Method and device for providing cloud service

Abstract

The invention provides a method and device for providing cloud services, the method is applied to a cloud management platform, the cloud management platform is used for providing various saving plans for cloud service products, the method comprises the steps that input information of tenants is acquired, and the input information indicates historical consumption data of the cloud service products and purchase modes of the saving plans; under the condition that the purchase mode of the saving plans is combined purchase, a saving plan combination is determined from the multiple saving plans according to the historical consumption data, and the deduction range of each saving plan in the saving plan combination comprises a first cloud service product; determining a target suggested commitment amount of each saving plan of the saving plan combination by adjusting the amount of the first cloud service product taken into account in a plurality of saving plans of the saving plan combination; and feeding back the target suggested commitment amount of each saving plan of the saving plan combination to the tenant. The method can reduce the total cost of the combined purchase suggestions of the plurality of saving plans.

Description

[0001] This application claims priority to a Chinese patent application filed with the Chinese Patent Office on July 11, 2023, with application number 202310847480.4 and application name “A method, device and computing device cluster for recommending a computing resource saving plan”, the entire contents of which are incorporated by reference in this application. Technical Field

[0002] The present application relates to the field of cloud computing, and more specifically, to a method and apparatus for providing cloud services. Background Art

[0003] The Savings Plan is a discount benefit plan that is billed based on a guaranteed consumption per unit time period (such as per hour). Users can exchange a lower pay-as-you-go discount by committing to use a stable amount of resources (such as cloud servers) within a certain period (such as 1 year or 3 years). The billing of the resources that the user commits to use is the committed consumption amount value, which can be measured in units of, for example, RMB / hour. After purchasing the Savings Plan, the portion of the customer's bill within the unit time period that does not exceed the committed consumption amount value will be billed with a discount unique to the Savings Plan, while the portion that exceeds the committed consumption amount value will not enjoy a discount and will be billed at the regular on-demand rate. In addition, the bill amount that does not reach the committed consumption amount value needs to be paid according to the committed consumption amount value.

[0004] At this stage, in order to maximize user rights and interests and encourage users to expand consumption, it is necessary to provide reasonable savings plan purchase suggestions, that is, to generate savings plan purchase suggestions for users that can save as much money as possible. Summary of the invention

[0005] The present application provides a method and apparatus for providing cloud services, which improves the cost savings of combined purchase recommendations of multiple savings plans by adjusting the usage of the same cloud service product that is considered in multiple savings plans.

[0006] In a first aspect, a method for providing cloud services is provided, the method being applied to a cloud management platform, the cloud management platform being used to provide multiple saving plans for cloud service products, wherein the deduction scope of each saving plan includes multiple cloud service products, the method comprising: obtaining input information of a tenant, the input information indicating historical consumption data of cloud service products and a purchase method of saving plans, the historical consumption data of the cloud service products including the usage of the multiple cloud service products of the tenant; in a case where the purchase method of the saving plans is a combination purchase, determining a saving plan combination from the multiple saving plans based on the historical consumption data, the saving plan combination including multiple saving plans, wherein the deduction scope of each saving plan in the saving plan combination includes a first cloud service product among the multiple cloud service products of the tenant; determining a target recommended commitment amount for each saving plan in the saving plan combination by adjusting the usage of the first cloud service product considered in the multiple saving plans in the saving plan combination respectively; and feeding back the target recommended commitment amount for each saving plan in the saving plan combination to the tenant.

[0007] It should be understood that a saving plan is a discount benefit plan that is charged based on a guaranteed consumption per unit time period (such as per hour). Tenants can exchange a lower pay-as-you-go discount for resources by committing to use a stable amount of resources (such as cloud service products) within a certain period (such as 1 year or 3 years). For example, saving plans can include computing, ECS (elastic compute service) and storage types, and each saving plan can provide tenants with pay-as-you-go discounts for cloud service products.

[0008] The scenario in which the method shown in the first aspect is applied is a situation in which the cloud management platform provides tenants with a purchase recommendation for a combination of savings plans, or provides tenants with a purchase recommendation for a combination of multiple savings plans. Among them, the deductible product ranges of multiple savings plans in the savings plan combination overlap, that is, the deductible product ranges of multiple savings plans include the same one or more cloud service products.

[0009] It should be understood that in the current combined purchase recommendations for multiple savings plans, the above-mentioned first cloud service product is considered separately and multiple times in multiple savings plans, so that tenants need to bear the cost of multiple times the usage when using a certain amount of the first cloud service product, which in turn leads to a high total cost of the purchase recommendations for the savings plan combination generated by the cloud management platform. In the method shown in the first aspect, the cloud management platform determines a purchase recommendation plan for a savings plan combination with a lower total cost and higher cost savings by adjusting the usage of cloud service products in overlapping ranges that are considered separately in multiple savings plans of the savings plan combination. Furthermore, the cost of using cloud service products for tenants can be further reduced, and the rights and interests of tenants can be maximized to encourage tenants to expand their cloud consumption.

[0010] Exemplarily, the cloud management platform can adjust the usage of the first cloud service product considered in multiple savings plans in the savings plan combination, determine the optimal recommended commitment amount of each savings plan in the savings plan combination and the payment cost of the savings plan combination based on the adjusted usage, and continuously adjust the usage of the first cloud service product considered, and then determine the optimal recommended commitment amount of each savings plan in the savings plan combination and the payment cost of the savings plan combination based on the adjusted usage. Until it is determined that the payment cost of the savings plan combination is the minimum of the payment costs of all savings plan combinations obtained during the adjustment process, the cloud management platform determines the optimal committed consumption amount of each savings plan under the savings plan combination as the target recommended commitment amount of each savings plan.

[0011] Optionally, the input information may also indicate the type of savings plan, the duration of the savings plan, the method of purchasing the savings plan, etc., for the cloud management platform to calculate the target recommended commitment amount.

[0012] Optionally, when a tenant selects the combined purchase method for a savings plan, they can also specify the type of savings plan to be purchased. For example, if a tenant also selects to purchase a storage-type savings plan and a computing-type savings plan, when the cloud management platform determines a savings plan combination from multiple savings plans, it only considers the combined purchase suggestions for the storage-type savings plan and the computing-type savings plan, and does not consider the ECS-type savings plan that has the same cloud service product in the deduction scope.

[0013] In combination with the first aspect, in certain implementations of the first aspect, the target recommended commitment amount for each saving plan in the saving plan combination is determined by adjusting the usage of the first cloud service product considered respectively in multiple saving plans in the saving plan combination, including: determining the usage of the second cloud service product in each saving plan in the saving plan combination based on the historical consumption data, wherein the second cloud service product is a cloud service product other than the first cloud service product in the saving plan; calculating the recommended commitment amount for each saving plan in the saving plan combination based on the usage of the second cloud service product in each saving plan in the saving plan combination and the distribution of the first cloud service product in the saving plan combination, wherein the distribution indicates the usage of the first cloud service product considered respectively in multiple saving plans in the saving plan combination; adjusting the distribution of the first cloud service product in the saving plan combination to determine the target recommended commitment amount for each saving plan in the saving plan combination.

[0014] In combination with the first aspect, in certain implementations of the first aspect, the recommended commitment amount for each saving plan in the saving plan combination is calculated based on the usage of the second cloud service product in each saving plan in the saving plan combination and the allocation of the first cloud service product in the saving plan combination, including: determining the discount coefficient of each cloud service product in each saving plan in the saving plan combination; calculating the recommended commitment amount for each saving plan in the saving plan combination based on the usage of the second cloud service product in each saving plan in the saving plan combination, the allocation of the first cloud service product in the saving plan combination, and the discount coefficient of each cloud service product.

[0015] In combination with the first aspect, in certain implementations of the first aspect, a sum of the usage of the first cloud service product considered in multiple saving plans of the saving plan combination is equal to the usage of the first cloud service product.

[0016] In other words, the usage of the first cloud service product in the historical consumption data is allocated to the multiple savings plans of the savings plan combination.

[0017] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: providing feedback to the tenant on the cost savings of the savings plan combination, the cost savings of the savings plan combination being the difference between the cost of purchasing the savings plan combination and the on-demand pay-per-use costs of the tenant's multiple cloud service products.

[0018] Optionally, the cloud management platform can also provide feedback on information such as estimated monthly cost savings, estimated monthly expenditures before purchase, and estimated monthly amortization costs after purchase.

[0019] Optionally, in the case where there are multiple savings plan combinations, the cloud management platform may simultaneously provide feedback on purchase recommendations, target recommended commitment amounts, etc. for the multiple savings plan combinations through step 540 .

[0020] In a second aspect, a device for providing cloud services is provided, the device is used to provide multiple saving plans for cloud service products, wherein the deduction scope of each saving plan includes multiple cloud service products, and the device includes: an acquisition module, used to: obtain tenant input information, the input information indicates historical consumption data of cloud service products and a purchase method of saving plans, the historical consumption data of cloud service products including the usage of multiple cloud service products of the tenant; a processing module, used to: when the purchase method of saving plans is combination purchase, determine a saving plan combination from the multiple saving plans according to the historical consumption data, the saving plan combination including multiple saving plans, wherein the deduction scope of each saving plan in the saving plan combination includes a first cloud service product among the multiple cloud service products of the tenant; determine a target recommended commitment amount for each saving plan in the saving plan combination by adjusting the usage of the first cloud service product considered in the multiple saving plans of the saving plan combination; a feedback module, used to: feedback the target recommended commitment amount for each saving plan in the saving plan combination to the tenant.

[0021] In combination with the second aspect, in certain implementations of the second aspect, the processing module is specifically used to: determine the usage of the second cloud service product in each saving plan of the saving plan combination based on the historical consumption data, wherein the second cloud service product is a cloud service product other than the first cloud service product in the saving plan; calculate the recommended commitment amount for each saving plan of the saving plan combination based on the usage of the second cloud service product in each saving plan of the saving plan combination and the distribution of the first cloud service product in the saving plan combination, wherein the distribution indicates the usage of the first cloud service product considered respectively in multiple saving plans of the saving plan combination; adjust the distribution of the first cloud service product in the saving plan combination to determine the target recommended commitment amount for each saving plan of the saving plan combination.

[0022] In combination with the second aspect, in certain implementations of the second aspect, the processing module is specifically used to: determine the discount coefficient for each cloud service product in each saving plan of the saving plan combination; calculate the recommended commitment amount for each saving plan of the saving plan combination based on the usage of the second cloud service product in each saving plan of the saving plan combination, the distribution of the first cloud service product in the saving plan combination, and the discount coefficient of each cloud service product.

[0023] In combination with the second aspect, in certain implementations of the second aspect, the sum of the usage of the first cloud service product considered in multiple saving plans of the saving plan combination is equal to the usage of the first cloud service product.

[0024] In combination with the second aspect, in certain implementations of the second aspect, the feedback module is also used to: provide feedback to the tenant on the cost savings of the savings plan combination, where the cost savings of the savings plan combination is the difference between the cost of purchasing the savings plan combination and the on-demand pay-per-use cost of the tenant's multiple cloud service products.

[0025] The specific scheme description and beneficial effects of the device shown in the second aspect can be referred to the first aspect and will not be repeated here.

[0026] In a third aspect, a computing device is provided, comprising a processor and a memory, wherein the memory is used to store instructions, and the processor is used to execute the instructions stored in the memory, so that the computing device executes the method in the first aspect or any possible implementation of the first aspect.

[0027] In a fourth aspect, a computing device cluster is provided, comprising at least two computing devices, each computing device comprising a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call and execute the instructions from the memory, so that the computing device cluster executes the method in the first aspect or any possible implementation of the first aspect.

[0028] Optionally, the processor may be a general-purpose processor, which may be implemented by hardware or software. When implemented by hardware, the processor may be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor may be a general-purpose processor, which is implemented by reading software codes stored in a memory, which may be integrated in the processor or may be located outside the processor and exist independently.

[0029] In a fifth aspect, a chip is provided, which obtains instructions and executes the instructions to implement the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

[0030] Optionally, as an implementation, the chip includes a processor and a data interface, and the processor reads instructions stored in the memory through the data interface to execute the method in the above-mentioned first aspect or any possible implementation of the first aspect.

[0031] Optionally, as an implementation method, the chip may also include a memory, in which instructions are stored, and the processor is used to execute the instructions stored in the memory. When the instructions are executed, the processor is used to execute the method in the above-mentioned first aspect or any possible implementation method of the first aspect.

[0032] In a sixth aspect, a computer program product comprising instructions is provided. When the instructions are executed by a computing device or a computing device cluster, the computing device or the computing device cluster executes the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

[0033] In the seventh aspect, a computer-readable storage medium is provided, comprising computer program instructions. When the computer instructions are executed by a computing device or a computing device cluster, the computing device or the computing device cluster executes the method in the above-mentioned first aspect or any possible implementation manner of the first aspect.

[0034] By way of example, these computer-readable storage media include, but are not limited to, one or more of the following: read-only memory (ROM), programmable ROM (PROM), erasable PROM (EPROM), Flash memory, electrically EPROM (EEPROM), and hard drive.

[0035] Optionally, as an implementation manner, the above-mentioned storage medium may specifically be a non-volatile storage medium. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of a cloud scenario provided in an embodiment of the present application.

[0037] Figure 2 It is a schematic diagram of a savings plan billing provided in an embodiment of the present application.

[0038] Figure 3 It is a schematic diagram of a current saving plan purchase suggestion provided by an embodiment of the present application.

[0039] Figure 4 This is a visual interface diagram of current savings plan purchase suggestions provided in an embodiment of the present application.

[0040] Figure 5 It is a schematic flowchart of a method for providing cloud services provided in an embodiment of the present application.

[0041] Figure 6 It is a schematic diagram of adjusting the usage of cloud service products provided by the embodiment itself.

[0042] Figure 7 This is another schematic diagram of adjusting the usage of cloud service products provided in an embodiment of the present application.

[0043] Figure 8 This is another visual interface diagram of a savings plan combination purchase suggestion provided in an embodiment of the present application.

[0044] Fig. 9 It is a schematic diagram of a saving plan purchase suggestion calculation module provided in an embodiment of the present application.

[0045] Fig.10 It is a schematic structural block diagram of a device for providing cloud services provided in an embodiment of the present application.

[0046] Fig.11 It is a schematic structural block diagram of a computing device provided in an embodiment of the present application.

[0047] Fig.12 It is a schematic structural block diagram of a computing device cluster provided in an embodiment of the present application.

[0048] Fig.13 It is a schematic structural block diagram of another computing device cluster provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0050] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0051] At present, the business in cloud scenarios is complex, and different businesses have different requirements for examples, regions, and availability zones at different time periods. Generally, when tenants use cloud service products such as cloud servers (elastic compute services, ECS) and elastic public IP addresses (elastic IP addresses, EIP) in cloud scenarios, they generally adopt a pay-as-you-go approach, that is, the billing of cloud service products is determined based on the amount of resources used, or annual and monthly packages are adopted. However, the cost of pay-as-you-go is high, and the flexibility of annual and monthly packages is limited. Therefore, at this stage, a savings plan that can achieve a balance between cost and flexibility is proposed.

[0052] Savings plans are discount benefit plans that are billed based on a guaranteed minimum consumption per unit time period (such as per hour). Tenants can exchange a lower pay-as-you-go discount for resources by committing to use a stable amount of resources (such as cloud service products) within a certain period (such as 1 year or 3 years). The consumption amount of resources that the user commits to use is the committed consumption amount of the savings plan, which can be measured in units of, for example, yuan per hour. After purchasing a savings plan, the portion of the tenant's bill within a unit time period that does not exceed the committed consumption amount will be billed with a savings plan-specific discount, while the portion that exceeds the committed consumption amount will not enjoy a discount and will be billed at the regular on-demand rate. In addition, the bill amount that does not reach the committed consumption amount needs to be paid according to the committed consumption amount.

[0053] To understand the cloud environment, Figure 1 A schematic diagram of a system based on a cloud server system is shown. Figure 1 As shown, the cloud management platform 110 is used to manage the infrastructure that provides multiple cloud services. The infrastructure includes multiple cloud data centers, each cloud data center includes multiple servers, and each server includes cloud service resources to provide corresponding cloud services to tenants.

[0054] The cloud management platform 110 provides an access interface (such as an interface or an application program interface (API)). The tenant can operate the client remote access access interface to register a cloud account and password on the code development platform and log in to the code development platform. After the code development platform successfully authenticates the cloud account and password, the tenant can further pay to select and purchase a virtual machine of a specific specification (processor, memory, disk) on the code development platform. After the paid purchase is successful, the code development platform provides the remote login account and password of the purchased virtual machine, and the client can remotely log in to the virtual machine, install and run the tenant's application in the virtual machine. The tenant of the cloud service can be an individual, an enterprise, a school, a hospital, an administrative agency, etc. The functions of the cloud management platform 110 include but are not limited to a user console, a computing management service, a network management service, a storage management service, an authentication service, and an image management service. The user console provides an interface or API to interact with the tenant, the computing management service is used to manage servers and bare metal servers running virtual machines and containers, the network management service is used to manage network services (such as gateways, firewalls, etc.), the storage management service is used to manage storage services (such as data bucket services), the authentication service is used to manage the tenant's account password, and the image management service is used to manage virtual machine images. The tenant can use the client 130 to log in to the cloud management platform 110 through the Internet 120 to manage the rented cloud services.

[0055] For example, in an embodiment of the present application, the tenant inputs information into the cloud management platform 110, so that the cloud management platform 110 obtains the historical consumption data of the tenant's cloud service products and confirms that the purchase method selected by the tenant is a combined purchase of a savings plan, and then the cloud management platform 110 outputs purchase recommendation information of the savings plan combination to the tenant, such as the covered products of each savings plan in the savings plan combination, the target recommended commitment amount, etc. The tenant can directly purchase the savings plan according to the target recommended commitment amount recommended in the purchase recommendation, or adjust the target recommended commitment amount according to its own business development before purchasing.

[0056] To facilitate understanding of the savings plan in the cloud scenario, Table 1 shows a schematic form of a savings plan. Figure 2 A schematic diagram of a savings plan billing provided in an embodiment of the present application is shown.

[0057] At present, there are many types of savings plans, such as computing, ECS (elastic compute service), and storage. As mentioned above, each savings plan can be used to deduct the cloud service products used by tenants, that is, to provide tenants with pay-as-you-go discounts for cloud service products. For example, an ECS-type savings plan can provide pay-as-you-go discounts for cloud service products such as ECS instances of a single specification family, cloud hard disk EVS (elastic volume service), and EIP.

[0058] Table 1

[0059]

[0060]

[0061] As shown in Table 1, each type of savings plan can include multiple deductible products, which are cloud service products in the savings plan that can have pay-as-you-go discounts. For example, the ECS-type savings plan can deduct cloud service products such as cloud server ECS, cloud hard disk EVS (elastic volume service), elastic public network IP (elastic IP Address, EIP); compared with the ECS-type savings plan, the computing-type savings plan can also deduct cloud service products such as cloud container instance (cloud container instance, CCI); the storage-type savings plan can deduct ECS, object storage service (object storage service, OBS), cloud backup and recovery (cloud backup and recovery, CBR), elastic file service (scalable file service, SFS) and other cloud service products. Among them, the ECS-type savings plan can be further divided according to factors such as region and specification family. For example, according to the south and north in the region, the ECS type saving plan can include the north-ECS type saving plan and the south-ECS type saving plan, the deductible products of the north-ECS type saving plan can include ECS located in the north region, and the deductible products of the south-ECS type saving plan can include ECS located in the south region. For another example, the ECS type saving plan in the same region can be further divided according to the specifications of the cloud service products, and the north-ECS type saving plan can further include the north-ECS-a1 type saving plan and the north-ECS-a2 type saving plan, where a1 and a2 are used to identify the specifications of the ECS respectively.

[0062] Unlike the ECS-type savings plan, the deductible product range of the computing and storage savings plans is not limited by region or rule family, that is, the deductible product range of the computing and storage savings plans is ECS, EVS and other cloud service products in all regions and specification families. However, the discount depth of the computing and storage savings plans can be lower than that of the ECS-type savings plan, that is, the charges provided to tenants may be higher.

[0063] It is worth noting that the categories, deductible product ranges and characteristics of the savings plans shown in Table 1 are only exemplary, and the savings plans applicable to the embodiments of the present application are not limited thereto. Any discount benefit plan that can provide tenants with discounts on cloud service products is applicable to the embodiments of the present application, and the classification of savings plans is not limited to the categories shown in Table 1. For example, the computing savings plans and storage savings plans in Table 1 can be classified in the same savings plan category due to the lack of regional and specification family restrictions, and can be named general savings plans. For another example, the categories of savings plans can also include flexible savings plans, that is, savings plans that determine the consumption amount value based on the actual usage of the tenant, and there is an upper limit on the consumption amount value. For another example, the three savings plans shown in Table 1 can also include more deductible products, such as function workflows (function graph) and the like.

[0064] It should also be understood that the above naming is only defined to facilitate the distinction between different functions and should not constitute any limitation to this application. This application does not exclude the possibility of using other naming in other cloud scenarios.

[0065] Optionally, the cloud management platform can provide tenants with purchase recommendation information for one or more savings plans based on the historical consumption data of cloud service products used by the tenants. For example, when the tenant's historical consumption data includes the usage records of ECS and EVS, the cloud management platform can provide tenants with purchase recommendations for computing-type savings plans and ECS-type savings plans for the tenants to choose from. Among them, the purchase recommendations for savings plans provided by the cloud management platform to tenants may include cloud service products that the tenants have historically used, the committed consumption amount of the savings plan, the usage of each cloud service product or the amount of on-demand consumption, and the discount factor for each cloud service product.

[0066] Optionally, the tenant can also manually select one or more savings plans they want to purchase in the cloud management platform, and then the cloud management platform will provide the tenant with purchase recommendations for one or more savings plans based on the tenant's historical consumption data of the cloud service products used by the tenant, which includes information such as the usage of the cloud service products used by the tenant, the discount factor, and the committed consumption amount of the savings plan.

[0067] Figure 2 A schematic diagram of a savings plan billing provided by an embodiment of the present application is shown, wherein: Figure 2 (a) shows a schematic diagram of a savings plan billing, Figure 2 (b) shows a schematic diagram of an example of savings plan billing.

[0068] like Figure 2As shown in (a) of , the committed consumption amount of the savings plan in each unit time period (e.g., each hour) is the same and fixed. If the actual consumption amount of the cloud service product after discount in the unit time period is within the committed consumption amount range, such as Figure 2 If the committed consumption amount is reached in the first unit time period or is not reached in the fourth unit time period, the unit time period will be charged according to the committed consumption amount. If the actual consumption amount of the cloud service product after discount in the unit time period exceeds the committed consumption amount, such as Figure 2 For the second and third unit time periods shown in (a) above, the excess amount will be charged at the regular pay-as-you-go rate.

[0069] To make it easier to understand the billing of the savings plan, such as Figure 2 As shown in (b) of FIG. 1 , the cloud management platform shows an example of a savings plan billing or a purchase suggestion for a savings plan, wherein the purchase suggestion for the savings plan includes cloud service products A to D, and the cloud service products A to D can be any cloud service products shown in Table 1. The cloud management platform can determine that the tenant has used cloud service products A to D based on the tenant's historical consumption data, and Figure 2 The deductible product range of the savings plan shown in (b) includes cloud service products A to D, so the cloud management platform can give purchase recommendations for the savings plan, and the purchase recommendations include the usage and discount factors of cloud service products A to D.

[0070] For example, in the tenant's historical consumption data, the tenant used cloud service products A and B in time period #1, the historical usage or on-demand payment amount of cloud service product A was 100, and the historical usage or on-demand payment amount of cloud service product B was 200. Similarly, the tenant used cloud service products A and C in time period #2, the usage or on-demand payment amount of cloud service product A was 100, and the usage or on-demand payment amount of cloud service product C was 200. In time period #3, the tenant used cloud service product D, and the usage or on-demand payment amount was 150. Then, based on the tenant's historical consumption data in the above example, the cloud management platform determines the following: Figure 2 The saving plan purchase suggestion is shown in (b) in . In the saving plan purchase suggestion, the time period in which each cloud service product is located and the usage in the time period are the same as the historical time period and historical usage of the cloud service product indicated in the historical consumption data. In other embodiments of the present application, the usage of the cloud service product in the saving plan purchase suggestion may also be higher than the historical usage of the cloud service product in the historical consumption data to provide tenants with more sufficient resource usage. For ease of description, the following will introduce an embodiment in the case where the usage of the cloud service product in the saving plan purchase suggestion is the same as the historical usage of the cloud service product in the historical consumption data.

[0071] In addition, the purchase recommendations of the savings plan may also include discount coefficients for cloud service products. For example, the cloud management platform may determine the discount coefficients for each cloud service product in the purchase recommendations of the savings plan based on factors such as the type of the savings plan, the period of use, and the payment method, such as Figure 2 The discount factor of cloud service product A shown in (b) is 0.2. For example, when the saving plan selected by the tenant has a longer usage period, the discount factor of the cloud service product in the saving plan purchase suggestion is lower.

[0072] The cloud management platform can determine the consumption amount for each unit time period based on the usage and discount coefficient of each cloud service product. For example, the consumption amount for time period #1 is 100 (the sum of 100*0.2 of cloud service product A and 200*0.4 of cloud service product B), the consumption amount for time period #2 is 140 (the sum of 100*0.2 of cloud service product A and 400*0.3 of cloud service product C), and the consumption amount for time period #3 is 45 (150*0.3 of cloud service product D).

[0073] Finally, the cloud management platform can determine the committed consumption amount of the savings plan based on the consumption amount in each time period. The committed consumption amount is Figure 2 Optionally, as shown in (a) Figure 2 As shown in (b), the committed consumption amount can be selected as the recommended consumption amount for time period #2, i.e., 140. At this time, after the tenant purchases the saving plan according to the purchase suggestion, the cost from time period #1 to time period #3 is 420 (140*3), i.e., the actual consumption amount from time period #1 and time period #3 does not reach the committed consumption amount, but the tenant needs to pay according to the committed consumption amount. Optionally, the committed consumption amount can be selected as 100 for time period #1. At this time, after the tenant purchases the saving plan according to the purchase suggestion, the cost from time period #1 to time period #3 can be 433 (100*3+(140-100) / 0.3), i.e., the portion of the actual consumption amount in time period #2 that exceeds the committed consumption amount needs to be paid according to the on-demand rate. In the above example, the actual consumption amount may exceed due to cloud service product C, and the on-demand rate can be charged according to the usage of cloud service product C. At this time, when the committed consumption amount is 100, the tenant's payment cost is higher than the tenant's payment cost when the committed consumption amount is 140.

[0074] Optionally, the committed consumption amount value can also be any amount between the maximum and minimum consumption amounts in different time periods. The cloud management platform can traverse any amount between the maximum and minimum values, calculate the payment cost when each amount is used as the committed consumption amount, and finally determine the consumption amount with the lowest payment cost as the optimal committed consumption amount of the savings plan, that is, when the tenant purchases the savings plan with the optimal committed consumption amount, the payment cost is the lowest. For example, Figure 2 Taking (b) in the figure as an example, the cloud management platform can traverse all integer values ​​between 0 and 140, that is, calculate the payment cost of the saving plan when all integer values ​​between 0 and 140 are used as the committed consumption amount, and finally determine that the payment cost of the saving plan is the lowest when the committed consumption amount is 140. Then the cloud management platform uses 140 as the optimal committed consumption amount of the saving plan and feeds it back to the tenant.

[0075] However, as can be seen from Table 1 above, the deductible product ranges of different types of savings plans may overlap, for example, the ECS-type savings plan and the computing-type savings plan can both deduct ECS, EVS, and EIP. Therefore, when the tenant's historical consumption data includes consumption records of any one or several of the above cloud service products, the cloud management platform can provide the tenant with a combined purchase recommendation of the above two savings plans. For example, when the tenant's historical consumption data includes the usage of north-ECS, south-ECS, and CCI, the cloud management platform can recommend to the tenant a combined purchase recommendation of the north-ECS-type savings plan, the south-ECS-type savings plan, and the computing-type savings plan, wherein the purchase recommendation of the north-ECS-type savings plan includes the usage and discount factor of north-ECS, the purchase recommendation of the south-ECS-type savings plan includes the usage and discount factor of south-ECS, and the purchase recommendation of the computing-type savings plan includes the usage and discount factor of north-ECS, south-ECS, and CCI. At this time, the three savings plans can form a combination of the north-ECS savings plan and the computing savings plan, as well as a combination of the south-ECS savings plan and the computing savings plan. The basis for the combination is that the cloud service products that can be deducted by the computing savings plan overlap with the cloud service products that can be deducted by the north-ECS savings plan and the south-ECS savings plan. However, it is worth noting that the north-ECS savings plan and the south-ECS savings plan cannot be in the same savings plan combination because the deductible product range of the two savings plans does not include overlapping cloud service products.

[0076] For ease of understanding, Figure 3 A schematic diagram showing a combination purchase suggestion for the current savings plan, Figure 4The visualization interface diagram of the combined purchase suggestion of the saving plan is shown. The tenant's historical consumption data includes the usage of cloud service products A to G, and the deductible product ranges of saving plan #1 and saving plan #2 overlap, and the overlapping cloud service products are A and B.

[0077] Then, the cloud management platform determines the following according to the tenant’s historical consumption data and the deductible product range of each savings plan: Figure 3 The purchase suggestions for Saving Plan #1 and Saving Plan #2 are shown. In which, the tenant used cloud service products B (usage of 270), E (usage of 150) and G (usage of 100) in time period #1. Saving Plan #1 can deduct B and G, and Saving Plan #2 can deduct B and E. Then, the cloud management platform determines that the usage of B in time period #1 of Saving Plan #1 is 270 and the usage of G is 100, and the usage of B in time period #1 of Saving Plan #2 is 270 and the usage of E is 150. Similarly, the cloud management platform determines the deductible cloud service products and the usage of each cloud service product in time period #2 and time period #3 respectively.

[0078] Finally, after determining Figure 3 After the combined purchase recommendations of the two saving plans are made, the cloud management platform determines the committed consumption amounts of the two purchase recommendations respectively, and combines the optimal committed consumption amount and the calculated lowest total payment cost through Figure 4 The visual interface shown is presented to the tenant. Figure 4 As shown, the tenant's historical consumption data can be selected as the past 30 days, or other optional time ranges such as a quarter, a year, etc. The purchase suggestions presented by the cloud management platform can include the coverage product range of the purchase suggestions of the two savings plans, and can also include the total savings cost of the combined purchase suggestions. Figure 3 For the combined purchase suggestion shown, the cloud management platform can determine that the optimal committed consumption amount value for Saving Plan #1 is 140 for time period #2, and the lowest total cost is 420 (140*3), and the optimal committed consumption amount value for Saving Plan #2 is 60 for time period #3, and the lowest total cost is 375 (60*3+(270*0.4+150*0.2-200*0.3) / 0.4), and based on the sum of the total costs and the total amount of on-demand payment (i.e. Figure 3 The total cost savings is 625.

[0079] For ease of description, the committed consumption amount when the paid cost of a savings plan is the lowest is referred to as the "optimal committed consumption amount" below, and the cloud management platform will automatically determine the optimal committed consumption amount of a savings plan each time it generates a purchase recommendation for the savings plan.

[0080] Optionally, unlike the above-mentioned cloud management platform determining the relevant savings plan based on the tenant's historical consumption data, the tenant can also manually select savings plan #1 and savings plan #2, and then the cloud management platform determines the savings plan based on the tenant's historical consumption data. Figure 3 and Figure 4 The deductible products in the purchase suggestions of Savings Plan #1 and Savings Plan #2 are shown. This application does not go into detail about this process.

[0081] However, Cloud Service Products A and B are overlapping deductible products of Savings Plan #1 and Savings Plan #2. Figure 3 The two purchase suggestions shown take into account the usage of cloud service products A and B, that is, the usage of cloud service products A and B is repeated in the two purchase suggestions. In other words, the usage of cloud service product A used by the tenant is 100, but if Figure 3 The tenant actually purchased 200 cloud service product A, which means that the tenant purchased cloud service product A once, and the same applies to cloud service product B. The reason is that the cloud management platform determines the purchase recommendations for savings plan #1 and savings plan #2 separately, so the usage of cloud service products A and B is considered once in the two purchase recommendation determination processes. Therefore, when the user needs to purchase savings plan #1 and savings plan #2 at the same time, Figure 3 The total savings cost of the purchase recommendations of the two savings plans given separately is high. The prior art cannot provide users with combined purchase recommendations on savings plans to further reduce the cost of users purchasing savings plans.

[0082] In order to save tenants' usage costs and improve their usage experience, the cloud management platform needs to generate reasonable savings plan purchase recommendations. The embodiment of the present application proposes a method 500 for providing cloud services. The method 500 is applied to a cloud management platform. The cloud management platform can provide a variety of savings plans such as the ECS type, computing type, and storage type mentioned above for tenants to choose from. Method 500 includes steps 510 to 540, which reduces the cost of combined purchase recommendations for multiple savings plans by adjusting the usage of overlapping cloud service products considered in multiple savings plans, thereby providing tenants with savings plan purchase recommendations with higher cost savings.

[0083] Step 510: Obtain input information of the tenant, which indicates historical consumption data of the cloud service product and a purchase method of the savings plan.

[0084] As mentioned above, the historical consumption data of cloud service products can include the usage of various cloud service products of tenants or the amount of on-demand payment, such as Figure 3Optionally, the historical consumption data of cloud service products may also include the time range of the tenant's use of the cloud service product, such as a historical usage time period.

[0085] In an embodiment of the present application, the input information may indicate the historical consumption data of cloud service products. For example, the tenant may input or manually select the time span of the historical consumption data as one month, and then the cloud management platform queries the historical consumption data of the cloud service products of the tenant within one month based on the input information obtained. For another example, the tenant may manually select the historical consumption data within a specific time range. For example, according to the actual business changes, the tenant may manually select the historical consumption data of the previous 1-10 days and the previous 20-30 days, or the historical consumption data of cloud service products in a specific region or specification family.

[0086] The input information may also indicate a method for purchasing a savings plan. For example, as mentioned above, a tenant may choose to purchase multiple savings plans in combination, or may specify to purchase a specific type of savings plan. The embodiments of the present application are applicable to situations where a tenant chooses to purchase a savings plan in combination, that is, the cloud management platform may provide tenants with purchase recommendations for multiple savings plan combinations. The following will describe in detail a solution for the cloud management platform to determine purchase recommendations for savings plan combinations.

[0087] Optionally, in other embodiments of the present application, the tenant's input information may also indicate the type of savings plan, the duration of the savings plan, the method of purchasing the savings plan, etc., so that the cloud management platform can determine the discount coefficient of each cloud service product in the purchase suggestion based on the above input information. For example, when the tenant selects a longer duration of the savings plan and the payment method is full payment, the discount coefficient of each cloud service product in the purchase suggestion of the savings plan is lower.

[0088] Step 520: When the purchase method of the saving plan is a combination purchase, a saving plan combination is determined from the multiple saving plans according to the historical consumption data.

[0089] As mentioned above, the historical consumption data includes the cloud service products used by the tenant and the usage of the cloud service products. In step 520, the cloud management platform can determine a savings plan combination based on the cloud service products in the historical consumption data. The savings plan combination includes multiple savings plans, and the deduction scope of each savings plan includes the first cloud service product among the multiple cloud service products.

[0090] It should be understood that Figure 3For example, the deduction scope of savings plan #1 and savings plan #2 both include cloud service products A and B, so cloud service products A and B can be the first cloud service product mentioned above. Furthermore, the savings plan combination is the combination of savings plan #1 and savings plan #2. For another example, the deduction scope of savings plan #3 includes cloud service product A, then the savings plan combination is the combination of savings plan #1, savings plan #2 and savings plan #3, that is, the deductible products of the savings plans in the combination all include cloud service product A. For another example, if the deduction scope of savings plan #4 includes cloud service product C, then savings plan #1 whose deduction scope includes cloud service product C can be combined with savings plan #4 as a savings plan combination. In other words, in an embodiment of the present application, the number of savings plan combinations determined by the cloud management platform can be one or more, and the basis for the combination is that the deduction scope includes the same one or more cloud service products.

[0091] In an embodiment of the present application, when a tenant selects a combined purchase method for a savings plan, the tenant can also specify the type of savings plan to be purchased. For example, the tenant also chooses to specify the purchase of a storage-type savings plan and a computing-type savings plan, and then when the cloud management platform determines a savings plan combination from a variety of savings plans, it only considers the combined purchase suggestions for storage-type savings plans and computing-type savings plans, and does not consider ECS-type savings plans with the same cloud service products in the deduction range. If the tenant does not specify the type of savings plan to be purchased, the cloud management platform can traverse all types of savings plans and provide all possible savings plan combinations to the tenant.

[0092] Step 530: Determine a target recommended commitment amount for each saving plan in the saving plan combination by adjusting the usage of the first cloud service product that is considered in each of the multiple saving plans in the saving plan combination.

[0093] It should be understood that, as mentioned above, in the current combined purchase recommendations of multiple savings plans, the first cloud service product is considered separately and multiple times in multiple savings plans, so that the tenant needs to bear the cost of multiple times the usage when using a certain amount of the first cloud service product, which leads to a high total cost of the purchase recommendation of the savings plan combination generated by the cloud management platform. Therefore, in step 530, the cloud management platform can reduce the total cost of the purchase recommendation of the savings plan combination by adjusting the usage of the first cloud service product considered separately in multiple savings plans in the savings plan combination.

[0094] For example, in Figure 3In the combined purchase suggestion shown, the cloud management platform can adjust the usage of cloud service product B in savings plan #2 to 0, so that the tenant can still use cloud service product B with a usage of 270 after purchasing savings plan #1, and the total cost of savings plan #2 is greatly reduced because there is no on-demand payment for cloud service product B. In addition, the cloud management platform can determine the optimal committed consumption amount for each savings plan in the savings plan combination based on the adjusted usage of the first cloud service product, so that the total cost of the combined purchase suggestion is lower and the cost savings are higher.

[0095] It should be understood that the target recommended commitment amount for each savings plan is the committed consumption amount for each savings plan that corresponds to the lowest cost of purchasing the savings plan combination. In other words, each time the cloud management platform adjusts the usage of the first cloud service product, it calculates the optimal committed consumption amount for each savings plan in the savings plan combination and the payment cost of the savings plan combination, and continuously compares until the recommended purchase plan for the savings plan combination with the lowest payment cost is determined. At this point, the optimal committed consumption amount for each savings plan in the savings plan combination with the lowest payment cost is the target recommended commitment amount for each savings plan mentioned in step 530. In other words, the target recommended commitment amount is the optimal committed consumption amount in the optimal usage allocation plan determined by the cloud management platform.

[0096] Optionally and preferably, the sum of the usage of the first cloud service product considered in the multiple savings plans of the savings plan combination is equal to the usage of the first cloud service product. In other words, the embodiment of the present application allocates the usage of the first cloud service product to the multiple savings plans of the savings plan combination. The process of adjusting the usage of the first cloud service product will be described in detail below, and will not be elaborated in this article.

[0097] Specifically, as mentioned above for Figure 3 As described in the description, the process of determining the optimal recommended commitment amount for each saving plan in the saving plan combination can be based on the usage of each cloud service product in the saving plan, the discount factor, etc. The discount factor can be determined based on the saving plan type, saving plan period, saving plan purchase method, etc. indicated by the above tenant. The specific value of the optimal recommended commitment amount for each saving plan can be determined based on the actual consumption amount in each time period in the saving plan, that is, the cloud management platform traverses the commitment amounts with different values, and Figure 2 The billing method shown determines the payment cost under different values ​​of the commitment amount, and finally determines the optimal recommended commitment amount corresponding to the lowest payment cost. The actual consumption amount in each time period is obtained by multiplying the usage of the included cloud service products by the discount coefficient.

[0098] In an embodiment of the present application, the cloud management platform needs to adjust the usage of the first cloud service product considered in multiple saving plans in the saving plan combination, determine the optimal recommended commitment amount of each saving plan in the saving plan combination and the payment cost of the saving plan combination based on the adjusted usage, and continuously adjust the usage of the first cloud service product considered, and then determine the optimal recommended commitment amount of each saving plan in the saving plan combination and the payment cost of the saving plan combination based on the adjusted usage, until the payment cost of the saving plan combination is the minimum of all payment costs obtained during the adjustment process, the cloud management platform determines that the optimal committed consumption amount for each saving plan in this situation is the target recommended commitment amount for each saving plan.

[0099] For example, the cloud management platform may first determine the usage, discount coefficient, etc. of a non-overlapping range of cloud service products such as the second cloud service product based on historical consumption data, for example Figure 3 The usage and discount coefficients of cloud service products C, D, E, and G are shown; secondly, the cloud management platform sets an initial allocated usage for the first cloud service product in the savings plan combination, for example Figure 3 The usage of cloud service product A shown is 100, and the cloud management platform can initially set the usage of cloud service product A to be considered as 50 and 50 in saving plan #1 and saving plan #2, respectively; then, the cloud management platform can determine the optimal committed consumption amount of each saving plan and the minimum payment cost of the saving plan combination based on the saving plan combination after the initial allocation, that is, according to the usage of cloud service products in non-overlapping ranges in multiple saving plans, the discount coefficient and the discount coefficient of the first cloud service product, and the usage considered in multiple saving plans, the optimal committed consumption amount of each saving plan is determined by traversing; thereafter, the cloud management platform adjusts the usage of the first cloud service product considered in multiple saving plans once or multiple times, for example, the usage of cloud service product A is adjusted to 40 and 60, and the optimal committed consumption amount of each saving plan and the payment cost of the corresponding saving plan combination are recalculated each time the adjustment is made, and the comparison is performed until the minimum payment cost of the saving plan combination is obtained, and the optimal allocation scheme for the usage of the first cloud service product considered in multiple saving plans and the target recommended commitment amount of each saving plan are determined.

[0100] It is worth noting that this application does not limit the specific algorithm for adjusting the usage of the cloud management platform and the algorithm for determining the optimal committed consumption amount. For example, the above algorithm can be implemented through an exhaustive algorithm, that is, by continuously trying different usage adjustment ratios to determine the optimal adjustment usage plan, and by setting a step size within a certain numerical range (for example, between the maximum and minimum values ​​of the actual consumption amount in different time periods), trying to calculate the payment cost of the savings plan combination under each value, and then determining the optimal committed consumption amount corresponding to the lowest payment cost.

[0101] In an embodiment of the present application, when there are multiple savings plan combinations, the cloud management platform can perform the above-mentioned steps of adjusting the usage and calculating the committed consumption amount for each savings plan combination. This process is the superposition of the process of the cloud management platform adjusting the usage and calculating the committed consumption amount for a single savings plan combination, which will not be described in detail in this article.

[0102] Step 540: Feedback the target recommended commitment amount of each savings plan in the savings plan combination to the tenant.

[0103] Specifically, step 540 can be performed by Figure 4 The visualization interface shown provides tenants with feedback on the target recommended commitment amount for each savings plan.

[0104] Alternatively, if Figure 4 As shown, the cloud management platform can also feedback the cost of each saving plan, the total cost of the saving plan combination, the saving cost, etc. to the tenant through step 540. In addition, the cloud management platform can also feedback the estimated monthly saving cost, the estimated monthly expenditure before purchase, the estimated monthly amortization cost after purchase, etc. This application does not limit the content of the visual interface feedback of the cloud management platform.

[0105] Optionally, in the case where there are multiple savings plan combinations, the cloud management platform may simultaneously provide feedback on purchase recommendations, target recommended commitment amounts, etc. for the multiple savings plan combinations through step 540 .

[0106] In order to facilitate understanding of how to adjust the usage of the first cloud service product in the multiple savings plans of the savings plan combination, based on Figure 3 Example of a savings plan in Figure 6 and Figure 7 A schematic diagram of adjusting the usage of cloud service products is shown. Figure 6 and Figure 7The purchase suggestions shown may be two combination purchase suggestions with lower costs finally determined by the cloud management platform in step 530, or may be two allocation situations in the process of the cloud management platform adjusting the first cloud service product. The first cloud service product is cloud service products A and B, and the cloud management platform considers the usage of cloud service products A and B in saving plan #1 and saving plan #2 respectively.

[0107] like Figure 6 As shown in Figure 1, the cloud management platform considers the usage of cloud service product A in savings plan #1 and savings plan #2 as 0 and 100, respectively, that is, the usage of cloud service product A is deleted from the purchase recommendation of savings plan #1. Figure 3 Savings Plan #1 in Figure 6 Savings Plan #1 shown has a lower premium cost because Figure 3 The committed consumption amount of savings plan #1 in is the actual consumption amount of time period #2, while Figure 6 In the savings plan #1 shown, the actual consumption amount in time period #2 is reduced by 100 (i.e., the total consumption of cloud service product A is reduced), so Figure 6 The optimal committed consumption amount of the savings plan #1 shown must be less than Figure 3 The optimal committed consumption amount of Saving Plan #1 is shown. Similarly, the cloud management platform considers the usage of cloud service product B in Saving Plan #1 and Saving Plan #2 as 195 and 75 respectively, and the sum is the usage of cloud service product B in historical consumption data as 270. Compared with Figure 3 In Saving Plan #1 and Saving Plan #2, after considering the usage of Cloud Service Product B, Cloud Service Product B Figure 6 The amount of savings plan #1 and savings plan #2 shown is less than Figure 3 The usage of Savings Plan #1 and Savings Plan #2 is shown, so Figure 6 The optimal committed consumption amount of savings plan #1 and savings plan #2 shown must be less than Figure 3 The optimal committed consumption amount for Saving Plan #1 and Saving Plan #2 is shown. Figure 6 As shown in the figure, the optimal committed consumption amounts of Saving Plan #1 and Saving Plan #2 can be 120 and 60 respectively, and the minimum total cost can be 540 (120*3+60*3), which is less than Figure 4 Total costs for Savings Plan #1 and Savings Plan #2 are shown.

[0108] In step 530, the cloud management platform can adjust the usage of cloud service products A and B in savings plan #1 and savings plan #2. For example, the cloud management platform can Figure 6 The distribution shown is adjusted to Figure 7The cloud management platform can adjust the usage of cloud service product B in savings plan #1 and savings plan #2 to 250 and 20 respectively. Figure 7 The optimal committed consumption amount is calculated for each of the savings plan combinations shown. Figure 7 As shown, the cloud management platform obtains the optimal committed consumption amounts of Saving Plan #1 and Saving Plan #2 through the algorithm, which are still 120 and 60 respectively, so the total cost is still 540. At this time, the cloud management platform can continuously adjust the usage of cloud service products A and B in Saving Plan #1 and Saving Plan #2, and calculate the total cost of each adjusted saving plan combination and the optimal committed consumption amount of each saving plan, until the target recommended committed amount of each saving plan is determined when the total payment cost is the lowest.

[0109] For example, suppose the cloud management platform determines during its ongoing adjustment that Figure 6 and Figure 7 The payment cost of the savings plan combination shown is the minimum value, and 120 is the target recommended commitment amount for savings plan #1, and 60 is the target recommended commitment amount for savings plan #2, and feedback is given to the tenant. Figure 6 and / or Figure 7 Purchase recommendations for savings plan combinations shown.

[0110] Figure 8 A schematic diagram of a feedback saving plan combination according to an embodiment of the present application is shown. Figure 8 As shown, the tenant's input information includes the time range of historical consumption data and the purchase method of the savings plan. Then, the cloud management platform obtains the tenant's historical consumption data of cloud service products based on the time range of historical consumption data, and combines the savings plan according to the purchase method, and provides the tenant with one or more possible combination purchase suggestions for the savings plan. If the cloud management platform continuously adjusts the usage of cloud service products A and B in savings plan #1 and savings plan #2, respectively, it determines Figure 6 or Figure 7 The total cost of the combination purchase suggestion shown is the lowest, and then Figure 8 As shown in Figure 1, the cloud management platform provides tenants with purchase recommendations for savings plan combinations through a visual interface. Figure 4 , the covered products of Saving Plan #1 do not include Cloud Service Product A, that is, the usage of Cloud Service Product A in Saving Plan #1 is 0, but the covered products of Saving Plan #2 include Cloud Service Product A, and the usage of Cloud Service Product A in Saving Plan #2 is the usage of Cloud Service Product A in the historical consumption data. For another example, compared with Figure 4 , Figure 8 The total cost is lower and the cost savings are higher, at 880, which is higher than Figure 4625. In other words, through the method 500 of the embodiment of the present application, the total cost of the savings plan combination purchase suggestion can be reduced, the savings cost can be increased, and thus a more economical and cost-effective savings plan purchase suggestion can be provided to the tenant.

[0111] Fig. 9 FIG. 1 is a schematic diagram showing a purchase suggestion calculation module for a savings plan according to an embodiment of the present application. Fig. 9 As shown, the purchase suggestion calculation module may include a purchase suggestion range acquisition module, a data preprocessing module, and a purchase suggestion information processing module. Among them, the purchase suggestion range acquisition module can obtain the tenant's input information, for example, the input information can be the time span range of historical consumption data, the purchase method, type, and usage period of the saving plan, and other configuration parameter information. Furthermore, the purchase suggestion range acquisition module can obtain the tenant's historical consumption data of cloud service products, including the cloud service products used by the tenant and the usage of each cloud service product. In the case where the tenant chooses to purchase the saving plan combination, the data preprocessing module can determine one or more saving plan combinations based on the tenant's historical consumption data obtained by the purchase suggestion range acquisition module. Finally, the purchase suggestion information processing module determines the usage and discount coefficient of the cloud service products in each saving plan in the saving plan combination, the optimal committed consumption amount and total cost of each saving plan, etc. through the saving plan combination purchase suggestion module, and outputs the purchase suggestion information to the tenant through a visual interface.

[0112] Optionally, in some other embodiments of the present application, the purchase method of the savings plan selected by the tenant may also be a single savings plan, that is, the tenant selects a specific type of savings plan to purchase. Fig. 9 The multiple modules shown can also output purchase suggestion information to the tenant based on the same process. For example, the purchase suggestion range acquisition module obtains the tenant's historical consumption data of deductible cloud service products using the specific type of savings plan and the configuration parameter information of the specific type of savings plan selected by the tenant. The data preprocessing module determines the coverage products or deductible product range of the specific type of savings plan based on the historical consumption data. The single savings plan purchase suggestion module in the purchase suggestion information processing module determines the usage and discount coefficient of the cloud service products in the specific type of savings plan, the optimal committed consumption amount and total cost of the specific type of savings plan, etc.

[0113] Based on the above method for providing cloud services, in an embodiment of the present application, when a tenant chooses to purchase a savings plan in combination, the cloud management platform determines a purchase recommendation plan for a savings plan combination with a lower total cost and higher cost savings by adjusting the usage of overlapping cloud service products in multiple savings plans of the savings plan combination. In turn, the cost of using cloud service products for tenants can be further reduced, and the tenants' rights and interests can be maximized to encourage tenants to expand their cloud consumption.

[0114] The method embodiments of the present application are described in detail above. Figures 10 to 13 The device embodiment of the embodiment of the present application is described. The device embodiment corresponds to the method embodiment, so the parts that are not described in detail can refer to the previous method embodiments. The device can implement any possible implementation method of the above method.

[0115] Combined with the following Fig.10 The following is a block diagram of a cloud service providing device 1000 according to an embodiment of the present application. Fig.10 The device 1000 shown may be the cloud management platform mentioned above, for executing Figure 5 The method shown can also be a device module for implementing a cloud management platform to provide cloud services. It should be understood that the device described below can execute the method of the aforementioned embodiment of the present application. In order to avoid unnecessary repetition, repeated descriptions are appropriately omitted when introducing the device of the embodiment of the present application.

[0116] Fig.10 is a schematic diagram of a device for providing cloud services according to an embodiment of the present application. Fig.10 The device 1000 shown includes: an acquisition module 1010 , a processing module 1020 and a feedback module 1030 .

[0117] Specifically, the acquisition module 1010 is used to: acquire input information of a tenant, the input information indicating historical consumption data of a cloud service product and a purchase method of a saving plan, the historical consumption data of the cloud service product including the usage of multiple cloud service products of the tenant;

[0118] Specifically, the processing module 1020 is used to: when the purchase method of the saving plan is a combination purchase, determine a saving plan combination from the multiple saving plans according to the historical consumption data, the saving plan combination including multiple saving plans, wherein the deduction scope of each saving plan in the saving plan combination includes the first cloud service product among the multiple cloud service products of the tenant;

[0119] Determine a target recommended commitment amount for each saving plan of the saving plan combination by adjusting the usage of the first cloud service product considered in each of the plurality of saving plans of the saving plan combination;

[0120] Specifically, the feedback module 1030 is used to: provide feedback to the tenant on the target recommended commitment amount of each saving plan in the saving plan combination.

[0121] The specific functions and beneficial effects of the acquisition module 1010, the processing module 1020 and the feedback module 1030 are described in the above embodiments, and will not be described again for the sake of brevity.

[0122] The above modules can be implemented by software or hardware. For example, the implementation of the processing module 1020 is described below by taking the processing module 1020 as an example. Similarly, the implementation of the acquisition module 1010 and the feedback module 1030 can refer to the implementation of the processing module 1020.

[0123] As an example of a software functional unit, the processing module 1020 may include code running on a computing instance. Among them, the computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Further, the above-mentioned computing instance may be one or more. For example, the processing module 1020 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region (region) or in different regions. Furthermore, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including a data center or multiple data centers with similar geographical locations. Among them, usually a region may include multiple AZs.

[0124] Similarly, multiple hosts / virtual machines / containers used to run the code can be distributed in the same virtual private cloud (VPC) or in multiple VPCs. Usually, a VPC is set up in a region. For cross-region communication between two VPCs in the same region and between VPCs in different regions, a communication gateway needs to be set up in each VPC to achieve interconnection between VPCs through the communication gateway.

[0125] As an example of a hardware functional unit, the processing module 1020 may include at least one computing device, such as a server, etc. Alternatively, the processing module 1020 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0126] The multiple computing devices included in the processing module 1020 can be distributed in the same region or in different regions. The multiple computing devices included in the processing module 1020 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the processing module 1020 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices included in the processing module 1020 can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0127] The present application also provides a computing device 1100. Fig.11 As shown, the computing device 1100 includes: a bus 1102, a processor 1104, a memory 1106, and a communication interface 1108. The processor 1104, the memory 1106, and the communication interface 1108 communicate through the bus 1102. The computing device 1100 can be a server or a terminal device. It should be understood that the present application does not limit the number of processors and memories in the computing device 1100.

[0128] The bus 1102 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.11 The bus 1102 may include a path for transmitting information between various components of the computing device 1100 (eg, the memory 1106, the processor 1104, and the communication interface 1108).

[0129] The processor 1104 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0130] The memory 1106 may include a volatile memory, such as a random access memory (RAM). The memory 1106 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0131] The memory 1106 stores executable program codes, and the processor 1104 executes the executable program codes to respectively implement the functions of the acquisition module 1010, the processing module 1020, and the feedback module 1030, thereby implementing the above-mentioned method for providing cloud services. That is, the memory 1306 stores instructions for executing the above-mentioned cloud service provision.

[0132] The communication interface 1108 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 1100 and other devices or a communication network.

[0133] The embodiment of the present application also provides a computing device cluster. The computing device cluster includes at least two computing devices. The computing device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smart phone.

[0134] like Fig.12 As shown, the computing device cluster includes at least two computing devices 1100. The memory 1106 in the multiple computing devices 1100 in the computing device cluster may store the same instructions for executing the above-mentioned cloud service provision.

[0135] In some possible implementations, the memory 1106 of the plurality of computing devices 1100 in the computing device cluster may also respectively store some instructions for executing the above-mentioned cloud service provision. In other words, a combination of one or more computing devices 1100 may jointly execute the instructions for executing the above-mentioned cloud service provision.

[0136] It should be noted that the memory 1106 in different computing devices 1100 in the computing device cluster can store different instructions, which are respectively used to execute part of the functions of the above-mentioned apparatus. That is, the instructions stored in the memory 1106 in different computing devices 1100 can implement the functions of one or more modules among the acquisition module, the processing module and the feedback module.

[0137] In some possible implementations, multiple computing devices in a computing device cluster may be connected via a network, which may be a wide area network or a local area network. Fig.13 A possible implementation is shown. Fig.13 As shown, two computing devices 1100A and 1100B are connected via a network. Specifically, the network is connected via a communication interface in each computing device. In this type of possible implementation, the memory 1106 in the computing device 1100A stores instructions for the functions of the acquisition module. At the same time, the memory 1106 in the computing device 1100B stores instructions for the functions of the execution processing module and the feedback module.

[0138] It should be understood that Fig.13 The functions of the computing device 1100A shown in FIG. 1100A may also be completed by multiple computing devices 1100. Similarly, the functions of the computing device 1100B may also be completed by multiple computing devices 1100.

[0139] An embodiment of the present application also provides a chip, which includes a processor and a data interface. The processor reads instructions stored in a memory through the data interface to execute the above-mentioned method for providing cloud services.

[0140] The embodiment of the present application also provides a computer program product including instructions. The computer program product may be a software or program product including instructions that can be run on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, the at least one computing device executes the above-mentioned method for providing cloud services.

[0141] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by the computing device or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute the above-mentioned method for providing cloud services.

[0142] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, 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 specification.

[0143] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the protection scope of the technical solutions of the embodiments of the present application.

[0144] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0145] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0146] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0147] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0148] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0149] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for providing cloud services, characterized in that: The method is applied to a cloud management platform, and the cloud management platform is used to provide multiple savings plans for cloud service products, wherein the deduction scope of each savings plan includes multiple cloud service products, and the method includes: Obtaining input information of the tenant, the input information indicating historical consumption data of cloud service products and a purchase method of a savings plan, the historical consumption data of cloud service products including usage of multiple cloud service products of the tenant; In the case where the saving plan is purchased in combination, a saving plan combination is determined from the multiple saving plans according to the historical consumption data, the saving plan combination including multiple saving plans, wherein the deduction scope of each saving plan in the saving plan combination includes the first cloud service product among the multiple cloud service products of the tenant; Determine a target recommended commitment amount for each saving plan of the saving plan combination by adjusting the usage of the first cloud service product considered in each of the plurality of saving plans of the saving plan combination; A target recommended commitment amount for each savings plan of the savings plan combination is fed back to the tenant.

2. The method according to claim 1, characterized in that: The step of determining a target recommended commitment amount for each saving plan of the saving plan combination by adjusting the usage of the first cloud service product considered in the plurality of saving plans of the saving plan combination includes: Determining, based on the historical consumption data, the usage of a second cloud service product in each saving plan of the saving plan combination, wherein the second cloud service product is a cloud service product other than the first cloud service product in the saving plan; Calculate a recommended commitment amount for each saving plan of the saving plan combination according to the usage of the second cloud service product in each saving plan of the saving plan combination and the allocation of the first cloud service product in the saving plan combination, wherein the allocation indicates the usage of the first cloud service product considered in the multiple saving plans of the saving plan combination respectively; The allocation of the first cloud service product in the savings plan combination is adjusted to determine the target recommended commitment amount for each savings plan in the savings plan combination.

3. The method according to claim 2, characterized in that The calculating the recommended commitment amount for each saving plan of the saving plan combination according to the usage of the second cloud service product in each saving plan of the saving plan combination and the allocation of the first cloud service product in the saving plan combination includes: Determining a discount factor for each cloud service product in each savings plan of the savings plan combination; The recommended commitment amount for each saving plan in the saving plan combination is calculated based on the usage of the second cloud service product in each saving plan in the saving plan combination, the distribution of the first cloud service product in the saving plan combination, and the discount factor of each cloud service product.

4. The method according to any one of claims 1 to 3, characterized in that A sum of usages of the first cloud service product considered in a plurality of saving plans of the saving plan combination is equal to the usage of the first cloud service product.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: The cost savings of the savings plan combination is fed back to the tenant, where the cost savings of the savings plan combination is the difference between the cost of purchasing the savings plan combination and the on-demand payment costs of the tenant's multiple cloud service products.

6. A device for providing cloud services, characterized in that: The device is used to provide multiple saving plans for cloud service products, wherein the deduction scope of each saving plan includes multiple cloud service products, and the device includes: An acquisition module, configured to: acquire input information of a tenant, wherein the input information indicates historical consumption data of a cloud service product and a purchase method of a saving plan, wherein the historical consumption data of the cloud service product includes usage of multiple cloud service products of the tenant; a processing module, configured to: when the purchase mode of the saving plan is a combined purchase, determine a saving plan combination from the multiple saving plans according to the historical consumption data, the saving plan combination including multiple saving plans, wherein the deduction scope of each saving plan in the saving plan combination includes the first cloud service product among the multiple cloud service products of the tenant; Determine a target recommended commitment amount for each saving plan of the saving plan combination by adjusting the usage of the first cloud service product considered in each of the plurality of saving plans of the saving plan combination; A feedback module is used to: provide feedback to the tenant on the target recommended commitment amount of each saving plan in the saving plan combination.

7. The device according to claim 6, characterized in that The processing module is specifically used for: Determining, based on the historical consumption data, the usage of a second cloud service product in each saving plan of the saving plan combination, wherein the second cloud service product is a cloud service product other than the first cloud service product in the saving plan; Calculate a recommended commitment amount for each saving plan of the saving plan combination according to the usage of the second cloud service product in each saving plan of the saving plan combination and the allocation of the first cloud service product in the saving plan combination, wherein the allocation indicates the usage of the first cloud service product considered in the multiple saving plans of the saving plan combination respectively; The allocation of the first cloud service product in the savings plan combination is adjusted to determine the target recommended commitment amount for each savings plan in the savings plan combination.

8. The device according to claim 7, characterized in that The processing module is specifically used for: Determining a discount factor for each cloud service product in each savings plan of the savings plan combination; The recommended commitment amount for each saving plan in the saving plan combination is calculated based on the usage of the second cloud service product in each saving plan in the saving plan combination, the distribution of the first cloud service product in the saving plan combination, and the discount factor of each cloud service product.

9. The device according to any one of claims 6 to 8, characterized in that A sum of usages of the first cloud service product considered in a plurality of saving plans of the saving plan combination is equal to the usage of the first cloud service product.

10. The device according to any one of claims 6 to 9, characterized in that The feedback module is also used for: The cost savings of the savings plan combination is fed back to the tenant, where the cost savings of the savings plan combination is the difference between the cost of purchasing the savings plan combination and the on-demand payment costs of the tenant's multiple cloud service products.

11. A computing device cluster, characterized in that: include: at least one computing device, each computing device comprising a processor and a memory; The processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method according to any one of claims 1 to 5.

12. A computer program product comprising instructions, characterized in that When the instructions are executed by a computing device cluster, the computing device cluster executes the method according to any one of claims 1 to 5.

13. A computer-readable storage medium, characterized in that: The method comprises computer program instructions, which, when executed by a computing device cluster, cause the computing device cluster to perform the method according to any one of claims 1 to 5.

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