Equipment emergency scheme determination method and device, equipment and medium

Abstract

The invention discloses an equipment emergency scheme determination method and device, equipment and a medium, and relates to the field of financial science and technology. The method comprises the steps of determining at least one emergency scheme corresponding to a current cluster according to acquired operation information corresponding to the current cluster; for each emergency scheme, determining scheme parameter items and weight coefficients of the emergency schemes according to the current cluster and operation information; according to the scheme parameter item and the weight coefficient of each emergency scheme, calculating to obtain an available probability corresponding to each emergency scheme; and according to the available probability corresponding to each emergency scheme, screening is carried out in each emergency scheme, and a target scheme is determined. According to the embodiment of the invention, the accuracy of determining the equipment emergency scheme can be improved.

Description

Technical Field

[0001] The present invention relates to the fields of data processing technology and financial technology, and in particular to a method, device, equipment and medium for determining an equipment emergency plan. Background Art

[0002] With the rapid development of science and technology, there are more and more types of electronic devices. However, clusters of electronic devices often fail during operation, and emergency processing is required to ensure the safety of cluster operation of electronic devices.

[0003] Currently, a target contingency plan is selected among a plurality of contingency plans according to a failure type of a cluster of electronic devices.

[0004] However, simply selecting a target emergency plan from multiple emergency plans based on the fault type results in a low screening accuracy. Summary of the invention

[0005] The present invention provides a method, device, equipment and medium for determining an equipment emergency plan, so as to improve the accuracy of determining an equipment emergency plan.

[0006] In a first aspect, an embodiment of the present invention provides a method for determining an equipment emergency plan, the method comprising:

[0007] Determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster;

[0008] For each emergency plan, determine the plan parameter items and weight coefficients of the emergency plan according to the current cluster and operation information;

[0009] According to the scheme parameter items and weight coefficients of each emergency plan, the availability probability corresponding to each emergency plan is calculated;

[0010] According to the available probability of each emergency plan, screen the emergency plans and determine the target plan.

[0011] In a second aspect, an embodiment of the present invention further provides a device for determining an emergency plan for equipment, the device comprising:

[0012] A plan acquisition module, used to determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster;

[0013] A data determination module is used to determine the scheme parameter items and weight coefficients of the emergency scheme according to the current cluster and operation information for each emergency scheme;

[0014] The probability calculation module is used to calculate the availability probability corresponding to each emergency plan according to the plan parameter items and weight coefficients of each emergency plan;

[0015] The scheme screening module is used to screen various emergency schemes according to the available probabilities corresponding to each emergency scheme and determine the target scheme.

[0016] In a third aspect, an embodiment of the present invention further provides a device for determining an emergency plan for a device, the device for determining an emergency plan for a device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by at least one processor so that the at least one processor can execute the device emergency plan determination method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the device emergency plan determination method of any embodiment of the present invention when executed.

[0021] The technical solution of the embodiment of the present invention determines at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster; for each emergency plan, determines the plan parameter items and weight coefficient of the emergency plan according to the current cluster and the operation information; calculates the available probability corresponding to each emergency plan according to the plan parameter items and the weight coefficient of each emergency plan; screens each emergency plan according to the available probability corresponding to each emergency plan to determine the target plan, screens each emergency plan through multi-dimensional data, and determines the optimal emergency plan, so as to maximize the cluster fault handling efficiency and be most suitable for the current operation status of the cluster, thereby improving the accuracy of determining the equipment emergency plan.

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

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

[0024] Figure 1is a flow chart of a method for determining an equipment emergency plan according to Embodiment 1 of the present invention;

[0025] Figure 2 is a flow chart of a method for determining an equipment emergency plan according to Embodiment 2 of the present invention;

[0026] Figure 3 is a structural diagram of a device for determining an emergency plan for equipment provided according to an embodiment of the present invention;

[0027] Figure 4 It is a structural diagram of a device for determining a device emergency plan provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] In the technical solutions of the embodiments of the present invention, the acquisition, storage and application of the operation information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0031] Embodiment 1

[0032] Figure 1 The present invention provides a flowchart of a method for determining a device emergency plan. The present invention is applicable to the case of determining a device emergency plan. The method can be executed by a device emergency plan determining device, which can be implemented in the form of hardware and / or software.

[0033] See also Figure 1 The method for determining the equipment emergency plan shown includes:

[0034] S101. Determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster.

[0035] Among them, cluster refers to connecting multiple independent computers (called nodes or servers) together so that they can perform tasks, process workloads or provide services as a whole. These computer nodes communicate and collaborate with each other through the network to share resources and workloads to achieve higher performance, reliability and scalability. The current cluster can be the cluster to be processed at the current time. Operation information can be records and descriptions of various data, states and events generated during the operation of the system, equipment, program or business corresponding to the current cluster. Emergency plan can refer to a series of plans and measures prepared in advance for emergencies, failures or emergencies that the cluster may face, aiming to ensure that the cluster can respond quickly and effectively when encountering problems, minimize losses and impacts, and ensure the normal operation of the cluster and the realization of related goals.

[0036] Specifically, the operation information corresponding to the current cluster is obtained, and the acquisition method includes but is not limited to: obtaining through monitoring tools, obtaining through a cluster management platform, or obtaining through viewing logs, and the embodiments of the present invention do not limit this. By collecting the operation information of the current cluster, the operation information is compared with the baseline data during normal operation to find out indicators that exceed the normal range or abnormal events, such as persistently high CPU utilization, a large number of error logs, or long service response time. According to the manifestation of the abnormal situation and related information, analyze the possible types of failures, clarify various emergency measures, and determine at least one emergency plan for the current cluster based on the operation information of the current cluster to ensure data integrity and consistency.

[0037] S102: For each emergency plan, determine the plan parameter items and weight coefficients of the emergency plan according to the current cluster and operation information.

[0038] The scheme parameter item can be used to describe the measures to be adjusted according to the emergency scheme. The weight coefficient can be used to describe the importance of the emergency scheme relative to the current cluster.

[0039] Specifically, different clusters correspond to different current operation information, and different operation information corresponds to different fault types. One fault type can correspond to multiple emergency plans, and different emergency plans correspond to different plan parameter items. Fault types include hardware failure (server failure, network device failure), software failure (application crash, system vulnerability), insufficient resources (memory exhaustion, full disk space), network problems (network interruption, high latency), etc. According to the impact of abnormal conditions on different nodes, services, and business processes in the cluster, determine the affected areas, user groups, and business functions, and judge the severity of the problem, such as whether it causes partial business interruption, data loss risk, or complete service unavailability. Measures for different fault types, for example, hardware failure: For server hardware failure, you can formulate plans such as enabling backup servers, hardware repair or replacement; if it is a network device failure, you can take measures such as checking network connections, restarting network devices, or replacing faulty network components. Software failure: When an application crashes, try to restart the application, roll back to the previous stable version, or fix software vulnerabilities; if there is a problem with the system software, you can perform system updates, patches, or restore system configurations. Insufficient resources: When memory or CPU resources are insufficient, consider expanding cluster nodes, adjusting resource allocation strategies, or optimizing applications to reduce resource consumption; when disk space is full, clean up useless files, delete logs, or expand disk capacity, etc. Network problems: When the network is interrupted, check the status of network equipment, troubleshoot line failures, or switch to backup network lines; when network latency is too high, optimize network configuration, adjust network bandwidth allocation, or check network congestion points, and determine the parameters and weight coefficients of each emergency plan.

[0040] S103: Calculate the availability probability of each emergency plan according to the plan parameter items and weight coefficients of each emergency plan.

[0041] Among them, the availability probability can be used to describe the accuracy of the emergency plan in handling the failure corresponding to the current cluster.

[0042] Specifically, different emergency plans correspond to different emergency measures to be operated, and the number of plan parameter items and the content of plan parameter items corresponding to different emergency plans are different. Different emergency plans correspond to different emergency measures, and the processing results of the faults corresponding to the current cluster are different, and the weight coefficients corresponding to different emergency plans are different. According to the number of plan parameter items, the content of plan parameter items and the weight coefficient of each emergency plan, the available probability corresponding to each emergency plan is calculated. The emergency plan corresponds to the available probability one by one. The higher the available probability, the better the emergency plan corresponding to the available probability is for the current cluster, and the emergency measures have the lowest interference ability on the results of other related services, ensuring the more stable operation of the current cluster; the lower the available probability, the worse the emergency plan corresponding to the available probability is for the current cluster, the emergency measures have a high interference ability on the results of other related services, and the accuracy of emergency processing is low.

[0043] S104. Screen the emergency plans according to the available probabilities corresponding to the emergency plans and determine the target plan.

[0044] The target plan may be used to describe a plan for preparing emergency response to the current cluster according to the plan content.

[0045] Specifically, different emergency plans correspond to different available probabilities. The available probabilities corresponding to the emergency plans are sorted, and the maximum available probability among the available probabilities corresponding to the emergency plans is screened. The emergency plan corresponding to the maximum available probability is determined as the target plan for solving the failure of the current cluster. The sorting method includes but is not limited to: bubble sort algorithm, selection sort algorithm, insertion sort algorithm, shell sort algorithm, merge sort algorithm, quick sort algorithm, heap sort algorithm or bucket sort algorithm, etc., which is not limited in the embodiment of the present invention.

[0046] The technical solution of the embodiment of the present invention determines at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster; for each emergency plan, determines the plan parameter items and weight coefficient of the emergency plan according to the current cluster and the operation information; calculates the available probability corresponding to each emergency plan according to the plan parameter items and the weight coefficient of each emergency plan; screens each emergency plan according to the available probability corresponding to each emergency plan to determine the target plan, screens each emergency plan through multi-dimensional data, and determines the optimal emergency plan, so as to maximize the cluster fault handling efficiency and be most suitable for the current operation status of the cluster, thereby improving the accuracy of determining the equipment emergency plan.

[0047] Embodiment 2

[0048] Figure 2This is a flow chart of a method for determining a device emergency plan provided in the second embodiment of the present invention. Based on the above embodiments, the embodiment of the present invention optimizes and improves the device emergency plan determination operation.

[0049] Further, "calculate the available probability corresponding to each emergency plan according to the plan parameter items and weight coefficients of each emergency plan" is refined into "for each emergency plan, obtain at least one plan parameter item corresponding to the emergency plan and the parameter value corresponding to each plan parameter item according to the current cluster and operation information; calculate the initial probability corresponding to the emergency plan according to the current cluster, operation information, each plan parameter item corresponding to the emergency plan and the parameter value corresponding to each plan parameter item; obtain the weight coefficient corresponding to the emergency plan according to the current cluster; calculate the available probability corresponding to the emergency plan according to the initial probability and weight coefficient corresponding to the emergency plan" to improve the operations determined by the equipment emergency plan.

[0050] It should be noted that for the parts not described in detail in the embodiments of the present invention, reference may be made to the descriptions of other embodiments.

[0051] See also Figure 2 The method for determining the equipment emergency plan shown includes:

[0052] S201. Determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster.

[0053] S202: For each emergency plan, determine the plan parameter items and weight coefficients of the emergency plan according to the current cluster and operation information.

[0054] S203 . For each emergency plan, obtain at least one plan parameter item corresponding to the emergency plan and parameter values ​​corresponding to each plan parameter item according to the current cluster and operation information.

[0055] Specifically, according to the cluster configuration information and operation information of the current cluster, determine the fault type corresponding to the current cluster, determine different emergency plans according to different fault types, and different emergency plans correspond to different plan parameter items, which are used to describe the items of emergency adjustment. Different emergency parameter items correspond to different parameter values, which are used to describe the adjustment content corresponding to the emergency adjustment items. For example, hardware failure: node redundancy can be increased, and multiple nodes can be deployed in the cluster. When some nodes fail, other nodes can continue to provide services. Software failure: Check the operating system and related software logs to determine the cause of the failure. Try to restart the related services or processes on the failed node; if it is an operating system problem, try to update, repair or reinstall the system. Use automated tools or scripts to quickly redeploy or configure the failed node to reduce the recovery time. Network connection interruption: Check the status and connection of network devices (such as switches and routers) to check whether there are problems such as loose ports and device failures. Restart the network device; if it is a network configuration error, adjust the network configuration in time. Configure multiple network routing paths to achieve network redundancy. When one path fails, data can be transmitted through other paths. Network congestion: Use network monitoring tools to monitor network traffic and determine the location and cause of congestion. Optimize network topology, increase network bandwidth, and allocate network resources reasonably; perform operations such as limiting network traffic to ensure network bandwidth for key businesses. Data loss or damage: Use data backup for recovery. According to the importance of the data and the recovery time requirements, choose full backup or incremental backup for recovery. If it is a system with transaction logs such as databases, transaction logs can be used to partially restore data to reduce data loss. Use multiple copies of storage or off-site disaster recovery for key data to prevent data from being permanently lost due to single point failures. Scheduling failure caused by insufficient resources: Increase cluster resources, such as adding nodes, expanding the CPU, memory and other resources of nodes; reasonably adjust resource allocation strategies, and reallocate resources according to business needs and priorities. Unreasonable scheduling algorithm: Evaluate the current scheduling algorithm, select a more appropriate scheduling algorithm based on the business characteristics and resource usage of the cluster; adjust the parameters of the scheduling algorithm, such as weight, priority, etc., to optimize the scheduling effect. Component configuration error: Check the configuration files of related components to ensure that the configuration parameters are correct; for complex configurations, configuration management tools can be used for management and deployment to ensure the consistency and accuracy of the configuration. Version control the configuration to facilitate rollback to the previous normal configuration version. Inconsistent environment configuration: Unify the operating system version, software version and other environment configurations of each node in the cluster; use automated deployment tools to install and configure the cluster environment to ensure environmental consistency.

[0056] S204. Calculate the initial probability corresponding to the emergency plan according to the current cluster, operation information, each plan parameter item corresponding to the emergency plan, and the parameter value corresponding to each plan parameter item.

[0057] Specifically, different scheme parameter items may correspond to different parameter values. When multiple schemes have the same scheme parameter items, and different emergency schemes' scheme parameter items correspond to different parameter values, the initial probabilities of the multiple schemes are different. Therefore, the configuration information of the current cluster, for example: the number of devices in the current cluster or the area where the current cluster is located, etc., has different configuration information corresponding to different current clusters. According to the configuration information of different current clusters and the operation information corresponding to the current cluster, the fault information corresponding to the current cluster can be determined, so as to obtain the emergency plan for the fault information of the current cluster. Different emergency plans may correspond to different numbers and types of scheme parameter items, as well as parameter values ​​corresponding to the scheme parameter items. According to the parameter values ​​of each emergency parameter item of each emergency plan, the initial probability corresponding to each emergency plan is determined.

[0058] S205. Obtain a weight coefficient corresponding to the emergency plan according to the current cluster.

[0059] Specifically, different emergency plans correspond to different emergency handling operations. Different current clusters have different operating information. Different clusters may correspond to different fault types. Different fault types correspond to different optimal emergency handling operations. Therefore, for the current cluster, different emergency plans correspond to different emergency operations, and different emergency plans correspond to different weight coefficients. One current cluster corresponds to at least one emergency plan. Emergency plans correspond to weight coefficients one to one.

[0060] S206. Calculate the availability probability corresponding to the emergency plan according to the initial probability and weight coefficient corresponding to the emergency plan.

[0061] Specifically, for the current cluster, at least one emergency plan for the current cluster is determined according to the configuration information and operation information of the current cluster. At least one emergency plan corresponding to the cluster is obtained. The emergency plan corresponds to the initial probability one by one, and the emergency plan corresponds to the weight coefficient one by one. For each emergency plan, the initial probability corresponding to the emergency plan is multiplied by the weight coefficient to obtain the available probability corresponding to each emergency plan. The larger the available probability of each emergency plan, the more suitable the emergency plan is for emergency handling of the current cluster; the smaller the available probability of each emergency plan, the less suitable the emergency plan is for emergency handling of the current cluster.

[0062] S207. Screen the emergency plans according to the available probabilities corresponding to the emergency plans and determine the target plan.

[0063] The embodiment of the present invention obtains, for each emergency plan, at least one plan parameter item corresponding to the emergency plan and the parameter value corresponding to each plan parameter item according to the current cluster and operation information; calculates the initial probability corresponding to the emergency plan according to the current cluster, operation information, each plan parameter item corresponding to the emergency plan and the parameter value corresponding to each plan parameter item; obtains the weight coefficient corresponding to the emergency plan according to the current cluster; calculates the available probability corresponding to the emergency plan according to the initial probability and weight coefficient corresponding to the emergency plan, analyzes each emergency parameter item of different emergency plans according to the real-time operation information of the current cluster, fine-grains the evaluation operation of the emergency plan, and improves the accuracy of emergency plan selection.

[0064] Optionally, the initial probability corresponding to the emergency plan is calculated based on the current cluster, operating information, each plan parameter item corresponding to the emergency plan, and the parameter value corresponding to each plan parameter item, including: for each plan parameter item, screening in the historical probability library corresponding to the current cluster based on the current cluster, operating information, each plan parameter item corresponding to the emergency plan, and the parameter value corresponding to the plan parameter item, to obtain the historical probability corresponding to the parameter value corresponding to the plan parameter item; multiplying the historical probabilities corresponding to the parameter values ​​corresponding to each plan parameter item of the emergency plan, to calculate the initial probability corresponding to the emergency plan.

[0065] The historical probability database can be used to describe a database storing probabilities acquired in historical time. The historical probability can be used to describe the probability corresponding to the parameter value corresponding to the solution parameter item in the historical time period.

[0066] Specifically, the configuration information of each cluster in the historical time, the fault information corresponding to each current cluster, and the emergency handling results of different emergency plans corresponding to the fault information of each current cluster are collected, and the available probabilities corresponding to the parameter values ​​of each plan parameter item corresponding to each cluster are calculated based on the collected historical information, and stored in the historical probability library. For each plan parameter item, the historical probability library corresponding to the current cluster is screened according to the current cluster, operation information, plan parameter items corresponding to the emergency plan, and parameter values ​​corresponding to the plan parameter items, to obtain the historical probabilities of the parameter values ​​corresponding to each plan parameter item corresponding to each current cluster. One current cluster corresponds to multiple emergency plans, one emergency plan corresponds to multiple emergency parameter items, emergency parameter items correspond to parameter values ​​one by one, and one emergency parameter item corresponds to one historical probability. Multiply the historical probabilities corresponding to the parameter values ​​corresponding to each plan parameter item of the emergency plan, and calculate the initial probability corresponding to the emergency plan.

[0067] By screening each plan parameter item in the historical probability library corresponding to the current cluster according to the current cluster, operation information, plan parameter items corresponding to the emergency plan and the parameter values ​​corresponding to the plan parameter items, the historical probability corresponding to the parameter values ​​corresponding to the plan parameter items is obtained; the historical probabilities corresponding to the parameter values ​​corresponding to each plan parameter item of the emergency plan are multiplied to calculate the initial probability corresponding to the emergency plan. The calculation method of the initial probability is fine-grained. By analyzing the historical probability corresponding to the parameter value of each plan parameter item, the initial probability is obtained through multi-dimensional data calculation, which improves the accuracy of the initial probability calculation.

[0068] Optionally, based on the current cluster, a weight coefficient corresponding to the emergency plan is obtained, including: based on the current cluster, obtaining at least one pending application corresponding to the emergency plan of the current cluster; combining the pending applications in pairs to obtain at least one application group; for each application group, calculating an application impact value corresponding to the application group; and determining the weight coefficient corresponding to the emergency plan of the current cluster based on the application impact values ​​of each application group corresponding to the emergency plan of the current cluster.

[0069] The pending application may be an application to be processed corresponding to the emergency plan of the current cluster. The application group may be a set of two pending applications. The application impact value may be the impact degree value of the change in configuration information of one application on the operation of another application.

[0070] Specifically, a current cluster corresponds to at least one application. When a fault occurs in the current cluster, the current cluster needs to adjust the configuration information of the application of the current cluster according to the emergency plan so that each application of the current cluster can run normally. According to the current cluster, at least one pending application corresponding to the emergency plan of the current cluster is obtained. Each pending application is combined in pairs to obtain at least one application group. For each application group, different applications are related to each other. When the configuration information of one application changes, it may affect the operation of another application. The application impact value corresponding to the application group is calculated according to each application group. If the application impact value between applications is larger, the degree of impact between applications is deeper. When the configuration information of one application changes, another application may not run normally; if the application impact value between applications is smaller, the degree of impact between applications is shallower. When the configuration information of one application changes, another application can run normally. The impact value between applications can be obtained by Analytic Hierarchy Process (AHP). An evaluation matrix is ​​established according to the application impact value of each application group corresponding to the emergency plan of the current cluster, and the value of the evaluation matrix is ​​determined as the weight coefficient corresponding to the emergency plan of the current cluster.

[0071] By obtaining at least one pending application corresponding to the emergency plan of the current cluster according to the current cluster; combining the pending applications in pairs to obtain at least one application group; and calculating the application impact value corresponding to each application group for each application group; determining the weight coefficient corresponding to the emergency plan of the current cluster according to the application impact value of each application group corresponding to the emergency plan of the current cluster, and determining the impact degree of the emergency plan on each application by calculating the impact degree between the influencing applications corresponding to the current cluster, the accuracy of the emergency plan determination is improved.

[0072] Optionally, based on the application impact values ​​of each application group corresponding to the emergency plan of the current cluster, a weight coefficient corresponding to the emergency plan of the current cluster is determined, including: obtaining at least one preset group and a preset impact value corresponding to each preset group; for each application group, comparing the application impact value of the application group with the preset impact value of the preset group corresponding to the application group to obtain a comparison result of the application group; based on the comparison result of the application group and the preset impact value of the preset group corresponding to the application group, adjusting the application impact value of the application group to determine the target impact value of the application group; based on the target impact values ​​of each application group corresponding to the emergency plan of the current cluster, the weight coefficient corresponding to the emergency plan of the current cluster is determined.

[0073] The preset group may be a set of preset applications. The preset impact value may be an impact value between applications in the preset group. The comparison result of the application group may be a result of comparing the application impact value of the application group with the preset impact value of the preset group corresponding to the application group. The target impact value may be an adjusted application impact value corresponding to the application group.

[0074] Specifically, at least one preset group and the preset impact value corresponding to each preset group are obtained, and the acquisition method can be obtained through industry experience. For each application group, the application impact value of the application group is compared with the preset impact value of the preset group corresponding to the application group to obtain the comparison result of the application group. The difference range can be preset. If the comparison result of the application group is within the difference range, it means that the application impact value of the application group is slightly different from the preset impact value of the preset group corresponding to the application group, and the application impact value of the application group is determined as the target impact value of the application group; if the comparison result of the application group is not within the difference range, it means that the application impact value of the application group is significantly different from the preset impact value of the preset group corresponding to the application group, and the preset impact value of the application group is determined as the target impact value of the application group. According to the target impact value of each application group corresponding to the emergency plan of the current cluster, the weight coefficient corresponding to the emergency plan of the current cluster is determined.

[0075] By obtaining at least one preset group and the preset influence value corresponding to each preset group; for each application group, comparing the application influence value of the application group with the preset influence value of the preset group corresponding to the application group, to obtain the comparison result of the application group; according to the comparison result of the application group and the preset influence value of the preset group corresponding to the application group, adjusting the application influence value of the application group, to determine the target influence value of the application group; according to the target influence value of each application group corresponding to the emergency plan of the current cluster, determining the weight coefficient corresponding to the emergency plan of the current cluster, correcting the application influence value through industry experience, avoiding the problem of inaccurate results caused by large calculation errors, and improving the accuracy of plan determination.

[0076] Optionally, the historical probability library corresponding to the current cluster is obtained through the following steps: obtaining at least one emergency event information corresponding to the current cluster; for each emergency event information, identifying the emergency event information to obtain at least one historical parameter item, a parameter value corresponding to each historical parameter item, and an emergency result; calculating the available probability corresponding to each parameter value of each historical parameter item based on each historical parameter item of each emergency event information, the parameter value corresponding to each historical parameter item, and the emergency result; storing each historical parameter item, each parameter value of each historical parameter item, and the available probability corresponding to each parameter value to obtain the historical probability library corresponding to the current cluster.

[0077] Specifically, at least one emergency event information corresponding to the current cluster is obtained, and one emergency event information includes: fault information corresponding to the cluster and at least one emergency measure and emergency result corresponding to different fault information. For each emergency event information, the emergency event information is identified to obtain at least one historical parameter item, a parameter value corresponding to each historical parameter item, and an emergency result. The identification method includes but is not limited to: a feedforward neural network, a feedback neural network, a convolutional neural network, a graph neural network, or a generative adversarial neural network, etc., which is not limited in the embodiment of the present invention. According to each historical parameter item of each emergency event information, the parameter value corresponding to each historical parameter item, and the emergency result, the available probability corresponding to each parameter value of each historical parameter item is calculated. The calculation method can be to calculate the available probability corresponding to each parameter value of each historical parameter item through a conditional probability algorithm. Each historical parameter item, each parameter value of each historical parameter item, and the available probability corresponding to each parameter value are stored to obtain a historical probability library corresponding to the current cluster.

[0078] By obtaining at least one emergency event information corresponding to the current cluster; for each emergency event information, identifying the emergency event information, obtaining at least one historical parameter item, the parameter value corresponding to each historical parameter item and the emergency result; calculating the available probability corresponding to each parameter value of each historical parameter item according to each historical parameter item of each emergency event information, the parameter value corresponding to each historical parameter item and the emergency result; storing each historical parameter item, each parameter value of each historical parameter item and the available probability corresponding to each parameter value, obtaining the historical probability library corresponding to the current cluster, determining the influence values ​​of different parameter items and parameter values ​​on the emergency result through historical information, thereby determining the available probabilities corresponding to different plans, and improving the accuracy of plan determination through analysis of historical real data.

[0079] Optionally, the operation information corresponding to the current cluster includes: fault information corresponding to the current cluster, the number of cluster devices, and application request traffic.

[0080] Specifically, the fault information corresponding to the current cluster can be used to describe the fault phenomenon, fault scope, fault time, and related events. Fault phenomenon: collect the specific manifestations of cluster failures from channels such as monitoring systems, log files, and user feedback, such as service interruption, slow response, and error information. Fault scope: clarify the scope of affected nodes, services, and business modules, and determine whether it is a local fault or an overall fault. Fault time: record the time when the fault occurred, the duration, and whether it is periodic. Related events: understand the operations, configuration changes, and hardware upgrades before and after the fault occurs. In order to analyze the cause of the fault through the cluster's fault information, and generate emergency plans based on the cause of the fault. The number of cluster devices describes the schedulable resource information of the cluster. A large number of devices: the resources that can be allocated in emergency processing are relatively abundant, and more spare devices can be put into use. By enabling a large number of spare devices, the faulty devices can be quickly replaced to maintain cluster operation. However, the complexity of resource allocation will also increase, and a more efficient resource management and scheduling system is needed to accurately find available devices and allocate them reasonably. Small number of equipment: The available backup resources are limited. Once a key device fails, the lack of sufficient replacement equipment may cause business interruption or serious performance degradation. However, resource allocation is relatively simple, and it is easy to quickly determine the equipment that can be used for emergency.

[0081] Large traffic: The system load will increase rapidly, which may cause slow server response, service interruption or even crash. The emergency plan should focus on quickly reducing the system load, such as adopting flow control measures to limit the number of requests per unit time; launching a downgrade strategy to temporarily shut down non-core businesses to release system resources; and quickly expanding resources, using the elastic expansion function of cloud computing to automatically increase server instances. Small traffic: The system load is relatively low, and the emergency plan can focus on ensuring the availability and stability of key services. The demand for rapid allocation and expansion of resources is not high, and it is more about troubleshooting the root cause of the fault to avoid the expansion of the problem. Read requests are the main pressure on cache and database reading. The emergency plan can focus on optimizing the cache strategy, increasing the cache hit rate, and reducing the pressure on the database. Write requests are the main ones: It may cause database write conflicts, transaction backlogs and other problems. The emergency plan needs to consider how to ensure data consistency and integrity, such as adopting distributed transaction solutions and queuing write requests.

[0082] By obtaining the fault information, number of cluster devices and application request traffic corresponding to the current cluster, it is convenient to comprehensively obtain the operating status and configuration information of each cluster corresponding to the current cluster, so as to generate at least one more accurate emergency plan for the current cluster in a targeted manner, facilitate cluster emergency handling, and improve the safety of cluster operation.

[0083] Embodiment 3

[0084] Figure 3 The schematic diagram of the structure of a device for determining a device emergency plan provided by the third embodiment of the present invention is shown. The embodiment of the present invention is applicable to the situation of determining a device emergency plan, the device can execute a method for determining a device emergency plan, and the device can be implemented in the form of hardware and / or software.

[0085] See also Figure 3 The device for determining an emergency plan for equipment shown in the figure comprises: a plan acquisition module 301, a data determination module 302, a probability calculation module 303 and a plan screening module 304, wherein:

[0086] A plan acquisition module 301 is used to determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster;

[0087] The data determination module 302 is used to determine the scheme parameter items and weight coefficients of the emergency scheme according to the current cluster and operation information for each emergency scheme;

[0088] The probability calculation module 303 is used to calculate the availability probability corresponding to each emergency plan according to the plan parameter items and weight coefficients of each emergency plan;

[0089] The plan screening module 304 is used to screen various emergency plans according to the availability probabilities corresponding to the emergency plans and determine the target plan.

[0090] The technical solution of the embodiment of the present invention determines at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster; for each emergency plan, determines the plan parameter items and weight coefficient of the emergency plan according to the current cluster and the operation information; calculates the available probability corresponding to each emergency plan according to the plan parameter items and the weight coefficient of each emergency plan; screens each emergency plan according to the available probability corresponding to each emergency plan to determine the target plan, screens each emergency plan through multi-dimensional data, and determines the optimal emergency plan, so as to maximize the cluster fault handling efficiency and be most suitable for the current operation status of the cluster, thereby improving the accuracy of determining the equipment emergency plan.

[0091] Optionally, the probability calculation module 303 includes:

[0092] A parameter value acquisition unit, used for acquiring, for each emergency plan, at least one plan parameter item corresponding to the emergency plan and a parameter value corresponding to each plan parameter item according to the current cluster and operation information;

[0093] An initial probability calculation unit, used to calculate the initial probability corresponding to the emergency plan according to the current cluster, operation information, each plan parameter item corresponding to the emergency plan and the parameter value corresponding to each plan parameter item;

[0094] A coefficient acquisition unit, used to acquire a weight coefficient corresponding to an emergency plan according to a current cluster;

[0095] The scheme probability acquisition unit is used to calculate the available probability corresponding to the emergency scheme according to the initial probability and weight coefficient corresponding to the emergency scheme.

[0096] Optionally, an initial probability calculation unit includes:

[0097] The library data screening subunit is used to screen each scheme parameter item in the historical probability library corresponding to the current cluster according to the current cluster, operation information, scheme parameter items corresponding to the emergency scheme, and parameter values ​​corresponding to the scheme parameter items, to obtain the historical probability corresponding to the parameter values ​​corresponding to the scheme parameter items;

[0098] The product acquisition subunit is used to multiply the historical probabilities corresponding to the parameter values ​​corresponding to the parameter items of each plan of the emergency plan, and calculate the initial probability corresponding to the emergency plan.

[0099] Optionally, a coefficient acquisition unit includes:

[0100] An application acquisition subunit, configured to acquire, according to a current cluster, at least one to-be-processed application corresponding to an emergency plan of the current cluster;

[0101] An application combination subunit, used for combining the applications to be processed in pairs to obtain at least one application group;

[0102] The influence value acquisition subunit is used to calculate the application influence value corresponding to each application group;

[0103] The weight coefficient determination subunit is used to determine the weight coefficient corresponding to the emergency plan of the current cluster according to the application impact value of each application group corresponding to the emergency plan of the current cluster.

[0104] Optionally, the weight coefficient determination subunit is specifically used for:

[0105] Obtain at least one preset group and a preset impact value corresponding to each preset group;

[0106] For each application group, compare the application impact value of the application group with the preset impact value of the preset group corresponding to the application group to obtain a comparison result of the application group;

[0107] According to the comparison result of the application group and the preset impact value of the preset group corresponding to the application group, the application impact value of the application group is adjusted to determine the target impact value of the application group;

[0108] According to the target impact value of each application group corresponding to the emergency plan of the current cluster, a weight coefficient corresponding to the emergency plan of the current cluster is determined.

[0109] Optionally, the historical probability library corresponding to the current cluster is obtained by the following steps:

[0110] Obtain at least one emergency event information corresponding to the current cluster;

[0111] For each emergency event information, the emergency event information is identified to obtain at least one historical parameter item, parameter values ​​corresponding to each historical parameter item, and an emergency result;

[0112] According to each historical parameter item of each emergency event information, the parameter value corresponding to each historical parameter item and the emergency result, the available probability corresponding to each parameter value of each historical parameter item is calculated;

[0113] Each historical parameter item, each parameter value of each historical parameter item and the available probability corresponding to each parameter value are stored to obtain a historical probability library corresponding to the current cluster.

[0114] Optionally, the operation information corresponding to the current cluster includes: fault information corresponding to the current cluster, the number of cluster devices, and application request traffic.

[0115] The device for determining an equipment emergency plan provided in the embodiment of the present invention can execute the method for determining an equipment emergency plan provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method for determining an equipment emergency plan.

[0116] Embodiment 4

[0117] Figure 4 A schematic structural diagram of a device emergency plan determination device 400 that can be used to implement an embodiment of the present invention is shown.

[0118] like Figure 4 As shown, the device 400 for determining a device for a device emergency plan includes at least one processor 401, and a memory connected to the at least one processor 401 in communication, such as a read-only memory (ROM) 402, a random access memory (RAM) 403, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 401 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 402 or the computer program loaded from the storage unit 408 to the random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 for determining a device emergency plan can also be stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0119] Multiple components in the device contingency plan determination device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device contingency plan determination device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0120] Processor 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. Processor 401 executes the various methods and processes described above, such as a device emergency plan determination method.

[0121] In some embodiments, the device contingency plan determination method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device contingency plan determination device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the processor 401, one or more steps of the device contingency plan determination method described above may be performed. Alternatively, in other embodiments, the processor 401 may be configured to perform the device contingency plan determination method in any other appropriate manner (e.g., by means of firmware).

[0122] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0124] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0125] To provide interaction with a user, the systems and techniques described herein may be implemented on a device contingency plan determination device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) through which a user can provide input to the device contingency plan determination device. Other types of devices may also be used to provide interaction with a user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0126] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0127] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS (Virtual Private Server) services.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0129] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining an equipment emergency plan, characterized in that: The method comprises: Determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster; For each of the emergency plans, determining a plan parameter item and a weight coefficient of the emergency plan according to the current cluster and the operation information; Calculate the availability probability of each emergency plan according to the plan parameter items and weight coefficients of each emergency plan; According to the availability probabilities corresponding to the emergency plans, the emergency plans are screened to determine the target plan.

2. The method according to claim 1, characterized in that The method of calculating the availability probability corresponding to each emergency plan according to the plan parameter items and weight coefficients of each emergency plan includes: For each of the emergency plans, obtaining at least one plan parameter item corresponding to the emergency plan and a parameter value corresponding to each of the plan parameter items according to the current cluster and the operation information; The initial probability corresponding to the emergency plan is calculated according to the current cluster, the operation information, each of the plan parameter items corresponding to the emergency plan, and the parameter value corresponding to each of the plan parameter items; According to the current cluster, obtaining a weight coefficient corresponding to the emergency plan; The available probability corresponding to the emergency plan is calculated based on the initial probability and weight coefficient corresponding to the emergency plan.

3. The method according to claim 2, characterized in that The calculating the initial probability corresponding to the emergency plan according to the current cluster, the operation information, each plan parameter item corresponding to the emergency plan, and the parameter value corresponding to each plan parameter item includes: For each of the scheme parameter items, screening is performed in the historical probability library corresponding to the current cluster according to the current cluster, the operation information, the scheme parameter item corresponding to the emergency scheme, and the parameter value corresponding to the scheme parameter item, to obtain the historical probability corresponding to the parameter value corresponding to the scheme parameter item; The historical probabilities corresponding to the parameter values ​​corresponding to the parameter items of the emergency plan are multiplied to calculate the initial probability corresponding to the emergency plan.

4. The method according to claim 2, characterized in that: The step of obtaining a weight coefficient corresponding to the emergency plan according to the current cluster includes: According to the current cluster, obtaining at least one to-be-processed application corresponding to the emergency plan of the current cluster; Combining the to-be-processed applications in pairs to obtain at least one application group; For each of the application groups, calculating an application impact value corresponding to the application group; A weight coefficient corresponding to the emergency plan of the current cluster is determined according to the application impact value of each of the application groups corresponding to the emergency plan of the current cluster.

5. The method according to claim 4, characterized in that The determining, according to the application impact value of each application group corresponding to the emergency plan of the current cluster, a weight coefficient corresponding to the emergency plan of the current cluster includes: Obtaining at least one preset group and a preset impact value corresponding to each of the preset groups; For each of the application groups, comparing the application impact value of the application group with the preset impact value of the preset group corresponding to the application group, to obtain a comparison result of the application group; According to the comparison result of the application group and the preset impact value of the preset group corresponding to the application group, the application impact value of the application group is adjusted to determine the target impact value of the application group; A weight coefficient corresponding to the emergency plan of the current cluster is determined according to the target impact value of each of the application groups corresponding to the emergency plan of the current cluster.

6. The method according to claim 2, characterized in that The historical probability library corresponding to the current cluster is obtained by the following steps: Obtain at least one emergency event information corresponding to the current cluster; For each of the emergency event information, the emergency event information is identified to obtain at least one historical parameter item, a parameter value corresponding to each of the historical parameter items, and an emergency result; Calculate the available probability corresponding to each parameter value of each historical parameter item according to each historical parameter item of the emergency event information, the parameter value corresponding to each historical parameter item and the emergency result; Each of the historical parameter items, each of the parameter values ​​of the historical parameter items, and the available probabilities corresponding to each of the parameter values ​​are stored to obtain a historical probability library corresponding to the current cluster.

7. The method according to claim 1, characterized in that The operation information corresponding to the current cluster includes: fault information corresponding to the current cluster, the number of cluster devices and application request traffic.

8. A device for determining an equipment emergency plan, characterized in that: The device comprises: A plan acquisition module, used to determine at least one emergency plan corresponding to the current cluster according to the acquired operation information corresponding to the current cluster; A data determination module, for determining, for each of the emergency plans, plan parameter items and weight coefficients of the emergency plan according to the current cluster and the operation information; A probability calculation module, used to calculate the availability probability corresponding to each of the emergency plans according to the plan parameter items and weight coefficients of each of the emergency plans; The scheme screening module is used to screen the emergency schemes according to the available probabilities corresponding to the emergency schemes and determine the target scheme.

9. A device for determining an equipment emergency plan, characterized in that: The equipment emergency plan determination device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the device contingency plan determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the device emergency plan determination method according to any one of claims 1 to 7 when executed.

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