A server determination method, apparatus, storage medium, and electronic device

Abstract

This application discloses a server determination method, apparatus, storage medium, and electronic device, relating to the field of cloud computing technology. The method includes: responding to a cloud server creation request, determining evaluation data for cloud server creation from multiple physical servers; based on the evaluation data, determining a target physical server from the multiple physical servers that meets the creation conditions, and using the target physical server to create the cloud server; and updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions if the creation of the target physical server fails. Compared with existing technologies, this application determines the target physical server based on evaluation data and performs the creation operation, updating its evaluation data to target evaluation data that does not meet the creation conditions when the creation of the target physical server fails. This avoids subsequent creation tasks being repeatedly assigned to the same physical server, reduces repeated creation failures, and ensures normal business operations.

Description

Technical Field

[0001] This application relates to the field of cloud computing technology, and in particular to a server determination method, apparatus, storage medium, and electronic device. Background Technology

[0002] In the field of cloud computing technology, cloud servers are created based on the virtualization technology of the host machine. The host machine deploys virtualization, storage, and network-related applications to support the operation of the cloud server. When the virtualization components of the host machine malfunction, the creation of the cloud server will fail.

[0003] Currently, cloud server creation uses a multi-level binning algorithm, which determines the available host machines for creating cloud servers through hard filtering conditions and priority sorting.

[0004] However, if the virtualization component of the host machine fails and the cloud server creation fails, this method cannot adjust the host machine selection logic based on the failure result. When the user retryes the creation task, the task will still be assigned to the faulty host machine, causing the creation task to fail repeatedly and affecting the normal operation of the business. Summary of the Invention

[0005] In view of this, this application provides a server determination method, apparatus, storage medium, and electronic device. The main purpose is to improve the technical problem that when the virtualization component of the host machine fails and the cloud server creation fails, the existing technology cannot adjust the host machine selection logic based on the failure result. When the user retryes the creation task, the task will still be assigned to the faulty host machine, resulting in repeated failures of the creation task and affecting the normal operation of the business.

[0006] Firstly, this application provides a method for determining a server, including: In response to a cloud server creation request, evaluation data for cloud server creation is determined from multiple physical servers, and the evaluation data is determined based on the historical creation results of the multiple physical servers; Based on the evaluation data, a target physical server that meets the creation conditions is determined from the plurality of physical servers, and the cloud server is created using the target physical server; If the creation of the target physical server fails, the evaluation data of the target physical server will be updated to target evaluation data that does not meet the creation conditions.

[0007] Optionally, determining a target physical server that meets the creation conditions from the plurality of physical servers based on the evaluation data, and using the target physical server to create a cloud server, includes: The evaluation data are sorted by priority from high to low, and the physical server with the highest evaluation data is determined as the target physical server. The cloud server is created using the target physical server.

[0008] Optionally, in the event that the creation of the target physical server fails, updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions includes: If the creation of the target physical server fails, a first adjustment value corresponding to the target physical server is determined based on the evaluation data of the other physical servers among the plurality of physical servers besides the target physical server. The difference between the evaluation data of the target physical server and the first value to be adjusted is determined as the target evaluation data.

[0009] Optionally, the method further includes: if the target physical server is successfully created, determining a second value to be adjusted corresponding to the target physical server based on the evaluation data of the other physical servers among the plurality of physical servers besides the target physical server; The sum of the evaluation data of the target physical server and the second value to be adjusted is determined as the updated evaluation data.

[0010] Optionally, after updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions in the event that the creation of the target physical server fails, the method further includes: If the target evaluation data is lower than the evaluation data threshold, the target physical server will be identified as an abnormal physical server. The exception handling module generates an exception alarm message for the abnormal physical server and removes the abnormal physical server from the candidate resource pool created by the cloud server.

[0011] Optionally, the exception handling module generates an exception alarm information for the abnormal physical server and removes the abnormal physical server from the candidate resource pool created by the cloud server, including: The abnormal physical server is generated through the abnormality handling module; Get the number of abnormal physical servers removed within the target time period; If the number of removals is less than or equal to the removal threshold, the abnormal physical server will be removed from the candidate resource pool created by the cloud server.

[0012] Optionally, after removing the abnormal physical server from the candidate resource pool created by the cloud server, the method further includes: Once the abnormal physical server has completed its anomaly repair, the anomaly evaluation data of the abnormal physical server is updated to the maximum evaluation data value, and the abnormal physical server is added to the candidate resource pool for cloud server creation.

[0013] Secondly, this application provides a server determining device, comprising: The determination module is configured to, in response to a cloud server creation request, determine evaluation data for cloud server creation using multiple physical servers, wherein the evaluation data is determined based on the historical creation results of the multiple physical servers; The determination module is also configured to determine a target physical server that meets the creation conditions from the plurality of physical servers based on the evaluation data, and to use the target physical server to create a cloud server; The update module is configured to update the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions if the creation of the target physical server fails.

[0014] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the server determination method described in the first aspect.

[0015] Fourthly, this application provides an electronic device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the computer program to implement the server determination method described in the first aspect.

[0016] Fifthly, this application provides a computer program product, which includes a computer program that, when executed by a processor, implements the server determination method described in the first aspect.

[0017] By employing the above technical solutions, this application provides a server determination method, apparatus, storage medium, and electronic device. In response to a cloud server creation request, it determines evaluation data for cloud server creation from multiple physical servers. This evaluation data is determined based on the historical creation results of the multiple physical servers. Based on the evaluation data, it identifies a target physical server from the multiple physical servers that meets the creation conditions and uses the target physical server to create the cloud server. If the creation of the target physical server fails, it updates the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions. Compared with existing technologies, this application, by determining the evaluation data of multiple physical servers in response to a cloud server creation request, achieves accurate screening of candidate physical servers based on historical creation results; by determining the target physical server based on the evaluation data and performing the creation operation, it ensures the targeted nature of cloud server creation; and by updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions when creation fails, it avoids subsequent creation tasks being repeatedly assigned to that physical server, reduces repeated creation failures, and ensures normal business operations. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic flowchart of a server determination method provided in an embodiment of this application is shown; Figure 2 A schematic flowchart of a server determination method provided in an embodiment of this application is shown; Figure 3 This document illustrates a flowchart illustrating an example of a host creation success score determination process provided in an embodiment of this application. Figure 4 A flowchart illustrating an example of exception event handling provided in an embodiment of this application is shown. Figure 5 This illustration shows a schematic diagram of the structure of a server determination device provided in an embodiment of this application; Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0021] The embodiments of this application will now be described in more detail with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0022] To address the technical issue of existing technologies failing to adjust host selection logic based on failure results when virtualization component failures on the host machine lead to cloud server creation failures, resulting in repeated creation failures and impacting normal business operations, this embodiment provides a server determination method, such as... Figure 1 As shown, the method includes: Step 101: In response to the cloud server creation request, determine the evaluation data for cloud server creation from multiple physical servers.

[0023] The evaluation data was determined based on the historical creation results of multiple physical servers.

[0024] In this embodiment, the physical server can be a host machine that hosts the cloud server in a cloud computing scenario. The physical server can be used to provide basic resource support such as computing, storage, and networking for the cloud server through virtualization technology. For example, the physical server in this embodiment can specifically be a physical machine that deploys virtualization, storage, and network-related applications. The physical server can virtualize its own hardware resources through virtualization components and allocate them to the cloud server to ensure the normal creation and operation of the cloud server.

[0025] In this embodiment of the application, the evaluation data can be a quantitative indicator characterizing the availability of cloud servers created by physical servers. The evaluation data can reflect the impact of the physical server's historical successes or failures in creating cloud servers on its current creation capability. For example, the evaluation data in this embodiment can specifically be the host machine's cloud server creation success score (corresponding to a newly added field `run_instance_succ_score` in the host machine resource table of the database). This score can store the results of the physical server's most recent cloud server creations, providing a basis for subsequent selection of target physical servers.

[0026] In the embodiments of this application, historical creation results can be used to dynamically adjust the values ​​of evaluation data. Specifically, historical creation results can include two situations: creation success and creation failure. Creation failure can further include failure caused by abnormality of physical server virtualization components. Different historical creation results correspond to different evaluation data update rules.

[0027] In this embodiment, when a cloud server creation request is received, the system can read the run_instance_succ_score field values ​​corresponding to multiple physical servers from the host resource table of the database as evaluation data for each physical server. The initial value of the evaluation data can be preset to a fixed value. For example, in this embodiment, the default value of the evaluation data can be 100, and this value can be dynamically updated as the physical server creation results continue.

[0028] Step 102: Based on the evaluation data, determine the target physical server that meets the creation conditions from multiple physical servers, and use the target physical server to create the cloud server.

[0029] In this embodiment, the creation conditions can be criteria used to filter physical servers capable of creating cloud servers. These conditions may include requirements for the values ​​of evaluation data, hardware resource requirements, and other priority-related requirements. For example, the creation conditions in this embodiment may specifically include evaluation data meeting a preset value range, the number of CPUs, memory size, hard disk size of the physical server, whether the host machine is empty, CPU fragmentation rate, and whether the image cache meets the requirements for cloud server creation.

[0030] In this embodiment of the application, the target physical server may be the physical server selected from multiple physical servers that best meets the requirements for creating a cloud server.

[0031] In this embodiment of the application, the selection of target physical servers based on evaluation data can be achieved by using hard filtering conditions to initially screen physical servers in the candidate resource pool. Each time the list of physical servers passes through a filtering condition, some physical servers that do not meet the condition will be filtered out. The remaining list of physical servers will then be used as input for the next filtering condition until the initial screening is completed. The remaining physical servers are then prioritized and sorted according to priority-related requirements in the creation conditions, including but not limited to evaluation data, whether it is an empty host, CPU fragmentation rate, etc. The priority weight of the evaluation data can be set to a high level. Physical servers with higher evaluation data have higher sorting priority, and physical servers with lower evaluation data have lower sorting priority. The physical server with the highest priority in the sorting results can be determined as the target physical server, and the system can use the target physical server to perform cloud server creation operations.

[0032] Step 103: If the creation of the target physical server fails, update the evaluation data of the target physical server to the target evaluation data that does not meet the creation conditions.

[0033] In this embodiment of the application, the target evaluation data can be the evaluation data updated after the creation of the target physical server fails. The target evaluation data can be used to reduce the probability that the physical server will be selected subsequently. For example, the target evaluation data in this embodiment of the application can be a value adjusted based on the original evaluation data, and the value of the target evaluation data can be lower than the minimum requirement for evaluation data in the creation conditions.

[0034] In this embodiment of the application, failure to meet the creation conditions may be due to the value of the target evaluation data exceeding the preset qualified range of evaluation data in the creation conditions.

[0035] In the embodiments of this application, if the creation of a cloud server fails on the target physical server, the reason for the failure is an abnormality in the virtualization component of the target physical server (an abnormality in the virtualization component will directly cause the cloud server to fail to be created successfully based on the physical server, without affecting the server side of storage and network-related applications). The original evaluation data of the target physical server can be updated to the target evaluation data, and the updated target evaluation data will be lower than the original evaluation data. When the user tries to create a cloud server again, the system will prioritize recommending other physical servers besides the target physical server, thereby avoiding repeated failures of the creation task.

[0036] Compared with the prior art, the embodiments of this application determine the evaluation data of multiple physical servers in response to the cloud server creation request, thereby achieving accurate screening of candidate physical servers based on historical creation results; by determining the target physical server based on the evaluation data and performing the creation operation, the targeted nature of cloud server creation is ensured; and by updating the evaluation data of the target physical server to the target evaluation data that does not meet the creation conditions when the creation of the target physical server fails, subsequent creation tasks are avoided from being repeatedly assigned to the same physical server, reducing the situation of repeated creation failures and ensuring the normal operation of business.

[0037] As an optional approach, when performing the task of "determining the target physical server that meets the creation conditions from multiple physical servers based on evaluation data, and using the target physical server to create the cloud server," the following methods can be used, but are not limited to them: Figure 2 As shown, the method includes: Step 201: Sort the evaluation data in descending order of priority, and determine the physical server with the highest evaluation data as the target physical server.

[0038] In this embodiment, the evaluation data can be used as the sorting criterion for prioritizing physical servers. The sorting rule can be set to sort the evaluation data from highest to lowest value. For example, there are 5 physical servers in the candidate resource pool, all of which meet the basic requirements related to hardware resources and priority in the creation conditions. Their evaluation data are 100, 80, 50, and 30, respectively. After sorting them in descending order, they are, in order, physical server A with evaluation data of 100, physical server B with evaluation data of 80, physical server C with evaluation data of 50, and physical server D with evaluation data of 30. Physical server A with the highest evaluation data can be determined as the target physical server.

[0039] Step 202: Create a cloud server using the target physical server.

[0040] In this embodiment of the application, the cloud server is created using the target physical server with the highest evaluation data.

[0041] As an optional approach, when executing "updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions in the event that the target physical server fails to be created", the following method can be used, but is not limited to: in the event that the target physical server fails to be created, determining the first value to be adjusted corresponding to the target physical server based on the evaluation data of the other physical servers among multiple physical servers besides the target physical server; and determining the difference between the evaluation data of the target physical server and the first value to be adjusted as the target evaluation data.

[0042] In this embodiment of the application, the evaluation data of other physical servers can reflect the overall creation capability level of physical servers in the current candidate resource pool.

[0043] In this embodiment of the application, the first value to be adjusted can be a dynamic value used to adjust the evaluation data of the target physical server. The value to be adjusted is not fixed and can be dynamically determined according to the overall evaluation of the physical servers in the resource pool, so as to avoid the problem of insufficient scenario adaptation caused by a single fixed value.

[0044] In the embodiments of this application, the determination of the first value to be adjusted may be to perform statistical analysis on the evaluation data of all other physical servers except the target physical server. The statistical dimensions may include, but are not limited to, the mean, median, mode, standard deviation, etc. of the evaluation data, and the first value to be adjusted is determined based on the data of the statistical analysis.

[0045] For example, if the average value of the evaluation data of other physical servers is A and the standard deviation is B, the calculation rules for the value to be adjusted can be set based on the average value and the standard deviation. When the original evaluation data of the target physical server is higher than the average value A, the value to be adjusted can be set as the difference between A and B; when the original evaluation data of the target physical server is lower than or equal to the average value A, the value to be adjusted can be set as half of A.

[0046] For example, the value to be adjusted can be determined based on the distribution range of evaluation data from other physical servers. If the evaluation data of other servers is mainly concentrated in the high range of [80, 100], the value to be adjusted can be set to 15% (i.e., 9) of the lower limit of this range to ensure that the evaluation data drops outside this range after the target physical server fails. If the evaluation data of other servers is concentrated in the medium range of [50, 80], the value to be adjusted can be set to 10% (i.e., 5) of the lower limit of this range to make the evaluation data of the target physical server different from the evaluation data of other servers.

[0047] It should be noted that determining the value to be adjusted requires adjusting the evaluation data of the target physical server that failed to be created. At the same time, it is also necessary to avoid the adjustment range deviating from the overall evaluation level of physical servers in the resource pool, so as to ensure that subsequent cloud server creation can prioritize other physical servers with better evaluation data.

[0048] For the embodiments of this application, the calculation formula for the target evaluation data can be as shown in Formula 1, and the target evaluation data can be the difference between the evaluation data and the value to be adjusted.

[0049] Target evaluation data = Original evaluation data of the target physical server - Value to be adjusted (Formula 1) As an optional approach, embodiments of this application may also employ the following method, but not limited thereto: the method includes: when the target physical server is successfully created, determining a second value to be adjusted corresponding to the target physical server based on the evaluation data of the other physical servers among the multiple physical servers besides the target physical server; and determining the sum of the evaluation data of the target physical server and the second value to be adjusted as the updated evaluation data.

[0050] In this embodiment of the application, the second value to be adjusted can be a dynamic value used to adjust the evaluation data of the target physical server. The value to be adjusted is not fixed and can be dynamically determined according to the overall evaluation of the physical servers in the resource pool, so as to avoid the problem of insufficient scenario adaptation caused by a single fixed value.

[0051] In the embodiments of this application, the determination of the second value to be adjusted may be based on the statistical analysis of the evaluation data of other physical servers besides the target physical server. The statistical dimensions may include, but are not limited to, the maximum value, average value, median, mode, standard deviation, etc. of the evaluation data, and the second value to be adjusted may be determined based on the data of the statistical analysis.

[0052] For example, if physical server A's evaluation data drops to 50 due to a previous creation failure, and the maximum value of the evaluation data is 100; if physical server A successfully creates a cloud server this time, it means that the virtualization components, hardware resources, etc. of physical server A are in normal condition. The evaluation data of physical server A and the second data to be adjusted can be added together to obtain the maximum value of the evaluation data, that is, the evaluation data is restored from 50 to 100, so that physical server A can obtain a higher ranking in the subsequent priority sorting and can be selected as the target physical server first.

[0053] As an optional approach, after executing "updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions in the event that the target physical server creation fails", the following method can be used, but is not limited to: if the target evaluation data is lower than the evaluation data threshold, the target physical server is identified as an abnormal physical server; abnormal alarm information of the abnormal physical server is generated through the abnormal handling module, and the abnormal physical server is removed from the candidate resource pool created by the cloud server.

[0054] In this embodiment of the application, the evaluation data threshold can be a threshold condition used to determine whether the physical server is in a faulty state. The evaluation data threshold can be set based on the value range of the evaluation data. For example, the evaluation data threshold in this embodiment of the application can specifically be 0. When the evaluation data is less than 0, it can be indicated that the physical server has failed to create multiple times due to virtualization component anomalies.

[0055] In the embodiments of this application, an abnormal physical server can be a target physical server that meets abnormal conditions, and an abnormal physical server can be a physical server that needs to be isolated and repaired. For example, in the embodiments of this application, an abnormal physical server can specifically be a physical server whose evaluation data is less than 0 and whose virtualization component exhibits abnormalities.

[0056] In this embodiment, the exception handling module can be a functional module for handling abnormal states of physical servers, and it can work in conjunction with message queues and alarm platforms. For example, the exception handling module in this embodiment can specifically be an event handling module, which can capture abnormal events and perform alarm and isolation operations.

[0057] In this embodiment, the candidate resource pool can be a collection of physical servers qualified to create cloud servers, and the candidate resource pool can provide a filtering basis for resource scheduling. For example, in this embodiment, the candidate resource pool can specifically be a list of physical servers recorded in a database, filtered by hard filtering and priority conditions.

[0058] In this embodiment of the application, after updating the target evaluation data, it can be detected whether the target evaluation data meets the abnormal condition (i.e., target evaluation data < 0). If the abnormal condition is met, the target physical server can be identified as an abnormal physical server.

[0059] In this embodiment, the resource scheduling module publishes abnormal events to a message queue. The message queue, as middleware, enables loose coupling between the resource scheduling module and the exception handling module, reducing development costs for adding new requirements and functions. After the exception handling module captures the abnormal event by listening to the message queue, it can link with the alarm platform to generate abnormal alarm information. The alarm information may include the identifier of the abnormal physical server, the time of the abnormality, evaluation data, etc., to notify the operation and maintenance personnel to handle the fault in a timely manner. The exception handling module can perform isolation operations to remove the abnormal physical server from the candidate resource pool created by the cloud server, so that it no longer participates in the cloud server creation process (hard filtering, priority sorting, and evaluation data sorting).

[0060] As an optional approach, when executing "generating abnormal alarm information for abnormal physical servers through the abnormal handling module and removing abnormal physical servers from the candidate resource pool created by the cloud server", the following method can be used, but is not limited to: generating abnormal alarm information for abnormal physical servers through the abnormal handling module; obtaining the number of abnormal physical servers removed within the target time; and removing the abnormal physical servers from the candidate resource pool created by the cloud server if the number of removals is less than or equal to a removal number threshold, wherein the removal number threshold is the maximum number of abnormal physical servers to be removed within the target time.

[0061] In this embodiment of the application, the target time can be a preset statistical time span, which can be set according to business needs and resource pool size. For example, the target time in this embodiment of the application can specifically include, but is not limited to, different time periods such as 1 hour, 2 hours, 12 hours, and 24 hours.

[0062] In this embodiment, the removal quantity can be the total number of abnormal physical servers removed from the candidate resource pool within a target time period. For example, in this embodiment, the removal quantity can specifically be the number of physical servers whose evaluation data is less than 0 and for which isolation operations have been performed within a target time period.

[0063] In this embodiment of the application, the removal quantity threshold can be the maximum number of abnormal physical servers allowed to be removed within a target time period. The removal quantity threshold can be set based on factors such as the total capacity of the candidate resource pool and the minimum resource requirements of the business. For example, the removal quantity threshold in this embodiment of the application can be 5 servers to be removed within 1 hour, 20 servers to be removed within 24 hours, etc.

[0064] In this embodiment of the application, after the exception handling module generates the exception alarm information, it can determine the removal quantity threshold corresponding to the current target time and count the total number of exception physical servers that have been removed within the target time. If the counted removal quantity is less than or equal to the corresponding removal quantity threshold, an isolation operation can be performed to remove the current exception physical server from the candidate resource pool. If the removal quantity is greater than the removal quantity threshold, the isolation operation can be paused, and only an exception alarm information can be generated to notify the operation and maintenance personnel to intervene and handle the issue.

[0065] As an optional approach, after executing "removing the abnormal physical server from the candidate resource pool for cloud server creation", the following method can be used, but is not limited to: if the abnormal physical server has completed the abnormal repair, update the abnormal evaluation data of the abnormal physical server to the maximum value of the evaluation data, and add the abnormal physical server to the candidate resource pool for cloud server creation.

[0066] In this embodiment, anomaly repair can be the process by which operations and maintenance personnel handle faults in abnormal physical servers. Anomaly repair can include operations such as repairing and maintaining virtualization components. For example, in this embodiment, anomaly repair can specifically involve IT operations and maintenance personnel investigating and repairing the virtualization components of the abnormal physical server after receiving alarm information.

[0067] In this embodiment, the maximum value of the evaluation data can be the upper limit of the evaluation data value, and the maximum value of the evaluation data can be used to characterize that the physical server is in the optimal creation state. For example, the maximum value of the evaluation data in this embodiment can specifically be 100, and the maximum value of the evaluation data can be consistent with the default value of the evaluation data.

[0068] In the embodiments of this application, after the abnormal physical server completes the abnormal repair, the evaluation data update instruction can be triggered by the operation and maintenance personnel. The system can update the current abnormal evaluation data of the abnormal physical server (i.e., evaluation data less than 0) to the maximum value of 100. At the same time, the repaired physical server can be added back to the candidate resource pool created by the cloud server, so that it can participate in the creation of the cloud server and realize the recycling of physical server resources.

[0069] Optionally, embodiments of this application also provide an example of a process for determining the success score of host creation, the flowchart of which is as follows: Figure 3 As shown, Figure 3 The specific process may include: the default score (i.e., the evaluation data in this embodiment) for the successful creation of a cloud server by each host machine (i.e., the physical server in this embodiment) is 100, and the maximum score is 100; when the cloud server is successfully created, the success score is modified to 100; when the cloud server creation fails, if it is due to an abnormality in the virtualization component on the host machine, the success score is reduced by 50; if the score is less than 0, it indicates that the host machine can no longer create a cloud server, triggering an abnormal event and isolating the host machine (i.e., removing the abnormal physical server from the candidate resource pool in this embodiment), no longer participating in the packing process, and generating an alarm to notify the operation and maintenance personnel to handle it; after the operation and maintenance personnel have handled it, they can modify the success score back to 100.

[0070] Optionally, embodiments of this application also provide an example of abnormal event handling, the flowchart of which is as follows: Figure 4 As shown, Figure 4 The specific process may include: the resource scheduling module (containing a bin packing algorithm) obtains and modifies the host information in the database (including the evaluation data in the embodiments of this application). When an anomaly is detected, the resource scheduling module can publish an anomaly event to the message queue. The event handling module can capture the anomaly event in the message queue. The event handling module links with the alarm platform to generate anomaly alarm information and synchronously modifies the host information in the database to complete the transmission, processing and updating of the corresponding data of the anomaly event.

[0071] Compared with existing technologies, this application's embodiments improve the efficiency and accuracy of cloud server creation by sorting evaluation data from high to low to determine target physical servers and executing their creation. In cases where target physical server creation fails or succeeds, the system determines the adjustment value based on the evaluation data of other physical servers and updates the target evaluation data, achieving reasonable dynamic adjustment of the evaluation data. By identifying abnormal physical servers when the target evaluation data falls below the evaluation data threshold, generating alarm information, and removing them from the candidate resource pool, the system achieves timely identification and scheduling isolation of abnormal physical servers. After generating abnormal alarm information, the system obtains the removal quantity within the target time period and performs removal operations when the removal quantity does not exceed the threshold, avoiding resource risks caused by large-scale physical server removal. Finally, by updating the evaluation data of abnormal physical servers after repair and re-adding them to the candidate resource pool, the system achieves the recycling of physical server resources.

[0072] Furthermore, as Figure 1 and Figure 2To illustrate the specific implementation of the method shown, this embodiment provides a server determination device, such as... Figure 5 As shown, the device includes: a determination module 31 and an update module 32.

[0073] The determination module 31 is configured to, in response to a cloud server creation request, determine evaluation data for cloud server creation from multiple physical servers. The evaluation data is determined based on the historical creation results of the multiple physical servers. The determination module 31 is also configured to determine the target physical server that meets the creation conditions from multiple physical servers based on the evaluation data, and to use the target physical server to create the cloud server; Update module 32 is configured to update the evaluation data of the target physical server to the target evaluation data that does not meet the creation conditions if the creation of the target physical server fails.

[0074] In some examples of this embodiment, the determining module 31 is specifically configured to prioritize the evaluation data in descending order, determine the physical server with the highest evaluation data as the target physical server, and use the target physical server to create the cloud server.

[0075] In some examples of this embodiment, the update module 32 is specifically configured to, in the event that the creation of the target physical server fails, determine the first value to be adjusted corresponding to the target physical server based on the evaluation data of the other physical servers among the multiple physical servers besides the target physical server; and determine the difference between the evaluation data of the target physical server and the first value to be adjusted as the target evaluation data.

[0076] In some examples of this embodiment, the determining module 31 is specifically configured to, when the target physical server is successfully created, determine the second value to be adjusted corresponding to the target physical server based on the evaluation data of the other physical servers among the multiple physical servers besides the target physical server; and determine the sum of the evaluation data of the target physical server and the second value to be adjusted as the updated evaluation data.

[0077] In some examples of this embodiment, the update module 32 is further configured to identify the target physical server as an abnormal physical server when the target evaluation data is lower than the evaluation data threshold; generate abnormal alarm information for the abnormal physical server through the abnormal handling module; and remove the abnormal physical server from the candidate resource pool created by the cloud server.

[0078] In some examples of this embodiment, the update module 32 is further configured to generate abnormal alarm information of abnormal physical servers through the abnormal handling module; obtain the number of abnormal physical servers removed within the target time; and remove the abnormal physical servers from the candidate resource pool created by the cloud server if the number of removals is less than or equal to the removal number threshold.

[0079] In some examples of this embodiment, the determining module 32 is further configured to update the abnormal evaluation data of the abnormal physical server to the maximum value of the evaluation data and add the abnormal physical server to the candidate resource pool for cloud server creation when the abnormal physical server completes the abnormal repair.

[0080] It should be noted that other corresponding descriptions of the functional units involved in the server determination device provided in this embodiment can be found in [reference]. Figure 1 and Figure 2 The corresponding description in [the document] will not be repeated here.

[0081] Based on the above, Figure 1 and Figure 2 Accordingly, this embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. Figure 1 and Figure 2 The method shown.

[0082] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to enable a computer device (such as a personal computer, server, or physical server, etc.) to execute the methods of various implementation scenarios of this application.

[0083] like Figure 6 The diagram shown is a hardware structure schematic of an electronic device according to the present invention, comprising: At least one processor 401; and, Memory 402 is communicatively connected to at least one processor 401; wherein, The memory 402 stores instructions that can be executed by at least one processor to enable the at least one processor to perform the server determination method as described above.

[0084] Figure 6 Take a processor 401 as an example.

[0085] The electronic device may also include an input device 403 and an output device 404.

[0086] The processor 401, memory 402, input device 403, and output device 404 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0087] Memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the server determination method in the embodiments of this application, for example, Figure 1 and Figure 2 The method flow is shown. The processor 401 executes various functional applications and data processing by running non-volatile software programs, instructions, and modules stored in the memory 402, thereby implementing the server determination method in the above embodiments.

[0088] Memory 402 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 according to the use of the server-determined method, etc. Furthermore, memory 402 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 402 may optionally include memory remotely located relative to processor 401, and these remote memories may be connected via a network to the apparatus executing the server-determined method. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0089] Input device 403 can receive user clicks and generate signal inputs related to user settings and function control determined by the server. Output device 404 may include display devices such as a display screen.

[0090] One or more modules are stored in memory 402, and when run by one or more processors 401, the server determination method in any of the above method embodiments is executed.

[0091] Optionally, the aforementioned physical devices may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0092] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0093] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0094] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms, or it can be implemented by hardware. By applying the solution of this embodiment, compared with related technologies, this application embodiment determines the evaluation data of multiple physical servers in response to cloud server creation requests, and realizes accurate screening of candidate physical servers based on historical creation results; by determining the target physical server according to the evaluation data sorting and executing the creation operation, the targetedness and efficiency of cloud server creation are ensured; by determining the value to be adjusted based on the evaluation data of other physical servers when creation fails, and updating the target evaluation data to the value that does not meet the creation conditions, the evaluation data is reasonably and dynamically adjusted, avoiding the repeated allocation of subsequent creation tasks to the same physical server and reducing the situation of repeated creation failures; by identifying abnormal physical servers when the target evaluation data is lower than the evaluation data threshold, generating alarm information, and removing them from the candidate resource pool within the target time if the number of removals does not exceed the threshold, the abnormal physical servers are identified and scheduled and isolated in a timely manner, avoiding resource risks caused by the removal of a large number of physical servers; by updating the evaluation data of abnormal physical servers after repair and re-adding them to the candidate resource pool, the recycling of physical server resources is realized, ensuring the normal operation of business.

[0095] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0096] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for determining a server, characterized in that, include: In response to a cloud server creation request, evaluation data for cloud server creation is determined from multiple physical servers, and the evaluation data is determined based on the historical creation results of the multiple physical servers; Based on the evaluation data, a target physical server that meets the creation conditions is determined from the plurality of physical servers, and the cloud server is created using the target physical server; If the creation of the target physical server fails, the evaluation data of the target physical server will be updated to target evaluation data that does not meet the creation conditions.

2. The method according to claim 1, characterized in that, The step of determining a target physical server that meets the creation conditions from the plurality of physical servers based on the evaluation data, and using the target physical server to create a cloud server, includes: The evaluation data are sorted by priority from high to low, and the physical server with the highest evaluation data is determined as the target physical server. The cloud server is created using the target physical server.

3. The method according to claim 1, characterized in that, In the event that the creation of the target physical server fails, updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions includes: If the creation of the target physical server fails, a first adjustment value corresponding to the target physical server is determined based on the evaluation data of the other physical servers among the plurality of physical servers besides the target physical server. The difference between the evaluation data of the target physical server and the first value to be adjusted is determined as the target evaluation data.

4. The method according to claim 1, characterized in that, The method further includes: If the target physical server is successfully created, a second value to be adjusted is determined based on the evaluation data of the other physical servers among the plurality of physical servers besides the target physical server. The sum of the evaluation data of the target physical server and the second value to be adjusted is determined as the updated evaluation data.

5. The method according to claim 1, characterized in that, In the event that the creation of the target physical server fails, after updating the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions, the method further includes: If the target evaluation data is lower than the evaluation data threshold, the target physical server will be identified as an abnormal physical server. The exception handling module generates an exception alarm message for the abnormal physical server and removes the abnormal physical server from the candidate resource pool created by the cloud server.

6. The method according to claim 5, characterized in that, The step of generating an anomaly alarm information for the abnormal physical server through the anomaly handling module and removing the abnormal physical server from the candidate resource pool created by the cloud server includes: The abnormal physical server is generated through the abnormality handling module; Get the number of abnormal physical servers removed within the target time period; If the number of removals is less than or equal to the removal threshold, the abnormal physical server will be removed from the candidate resource pool created by the cloud server.

7. The method according to claim 6, characterized in that, After removing the abnormal physical server from the candidate resource pool created by the cloud server, the method further includes: Once the abnormal physical server has completed its anomaly repair, the anomaly evaluation data of the abnormal physical server is updated to the maximum evaluation data value, and the abnormal physical server is added to the candidate resource pool for cloud server creation.

8. A server determination device, characterized in that, include: The determination module is configured to, in response to a cloud server creation request, determine evaluation data for cloud server creation using multiple physical servers, wherein the evaluation data is determined based on the historical creation results of the multiple physical servers; The determination module is also configured to determine a target physical server that meets the creation conditions from the plurality of physical servers based on the evaluation data, and to use the target physical server to create a cloud server; The update module is configured to update the evaluation data of the target physical server to target evaluation data that does not meet the creation conditions if the creation of the target physical server fails.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

10. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

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