Equipment off-shelf risk control method and device, electronic equipment and storage medium

Abstract

The invention discloses an equipment off-shelf risk control method and device, electronic equipment and a storage medium. The method comprises the following steps: generating an equipment topology according to a dependency relationship between equipment on shelf, and generating a business topology according to an association relationship between businesses; target equipment needing to be taken off is determined, and the equipment health degree of the target equipment is determined based on the health index of the target equipment; determining a physical topology dependency degree of the target device based on the device topology; determining a business topology dependency degree of the target device based on the business topology; generating a risk assessment result of the target equipment based on the equipment health degree, the physical topology dependency degree and the business topology dependency degree; and generating risk control suggestions of the off-shelf target equipment according to the risk assessment result. The risk in the equipment unloading process is effectively identified and controlled, and the safety and reliability of the equipment unloading process are ensured.

Description

Technical Field

[0001] This application relates to the field of computer technology, and particularly to a method and device for controlling the risk of equipment removal, an electronic device, and a storage medium. Background Art

[0002] With the rapid development of information technology, the scale and complexity of data centers have been continuously increasing, and the management of equipment removal has become a key link in ensuring the stability and security of the system. In the related art, the risk control of equipment removal operations in data centers mainly relies on simple business records and manual experience judgments, making it difficult to effectively prevent systematic risks caused by improper equipment operations.

[0003] Therefore, how to effectively identify and control the risks in the process of equipment removal and ensure the safety and reliability of the equipment removal process is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] This application provides a method and device for controlling the risk of equipment removal, an electronic device, and a storage medium, which can effectively identify and control the risks in the process of equipment removal and ensure the safety and reliability of the equipment removal process.

[0005] This application provides a method for controlling the risk of equipment removal, including:

[0006] Generating an equipment topology based on the dependency relationships between the already installed equipment, and generating a service topology based on the association relationships between the services;

[0007] Determining the target equipment to be removed, and determining the equipment health of the target equipment based on the health indicators of the target equipment;

[0008] Determining the physical topology dependency of the target equipment based on the equipment topology;

[0009] Determining the service topology dependency of the target equipment based on the service topology;

[0010] Generating a risk assessment result of the target equipment based on the equipment health, physical topology dependency, and service topology dependency;

[0011] Generating a risk control recommendation for removing the target equipment according to the risk assessment result.

[0012] This application also provides a device for controlling the risk of equipment removal, including:

[0013] A first generation module, configured to generate an equipment topology based on the dependency relationships between the already installed equipment, and generate a service topology based on the association relationships between the services;

[0014] The first determination module is used to determine the target device to be taken off the shelf, and determine the device health of the target device based on the health indicators of the target device;

[0015] The second determination module is used to determine the physical topology dependency of the target device based on the device topology;

[0016] The third determination module is used to determine the business topology dependency of the target device based on the business topology;

[0017] The second generation module is used to generate a risk assessment result of the target device based on the device health, physical topology dependency, and business topology dependency;

[0018] The third generation module is used to generate risk control suggestions for taking off the target device from the shelf according to the risk assessment result.

[0019] This application also provides an electronic device, including: a memory for storing a computer program; a processor for implementing the steps of any of the above device off-shelf risk control methods when executing the computer program.

[0020] This application also provides a computer-readable storage medium, in which a computer program is stored, and the computer program implements the steps of any of the above device off-shelf risk control methods when executed by a processor.

[0021] This application also provides a computer program product, including a computer program, and the computer program implements the steps of any of the above device off-shelf risk control methods when executed by a processor.

[0022] This application comprehensively considers three dimensions of device health, physical topology dependency, and business topology dependency, generates a risk assessment result of the target device, and generates risk control suggestions for taking off the shelf accordingly, effectively solving the problems in the prior art such as relying on manual experience, lacking real-time risk assessment, and single risk assessment dimension. First, by automatically generating device topology and business topology, it can accurately identify the dependency relationship between devices and the association relationship between services, avoiding the subjectivity and misjudgment of manual judgment and improving the accuracy of risk assessment. Second, based on real-time device health indicators, physical topology dependency, and business topology dependency for risk assessment, it realizes real-time monitoring and dynamic adjustment of the risk of taking off the device from the shelf, can timely discover potential risks and take corresponding measures, and enhances the stability and reliability of the system. Finally, the multi-dimensional risk assessment method can comprehensively reflect the impact of taking off the device from the shelf on the system, provides a more scientific and comprehensive decision-making basis for operation and maintenance personnel, helps to optimize the device off-shelf operation plan, reduce operation and maintenance costs, and improve operation and maintenance efficiency. This application also discloses a device off-shelf risk control device, an electronic device, a computer-readable storage medium, and a computer program product, which can also achieve the above technical effects.

[0023] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] To more clearly illustrate the embodiments of this application, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0025] Figure 1 It is a flowchart of a method for controlling the risk of equipment removal according to an exemplary embodiment;

[0026] Figure 2 It is a structural diagram of a system for controlling the risk of equipment removal in an application embodiment provided by this application;

[0027] Figure 3 It is a structural diagram of an information collection module in an application embodiment provided by this application;

[0028] Figure 4 It is a structural diagram of an equipment topology relationship module in an application embodiment provided by this application;

[0029] Figure 5 It is a structural diagram of a risk assessment module in an application embodiment provided by this application;

[0030] Figure 6 It is a structural diagram of a device for controlling the risk of equipment removal according to an exemplary embodiment;

[0031] Figure 7 It is a structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only some embodiments of this application, rather than all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0033] It should be noted that in the description of this application, the terms "including", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. The terms "first", "second", etc. in this application are used to distinguish similar objects and not to describe a specific order or sequence.

[0034] To enable those skilled in the art of this technology to better understand the solution of this application, the following further detailed description of this application will be given in conjunction with the accompanying drawings and specific embodiments.

[0035] An embodiment of this application provides a method for controlling the risk of equipment removal. In combination with the execution process of the method for controlling the risk of equipment removal, the method will be described in detail.

[0036] See Figure 1 , a flowchart of a method for controlling the risk of equipment removal shown according to an exemplary embodiment, as Figure 1 shown, includes:

[0037] S101: Generate an equipment topology based on the dependency relationships between the already installed equipment, and generate a service topology based on the association relationships between the services;

[0038] Among them, the equipment topology describes the connection relationships and interaction patterns between the equipment in the data center, reflecting the physical or logical dependencies between the equipment. The service topology reflects the mutual dependency relationships between different services, as well as the mapping relationships between the services and the equipment.

[0039] In this step, through network management and monitoring tools, obtain the connection information between the equipment, including but not limited to the connection status of network interfaces, traffic flow directions, etc., so as to construct the topology structure between the equipment. At the same time, analyze the data interaction patterns and dependency relationships between the services, and combine the service-bearing situations of the equipment to generate a service topology. This process can be completed by automated tools or optimized in combination with manually input service rules.

[0040] Generating the equipment topology and the service topology can provide a comprehensive view of the dependency relationships for subsequent risk assessment, helping the operation and maintenance personnel to more clearly understand the complex relationships between the equipment and the services, and thus more accurately evaluate the possible impacts brought by the removal of the equipment.

[0041] S102: Determine the target equipment to be removed, and determine the equipment health of the target equipment based on the health indicators of the target equipment;

[0042] Among them, the target device refers to the device that needs to be taken off the shelf, and the device health indicates the health status of the device. The value range is [0, 1], and the larger the value, the healthier the device.

[0043] In this step, the operation data of the target device, such as performance indicators, fault alarms, etc., are collected through the monitoring system, and these data are analyzed and processed to generate a quantitative score of the device health. This process can adopt various algorithms, such as rule-based evaluation, machine learning models, etc., to adapt to different application scenarios and requirements.

[0044] Accurately evaluating the health of the target device in this step can help the operation and maintenance personnel understand the operation status of the device before taking it off the shelf, so as to better evaluate the risks of the take-off operation and avoid additional risks caused by device failures.

[0045] S103: Determine the physical topology dependency of the target device based on the device topology;

[0046] Among them, the physical topology dependency indicates the degree of dependency of the device in the device topology relationship. The value range is [0, 1], and the larger the value, the higher the degree of dependency.

[0047] In this step, analyze the position and connection relationship of the target device in the device topology, and evaluate its degree of dependency on other devices. The physical topology dependency can be comprehensively obtained by calculating factors such as the number of devices directly connected to the target device and the importance of the links.

[0048] By quantifying the physical topology dependency in this step, the operation and maintenance personnel can more intuitively understand the importance of the target device in the data center network, and thus take more cautious measures when taking it off the shelf to avoid adverse effects on the network connection.

[0049] As a feasible implementation method, determining the physical topology dependency of the target device based on the device topology includes: determining the importance score of the links in the device topology; calculating the sum of the importance scores of the target links directly connected to the target device, and calculating the sum of the importance scores of all links in the device topology; calculating the ratio between the sum of the importance scores of the target links and the sum of the importance scores of all links as the physical topology dependency of the target device.

[0050] In specific implementation, the importance score of the link is determined based on its role and influence in the data center network. For example, factors such as the bandwidth, traffic, type of connected devices, and whether there is redundancy of the link may affect its importance score. By analyzing these factors, a quantitative importance score can be assigned to each link, providing basic data for subsequent dependency calculation.

[0051] As a feasible implementation, determining the importance score of a link in a device topology includes: determining the importance score of a link based on the bandwidth and traffic of the link in the device topology.

[0052] In a specific implementation, determining the importance score of a link in a device topology can be achieved by analyzing the bandwidth and traffic of the link. Bandwidth and traffic are key metrics for measuring link performance and load, and can reflect the importance of a link in a data center network. Specifically, links with higher bandwidths can generally support more data transmission, which is crucial for maintaining the efficient operation of the network; while links with higher traffic indicate that they undertake more data interaction tasks in the current network environment and are key paths for network communication. Therefore, by comprehensively considering the bandwidth and traffic of a link, a quantitative importance score can be assigned to each link. For example, certain weights can be assigned to the bandwidth and traffic of a link respectively, and then the importance score of the link can be calculated by weighted summation. This scoring method can intuitively reflect the importance of a link in the network and provide a scientific basis for subsequent risk assessment and decision-making.

[0053] Next, calculate the sum of the importance scores of the links directly connected to the target device (target links). This step is to traverse the device topology, find all the links directly connected to the target device, and add up their importance scores. This sum reflects the degree of dependence of the target device on its directly connected links, that is, the local dependence degree.

[0054] At the same time, it is also necessary to calculate the sum of the importance scores of all links in the entire device topology. This step involves traversing all the links in the entire data center network and adding up their importance scores. This sum provides a global view of the importance of all network links and serves as a reference for subsequent dependence calculation.

[0055] Finally, by calculating the ratio between the sum of the importance scores of the target links and the sum of the importance scores of all links, the physical topology dependence degree of the target device is obtained. This ratio reflects the relative dependence degree of the target device in the entire data center network. The higher the physical topology dependence degree, the higher the criticality of the target device in the data center network, and more caution is required when taking it off the shelf.

[0056] The calculation formula for the physical topology dependence degree is:

[0057] ;

[0058] where, is the physical topology dependence degree of the target device ; is the set of links in the device topology, is the device in the device topology, The importance score of a device in the device topology is the set of target links is a target link is a target link and its importance score

[0059] By quantifying the importance score of the link and calculating the physical topology dependency of the target device, this implementation method can accurately evaluate the criticality of the target device in the data center network. This method not only considers the local dependency relationship of the target device but also combines the global link importance distribution, providing a scientific basis for the risk assessment of device removal operations.

[0060] S104: Determine the service topology dependency of the target device based on the service topology;

[0061] Among them, the service topology dependency represents the importance level of the service to which the device belongs, and its value range is [0, 1]. The larger the value, the more important the service.

[0062] In this step, combined with the service topology, analyze the criticality of the services carried by the target device and the dependency relationships between these services and other services. The service topology dependency of the target device can be calculated by evaluating factors such as the priority of the service and the data interaction frequency.

[0063] This step clarifies the service topology dependency of the target device, which helps the operation and maintenance personnel fully consider the impact of service continuity when removing the device, prioritize ensuring the stable operation of critical services, and reduce the potential risks to the services.

[0064] As a feasible implementation method, determining the service topology dependency of the target device based on the service topology includes: determining the importance score of the services in the service topology; determining the set of target services associated with the target device; and determining the service topology dependency of the target device based on the correlation coefficients between the target services in the set of target services and the importance scores of the services in the service topology.

[0065] In specific implementation, first, it is necessary to determine the importance scores of each service in the service topology. The importance score of a service reflects the criticality of the service in the overall system and can usually be determined based on factors such as the type of service, the impact on users, and the transaction volume of the service. For example, the core business system may have a relatively high importance score because it directly affects the key operations of the enterprise.

[0066] Next, determine the set of target services associated with the target device. This step involves identifying all the services supported by the target device and the interdependency relationships between these services. By analyzing the service topology, it is possible to clarify which services depend on the target device and the call relationships between these services.

[0067] Finally, based on the correlation coefficients between the target services in the target service set and the importance scores of the services, calculate the service topology dependency of the target device. The correlation coefficient is used to measure the dependency strength between services. For example, if one service highly depends on another service, the correlation coefficient is relatively high. By comprehensively considering the importance scores of each service in the target service set and the correlation coefficients between them, the dependency degree of the target device at the service level can be quantified. This method can help the operation and maintenance personnel more comprehensively evaluate the impact of device decommissioning on services, so as to formulate more reasonable operation strategies.

[0068] As a feasible implementation, determining the service topology dependency of the target device based on the correlation coefficients between the target services in the target service set and the importance scores of the services in the service topology includes: determining the service topology dependency of the target device based on the service topology dependency calculation formula; wherein, the service topology dependency calculation formula is:

[0069] ;

[0070] wherein, is the service topology dependency of the target device , is the set of services in the service topology, is a service in the service topology, is the importance score of the service in the service topology, is the target service set, , are the target services associated with the target device, is the target service 's importance score, is the target service and the target service 's correlation coefficient, indicating the influence degree of the target service on the target service , and the value ranges from 0 to 1.

[0071] It can be seen that the above implementation not only considers the importance scores of the services, but also considers the correlation between the target services, improving the accuracy of calculating the service topology dependency.

[0072] As a preferred implementation, after determining the service topology dependency of the target device based on the correlation coefficients between different target services in the target service set and the importance scores of the services in the service topology, it further includes: normalizing the service topology dependency of the target device.

[0073] ​​In specific implementation, the business topology dependency degree of the target device is normalized. Normalization is a process of scaling data to a range of (0, 1), aiming to eliminate the differences in dimension and magnitude between different business dependency degrees, enabling them to be compared on a unified scale. Through normalization, it can be ensured that the calculation results of the business topology dependency degree are not affected by extreme values, thereby improving the stability and accuracy of the evaluation. In addition, the normalized dependency degree value can more intuitively reflect the relative importance of the target device in the business topology, facilitating the operation and maintenance personnel to make trade-offs and optimizations in the decision-making of device removal from the rack.

[0074] As a feasible implementation method, normalizing the business topology dependency degree of the target device includes: normalizing the business topology dependency degree of the target device based on the normalization formula; where the normalization formula is:

[0075] ;

[0076] where, is the business topology dependency degree of the target device , is the business topology dependency degree of the target device after normalization processing, is the maximum value of the business topology dependency degrees of all devices, is the minimum value of the business topology dependency degrees of all devices.

[0077] S105: Generate a risk assessment result for the target device based on the device health degree, physical topology dependency degree, and business topology dependency degree;

[0078] where the risk assessment result is the result of quantitatively evaluating the risk of the removal operation of the target device after comprehensively considering the device health degree, physical topology dependency degree, and business topology dependency degree.

[0079] In this step, the device health degree, physical topology dependency degree, and business topology dependency degree are used as input parameters, and through a preset risk assessment model for comprehensive calculation, the risk assessment result of the target device is obtained. The risk assessment model can be adjusted and optimized according to actual needs to adapt to different data center environments.

[0080] This step comprehensively evaluates multiple key factors of the target device, can more comprehensively and accurately reflect the risk of the device removal operation, provides a reliable decision-making basis for the operation and maintenance personnel, and helps them formulate a more reasonable removal strategy.

[0081] As a feasible implementation, a risk assessment result of the target device is generated based on the device health, physical topology dependency, and service topology dependency, including: assigning different weighting coefficients to the device health, physical topology dependency, and service topology dependency, and performing weighted processing on the device health, physical topology dependency, and service topology dependency based on the weighting coefficients to generate a risk score of the target device; wherein, the risk score is positively correlated with the physical topology dependency and the service topology dependency, and the risk score is negatively correlated with the device health.

[0082] In a specific implementation, generating the risk assessment result of the target device can be achieved by performing weighted processing on the device health, physical topology dependency, and service topology dependency. First, different weighting coefficients are assigned to the device health, physical topology dependency, and service topology dependency. These weighting coefficients reflect the relative importance of each factor in the risk assessment and can be adjusted according to the actual application scenario and requirements. For example, if the business continuity requirement of the data center is relatively high, the weighting coefficient of the service topology dependency may be set higher. After determining the weighting coefficients, the device health, physical topology dependency, and service topology dependency are respectively multiplied by their corresponding weighting coefficients, and the results are added together to generate the risk score of the target device. This weighted processing method can comprehensively consider the impacts of multiple key factors on the risk of removing the device from the rack, making the risk assessment more comprehensive and accurate.

[0083] It should be noted that the risk score is positively correlated with the physical topology dependency and the service topology dependency, which means that the higher the physical topology dependency and the service topology dependency, the higher the risk of removing the target device from the rack. This is because the higher the criticality of the device in the physical topology and the service topology, the greater the impact of its removal on the system. On the contrary, the risk score is negatively correlated with the device health, that is, the higher the device health, the lower the risk of its removal from the rack. This is because a healthy device is less likely to cause failures or other problems when removed from the rack.

[0084] The risk score generated in this way can provide a quantitative risk indicator for the target device removal for the operation and maintenance personnel, helping them better evaluate the feasibility and risk level of the device removal operation, so as to formulate more reasonable operation and maintenance strategies.

[0085] As a feasible implementation, generating the risk score of the target device includes: generating the risk score of the target device based on the risk score calculation formula; wherein, the risk score calculation formula is:

[0086] ;

[0087] Wherein, is the risk score of the target device of the target device is the target device The physical topology dependency degree, is the business topology dependency degree of the target device The business topology dependency degree, is the device health degree of the target device The device health degree, , , are respectively the weighting coefficients corresponding to the device health degree, the physical topology dependency degree, and the business topology dependency degree. , , The sum of them is 1. For example, is 0.4, is 0.4, is 0.2.

[0088] S106: Generate risk control suggestions for taking the target device off the shelf according to the risk assessment result.

[0089] Among them, the risk control suggestions are specific suggestions for equipment off - shelf operations provided to operation and maintenance personnel based on the risk assessment result, including operation timing, priority, etc.

[0090] In this step, according to the risk assessment result, combined with the operation and maintenance strategy and business requirements of the data center, targeted risk control suggestions are generated. For example, for high - risk devices, it is recommended to perform off - shelf operations during the low - peak period of business, and make backups and emergency preparations in advance.

[0091] It can be seen that this step can provide specific risk control suggestions, which can help operation and maintenance personnel take more targeted measures when performing equipment off - shelf operations, reduce operation risks, and ensure the stable operation of the data center.

[0092] As a feasible implementation method, generating risk control suggestions for taking the target device off the shelf according to the risk assessment result includes: determining the priority of taking the target device off the shelf according to the risk score; among them, the priority is negatively correlated with the risk score.

[0093] In specific implementation, when generating risk control suggestions for taking the target device off the shelf according to the risk assessment result, the priority of taking it off the shelf is determined based on the risk score of the device. Specifically, the priority is negatively correlated with the risk score, that is, the lower the risk score of the device, the higher its off - shelf priority. The core idea of this strategy is to give priority to dealing with devices that have less impact on the system, so as to efficiently complete the equipment off - shelf operation on the premise of ensuring the overall stability and business continuity of the data center.

[0094] In actual operation, the operation and maintenance personnel can classify devices into different priority categories according to the risk score. For example, low-risk devices (R < 0.3) can be set as high priority. Since the removal of these devices has little impact on the system, they can be operated preferentially. Medium-risk devices (0.3 < R < 0.6) are medium priority. Removing them has a certain impact on the system, so cautious operation is required. High-risk devices (0.6 < R < 0.9) are low priority. Removing these devices has a greater impact on the system, so strict evaluation is needed. Extremely high-risk devices (R ≥ 0.9) are extremely high priority. Removing these devices may cause serious system failures and are prohibited from being operated. In this way, the operation and maintenance personnel can reasonably arrange the work plan and avoid potential system failures or business interruptions caused by removing high-risk devices.

[0095] In addition, this priority classification method based on risk scores can also help the operation and maintenance team optimize resource allocation. For example, for low-risk devices with high priority, less resources and time can be allocated for the preparation work before removal; while for high-risk devices with low priority, more effort needs to be invested in risk assessment, backup operations, and the formulation of contingency plans. In this way, the operation and maintenance team can maximize the reduction of the overall risk of device removal operations with limited resources and ensure the stable operation of the data center.

[0096] As a feasible implementation method, after generating the risk assessment result of the target device based on the device health degree, physical topology dependency, and business topology dependency, it includes: displaying the target business associated with the target device; where the target business is the business affected by removing the target device.

[0097] In specific implementation, after generating the risk assessment result of the target device, further display the target business associated with the target device, which are the businesses that may be affected by removing the target device. This approach can help the operation and maintenance personnel intuitively understand the specific impact of device removal operations on the business, so as to better assess risks and formulate corresponding risk control suggestions.

[0098] By displaying the affected business, the operation and maintenance personnel can clearly identify which businesses depend on the target device and the importance of these businesses in the overall business process, providing support for subsequent risk control suggestions. For example, if the removal of a certain device may have a significant impact on key business functions, the operation and maintenance personnel can give priority to taking measures to reduce this risk, such as making data backups in advance, formulating contingency plans, or adjusting business processes. This method can ensure that the continuity and stability of key businesses are maximally guaranteed during the device removal process, and at the same time provide more comprehensive decision-making support for the operation and maintenance team.

[0099] In the embodiments of the present application, by comprehensively considering three dimensions of device health, physical topology dependency, and service topology dependency, a risk assessment result of the target device is generated, and a risk control recommendation for taking the device off the shelf is generated accordingly, effectively solving problems such as relying on manual experience, lacking real-time risk assessment, and having a single risk assessment dimension in the prior art. First, by automatically generating the device topology and service topology, the dependency relationships between devices and the association relationships between services can be accurately identified, avoiding the subjectivity and misjudgment of manual judgment and improving the accuracy of risk assessment. Second, based on real-time device health indicators, physical topology dependency, and service topology dependency for risk assessment, real-time monitoring and dynamic adjustment of the risk of taking the device off the shelf are realized, potential risks can be discovered in a timely manner and corresponding measures can be taken, enhancing the stability and reliability of the system. Finally, the multi-dimensional risk assessment method can comprehensively reflect the impact of taking the device off the shelf on the system, providing a more scientific and comprehensive decision-making basis for operation and maintenance personnel, helping to optimize the operation plan for taking the device off the shelf, reducing operation and maintenance costs, and improving operation and maintenance efficiency.

[0100] On the basis of the above embodiments, as a preferred implementation manner, during the process of taking the device off the shelf, the device status and service operation conditions are monitored in real time, the risk assessment result is dynamically adjusted, and a warning message is sent to the operation and maintenance personnel in a timely manner.

[0101] In specific implementation, during the operation of taking the device off the shelf, the health indicators of the target device and the operation data of the relevant target service are continuously collected through the monitoring system. According to the real-time collected data, the physical topology dependency and service topology dependency of the device are dynamically adjusted. For example, if it is detected that the network traffic of the device suddenly increases, it may indicate that the importance of the device in the service has been temporarily improved, and its service topology dependency needs to be increased accordingly. Based on the updated dependency, the risk score of the target device is recalculated. If the risk score exceeds the preset threshold, the priority of the operation of taking the device off the shelf is automatically adjusted. When the risk score increases significantly, a warning signal is sent to the operation and maintenance personnel, and specific abnormal information and recommended measures are provided, such as suspending the operation of taking the device off the shelf, performing an emergency backup, or adjusting the service traffic, etc.

[0102] It can be seen that the real-time dynamic risk assessment and warning mechanism can quickly respond to changes in device status and service operation, discover potential risks in a timely manner and take measures to avoid service interruption or performance degradation caused by taking the device off the shelf. By dynamically adjusting the risk score and the priority of taking the device off the shelf, the operation and maintenance personnel can arrange the operation of taking the device off the shelf more flexibly, reduce unnecessary waiting and repeated assessments, and improve operation and maintenance efficiency. The real-time warning function enables the operation and maintenance personnel to take preventive measures before the risk occurs, minimizing the impact of taking the device off the shelf on the service and ensuring the continuity and stability of the service. This mechanism can dynamically adjust the resource allocation according to the real-time risk situation, ensuring that key services and high-risk devices receive sufficient attention and resource support, and improving the utilization efficiency of the overall operation and maintenance resources.

[0103] The following introduces an application embodiment provided by the present application. The structural diagram of the equipment off-shelf risk control system is as Figure 2 shown, including an information collection module, an equipment topology relationship module, a risk assessment module, and a compliance verification and recommendation module.

[0104] Among them, the structural diagram of the information collection module is as Figure 3 shown, and it is responsible for collecting topology relationship data of the shelved equipment to maintain the topological association relationship between equipment. At the same time, this module also collects the health indicators of the equipment, such as CPU (Central Processing Unit) usage rate, memory usage rate, alarms and other information. Specifically, the collection of health indicators is completed through SNMP (Simple Network Management Protocol), API (Application Programming Interface) or log analysis tools, covering the CPU usage rate, memory usage rate, disk status and network traffic of the equipment. The collection of topological connection relationships uses network scanning tools or network management protocols to obtain the physical and logical connection relationships between equipment. Network scanning tools such as Nmap (Network Mapper), and network management protocols such as LLDP (Link Layer Discovery Protocol).

[0105] The structural diagram of the equipment topology relationship module is as Figure 4 shown. Based on the topological link relationship provided by the information collection module, it maintains the topology relationship of the equipment and processes the business functions supported by the equipment and their importance. This module analyzes the connections between equipment nodes (such as servers, switches, routers, etc.) according to the topological connection relationship, constructs the physical topology between equipment based on bandwidth information, and clarifies the data flow direction and dependency levels. In addition, this module also maintains the business to which the equipment belongs, sets business information, classifies it according to the business importance level (such as core business, non-core business), sets risk scores for each business level, and then constructs the business topology relationship of the equipment. Finally, combining the equipment link topology and the business topology, a topology dependency relationship model is constructed, and the dependency relationship information is stored in the database for quick query and analysis. At the same time, this module also provides the function of manually maintaining the topology relationship to cope with the situation where some equipment information cannot be collected.

[0106] The structural diagram of the risk assessment module is as Figure 5 shown, and it conducts equipment risk assessment according to the topological dependency relationship, business dependency relationship between equipment and the health status of the equipment.

[0107] The compliance verification recommendation module conducts a risk assessment on the decommissioned devices according to the decommissioning requirements, and displays the affected services based on the assessment results, providing risk control suggestions, including the priority order and operation timing of device decommissioning, etc.

[0108] The device decommissioning risk control method includes the following steps:

[0109] Step 1: Device information collection: Collect device health indicators and topology link data.

[0110] Step 2: Establish a device topology relationship model: Construct a device physical topology relationship model according to the collected topology link relationships, link bandwidths, and data flows; at the same time, record the services to which the devices belong, service relevance, and service importance levels to construct a device service topology relationship model.

[0111] Step 3: Real-time analysis and risk assessment: Before device decommissioning, conduct real-time analysis on the device topology relationships, identify dependencies, and use risk assessment algorithms to evaluate the risk levels of decommissioning operations.

[0112] Step 4: Risk control suggestions: Based on the risk assessment results, display the affected services and provide risk control suggestions, including the priority order and operation timing of device decommissioning.

[0113] Step 5: Implementation and monitoring: Implement the updated topology relationships, monitor the device status, and ensure the safe implementation of decommissioning operations.

[0114] Next, an apparatus for controlling the risk of device decommissioning provided by an embodiment of the present application will be introduced. The apparatus for controlling the risk of device decommissioning described below can be referred to in mutual reference with the method for controlling the risk of device decommissioning described above.

[0115] See Figure 6 , a structural diagram of an apparatus for controlling the risk of device decommissioning shown according to an exemplary embodiment, as Figure 6 shown, includes:

[0116] A first generation module 100, configured to generate a device topology according to the dependencies between the already installed devices, and generate a service topology according to the association relationships between services;

[0117] A first determination module 200, configured to determine a target device to be decommissioned, and determine the device health degree of the target device based on the health indicators of the target device;

[0118] A second determination module 300, configured to determine the physical topology dependency degree of the target device based on the device topology;

[0119] A third determination module 400, configured to determine the service topology dependency degree of the target device based on the service topology;

[0120] The second generation module 500 is configured to generate a risk assessment result of the target device based on the device health degree, the physical topology dependency degree, and the service topology dependency degree;

[0121] The third generation module 600 is configured to generate a risk control recommendation for taking the target device off the shelf according to the risk assessment result.

[0122] In the embodiment of the present application, by comprehensively considering three dimensions of the device health degree, the physical topology dependency degree, and the service topology dependency degree, a risk assessment result of the target device is generated, and a risk control recommendation for taking the device off the shelf is generated accordingly, effectively solving the problems in the prior art such as relying on manual experience, lacking real-time risk assessment, and single risk assessment dimension. First, by automatically generating the device topology and the service topology, the dependency relationship between devices and the association relationship between services can be accurately identified, avoiding the subjectivity and misjudgment of manual judgment and improving the accuracy of risk assessment. Second, based on real-time device health indicators, physical topology dependency degree, and service topology dependency degree for risk assessment, real-time monitoring and dynamic adjustment of the risk of taking the device off the shelf are realized, potential risks can be discovered in time and corresponding measures can be taken, enhancing the stability and reliability of the system. Finally, the multi-dimensional risk assessment method can comprehensively reflect the impact of taking the device off the shelf on the system, providing a more scientific and comprehensive decision-making basis for operation and maintenance personnel, helping to optimize the operation plan for taking the device off the shelf, reducing operation and maintenance costs, and improving operation and maintenance efficiency.

[0123] On the basis of the above embodiment, as a preferred embodiment, the health indicator includes any one or a combination of several of the processor usage rate, the memory usage rate, the disk status, and the network traffic.

[0124] On the basis of the above embodiment, as a preferred embodiment, the second determination module 300 includes:

[0125] The first determination unit is configured to determine the importance score of the link in the device topology;

[0126] The first calculation unit is configured to calculate the sum of the importance scores of the target links directly connected to the target device, and calculate the sum of the importance scores of all links in the device topology;

[0127] The second calculation unit is configured to calculate the ratio between the sum of the importance scores of the target links and the sum of the importance scores of all links as the physical topology dependency degree of the target device.

[0128] On the basis of the above embodiment, as a preferred embodiment, the first determination unit is specifically configured to: determine the importance score of the link according to the bandwidth and traffic of the link in the device topology.

[0129] On the basis of the above embodiment, as a preferred embodiment, the third determination module 400 includes:

[0130] A second determination unit, configured to determine an importance score of a service in a service topology;

[0131] A third determination unit, configured to determine a target service set associated with a target device;

[0132] A fourth determination unit, configured to determine a service topology dependency degree of the target device based on a correlation coefficient between target services in the target service set and the importance score of the service in the service topology.

[0133] Based on the above embodiments, as a preferred implementation manner, the fourth determination unit is specifically configured to: determine the service topology dependency degree of the target device based on a service topology dependency degree calculation formula; wherein, the service topology dependency degree calculation formula is:

[0134] ;

[0135] Wherein, is the service topology dependency degree of the target device , is the set of services in the service topology, is a service in the service topology, is the importance score of the service in the service topology, is the target service set, , are target services associated with the target device, is the target service 's importance score, is the target service and the target service 's correlation coefficient.

[0136] Based on the above embodiments, as a preferred implementation manner, the third determination module 400 further includes:

[0137] A normalization unit, configured to perform normalization processing on the service topology dependency degree of the target device.

[0138] In the above embodiments, as a preferred implementation manner, the normalization unit is specifically configured to: perform normalization processing on the service topology dependency degree of the target device based on a normalization processing formula; wherein, the normalization processing formula is:

[0139] ;

[0140] Wherein, is the service topology dependency degree of the target device , is the target device The business topology dependency after normalization, is the maximum value of the business topology dependencies of all devices, and is the minimum value of the business topology dependencies of all devices.

[0141] Based on the above embodiments, as a preferred embodiment, the second generation module 500 is specifically configured to: assign different weighting coefficients to the device health degree, the physical topology dependency, and the business topology dependency, and perform a weighting process on the device health degree, the physical topology dependency, and the business topology dependency based on the weighting coefficients to generate a risk score for the target device; wherein, the risk score is positively correlated with the physical topology dependency and the business topology dependency, and the risk score is negatively correlated with the device health degree.

[0142] Based on the above embodiments, as a preferred embodiment, the second generation module 500 is specifically configured to: generate a risk score for the target device based on a risk score calculation formula; wherein, the risk score calculation formula is:

[0143] ;

[0144] wherein, is the risk score of the target device , is the physical topology dependency of the target device , is the business topology dependency of the target device , is the device health degree of the target device , , , are the weighting coefficients corresponding to the device health degree, the physical topology dependency, and the business topology dependency respectively.

[0145] Based on the above embodiments, as a preferred embodiment, the third generation module 600 is specifically configured to: determine the priority for taking the target device off the shelf according to the risk score; wherein, the priority is negatively correlated with the risk score.

[0146] Based on the above embodiments, as a preferred embodiment, further includes:

[0147] A display module, configured to display the target service associated with the target device; wherein, the target service is the service affected by taking the target device off the shelf.

[0148] Regarding the device in the above embodiments, the specific manners of operations performed by each module have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0149] Embodiments of the present application further provide an electronic device. Figure 7 FIG. Figure 7 is a structural diagram of an electronic device shown according to an exemplary embodiment. As Figure 7 shown, the electronic device includes:

[0150] A communication interface 1 capable of interacting with other devices such as network devices for information.

[0151] A processor 2 is connected to the communication interface 1 to achieve information interaction with other devices. When running a computer program, it executes the device off-shelf risk control method provided by one or more of the above technical solutions. The computer program is stored on a memory 3.

[0152] Of course, in actual application, each component in the electronic device is coupled together through a bus system 4. It can be understood that the bus system 4 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 4 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clear illustration, in Figure 7 all kinds of buses are labeled as the bus system 4.

[0153] The memory 3 in the embodiments of the present application is used to store various types of data to support the operation of the electronic device. Examples of these data include: any computer program for operating on the electronic device.

[0154] It can be understood that the memory 3 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory), an electrically erasable programmable read-only memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), a ferromagnetic random access memory (FRAM, ferromagnetic random access memory), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM, Compact Disc Read-Only Memory); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM, Random Access Memory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as a static random access memory (SRAM, Static Random Access Memory), a synchronous static random access memory (SSRAM, Synchronous Static Random Access Memory), a dynamic random access memory (DRAM, Dynamic Random Access Memory), a synchronous dynamic random access memory (SDRAM, Synchronous Dynamic Random Access Memory), a double data rate synchronous dynamic random access memory (DDR SDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), an enhanced synchronous dynamic random access memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), a sync link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and a direct rambus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 3 described in the embodiments of the present application is intended to include but not limited to these and any other suitable types of memories.

[0155] The method disclosed in the embodiments of the present application above can be applied to the processor 2 or implemented by the processor 2. The processor 2 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 2 or the instructions in the form of software. The above-mentioned processor 2 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 2 can implement or execute each method, step, and logic block diagram disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. Combining the steps of the method disclosed in the embodiments of the present application, it can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in the storage medium, and this storage medium is located in the memory 3. The processor 2 reads the program in the memory 3 and combines its hardware to complete the steps of the foregoing method.

[0156] When the processor 2 executes the program, it implements the corresponding processes in each method of the embodiments of the present application. For the sake of brevity, it will not be repeated here.

[0157] The embodiments of the present application also provide a computer-readable storage medium, in which a computer program is stored. Among them, the computer program is set to execute the steps in any of the above-mentioned method embodiments for controlling the risk of device delisting when running.

[0158] In an exemplary embodiment, the above-mentioned computer-readable storage medium may include but not limited to: USB flash drives, read-only memories (ROM for short), random access memories (RAM for short), mobile hard disks, magnetic disks, or optical discs, etc., various media that can store computer programs.

[0159] The embodiments of the present application also provide a computer program product. The above-mentioned computer program product includes a computer program, and when the computer program is executed by the processor 2, it implements the steps in any of the above-mentioned method embodiments for controlling the risk of device delisting.

[0160] The embodiments of the present application also provide another computer program product, including a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by the processor 2, it implements the steps in any of the above-mentioned method embodiments for controlling the risk of device delisting.

[0161] Those skilled in the art may further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner 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 as exceeding the scope of this application.

[0162] The above has introduced in detail a method, device, equipment, medium, and product for controlling the risk of equipment removal provided by this application. Specific examples have been used herein to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this application, several improvements and modifications can still be made to this application, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A method for controlling the risk of equipment removal, characterized in that Including: Generating a device topology based on the dependency relationships among the devices already on the shelves, and generating a service topology based on the association relationships among the services; Determining the target device to be taken off the shelves, and determining the device health of the target device based on the health metrics of the target device; Determining the physical topology dependency of the target device based on the device topology; Determining the service topology dependency of the target device based on the service topology; Generating a risk assessment result of the target device based on the device health, the physical topology dependency, and the service topology dependency; Generating a risk control recommendation for taking off the target device based on the risk assessment result.

2. The method for controlling the risk of equipment removal according to claim 1, wherein The health metrics include any one or a combination of several of the processor usage rate, memory usage rate, disk status, and network traffic.

3. The device off-shelf risk control method according to claim 1, wherein The determining the physical topology dependency of the target device based on the device topology includes: Determining the importance score of the links in the device topology; Calculating the sum of the importance scores of the target links directly connected to the target device, and calculating the sum of the importance scores of all the links in the device topology; Calculating the ratio between the sum of the importance scores of the target links and the sum of the importance scores of all the links as the physical topology dependency of the target device.

4. The method for controlling the risk of equipment removal according to claim 3, characterized in that, The determining the importance score of the links in the device topology includes: Determining the importance score of the link according to the bandwidth and traffic of the link in the device topology.

5. The method for controlling the risk of equipment removal according to claim 1, wherein, The determining the service topology dependency of the target device based on the service topology includes: Determining the importance score of the services in the service topology; Determining the set of target services associated with the target device; Determining the service topology dependency of the target device based on the correlation coefficients among the target services in the set of target services and the importance scores of the services in the service topology.

6. The method for controlling the risk of equipment removal according to claim 5, wherein The determining the service topology dependency of the target device based on the correlation coefficients among the target services in the set of target services and the importance scores of the services in the service topology includes: Determining the service topology dependency of the target device based on the service topology dependency calculation formula; wherein, the service topology dependency calculation formula is: ； wherein, is the business topology dependency of the target device is the set of services in the business topology is the service in the business topology is the importance score of the service in the business topology is the importance score of the service in the business topology is the target service set and is the target service associated with the target device is the target service is the importance score of the target service is the target service and the target service is the correlation coefficient therebetween 7. The method for controlling the risk of equipment removal according to claim 5, wherein After determining the service topology dependency of the target device based on the correlation coefficients among different target services in the set of target services and the importance scores of the services in the service topology, it further includes: Performing normalization processing on the service topology dependency of the target device.

8. The method for controlling the risk of equipment removal according to claim 7, wherein The performing normalization processing on the service topology dependency of the target device includes: Performing normalization processing on the service topology dependency of the target device based on the normalization processing formula; wherein, the normalization processing formula is: ； Among them, is the business topology dependency of the target device , is the normalized business topology dependency of the target device , is the maximum value of the business topology dependencies of all devices is the minimum value of the business topology dependencies of all devices 9. The device off-shelf risk control method according to claim 1, characterized in that The generating the risk assessment result of the target device based on the device health, the physical topology dependency, and the service topology dependency includes: Assign different weighting coefficients to the device health degree, the physical topology dependency degree, and the service topology dependency degree, and perform weighted processing on the device health degree, the physical topology dependency degree, and the service topology dependency degree based on the weighting coefficients to generate a risk score for the target device; wherein, the risk score is positively correlated with the physical topology dependency degree and the service topology dependency degree, and the risk score is negatively correlated with the device health degree.

10. The method for controlling the risk of equipment removal according to claim 9, wherein The generating the risk score for the target device includes: Generating the risk score for the target device based on a risk score calculation formula; wherein, the risk score calculation formula is: ； Among them, is the risk score of the target device , is the physical topology dependency of the target device , is the business topology dependency of the target device , is the device health of the target device , , , are the weighting coefficients corresponding to the device health, the physical topology dependency, and the business topology dependency, respectively.

11. The method for controlling the risk of equipment removal according to claim 9, wherein The generating risk control suggestions for taking the target device off the shelf according to the risk assessment result includes: Determining the priority for taking the target device off the shelf according to the risk score; wherein, the priority is negatively correlated with the risk score.

12. The method for controlling the risk of equipment removal according to claim 1, wherein After generating the risk assessment result for the target device based on the device health degree, the physical topology dependency degree, and the service topology dependency degree, it further includes: Displaying the target service associated with the target device; wherein, the target service is the service affected by taking the target device off the shelf.

13. A device off-shelf risk control device, characterized in that, It includes: A first generation module, configured to generate a device topology according to the dependency relationship between the devices already on the shelf, and generate a service topology according to the association relationship between services; A first determination module, configured to determine the target device to be taken off the shelf, and determine the device health degree of the target device based on the health indicators of the target device; A second determination module, configured to determine the physical topology dependency degree of the target device based on the device topology; A third determination module, configured to determine the service topology dependency degree of the target device based on the service topology; A second generation module, configured to generate a risk assessment result for the target device based on the device health degree, the physical topology dependency degree, and the service topology dependency degree; A third generation module, configured to generate risk control suggestions for taking the target device off the shelf according to the risk assessment result.

14. An electronic device, characterized in that, It includes: A memory, configured to store a computer program; A processor, configured to implement the steps performed by the device off-shelf risk control method according to any one of claims 1 to 12 when executing the computer program.

15. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed, the steps performed by the device off-shelf risk control method according to any one of claims 1 to 12 are implemented.

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