Method, device and storage medium for evaluating resource capacity of inter-cloud service

Abstract

The application relates to a method, device and equipment for evaluating resource capacity of inter-cloud services and a storage medium. The method comprises the following steps: obtaining current service carrying capacity and historical resource usage of a target inter-cloud service, wherein the target inter-cloud service is constructed according to service resources of at least one target cloud service providing end; performing resource simulation scheduling on the target inter-cloud service according to the current service carrying capacity and the historical resource usage to obtain estimated service carrying capacity of the target inter-cloud service; and determining a resource capacity evaluation result of the target inter-cloud service according to the current service carrying capacity and the estimated service carrying capacity. The method can improve the efficiency and accuracy of resource capacity evaluation of inter-cloud services.

Description

Technical Field

[0001] This application relates to the field of cloud service technology, and in particular to a method, apparatus, device and storage medium for assessing the resource capacity of cloud services. Background Technology

[0002] With the continuous development of cloud service technology, in order to improve the flexibility of cloud services, cloud computing services based on multiple cloud service providers have emerged. Therefore, in order to better evaluate the capacity of cloud computing services, resource capacity assessment methods for cloud services have emerged.

[0003] Existing resource capacity assessment methods generally assess the resource capacity of each individual cloud service provider within the cloud computing service, thereby determining the overall resource capacity assessment result of the cloud computing service.

[0004] However, due to the complexity and heterogeneity of the evaluation factors among different cloud service providers, adopting existing cloud service resource capacity evaluation methods will reduce the efficiency and accuracy of cloud service resource capacity evaluation. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, apparatus, device, and storage medium for assessing the resource capacity of cloud services, which can improve the efficiency and accuracy of assessing the resource capacity of cloud services.

[0006] Firstly, this application provides a method for assessing the resource capacity of cloud services, including:

[0007] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0008] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0009] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0010] In this embodiment, on the one hand, performing resource simulation scheduling on the target cloud service can ensure the rationality of resource allocation for the target cloud service, thereby improving the utilization rate of service resources in the target cloud service; on the other hand, from an overall perspective, performing resource capacity assessment on the target cloud service based on the current service capacity and historical resource usage can effectively improve the efficiency and accuracy of resource capacity assessment.

[0011] In one embodiment, resource simulation scheduling is performed on the target cloud service based on the current service capacity and historical resource usage to obtain the estimated service capacity of the target cloud service, including:

[0012] Based on the current service capacity, determine the current available resources of the target cloud service under each resource type; based on historical resource usage, determine the predicted resource usage of the target cloud service under each resource type; based on the predicted resource usage and current available resources under each resource type, perform resource simulation scheduling for the target cloud service to obtain the estimated service capacity of the target cloud service.

[0013] In this embodiment of the application, by performing resource simulation scheduling on the target cloud service based on the difference between the predicted resource usage and the current available resource quantity under each resource type, the estimated service capacity of the target cloud service can be obtained, which can ensure the accuracy of the estimated service capacity under each resource type.

[0014] In one embodiment, resource simulation scheduling is performed on the target cloud service based on the predicted resource usage and currently available resource quantity for each resource type to obtain the estimated service capacity of the target cloud service, including:

[0015] Based on the predicted resource usage and current available resources for each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service; based on the resource types to be exhausted, perform resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0016] In this embodiment of the application, by performing resource simulation scheduling on the services to be accessed by the target cloud service according to the type of resources to be exhausted, the rationality of the resource simulation scheduling can be guaranteed, thereby ensuring the accuracy of the estimated service capacity.

[0017] In one embodiment, the method further includes:

[0018] Based on the resource needs of the target users, select at least two target cloud service providers from various cloud service providers; and use the service resources of each target cloud service provider to construct the target cloud service.

[0019] In this embodiment of the application, by determining the target cloud service provider for constructing the target cloud service based on the resource requirements of the target user, the compatibility between the target cloud service and the resource requirements of the target user can be guaranteed.

[0020] In one embodiment, based on the resource needs of the target user, at least two target cloud service providers are selected from various cloud service providers, including:

[0021] Based on the configuration information and historical operation data of each cloud service provider, determine the service recommendation value corresponding to each cloud service provider; based on the resource needs of the target user and the service recommendation value corresponding to each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0022] In this embodiment of the application, by selecting the target cloud service provider based on the service recommendation value corresponding to each cloud service provider, the reliability of the cloud services provided by the target cloud service provider can be guaranteed, thereby ensuring the reliability of the target cloud service.

[0023] In one embodiment, based on the configuration information and historical operating data of each cloud service provider, a service recommendation value is determined for each cloud service provider, including:

[0024] For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider; based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the recommended service value corresponding to the cloud service provider.

[0025] In this embodiment, by optimizing the basic service value based on the historical operation data and resource reporting data of the cloud service provider, a service recommendation value is obtained, which can ensure that the service recommendation value matches the actual operation of the cloud service provider, thereby improving the accuracy of the service recommendation value.

[0026] In one embodiment, target cloud services are constructed using the service resources of each target cloud service provider, including:

[0027] Based on each target cloud service provider, at least two different candidate service groups are generated; each candidate service group includes at least one target cloud service provider; resource simulation scheduling is performed on each candidate service group to obtain the service score corresponding to each candidate service group; based on the service score corresponding to each candidate service group, the target service group is determined from each candidate service group; based on the service resources of the target cloud service providers in the target service group, the target cloud service is constructed.

[0028] In this embodiment of the application, by determining the target service group for constructing the target cloud service from among the candidate service groups according to the service scores corresponding to each candidate service group, the reliability of the construction of the target cloud service can be guaranteed.

[0029] Secondly, this application also provides a resource capacity assessment device for cloud services, comprising:

[0030] The data acquisition module is used to acquire the current service capacity and historical resource usage of the target cloud service; wherein the target cloud service is constructed based on the service resources of at least one target cloud service provider.

[0031] The simulation scheduling module is used to simulate resource scheduling for the target cloud service based on the current service capacity and historical resource usage, so as to obtain the estimated service capacity of the target cloud service.

[0032] The capacity assessment module is used to determine the resource capacity assessment result of the target cloud service based on the current service capacity and the estimated service capacity.

[0033] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0034] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0035] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0036] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0037] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0038] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0039] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0040] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0041] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0042] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0043] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0044] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0045] The aforementioned method, apparatus, equipment, and storage medium for assessing the resource capacity of cloud services obtain the current service capacity and historical resource usage of the target cloud service by acquiring the service resources of at least one target cloud service provider. Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain its estimated service capacity. Then, based on the current service capacity and estimated service capacity, the resource capacity assessment result of the target cloud service is determined. Compared to related technologies that assess the resource capacity of each cloud service provider individually, this method, on the one hand, ensures the rationality of resource allocation for the target cloud service through resource simulation scheduling, thereby improving the utilization rate of service resources within the target cloud service; on the other hand, from an overall perspective, assessing the resource capacity of the target cloud service based on its current service capacity and historical resource usage effectively improves the efficiency and accuracy of resource capacity assessment. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart illustrating a resource capacity assessment method for cloud services in one embodiment;

[0048] Figure 2 This is a schematic diagram of the process for determining the estimated service capacity in one embodiment;

[0049] Figure 3 This is a schematic diagram of the process for determining the target cloud service provider in one embodiment;

[0050] Figure 4 This is a flowchart illustrating the process of determining a service recommendation value in one embodiment;

[0051] Figure 5 This is a schematic diagram illustrating the process of constructing a target cloud service in one embodiment.

[0052] Figure 6 This is a flowchart illustrating the resource capacity assessment method for cloud services in another embodiment;

[0053] Figure 7 This is a structural block diagram of a cloud service resource capacity assessment device in one embodiment.

[0054] Figure 8 A structural block diagram of a resource capacity assessment device for cloud services in another embodiment;

[0055] Figure 9 This is a structural block diagram of a resource capacity assessment device for cloud services in yet another embodiment;

[0056] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0058] With the continuous development of cloud service technology, in order to improve the flexibility of cloud services, cloud computing services based on multiple cloud service providers have emerged. Therefore, in order to better evaluate the capacity of cloud computing services, resource capacity assessment methods for cloud services have emerged.

[0059] Existing resource capacity assessment methods generally assess the resource capacity of each individual cloud service provider within the cloud computing service, thereby determining the overall resource capacity assessment result of the cloud computing service.

[0060] However, due to the complexity and heterogeneity of the evaluation factors among different cloud service providers, adopting existing cloud service resource capacity evaluation methods will reduce the efficiency and accuracy of cloud service resource capacity evaluation.

[0061] Based on this, in an exemplary embodiment, a method for assessing the resource capacity of cloud services is provided. The method is illustrated using the example of its application to the server hosting the target cloud service. Figure 1 As shown, the specific steps include:

[0062] S101, obtain the current service capacity and historical resource usage of the target cloud service.

[0063] The target cloud service is constructed based on the service resources of at least one target cloud service provider. The target cloud service provider is a cloud service participant that can provide service resources, which may include, but are not limited to, data resources, software service resources, network resources, computing resources, and storage resources.

[0064] Current service capacity refers to the service capacity carried by the target cloud service at the current moment; historical resource usage refers to the resource usage of the target cloud service during historical usage periods.

[0065] Optionally, in response to the cloud service administrator's resource capacity assessment event for the target cloud service, the current service capacity of the target cloud service and the historical resource usage of each resource type during the historical usage period can be directly obtained.

[0066] S102, Based on the current service capacity and historical resource usage, perform resource simulation scheduling on the target cloud service to obtain the estimated service capacity of the target cloud service.

[0067] The estimated service capacity refers to the amount of service that the target cloud service will be able to handle in the future.

[0068] Optionally, the current service capacity and historical resource usage of each resource type can be input into the simulation scheduling model for training. The simulation scheduling model will then output the simulated scheduling method for the target cloud service based on the current service capacity, historical resource usage, and model parameters.

[0069] Furthermore, after performing simulated scheduling of resources for the target cloud service using a simulated scheduling method, the current resource allocation and historical resource usage are input into the trained prediction model. The prediction model can then output the estimated service capacity of the target cloud service under each resource type based on the current resource allocation, historical resource usage, and model parameters.

[0070] S103, Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment result of the target cloud service.

[0071] Among them, the resource capacity assessment result refers to the result obtained by assessing the resource capacity of the target cloud service.

[0072] Optionally, the current service capacity and the estimated service capacity can be simultaneously input into the trained capacity assessment model, which will then directly output the resource capacity assessment result of the target cloud service based on the current service capacity, the estimated service capacity, and the model parameters.

[0073] Understandably, in order to ensure the accuracy of resource capacity assessment results, the results can be optimized based on the service quality of the target cloud service.

[0074] For example, overall performance data of the target cloud service can be collected, such as availability, throughput, success rate, reliability, latency, response time, and customer service response time; then, based on the overall performance data, the service quality of the target cloud service can be determined.

[0075] Alternatively, the service quality of each service resource provided by the target cloud service can be monitored separately. For example, for each service resource, the actual usage effect of the service resource can be monitored, such as the stability of bandwidth, IO, and errors. Based on the actual usage effect of the service resource, the service quality of the service resource can be determined. Then, by statistically analyzing the service quality of each service resource, the service quality of the target cloud service can be determined.

[0076] Furthermore, the output of the capacity assessment model can be used as the initial resource capacity assessment result; subsequently, the initial resource capacity assessment result can be optimized based on the service quality of the target cloud service to determine the final resource capacity assessment result of the target cloud service.

[0077] After determining the resource capacity assessment results of the target cloud service, the target cloud service can be expanded or reduced in advance based on the resource capacity assessment results to ensure the continuity and stability of the target cloud service in processing business.

[0078] In the aforementioned method for assessing the resource capacity of cloud services, the current service capacity and historical resource usage of the target cloud service are obtained by acquiring the service resources of at least one target cloud service provider. Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity. Then, based on the current service capacity and the estimated service capacity, the resource capacity assessment result of the target cloud service is determined. Compared to related technologies that assess the resource capacity of each cloud service provider one by one, this method, on the one hand, ensures the rationality of resource allocation for the target cloud service through resource simulation scheduling, thereby improving the utilization rate of service resources within the target cloud service; on the other hand, from an overall perspective, assessing the resource capacity of the target cloud service based on its current service capacity and historical resource usage effectively improves the efficiency and accuracy of resource capacity assessment.

[0079] In practical applications, to ensure the accuracy of estimated service capacity, based on the above embodiments, this embodiment provides an optional method for determining estimated service capacity, such as... Figure 2As shown, the specific steps include:

[0080] S201, Based on the current service capacity, determine the current available resources of the target cloud service under each resource type.

[0081] The currently available resources refer to the amount of resources available for the target cloud service at the current moment.

[0082] Optionally, the overall resource quantity of the target cloud service under each resource type can be determined based on the configuration information of the target cloud service. Subsequently, the current available resource quantity of the target cloud service under each resource type can be calculated based on the resource usage and overall resource quantity corresponding to the current service capacity of the target cloud service under each resource type.

[0083] S202, Based on historical resource usage, determine the predicted resource usage of the target cloud service under each resource type.

[0084] The predicted resource usage refers to the amount of resources required by the target cloud service to process subsequent tasks.

[0085] Optionally, the historical resource usage of the target cloud service under each resource type can be directly input into the trained usage prediction model. The usage prediction model will then output the predicted resource usage for each resource type based on the historical resource usage and model parameters.

[0086] Alternatively, the performance data of the target cloud service at the current moment can be used to optimize the historical resource usage of each resource type, thereby obtaining the predicted resource usage for each resource type.

[0087] S203. Based on the predicted resource usage and current available resource quantity under each resource type, perform resource simulation scheduling on the target cloud service to obtain the estimated service capacity of the target cloud service.

[0088] Optionally, the predicted resource usage under each resource type can be compared with the current available resource amount to determine the resource depletion probability used to represent the service resource usage under each resource type in the future period; then, based on the resource depletion probability corresponding to each resource type, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service.

[0089] For example, for each resource type in the target cloud service, determine whether the resource exhaustion probability corresponding to that resource type is greater than a preset probability threshold. If so, expand the resource capacity corresponding to that resource type based on the estimated service capacity. If not, shrink the resource capacity corresponding to that resource type based on the estimated service capacity, or do not process it.

[0090] Furthermore, after performing resource simulation scheduling on the target cloud service, the estimated service capacity of the target cloud service under each resource type can be re-determined based on the resource capacity adjustment corresponding to each resource type.

[0091] It is understandable that in practical applications, there are certain special service resources that are used for specific usage scenarios. Therefore, when there are special service resources in the target cloud service, it is necessary to simulate and schedule these special service resources in combination with the current usage scenario.

[0092] In this embodiment of the application, by performing resource simulation scheduling on the target cloud service based on the difference between the predicted resource usage and the current available resource quantity under each resource type, the estimated service capacity of the target cloud service can be obtained, which can ensure the accuracy of the estimated service capacity under each resource type.

[0093] To ensure the reliability of resource simulation scheduling, based on the above embodiments, this embodiment provides an optional method for resource simulation scheduling. Specifically, based on the predicted resource usage and current available resource quantity under each resource type, the resource types to be exhausted are determined from the resource types provided by the target cloud service; based on the resource types to be exhausted, resource simulation scheduling is performed on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0094] Optionally, after determining the predicted resource usage and current available resource quantity for each resource type, the resource type to be exhausted can be determined from each resource type based on the relationship between the predicted resource usage and current available resource quantity for each resource type.

[0095] It is understandable that computing tasks in the target cloud service are connected gradually. Therefore, when it is determined that a certain resource type is about to be exhausted, the service capacity of subsequent accesses of resources under that resource type can be adjusted according to the service capacity that the resource type to be exhausted can handle. Subsequently, the estimated service capacity of that resource type is recalculated according to the service capacity that each resource type to be exhausted can handle.

[0096] In this embodiment of the application, by performing resource simulation scheduling on the services to be accessed by the target cloud service according to the type of resources to be exhausted, the rationality of the resource simulation scheduling can be guaranteed, thereby ensuring the accuracy of the estimated service capacity.

[0097] In practical applications, in order to ensure that the target cloud service is compatible with the user's resource needs, based on the above embodiments, this embodiment provides an optional way to construct the target cloud service. Specifically, according to the resource needs of the target user, at least two target cloud service providers are selected from each cloud service provider; and the target cloud service is constructed using the service resources of each target cloud service provider.

[0098] Among them, target users refer to users who have a need to use cloud resources; resource demand refers to the target users' demand information for cloud resources.

[0099] Optionally, at least two target cloud service providers can be selected from among the cloud service providers based on the resource quantity of each resource type in the resource requirements of the target user, as well as the resource types and corresponding resource quantities provided by each cloud service provider.

[0100] Understandably, in order to reduce the data exchange cost and complexity of the target cloud service, the goal can be to minimize the number of cloud service providers and select the target cloud service provider that can cover the resource needs of the target users.

[0101] For example, a user's resource requirements include resource A (resource requirement A'), resource B (resource requirement B'), and resource C (resource requirement C'). Cloud service provider S1 provides resource A (resource requirement A') and resource C (resource requirement C'), cloud service provider S2 provides resource B (resource requirement B'), and cloud service provider S3 provides resource C (resource requirement C'). In this case, cloud service provider S1 and cloud service provider S2 can be selected as the target cloud service provider.

[0102] Furthermore, after identifying the target cloud service providers, a cloud computing platform can be used to integrate the service resources of each target cloud service provider in order to construct the target cloud service.

[0103] In this embodiment of the application, by determining the target cloud service provider for constructing the target cloud service based on the resource requirements of the target user, the compatibility between the target cloud service and the resource requirements of the target user can be guaranteed.

[0104] In practical applications, to ensure the reliability of the services provided by the target cloud service provider, based on the above embodiments, this embodiment provides an optional method for determining the target cloud service provider, such as... Figure 3 As shown, the specific steps include:

[0105] S301, based on the configuration information and historical operation data of each cloud service provider, determines the recommended service value for each cloud service provider.

[0106] The configuration information is used to characterize the basic configuration of the cloud service provider. For example, the configuration information may include, but is not limited to, the network information corresponding to the cloud service provider, such as the region where the cloud service network is located, the number of operators, the network latency of each operator, and the network bandwidth.

[0107] Historical operational data refers to data related to the provision of service resources by the cloud service provider within a historical period. For example, historical operational data may include, but is not limited to, the success rate, stability, anomaly rate, average response time, and average recovery time of service resource usage. Service recommendation value refers to a numerical value that can characterize the service provided by the cloud service provider.

[0108] Optionally, for each cloud service provider, the configuration information and historical operating data corresponding to that cloud service provider can be simultaneously input into the trained evaluation model. The evaluation model will then output a service recommendation value for that cloud service provider based on the configuration information, historical operating data, and model parameters.

[0109] S302, based on the resource needs of the target user and the service recommendation values ​​of each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0110] Optionally, cloud service providers can be sorted in descending order based on their service recommendation values. This sorting order allows for the selection of at least two target cloud service providers based on the target user's resource needs. Alternatively, all cloud service providers with values ​​greater than the service recommendation threshold can be selected as target cloud service providers.

[0111] In this embodiment of the application, by selecting the target cloud service provider based on the service recommendation value corresponding to each cloud service provider, the reliability of the cloud services provided by the target cloud service provider can be guaranteed, thereby ensuring the reliability of the target cloud service.

[0112] In practical applications, to ensure the accuracy of service recommendation values, based on the above embodiments, this embodiment provides an optional method for determining service recommendation values, such as... Figure 4As shown, the specific steps include:

[0113] S401: For each cloud service provider, determine the corresponding basic service value based on the cloud service provider's configuration information.

[0114] Among them, the basic service value is used to characterize the initial service recommendation value of the cloud service provider.

[0115] Optionally, for each cloud service provider, the configuration information of the cloud service provider can be input into the trained basic value determination model, and the basic value determination model can output the basic service value corresponding to the cloud service provider based on the configuration information and model parameters.

[0116] Alternatively, the standard service value of each operator can be uniformly determined based on the service quality of the cloud services provided by each operator; correspondingly, for each cloud service provider, operator information can be extracted from the configuration information of the cloud service provider, and then the standard service value of the cloud service provider can be determined based on the standard service value associated with each operator.

[0117] Furthermore, the hardware performance of the hardware associated with the cloud service provider can be extracted from the configuration information of the cloud service provider, and the standard service value of the cloud service provider can be optimized based on the hardware performance to obtain the basic service value corresponding to the cloud service provider.

[0118] S402, based on the historical operation data and resource reporting data of the cloud service provider, optimize the basic service value corresponding to the cloud service provider to obtain the service recommendation value corresponding to the cloud service provider.

[0119] Among them, resource reporting data refers to the standard resource usage information of the cloud service provider that is proactively reported by the cloud service provider's administrator.

[0120] Optionally, for each cloud service provider, the administrator of that cloud service provider can proactively upload the standard resource usage information of the additional service resources provided by the cloud service provider as resource reporting data to the cloud computing platform. Subsequently, the cloud computing platform can extract the historical operating data of the cloud service provider and optimize the basic service value corresponding to the cloud service provider based on the difference between the historical operating data and the resource reporting data to obtain the service recommendation value corresponding to the cloud service provider.

[0121] For example, evaluation indicators under different dimensions that can evaluate the service quality of cloud service provider T are determined in advance, and the initial weight value of each evaluation indicator is determined according to the importance of each evaluation indicator, wherein the sum of the initial weight values ​​is 1.

[0122] Furthermore, the resource reporting data and historical operation data of cloud service provider T under each evaluation indicator can be obtained. Then, based on the differences between the resource reporting data and the historical operation data, the initial weight values ​​of each evaluation indicator can be corrected to obtain the actual weight values ​​of each evaluation indicator. Subsequently, the actual weight values ​​of each evaluation indicator can be used to weight the basic service value of cloud service provider T to calculate the service recommendation value corresponding to cloud service provider T.

[0123] In this embodiment, by optimizing the basic service value based on the historical operation data and resource reporting data of the cloud service provider, a service recommendation value is obtained, which can ensure that the service recommendation value matches the actual operation of the cloud service provider, thereby improving the accuracy of the service recommendation value.

[0124] In practical applications, to ensure the reliability of the target cloud service construction, based on the above embodiments, this embodiment provides an optional method for constructing the target cloud service, such as... Figure 5 As shown, the specific steps include:

[0125] S501 generates at least two different candidate service groups based on each target cloud service provider.

[0126] Among them, a candidate service group refers to a combination of cloud service providers that can cover resource requirements; each candidate service group includes at least one target cloud service provider.

[0127] Optionally, after identifying each target cloud service provider, the target cloud service providers can be combined into at least two candidate service groups, and the service resources provided by each candidate service group can fully cover the resource needs of the target users.

[0128] S502, respectively, performs resource simulation scheduling for each candidate service group to obtain the service score corresponding to each candidate service group.

[0129] Among them, the service score refers to the score of the services provided by the cloud services provided by each target cloud service provider in the candidate service group.

[0130] Optionally, for each candidate service group, a basic quality score can be determined based on the service recommendation value corresponding to each target cloud service provider in the candidate service group; at the same time, a cloud computing platform can be used to perform resource simulation scheduling for the candidate service group to obtain resource interaction data between each target cloud service provider in the candidate service group (e.g., the number of entities interacting with resources, the number of cross-entity interactions, data transmission costs, etc.).

[0131] Subsequently, the resource interaction data can be input into the trained interaction coefficient determination model, which will then output the interaction coefficient corresponding to the candidate service group based on the resource interaction data and model parameters.

[0132] Finally, the interaction coefficient can be used to adjust the baseline quality score corresponding to the candidate service group, thereby obtaining the service score for that candidate service group. For example, the product of the interaction coefficient and the baseline quality score can be directly used as the service score for the candidate service group.

[0133] S503, based on the service scores corresponding to each candidate service group, determine the target service group from among the candidate service groups.

[0134] The target service group refers to the collection of target cloud service providers used to build target cloud services.

[0135] Optionally, the target service group can be determined from among the candidate service groups based on the relationship between their service ratings. For example, the candidate service group with the highest service rating can be selected as the target service group.

[0136] S504, construct the target cloud service based on the service resources of the target cloud service provider in the target service group.

[0137] Optionally, a cloud computing platform can be used to integrate the service resources of each target cloud service provider in the target service group to construct the target cloud service.

[0138] Understandably, to ensure the reliability of the target cloud service, after the target cloud service is built, the various target cloud service providers within it can be monitored based on a variety of metrics. These metrics include, but are not limited to, the availability, throughput, success rate, reliability, latency, response time, and customer service response time of the target cloud service. Subsequently, the service score of the target cloud service can be revised based on the actual operating conditions of each target cloud service provider under these various metrics, resulting in the current service score of the target cloud service.

[0139] Furthermore, if the current service score of the target cloud service is less than the score threshold, the abnormal cloud service provider can be identified from among the target cloud service providers based on the actual operation of each target cloud service provider under each metric. Subsequently, based on the actual operation of the abnormal cloud service provider, it can be determined whether the abnormal cloud service provider can continue to provide service resources. If not, the abnormal cloud service provider needs to be isolated or downgraded.

[0140] If the current service score of the target cloud service is greater than or equal to the score threshold, continue to use the target cloud service to provide cloud resources to the target user.

[0141] In this embodiment of the application, by determining the target service group for constructing the target cloud service from among the candidate service groups according to the service scores corresponding to each candidate service group, the reliability of the construction of the target cloud service can be guaranteed.

[0142] Figure 6 This is a flowchart illustrating a resource capacity assessment method for cloud services in another embodiment. Based on the above embodiments, this embodiment provides an optional example of a resource capacity assessment method for cloud services. (Combined with...) Figure 6 The specific implementation process is as follows:

[0143] S601 determines the basic service value corresponding to each cloud service provider based on the configuration information of each cloud service provider.

[0144] S602, based on the historical operation data and resource reporting data of each cloud service provider, optimize the basic service value corresponding to each cloud service provider to obtain the service recommendation value corresponding to each cloud service provider.

[0145] S603: Based on the resource needs of the target user and the service recommendation values ​​of each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0146] S604 generates at least two different candidate service groups based on each target cloud service provider.

[0147] Each candidate service group includes at least one target cloud service provider.

[0148] S605 performs resource simulation scheduling for each candidate service group to obtain the service score corresponding to each candidate service group.

[0149] S606, Based on the service scores corresponding to each candidate service group, determine the target service group from among the candidate service groups.

[0150] S607, construct the target cloud service based on the service resources of the target cloud service provider in the target service group.

[0151] S608 retrieves the current service capacity and historical resource usage of the target cloud service.

[0152] The target cloud service is constructed based on the service resources of at least one target cloud service provider.

[0153] S609, based on the current service capacity, determine the current available resources of the target cloud service under each resource type.

[0154] S610 determines the predicted resource usage of the target cloud service under each resource type based on historical resource usage data.

[0155] S611, based on the predicted resource usage and current available resource quantity under each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service.

[0156] S612, based on the type of resources to be exhausted, performs resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0157] S613, determine the resource capacity assessment result of the target cloud service based on the current service capacity and the estimated service capacity.

[0158] The specific processes of S601-S613 described above can be found in the description of the above method embodiments. Their implementation principles and technical effects are similar, and will not be repeated here.

[0159] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0160] Based on the same inventive concept, this application also provides a cloud service resource capacity assessment device for implementing the cloud service resource capacity assessment method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more cloud service resource capacity assessment device embodiments provided below can be found in the limitations of the cloud service resource capacity assessment method described above, and will not be repeated here.

[0161] In one exemplary embodiment, such as Figure 7 As shown, a resource capacity assessment device 1 for cloud services is provided, comprising: a data acquisition module 10, a simulation scheduling module 20, and a capacity assessment module 30, wherein:

[0162] Data acquisition module 10 is used to acquire the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0163] The simulation scheduling module 20 is used to perform resource simulation scheduling on the target cloud service based on the current service capacity and historical resource usage to obtain the estimated service capacity of the target cloud service.

[0164] The capacity assessment module 30 is used to determine the resource capacity assessment result of the target cloud service based on the current service capacity and the estimated service capacity.

[0165] In one exemplary embodiment, such as Figure 8 As shown, the simulation scheduling module 20 includes:

[0166] Resource quantity determination unit 21 is used to determine the current available resource quantity of the target cloud service under each resource type based on the current service capacity;

[0167] Usage determination unit 22 is used to determine the predicted resource usage of the target cloud service under each resource type based on historical resource usage.

[0168] The capacity determination unit 23 is used to perform resource simulation scheduling on the target cloud service based on the predicted resource usage and current available resource quantity under each resource type, so as to obtain the estimated service capacity of the target cloud service.

[0169] In an exemplary embodiment, the load capacity determination unit 23 is specifically used for:

[0170] Based on the predicted resource usage and current available resources for each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service; based on the resource types to be exhausted, perform resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0171] In an exemplary embodiment, the cloud service resource capacity assessment device 1 further includes a service construction module 40, wherein, as Figure 9 As shown, the service building module 40 includes:

[0172] Selection unit 41 is used to select at least two target cloud service providers from among the cloud service providers according to the resource needs of the target user;

[0173] Construction unit 42 is used to construct target cloud services by using the service resources of each target cloud service provider.

[0174] In one exemplary embodiment, the selection unit 41 includes:

[0175] The first subunit is used to determine the recommended service value for each cloud service provider based on the configuration information and historical operation data of each cloud service provider.

[0176] The second subunit is used to select at least two target cloud service providers from among the cloud service providers based on the resource needs of the target user and the service recommendation values ​​of each cloud service provider.

[0177] In an exemplary embodiment, the first subunit is specifically used for:

[0178] For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider; based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the recommended service value corresponding to the cloud service provider.

[0179] In an exemplary embodiment, the building unit 42 is specifically used for:

[0180] Based on each target cloud service provider, at least two different candidate service groups are generated; each candidate service group includes at least one target cloud service provider; resource simulation scheduling is performed on each candidate service group to obtain the service score corresponding to each candidate service group; based on the service score corresponding to each candidate service group, the target service group is determined from each candidate service group; based on the service resources of the target cloud service providers in the target service group, the target cloud service is constructed.

[0181] Each module in the aforementioned cloud service resource capacity assessment device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can invoke and execute the operations corresponding to each module.

[0182] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores historical operating data from various cloud service providers. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a resource capacity assessment method for cloud services.

[0183] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0184] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0185] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0186] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0187] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0188] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0189] Based on the current service capacity, determine the current available resources of the target cloud service under each resource type; based on historical resource usage, determine the predicted resource usage of the target cloud service under each resource type; based on the predicted resource usage and current available resources under each resource type, perform resource simulation scheduling for the target cloud service to obtain the estimated service capacity of the target cloud service.

[0190] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0191] Based on the predicted resource usage and current available resources for each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service; based on the resource types to be exhausted, perform resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0192] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0193] Based on the resource needs of the target users, select at least two target cloud service providers from various cloud service providers; and use the service resources of each target cloud service provider to construct the target cloud service.

[0194] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0195] Based on the configuration information and historical operation data of each cloud service provider, determine the service recommendation value corresponding to each cloud service provider; based on the resource needs of the target user and the service recommendation value corresponding to each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0196] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0197] For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider; based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the recommended service value corresponding to the cloud service provider.

[0198] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0199] Based on each target cloud service provider, at least two different candidate service groups are generated; each candidate service group includes at least one target cloud service provider; resource simulation scheduling is performed on each candidate service group to obtain the service score corresponding to each candidate service group; based on the service score corresponding to each candidate service group, the target service group is determined from each candidate service group; based on the service resources of the target cloud service providers in the target service group, the target cloud service is constructed.

[0200] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0201] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0202] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0203] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0204] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0205] Based on the current service capacity, determine the current available resources of the target cloud service under each resource type; based on historical resource usage, determine the predicted resource usage of the target cloud service under each resource type; based on the predicted resource usage and current available resources under each resource type, perform resource simulation scheduling for the target cloud service to obtain the estimated service capacity of the target cloud service.

[0206] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0207] Based on the predicted resource usage and current available resources for each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service; based on the resource types to be exhausted, perform resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0208] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0209] Based on the resource needs of the target users, select at least two target cloud service providers from various cloud service providers; and use the service resources of each target cloud service provider to construct the target cloud service.

[0210] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0211] Based on the configuration information and historical operation data of each cloud service provider, determine the service recommendation value corresponding to each cloud service provider; based on the resource needs of the target user and the service recommendation value corresponding to each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0212] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0213] For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider; based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the recommended service value corresponding to the cloud service provider.

[0214] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0215] Based on each target cloud service provider, at least two different candidate service groups are generated; each candidate service group includes at least one target cloud service provider; resource simulation scheduling is performed on each candidate service group to obtain the service score corresponding to each candidate service group; based on the service score corresponding to each candidate service group, the target service group is determined from each candidate service group; based on the service resources of the target cloud service providers in the target service group, the target cloud service is constructed.

[0216] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0217] Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider;

[0218] Based on the current service capacity and historical resource usage, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service;

[0219] Based on the current service capacity and the estimated service capacity, determine the resource capacity assessment results for the target cloud service.

[0220] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0221] Based on the current service capacity, determine the current available resources of the target cloud service under each resource type; based on historical resource usage, determine the predicted resource usage of the target cloud service under each resource type; based on the predicted resource usage and current available resources under each resource type, perform resource simulation scheduling for the target cloud service to obtain the estimated service capacity of the target cloud service.

[0222] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0223] Based on the predicted resource usage and current available resources for each resource type, determine the resource types to be exhausted from the resource types provided by the target cloud service; based on the resource types to be exhausted, perform resource simulation scheduling on the services to be accessed by the target cloud service to obtain the estimated service capacity of the target cloud service.

[0224] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0225] Based on the resource needs of the target users, select at least two target cloud service providers from various cloud service providers; and use the service resources of each target cloud service provider to construct the target cloud service.

[0226] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0227] Based on the configuration information and historical operation data of each cloud service provider, determine the service recommendation value corresponding to each cloud service provider; based on the resource needs of the target user and the service recommendation value corresponding to each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

[0228] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0229] For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider; based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the recommended service value corresponding to the cloud service provider.

[0230] In one embodiment, when the computer program is executed by a processor, it further performs the following steps:

[0231] Based on each target cloud service provider, at least two different candidate service groups are generated; each candidate service group includes at least one target cloud service provider; resource simulation scheduling is performed on each candidate service group to obtain the service score corresponding to each candidate service group; based on the service score corresponding to each candidate service group, the target service group is determined from each candidate service group; based on the service resources of the target cloud service providers in the target service group, the target cloud service is constructed.

[0232] It should be noted that the data involved in this application (including but not limited to historical operational data of various cloud service providers) are all data authorized by users or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0233] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0234] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0235] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for assessing the resource capacity of cloud services, characterized in that, The method includes: Obtain the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider; Based on the current service capacity, determine the current available resources of the target cloud service under each resource type; Based on the historical resource usage, the predicted resource usage of the target cloud service under each resource type is determined; Based on the predicted resource usage and current available resource quantity under each resource type, resource simulation scheduling is performed on the target cloud service to obtain the estimated service capacity of the target cloud service. The resource capacity assessment result of the target cloud service is determined based on the current service capacity and the estimated service capacity of the target cloud service. The step of performing resource simulation scheduling on the target cloud service based on the predicted resource usage and current available resource quantity under each resource type to obtain the estimated service capacity of the target cloud service includes: Based on the relationship between the predicted resource usage and the current available resource amount for each resource type, the resource types to be exhausted are determined from the resource types provided by the target cloud service. Adjust the service volume of subsequent accesses of resources under the resource type to be exhausted based on the service volume that the resources under the resource type to be exhausted can handle. Calculate the estimated service capacity of the resource type to be exhausted based on the amount of services that can be subsequently accessed under the resource type to be exhausted.

2. The method according to claim 1, characterized in that, The method further includes: Based on the resource needs of the target users, select at least two target cloud service providers from various cloud service providers; Utilize the service resources of each target cloud service provider to construct target cloud-to-cloud services.

3. The method according to claim 2, characterized in that, The step of selecting at least two target cloud service providers from various cloud service providers based on the resource needs of the target users includes: Based on the configuration information and historical operation data of each cloud service provider, the recommended service value for each cloud service provider is determined. Based on the resource needs of the target users and the service recommendation values ​​of each cloud service provider, select at least two target cloud service providers from among the cloud service providers.

4. The method according to claim 3, characterized in that, The step of determining the recommended service value for each cloud service provider based on its configuration information and historical operational data includes: For each cloud service provider, the basic service value corresponding to the cloud service provider is determined based on the configuration information of the cloud service provider. Based on the historical operation data and resource reporting data of the cloud service provider, the basic service value corresponding to the cloud service provider is optimized to obtain the service recommendation value corresponding to the cloud service provider.

5. The method according to claim 4, characterized in that, The configuration information of the cloud service provider includes at least one of the following: the geographical location of the cloud service network, the number of operators, the network latency of each operator, and the network bandwidth.

6. The method according to claim 2, characterized in that, The construction of target cloud services using the service resources of each target cloud service provider includes: Based on each target cloud service provider, at least two different candidate service groups are generated; wherein each candidate service group includes at least one target cloud service provider; Resource simulation scheduling was performed on each candidate service group to obtain the service score for each candidate service group. Based on the service scores of each candidate service group, the target service group is determined from each candidate service group; Based on the service resources of the target cloud service provider in the target service group, construct the target cloud service.

7. A resource capacity assessment device for cloud services, characterized in that, The device includes: The data acquisition module is used to acquire the current service capacity and historical resource usage of the target cloud service; wherein, the target cloud service is constructed based on the service resources of at least one target cloud service provider; The simulation scheduling module is used to determine the current available resource quantity of the target cloud service under each resource type based on the current service capacity; determine the predicted resource usage of the target cloud service under each resource type based on the historical resource usage; and perform resource simulation scheduling on the target cloud service based on the predicted resource usage and the current available resource quantity under each resource type to obtain the estimated service capacity of the target cloud service. The capacity assessment module is used to determine the resource capacity assessment result of the target cloud service based on the current service capacity and the estimated service capacity of the target cloud service. The simulation scheduling module is further configured to: determine the resource types to be exhausted from the resource types provided by the target cloud service based on the relationship between the predicted resource usage and the current available resource quantity for each resource type; adjust the subsequent service quantity of the resources under the resource types to be exhausted based on the service quantity that the resources under the resource types to be exhausted can handle; and calculate the estimated service capacity of the resource types to be exhausted based on the subsequent service quantity that the resources under the resource types to be exhausted can handle.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

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 steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images