current round, the electronic equipment compares these results with preset evaluation criteria to determine the category to which the evaluation results belong. For example, the electronic equipment pre-sets quantitative scoring thresholds: 90 points and above is the first preset evaluation result, 75 to 89 points is the second preset evaluation result, and 74 points and below is the third preset evaluation result. The electronic equipment analyzes the score range to which the exercise evaluation results belong and executes the corresponding exercise time interval adjustment operation.

[0108] If the evaluation results meet the first preset evaluation criteria, it indicates that the target plan is highly stable and effective. The electronic equipment will automatically execute the increased operation, extending the exercise interval by a preset amount. For example, the exercise interval can be extended to 1.5 times the original exercise interval, reducing the number of exercises and saving resources.

[0109] If the evaluation results meet the judgment criteria of the second preset evaluation results, it indicates that the target plan has met the standards and is in a stable state, and the electronic equipment maintains the original exercise time interval.

[0110] If the evaluation result falls within the scope of the third preset evaluation result, it indicates that there is room for improvement in the target plan. The electronic equipment will automatically perform a reduction operation, shortening the exercise interval by a preset amount. For example, the exercise interval can be shortened to 0.8 or 0.5 times the original exercise interval, increasing the exercise frequency of the plan in order to verify the optimization effect of the target plan in a timely manner.

[0111] In some instances, the specific adjustment range of the exercise time interval can be pre-set based on the characteristics of the target plan.

[0112] After the adjustment is completed, the electronic equipment will store the new exercise time interval as the effective interval of the corresponding target plan, which will be used for triggering judgment in subsequent exercises.

[0113] Thus, in this embodiment, when the evaluation result is the first preset evaluation result, the exercise time interval is increased; when the evaluation result is the second preset evaluation result, the original interval is maintained; and when the evaluation result is the third preset evaluation result, the exercise time interval is decreased. This achieves standardized dynamic adjustment of the exercise time interval. Compared with the mode that lacks unified adjustment rules and relies on subjective human judgment of the interval adjustment range, it avoids the situation where different personnel make different adjustment decisions for the same evaluation result. This ensures the consistency and standardization of adjustment operations to a certain extent, enhances the matching degree between the exercise time interval and the actual effect of the plan, and effectively improves resource utilization efficiency.

[0114] In some embodiments provided in this application, please refer to Figure 2 , Figure 2This is a flowchart illustrating the pre-processing method provided in an embodiment of this application. It should be noted that the steps shown may be executed in a logical order different from that shown in the flowchart. Step 130 includes:

[0115] 131: Based on the first relevant data, generate the first exercise score of the target plan in the current round, wherein the first exercise score is used to indicate the execution status of the target system in the current round in performing the operations in the target plan;

[0116] 132: Based on the second relevant data, generate the second exercise score of the target plan in the current round, wherein the second exercise score is used to indicate the difference between the first operating environment and the second operating environment. The first operating environment is the operating environment of the target system in the current round, and the second operating environment is the operating environment of the target plan during the first round of exercise or before the first round of exercise.

[0117] 133: Based on the historical exercise evaluation results, generate the target contingency plan's third exercise score in the current round;

[0118] 134: Based on the scores of the first, second, and third exercises, evaluate the effectiveness of the target plan in the current round of exercises and obtain the evaluation results of the target plan in the current round of exercises.

[0119] Specifically, in the process of evaluating the effectiveness of drills, the evaluation method is relatively simple, relying solely on scattered data for subjective judgment. This cannot comprehensively and objectively reflect the effectiveness of the drills, and the accuracy and reliability of the evaluation results are insufficient, making it difficult to provide a strong basis for the optimization and adjustment of the plan. Based on the above problems, in some embodiments provided in this application, a multi-dimensional drill scoring evaluation system is constructed. Corresponding drill scores are generated based on different types of drill-related data, and then multiple drill scores are combined for comprehensive evaluation to improve the comprehensiveness and objectivity of the evaluation results.

[0120] In some embodiments, the first relevant data can be understood as various information indicating the operating status of the target system when it executes the target plan operation in the current round of exercise, including data such as operation execution success rate, execution time, and fault response parameters.

[0121] In some embodiments, the first exercise score can be understood as a quantitative score generated based on the first relevant data, used to reflect the overall status of the target system in performing the target plan operation in the current round, including performance such as operation completion and execution efficiency.

[0122] In some embodiments, the second relevant data can be understood as various information characterizing the current operating environment of the target system when it is running according to the target plan, including hardware configuration, software version, network bandwidth, status of dependent services, etc.

[0123] In some embodiments, the second exercise score can be understood as a quantitative score generated based on second relevant data, used to indicate the degree of difference between the first operating environment and the second operating environment. The greater the difference in environment, the more obvious the impact on the exercise effect may be.

[0124] In some embodiments, the formula for calculating the second exercise score can be:

[0125]

[0126] in, For the second exercise, For the drift factor, Based on the basic components, in the embodiments of this application, The second exercise score typically involves four drift factors.

[0127] In some embodiments, The formula for calculating whether there have been changes to the service application programming interfaces (APIs) that the target system depends on is as follows:

[0128]

[0129] in, This represents the number of API interfaces that have changed. This represents the total number of associated API interfaces.

[0130] In some embodiments, The formula for determining whether the associated middleware / database version has been upgraded is as follows:

[0131]

[0132] in, For the number of middleware / database versions to match, This represents the total number of middleware / database versions that the system depends on.

[0133] In some embodiments, The formula for representing the number of releases occurring in the associated system is:

[0134]

[0135] in, The number of systems that have undergone changes. This represents the total number of associated systems.

[0136] In some embodiments, The formula for determining whether the configuration of system resource nodes has changed is as follows:

[0137]

[0138] in, The number of system resource nodes to be changed. This represents the total number of resource nodes in the original system.

[0139] In some embodiments, the weights corresponding to the four drift factors included in the second exercise score can be configured by the operations and maintenance personnel according to the actual application scenario.

[0140] In some embodiments, the first operating environment can be understood as the actual operating environment of the target system in the current round of exercises, and the second operating environment can be understood as the initial operating environment during the first round of exercises of the target plan or before the first exercise.

[0141] In some embodiments, historical exercise evaluation results can be understood as a comprehensive evaluation conclusion and data record formed after at least one target plan exercise prior to the current round of exercises.

[0142] In some embodiments, the third exercise score can be understood as a quantitative score generated based on historical exercise evaluation results, used to reflect the performance trend and stability of the target plan in long-term exercises.

[0143] In some embodiments, the exercise evaluation result can be understood as a comprehensive evaluation of the effectiveness of the current round of exercises, formed by combining the first exercise score, the second exercise score, and the third exercise score through preset logical analysis.

[0144] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0145] After collecting three types of relevant data—first relevant data, second relevant data, and historical exercise evaluation results—the electronic equipment extracts indicators from the first relevant data, including operation execution success rate, execution time of each operation step, and fault response speed. These indicators are then integrated and calculated using a preset quantitative algorithm to obtain the first exercise score. The first exercise score reflects the target system's performance in executing the planned operations in the current round; a higher score indicates smoother operation execution and stronger plan executability.

[0146] Simultaneously, the electronic equipment compares and analyzes the differences in various parameters between the first and second operating environments in the second set of relevant data, including changes in hardware configuration, software version updates, network status fluctuations, and changes in dependent services. An environmental difference quantification model is used to calculate the degree of difference between the first and second operating environments, which is then converted into a second exercise score. A higher score indicates a smaller difference between the current and initial operating environments, and a stronger environmental adaptability of the contingency plan; a lower score indicates a greater potential impact of environmental changes on the execution of the contingency plan.

[0147] In addition, the electronic equipment also analyzes data from historical exercise evaluations, including the effectiveness level, performance indicators, and problem records of each round of exercises. It then uses trend analysis algorithms to extract the long-term performance characteristics of the contingency plan and converts them into a third-party exercise score. A higher score indicates that the contingency plan performs more stably and reliably over long-term exercises.

[0148] Finally, the electronic equipment integrates and analyzes the scores of the first, second, and third exercises through a preset comprehensive evaluation logic, ultimately forming an exercise evaluation result that can objectively and comprehensively reflect the effect of the current round of exercises.

[0149] Thus, in this embodiment, after obtaining exercise-related data including first relevant data, second relevant data, and historical exercise evaluation results, a first exercise score indicating the target system's operational execution status is generated based on the first relevant data; a second exercise score indicating the difference between the current operating environment and the initial operating environment is generated based on the second relevant data; and a third exercise score reflecting the long-term performance trend of the contingency plan is generated based on the historical exercise evaluation results. The three scores are then combined to obtain the exercise evaluation result for the current round. This achieves multi-dimensional exercise effectiveness evaluation. Compared to evaluation methods that simply integrate exercise-related data and lack clearly defined evaluation dimensions, this approach allows exercise evaluation to cover aspects such as operational execution quality, environmental adaptation changes, and historical stable performance. The score for each dimension provides reliable data support for the evaluation results, avoiding the one-sidedness of single-dimensional evaluation to a certain extent. It clearly presents the performance of the contingency plan in different aspects, thereby improving the credibility and practicality of the evaluation results and ensuring that the target contingency plan can play a more reliable role in actual fault scenarios.

[0150] In some embodiments provided in this application, the effectiveness of the target plan in the current round of drills is evaluated based on the first drill score, the second drill score, and the third drill score, to obtain the drill evaluation result of the target plan in the current round, including:

[0151] The target exercise score for the current round is obtained by weighting and summing the first exercise score with its corresponding first weight, the second exercise score with its corresponding second weight, and the third exercise score with its corresponding third weight.

[0152] The target evaluation result corresponding to the target exercise score in the pre-determined score-result mapping data is determined as the exercise evaluation result of the target plan in the current round. The score-result mapping data includes multiple scores and the evaluation result corresponding to each score.

[0153] Specifically, in the multi-dimensional scoring evaluation process, the lack of clear scoring integration rules and evaluation result mapping standards makes it impossible to reasonably reflect the importance of scores in different dimensions, resulting in insufficient consistency and accuracy of evaluation results and difficulty in quickly determining the specific effectiveness level of the contingency plan exercise. Based on the above problems, in some embodiments provided in this application, corresponding weights are assigned to the exercise scores of each dimension, and the target exercise score is obtained by weighted summation. Then, the final evaluation result is determined based on the preset score-result mapping data, making the evaluation process more standardized and accurate.

[0154] In some embodiments, the first weight can be understood as a weight coefficient pre-set for the first exercise score, used to reflect the importance of the first exercise score in the comprehensive evaluation. The value of the first weight can be determined according to the degree of influence of the operational execution status reflected by the first exercise score on the effectiveness of the contingency plan.

[0155] In some embodiments, the second weight can be understood as a weight coefficient set for the second exercise score, used to characterize the proportion of environmental difference factors corresponding to the second exercise score in the comprehensive evaluation, and the weight configuration is based on the impact of environmental changes on the implementation effect of the contingency plan.

[0156] In some embodiments, the third weight can be understood as a weighting coefficient pre-set for the third exercise score, used to reflect the importance of historical performance trends in the comprehensive evaluation, and determined based on the reference value of historical exercise data for judging the stability of the contingency plan.

[0157] In some embodiments, the target exercise score can be understood as a quantitative score obtained by weighting and summing the first exercise score, the second exercise score, and the third exercise score with their respective weights, which can comprehensively reflect the effect of the current round of exercises.

[0158] In some embodiments, score-result mapping data can be understood as a pre-constructed standardized dataset, including multiple continuous or discrete score intervals and the evaluation results corresponding to each score interval, providing a clear basis for the conversion of target practice scores into practice evaluation results.

[0159] In some embodiments, the target evaluation result can be understood as the evaluation conclusion in the score-result mapping data corresponding to the score range to which the target exercise score belongs.

[0160] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0161] The electronic equipment pre-assigns corresponding weights to the exercise scores based on the impact of the dimensions reflected in the first, second, and third exercise scores on the effectiveness of the contingency plan. The first weight corresponds to the first exercise score, focusing on the role of the operational execution status, and has a relatively high weight value. The second weight corresponds to the second exercise score, reflecting the impact of environmental differences, and its weight value is reasonably configured according to environmental stability. The third weight corresponds to the third exercise score, reflecting the reference value of historical performance, and its weight value is set in conjunction with the contingency plan's life cycle characteristics. The sum of the first and third weights is 1 to ensure the rationality of the weighted summation logic.

[0162] Subsequently, the electronic device performs a weighted summation operation according to a preset formula, namely:

[0163]

[0164] in, , , Practice scores to achieve the target score. Score for the third exercise. Score for the first exercise. For the second exercise, As the first weight, It is the third weight.

[0165] In some embodiments, the values ​​of the first weight and the third weight can be configured according to the specific application scenario of the current round of drills. For example, for a database master-slave switchover plan with extremely low change frequency, a higher initial value can be set. ,like For service degradation plans that rely on weak dependencies in business chains with high change frequency, a lower threshold can be set. ,like Historical drill data (more than 10 drills) is highly valuable for assessing the stability of contingency plans. Therefore, increasing the weight of historical drill scores (i.e., the third drill score) is configurable. Historical exercise data (less than 3 times) has low reference value for judging the stability of the contingency plan. Therefore, the weight of the historical exercise score (i.e., the third exercise score) should be reduced. .

[0166] By using the weighted summation operation described above, the scores from the three different dimensions are integrated into a comprehensive quantitative indicator. This not only highlights the impact of the important dimensions but also takes into account the role of other dimensions, ensuring that the comprehensive score can fully and objectively reflect the overall effect of the current round of exercises.

[0167] Before the emergency drill, electronic devices are pre-divided into multiple consecutive score ranges, each corresponding to a specific evaluation result. For example, 90 to 100 points corresponds to excellent, 75 to 89 points to good, 60 to 74 points to average, 40 to 59 points to warning, and 0 to 39 points to failure. The score range division and corresponding evaluation results of the mapping data can be determined in conjunction with the actual needs of emergency plan management and industry standards to ensure the standardization and universality of score-result mapping data.

[0168] Finally, the electronic device compares the calculated target practice score with the preset score-result mapping data to determine the score range to which the target practice score belongs, and then extracts the evaluation result corresponding to the score range as the target evaluation result, that is, the practice evaluation result of the current round.

[0169] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to [link / reference]. Figure 3 And the following exemplary description, Figure 3 This application provides a schematic diagram of the entire process of automated evaluation and triggering of contingency plan exercises, as shown in the embodiments below:

[0170] Maintenance personnel can preset the time cycle for electronic devices to perform contingency plan drills, that is, set the contingency plan drills as scheduled tasks. For example, set the electronic devices to automatically start the entire contingency plan assessment and drill process at 8:00 am every weekday without manual intervention.

[0171] After the scheduled task is triggered, the electronic device first performs the operation of obtaining the list of contingency plans, which retrieves all the configured executable contingency plans in the target system, laying the foundation for subsequent evaluation work and ensuring that no contingency plan is missed outside the evaluation scope.

[0172] Subsequently, the electronic equipment integrates the first relevant data, the second relevant data, and the historical exercise evaluation results to quantify and score each contingency plan, ensuring the objectivity and accuracy of the evaluation results.

[0173] Then, the electronic equipment updates the contingency plan status according to the quantitative scoring results. For example, in the scoring... If the score is 90, update the contingency plan status to excellent; if it is 75... score If the score is 90, update the contingency plan status to "good"; if it is 60... score At a score of 74, the contingency plan status will be updated to general, with a target of 40. score If the score is 60, the contingency plan status will be updated to warning, and the scoring will be adjusted accordingly. If the score is 40, the contingency plan status will be updated to invalid, thus linking the scoring result with the actual performance of the contingency plan.

[0174] Furthermore, regarding the rating At 40 minutes, the status is updated to invalid. The electronic equipment will further determine whether the target plan in this task has been rehearsed. If the target plan has not been rehearsed in the current timed task cycle, the plan rehearsal will be automatically triggered. The electronic equipment will start a re-evaluation process to confirm the accuracy of the invalidation conclusion through secondary verification. This avoids misjudgment due to accidental errors in a single evaluation, ensures that high-risk plans can be accurately identified, and provides a reliable basis for subsequent emergency handling.

[0175] If the target contingency plan has already been practiced in this mission, then proceed directly to the closing stage to avoid wasting system resources due to repeated practice.

[0176] Thus, in this embodiment, corresponding first weight, second weight, and third weight are assigned to the first exercise score, the second exercise score, and the third exercise score, respectively. The target exercise score is calculated by weighted summation. Then, the target exercise score is compared with the pre-determined score-result mapping data, and the corresponding target evaluation result is extracted as the exercise evaluation result for the current round. This achieves the scientific integration of multi-dimensional scores and the standardized output of evaluation results. Compared with evaluation methods that simply average or subjectively integrate multi-dimensional data, this allows the exercise evaluation to allocate differentiated weights according to the importance of different scores, highlighting the operational execution status and environment. The varying influences of adaptation differences and historical performance trends ensure that the target exercise score accurately reflects the overall effectiveness of the contingency plan. Furthermore, the standardized score-result mapping data provides a unified basis for generating evaluation results, avoiding inconsistencies caused by subjective judgments in different rounds or different contingency plan evaluations. This ensures the objectivity and comparability of the evaluation results, thereby enhancing their credibility to a certain extent. It also facilitates technical personnel in quickly and accurately grasping the actual status of the contingency plan, providing a reliable basis for subsequent decisions such as adjusting exercise intervals and optimizing and iterating the contingency plan. This improves the level of refinement in contingency plan management and the ability to respond to system failures.

[0177] In some embodiments provided in this application, a third exercise score for the target plan in the current round is generated based on historical exercise evaluation results, including:

[0178] The third training score is obtained by weighted summing of the scores of the first training sessions in the previous rounds and the weights corresponding to each previous round. The weights corresponding to the previous rounds are negatively correlated with the round difference between the previous and current rounds.

[0179] Specifically, the method of utilizing historical exercise evaluation results in the process of generating the third exercise score is relatively simple. It does not consider the time correlation between different historical rounds of exercises and the current round of exercises, and assigns the same weight to recent and long-term exercise results. As a result, the third exercise score cannot accurately reflect the recent performance and trend changes of the plan, affecting the timeliness and accuracy of the overall evaluation results. Based on the above problems, in some embodiments provided in this application, different weights are set according to the round difference between the historical rounds and the current round. The smaller the round difference, the higher the weight. The third exercise score is generated by weighted summation, highlighting the impact of recent exercise results.

[0180] In some embodiments, the previous rounds can be understood as the various independent training rounds that have been completed before the current round of training. Each previous round has a corresponding first training score, and the number of previous rounds can be configured by the operation and maintenance personnel. The target system selects the 10 most recent valid training rounds by default.

[0181] In some embodiments, the scores of the first drills in previous rounds before the current round can be understood as the quantitative score of the drill effect obtained by the electronic device evaluating and quantifying the relevant parameters in the drill process through preset evaluation logic after the completion of each pre-planned drill in the previous round.

[0182] In some embodiments, the weight can be understood as a coefficient assigned to each score in the first exercise of the preceding rounds, used to adjust the degree of influence of different preceding rounds on the score of the third exercise.

[0183] In some embodiments, the weights can be calculated using a time decay factor, giving higher weights to more recent exercise rounds.

[0184] In some implementations, the score for the third exercise can be calculated using the following formula:

[0185]

[0186] in, The attenuation coefficient can take values ​​ranging from 1 to 2. The corresponding half-lives are approximately 14 days and 7 days, respectively. A weekly iterative exercise cycle can be selected using... Long-cycle training can be selected This ensures that the weight decay rate matches the business iteration frequency.

[0187] In some embodiments, the round difference can be understood as a time difference between a previous round and the current round, i.e., in the formula above. The calculation method is as follows:

[0188]

[0189] in, For the current time, In order to complete the previous round of drills within the allotted time, Measured in days.

[0190] Furthermore, the round difference can also be correlated with the number of practice rounds in between. For example, if the current round is round 10 and the previous round was round 8, with a gap of 2 rounds, the corresponding... This refers to the number of days from the completion time of the previous round of exercises to the current time.

[0191] In some embodiments, negative correlation can be understood as the weight corresponding to a previous round decreasing as the round difference increases; the smaller the round difference, the greater the weight, meaning that more recent rounds have a greater impact on the score of the third exercise. The weight is calculated using a time decay factor. , That is, in the most recent exercise before the current round, the decay factor was 1, and the weight was the largest. As the value increases, the attenuation factor rapidly approaches 0, meaning the weight gradually decreases. For example, when selecting... When the round difference is 7 days, the weight is approximately 0.5; when the round difference is 14 days, the weight is approximately 0.25; and the sum of all weights in the previous rounds after normalizing the denominator in the formula is 1.

[0192] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0193] The electronic equipment selects multiple valid previous rounds from the historical exercise evaluation results. The specific number of previous rounds to be selected can be preset according to the length of the exercise history and the evaluation accuracy requirements. The system defaults to selecting the most recent 10 rounds to ensure that sufficient historical performance samples are included.

[0194] For each selected previous round, the electronic device automatically calculates the round difference between the previous round and the current round, obtains the corresponding round difference value, and determines the preset attenuation coefficient. .

[0195] The electronic devices assign weights to each student's first practice score in previous rounds based on the negative correlation between round difference and weight, and the time decay formula. First, the time decay factor for each student in previous rounds is calculated. Then, the sum of all decay factors from previous rounds is used as the denominator for normalization. The decay factor of each round serves as the basis for calculating the weight of the corresponding round, ensuring that the round difference is minimized, i.e., the weight of the most recent previous round is maximized, and the weight gradually decreases exponentially as the round difference increases. For example, using... In the previous rounds The corresponding attenuation factor is If the sum of the decay factors across all rounds is 2.8188, then the weights corresponding to the previous rounds are as follows: 。

[0196] Finally, the electronic device calculates the sum of the products of all scores from the first practice session in the previous rounds and their corresponding attenuation factors, and then divides this sum by the sum of all attenuation factors from the previous rounds to obtain the normalized score for the third practice session, i.e.:

[0197]

[0198] Thus, in this embodiment, the first exercise scores from multiple previous rounds are extracted, and a corresponding weight is assigned to each previous round based on the time decay factor. The weight is negatively correlated with the round difference between the previous round and the current round. The third exercise score is then calculated by weighted summation. This achieves differentiated integration of historical exercise data. Compared to the integration method of using average weight or fixed weight for all first exercise scores from previous rounds, by assigning different weights to historical exercise results with different round differences, the impact of recent exercise results on the third exercise score is highlighted. This allows the third exercise score to reflect the recent performance and trend changes of the plan, thereby improving the timeliness and accuracy of the third exercise score to a certain extent. This provides reliable data for subsequent plan optimization and exercise strategy adjustment, and enhances the refinement and intelligence of plan management.

[0199] In some embodiments provided in this application, the target contingency plan is one of a plurality of executable contingency plans, each executable contingency plan corresponding to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable contingency plan corresponding to the fault type of the detected fault, and generates a first exercise score for the target contingency plan in the current round based on first relevant data, including:

[0200] Based on the first relevant data, a first sub-score, a second sub-score, and a third sub-score are generated. The first sub-score is used to indicate the difference between the fault type detected by the target system in the current round and the fault type corresponding to the target plan. The second sub-score is used to indicate the percentage of operations successfully executed by the target system among all operations included in the target plan. The third sub-score is used to indicate the difference between the operating status of the target system after executing the operations in the target plan and the expected system status corresponding to the target plan.

[0201] The first exercise score is obtained by weighting and summing the first sub-score and its corresponding weight, the second sub-score and its corresponding weight, and the third sub-score and its corresponding weight.

[0202] Specifically, the assessment of the operation execution status during the first exercise score generation process is relatively simple, resulting in the first exercise score failing to accurately reflect the performance of each dimension during operation execution and making it difficult to accurately pinpoint problems in the contingency plan operation. Based on the above problems, in some embodiments provided in this application, the first exercise score is further refined into three sub-scores, evaluated from three dimensions: fault type matching, operation execution success rate, and system state recovery. These sub-scores are then weighted and summed to generate the final first exercise score, achieving a refined assessment of the first exercise score and providing a clear direction for contingency plan optimization.

[0203] In some embodiments, the first sub-score can be understood as a quantitative score generated based on the first relevant data to evaluate the success rate of fault injection verification. It is used to indicate the degree of difference between the fault type detected by the target system and the fault type corresponding to the target contingency plan, while taking into account the accuracy of the impact range of fault injection and the timeliness of injection.

[0204] In some embodiments, the first sub-score is calculated based on the base success rate, which is the ratio of the number of successfully validated fault injections to the total number of planned fault injections. This base success rate is then weighted by three dimensions: fault type matching degree, impact scope accuracy, and injection timeliness.

[0205]

[0206] in, This refers to the success rate of fault injection verification. Based on the success rate, For fault type matching degree, To affect the accuracy of the range, To inject timeliness, Based on the base score.

[0207] In the embodiments of this application, The accuracy of fault type matching, impact range, and injection timeliness can all be assigned a score between 0 and 1 based on the degree of conformity between the actual performance and the preset standard. A perfect match gets 1 point, a complete mismatch gets 0 points, and a partial match gets a proportional score.

[0208] In some embodiments, the second sub-score can be understood as a quantitative score of the completion of the evaluation plan execution steps generated based on the first relevant data. It is used to indicate the proportion of the number of operations successfully executed by the target system in all operations of the target plan. The more operations are successfully executed, the higher the second sub-score, which can reflect the overall execution success rate of the plan operations.

[0209] In some embodiments, the formula for calculating the second sub-score is:

[0210]

[0211] in, For the first The weight of each step, For the corresponding number The quality of each step is scored, and the weight of each step can be configured by the operations and maintenance personnel on the contingency plan management page. The system defaults to a weight of [weight missing] for each step. , This represents the number of steps required to execute the contingency plan.

[0212] In some embodiments, the formula for calculating the quality score upon completion of the steps is:

[0213]

[0214] in, For the first The success rate of each step. To execute the first The expected time for each step To execute the first The actual execution time of each step, and the success rate, is the ratio of the number of successfully executed steps to the total number of executed steps. The execution time ratio is 1 when the actual execution time is less than or equal to the expected execution time. When the actual execution time is greater than the expected execution time, the ratio of the expected execution time to the actual execution time is used, which reflects the impact of execution efficiency on the second sub-score.

[0215] In some embodiments, the third sub-score can be understood as a quantitative score generated based on the first relevant data to assess the compliance rate of business recovery verification. It is used to indicate the degree of difference between the actual operating state of the target system and the expected system state corresponding to the contingency plan after the system performs the contingency plan operation. The expected system state can be understood as the ideal system state after fault handling set during the contingency plan design. The closer the actual operating state is to the expected state, the higher the third sub-score.

[0216] In some embodiments, the third sub-score is calculated using a multi-indicator weighted approach, namely:

[0217]

[0218] in, For the first The weights of each verification metric, For the first The compliance coefficient of each verification indicator. It can be adjusted according to the actual application scenario.

[0219] In some embodiments, the verification metrics may include functional recovery metrics, performance recovery metrics, and user experience metrics. The functional recovery metric, i.e., the interface success rate, can have a weight of 0.5, and the corresponding compliance coefficient is calculated using the following formula:

[0220]

[0221] in, For the actual success rate, The target success rate.

[0222] In some embodiments, the performance recovery metric includes information on both system response time and throughput. The weight of the performance recovery metric can be set to 0.3, and the corresponding compliance coefficient is calculated using the following formula:

[0223]

[0224] in, It is the weight of the system response time. It is the weight of system throughput, usually 50%. .

[0225] In some embodiments, the response time compliance factor The value is 1 when the actual response time is less than or equal to the expected response time; when the actual response time is greater than the expected response time, the calculation formula is as follows:

[0226]

[0227] in, This is the actual response time. This represents the expected response time.

[0228] In some embodiments, throughput compliance coefficient The value is 1 when the actual throughput is greater than or equal to the expected throughput; when the actual throughput is less than the expected throughput, the calculation formula is as follows:

[0229]

[0230] in, For actual throughput, This represents the expected throughput.

[0231] In some embodiments, the weight of the user experience metric, i.e., the end-to-end success rate of the business process, can be set to 0.2, and the corresponding achievement coefficient is calculated using the following formula:

[0232]

[0233] in, This represents the actual number of successful transactions in the business scenario. This represents the expected number of successes.

[0234] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to the following exemplary description:

[0235] The target contingency plan is one of several executable contingency plans. The target contingency plan is pre-bound to a specific fault type, and the target system will automatically execute the corresponding target contingency plan operation when it detects a fault type.

[0236] In the current round of drills, electronic equipment has completed fault injection according to the fault type corresponding to the target plan, ensuring that the drill scenario is compatible with the plan.

[0237] Subsequently, the electronic device extracts fault type matching information from the first relevant data, compares the fault type currently detected by the target system with the fault type corresponding to the target contingency plan, and quantifies the degree of difference from dimensions such as fault manifestation, scope of impact, and triggering conditions. The smaller the difference, the higher the score, forming the first sub-score, which reflects the fit between fault injection and contingency plan design.

[0238] At the same time, the total number of all operations included in the target plan and the number of operations successfully executed by the target system are statistically analyzed. The second sub-score is calculated by the ratio of the number of successful executions to the total number of operations, which reflects the success rate of the plan's operations.

[0239] In addition, the electronic device simultaneously extracts the expected state of the system corresponding to the target plan, compares it with the actual operating state of the target system after all operations are completed, and quantifies the differences in terms of function recovery, performance indicators, user experience, etc. The closer the actual state is to the expected state, the higher the score, forming a third sub-score that reflects the fault resolution effect of the plan.

[0240] Then, the electronic equipment presets weights based on the importance of the three sub-scores, with the sum of the weights being 1. For example, the fault type matching degree affects the effectiveness of the exercise, and the weight can be set to 0.2; the operation execution success rate reflects the feasibility of the plan, and the weight can be set to 0.3; the system state recovery effect is the ultimate goal of the plan, and the weight can be set to 0.5. The weight configuration can be flexibly adjusted according to business needs.

[0241] Finally, multiply the first sub-score by its corresponding weight, the second sub-score by its corresponding weight, and the third sub-score by its corresponding weight, then sum the three products to obtain the final first exercise score, i.e.:

[0242]

[0243] in, .

[0244] Thus, in this embodiment, a first sub-score, a second sub-score, and a third sub-score are generated based on the first relevant data. Then, corresponding weights are assigned to each of the three sub-scores, and a weighted sum is used to obtain the first exercise score. This achieves a quantitative evaluation of the first exercise score. Compared to the evaluation method that simply integrates the first relevant data to generate a single score without being able to subdivide the dimensional performance, this method makes the first exercise score more objective and accurate. Each sub-score can independently reflect the true performance of its corresponding dimension, enabling maintenance personnel to accurately identify problems in fault type matching, operation execution success rate, and system state recovery. This provides a clear basis for the refined optimization of the contingency plan. Furthermore, by assigning corresponding weights to different sub-scores, the first exercise score better aligns with the actual priority of the contingency plan execution, avoiding interference from single-dimensional data on the overall evaluation results to a certain extent. This improves the reliability and practicality of the first exercise score, thereby providing reliable support for the accuracy of the comprehensive evaluation results and strengthening the refinement level of contingency plan management and the effectiveness of system fault response.

[0245] To more clearly illustrate the contingency processing method provided in the embodiments of this application, please refer to Figures 4(a), 4(b), and 4(c). Figure 5 The following exemplary descriptions, Figures 4(a) and 4(b) are schematic diagrams of the contingency plan exercise execution and status closed-loop management process provided in the embodiments of this application. Figure 5 This is a schematic diagram of the effectiveness scoring data for the proposed solution provided in the embodiments of this application, namely:

[0246] In some embodiments, the electronic device includes a contingency plan management module, a data acquisition module, a model scoring calculation module, a decision-making module, an automated execution module, a fault execution module, and a status management module. The contingency plan management module is responsible for the input, classification, and version management of contingency plans, and synchronizes the output contingency plan list to the data acquisition module and the decision-making module. The data acquisition module collects historical exercise data and current environmental data, and provides real-time feedback on exercise process data. The model scoring calculation module performs multi-dimensional scoring based on the input data and transmits the results to the decision-making module. The decision-making module combines the scoring results with preset rules to issue instructions to the automated execution module and the fault execution module. The status management module synchronously records the status information of the entire process, forming a two-way data interaction between the modules.

[0247] After a scheduled task is triggered, the electronic device first obtains a list of contingency plans through the contingency plan management module, and then the model scoring calculation module evaluates each contingency plan according to the scoring model, combining... The calculation results are used to divide the scoring intervals. Among them, the scoring... 90 points is excellent, 75 points is good. score 90 points is good, 60 points is good. score 74 points is average, 40 points is average. score A score of 60 is required for early warning and scoring. If the score is 40, the contingency plan status will be updated accordingly.

[0248] For rating The 40-minute failure contingency plan first determines whether the contingency plan has been practiced in this task. If not, it triggers a practice to re-evaluate and confirm the accuracy of the conclusion. If it has been practiced, the process ends, ensuring the relevance of the contingency plan practice and the efficient use of resources.

[0249] In existence rating After the decision-making module triggers the exercise based on the 40-point failure contingency plan, the fault execution module injects a fault according to the fault type corresponding to the target contingency plan and executes automated scenario test cases to confirm whether the fault injection was successful. After confirming successful fault injection, the contingency plan execution module executes the contingency plan according to preset operations, and then executes the automated scenario test cases again to confirm whether the contingency plan is effective. The automated scenario test cases play a detection role during the exercise, confirming whether the fault injection was successful and whether the contingency plan is effective, ensuring the effectiveness verification of the exercise process.

[0250] After each operation is executed, the fault execution module performs fault recovery processing to ensure that the business application no longer detects the corresponding fault type.

[0251] After the exercise is completed, the data acquisition module collects data again, the model scoring calculation module recalculates the exercise score, and the decision-making module updates the contingency plan status.

[0252] To more clearly illustrate the contingency plan processing method provided in the embodiments of this application, this embodiment takes the contingency plan of automatically downgrading the activity system when the activity system's response times out as an example to explain the automated contingency plan drill method of some of the above embodiments:

[0253] The application scenario of this application is emergency handling of payment system failures on e-commerce platforms. As the link in the fund flow of e-commerce platforms, the payment system needs to ensure the continuity of payment services when related systems are abnormal. Among them, the activity system is an associated system of the payment system. During the payment process, users call the activity system interface to obtain discount information. When the response timeout rate of the activity system is greater than or equal to 10% due to reasons such as a sudden increase in traffic or service abnormalities, it is easy to cause the payment system request to be blocked, affecting the user's payment experience or even causing the user's payment to fail.

[0254] To address the aforementioned failure scenarios, technical personnel have pre-designed a contingency plan—a target plan—that automatically degrades the activity system when the activity system times out. This target plan is a business contingency plan in the payment system's executable contingency plan library. When the payment system detects that the activity system's response timeout rate is greater than or equal to 10%, it automatically triggers a service degradation operation, cutting off the payment system's calls to the activity system's discount interface. The user's payment process no longer retrieves activity discount information and directly executes the payment process, ensuring the smooth completion of the payment transaction.

[0255] In this embodiment of the application, the execution steps of the preset target plan are two steps. Step 1 is to detect the call threshold of the activity system interface:

[0256] The payment system monitors the response timeout rate of the activity system interface in real time. When the response timeout rate is greater than or equal to 10% within 5 consecutive seconds, a service degradation signal is triggered.

[0257] Step 2 involves cutting off the payment system's access to the promotional API:

[0258] The payment system blocks requests to the activity discount query interface and returns a standardized response to the user indicating that no discounts are currently available, while maintaining the normal operation of the payment interface.

[0259] In addition, the default exercise interval for the preset target plan is 7 days, and the preset scheduled task is to automatically start the plan evaluation and exercise at 8:00 am every working day.

[0260] In addition, in this embodiment of the application, the number of historical drills of the preset target plan is 8, and the time difference between the completion time of the most recent drill and the current time is 20 days. Since the historical drill data has time decay, and the current operating environment is different from the initial environment of the plan design, there is a risk of plan corruption.

[0261] During the drills of the target contingency plan, electronic devices trigger a timed task at 8:00 AM on weekdays to conduct a self-assessment of the target contingency plan.

[0262] First, the contingency plan management module retrieves complete information about the target contingency plan from the executable contingency plan library of the payment system, including contingency plan execution steps, fault type matching rules, environmental configuration parameters, historical exercise data, etc. Then, the model scoring calculation module is called to calculate the score of this exercise, i.e., the first exercise score, according to the dynamic scoring model for contingency plan effectiveness described in some of the above embodiments. The historical exercise score is the same as the score of the third exercise. The environmental drift index, i.e., the score of the second exercise. The final overall effectiveness score, i.e., the target exercise score, is obtained. .

[0263] For example, first calculate the score of this exercise. The score for this exercise Used to characterize the actual implementation effect of the target plan in the most recent exercise, by weights Fault injection verification success rate Weight Completion rate of the contingency plan execution steps Weight Business recovery verification compliance rate The weighted sum of the first relevant data is obtained, and the calculation formula is:

[0264]

[0265] In some embodiments, the success rate of fault injection verification Completion rate of the contingency plan execution steps Business recovery verification compliance rate The calculation process and data source can be extracted from the automated verification log of this exercise by the data acquisition module of the electronic device.

[0266] Among them, the success rate of fault injection verification is the first sub-score. The effectiveness of fault injection in the exercise is characterized by a weighted calculation based on the basic success rate, fault type matching degree, accuracy of impact range, and injection timeliness. The calculation formula is as follows:

[0267]

[0268] In this embodiment, the electronic device can extract the basic success rate of the current contingency plan exercise from the execution log of the fault injection module. The fault types corresponding to the target contingency plan are two fault items: activity system interface response timeout and activity system discount data return delay. These two fault items are injected into the contingency plan exercise system, i.e., the target system. After the fault injection module executes, both fault items are verified to be successful. Therefore...

[0269]

[0270] in, The number of successfully validated fault injection items. Total number of faults to be injected into the plan.

[0271] Meanwhile, since the two fault items injected into this contingency plan exercise are consistent with the activity system response timeout fault scenario designed in the target contingency plan, and there are no missing dimensions, therefore,

[0272]

[0273] in, The number of dimensions for the actual matched fault types. The total number of dimensions for fault types designed for the contingency plan.

[0274] In addition, the target contingency plan exercise of this application has five preset fault impact monitoring indicators, including payment system preferential interface call time, timeout ratio, payment interface call time, payment success rate, and transaction completion rate.

[0275] In this exercise, through automated test case verification via API, four out of the five monitoring metrics matched the scope of the fault's impact. Therefore...

[0276]

[0277] in, The number of resources within the target area actually affected by the fault. This represents the total number of resources affected by the fault.

[0278] In addition, the injection timeliness of the target contingency plan in this application embodiment is whether the fault injection can take effect within 10 seconds. In this application embodiment, the fault injection takes effect 19 seconds after being triggered. According to the contingency plan exercise rules: the timeliness is 1 if the fault injection takes effect within 10 seconds, 0.9 if it takes effect within 20 seconds, and the timeliness decreases by 0.1 for every additional 10 seconds. Therefore, the injection timeliness of this contingency plan exercise is determined to be 0.9.

[0279] Finally, the basic success rate, fault type matching degree, impact range accuracy, and injection timeliness obtained from the above calculations are weighted and calculated:

[0280]

[0281] Completion rate of contingency plan execution steps The quality of actual completion of the execution steps of the target plan is used to characterize the quality of each step in the plan exercise. It is obtained by summing the weight of each step and the corresponding quality score of the step. The calculation formula is as follows:

[0282]

[0283] The step weights can be configured by operations and maintenance personnel on the contingency plan management page. The system defaults to a weight of 1 for each step. Where n is the number of execution steps in the plan, and in this embodiment of the application, the target plan has a total of 2 execution steps, with the default weight of each step being:

[0284]

[0285] The quality score for step completion is calculated by weighting the success rate and execution time ratio, using the following formula:

[0286]

[0287] The electronic device extracts the execution parameters for each step from the logs of the pre-plan execution module. Specifically, step 1, which checks the call threshold of the activity system interface, has a 100% success rate, an expected execution time of 0.8 seconds, and an actual execution time of 1 second. The execution time ratio is:

[0288]

[0289]

[0290] Step 2, which involves cutting off the payment system's call to the promotional interface, has a 100% success rate. The expected execution time is 1 second, and the actual execution time is 0.9 seconds. The execution time ratio is:

[0291]

[0292]

[0293] Finally, the completion rate of the contingency plan execution steps can be calculated and determined as follows:

[0294]

[0295] Business recovery verification pass rate The degree to which the payment system's business recovers to the expected state after the execution of the target contingency plan is characterized is obtained by a weighted sum of three sub-indicators: functional recovery, performance recovery, and user experience. In this embodiment, the electronic device quantifies this through automated scenario use case detection. The score was 95, with the test indicators including a payment interface success rate of 99.9%, a payment response time of 50ms, and an end-to-end payment process success rate of 99.8%, all of which met the preset expected standards.

[0296] Based on the above... , and Calculate the score for this exercise. :

[0297]

[0298] Then, the historical exercise scores were calculated. Among them, the historical drills scored This is used to characterize the performance of the target contingency plan in long-term exercises. It is calculated by weighting the scores of the most recent N exercises with a time decay factor. The system defaults to N=10. The calculation formula is as follows:

[0299]

[0300] in, This is the time difference between the current time and the completion time of the historical exercise. As the decay coefficient, the payment system in this embodiment iterates weekly, taking... =0.1, corresponding to a half-life of 7 days.

[0301] In this embodiment, the target plan has been practiced 8 times in the past, with the most recent exercise completed 20 days ago. The other exercises were conducted even earlier. After being weighted by a time decay factor, the reference value of the historical exercise data is reduced, and the electronic equipment calculates... It is 50.

[0302] Next, the environmental drift index is calculated. Environmental drift index This is used to characterize the degree of difference between the current operating environment of the payment system and the initial environment of the target plan design. It is a deduction item for environmental drift, usually obtained by weighted summation of four drift factors. The calculation formula is as follows:

[0303]

[0304] in, The API interface has changed, with a weight of 0.3. Indicates whether the middleware / database version has been upgraded, with a weight of 0.25. The number of times a related system publishes data, with a weight of 0.25. This indicates whether the configuration of system resource nodes has changed, with a weight of 0.2.

[0305] The electronic device collects current operating environment parameters through a data acquisition module, compares these parameters with the initial environment of the pre-design plan, and calculates a combined drift factor value of 0.25. Therefore,

[0306]

[0307] In some embodiments, the reasons for drift include a change in a field of the linkage interface between the activity system and the payment system, an upgrade of the caching middleware version of the payment system, two recent feature releases by the activity system, and an expansion of the payment system server nodes from 5 to 6.

[0308] Finally, calculate the overall effectiveness score. Overall effectiveness score The final evaluation score for the target contingency plan is obtained by weighting the historical exercise scores and the current exercise scores with dynamic weights, and then subtracting the environmental drift index. The calculation formula is as follows:

[0309]

[0310] in, The weight given to historical credibility is the first weight. This is the third weight for this exercise, and .

[0311] In some cases, the classification can be based on the inherent attributes of the contingency plan and the sufficiency of historical data. and The weighting, in this embodiment of the application, the target plan is a business plan of a payment system, and the number of historical drills is 8, which is greater than 3, therefore it can be configured. .

[0312] therefore,

[0313]

[0314] Subsequently, the decision-making module of the electronic device will calculate the overall effectiveness score. The score of 37.3 is compared with the score range, and the contingency plan status is updated accordingly based on the comparison results. For example, in the scoring... If the score is 90, the contingency plan status will be updated to excellent, and the exercise interval will be automatically extended to 75. score If the score is 90, update the contingency plan status to "good" and maintain the original exercise interval, within 60 minutes. score At a score of 74, the contingency plan status will be updated to normal, maintaining the original exercise interval of 40. score If the score is 60, the contingency plan status will be updated to warning, the exercise interval will be shortened, and the scoring will be adjusted accordingly. If the score is 40, the contingency plan status will be updated to invalid, and an automated drill will be triggered immediately.

[0315] In this application embodiment, the overall validity score The score was 37.3, which falls within the failure range of 0 to 39 points. Furthermore, the electronic equipment determined that the target contingency plan had not been practiced within the current timed task cycle, and therefore immediately triggered the automated practice process for the target contingency plan.

[0316] After the electronic device triggers the drill, the entire process of fault injection, contingency plan execution, fault recovery, and effect verification is automated through the fault execution module, automated execution module, and data acquisition module. The specific steps are as follows:

[0317] First, the fault execution module injects faults into the payment system test environment according to the fault type of the activity system response timeout corresponding to the target plan, simulating a fault scenario where the activity system interface response timeout rate reaches 15%, ensuring that the payment system detects the preset fault type.

[0318] Subsequently, the automated execution module controls the payment system to execute the two execution steps of the target plan in sequence. Step 1 completes the timeout ratio detection and triggers the degradation signal, and step 2 completes the disconnection of the activity discount interface. No manual intervention is required throughout the process.

[0319] Then, after each execution step of the target plan is completed, the fault execution module immediately performs fault recovery processing to eliminate the impact of the fault corresponding to each execution step, ensuring that the execution effect of each step is independently verified, and avoiding the distortion of the exercise results caused by the superposition of faults.

[0320] Next, the electronic device invokes preset automated scenario use cases to test the payment system after the contingency plan is executed, including fault type matching degree, step completion quality, business recovery indicators, etc., and collects all data during the exercise and synchronizes it to the data acquisition module.

[0321] Finally, after the exercise is completed, the model scoring calculation module recalculates the target plan based on the newly collected exercise data. , , as well as The exercise data was refreshed.

[0322] If the overall effectiveness score of the target plan improves to 93 points after this automated exercise is completed, the electronic equipment will update the status of the target plan to excellent.

[0323] The decision module of the electronic device dynamically adjusts the exercise time interval of the target plan according to the strategy described in some of the above embodiments, based on the updated overall effectiveness score after the exercise.

[0324] In rating If the score is 90, the contingency plan status will be updated to excellent, and the original exercise interval will be increased to 1.5 times, within 75... score If the score is 90, update the contingency plan status to "good" and maintain the original exercise interval, within 60 minutes. score If the score is 74, the contingency plan status will be updated to normal, maintaining the original exercise interval. (This is followed by a scoring process.) If the score is 60, the contingency plan status will be updated to warning, and the original exercise interval will be reduced to 0.5 times.

[0325] In this embodiment, the target contingency plan was scored 93 points after the exercise. The original default exercise interval was 7 days, therefore the electronic device automatically adjusted the exercise interval to... The number of days is rounded up to 11 days, and the new exercise interval is synchronized to the contingency plan management module as the basis for triggering subsequent scheduled tasks.

[0326] In some embodiments, during the automated evaluation, drill execution, and periodic adjustment of the target plan, the status management module of the electronic device records the execution status, data indicators, scoring results, and operation actions of each stage in real time, forming a complete plan drill log, including the timed task trigger time, the scores of each dimension of the plan evaluation, the reason for the drill trigger, the time of fault injection or recovery, the completion status of the plan execution steps, the score after the drill, and the results of the adjustment of the drill time interval, etc.

[0327] In some embodiments, all log data supports visual querying and export, providing reliable data support for subsequent contingency plan optimization, fault analysis, and system maintenance by operations and maintenance personnel. At the same time, log data can serve as the basis for calculating the score of the next historical exercise of the target contingency plan, realizing the periodic management of contingency plan exercises.

[0328] In some embodiments, based on the above embodiments, the contingency plan processing method of this application can also be used to implement extended functions such as indicator anomaly analysis, contingency plan adaptive optimization, and hierarchical early warning error reporting.

[0329] For example, if in this exercise With an accuracy of 0.8, the system will automatically check the monitoring indicator configuration of the fault injection module, locate the problem of "the threshold setting of the transaction completion rate indicator of the payment system is inconsistent with the contingency plan design", and push the cause of the problem, abnormal indicator data, and optimization suggestions to the operation and maintenance personnel of the payment system.

[0330] For example, in response to the issue that the execution time of step 1 was 1 second, exceeding the expected 0.8 seconds, the system automatically optimized the resource allocation strategy for the execution of the contingency plan. More server computing resources were allocated to the step of detecting the threshold of the system interface call for the detection activity. At the same time, the time window for the timeout ratio statistics was fine-tuned from 5 seconds to 3 seconds, improving the execution efficiency of step 1. After optimization, the verification was re-executed, and the execution time of step 1 was reduced to 0.7 seconds, meeting the expected standard.

[0331] For example, the system presets tiered thresholds for various dimensions of the target plan's indicators. If the payment success rate drops sharply to 90%, below the preset threshold of 95%, the system will trigger a red level 3 error, suspend the automatic execution of the target plan, switch to manual takeover mode, and simultaneously activate the payment system's backup degradation plan to ensure the continuity of payment services in actual business operations.

[0332] In addition, if both the payment system's activity system downgrade contingency plan and the risk control system's anomaly contingency plan fail... If the throughput compliance coefficient is low, the system will determine that the current fault is a bottleneck in the overall throughput of the payment system, rather than a problem with a single contingency plan. The current fault will be pushed to the architect for server expansion and traffic scheduling strategy optimization to achieve global resource allocation across contingency plans.

[0333] To facilitate better implementation of the contingency plan processing method in the embodiments of this application, the embodiments of this application also provide a contingency plan processing apparatus. Please refer to... Figure 6 , Figure 6 A schematic diagram of the scheme processing device provided in an embodiment of this application. The scheme processing device 200 may include:

[0334] The control module 210 is used to control the target system to execute the operation in the target plan in response to the exercise conditions of the target plan, so as to carry out the current round of exercise of the target plan. The exercise conditions include that the time difference between the current round and the previous round is greater than or equal to the exercise time interval corresponding to the target plan.

[0335] The acquisition module 220 is used to acquire exercise-related data corresponding to the target plan after the target system executes the operation in the target plan. The exercise-related data includes first related data, second related data and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running according to the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round.

[0336] The evaluation module 230 is used to evaluate the effectiveness of the target plan in the current round of exercises based on relevant exercise data, and obtain the evaluation results of the target plan in the current round of exercises.

[0337] In some embodiments, the target plan is one of a plurality of executable plans, each executable plan corresponding to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable plan corresponding to the fault type of the detected fault. The control module 210 can also be used to perform fault injection processing on the target system according to the fault type corresponding to the target plan when the exercise conditions of the target plan are met. After the fault injection processing is performed on the target system, the target system detects the fault type corresponding to the target plan.

[0338] In some embodiments, the target plan includes at least one operation, and the control module 210 can also be used to perform fault recovery processing on the target system according to the fault type corresponding to the target plan after each operation in the target plan is executed by the target system, wherein the target system cannot detect the fault type corresponding to the target plan after the fault recovery processing is performed on the target system.

[0339] In some embodiments, the control module 210 can also be used to update or maintain the exercise time interval based on the exercise evaluation results.

[0340] In some embodiments, the exercise evaluation result is one of a plurality of preset evaluation results. The control module 210 may also be used to increase the exercise time interval when the exercise evaluation result is the first preset evaluation result among the plurality of preset evaluation results, or to maintain the exercise time interval unchanged when the exercise evaluation result is the second preset evaluation result among the plurality of preset evaluation results, or to decrease the exercise time interval when the exercise evaluation result is the third preset evaluation result among the plurality of preset evaluation results.

[0341] In some embodiments, the evaluation module 230 can also be used to generate a first exercise score for the target plan in the current round based on the first relevant data, generate a second exercise score for the target plan in the current round based on the second relevant data, generate a third exercise score for the target plan in the current round based on historical exercise evaluation results, and evaluate the exercise effect of the target plan in the current round based on the first exercise score, the second exercise score and the third exercise score to obtain the exercise evaluation result of the target plan in the current round. The first exercise score is used to indicate the execution status of the target system in the current round when performing the operations in the target plan, and the second exercise score is used to indicate the difference between the first operating environment and the second operating environment. The first operating environment is the operating environment of the target system in the current round, and the second operating environment is the operating environment of the target plan during the first round of exercise or before the first round of exercise.

[0342] In some embodiments, the evaluation module 230 can also be used to perform a weighted summation of the first exercise score and the first weight corresponding to the first exercise score, the second exercise score and the second weight corresponding to the second exercise score, and the third exercise score and the third weight corresponding to the third exercise score to obtain the target exercise score of the target plan in the current round. The target evaluation result corresponding to the target exercise score in the predetermined score-result mapping data is determined as the exercise evaluation result of the target plan in the current round. The score-result mapping data includes multiple scores and the evaluation result corresponding to each score.

[0343] In some embodiments, the evaluation module 230 can also be used to perform a weighted summation of the first training scores of multiple previous rounds before the current round and the weights corresponding to each previous round to obtain a third training score, wherein the weights corresponding to the previous rounds are negatively correlated with the round difference of the previous rounds, and the round difference is the difference between the previous rounds and the current round.

[0344] In some embodiments, the target plan is one of a plurality of executable plans, each executable plan corresponding to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable plan corresponding to the fault type of the detected fault. The evaluation module 230 can also be used to generate a first sub-score, a second sub-score, and a third sub-score based on the first relevant data, and to perform a weighted summation of the first sub-score and its corresponding weight, the second sub-score and its corresponding weight, and the third sub-score and its corresponding weight to obtain a first exercise score. The first sub-score is used to indicate the difference between the fault type detected by the target system and the fault type corresponding to the target plan in the current round. The second sub-score is used to indicate the percentage of operations successfully executed by the target system among all operations included in the target plan. The third sub-score is used to indicate the difference between the operating state of the target system after executing the operations in the target plan and the expected state of the system corresponding to the target plan.

[0345] Each unit in the aforementioned contingency plan processing device can be implemented entirely or partially through software, hardware, or a combination thereof. Each unit can be embedded in or independent of the processor of the electronic device in hardware form, or stored in the memory of the electronic device in software form, so that the processor can call and execute the operations corresponding to each unit.

[0346] The contingency plan processing device 200 can be integrated into a terminal or server that has a memory and a processor and thus computing power, or the contingency plan processing device 200 can be the terminal or server.

[0347] Optionally, this application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0348] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may be a terminal or a server. Figure 7 As shown, the electronic device 300 includes a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, and a computer program stored in the memory 302 and executable on the processor. The processor 301 and the memory 302 are electrically connected. Those skilled in the art will understand that the electronic device structure shown in the figures does not constitute a limitation on the electronic device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0349] The processor 301 is the control center of the electronic device 300. It connects various parts of the electronic device 300 through various interfaces and lines. By running or loading software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device 300 and processes data, thereby performing overall processing of the electronic device 300.

[0350] In this embodiment, the processor 301 in the electronic device 300 loads the instructions corresponding to the processes of one or more computer programs into the memory 302 according to the following steps, and the processor 301 runs the computer programs stored in the memory 302 to realize various functions:

[0351] In response to meeting the exercise conditions of the target plan, the target system is controlled to execute the operations in the target plan to carry out the current round of exercise of the target plan. The exercise conditions include that the time difference between the current round and the previous round is greater than or equal to the exercise time interval corresponding to the target plan.

[0352] After the target system executes the operation in the target plan, the exercise-related data corresponding to the target plan is obtained. The exercise-related data includes first related data, second related data and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running according to the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round.

[0353] Based on the relevant data from the exercise, the effectiveness of the target plan in the current round of exercise is evaluated, and the evaluation results of the target plan in the current round of exercise are obtained.

[0354] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0355] Optional, such as Figure 7 As shown, the electronic device 300 also includes: a display screen 303, a radio frequency circuit 304, an audio circuit 305, an input unit 306, and a power supply 307. The processor 301 is electrically connected to the display screen 303, the radio frequency circuit 304, the audio circuit 305, the input unit 306, and the power supply 307. Those skilled in the art will understand that... Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0356] The display screen 303 can be used to display a graphical user interface (GUI) and receive operation commands generated by the user interacting with the GUI. The display screen 303 may include a display panel and a touch panel. The display panel can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the electronic device. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. The touch panel can be used to collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel), generate corresponding operation commands, and execute the corresponding program. Optionally, the touch panel may include a touch detection device and a touch controller. The touch detection device detects the user's touch location and the signal generated by the touch operation, and transmits the signal to the touch controller. The touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 301, and can receive and execute commands from the processor 301. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it transmits a detection signal to the processor 301 to determine the type of touch event. Subsequently, the processor 301 provides corresponding visual output on the display panel according to the type of touch event. In this embodiment, the touch panel and the display panel can be integrated into the display screen 303 to realize input and output functions. However, in some embodiments, the touch panel and the display panel can be implemented as two independent components to realize input and output functions. That is, the display screen 303 can also be used as part of the input unit 306 to realize input functions.

[0357] The radio frequency circuit 304 can be used to transmit and receive radio frequency signals to establish wireless communication with network devices or other electronic devices, and to transmit and receive signals with network devices or other electronic devices.

[0358] Audio circuitry 305 can be used to provide an audio interface between a user and an electronic device via a speaker and a microphone. Audio circuitry 305 converts received audio data into electrical signals, transmits them to the speaker, and the speaker converts them into sound signals for output. Conversely, the microphone converts collected sound signals into electrical signals, which are then received by audio circuitry 305, converted back into audio data, and then processed by processor 301 before being transmitted via radio frequency circuitry 304 to, for example, another electronic device, or output to memory 302 for further processing. Audio circuitry 305 may also include an earphone jack to facilitate communication between peripheral headphones and electronic devices.

[0359] The input unit 306 can be used to receive input numbers, characters, or object feature information (such as fingerprints, irises, facial information, etc.), and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control.

[0360] Power supply 307 is used to supply power to various components of electronic device 300. Optionally, power supply 307 can be logically connected to processor 301 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. Power supply 307 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0361] although Figure 7 As not shown in the diagram, the electronic device 300 may also include a camera, sensor, wireless fidelity module, Bluetooth module, etc., which will not be described in detail here.

[0362] This application also provides a computer-readable storage medium for storing a computer program. This computer-readable storage medium can be applied to a computer device, and the computer program causes the computer device to execute the corresponding process in the pre-planned processing method of the embodiments of this application; for the sake of brevity, further details are omitted here.

[0363] This application also provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the corresponding process in the pre-planned processing method in the embodiments of this application. For simplicity, further details are omitted here.

[0364] This application also provides a computer program comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the corresponding process in the proposed processing method of this application. For brevity, further details are omitted here.

[0365] It should be understood that the processor in this application may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0366] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0367] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0368] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0369] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0370] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0371] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0372] In addition, the functional units in this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0373] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer or a server) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0374] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A contingency plan handling method, characterized in that, The method includes: In response to meeting the exercise conditions of the target plan, the target system is controlled to execute the operation in the target plan to conduct the current round of exercise of the target plan, wherein the exercise conditions include the time difference from the previous round of the current round being greater than or equal to the exercise time interval corresponding to the target plan; After the target system executes the operation in the target plan, exercise-related data corresponding to the target plan is obtained. The exercise-related data includes first related data, second related data, and historical exercise evaluation results. The first related data includes operation execution success rate, execution time, and fault response parameters. The first related data is used to indicate the operating status of the target system in the current round. The second related data includes hardware configuration, software version, network bandwidth, and dependent service status. The second related data is used to indicate the operating environment of the target system when running according to the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round. Based on the first relevant data, a first exercise score of the target plan in the current round is generated, wherein the first exercise score is used to indicate the execution status of the target system in the current round in performing the operations in the target plan; Based on the second relevant data, a second exercise score of the target plan in the current round is generated, wherein the second exercise score is used to indicate the difference between the first operating environment and the second operating environment, the first operating environment is the operating environment of the target system in the current round, and the second operating environment is the operating environment of the target plan in the first round of exercise or before the first round of exercise; Based on the historical exercise evaluation results, the target plan is given a third exercise score in the current round. Based on the first exercise score, the second exercise score, and the third exercise score, the exercise effectiveness of the target plan in the current round is evaluated to obtain the exercise evaluation result of the target plan in the current round.

2. The contingency plan processing method according to claim 1, characterized in that, The target contingency plan is one of multiple executable contingency plans, each of which corresponds to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable contingency plan corresponding to the fault type of the detected fault. The step of controlling the target system to execute the operation in the target contingency plan in response to meeting the exercise conditions of the target contingency plan, to conduct the current round of exercise of the target contingency plan, includes: In response to meeting the exercise conditions of the target plan, the target system is subjected to fault injection processing according to the fault type corresponding to the target plan, wherein after the fault injection processing is performed on the target system, the target system detects the fault type corresponding to the target plan.

3. The contingency plan processing method according to claim 2, characterized in that, The target plan includes at least one operation, and the method further includes: After the target system executes each operation in the target plan, the target system is subjected to fault recovery processing according to the fault type corresponding to the target plan. After the fault recovery processing is performed on the target system, the target system cannot detect the fault type corresponding to the target plan.

4. The contingency plan processing method according to claim 1, characterized in that, The step of evaluating the effectiveness of the target plan in the current round of drills based on the first drill score, the second drill score, and the third drill score, to obtain the drill evaluation result of the target plan in the current round, includes: The target exercise score of the target plan in the current round is obtained by weighting and summing the first exercise score with the first weight corresponding to the first exercise score, the second exercise score with the second weight corresponding to the second exercise score, and the third exercise score with the third weight corresponding to the third exercise score. The target evaluation result corresponding to the target exercise score in the predetermined score-result mapping data is determined as the exercise evaluation result of the target plan in the current round. The score-result mapping data includes multiple scores and the evaluation result corresponding to each score.

5. The contingency plan processing method according to claim 4, characterized in that, The step of generating the third exercise score for the target contingency plan in the current round based on the historical exercise evaluation results includes: The third training score is obtained by weighted summing of the first training scores of multiple previous rounds preceding the current round and the weights corresponding to each previous round, wherein the weights corresponding to the previous rounds are negatively correlated with the round difference of the previous rounds, and the round difference is the difference between the previous rounds and the current round.

6. The contingency plan processing method according to claim 1, characterized in that, The target contingency plan is one of multiple executable contingency plans, each of which corresponds to at least one fault type of the target system. When the target system detects a fault, it executes the operation in the executable contingency plan corresponding to the fault type of the detected fault. The step of generating a first exercise score for the target contingency plan in the current round based on the first relevant data includes: Based on the first relevant data, a first sub-score, a second sub-score, and a third sub-score are generated. The first sub-score is used to indicate the difference between the fault type detected by the target system in the current round and the fault type corresponding to the target plan. The second sub-score is used to indicate the percentage of operations successfully executed by the target system among all operations included in the target plan. The third sub-score is used to indicate the difference between the operating state of the target system after executing the operations in the target plan and the expected state of the system corresponding to the target plan. The first exercise score is obtained by weighting and summing the first sub-score and its corresponding weight, the second sub-score and its corresponding weight, and the third sub-score and its corresponding weight.

7. A contingency plan processing device, characterized in that, The device includes: The control module is used to control the target system to execute the operation in the target plan in response to the exercise conditions of the target plan, so as to carry out the current round of exercise of the target plan, wherein the exercise conditions include the time difference from the previous round to the current round being greater than or equal to the exercise time interval corresponding to the target plan. The acquisition module is used to acquire exercise-related data corresponding to the target plan after the target system executes the operation in the target plan. The exercise-related data includes first related data, second related data, and historical exercise evaluation results. The first related data is used to indicate the operating status of the target system in the current round. The second related data is used to indicate the operating environment of the target system when running the target plan. The historical exercise evaluation results include the exercise evaluation results of at least one round before the current round. An evaluation module is used to generate a first exercise score for the target plan in the current round based on the first relevant data, wherein the first exercise score is used to indicate the execution status of the target system in the current round in performing the operations in the target plan; Based on the second relevant data, a second exercise score of the target plan in the current round is generated, wherein the second exercise score is used to indicate the difference between the first operating environment and the second operating environment, the first operating environment is the operating environment of the target system in the current round, and the second operating environment is the operating environment of the target plan in the first round of exercise or before the first round of exercise; Based on the historical exercise evaluation results, the target plan is given a third exercise score in the current round. Based on the first exercise score, the second exercise score, and the third exercise score, the exercise effectiveness of the target plan in the current round is evaluated to obtain the exercise evaluation result of the target plan in the current round.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing a computer program, and the processor executing the pre-processing method according to any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted for loading by a processor to execute the pre-processing method according to any one of claims 1-6.

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