A hardware configuration information processing method, device, equipment and medium

Abstract

This invention relates to the field of computer science and technology, and discloses a method, apparatus, device, and medium for processing hardware configuration information. It can acquire target hardware attribute information for each server, map the target hardware attribute information of each server using a mapping library to determine the target hardware model of each server, and then determine the first hardware configuration information for each server. If no inclusion relationship exists between the first hardware configuration information pieces, the first hardware configuration information is compared with the target hardware configuration information stored in the configuration library. If they are the same, the first hardware configuration information is determined to be the accurate hardware configuration information. This embodiment can use a mapping library to map the server's hardware model, determine the server's hardware configuration information based on the hardware model, and then use the configuration library to determine the accuracy of its hardware configuration information, effectively ensuring the accuracy of the server hardware configuration information.

Description

Technical Field

[0001] This invention relates to the field of computer science and technology, and specifically to a hardware configuration information processing method, apparatus, device, and medium. Background Technology

[0002] With the development of computer science and technology, server management and control technologies are constantly improving.

[0003] Currently, server hardware configuration parameters are the fundamental parameters upon which server management software bases its management. Different hardware configurations require significantly different management methods. To ensure accurate management, precise hardware configuration information must be provided to the server management software.

[0004] However, due to various factors, the accuracy of the collected hardware configuration information is low. Summary of the Invention

[0005] In view of this, the present invention provides a hardware configuration information processing method, apparatus, device and medium to solve the problem of low accuracy of hardware configuration information.

[0006] In a first aspect, the present invention provides a hardware configuration information processing method, the method comprising: Obtain target hardware attribute information for at least one server; Based on the target hardware attribute information of each server, the target hardware model of each server is determined in the first correspondence stored in the mapping library; the first correspondence is the correspondence between hardware attribute information and hardware model. Determine the initial hardware configuration information for each server based on the target hardware model of each server; If it is determined that there is no inclusion relationship between each first hardware configuration information, the first hardware configuration information is compared with the target hardware configuration information stored in the configuration library. If they are the same, the first hardware configuration information is determined to be the accurate hardware configuration information.

[0007] In one optional implementation, at least one server includes a first server, and the target hardware attribute information includes at least one hardware attribute information; based on the target hardware attribute information of each server, the target hardware model of each server is determined in a first correspondence stored in a mapping library, including: Based on at least one hardware attribute information in the target hardware attribute information of the first server, at least one hardware model is determined in the first correspondence relationship; At least one hardware model is identified as the target hardware model for the first server.

[0008] In one optional implementation, at least one hardware attribute information of the first server includes first hardware attribute information, and the first correspondence includes at least one second hardware attribute information; determining at least one hardware model in the first correspondence based on at least one hardware attribute information in the target hardware attribute information of the first server includes: Calculate the similarity between each second hardware attribute information and the first hardware attribute information; When the similarity is not less than the first preset threshold, it is determined that the second hardware attribute information matches the first hardware attribute information. The first hardware model is determined in the first correspondence based on the second hardware attribute information that matches the first hardware attribute information.

[0009] In one alternative implementation, after calculating the similarity between each second hardware attribute information and the first hardware attribute information, the method further includes: When each similarity score is less than the first preset threshold, the maximum similarity score is determined based on each similarity score. When the maximum similarity is less than the second preset threshold, a mapping library filling operation is performed based on the first hardware attribute information. When the maximum similarity is not less than the second preset threshold, the first hardware attribute information and the second hardware attribute information are suspected to match, and calibration and mapping library filling operations are performed based on the first hardware attribute information.

[0010] In one optional implementation, the first hardware configuration information of each server is determined based on the target hardware model of each server, including: Cluster at least one hardware model among the target hardware models of the first server, and determine at least one type of hardware and the hardware models under each type of hardware; The first hardware configuration information of the first server is determined by identifying at least one type of hardware and the hardware model under each type of hardware.

[0011] In one optional implementation, comparing the first hardware configuration information with the target hardware configuration information stored in the configuration library includes: Obtain the machine model of the first server; At least one second hardware configuration information is determined from the second correspondence stored in the configuration database based on the model of the first server, and is used as the target hardware configuration information; wherein, the second correspondence is the correspondence between the server model and the hardware configuration information, and in the second correspondence, one server model corresponds to at least one hardware configuration information; The first hardware configuration information of the first server is compared with the second hardware configuration information of each server.

[0012] In one optional implementation, if they are the same, determining the first hardware configuration information as the accurate hardware configuration information includes: If the first hardware configuration information of the first server is the same as the second hardware configuration information, then the first hardware configuration information is determined to be the accurate hardware configuration information. After comparing the first hardware configuration information of the first server with each second hardware configuration information, the method further includes: If the first hardware configuration information is different from each of the second hardware configuration information, and the second hardware configuration information contains the first hardware configuration information, then the first server is subjected to fault tolerance processing through the fault tolerance model. If the first hardware configuration information is different from each of the second hardware configuration information, and each of the second hardware configuration information does not contain the first hardware configuration information, then the configuration library filling operation is performed based on the first hardware configuration information.

[0013] In one optional implementation, fault tolerance processing is performed on the first server using a fault tolerance model, including: Determine the missing information in the first hardware configuration information relative to the second hardware configuration information; Obtain the device characteristic information of the first server; The missing information and device characteristic information are sent to the fault tolerance model so that the fault tolerance model can determine the device optimization scheme based on the missing information and device characteristic information, and perform optimization operations on the first server according to the device optimization scheme.

[0014] In one alternative implementation, after determining the first hardware configuration information of each server based on the target hardware model of each server, the method further includes: Identify and delete other first hardware configuration information that is identical to the first hardware configuration information of the first server; If it is determined that there is an inclusion relationship between the first hardware configuration information of the first server and other first hardware configuration information, the maximum hardware configuration information is determined according to the inclusion relationship. Compare the maximum hardware configuration information with the target hardware configuration information; If they are the same, then determine that the maximum hardware configuration information is the accurate hardware configuration information and output the maximum hardware configuration information; If they are different, the first server is fault-tolerant through a fault-tolerant model, or a configuration library filling operation is performed based on the first hardware configuration information.

[0015] In one optional implementation, obtaining target hardware attribute information of at least one server includes: The target hardware attribute information of the first server is collected from the first server using a preset acquisition protocol; After determining the maximum hardware configuration information based on the inclusion relationship, the method also includes: If the first hardware configuration information of the first server is not the maximum hardware configuration information, then the preset acquisition protocol is changed, and the hardware attribute information of the first server is collected again using the changed acquisition protocol to collect the hardware configuration information of the first server. Determine whether the collected hardware configuration information of the first server is the maximum hardware configuration information. If not, continue to change the acquisition protocol and collect the hardware configuration information of the first server until the collected hardware configuration information of the first server is the maximum hardware configuration information. If so, record the currently used acquisition protocol and determine it as the optimal acquisition protocol for the first server.

[0016] In one optional implementation, after continuing to collect hardware attribute information of the first server using the changed acquisition protocol to collect the hardware configuration information of the first server, the method further includes: When the hardware configuration information collected by all acquisition protocols is not the maximum hardware configuration information, the first server is subjected to fault tolerance processing through the fault tolerance model.

[0017] In a second aspect, the present invention provides a hardware configuration information processing device, the device comprising: The information acquisition module is used to acquire target hardware attribute information of at least one server; The first determining module is used to determine the target hardware model of each server based on the target hardware attribute information of each server and in the first correspondence stored in the mapping library; the first correspondence is the correspondence between hardware attribute information and hardware model. The second determining module is used to determine the first hardware configuration information of each server based on the target hardware model of each server. The first comparison module is used to compare the first hardware configuration information with the target hardware configuration information stored in the configuration library when it is determined that there is no inclusion relationship between each first hardware configuration information. The third determining module is used to determine that the first hardware configuration information is accurate hardware configuration information if the first hardware configuration information is the same as the target hardware configuration information.

[0018] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the hardware configuration information processing method of the first aspect or any corresponding embodiment described above.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the hardware configuration information processing method of the first aspect or any corresponding embodiment thereof.

[0020] The hardware configuration information processing method, apparatus, device, and medium proposed in this invention can acquire target hardware attribute information for each server, map the target hardware attribute information of each server using a mapping library to determine the target hardware model of each server, and determine the first hardware configuration information of each server based on the target hardware model. If no inclusion relationship exists between the first hardware configuration information pieces, the first hardware configuration information is compared with the target hardware configuration information stored in the configuration library. If they are the same, the first hardware configuration information is determined to be the accurate hardware configuration information. This embodiment can use a mapping library to map each hardware attribute information of the server to a corresponding hardware model, determine the server's hardware configuration information based on the hardware model, and then compare the hardware configuration information with the hardware configuration information stored in the configuration library to determine the accuracy of the server's hardware configuration information, effectively ensuring the accuracy of the server's hardware configuration information. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating a hardware configuration information processing method according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating another hardware configuration information processing method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the data structure of a mapping library according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the data structure of a configuration library according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a hardware configuration information processing device according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] This invention proposes a hardware configuration information processing method, which can effectively ensure the accuracy of the collected server hardware configuration information and the accuracy of the hardware configuration information provided to users.

[0025] According to an embodiment of the present invention, a hardware configuration information processing method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0026] like Figure 1 As shown, this embodiment proposes a first hardware configuration information processing method, which may include the following steps: S101. Obtain target hardware attribute information for at least one server.

[0027] It should be noted that this embodiment can be applied to electronic devices, such as mobile phones, desktop computers, and laptops.

[0028] Specifically, at least one of the aforementioned servers can be a batch of servers incorporated into server management software.

[0029] Specifically, the target hardware attribute information can include the attribute information of the hardware in the server. This hardware attribute information can include information such as the hardware vendor ID, vendor name, sub-vendor ID, device ID, device name, and sub-device ID.

[0030] Specifically, the target hardware attribute information may include the attribute information of one or more hardware components in the server. This embodiment can collect the attribute information of each hardware component in the server, and the collected attribute information can be used as the target hardware attribute information of the server. Optionally, the hardware in the server may include network cards, hard drives, and power supplies, etc.

[0031] Specifically, this embodiment can use various related protocols to collect target hardware attribute information of the server, such as the Intelligent Platform Management Interface (IPMI) protocol, the Redfish protocol, and the Simple Network Management Protocol (SNMP).

[0032] It is understood that this embodiment can collect the attribute information of the hardware in each server to obtain the target hardware attribute information of each server.

[0033] S102. Based on the target hardware attribute information of each server, determine the target hardware model of each server in the first correspondence stored in the mapping library. The first correspondence is the correspondence between hardware attribute information and hardware model.

[0034] The mapping library can be generated by technicians through initialization operations based on their hardware usage experience, adapted data, and server management software compatibility experience. The initial correspondence in the mapping library can be constructed by technicians based on the correspondence between hardware attribute information and hardware models.

[0035] Specifically, in the first correspondence, one hardware attribute information can correspond to one hardware model, and one hardware model can correspond to one or more hardware attribute information.

[0036] It is understood that, based on the attribute information of a piece of hardware, this embodiment can determine the corresponding hardware model from the first correspondence relationship.

[0037] Optionally, the at least one server mentioned above includes a first server, and the target hardware attribute information includes at least one hardware attribute information. In this case, step S102 may include: Based on at least one hardware attribute information from the target hardware attribute information of the first server, at least one hardware model is determined in the first correspondence.

[0038] At least one hardware model is identified as the target hardware model for the first server.

[0039] Optionally, at least one hardware attribute information of the first server includes first hardware attribute information, and the first correspondence includes at least one second hardware attribute information. In this case, determining at least one hardware model in the first correspondence based on at least one hardware attribute information in the target hardware attribute information of the first server includes: Calculate the similarity between each second hardware attribute information and the first hardware attribute information.

[0040] When the similarity is not less than the first preset threshold, it is determined that the second hardware attribute information matches the first hardware attribute information.

[0041] The first hardware model is determined in the first correspondence based on the second hardware attribute information that matches the first hardware attribute information.

[0042] It should be noted that this embodiment can take the first server as an example to illustrate the process of determining the target hardware model of the server.

[0043] The first hardware attribute information is a certain hardware attribute information of the first server.

[0044] The second hardware attribute information is the same as the hardware attribute information contained in the first correspondence.

[0045] The first preset threshold can be 100%, or other values ​​close to 100%, such as 95% and 98%.

[0046] In this embodiment, when the similarity between a second hardware attribute and a first hardware attribute is calculated to be 100%, it is determined that the second hardware attribute matches the first hardware attribute. Then, based on the second hardware attribute, the corresponding first hardware model is determined in the first correspondence relationship. This first hardware model is the hardware model mapped from the first hardware attribute in the mapping library.

[0047] Specifically, the target hardware attribute information of the first server includes one or more hardware attribute information. In this embodiment, each hardware attribute information of the first server can be used as the first hardware attribute information, and the corresponding first hardware model can be mapped from the mapping library. Therefore, each hardware attribute information can be mapped to a corresponding hardware model, and all the mapped hardware models constitute the target hardware model of the first server.

[0048] Optionally, in other hardware configuration information processing methods proposed in this embodiment, after calculating the similarity between each second hardware attribute information and the first hardware attribute information, the method may further include: When each similarity score is less than the first preset threshold, the maximum similarity score is determined based on each similarity score.

[0049] When the maximum similarity is less than the second preset threshold, the mapping library filling operation is performed based on the first hardware attribute information.

[0050] When the maximum similarity is not less than the second preset threshold, the first hardware attribute information and the second hardware attribute information are suspected to match, and calibration and mapping library filling operations are performed based on the first hardware attribute information.

[0051] The second preset threshold can be 80%, or other values ​​less than 100%, such as 85% and 79%.

[0052] Specifically, when each similarity score is less than a first preset threshold, it can be assumed that the first hardware attribute information does not exist in the mapping library. In this case, the mapping library cannot accurately map the hardware model corresponding to the first hardware attribute information. In this embodiment, the maximum similarity score, i.e., the similarity score with the largest numerical value, can be determined from the calculated similarities.

[0053] Specifically, when the maximum similarity is less than the second preset threshold, it can be assumed that the first hardware attribute information does not exist in the mapping library. Technicians can be prompted to manually determine the hardware model corresponding to the first hardware attribute information and fill the first hardware attribute information and the hardware model into the mapping library to achieve dynamic expansion of the mapping library.

[0054] Specifically, when the similarity is not less than the second preset threshold, the first hardware attribute information can be considered to be a suspected match with the corresponding second hardware attribute information (i.e., the second hardware attribute information with the highest similarity). The first hardware attribute information is then manually calibrated to determine whether the two match. If they match, the corresponding hardware model is manually determined in the mapping library. If they do not match, the corresponding hardware model is manually determined and the first hardware attribute information and the corresponding hardware model are filled into the mapping library.

[0055] S103. Determine the first hardware configuration information for each server based on the target hardware model of each server.

[0056] The first hardware configuration information is the hardware configuration information of a certain server.

[0057] Optionally, step S103 may include: Cluster at least one hardware model among the target hardware models of the first server, and determine at least one type of hardware and the hardware models under each type of hardware.

[0058] The first hardware configuration information of the first server is determined by identifying at least one type of hardware and the hardware model under each type of hardware.

[0059] It should be noted that this embodiment can take the first server as an example to illustrate the process of determining the first hardware configuration information.

[0060] Specifically, in this embodiment, after determining the target hardware model of the first server, the various hardware models within the target hardware model are clustered to determine the corresponding types of hardware and the hardware models under each type of hardware, that is, to determine the first hardware configuration information of the first server. For example, when the target hardware model includes network card model 1, network card model 2, network card model 3, hard drive model 1, hard drive model 2, power supply model 1, and power supply model 2, after clustering in this embodiment, three types of hardware can be determined, namely network cards, hard drives, and power supplies. The hardware models of network cards are determined to include network card model 1, network card model 2, and network card model 3; the hardware models of hard drives are determined to include hard drive model 1 and hard drive model 2; and the hardware models of power supplies are determined to include power supply model 1 and power supply model 2, such as {"Network Card": "Network Card Model 1, Network Card Model 2, Network Card Model 3", "Hard Drive": "Hard Drive Model 1, Hard Drive Model 2", "Power Supply": "Power Supply Model 1, Power Supply Model 2"}.

[0061] S104. If it is determined that there is no inclusion relationship between each first hardware configuration information, compare the first hardware configuration information with the target hardware configuration information stored in the configuration library.

[0062] It should be noted that if two hardware configuration information A and B are related, A contains B or B contains A, then there is an inclusion relationship between A and B.

[0063] Specifically, the absence of an inclusion relationship between the first hardware configuration information of each server means that the first hardware configuration information of any server does not contain the first hardware configuration information of other servers, nor is it contained in the first hardware configuration information of other servers.

[0064] Specifically, the configuration library can include standard hardware configuration information for the server (such as the hardware configuration information at the time of the server's shipment), as well as hardware configuration information formed based on experience. The configuration library can be generated by technical personnel through initialization operations based on server configuration experience, adapted data, and server management software compatibility experience.

[0065] It should be noted that after purchasing a server, users may reduce its configuration, such as removing a few hard drives or network cards, resulting in the actual configuration information of the server differing from the standard hardware configuration information.

[0066] The target hardware configuration information can be any hardware configuration information stored in the configuration library. It is understood that the content format of the target hardware configuration information is the same as that of the first hardware configuration information; that is, the target hardware configuration information also includes at least one type of hardware and the hardware model under each type of hardware.

[0067] S105. If the first hardware configuration information is the same as the target hardware configuration information in the configuration library, then the first hardware configuration information is determined to be accurate hardware configuration information.

[0068] Specifically, in this embodiment, the first hardware configuration information can be compared with the target hardware configuration information in the configuration library. When there is target hardware configuration information in the configuration library that is the same as the first hardware configuration information, the first hardware configuration information is determined to be accurate hardware configuration information.

[0069] Specifically, when there is no target hardware configuration information in the configuration library that is the same as the first hardware configuration information, it cannot be determined that the first hardware configuration information is the accurate hardware configuration information.

[0070] Specifically, this embodiment uses a first server as an example. This embodiment compares the first hardware configuration information of the first server with the target hardware configuration information in the configuration library. When a target hardware configuration information identical to the first hardware configuration information exists in the configuration library, the first hardware configuration information is determined to be the accurate hardware configuration information of the first server. Conversely, when no target hardware configuration information identical to the first hardware configuration information exists in the configuration library, it cannot be determined that the first hardware configuration information is the accurate hardware configuration information of the first server.

[0071] The hardware configuration information processing method proposed in this embodiment can obtain the target hardware attribute information of each server, map the target hardware attribute information of each server using a mapping library to map the target hardware model of each server, determine the first hardware configuration information of each server based on the target hardware model, and, if it is determined that there is no inclusion relationship between each first hardware configuration information, compare the first hardware configuration information with the target hardware configuration information stored in the configuration library. If they are the same, then the first hardware configuration information can be determined as the accurate hardware configuration information. This embodiment can use a mapping library to map each hardware attribute information of the server to the corresponding hardware model, determine the server's hardware configuration information based on each hardware model, and then compare the hardware configuration information with the hardware configuration information stored in the configuration library to determine the accuracy of the server hardware configuration information, effectively ensuring the accuracy of the server hardware configuration information.

[0072] based on Figure 1 This embodiment proposes a second method for processing hardware configuration information. In this method, step S104 may include: Obtain the machine model of the first server.

[0073] At least one second hardware configuration piece of information is determined from the second correspondence stored in the configuration database based on the model of the first server, and is used as the target hardware configuration piece of information. The second correspondence is the correspondence between server models and hardware configuration pieces of information, and in the second correspondence, one server model corresponds to at least one piece of hardware configuration piece of information.

[0074] The first hardware configuration information of the first server is compared with the second hardware configuration information of each server.

[0075] In the second correspondence, one server model can correspond to one or more hardware configuration information, and one hardware configuration information corresponds to only one server model.

[0076] Specifically, in this embodiment, based on the model of the first server, the corresponding hardware configuration information, i.e., the various second hardware configuration information, can be determined from the second correspondence stored in the configuration library. It is understood that the content format of the second hardware configuration information is the same as that of the first hardware configuration information; that is, the second hardware configuration information includes at least one type of hardware and the hardware models under each type of hardware.

[0077] Specifically, the target hardware configuration information may include the determined second hardware configuration information.

[0078] Specifically, in this embodiment, the first hardware configuration information of the first server can be compared with each of the second hardware configuration information in the target hardware configuration information.

[0079] At this point, step S105 may include: If the first hardware configuration information of the first server is the same as the second hardware configuration information, then the first hardware configuration information is determined to be the accurate hardware configuration information.

[0080] Optionally, after step S104 above, the following may also be included: If the first hardware configuration information is different from each of the second hardware configuration information, and the second hardware configuration information contains the first hardware configuration information, then the first server is subjected to fault tolerance processing through the fault tolerance model.

[0081] If the first hardware configuration information is different from each of the second hardware configuration information, and each of the second hardware configuration information does not contain the first hardware configuration information, then the configuration library filling operation is performed based on the first hardware configuration information.

[0082] Specifically, if the first hardware configuration information of the first server is the same as a certain second hardware configuration information, then the first hardware configuration information can be considered the accurate hardware configuration information of the first server.

[0083] Specifically, if the first hardware configuration information of the first server is different from each of the second hardware configuration information, and a certain second hardware configuration information contains the first hardware configuration information, it can be considered that the complete hardware attribute information of the first server has not been collected. In this case, fault tolerance processing can be performed on the first server through the fault tolerance model, and the relevant software or hardware facilities of the first server can be optimized so as to improve the completeness and accuracy of information collection when re-collecting the hardware attribute information of the first server.

[0084] Specifically, if the first hardware configuration information of the first server is different from each of the second hardware configuration information, and each of the second hardware configuration information does not contain the first hardware configuration information, then the first hardware configuration information can be considered a new configuration and can be manually confirmed. In this case, when the first hardware configuration information is manually confirmed as a new configuration, the new configuration of the first server can be added to and saved in the configuration library, thus achieving dynamic expansion of the configuration library.

[0085] It should be noted that this embodiment can perform different optimization operations under different comparison results between the first hardware configuration information and the target hardware configuration information, so as to improve the accuracy of the hardware configuration information. That is, it can improve the accuracy of the hardware configuration information in multiple scenarios and increase the diversity of applicable scenarios.

[0086] Optionally, the above-mentioned fault-tolerant processing of the first server using a fault-tolerant model includes: Determine the missing information in the first hardware configuration information relative to the second hardware configuration information.

[0087] Obtain the device characteristic information of the first server.

[0088] The missing information and device characteristic information are sent to the fault tolerance model so that the fault tolerance model can determine the device optimization scheme based on the missing information and device characteristic information, and perform optimization operations on the first server according to the device optimization scheme.

[0089] Specifically, this embodiment can collect server performance metrics and operating status information, such as performance metrics and operating status, through monitoring tools, log files, operating system instructions, hardware monitoring devices, and remote monitoring and management tools. This device characteristic information may also include the hardware configuration information of the first server. This embodiment can send the aforementioned missing information and device characteristic information to a fault-tolerant model, allowing the model to assess the health status, availability, operating load, and performance bottlenecks of the first server, determine its optimization needs and limitations, and ultimately determine an optimization plan for the first server.

[0090] It should be noted that the fault-tolerant model can first identify the reasons for incomplete hardware data acquisition. These reasons may include an unstable Baseboard Management Controller (BMC) interface, an outdated BMC version, an outdated Basic Input Output System (BIOS) version, the server being powered off, and the BMC not providing an acquisition interface for a certain type of hardware.

[0091] Specifically, this embodiment can display the first hardware configuration information to the user and intelligently recommend device optimization solutions based on the missing data collection items and server-related characteristics. Users can also choose solutions from the fault-tolerant model. Solutions may include BMC restart, upgrading the BMC to the optimal version, upgrading the BIOS to the optimal version, restoring the BMC to factory settings, and manually mounting the image. Manually mounting the image involves embedding an operating system containing data collection components and using the operating system to re-collect data.

[0092] The hardware configuration information processing method proposed in this embodiment can optimize the server using a fault-tolerant model when accurate hardware configuration information of the server cannot be collected, so that the integrity and accuracy of the hardware configuration information can be guaranteed when the server's hardware configuration information is collected again.

[0093] based on Figure 1 This embodiment proposes a third method for processing hardware configuration information. After step S104 above, this method may further include: Identify and delete other first hardware configuration information that is identical to the first hardware configuration information of the first server.

[0094] If it is determined that there is an inclusion relationship between the first hardware configuration information of the first server and the first hardware configuration information of other servers, the maximum hardware configuration information is determined based on the inclusion relationship.

[0095] Compare the maximum hardware configuration information with the target hardware configuration information.

[0096] If they are the same, the maximum hardware configuration information is determined to be the accurate hardware configuration information, and the maximum hardware configuration information is output.

[0097] If they are different, the first server is fault-tolerant through a fault-tolerant model, or a configuration library filling operation is performed based on the first hardware configuration information.

[0098] Specifically, in this embodiment, after determining the first hardware configuration information of each server, configuration normalization is performed on the first hardware configuration information of each server. That is, multiple identical first hardware configuration information entries are identified within the first hardware configuration information of each server, and only one of these identical entries is retained while the others are deleted. For example, when the first hardware configuration information of each server includes A, A, A, B, B, B, and B, configuration normalization can delete A, A, B, B, and B, retaining only A and B. It is understood that this embodiment can record the device identifiers, such as serial numbers, of each server, associating servers with the same hardware configuration information. When comparing the first hardware configuration information of a server with the target hardware configuration information in the configuration library, only the first hardware configuration information of one server is compared to determine the accuracy of the hardware configuration information of other associated servers.

[0099] Specifically, in this embodiment, when the first hardware configuration information of the first server includes or is included in the first hardware configuration information of other servers, the first hardware configuration information containing the most elements, i.e., the maximum hardware configuration information, is determined based on this inclusion relationship. For example, when the first hardware configuration information A includes B, and A includes C, then C is the maximum hardware configuration information.

[0100] Specifically, this embodiment can compare the maximum hardware configuration information with the target hardware configuration information in the configuration library. It should be noted that the specific comparison process can refer to the comparison process between the first hardware configuration information and the target hardware configuration information described above.

[0101] When the comparison results are the same, the maximum hardware configuration information can be determined as the accurate hardware configuration information of the first server. The specific execution process when the first hardware configuration information and the target hardware configuration information are the same can be referred to above. When the comparison results are different, fault tolerance can be handled through a fault-tolerant model or the configuration library can be manually populated. The specific execution process when the first hardware configuration information and the target hardware configuration information are different can also be referred to above.

[0102] Optionally, in this method, step S101 may include: The target hardware attribute information of the first server is collected from the first server using a preset acquisition protocol.

[0103] Optionally, after determining the maximum hardware configuration information based on the inclusion relationship, the method may further include: If the first hardware configuration information of the first server is not the maximum hardware configuration information, then the preset acquisition protocol is changed, and the hardware attribute information of the first server is collected again using the changed acquisition protocol to collect the hardware configuration information of the first server.

[0104] Determine if the collected hardware configuration information of the first server is the maximum hardware configuration information. If not, continue to change the acquisition protocol and collect the hardware configuration information of the first server until the collected hardware configuration information of the first server is the maximum hardware configuration information. If it is, record the currently used acquisition protocol and determine it as the optimal acquisition protocol for the first server.

[0105] Specifically, if the first hardware configuration information of the first server is not the aforementioned maximum hardware configuration information, this embodiment can change the acquisition protocol and re-acquire the first hardware configuration information of the first server until the aforementioned maximum hardware configuration information is acquired. At this point, this embodiment can determine the acquisition protocol used to acquire the aforementioned maximum hardware configuration information from the first server as the optimal acquisition protocol adapted to the first server.

[0106] Optionally, after continuing to collect the hardware attribute information of the first server using the changed acquisition protocol to collect the hardware configuration information of the first server, the method further includes: When the hardware configuration information collected by all acquisition protocols is not the maximum hardware configuration information, the first server is subjected to fault tolerance processing through the fault tolerance model.

[0107] It should be noted that when all acquisition protocols fail to acquire the expected result, namely the maximum hardware configuration information mentioned above, from the first server, this embodiment can perform fault tolerance processing on the first server.

[0108] The hardware configuration information processing method proposed in this embodiment can expand the processing scenarios of hardware configuration information, increase the diversity of adaptable scenarios, and further ensure the accuracy of hardware configuration information collected in different scenarios.

[0109] The hardware configuration information processing method proposed in this embodiment can effectively calculate similarity, thereby ensuring the accuracy of hardware configuration information.

[0110] like Figure 2 As shown, this embodiment proposes another method for processing hardware configuration information. This method may include the following steps: S201. Collect all server hardware information using the default protocol.

[0111] It's important to note that when server management software manages a server, it needs to collect the server's hardware configuration information. This serves two purposes: firstly, to display the hardware configuration information of the servers managed by the software to the user; and secondly, to provide the server management software with this information, improving the accuracy of its management. This hardware configuration information can be collected using IPMI, REDFISH, and SNMP protocols. These protocols utilize their interfaces to obtain information such as server model, RAID card model and quantity, disk model and quantity, host bus adapter model and quantity, network card model and quantity, CPU model and quantity, memory model and quantity, fan model and quantity, and power supply model and quantity. However, due to factors such as the server's BMC version, BIOS version, and current environment, the collected hardware configuration information may sometimes be incomplete, leading to less accurate server management by the software.

[0112] Specifically, in this embodiment, after the process begins, a default protocol can be used to collect hardware attribute information from each server.

[0113] S202. Map each hardware six-dimensional vector to the mapping library.

[0114] Specifically, in this embodiment, a six-dimensional vector can be extracted from the hardware attribute information of each server.

[0115] It should be noted that this embodiment can uniquely identify a piece of hardware using six attributes: hardware vendor ID, vendor name, sub-vendor ID, device ID, device name, and sub-device ID. Due to the large number of hardware attributes involved, for the same hardware, the results collected using the same protocol will differ when the server's BMC type and version, BIOS type and version, are different. This embodiment can use the first correspondence stored in the mapping library to map the hardware attribute information of the same hardware to the same type of hardware. Furthermore, the feature vectors corresponding to the six attributes of each type of hardware are used as a set of six-dimensional vectors in the mapping library. For example, a disk array card with the model PM8204 has multiple sets of six-dimensional vectors because PM8204 may have different six attributes under different BMC versions, but the hardware corresponding to the six attributes is the same. The server management software will manage this hardware as PM8204.

[0116] Specifically, in this embodiment, the mapping library can be initialized first, and the 6-dimensional vector that can uniquely identify the hardware, queried through the server protocol, can be mapped to a general model that can be identified by the server management software.

[0117] like Figure 3 As shown, in order to better explain the first correspondence stored in the mapping library, this embodiment proposes its data structure and explains it.

[0118] Reference Figure 3 A server can include various types of hardware, such as network interface cards (NICs), hard drives, and RAID controllers. Each type of hardware has multiple model numbers; for example, RAID controllers have model 1, model 2, and model 3. Each model of hardware also has multiple six-dimensional vectors; for example, a model 2 RAID controller has six-dimensional vector 1, six-dimensional vector 2, and six-dimensional vector 3. The mapping library stores the correspondence between six-dimensional vectors and hardware model numbers; one six-dimensional vector can correspond to one hardware model, and one hardware model can correspond to multiple six-dimensional vectors.

[0119] S203. Determine the relationship between the similarity and the relevant preset value.

[0120] Specifically, for any server, such as the first server, this embodiment can collect the first hardware attribute information of the first server, calculate the similarity between the first hardware attribute information and the hardware attribute information in the mapping library, and determine the relationship between the similarity and the relevant preset value.

[0121] S204. When the similarity is less than 80%, manually populate the mapping library.

[0122] Specifically, when the similarity is less than 80%, it can be assumed that the first hardware attribute information mentioned above does not exist in the mapping library. In this case, the mapping library can be manually filled in by humans based on the first hardware attribute information.

[0123] S205. When the similarity is not less than 80% and less than 100%, a suspected match is identified, manually calibrated, and the mapping library is automatically populated.

[0124] Specifically, when a match is suspected, manual calibration can be supported to determine whether it meets expectations, and the actual results can be synchronously expanded into the mapping library.

[0125] S206. When the similarity is 100%, normalize the six-dimensional vector to obtain the hardware configuration information of each server.

[0126] Specifically, when the similarity is 100%, this embodiment can map the corresponding hardware model.

[0127] Specifically, this embodiment can use a mapping library to map the various hardware attribute information of the first server to the corresponding hardware model, thereby determining the hardware configuration information of the first server. In this way, this embodiment can determine the hardware configuration information of each server.

[0128] S207. Perform configuration normalization on the hardware configuration information of each server.

[0129] Specifically, in this embodiment, the hardware configuration information of each server can be normalized, and the same hardware configuration information can be normalized into one, that is, only one is retained.

[0130] S208. Determine whether there is an inclusion relationship between the various configurations, i.e., the various hardware configuration information. If yes, proceed to step S209. If no, proceed to step S210.

[0131] S209. Intelligently switch acquisition protocols and use the switched acquisition protocol to re-acquire the server's hardware configuration information until the expected results are obtained, completing the internal calibration of the hardware configuration information of each server, i.e., the internal calibration of configuration types is completed. When all protocols fail to acquire the expected results, extract the devices that require fault tolerance for fault tolerance processing.

[0132] It should be noted that customers purchase servers in batches, so each batch of servers has the same factory configuration. However, customers may change the configuration of some servers, resulting in changes to the server configuration.

[0133] Specifically, in this embodiment, after using a mapping library to complete all the hardware configuration information of the managed devices in the server management software, each configuration and its corresponding server serial number are determined, and then the inclusion relationship between each hardware configuration information is determined.

[0134] For example, the hardware configuration information corresponding to configuration 1 is: {"disk": "Hard drive model 1, Hard drive model 2, Hard drive model 3, Hard drive model 4, Hard drive model 5, Hard drive model 6, Hard drive model 7", "psu": "Power supply model 1, Power supply model 2", "nic": "Network card model 1, Network card model 2", "raid": "RAID card model 1, RAID card model 2", "cpu": "CPU model 1, CPU model 2"}, and the information for configuration 2 is: {"disk": "Hard drive model 1, Hard drive model 2, Hard drive model 6, Hard drive model 7", "psu": "Power supply model 1, Power supply model 2", "nic": "Network card model 1, Network card model 2", "raid": "RAID card model 1, RAID card model 2", "cpu": "CPU model 1, CPU model 2"}. As can be seen from the two configurations above, Configuration 1 completely includes Configuration 2. This data feedback indicates that the server corresponding to Configuration 2 did not acquire complete data when scanning using the IPMI protocol. Therefore, it is necessary to intelligently switch protocols for the server in Configuration 2 and re-collect data using REDFISH. If the REDFISH protocol collection results also do not meet expectations, then the SNMP protocol is used to continue collection. If the SNMP protocol still does not meet expectations, the server is tagged, and the user can manually verify the accuracy of the configuration. If the manual verification result is inaccurate, then the intelligent fault-tolerance model is entered for fault tolerance processing. After the above operations, the protocol that collects the most complete data in this embodiment can be determined as the optimal protocol, and the optimal protocol corresponding to the server serial number is recorded. The next time the server collects hardware information, its optimal protocol can be directly used for collection.

[0135] S210. Compare the server's hardware configuration information with the hardware configuration information stored in the configuration library, i.e., calibrate with the configuration library.

[0136] S211. When it is determined that the server's hardware configuration information is a new configuration, the hardware configuration information is populated into the configuration library.

[0137] Specifically, in this embodiment, the configuration library can be initialized first, and the second correspondence and configuration library can be initialized based on the adapted data and server management software compatibility experience. The configuration library can record various configuration information corresponding to each machine model, as well as the optimal BMC version and BIOS version.

[0138] The data structure of the configuration library can be as follows: Figure 4As shown, the configuration types in the configuration library, i.e., hardware configuration information, can be represented by the machine model as the root node, with the model number and quantity of each hardware type as the leaves. For example, the configuration library can include hardware configuration information corresponding to multiple machine models such as Model 1, Model 2, and Model 3. Under Model 2, there are corresponding optimal BMC version, configuration combinations, and optimal BIOS version settings. Configuration combinations include multiple configurations such as Configuration 1, Configuration 2, and Configuration 3, etc., and each configuration is a piece of hardware configuration information. It can be understood that in the second correspondence, one machine model can correspond to one or more types of hardware configuration information.

[0139] Specifically, this embodiment can compare the server's maximum hardware configuration information with the hardware configuration information of the corresponding model in the configuration library to determine whether the server's maximum hardware configuration information is accurate. For example, a certain configuration of model 1 is {"disk": "Hard drive model 1, Hard drive model 2, Hard drive model 3, Hard drive model 4, Hard drive model 5, Hard drive model 6, Hard drive model 7", "psu": "Power supply model 1, Power supply model 2", "nic": "Network card model 1, Network card model 2", "raid": "RAID card model 1, RAID card model 2", "cpu": "CPU model 1, CPU model 2", "memory": "Memory model 1"}. After scanning the server management software, it was found that the maximum configuration information corresponding to the current model is {"disk": "Hard drive model 1, Hard drive model 2, Hard drive model 3, Hard drive model 4, Hard drive model 5, Hard drive model 6, Hard drive model 7", "psu": "Power supply model 1, Power supply model 2", "nic": "Network card model 1, Network card model 2", "raid": "RAID card model 1, RAID card model 2", "cpu": ... The data for "CPU model 1, CPU model 2" is missing memory information compared to the configuration database. However, since the server does not experience a memory shortage, it indicates that the maximum hardware configuration collected by the server management software is likely not as expected. In this case, the device corresponding to the maximum configuration needs to be re-collected using the intelligent switching protocol, and this type of situation should be tagged. If the intelligent switching protocol still does not meet the requirements, it may be a new configuration. This result should be displayed to the user, who can manually verify whether this configuration is new and dynamically expand the configuration database accordingly.

[0140] S212. When the hardware configuration information stored in the configuration library includes the server's hardware configuration information, fault tolerance processing is performed on the server using a fault tolerance model. That is, when the configuration is included, the devices that require fault tolerance are extracted and processed to optimize the server. End of process.

[0141] Specifically, this embodiment can set up an intelligent fault-tolerant model to handle the problem that the hardware configuration cannot be fully collected by the three mainstream protocols.

[0142] In this embodiment, the configuration library initializes the optimal BMC and BIOS versions for each model during initialization, and the optimal versions of BMC and BIOS are dynamically expanded during runtime.

[0143] The hardware configuration information processing method proposed in this embodiment can solve the problem of information omission when server management software collects server hardware configuration information. It can effectively ensure the integrity of the hardware configuration information collected from each server, solve the problem of accurate identification of server hardware, avoid inconsistencies in display due to non-standard interface returns for the same hardware, and effectively ensure that each hardware configuration information can be displayed to the user in a standardized and easy-to-understand manner.

[0144] This embodiment also provides a hardware configuration information processing device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0145] like Figure 5 As shown, this embodiment provides a hardware configuration information processing device, including: The information acquisition module 501 is used to acquire target hardware attribute information of at least one server.

[0146] The first determining module 502 is used to determine the target hardware model of each server based on the target hardware attribute information of each server and in the first correspondence stored in the mapping library. The first correspondence is the correspondence between hardware attribute information and hardware model.

[0147] The second determining module 503 is used to determine the first hardware configuration information of each server based on the target hardware model of each server.

[0148] The first comparison module 504 is used to compare the first hardware configuration information with the target hardware configuration information stored in the configuration library when it is determined that there is no inclusion relationship between each first hardware configuration information.

[0149] The third determining module 505 is used to determine that the first hardware configuration information is accurate hardware configuration information if the first hardware configuration information is the same as the target hardware configuration information.

[0150] Optionally, at least one server includes a first server, and the target hardware attribute information includes at least one hardware attribute information.

[0151] The first determining module 502 is further configured to determine at least one hardware model in the first correspondence based on at least one hardware attribute information in the target hardware attribute information of the first server. The at least one hardware model is then determined as the target hardware model of the first server.

[0152] Optionally, at least one hardware attribute information of the first server includes first hardware attribute information, and the first correspondence includes at least one second hardware attribute information.

[0153] The first determining module 502 is also used to calculate the similarity between each second hardware attribute information and the first hardware attribute information.

[0154] The first determining module 502 is further configured to determine that the second hardware attribute information matches the first hardware attribute information when the similarity is not less than the first preset threshold.

[0155] The first determining module 502 is further configured to determine the first hardware model in the first correspondence relationship based on the second hardware attribute information that matches the first hardware attribute information.

[0156] Optionally, the above-mentioned device further includes: The fourth determining module is used to determine the maximum similarity based on each similarity when each similarity is less than a first preset threshold after calculating the similarity between each second hardware attribute information and the first hardware attribute information.

[0157] The first operation module is used to perform a mapping library filling operation based on the first hardware attribute information when the maximum similarity is less than the second preset threshold.

[0158] The second operation module is used to determine that the first hardware attribute information and the second hardware attribute information are suspected to match when the maximum similarity is not less than the second preset threshold, and to perform calibration and mapping library filling operations based on the first hardware attribute information.

[0159] Optionally, the second determining module 503 is further configured to cluster at least one hardware model among the target hardware models of the first server, and determine at least one type of hardware and the hardware models under each type of hardware. The second determining module 503 is further configured to determine the at least one type of hardware and the hardware models under each type of hardware as the first hardware configuration information of the first server.

[0160] Optionally, the first comparison module 504 is further configured to obtain the model of the first server. The first comparison module 504 is also configured to determine at least one second hardware configuration information based on the model of the first server in a second correspondence stored in the configuration database, and use this as the target hardware configuration information. The second correspondence is a correspondence between server models and hardware configuration information, and in the second correspondence, one server model corresponds to at least one piece of hardware configuration information. The first comparison module 504 is further configured to compare the first hardware configuration information of the first server with each piece of second hardware configuration information.

[0161] Optionally, the third determining module 505 is further configured to determine that the first hardware configuration information is accurate hardware configuration information if the first hardware configuration information of the first server is the same as the second hardware configuration information.

[0162] Optionally, the above-mentioned device further includes: The first processing module is used to perform fault tolerance processing on the first server through a fault tolerance model after comparing the first hardware configuration information of the first server with each second hardware configuration information. If the first hardware configuration information is different from each second hardware configuration information and the second hardware configuration information contains the first hardware configuration information, the module is used to perform fault tolerance processing on the first server.

[0163] The third operation module is used to perform a configuration library filling operation based on the first hardware configuration information if the first hardware configuration information is different from each second hardware configuration information and each second hardware configuration information does not contain the first hardware configuration information.

[0164] Optionally, the first processing module is further configured to determine missing information in the first hardware configuration information relative to the second hardware configuration information. The first processing module is also configured to obtain device characteristic information of the first server. The first processing module is further configured to send the missing information and the device characteristic information to a fault-tolerant model, so that the fault-tolerant model determines a device optimization scheme based on the missing information and the device characteristic information, and performs optimization operations on the first server according to the device optimization scheme.

[0165] Optionally, the above-mentioned device further includes: The deletion module is used to determine and delete other first hardware configuration information that is the same as the first hardware configuration information of the first server after determining the first hardware configuration information of each server according to the target hardware model of each server.

[0166] The fifth determining module is used to determine the maximum hardware configuration information based on the inclusion relationship when it is determined that there is an inclusion relationship between the first hardware configuration information of the first server and other first hardware configuration information.

[0167] The second comparison module is used to compare the maximum hardware configuration information with the target hardware configuration information.

[0168] The output module is used to determine that the maximum hardware configuration information is the accurate hardware configuration information if the maximum hardware configuration information is the same as the target hardware configuration information, and then outputs the maximum hardware configuration information.

[0169] The second processing module is used to perform fault tolerance processing on the first server through a fault tolerance model if the maximum hardware configuration information is different from the target hardware configuration information, or to perform a configuration library filling operation based on the first hardware configuration information.

[0170] Optionally, the information acquisition module 501 is also used to acquire target hardware attribute information of the first server from the first server using a preset acquisition protocol.

[0171] Optionally, the above-mentioned device further includes: The acquisition module is used to determine the maximum hardware configuration information based on the inclusion relationship. If the first hardware configuration information of the first server is not the maximum hardware configuration information, the module will change the preset acquisition protocol and use the changed acquisition protocol to continue to acquire the hardware attribute information of the first server in order to acquire the hardware configuration information of the first server.

[0172] The third processing module determines whether the collected hardware configuration information of the first server is the maximum hardware configuration information. If not, it continues to change the acquisition protocol and acquire the hardware configuration information of the first server until the acquired hardware configuration information of the first server is the maximum hardware configuration information. If so, it records the currently used acquisition protocol and determines it as the optimal acquisition protocol for the first server.

[0173] Optionally, the above-mentioned device further includes: The fourth processing module is used to perform fault tolerance processing on the first server when the hardware configuration information collected by all acquisition protocols is not the maximum hardware configuration information after the hardware attribute information of the first server is collected using the changed acquisition protocol.

[0174] The hardware information processing device proposed in this embodiment can acquire target hardware attribute information for each server, map the target hardware attribute information of each server using a mapping library to determine the target hardware model of each server, and determine the first hardware configuration information of each server based on the target hardware model. If no inclusion relationship exists between the first hardware configuration information pieces, the first hardware configuration information is compared with the target hardware configuration information stored in the configuration library. If they are the same, the first hardware configuration information is determined to be the accurate hardware configuration information. This embodiment can use a mapping library to map each hardware attribute information of the server to a corresponding hardware model, determine the server's hardware configuration information based on the hardware model, and then compare the hardware configuration information with the hardware configuration information stored in the configuration library to determine the accuracy of the server hardware configuration information, effectively ensuring the accuracy of the server hardware configuration information.

[0175] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0176] In this embodiment, the hardware information processing device is presented in the form of a functional unit. Here, a unit refers to an application-specific integrated circuit (ASIC) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0177] This invention also provides a computer device having the above-described features. Figure 5 The hardware information processing device shown.

[0178] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6Take a processor 10 as an example.

[0179] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0180] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0181] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0182] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0183] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0184] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0185] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A hardware configuration information processing method, characterized by, The method includes: Obtain target hardware attribute information of at least one server, wherein the at least one server includes a first server, the target hardware attribute information includes at least one hardware attribute information, and the at least one hardware attribute information of the first server includes a first hardware attribute information. Based on at least one hardware attribute information in the target hardware attribute information of the first server, at least one hardware model is determined in the first correspondence stored in the mapping library, wherein the first correspondence is the correspondence between hardware attribute information and hardware model, and the first correspondence includes at least one second hardware attribute information. The at least one hardware model is determined as the target hardware model of the first server; Determine the first hardware configuration information of each server based on the target hardware model of each server; If it is determined that there is no inclusion relationship between each of the first hardware configuration information, the model of the first server is obtained; At least one second hardware configuration information is determined in the second correspondence stored in the configuration library according to the model of the first server, and is used as the target hardware configuration information. The second correspondence is the correspondence between server model and hardware configuration information, and in the second correspondence, one server model corresponds to at least one hardware configuration information. The first hardware configuration information of the first server is compared with each of the second hardware configuration information. If the first hardware configuration information of the first server is the same as the second hardware configuration information, then the first hardware configuration information is determined to be accurate hardware configuration information. The step of determining at least one hardware model in the first correspondence stored in the mapping library based on at least one hardware attribute information in the target hardware attribute information of the first server includes: Calculate the similarity between each of the second hardware attribute information and the first hardware attribute information; When the similarity is not less than a first preset threshold, it is determined that the second hardware attribute information matches the first hardware attribute information. The first hardware model is determined in the first correspondence based on the second hardware attribute information that matches the first hardware attribute information.

2. The method of claim 1, wherein, After calculating the similarity between each piece of second hardware attribute information and the first hardware attribute information, the method further includes: When each of the similarities is less than the first preset threshold, the maximum similarity is determined based on each of the similarities. When the maximum similarity is less than the second preset threshold, a mapping library filling operation is performed based on the first hardware attribute information. When the maximum similarity is not less than the second preset threshold, it is determined that the first hardware attribute information and the second hardware attribute information are suspected to match, and calibration and mapping library filling operations are performed based on the first hardware attribute information.

3. The method according to claim 1 or 2, characterized in that, The step of determining the first hardware configuration information of each server based on the target hardware model of each server includes: Cluster the at least one hardware model among the target hardware models of the first server, and determine at least one type of hardware and the hardware models under each type of hardware; The at least one type of hardware and the hardware models under each type of hardware are determined as the first hardware configuration information of the first server.

4. The method according to claim 1 or 2, characterized in that, After comparing the first hardware configuration information of the first server with each of the second hardware configuration information, the method further includes: If the first hardware configuration information is different from each of the second hardware configuration information, and the second hardware configuration information contains the first hardware configuration information, then the first server is subjected to fault tolerance processing through the fault tolerance model. If the first hardware configuration information is different from each of the second hardware configuration information, and each of the second hardware configuration information does not contain the first hardware configuration information, then a configuration library filling operation is performed based on the first hardware configuration information.

5. The method according to claim 4, characterized in that, The fault-tolerant processing of the first server using a fault-tolerant model includes: Determine the missing information in the first hardware configuration information relative to the second hardware configuration information; Obtain the device characteristic information of the first server; The missing information and the device feature information are sent to the fault tolerance model so that the fault tolerance model can determine the device optimization scheme based on the missing information and the device feature information, and perform optimization operations on the first server based on the device optimization scheme.

6. The method according to claim 1 or 2, characterized in that, After determining the first hardware configuration information of each server based on the target hardware model of each server, the method further includes: Identify and delete other first hardware configuration information that is identical to the first hardware configuration information of the first server; If it is determined that there is an inclusion relationship between the first hardware configuration information of the first server and other first hardware configuration information, the maximum hardware configuration information is determined according to the inclusion relationship; Compare the maximum hardware configuration information with the target hardware configuration information; If they are the same, then the maximum hardware configuration information is determined to be the accurate hardware configuration information, and the maximum hardware configuration information is output. If they are different, the first server is subjected to fault tolerance processing through the fault tolerance model, or a configuration library filling operation is performed based on the first hardware configuration information.

7. The method according to claim 6, characterized in that, The step of obtaining target hardware attribute information for at least one server includes: The target hardware attribute information of the first server is collected from the first server using a preset acquisition protocol; After determining the maximum hardware configuration information based on the inclusion relationship, the method further includes: If the first hardware configuration information of the first server is not the maximum hardware configuration information, then the preset acquisition protocol is changed, and the hardware attribute information of the first server is collected again using the changed acquisition protocol to collect the hardware configuration information of the first server. Determine whether the collected hardware configuration information of the first server is the maximum hardware configuration information. If not, continue to change the acquisition protocol and collect the hardware configuration information of the first server until the collected hardware configuration information of the first server is the maximum hardware configuration information. If yes, record the currently used acquisition protocol and determine it as the optimal acquisition protocol for the first server.

8. The method according to claim 7, characterized in that, After continuing to collect hardware attribute information of the first server using the changed acquisition protocol to collect the hardware configuration information of the first server, the method further includes: When the hardware configuration information collected by all acquisition protocols is not the maximum hardware configuration information, the first server is subjected to fault tolerance processing through the fault tolerance model.

9. A hardware configuration information processing device, characterized in that, The device includes: An information acquisition module is used to acquire target hardware attribute information of at least one server, wherein the at least one server includes a first server, the target hardware attribute information includes at least one hardware attribute information, and the at least one hardware attribute information of the first server includes a first hardware attribute information. The first determining module is configured to determine at least one hardware model in a first correspondence stored in a mapping library based on at least one hardware attribute information in the target hardware attribute information of the first server, wherein the first correspondence is a correspondence between hardware attribute information and hardware model, and the first correspondence includes at least one second hardware attribute information; and determine the at least one hardware model as the target hardware model of the first server. The second determining module is used to determine the first hardware configuration information of each server according to the target hardware model of each server; The first comparison module is configured to: obtain the model of the first server when it is determined that there is no inclusion relationship between each of the first hardware configuration information; determine at least one second hardware configuration information in the second correspondence relationship stored in the configuration library according to the model of the first server, and use it as the target hardware configuration information, wherein the second correspondence relationship is the correspondence relationship between server model and hardware configuration information, and in the second correspondence relationship, one server model corresponds to at least one hardware configuration information; and compare the first hardware configuration information of the first server with each of the second hardware configuration information. The third determining module is used to determine that the first hardware configuration information is accurate hardware configuration information if the first hardware configuration information is the same as the target hardware configuration information. The step of determining at least one hardware model in the first correspondence stored in the mapping library based on at least one hardware attribute information in the target hardware attribute information of the first server includes: Calculate the similarity between each of the second hardware attribute information and the first hardware attribute information; When the similarity is not less than a first preset threshold, it is determined that the second hardware attribute information matches the first hardware attribute information. The first hardware model is determined in the first correspondence based on the second hardware attribute information that matches the first hardware attribute information.

10. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the hardware configuration information processing method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the hardware configuration information processing method according to any one of claims 1 to 8.

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