Cloud management platform-based auto-scaling method and cloud management platform

Abstract

Disclosed in the present application are a cloud management platform-based auto-scaling method and a cloud management platform, which can improve the trust of tenants in the entire cloud service system, that is, improve the reliability of the entire cloud service system. The method of the present application comprises: when a tenant needs to perform auto-scaling for a scaling group thereof, a cloud management platform can receive, by means of a network interface, an auto-scaling formula input by the tenant for the scaling group, the auto-scaling formula comprising a variable for indicating the current load of the scaling group, a target load index of the scaling group and a sign of operation; then, the cloud management platform can acquire the current load index of the scaling group and substitute same into the variable for indicating the current load of the scaling group in the auto-scaling formula, thereby obtaining a target capacity of the scaling group; and finally, the cloud management platform can adjust the number of cloud instances comprised in the scaling group until the adjusted capacity of the scaling group is matched with the target capacity of the scaling group.

Description

An elastic scaling method based on cloud management platform and cloud management platform

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on September 20, 2023, with application number 202311224341.2 and application name “A capacity determination method based on a cloud management platform and a cloud management platform”, and claims priority to the Chinese patent application filed with the State Intellectual Property Office on January 9, 2024, with application number 202410032231.4 and application name “A elastic scaling method based on a cloud management platform and a cloud management platform”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to the field of cloud technology, and in particular to an elastic scaling method based on a cloud management platform and a cloud management platform. Background Art

[0003] Auto scaling (AS) technology is one of the cornerstones of cloud service systems. This technology can increase or decrease the number of cloud resources providing cloud services to tenants according to certain strategies, hoping to control the operating costs of the cloud service system by controlling the number of cloud resources while meeting the business needs of tenants.

[0004] Cloud service systems in related technologies include a cloud management platform and scaling groups created by the cloud management platform for tenants. These scaling groups typically contain cloud instances created by the cloud management platform for the tenants. When the scaling group runs a tenant's application, the cloud management platform determines the scaling group's target capacity based on the scaling group's capacity and pre-configured elastic scaling policies. The cloud management platform then adjusts the number of cloud instances in the scaling group until the adjusted scaling group capacity equals the target capacity.

[0005] In the above process, the elastic scaling policy is a black box to users. That is, users cannot determine how the cloud management platform obtains the target capacity of the scaling group. In other words, tenants cannot know the reasons for the adjustments performed by the cloud management platform on the scaling group. This leads to reduced trust in the entire cloud service system, which means that the reliability of the entire cloud service system is low.

[0006] Summary of the Invention

[0007] The embodiments of the present application provide an elastic scaling method and a cloud management platform based on a cloud management platform, which can improve tenants' trust in the entire cloud service system, that is, improve the reliability of the entire cloud service system.

[0008] A first aspect of an embodiment of the present application provides an elastic scaling method based on a cloud management platform, wherein the cloud management platform is used to manage an infrastructure that provides cloud services, wherein a scaling group of a tenant is configured in the infrastructure. The method includes:

[0009] When a tenant needs to use the cloud management platform to automatically scale a tenant's dedicated scaling group, the cloud management platform can provide the tenant with a network interface. The tenant can then send the scaling formula defined by the tenant for their dedicated scaling group to the network interface, allowing the cloud management platform to receive the scaling formula sent by the tenant through the network interface. The scaling formula can include a variable indicating the current load of the scaling group, a target load indicator for the scaling group, and an operator between the two.

[0010] After obtaining the elastic scaling formula defined by the tenant for its scaling group, the cloud management platform collects information about the scaling group to obtain the current load indicator of the scaling group. This information is then substituted into the variable representing the current load indicator in the elastic scaling formula to determine the target capacity of the scaling group. After determining the target capacity of the scaling group, the cloud management platform adjusts the number of cloud instances in the scaling group until the adjusted capacity matches the target capacity.

[0011] As can be seen from the above method, when a tenant needs to perform auto-scaling for their scaling group, the cloud management platform can provide a network interface to the tenant to receive the scaling formula for the scaling group input by the tenant. The scaling formula includes a variable indicating the current load of the scaling group, a target load indicator for the scaling group, and an operator. The variable indicating the current load of the scaling group, the target load indicator for the scaling group, and the operator are used to determine the target capacity of the scaling group. The cloud management platform then obtains the current load indicator of the scaling group and substitutes it into the variable indicating the current load of the scaling group in the scaling formula to obtain the target capacity of the scaling group. Finally, the cloud management platform adjusts the number of cloud instances in the scaling group until the adjusted scaling group capacity matches the target capacity of the scaling group. At this point, the cloud management platform automatically performs auto-scaling for the tenant's scaling group based on the scaling formula specified by the tenant. In the aforementioned process, the elastic scaling formula is defined by the tenant for their scaling group. That is, the content of the elastic scaling formula is set by the tenant. Therefore, the cloud management platform determines the target capacity of the scaling group based on the content of the elastic scaling formula. This process is deterministic for the tenant. In other words, the tenant can understand why and how the cloud management platform automatically elastically scales the scaling group. The elastic scaling operations performed by the cloud management platform on the scaling group are explainable to a certain extent, which can increase tenants' trust in the entire cloud service system, which is equivalent to improving the reliability of the entire cloud service system.

[0012] In one possible implementation, the scaling formula for a scaling group includes an expansion formula, and the target capacity of the scaling group is greater than the current capacity of the scaling group. In the aforementioned approach, when the scaling formula is an expansion formula, the target capacity of the scaling group derived from the scaling formula is typically greater than the current capacity of the scaling group. In other words, if the ratio between the current capacity of the scaling group and the target capacity of the scaling group is less than one, the cloud management platform needs to expand the capacity of the scaling group. Therefore, the cloud management platform adds additional cloud instances to the scaling group, resulting in an adjusted scaling group.

[0013] In one possible implementation, the scaling formula for a scaling group includes a scaling-in formula, and the target capacity of the scaling group is smaller than the current capacity of the scaling group. In the aforementioned implementation, when the scaling formula is a scaling-out formula, the target capacity of the scaling group derived from the scaling formula is typically larger than the current capacity of the scaling group. In other words, if the ratio between the current capacity of the scaling group and the target capacity of the scaling group is less than one, the cloud management platform needs to expand the capacity of the scaling group. Therefore, the cloud management platform adds additional cloud instances to the scaling group, resulting in an adjusted scaling group.

[0014] In one possible implementation, the cloud management platform obtains the current load indicator of the scaling group, substitutes the current load indicator into a variable, and confirms the target capacity of the scaling group according to the elastic scaling formula, including: the cloud management platform obtains the current load indicator of the scaling group, substitutes the current load indicator into a variable, and obtains the ratio between the current capacity of the scaling group and the target capacity of the scaling group; the cloud management platform calculates the current capacity of the scaling group and the ratio to obtain the target capacity of the scaling group. In the aforementioned implementation, the cloud management platform can collect information on the scaling group to obtain the current load indicator of the scaling group, substitute the current load indicator of the scaling group into the variable used to indicate the current load indicator in the elastic scaling formula, and obtain the ratio between the current capacity of the scaling group and the target capacity of the scaling group according to the elastic scaling formula. Then, the cloud management platform can calculate the current capacity of the scaling group and the ratio between the current capacity of the scaling group and the target capacity of the scaling group to obtain the target capacity of the scaling group.

[0015] In one possible implementation, the current load indicator includes at least one of the following: the current utilization rate of computing resources of cloud instances in the scaling group, the current utilization rate of storage resources of cloud instances in the scaling group, the current utilization rate of communication resources of cloud instances in the scaling group, the current request latency of cloud instances in the scaling group, and the current number of requests for cloud instances in the scaling group; the target load indicator of the scaling group includes at least one of the following: the target utilization rate of computing resources of cloud instances in the scaling group, the target utilization rate of storage resources of cloud instances in the scaling group, the target utilization rate of communication resources of cloud instances in the scaling group, the target request latency of cloud instances in the scaling group, and the target number of requests for cloud instances in the scaling group.

[0016] In one possible implementation, the current capacity of a scaling group includes at least one of the following: the current total amount of computing resources of the cloud instances in the scaling group, the current total amount of storage resources of the cloud instances in the scaling group, and the current total amount of communication resources of the cloud instances in the scaling group. The target load of a scaling group includes at least one of the following: the target total amount of computing resources of the cloud instances in the scaling group, the target total amount of storage resources of the cloud instances in the scaling group, and the target total amount of communication resources of the cloud instances in the scaling group.

[0017] In one possible implementation, the cloud instance in the scaling group can be any of the following: a physical server, a virtual machine, a micro virtual machine, a container, or a bare metal server.

[0018] A second aspect of an embodiment of the present application provides a cloud management platform, which is used to manage infrastructure that provides cloud services. The infrastructure is provided with a tenant's scaling group. The cloud management platform includes: a receiving module, which receives an elastic scaling formula for the scaling group input by the tenant through a network interface, the elastic scaling formula including a variable for indicating the current load of the scaling group, a target load indicator of the scaling group, and an operator. The variable, the target load indicator of the scaling group, and the operator are used to determine the target capacity of the scaling group; an acquisition module, which is used to obtain the current load indicator of the scaling group, substitute the current load indicator into the variable, and determine the target capacity of the scaling group according to the elastic scaling formula; and an adjustment module, which is used to adjust the scaling group according to the target capacity, so that the capacity of the adjusted scaling group matches the target capacity.

[0019] In one possible implementation, the elastic scaling formula of the scaling group includes a capacity expansion formula, and the target capacity of the scaling group is greater than the current capacity of the scaling group.

[0020] In one possible implementation, the elastic scaling formula of the scaling group includes a scaling-in formula, and the target capacity of the scaling group is smaller than the current capacity of the scaling group.

[0021] In one possible implementation, an acquisition module is configured to: obtain a current load indicator of a scaling group, substitute the current load indicator into a variable, and obtain a ratio of a current capacity of the scaling group to a target capacity of the scaling group; and calculate the current capacity of the scaling group and the ratio to obtain the target capacity of the scaling group.

[0022] In one possible implementation, the current load indicator includes at least one of the following: the current utilization rate of computing resources of cloud instances in the scaling group, the current utilization rate of storage resources of cloud instances in the scaling group, the current utilization rate of communication resources of cloud instances in the scaling group, the current request latency of cloud instances in the scaling group, and the current number of requests for cloud instances in the scaling group; the target load indicator of the scaling group includes at least one of the following: the target utilization rate of computing resources of cloud instances in the scaling group, the target utilization rate of storage resources of cloud instances in the scaling group, the target utilization rate of communication resources of cloud instances in the scaling group, the target request latency of cloud instances in the scaling group, and the target number of requests for cloud instances in the scaling group.

[0023] In one possible implementation, the current capacity of a scaling group includes at least one of the following: the current total amount of computing resources of the cloud instances in the scaling group, the current total amount of storage resources of the cloud instances in the scaling group, and the current total amount of communication resources of the cloud instances in the scaling group. The target load of a scaling group includes at least one of the following: the target total amount of computing resources of the cloud instances in the scaling group, the target total amount of storage resources of the cloud instances in the scaling group, and the target total amount of communication resources of the cloud instances in the scaling group.

[0024] In one possible implementation, the cloud instance in the scaling group can be any of the following: a physical server, a virtual machine, a micro virtual machine, a container, or a bare metal server.

[0025] A third aspect of an embodiment of the present application provides a computing device cluster, which includes at least one computing device, each computing device including a processor and a memory: the memory is used to store instructions; the processor is used to enable the computing device cluster to execute the method described in the first aspect or any possible implementation method of the first aspect according to the instructions.

[0026] A fourth aspect of an embodiment of the present application provides a computer storage medium storing one or more instructions, which, when executed by one or more computers, enables the one or more computers to implement the method described in the first aspect or any possible implementation method of the first aspect.

[0027] A fifth aspect of the embodiments of the present application provides a computer program product, which stores instructions. When the instructions are executed by a computer, the computer implements the method described in the first aspect or any possible implementation method of the first aspect.

[0028] In an embodiment of the present application, when a tenant needs to complete elastic scaling for its scaling group, the cloud management platform can provide a network interface to the tenant to receive the elastic scaling formula for the scaling group input by the tenant through the network interface. The elastic scaling formula includes a variable for indicating the current load of the scaling group, a target load indicator of the scaling group, and an operator. The variable for indicating the current load of the scaling group, the target load indicator of the scaling group, and the operator are used to determine the target capacity of the scaling group. Then, the cloud management platform can obtain the current load indicator of the scaling group and substitute it into the variable for indicating the current load of the scaling group in the elastic scaling formula to obtain the target capacity of the scaling group. Finally, the cloud management platform can adjust the number of cloud instances included in the scaling group until the adjusted scaling group capacity matches the target capacity of the scaling group. At this point, the cloud management platform can automatically complete the elastic scaling of the tenant's scaling group based on the elastic scaling formula formulated by the tenant. In the aforementioned process, the elastic scaling formula is defined by the tenant for their scaling group. That is, the content of the elastic scaling formula is set by the tenant. Therefore, the cloud management platform determines the target capacity of the scaling group based on the content of the elastic scaling formula. This process is deterministic for the tenant. In other words, the tenant can understand why and how the cloud management platform automatically elastically scales the scaling group. The elastic scaling operations performed by the cloud management platform on the scaling group are explainable to a certain extent, which can increase tenants' trust in the entire cloud service system, which is equivalent to improving the reliability of the entire cloud service system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] FIG1 is a schematic diagram of the structure of a cloud service system provided in an embodiment of the present application;

[0030] FIG2 is a flow chart of an elastic scaling method based on a cloud management platform provided in an embodiment of the present application;

[0031] FIG3 is a schematic diagram of a tenant interface provided in an embodiment of the present application;

[0032] FIG4 is another schematic diagram of a tenant interface provided in an embodiment of the present application;

[0033] FIG5 is a schematic diagram of expansion and contraction provided in an embodiment of the present application;

[0034] FIG6 is another flow chart of the elastic scaling method based on the cloud management platform provided in an embodiment of the present application;

[0035] FIG7 is another flow chart of an elastic scaling method based on a cloud management platform provided in an embodiment of the present application;

[0036] FIG8 is a schematic diagram of the structure of a cloud management platform provided in an embodiment of the present application;

[0037] FIG9 is a schematic diagram of a structure of a computing device provided in an embodiment of the present application;

[0038] FIG10 is a schematic diagram of a structure of a computing device cluster provided in an embodiment of the present application;

[0039] FIG11 is a schematic diagram of computer devices in a computer cluster provided by an embodiment of the present application being connected via a network. DETAILED DESCRIPTION

[0040] The embodiments of the present application provide an elastic scaling method and a cloud management platform based on a cloud management platform, which can improve tenants' trust in the entire cloud service system, that is, improve the reliability of the entire cloud service system.

[0041] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, and this is merely a way of distinguishing the objects of the same attributes when describing them in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0042] Elastic scaling technology is one of the cornerstones of cloud service systems. This technology can increase or decrease the number of cloud resources providing cloud services to tenants according to certain strategies, hoping to control the operating costs of the cloud service system by controlling the number of cloud resources while meeting the business needs of tenants.

[0043] The cloud service system in the related art includes a cloud management platform and a scaling group created by the cloud management platform for tenants. The scaling group usually includes cloud instances created by the cloud management platform for tenants. When the scaling group is running the tenant's application, the cloud management platform can determine the target capacity of the scaling group based on the capacity of the scaling group and the preset elastic scaling policy. Then, the cloud management platform can adjust the number of cloud instances in the scaling group until the capacity of the adjusted scaling group is equal to the target capacity. For example, if the preset elastic scaling policy includes a maximum capacity and a minimum capacity, after the cloud management platform determines that the capacity of the scaling group is outside the interval formed by the maximum capacity and the minimum capacity, it can take a capacity in the interval as the target capacity and increase or decrease the cloud instances in the scaling group so that the capacity of the adjusted scaling group is equal to the target capacity.

[0044] In the above process, the elastic scaling policy is a black box to users. That is, users cannot determine how the cloud management platform obtains the target capacity of the scaling group. In other words, tenants cannot know the reasons for the adjustments performed by the cloud management platform on the scaling group. This leads to reduced trust in the entire cloud service system, which means that the reliability of the entire cloud service system is low.

[0045] To solve the above problems, an embodiment of the present application provides an elastic scaling method based on a cloud management platform. This method can be implemented through a cloud service system. FIG1 is a structural diagram of a cloud service system provided by an embodiment of the present application. As shown in FIG1 , the cloud service system includes an infrastructure that can provide cloud services and a cloud management platform that manages these infrastructures. The cloud management platform and the infrastructure are introduced separately below:

[0046] The cloud management platform can comprehensively manage all cloud instances in the entire cloud service system (for example, the cloud management platform can create a dedicated scaling group for a tenant, and the cloud instances contained in the scaling group are used to run the tenant's applications. For another example, the cloud management platform can also adjust the number of cloud instances contained in the tenant's scaling group, and the adjusted scaling group, etc.). It can also be open to tenants outside the system and respond to their requests. For example, the cloud management platform can provide various interfaces such as login interfaces and network interfaces for access by tenant clients (for example, the terminal device used by the tenant or the browser on the terminal device, etc.). Among them, the cloud management platform can authenticate the tenant's client through the login interface, and after successful authentication, the tenant's client can be allowed to log in to the cloud management platform. For another example, the cloud management platform can also send preset templates to the tenant's client through the network interface, so that the tenant's client can display the preset templates for the tenant to view and use, so that the tenant can formulate elastic scaling policies for its dedicated scaling group on its client and send the elastic scaling policies to the cloud management platform through the network interface. For example, the cloud management platform can also allow tenants to send their own elastic scaling formulas (i.e., elastic scaling policies) for their own scaling groups through a client via a network interface. Because elastic scaling formulas contain variables indicating the current load of the scaling group, the target load indicator for the scaling group, and an operator between the two, the cloud management platform can obtain the current load indicator of the scaling group and substitute it into the elastic scaling formula to determine the target capacity of the scaling group. In this way, the cloud management platform can adjust the number of cloud instances in the scaling group until the adjusted capacity of the scaling group matches the target capacity.

[0047] The infrastructure includes scaling groups created by the cloud management platform for tenants. A scaling group can contain one or more cloud instances. It should be noted that any cloud instance in a scaling group can be presented in a variety of ways. For example, the cloud instance can be a physical server designated by the cloud management platform, or a virtual machine (VM) created by the cloud management platform on a physical server using virtualization technology. Alternatively, the cloud instance can be a container (Docker) created by the cloud management platform on a physical server using virtualization technology. Alternatively, the cloud instance can be a microVM created by the cloud management platform on a physical server using virtualization technology. Alternatively, the cloud instance can be a container (Docker) created by the cloud management platform on a physical server using virtualization technology. Alternatively, the cloud instance can be a bare metal server designated by the cloud management platform, and so on.

[0048] Furthermore, if a tenant's scaling group contains multiple cloud instances, these multiple cloud instances can be set up at one or more sites. The sites can be presented in various forms. For example, one or more sites can be multiple regions in the infrastructure, or one or more sites can be multiple availability zones in the infrastructure, or one or more sites can be at least one edge site and at least one central cloud site in the infrastructure, and so on.

[0049] It should be noted that in an embodiment of the present application, the tenant can send the elastic scaling formula formulated for the scaling group to the cloud management platform, so that the cloud management platform can calculate the target capacity of the scaling group based on the elastic scaling formula, and then adjust the tenant's scaling group based on the target capacity to obtain the adjusted scaling group. It can be seen that in this case, the target capacity of the scaling group is calculated by the cloud management platform. If the tenant wants to protect its data security, the tenant (the client) or the tenant's cloud instance can also calculate the target capacity of the scaling group based on the elastic scaling formula, and then return the target capacity to the cloud management platform, so that the tenant's scaling group is adjusted based on the target capacity to obtain the adjusted scaling group. It can be seen that in both cases, the target capacity of the scaling group is no longer calculated by the cloud management platform, so the cloud management platform does not need to obtain the elastic scaling policy formulated by the tenant, which is conducive to ensuring the data security of the tenant.

[0050] It can be seen that there are three situations in the method provided in the embodiment of the present application. The following mainly introduces the first situation. Figure 2 is a flow chart of the elastic scaling method based on the cloud management platform provided in the embodiment of the present application. As shown in Figure 2, the method can be implemented by the cloud management platform in the cloud service system shown in Figure 1. The cloud management platform is used to manage the infrastructure that provides cloud services. The infrastructure includes a scaling group created by the cloud management platform for the tenant. The scaling group includes one or more cloud instances for running the tenant's application. The method includes:

[0051] 201. The cloud management platform receives an elastic scaling formula for a scaling group input by a tenant through a network interface. The elastic scaling formula includes a variable for indicating the current load of the scaling group, a target load indicator of the scaling group, and an operator. The variable, the target load indicator of the scaling group, and the operator are used to determine the target capacity of the scaling group.

[0052] In this embodiment, when a tenant needs to automatically scale a tenant-specific scaling group with the help of the cloud management platform, the cloud management platform can provide a network interface to the tenant's client (for example, the scaling policy input field and template display window on the tenant interface, etc.). Therefore, the tenant can send the scaling formula formulated by the tenant for its dedicated scaling group to the network interface through the client, so that the cloud management platform receives the scaling formula formulated by the tenant for its dedicated scaling group sent by the tenant's client through the network interface.

[0053] It should be noted that the initial elastic scaling formula formulated by the tenant for its exclusive scaling group may also include variables used to indicate the current load of the scaling group, variables used to indicate the target load of the scaling group, and an operator between the two, etc. Since the target load indicator of the scaling group is usually also formulated by the tenant, the tenant can directly substitute the target load indicator of the scaling group into the initial elastic scaling formula to obtain the elastic scaling formula formulated by the tenant for its exclusive scaling group. The elastic scaling formula may include variables used to indicate the current load of the scaling group, the target load indicator of the scaling group, and an operator between the two, etc.

[0054] The current load indicator of a scaling group may include one or more of the following: the current utilization of computing resources (e.g., CPU, GPU, etc.) of all cloud instances in the scaling group; the current utilization of storage resources (e.g., memory, hard disk, etc.) of all cloud instances in the scaling group; the current utilization of communication resources (e.g., network bandwidth, etc.) of all cloud instances in the scaling group; the current request latency of all cloud instances in the scaling group; the current number of requests for all cloud instances in the scaling group; etc. Similarly, the target load indicator of a scaling group may include one or more of the following: the target utilization of computing resources of all cloud instances in the scaling group; the target utilization of storage resources of all cloud instances in the scaling group; the target utilization of communication resources of all cloud instances in the scaling group; the target request latency of all cloud instances in the scaling group; the target number of requests for all cloud instances in the scaling group; etc.

[0055] For example, as shown in FIG3 ( FIG3 is a schematic diagram of a tenant interface provided in an embodiment of the present application), when a tenant needs to formulate an elastic scaling policy for its scaling group, the tenant can first log in to the cloud management platform and enter the following initial elastic scaling formula formulated by the tenant for its scaling group in the elastic scaling formula input field of the tenant interface provided by the cloud management platform:

[0056] Based on the tenant's customized initial auto-scaling formula, it's clear that the tenant wants the cloud management platform to adjust the scaling group's capacity exponentially when expanding or shrinking it. Furthermore, the tenant defines an initial auto-scaling formula that includes the variables "current" and "target." "Current" represents the scaling group's current load, and "target" represents the scaling group's target load. The auto-scaling formula includes operators such as the multiplication sign "*," the division sign " / ," and the sqrt sign. If the tenant also customizes the scaling group's target load to 60%, the tenant can replace "target" with 60% to obtain the final auto-scaling formula. This way, the cloud management platform receives the tenant's final auto-scaling formula for the scaling group through the auto-scaling formula input field.

[0057] Specifically, before sending the elastic scaling formula to the cloud management platform, the tenant can customize the elastic scaling formula in the following ways:

[0058] When a tenant needs to formulate an elastic scaling formula for its scaling group, the cloud management platform can provide a network interface to the tenant's client. The network interface can display preset formula templates to the tenant. These formula templates can contain multiple preset variables and multiple preset operators. After browsing these formula templates, the tenant can select certain variables (variables used to indicate the current load of the scaling group and variables used to indicate the target load of the scaling group, etc.), certain operators and / or certain operation functions from the preset multiple variables and multiple operators to establish mathematical relationships between these variables to generate the initial elastic scaling formula customized by the tenant for the scaling group. In addition, the tenant can also customize the target load index of the scaling group and substitute the target load index of the scaling group into the variable used to indicate the target load of the scaling group in the initial elastic scaling formula to obtain the elastic scaling formula customized by the tenant for the scaling group, and send the elastic scaling formula customized by the tenant for the scaling group to the cloud management platform via the network interface.

[0059] It should be noted that the pre-set variables and operators can be set in advance by the tenant or by the administrator of the cloud management platform, with no restrictions here. Regardless of whether the tenant or the administrator sets them, these variables and operators are set according to certain rules agreed upon by the tenant and the administrator, so both the tenant's client and the cloud management platform can recognize and transmit these variables and operators.

[0060] For example, as shown in Figure 4 (Figure 4 is another schematic diagram of the tenant interface provided in an embodiment of the present application, and Figure 4 is drawn based on Figure 3), after the tenant logs in to the cloud management platform, the cloud management platform can provide the tenant with a template display window of the tenant interface. The template display window displays multiple preset variables such as "current" and "target", and also displays multiple preset operation symbols such as "+", "-", "*", " / ", "sum" and "sqrt". After browsing the content displayed in the template display window, the tenant can select from it and enter the selected "current", "target", "*", " / " and "sqrt" into the elastic scaling formula input bar to edit it into the initial elastic scaling formula formulated by the tenant for its scaling group, and substitute the target load indicator of the scaling group to obtain the final elastic scaling formula formulated by the tenant for its scaling group. In this way, the cloud management platform can receive the final elastic scaling formula formulated by the tenant for its scaling group through the elastic scaling formula input bar.

[0061] It should be understood that the usage rate involved in this embodiment can be understood as the usage rate at the current moment or the usage rate at a certain moment in the future, etc. The target usage rate involved in this embodiment can be understood as the maximum usage rate set by the tenant, etc. Similarly, the request delay involved in this embodiment can be understood as the request delay at the current moment or the request delay at a certain moment in the future, etc., and the target request delay involved in this embodiment can be understood as the maximum request delay set by the tenant, etc. Similarly, the number of requests involved in this embodiment can be understood as the request delay at the current moment or the number of requests at a certain moment in the future, etc., and the target number of requests involved in this embodiment can be understood as the maximum number of requests set by the tenant, etc.

[0062] It should also be understood that in this embodiment, the example shown in Figure 3 is a schematic introduction using the formula in the elastic scaling formula as containing parameters, operation symbols and operation functions. In actual applications, the formula in the elastic scaling formula may also only contain parameters and operation symbols, or the formula in the elastic scaling formula may also only contain parameters and operation functions, etc., and there is no limitation here.

[0063] 202. The cloud management platform obtains the current load indicator of the scaling group, substitutes the current load indicator into the variable, and determines the target capacity of the scaling group according to the elastic scaling formula.

[0064] After obtaining the elastic scaling formula defined by the tenant for its scaling group, the cloud management platform collects information about the scaling group to obtain the scaling group's current load indicator. This information is then substituted into the variable in the elastic scaling formula that indicates the current load indicator, thereby determining the scaling group's target capacity. Generally, when the elastic scaling formula is used for expansion, the resulting target capacity is typically greater than the scaling group's current capacity. When the elastic scaling formula is used for reduction, the resulting target capacity is typically less than the scaling group's current capacity.

[0065] The current capacity of a scaling group may include one or more of the following: the current total amount of computing resources of all cloud instances in the scaling group, the current total amount of storage resources of all cloud instances in the scaling group, and the current total amount of communication resources of all cloud instances in the scaling group. Similarly, the target load of a scaling group may include one or more of the following: the target total amount of computing resources of all cloud instances in the scaling group, the target total amount of storage resources of all cloud instances in the scaling group, and the target total amount of communication resources of all cloud instances in the scaling group.

[0066] Specifically, the cloud management platform can obtain the target capacity of the scaling group through the following methods:

[0067] The cloud management platform obtains the current load indicator of the scaling group, substitutes it into the variable indicating the current load indicator in the elastic scaling formula, and uses the elastic scaling formula to calculate the ratio between the scaling group's current capacity and the scaling group's target capacity. The cloud management platform then calculates the scaling group's current capacity and the ratio between the scaling group's current capacity and the scaling group's target capacity to determine the scaling group's target capacity.

[0068] Continuing with the above example, assume the scaling group has four cloud instances, and the capacity of one cloud instance is considered to be 1, so the current capacity of the scaling group is 4. The current load of the scaling group is 90%, and the target load of the scaling group is 60%. Based on the elastic scaling formula specified by the tenant, the cloud management platform can perform the following calculation: (90% / 60%) * (90% / 60%) = 2.25. In this case, 2.25 can be considered the ratio between the scaling group's target capacity and the scaling group's current capacity. After determining that the ratio between the scaling group's target capacity and the scaling group's current capacity is 2.25, the cloud management platform can perform the following calculation: 2.25 * 4 = 9. At this point, the cloud management platform can determine that the scaling group's target capacity is 9.

[0069] It should be understood that the current capacity involved in this embodiment can be understood as the capacity at the current moment, and the target capacity involved in this embodiment can be understood as the ideal capacity obtained by the cloud management platform according to the needs of the tenants.

[0070] 203. The cloud management platform adjusts the scaling group based on the target capacity, so that the capacity of the adjusted scaling group matches the target capacity.

[0071] After obtaining the target capacity of the scaling group, the cloud management platform can adjust the number of cloud instances included in the scaling group until the capacity of the adjusted scaling group matches the target capacity of the scaling group. Generally, if the ratio between the current capacity of the scaling group and the target capacity of the scaling group is less than one, it means that the cloud management platform needs to expand the scaling group. The cloud management platform then adds additional cloud instances to the scaling group, thereby obtaining an adjusted scaling group. If the ratio between the current capacity of the scaling group and the target capacity of the scaling group is greater than one, it means that the cloud management platform needs to shrink the scaling group. The cloud management platform then reduces some cloud instances in the scaling group, thereby obtaining an adjusted scaling group. At this point, the cloud management platform automatically completes the elastic scaling of the tenant's scaling group based on the elastic scaling formula formulated by the tenant (that is, expansion and contraction, because the cloud instances of the adjusted scaling group increase or decrease relative to the cloud instances of the original scaling group, the capacity of the adjusted scaling group also increases or decreases accordingly relative to the capacity of the original scaling group).

[0072] For example, as shown in Figure 5 (Figure 5 is a schematic diagram of scaling provided in an embodiment of the present application, and Figure 5 is drawn based on Figure 4), after obtaining the target capacity of the scaling group as 9, the cloud management platform can create 5 additional cloud instances for the tenant's scaling group. At this time, the adjusted scaling group contains 9 cloud instances, and the adjusted current capacity of the scaling group is 9, reaching the target capacity.

[0073] It should be understood that in this embodiment, the cloud management platform is only used as a tenant for illustrative purposes, and does not limit the specific types of objects. In actual applications, the cloud management platform can also target the internal systems of cloud vendors (for example, cloud vendor staff, etc.), etc., and this is not limited here.

[0074] In an embodiment of the present application, when a tenant needs to complete elastic scaling for its scaling group, the cloud management platform can provide a network interface to the tenant to receive the elastic scaling formula for the scaling group input by the tenant through the network interface. The elastic scaling formula includes a variable for indicating the current load of the scaling group, a target load indicator of the scaling group, and an operator. The variable for indicating the current load of the scaling group, the target load indicator of the scaling group, and the operator are used to determine the target capacity of the scaling group. Then, the cloud management platform can obtain the current load indicator of the scaling group and substitute it into the variable for indicating the current load of the scaling group in the elastic scaling formula to obtain the target capacity of the scaling group. Finally, the cloud management platform can adjust the number of cloud instances included in the scaling group until the adjusted scaling group capacity matches the target capacity of the scaling group. At this point, the cloud management platform can automatically complete the elastic scaling of the tenant's scaling group based on the elastic scaling formula formulated by the tenant. In the aforementioned process, the elastic scaling formula is defined by the tenant for their scaling group. That is, the content of the elastic scaling formula is set by the tenant. Therefore, the cloud management platform determines the target capacity of the scaling group based on the content of the elastic scaling formula. This process is deterministic for the tenant. In other words, the tenant can understand why and how the cloud management platform automatically elastically scales the scaling group. The elastic scaling operations performed by the cloud management platform on the scaling group are explainable to a certain extent, which can increase tenants' trust in the entire cloud service system, which is equivalent to improving the reliability of the entire cloud service system.

[0075] Furthermore, in an embodiment of the present application, the cloud management platform provides tenants with a customized network interface. Tenants can customize exclusive elastic scaling formulas for their scaling groups based on their own service quality requirements, so that the cloud management platform can adjust the capacity of the scaling group accordingly based on the content of the elastic scaling formula. In this way, the capacity of the adjusted scaling group can match the service quality expected by the tenant, thereby achieving an improvement in service quality.

[0076] The above is a detailed description of the first case of the method provided in the embodiment of the present application. The second case of the method provided in the embodiment of the present application will be introduced below. Figure 6 is another flow chart of the elastic scaling method based on the cloud management platform provided in the embodiment of the present application. As shown in Figure 6, the method can be implemented by the cloud management platform in the cloud service system shown in Figure 1. The cloud management platform is used to manage the infrastructure that provides cloud services. The infrastructure includes a scaling group created by the cloud management platform for the tenant. The scaling group contains one or more cloud instances for running the tenant's application. The method includes:

[0077] 601. The cloud management platform sends the current load indicator and current capacity of the scaling group to the tenant through the processing interface provided by the tenant.

[0078] 602. The cloud management platform receives the target capacity of the scaling group sent by the tenant through a processing interface. The target capacity is obtained by processing the current load indicator of the scaling group, the target load indicator of the scaling group, and the current capacity of the scaling group based on a preset elastic scaling formula.

[0079] In this embodiment, when a tenant needs to perform elastic scaling on their dedicated scaling group with the help of the cloud management platform, they can deploy the elastic scaling formula they have defined for the scaling group on their client and have the terminal provide a processing interface to the cloud management platform. The elastic scaling formula they have defined for the scaling group can be deployed in the tenant's client as a plug-in, and the tenant's client is configured with a processing interface corresponding to the plug-in (e.g., a representational state transfer (REST) ​​interface, etc.), which is accessible to the cloud management platform.

[0080] Because the elastic scaling formula defined by the tenant for the scaling group includes a variable for indicating the current load indicator of the scaling group, the target load indicator of the scaling group, and an operation symbol, the cloud management platform can send the current load indicator of the scaling group and the current capacity of the scaling group to the processing interface provided by the tenant's client, so that the tenant's client receives the current load indicator of the scaling group and the current capacity of the scaling group sent by the cloud management platform through the processing interface.

[0081] The tenant's client can then substitute the current load indicator of the scaling group into the variable indicating the current load indicator in the elastic scaling formula to obtain the target capacity of the scaling group, and send the target capacity of the scaling group to the cloud management platform through the processing interface.

[0082] It should be understood that in this embodiment, the introduction to the elastic scaling formula and the calculation process of the target capacity of the scaling group can be referred to the relevant description part of the embodiment shown in Figure 2, and will not be repeated here.

[0083] 603. The cloud management platform adjusts the number of cloud instances included in the scaling group to obtain an adjusted scaling group, where the capacity of the adjusted scaling group matches the target capacity.

[0084] After obtaining the target capacity of the scaling group, the cloud management platform can adjust the number of cloud instances included in the scaling group until the adjusted capacity of the scaling group matches the scaling group's target capacity. Generally, if the ratio between the scaling group's current capacity and the scaling group's target capacity is less than one, it indicates that the cloud management platform needs to expand the scaling group. The cloud management platform then adds additional cloud instances to the scaling group, resulting in an adjusted scaling group. If the ratio between the scaling group's current capacity and the scaling group's target capacity is greater than one, it indicates that the cloud management platform needs to reduce the scaling group. The cloud management platform then removes some cloud instances from the scaling group, resulting in an adjusted scaling group. At this point, the cloud management platform automatically completes the elastic scaling of the tenant's scaling group based on the elastic scaling formula defined by the tenant.

[0085] In the embodiments of the present application, the elastic scaling formula is established by the tenant for its scaling group. That is, the content of the elastic scaling formula is set by the tenant. Therefore, after the cloud management platform provides the scaling group data required by the policy, the tenant can independently determine the target capacity of the scaling group based on the content of the elastic scaling formula and submit the target capacity of the scaling group to the cloud management platform, so that the cloud management platform can perform elastic scaling for the scaling group. During this process, the elastic scaling formula established by the tenant for the scaling group remains on the tenant's side, and the cloud management platform does not obtain any information related to the elastic scaling formula. This effectively ensures the confidentiality of the tenant's policy while enabling the elastic scaling of the scaling group with the help of the cloud management platform.

[0086] The above is a detailed description of the second case of the method provided in the embodiment of the present application. The third case of the method provided in the embodiment of the present application will be introduced below. Figure 7 is another flow chart of the elastic scaling method based on the cloud management platform provided in the embodiment of the present application. As shown in Figure 7, the method can be implemented by the cloud management platform in the cloud service system shown in Figure 1. The cloud management platform is used to manage the infrastructure for providing cloud services. The infrastructure includes the scaling group and the target cloud instance created by the cloud management platform for the tenant. The scaling group contains one or more cloud instances for running the tenant's application. The target cloud instance contains the elastic scaling formula and processing interface formulated by the tenant for the scaling group. The method includes:

[0087] 701. The cloud management platform sends the current load indicator and the current capacity of the scaling group to the target cloud instance through the processing interface.

[0088] 702. The cloud management platform receives the target capacity of the scaling group sent by the target cloud instance through a processing interface. The target capacity is obtained by the target cloud instance processing the current load indicator of the scaling group, the target load indicator of the scaling group, and the current capacity of the scaling group based on a preset elastic scaling formula.

[0089] In this embodiment, when a tenant needs to use the cloud management platform to elastically scale its dedicated scaling group, the tenant can ask the cloud management platform to create a dedicated target cloud instance for it, and deploy the elastic scaling formula formulated by the tenant for the scaling group and the processing interface for the cloud management platform in the target cloud instance. Among them, the elastic scaling formula formulated by the tenant for the scaling group can be deployed in the target cloud instance in the form of a plug-in, and the target cloud instance is configured with a processing interface corresponding to the plug-in (for example, a REST interface, etc.), and the processing interface is accessible to the cloud management platform. Generally, the tenant's target cloud instance is isolated from the tenant's scaling group (for example, logical isolation or physical isolation, etc.).

[0090] Because the elastic scaling formula defined by the tenant for the scaling group contains a variable used to indicate the current load indicator of the scaling group, the target load indicator of the scaling group, and an operation symbol, the cloud management platform can send the current load indicator of the scaling group and the current capacity of the scaling group to the processing interface provided by the target cloud instance, so that the target cloud instance receives the current load indicator of the scaling group and the current capacity of the scaling group sent by the cloud management platform through the processing interface.

[0091] The target cloud instance can then substitute the current load indicator of the scaling group into the variable indicating the current load indicator in the elastic scaling formula to obtain the target capacity of the scaling group, and send the target capacity of the scaling group to the cloud management platform through the processing interface.

[0092] It should be understood that in this embodiment, the introduction to the elastic scaling formula and the calculation process of the target capacity of the scaling group can be referred to the relevant description part of the embodiment shown in Figure 2, and will not be repeated here.

[0093] 703. The cloud management platform adjusts the number of cloud instances included in the scaling group to obtain an adjusted scaling group, where the capacity of the adjusted scaling group matches the target capacity.

[0094] After obtaining the target capacity of the scaling group, the cloud management platform can adjust the number of cloud instances included in the scaling group until the adjusted capacity of the scaling group matches the scaling group's target capacity. Generally, if the ratio between the scaling group's current capacity and the scaling group's target capacity is less than one, it indicates that the cloud management platform needs to expand the scaling group. The cloud management platform then adds additional cloud instances to the scaling group, resulting in an adjusted scaling group. If the ratio between the scaling group's current capacity and the scaling group's target capacity is greater than one, it indicates that the cloud management platform needs to reduce the scaling group. The cloud management platform then removes some cloud instances from the scaling group, resulting in an adjusted scaling group. At this point, the cloud management platform automatically completes the elastic scaling of the tenant's scaling group based on the elastic scaling formula defined by the tenant.

[0095] In the embodiment of the present application, the elastic scaling formula is formulated by the tenant for its scaling group, that is, the content of the elastic scaling formula is set by the tenant. Therefore, after the cloud management platform provides the data of the scaling group required by the policy, the tenant's target cloud instance can determine the target capacity of the scaling group based on the content of the elastic scaling formula and submit the target capacity of the scaling group to the cloud management platform, so that the cloud management platform can complete elastic scaling for the scaling group. During this process, the elastic scaling formula formulated by the tenant for the scaling group remains in the tenant's target cloud instance, and the cloud management platform generally does not obtain any information related to the elastic scaling formula. In this way, on the basis of completing the elastic scaling of the scaling group with the help of the cloud management platform, the confidentiality of the policy formulated by the tenant can be guaranteed to a certain extent.

[0096] The above is a detailed description of the elastic scaling method based on the cloud management platform provided in the embodiment of the present application. The cloud management platform provided in the embodiment of the present application will be introduced below. Figure 8 is a structural diagram of the cloud management platform provided in the embodiment of the present application. As shown in Figure 8, the cloud management platform is used to manage the infrastructure that provides cloud services. The infrastructure includes a tenant's scaling group. The cloud instance included in the scaling group is used to run the tenant's application. The cloud management platform includes:

[0097] Receiving module 801 receives, through a network interface, an elastic scaling formula for a scaling group input by a tenant. The elastic scaling formula includes a variable indicating the current load of the scaling group, a target load indicator for the scaling group, and an operator. The variable, the target load indicator for the scaling group, and the operator are used to determine the target capacity of the scaling group. For example, receiving module 801 is used to implement step 201 in the embodiment shown in FIG. 2 .

[0098] The acquisition module 802 is used to obtain the current load index of the scaling group, substitute the current load index into the variable, and determine the target capacity of the scaling group according to the elastic scaling formula; for example, the acquisition module 802 is used to implement step 202 in the embodiment shown in Figure 2.

[0099] The adjustment module 803 is configured to adjust the scaling group according to the target capacity so that the capacity of the scaling group after adjustment matches the target capacity. For example, the adjustment module 803 is configured to implement step 203 in the embodiment shown in FIG2 .

[0100] In one possible implementation, the elastic scaling formula of the scaling group includes a capacity expansion formula, and the target capacity of the scaling group is greater than the current capacity of the scaling group.

[0101] In one possible implementation, the elastic scaling formula of the scaling group includes a scaling-in formula, and the target capacity of the scaling group is smaller than the current capacity of the scaling group.

[0102] In one possible implementation, an acquisition module is configured to: obtain a current load indicator of a scaling group, substitute the current load indicator into a variable, and obtain a ratio of the current capacity of the scaling group to a target capacity of the scaling group; and calculate the current capacity of the scaling group and the ratio to obtain the target capacity of the scaling group.

[0103] In one possible implementation, the current load indicator includes at least one of the following: the current utilization rate of computing resources of cloud instances in the scaling group, the current utilization rate of storage resources of cloud instances in the scaling group, the current utilization rate of communication resources of cloud instances in the scaling group, the current request latency of cloud instances in the scaling group, and the current number of requests for cloud instances in the scaling group; the target load indicator of the scaling group includes at least one of the following: the target utilization rate of computing resources of cloud instances in the scaling group, the target utilization rate of storage resources of cloud instances in the scaling group, the target utilization rate of communication resources of cloud instances in the scaling group, the target request latency of cloud instances in the scaling group, and the target number of requests for cloud instances in the scaling group.

[0104] In one possible implementation, the current capacity of a scaling group includes at least one of the following: the current total amount of computing resources of the cloud instances in the scaling group, the current total amount of storage resources of the cloud instances in the scaling group, and the current total amount of communication resources of the cloud instances in the scaling group. The target load of a scaling group includes at least one of the following: the target total amount of computing resources of the cloud instances in the scaling group, the target total amount of storage resources of the cloud instances in the scaling group, and the target total amount of communication resources of the cloud instances in the scaling group.

[0105] In one possible implementation, the cloud instance in the scaling group can be any of the following: a physical server, a virtual machine, a micro virtual machine, a container, or a bare metal server.

[0106] It should be noted that the information interaction, implementation process, etc. between the modules / units of the above-mentioned device are based on the same concept as the method embodiment of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown above in the embodiment of the present application, and no further details will be given here.

[0107] Please refer to Figure 9, which is a schematic diagram of the structure of a computing device provided in an embodiment of the present application. As shown in Figure 9, the computing device 900 (which can be used to present the aforementioned cloud management platform) includes: a processor 901, a memory 902, a communication interface 903, and a bus 904. The processor 901, the memory 902, and the communication interface 903 are coupled via a bus (not labeled in the figure). The memory 902 stores instructions. When the execution instructions in the memory 902 are executed, the computing device 900 executes the method executed by the cloud management platform in the above method embodiment.

[0108] The computing device 900 may be one or more integrated circuits configured to implement the above method, such as one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms. For example, when a unit in the apparatus can be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For example, these units may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0109] The processor 901 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0110] The memory 902 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0111] Memory 902 stores executable program code. Processor 901 executes the executable program code to implement the functions of the aforementioned receiving module, acquisition module, and adjustment module, thereby implementing the aforementioned elastic scaling method based on the cloud management platform. In other words, memory 902 stores instructions for executing the aforementioned elastic scaling method based on the cloud management platform.

[0112] The communication interface 903 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 900 and other devices or a communication network.

[0113] In addition to the data bus, bus 904 may also include a power bus, a control bus, and a status signal bus. The bus may be a Peripheral Component Interconnect Express (PCIe) bus, an Extended Industry Standard Architecture (EISA) bus, a unified bus (Ubus or UB), a Compute Express Link (CXL), or a Cache Coherent Interconnect for Accelerators (CCIX). Buses can be categorized as address buses, data buses, and control buses.

[0114] Please refer to Figure 10 , which is a schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application. As shown in Figure 10 , the computing device cluster 1000 includes at least one computing device 900 .

[0115] As shown in Figure 10, the computing device cluster 1000 includes at least one computing device 900. The memory 902 in one or more computing devices 900 in the computing device cluster 1000 may store the same instructions for executing the above-mentioned elastic scaling method based on the cloud management platform.

[0116] In some possible implementations, the memory 902 of one or more computing devices 900 in the computing device cluster 1000 may also store partial instructions for executing the aforementioned elastic scaling method based on the cloud management platform. In other words, the combination of one or more computing devices 900 can jointly execute the aforementioned elastic scaling method based on the cloud management platform.

[0117] It should be noted that the memory 902 in different computing devices 900 in the computing device cluster 1000 may store different instructions, each for executing a portion of the functions of the aforementioned cloud management platform. In other words, the instructions stored in the memory 902 in different computing devices 900 may implement the functions of one or more modules among the receiving module, the obtaining module, and the adjusting module.

[0118] In some possible implementations, one or more computing devices 900 in the computing device cluster 1000 may be connected via a network, which may be a wide area network or a local area network.

[0119] Please refer to Figure 11, which is a schematic diagram of computer devices in a computer cluster provided by an embodiment of the present application being connected via a network. As shown in Figure 11, two computing devices 900A and 900B are connected via a network. Specifically, each computing device is connected to the network via a communication interface.

[0120] In one possible implementation, the memory of computing device 900A stores instructions for executing the functions of a receiving module, etc., while the memory of computing device 900B stores instructions for executing the functions of an acquisition module, an adjustment module, etc. Alternatively, the memory of computing device 900A stores instructions for executing the functions of a receiving module, etc., while the memory of computing device 900B stores instructions for executing the functions of an adjustment module, etc., which is not shown in the figure.

[0121] It should be understood that the functions of the computing device 900A shown in Figure 11 may also be completed by multiple computing devices. Similarly, the functions of the computing device 900B may also be completed by multiple computing devices.

[0122] An embodiment of the present application also relates to a computer storage medium, which stores a program for signal processing. When the computer storage medium runs on a computer, it enables the computer to execute the steps executed by the cloud management platform in the embodiment shown in Figure 2, Figure 6 or Figure 7.

[0123] An embodiment of the present application also relates to a computer program product, which stores instructions that, when executed by a computer, enable the computer to execute the steps performed by the cloud management platform in the embodiment shown in Figure 2, Figure 6 or Figure 7.

[0124] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0125] In the several embodiments provided in this 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 merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0127] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0128] If the integrated unit 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 is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. An elastic scaling method based on a cloud management platform, characterized in that: The cloud management platform is used to manage an infrastructure that provides cloud services, wherein a scaling group of a tenant is provided in the infrastructure, and the method includes: The cloud management platform receives, through a network interface, an elastic scaling formula for the scaling group input by the tenant, where the elastic scaling formula includes a variable for indicating a current load of the scaling group, a target load index of the scaling group, and an operation symbol, and the variable, the target load index of the scaling group, and the operation symbol are used to determine a target capacity of the scaling group; The cloud management platform obtains a current load indicator of the scaling group, substitutes the current load indicator into the variable, and determines a target capacity of the scaling group according to the elastic scaling formula; The cloud management platform adjusts the scaling group according to the target capacity, so that the capacity of the adjusted scaling group matches the target capacity.

2. The method according to claim 1, characterized in that The elastic scaling formula of the scaling group includes a capacity expansion formula, and the target capacity of the scaling group is greater than the current capacity of the scaling group.

3. The method according to claim 1, characterized in that The elastic scaling formula of the scaling group includes a shrinking formula, and the target capacity of the scaling group is smaller than the current capacity of the scaling group.

4. The method according to any one of claims 1 to 3, characterized in that: The cloud management platform obtains the current load index of the scaling group, substitutes the current load index into the variable, and determines the target capacity of the scaling group according to the elastic scaling formula, including: The cloud management platform obtains a current load indicator of the scaling group, substitutes the current load indicator into the variable, and obtains a ratio between the current capacity of the scaling group and the target capacity of the scaling group; The cloud management platform calculates the current capacity of the scaling group and the ratio to obtain a target capacity of the scaling group.

5. The method according to any one of claims 1 to 4, characterized in that: The current load indicator includes at least one of the following: current usage rate of computing resources of the cloud instances in the scaling group, current usage rate of storage resources of the cloud instances in the scaling group, current usage rate of communication resources of the cloud instances in the scaling group, current request latency of the cloud instances in the scaling group, and current number of requests of the cloud instances in the scaling group; The target load indicator of the scaling group includes at least one of the following: a target utilization rate of computing resources of the cloud instances in the scaling group, a target utilization rate of storage resources of the cloud instances in the scaling group, a target utilization rate of communication resources of the cloud instances in the scaling group, a target request latency of the cloud instances in the scaling group, and a target number of requests for the cloud instances in the scaling group.

6. The method according to any one of claims 1 to 5, characterized in that: The current capacity of the scaling group includes at least one of the following: the current total amount of computing resources of the cloud instances in the scaling group, the current total amount of storage resources of the cloud instances in the scaling group, and the current total amount of communication resources of the cloud instances in the scaling group; The target load of the scaling group includes at least one of the following: a target total amount of computing resources of the cloud instances in the scaling group, a target total amount of storage resources of the cloud instances in the scaling group, and a target total amount of communication resources of the cloud instances in the scaling group.

7. The method according to any one of claims 1 to 6, characterized in that: The cloud instance in the scaling group is any of the following: a physical server, a virtual machine, a micro virtual machine, a container, and a bare metal server.

8. A cloud management platform, characterized in that: The cloud management platform is used to manage the infrastructure that provides cloud services, wherein the infrastructure is provided with a tenant's scaling group, and the cloud management platform includes: a receiving module, receiving, through a network interface, an elastic scaling formula for the scaling group input by the tenant, the elastic scaling formula including a variable for indicating a current load of the scaling group, a target load index of the scaling group, and an operation symbol, wherein the variable, the target load index of the scaling group, and the operation symbol are used to determine a target capacity of the scaling group; an acquisition module, configured to acquire a current load indicator of the scaling group, substitute the current load indicator into the variable, and determine a target capacity of the scaling group according to the elastic scaling formula; The adjustment module is configured to adjust the scaling group according to the target capacity, so that the capacity of the scaling group after adjustment matches the target capacity.

9. The cloud management platform according to claim 8, characterized in that: The elastic scaling formula of the scaling group includes a capacity expansion formula, and the target capacity of the scaling group is greater than the current capacity of the scaling group.

10. The cloud management platform according to claim 8, characterized in that: The elastic scaling formula of the scaling group includes a shrinking formula, and the target capacity of the scaling group is smaller than the current capacity of the scaling group.

11. The cloud management platform according to any one of claims 8 to 10, characterized in that: The acquisition module is used to: Get the current load index of the scaling group, substitute the current load index into the variable, and get the current capacity of the scaling group to a target capacity of the scaling group; The current capacity of the scaling group and the ratio are calculated to obtain a target capacity of the scaling group.

12. The cloud management platform according to any one of claims 8 to 11, characterized in that: The current load indicator includes at least one of the following: current usage rate of computing resources of the cloud instances in the scaling group, current usage rate of storage resources of the cloud instances in the scaling group, current usage rate of communication resources of the cloud instances in the scaling group, current request latency of the cloud instances in the scaling group, and current number of requests of the cloud instances in the scaling group; The target load indicator of the scaling group includes at least one of the following: a target utilization rate of computing resources of the cloud instances in the scaling group, a target utilization rate of storage resources of the cloud instances in the scaling group, a target utilization rate of communication resources of the cloud instances in the scaling group, a target request latency of the cloud instances in the scaling group, and a target number of requests for the cloud instances in the scaling group.

13. The cloud management platform according to any one of claims 8 to 12, characterized in that: The current capacity of the scaling group includes at least one of the following: the current total amount of computing resources of the cloud instances in the scaling group, the current total amount of storage resources of the cloud instances in the scaling group, and the current total amount of communication resources of the cloud instances in the scaling group; The target load of the scaling group includes at least one of the following: a target total amount of computing resources of the cloud instances in the scaling group, a target total amount of storage resources of the cloud instances in the scaling group, and a target total amount of communication resources of the cloud instances in the scaling group.

14. The cloud management platform according to any one of claims 8 to 13, characterized in that: The cloud instance in the scaling group is any of the following: a physical server, a virtual machine, a micro virtual machine, a container, and a bare metal server.

15. A computing device cluster, characterized in that: The computing device cluster includes at least one computing device, each computing device including a processor and a memory: The memory is used to store instructions; The processor is configured to cause the computing device cluster to execute the method according to any one of claims 1 to 7 according to the instructions.

16. A computer storage medium, characterized in that: The computer storage medium stores one or more instructions, which, when executed by one or more computers, enable the one or more computers to implement the method of any one of claims 1 to 7.

17. A computer program product, characterized in that The computer program product stores instructions, and when the instructions are executed by a computer, the computer implements the method according to any one of claims 1 to 7.

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