WO2025011247A9 - Method and apparatus for creating cloud service instance - Google Patents

Abstract

The present application relates to the field of computers, and provides a method and apparatus for creating a cloud service instance, aiming to improve the balance of utilization of computing resources in a hybrid resource pool and ensure stable resource expectation of various heterogeneous services deployed in the hybrid resource pool, thereby improving the anti-risk capability of the hybrid resource pool and reducing the operation costs. The method comprises: a cloud management platform receiving a service request of a tenant, wherein the service request is used for using computing resources in a physical resource pool to create a target cloud service instance, the physical resource pool is provided with a plurality of logical resource pools, the plurality of logical resource pools are used for providing different types of cloud service instances, and the proportions of computing resources required by the types of cloud service instances are different; in response to the service request, determining, from among the plurality of logical resource pools of the physical resource pool, a target logical resource pool matching the type of the target cloud service instance; and using computing resources in the target logical resource pool to create the target cloud service instance.

Description

A method and device for creating a cloud service instance

This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on July 10, 2023, with application number 202310840577.2, and invention name “A computing resource management method, device and computing device cluster”, and the Chinese patent application filed with the State Intellectual Property Office on November 9, 2023, with application number 202311489551.4, and invention name “A method and device for creating a cloud service instance”, all contents of which are incorporated by reference in this application.

Technical Field

The present application relates to the field of computers, and in particular to a method and device for creating a cloud service instance.

Background Art

In the field of cloud computing, the collection of various hardware and software involved in a cloud computing data center is called a resource pool, which is a logical abstraction for flexible resource management.

At present, cloud computing resource pools are mostly managed as a single resource pool (whether it is a public cloud operated by a cloud vendor or a customer's private cloud or exclusive cloud resource pool). As a result, cloud services are composed of multiple small resource pools. But in fact, the larger the resource pool, the stronger the risk resistance and resource efficiency, and the lower the cost. Through resource pool normalization technology, multiple resource pools that were originally operated and managed individually will be deployed in the same physical resource pool (mixed resource pool) for operation and management in the future, which has high commercial value.

In a single resource pool, the remaining available amount of a service can be simply obtained by subtracting the amount of resources that have been issued from the total computing resources in the resource pool. However, in a hybrid resource pool, since the resource pool can issue multiple types of services, it is impossible to assess how much resources the hybrid resource pool can issue to each type of service, resulting in unstable resource expectations for various services. This will also cause unbalanced utilization of computing resources in the hybrid resource pool and resource squeezes between heterogeneous services, ultimately leading to weak risk resistance and high operating costs for the hybrid resource pool.

Summary of the invention

The method and device for creating a cloud service instance provided in the present application improve the balance of computing resource utilization in a hybrid resource pool, ensure the stability of resource expectations of various heterogeneous services deployed in the hybrid resource pool, thereby improving the risk resistance of the hybrid resource pool and reducing operating costs.

In order to achieve the above-mentioned purpose, the embodiment of the present application adopts the following technical solution:

In a first aspect, a method for creating a cloud service instance is provided, which is applied to a cloud management platform, and the cloud management platform is used to manage the physical resource pool of a tenant. The method may include: the cloud management platform receives a service request from a tenant, and the service request is used to create a target cloud service instance using computing resources in a physical resource pool, and the physical resource pool is configured as a plurality of logical resource pools, and the plurality of logical resource pools are used to provide different types of cloud service instances, and each type of cloud service instance requires a different proportion of computing resources, and the computing resources include a central processing unit (CPU) and a memory; in response to the service request, a target logical resource pool matching the type of the target cloud service instance is determined from the plurality of logical resource pools of the physical resource pool; and the target cloud service instance is created using the computing resources in the target logical resource pool.

Through the solution provided by the present application, the physical resource pool is abstracted into multiple logical resource pools. One logical resource pool is used to provide one type of cloud service instance. The internal operation of the logical resource pool can be similar to that of a single unit. According to the amount of resources issued in the logical resource pool, it is possible to know how much computing resources can be issued to the corresponding type of cloud service instance, thereby ensuring the stability of resource expectations of each type of cloud service instance in the mixed resource pool. In the balanced consideration of the multi-dimensional setting configuration items, the number of computing resources allocated to each logical resource pool, and heterogeneous services corresponding to different logical resource pools, can ensure balanced utilization of computing resources in the mixed resource pool, avoiding resource runs between heterogeneous services. Therefore, the solution provided by the present application realizes the operation and management after heterogeneous services are deployed in a physical resource pool, improves the risk resistance of the resource pool, and reduces operating costs.

In a possible implementation, the method provided by the present application further includes: after a trigger condition is met, the cloud management platform adjusts the number of computing resources corresponding to at least one logical resource pool in the physical resource pool to increase the amount of cloud service instances of the first type that can be issued, where the first type of cloud service instance is a logical resource pool in the physical resource pool, any one of the different types of cloud service instances provided. Under the trigger condition, the computing resources contained in the logical resource pool are adjusted to improve the computing resource utilization of the physical resource pool.

In another possible implementation, the trigger condition includes one or more of the following: a preset time, a preset period, the available amount of the first type of cloud service instance is less than a first threshold, and the allocation rate of the second type of cloud service instance exceeds a second threshold. The second type of cloud service instance is a logical resource pool in a physical resource pool, and is any one of the different types of cloud service instances provided.

In another possible implementation, the method provided in the present application further includes: the cloud management platform receives the trigger conditions and capacity planning goals input by the tenant, and the capacity planning goals include: the maximum number of cloud service instances of the first type that can be issued.

In another possible implementation, after the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool. Specifically, it can be implemented as follows: after the trigger condition is met, the cloud management platform performs mathematical modeling and solves according to the capacity planning target to obtain a resource allocation plan; according to the obtained resource allocation plan, the number of computing resources allocated to at least one logical resource pool in the physical resource pool is adjusted. By establishing a mathematical model optimization solution, the resource allocation plan that best matches the capacity planning target is determined, so that the re-planning effect is better.

In another possible implementation, the method provided by the present application also includes: the cloud management platform receives capacity planning constraints input by the tenant, and the capacity planning constraints include one or more of the following: the number of physical hosts whose resource allocations are adjusted does not exceed the third threshold, and the change in the amount of cloud service instances of the third type that can be issued between two adjacent adjustments does not exceed the fourth threshold. Among them, the third type of cloud service instance is any one of the above-mentioned different types of cloud service instances. Accordingly, after the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool, including: after the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool according to the capacity planning constraints.

In another possible implementation, the method provided by the present application further includes: before the cloud management platform receives the service request, the cloud management platform receives the configuration items about the physical resource pool input by the tenant, the configuration items are used to indicate multiple logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool. Then, the cloud management platform configures the physical resource pool into multiple logical resource pools according to the configuration items.

In a possible implementation, the above configuration item is also used to indicate: the identifier of the physical machine corresponding to each logical resource pool in the physical resource pool. The tenant specifies the physical machine that provides computing resources to the logical resource pool, which improves the tenant experience.

In another possible implementation, the method provided by the present application further includes: providing a visualization interface, the visualization interface being used to display the values of the observation indicators of the physical resource pool and/or the values of the observation indicators of the multiple logical resource pools;

The observation indicators of the physical resource pool include one or more of the following indicators: the number of types of cloud service instances provided by the physical resource pool, the total amount of computing resources in the physical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources;

The observation indicators of the multiple logical resource pools include one or more of the following indicators: the total amount of computing resources in each logical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources.

In another possible implementation, the method provided in the present application further includes: receiving an add operation of a tenant, where the add operation is used to input an observation indicator.

In a second aspect, a method for configuring a physical resource pool is provided, which is applied to a cloud management platform, and the cloud management platform is used to manage the physical resource pool of a tenant. The method may include: the cloud management platform receives a configuration item about the physical resource pool input by the tenant, and the configuration item is used to indicate a plurality of logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool. Then, the cloud management platform configures the physical resource pool into a plurality of logical resource pools according to the configuration item.

In a possible implementation, the above configuration item is also used to indicate: the identifier of the physical machine corresponding to each logical resource pool in the physical resource pool. The tenant specifies the physical machine that provides computing resources to the logical resource pool, which improves the tenant experience.

In a third aspect, a device for creating a cloud service instance is provided, the device being deployed on a cloud management platform, the cloud management platform being used to manage a tenant's physical resource pool. The device for creating a cloud service instance comprises: a receiving unit, a determining unit, and a creating unit. Among them:

A receiving unit is used to receive a tenant's service request, where the service request is used to create a target cloud service instance using computing resources in a physical resource pool. The physical resource pool is configured as multiple logical resource pools, which are used to provide different types of cloud service instances. Each type of cloud service instance requires a different proportion of computing resources, including CPU and memory.

The determining unit is configured to determine, in response to a service request, a target logical resource pool that matches the type of the target cloud service instance from a plurality of logical resource pools in the physical resource pool.

The creation unit is used to create a target cloud service instance by using computing resources in the target logical resource pool.

It should be noted that the device for creating a cloud service instance provided in the second aspect is used to execute the functions of the cloud management platform in the above-mentioned first aspect. The specific implementation can refer to the description of the above-mentioned first aspect or any possible implementation method, which will not be repeated here.

In a fourth aspect, a computing device is provided, which includes a memory and at least one processor, the memory being used to store a set of computer instructions; when the processor executes the computer instructions, the computing device executes the operating steps described in the method described in the first aspect or any possible implementation method.

In a fifth aspect, a computer-readable storage medium is provided, comprising: computer software instructions; when the computer software instructions are executed in a computer, the computer executes the operating steps of the method described in the first aspect or any possible implementation method.

In a sixth aspect, a computer program product is provided, which, when executed on a computer, enables the computer to execute the operating steps of the method described in the first aspect or any possible implementation manner.

It should be noted that various possible implementation methods of any of the above aspects can be combined under the premise that there is no contradiction between the solutions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a physical resource pool;

FIG2 is a schematic diagram of the principle of the solution provided in the embodiment of the present application;

FIG3 is a schematic diagram of the architecture of a cloud management platform provided in an embodiment of the present application;

FIG4 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application;

FIG5 is a flow chart of a method for creating a cloud service instance provided in an embodiment of the present application;

FIG6 is a flow chart of a method for configuring a physical resource pool according to an embodiment of the present application;

FIG7 is a schematic diagram of a configuration interface provided in an embodiment of the present application;

FIG8 is a flow chart of another method for creating a cloud service instance provided in an embodiment of the present application;

FIG9 is a schematic diagram of a visualization interface provided in an embodiment of the present application;

FIG10 is a schematic diagram of the working principle of the solution provided in an embodiment of the present application;

FIG11 is a schematic diagram of the structure of an apparatus for creating a cloud service instance provided in an embodiment of the present application;

FIG12 is a schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application;

FIG. 13 is a schematic diagram of an implementation method of a computing device cluster provided in an embodiment of the present application.

DETAILED DESCRIPTION

In the embodiments of the present application, in order to clearly describe the technical solutions of the embodiments of the present application, words such as "first" and "second" are used to distinguish between identical or similar items with substantially identical functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different. There is no order of precedence or size between the technical features described by the "first" and "second".

In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

In the embodiments of the present application, at least one can also be described as one or more, and multiple can be two, three, four or more, which is not limited in the present application.

In addition, the network architecture and scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

To facilitate understanding, the terms involved in the embodiments of the present application are first explained.

Computing resources refer to the hardware resources provided by computers for computing. Computing resources include but are not limited to: central processing unit (CPU), memory, bandwidth, graphics processing unit (GPU) or others.

Cloud service refers to obtaining required services through the Internet in an on-demand and easily scalable manner.

A cloud service instance is a collection of resources obtained through cloud services. A cloud service instance can be a virtual machine, container, or other form.

Heterogeneous services refer to cloud services with different computing resource ratios. For example, a virtual machine with a central processing unit (CPU) memory ratio of 1:2 and a virtual machine with a CPU memory ratio of 1:4 are heterogeneous services. The types of cloud services described in this application can be infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), function as a service (FaaS), etc. As long as the proportion of server computing resources they occupy is different, they can be considered heterogeneous services.

A co-location resource pool refers to a scenario where two or more heterogeneous services are deployed in the same physical resource pool. Figure 1 shows a scenario of a co-location resource pool. As shown in Figure 1, multiple types of cloud services are deployed in the physical resource pool shown in (a) of Figure 1, and the computing resources allocated to each cloud service are shown in (b) of Figure 1.

Resource pool unification refers to a deployment method in which multiple resource pools that are managed by a single operation department and provide resources to different types of cloud services are mixed and deployed in the same physical resource pool for operation and management.

Capacity planning refers to allocating computing resources for different types of heterogeneous services in a co-located resource pool to avoid resource squeezes between heterogeneous services.

In a resource pool with single-unit operation management (a resource pool that only provides resources to one type of cloud service), you can simply use the total computing resources of the resource pool, minus the amount that has been issued, to get the remaining available amount for that type of cloud service. However, in a mixed resource pool, since the resource pool provides resources to multiple types of cloud services, the total resource amount of the resource pool minus the amount that has been issued can only get the remaining computing resources of the resource pool, and it is impossible to evaluate how much resources can be issued to each type of cloud service. This causes resource runs between heterogeneous services. For example, the surplus resources allocated to a certain type of cloud service cause insufficient resources for other types of cloud services, which ultimately makes the resource expectations of various types of cloud service instances unstable, which brings challenges to the operation of cloud service instances.

Although existing cloud computing providers support tenants to customize service specifications, or support tenants to customize whether private resource pools can be co-located, they still only provide the function of querying the remaining computing resources of the host. There is a lack of scientific management methods and management tools, and it is impossible to know the number of remaining computing resources that can be issued for various types of cloud service instances.

At present, when tenants want to deploy heterogeneous services (that is, colocation) on their own private resource pools, it is difficult to consider the balanced placement of computing resources in multiple dimensions, that is, there may be an excess of computing resources allocated to a certain type of cloud service, resulting in insufficient computing resources for other types of cloud services, which will cause problems such as uneven utilization of computing resources and resource runs in colocation. The problem of unbalanced utilization of computing resources and resource runs will be aggravated by tenants' customized service rules. The resource run problem will further lead to unstable expectations for the release of cloud service instances, forming a vicious cycle, resulting in weak risk resistance and high operating costs in the colocation resource pool.

Based on this, the present application provides a method for creating a service instance, in which a physical resource pool is abstracted into multiple logical resource pools, and a logical resource pool is used to provide a type of cloud service instance. The internal operation of the logical resource pool can be similar to that of a single unit. In this way, according to the amount of resources issued by the logical resource pool, it is possible to know how much computing resources can be issued to the corresponding type of cloud service instance, so that the expected stability of resources for each type of cloud service instance in the mixed resource pool can be ensured; in the balanced consideration of the multi-dimensional setting items, each logical resource pool corresponds to the number of allocated computing resources, and heterogeneous services correspond to different logical resource pools, so that the computing resources in the mixed resource pool can be balanced, avoiding resource runs between heterogeneous services. Therefore, the solution provided by the present application realizes the operation and management after heterogeneous services are deployed in a physical resource pool, improves the weak risk resistance of the resource pool, and reduces the operating costs.

Exemplarily, the principle of the solution provided by the present application may be shown in Figure 2. The physical resource pool provided by the X-type physical machine is abstracted into multiple logical resource pools of different types, and the multiple logical resource pools are used to provide different types of cloud service instances.

The solutions provided by the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

The solution provided in this application can be applied to the cloud management platform shown in Figure 3. As shown in Figure 3, the cloud management platform includes a management device 301, a data center 302, and a scheduler 303. The cloud management platform is used to manage the physical resource pool of tenants.

The data center 302 includes multiple physical machines 3021. The computing resources of the data center 302 are provided by the physical machines 3021 included therein, and the computing resources of the data center 302 form a resource pool. The data center 302 can deploy at least two different types of cloud services, namely heterogeneous services, and the resource pool formed by the data center 302 is called a co-location resource pool.

Exemplarily, the resource pool of the data center 302 may be a resource pool of a public cloud, a resource pool of a private cloud, or a dedicated resource pool, which is not limited in the embodiments of the present application.

The management device 301, the data center 302, and a plurality of physical machines 3021 included in the data center 302 are connected via a network.

The management device 301 is used to manage and operate the resource pool formed by the data center 302. The resource pool management system 304 is deployed on the management device 301. The tenant operates the resource pool management system 304 to control the management device 301 and manage and operate the resource pool formed by the data center 302.

The scheduler 303 is used to receive a service request for creating a cloud service instance initiated by a tenant, and create a cloud service instance using computing resources in the data center 302 according to the service request.

Exemplarily, the architecture of the cloud management platform shown in FIG3 can add or reduce network elements according to actual needs. The embodiments of the present application are not limited to this, and FIG3 is for illustration only.

Exemplarily, the management device 301 can execute the solution provided in the present application, abstract the physical resource pool into multiple logical resource pools, and the multiple logical resource pools are used to provide different types of cloud service instances, and manage and operate the resource pool of the data center 302. The specific management process can be described in the subsequent method embodiments and will not be repeated here.

In one aspect, an embodiment of the present application provides a computing device 400. The computing device 400 may be the management device 301 or the scheduler 303 illustrated in FIG. 2 or FIG. 3 .

As shown in FIG4 , computing device 400 may include bus 402, processor 404, memory 406, and communication interface 408. Processor 404, memory 406, and communication interface 408 communicate via bus 402. Computing device 400 may 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 computing device 400.

The bus 402 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, FIG4 is represented by only one line, but does not mean that there is only one bus or one type of bus. Bus 404 may include a pathway for transferring information between various components of computing device 400 (eg, memory 406 , processor 404 , communication interface 408 ).

Processor 404 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).

The memory 406 may include a volatile memory, such as a random access memory (RAM). The processor 404 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).

The communication interface 403 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 100 and other devices or a communication network.

In a possible implementation, the memory 406 stores executable program codes, and the processor 404 executes the executable program codes to implement the following functions:

Receive a service request from a tenant, where the service request is used to create a target cloud service instance using computing resources in a physical resource pool, where the physical resource pool is configured as multiple logical resource pools, where the multiple logical resource pools are used to provide different types of cloud service instances, and where each type of cloud service instance requires a different proportion of computing resources, including CPU and memory; in response to the service request, determine a target logical resource pool that matches the type of the target cloud service instance from the multiple logical resource pools in the physical resource pool; and create the target cloud service instance using the computing resources in the target logical resource pool.

In another possible implementation, the memory 406 stores an executable program code, and the processor 404 executes the executable program code to implement the following functions:

Receive configuration items about physical resource pools input by tenants, where the configuration items are used to indicate multiple logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool; configure the physical resource pool into multiple logical resource pools according to the configuration items.

On the other hand, an embodiment of the present application provides a method for creating a cloud service instance, which is applied to a cloud management platform (e.g., the cloud management platform shown in FIG3), and the cloud management platform is used to manage the physical resource pool of the tenant. The physical resource pool deploys multiple types of cloud service instances (heterogeneous services) with different computing resource ratios, that is, the physical resource pool is a mixed resource pool. When the physical resource pool is a mixed resource pool, that is, the physical resource pool is used to provide multiple different types of cloud service instances.

As shown in FIG. 5 , the method for creating a cloud service instance provided in an embodiment of the present application may include:

S501. A cloud management platform receives a service request from a tenant of a physical resource pool, where the service request is used to create a target cloud service instance.

The physical resource pool is configured as multiple logical resource pools, which are used to provide different types of cloud service instances. Each type of cloud service instance requires a different proportion of computing resources, including CPU and memory. Different logical resource pools are isolated from each other.

Furthermore, each logical resource pool can be isolated by software isolation.

Specifically, the cloud management platform can configure the physical resource pool into multiple logical resource pools according to actual needs.

For example, the specific configuration process can refer to the process of configuring the physical resource pool shown in Figure 6 below. Of course, the cloud management platform can also configure the physical resource pool into multiple logical resource pools in other ways, such as configuring the physical resource pool into multiple logical resource pools according to statically configured configuration items. The embodiment of the present application does not limit the process of configuring the physical resource pool by the cloud management platform.

The service request may include a type identifier of the target cloud service instance. The specific form and content of the type identifier are not limited in the embodiments of the present application.

In another possible implementation, the service request may include the computing resource requirements (eg, CPU-to-memory ratio) of the target cloud service instance, and different computing resource requirements indicate different types of cloud service instances.

S502: In response to the service request, the cloud management platform determines a target logical resource pool that matches the type of the target cloud service instance from multiple logical resource pools in the physical resource pool.

Specifically, the type of cloud service instance provided by each logical resource pool in the physical resource pool is the type of cloud service instance matched by the logical resource pool. Therefore, the target logical resource pool that matches the type of the target cloud service instance is the logical resource pool used to provide the type of the target cloud service instance.

S503: The cloud management platform uses the computing resources in the target logical resource pool to create a target cloud service instance.

Specifically, the cloud management platform can schedule computing resources in the target logical resource pool and create a target cloud service instance according to the configuration of the target cloud service instance indicated by the service request. The embodiments of the present application do not limit the creation process.

Exemplarily, the process from S501 to S503 may be performed by a scheduler deployed in the cloud management platform (eg, scheduler 303 in FIG. 3 ).

Through the solution provided by the present application, the physical resource pool is abstracted into multiple logical resource pools. One logical resource pool is used to provide one type of cloud service instance. The internal operation of the logical resource pool can be similar to that of a single unit. According to the amount of resources issued in the logical resource pool, it is possible to know how much computing resources can be issued to the corresponding type of cloud service instance, thereby ensuring the stability of resource expectations of each type of cloud service instance in the mixed resource pool. In the balanced consideration of the multi-dimensional setting configuration items, the number of computing resources allocated to each logical resource pool, and heterogeneous services corresponding to different logical resource pools, can ensure balanced utilization of computing resources in the mixed resource pool, avoiding resource runs between heterogeneous services. Therefore, the solution provided by the present application realizes the operation and management after heterogeneous services are deployed in a physical resource pool, improves the risk resistance of the resource pool, and reduces operating costs.

Furthermore, an embodiment of the present application also provides a process for configuring a physical resource pool, as shown in FIG6 , which may include processes S601 and S602.

S601. The cloud management platform receives configuration items about physical resource pools input by the tenant, where the configuration items are used to indicate multiple logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool.

The configuration items are used to indicate multiple logical resource pools, which are used to provide different types of cloud service instances.

For example, the cloud management platform can display a configuration interface to the tenant, and the configuration interface includes controls for inputting configuration items. The embodiment of the present application does not limit the style and specific content of the configuration interface.

Among them, the configuration item is used to indicate multiple logical resource pools, which can be a number N, or an identifier of N logical resource pools, or other forms, which is not limited in this embodiment of the present application.

The number N of logical resource pools can be configured according to actual needs and input by the tenant, and this embodiment of the present application is not limited to this.

Exemplarily, the number N of logical resource pools may be the number of types of cloud service instances supported by the physical resource pool, and a logical resource pool provides computing resources only to one type of cloud service. Different types of cloud service instances require different proportions of computing resources.

For example, one logical resource pool is used to provide one type of cloud service instance, and N logical resource pools are used to provide N types of cloud service instances. The number N of logical resource pools may be equal to the number of types of cloud service instances supported by the physical resource pool.

It is understandable that the number of computing resources allocated to each logical resource pool refers to the number of various computing resources allocated to each logical resource pool. The computing resources may include CPU, memory, etc.

In one possible implementation, the configuration item indicates the number of computing resources allocated to each logical resource pool, but the configuration item does not limit the specific location of the computing resources allocated to each logical resource pool in the physical resource pool (distributed in which physical hosts).

In another possible implementation, the configuration item indicates not only the number of computing resources allocated to each logical resource pool, but also the identifier of the physical machine corresponding to each logical resource pool. The identifier of the physical machine corresponding to each logical resource pool indicated by the configuration item indicates the physical machine to which the computing resources allocated to the logical resource pool belong.

Exemplarily, the configuration item may include the number of allocated computing resources corresponding to the first logical resource pool and the identification of the physical machine: CPU 20 for physical machine 1, and memory 200 for physical machine 2.

Furthermore, the type of cloud service instance corresponding to each logical resource pool indicated by the configuration item is used to reflect the correspondence between the types of logical resource pools and cloud service instances. A logical resource pool is used to provide a cloud service instance of its corresponding type.

Exemplarily, the configuration interface displayed by the cloud management platform to the tenant may be as shown in FIG7. In the configuration interface shown in FIG7, a configuration area is included, and the configuration area includes a control 701 and a control 702. Among them, the control 701 is used to input the number N of logical resource pools and the number of computing resources allocated to the logical resource pools, and the control 702 is used to input the type of cloud service instance corresponding to each logical resource pool.

The control shown in Fig. 7 includes a drop-down box and an add icon. The drop-down box can be used to select specific input content by pulling down, and the add icon allows the tenant to input the selected and/or input content into the management device.

For example, when the tenant clicks the arrow icon of the drop-down box included in the control 701, the property content of a logical resource pool can be displayed to the tenant. The tenant can complete the configuration of the property of a logical resource pool by manually entering the relevant content and then clicking the add icon of the control 701. The tenant can complete the configuration of the properties of multiple logical resource pools by operating the control 701 multiple times, which is equivalent to inputting the number N of logical resource pools, or equivalent to inputting the configuration items indicating N logical resource pools.

For example, when the tenant clicks the arrow icon of the drop-down box included in control 702, the property content of a cloud service instance can be displayed to the tenant. The tenant can add a corresponding relationship between a type of cloud service instance and a logical resource pool by manually entering relevant content and then clicking the add icon of control 702. The tenant can add a corresponding relationship between multiple types of cloud service instances and logical resource pools by operating control 702 multiple times.

Of course, FIG. 7 is only an example of the content of a configuration interface. In actual applications, the content in the configuration interface and the style of the configuration interface can be configured according to actual needs.

S602. The cloud management platform configures the physical resource pool into multiple logical resource pools according to the configuration items.

Specifically, in S602, the cloud management platform configures the physical resource pool according to the configuration items obtained in S601, and divides it (logically divides) into multiple (N) logical resource pools indicated by the configuration items. During the division process, the number of computing resources corresponding to each logical resource pool indicated by the configuration items is allocated, and the resources contained in each logical resource pool are configured.

Furthermore, the cloud management platform also obtains the type of cloud service instance corresponding to each logical resource pool based on the configuration items, that is, it establishes a correspondence between the logical resource pool and the type of cloud service instance, so that after receiving a service request to create a cloud service instance, it can schedule resources from the logical resource pool corresponding to the type to create a cloud service instance.

Exemplarily, the process from S601 to S602 may be performed by a management device deployed in a cloud management platform (eg, scheduler 301 in FIG. 3 ).

At this point, the cloud management platform has completed the configuration of the physical resource pool and abstracted the physical resource pool into multiple isolated logical resource pools.

Furthermore, the method for creating a cloud service instance provided by the present application also includes a process of re-dividing the computing resources of the logical resource pool. For example, as shown in FIG8 , the method for creating a cloud service instance provided by the embodiment of the present application may also include S504.

S504: After the trigger condition is met, the cloud management platform adjusts the quantity of computing resources allocated to at least one logical resource pool in the physical resource pool to increase the amount of cloud service instances of the first type that can be issued.

The first type of cloud service instance is any one of the different types of cloud service instances provided by multiple logical resource pools in the physical resource pool.

The trigger condition is used to indicate the premise for performing resource reallocation. For example, the content of the trigger condition can be configured according to actual needs, and the embodiment of the present application is not limited to this.

In a possible implementation, the trigger condition may be input by the tenant.

In another possible implementation, the trigger condition may be static content configured in the management device.

Exemplarily, the triggering condition includes one or more of the following: a preset time, a preset period, the available amount of the first type of cloud service instance is less than a first threshold, and the allocation rate of the second type of cloud service instance exceeds a second threshold. The second type of cloud service instance is any one of different types of cloud service instances provided by multiple logical resource pools in the physical resource pool.

The computing resource allocation rate of a cloud service instance refers to the computing resource allocation rate of the logical resource pool used to provide the cloud service instance of this type. The computing resource allocation rate of a logical resource pool refers to the ratio of the computing resources in the logical resource pool that have been allocated to the cloud service instance to the total computing resources in the logical resource pool.

Exemplarily, the preset time may be X o'clock every day. The preset period may be every Y hours, or every holiday.

Exemplarily, the fact that the releasable quantity of the first type of cloud service instance is less than the first threshold value may be: the releasable number of cores of a certain type A cloud service instance is less than C cores.

Exemplarily, the allocation rate of the second type of cloud service instance exceeding the second threshold may be: the ratio of the number of issuable cores of a certain type A cloud service instance to the number of remaining cores in its corresponding logical resource pool exceeds D%.

Of course, the specific content of the trigger condition can be configured according to actual needs, and the embodiments of the present application are not limited to this.

Furthermore, the trigger condition can be configured with a corresponding repartition restriction condition. When the repartition restriction condition is met, the cloud management platform performs the resource repartition operation. When the repartition restriction condition is not met, a reminder message is output to remind the tenant that the trigger condition is met but the restriction condition is not met.

The repartition restriction condition may be input by the tenant, or may be pre-configured in the management device.

For example, the repartitioning restriction condition may be that the minimum interval is at least F days, or no more than H times within G days, or the number of hosts adjusted in a single replanning does not exceed I.

Of course, the re-division restriction conditions corresponding to the trigger conditions can be configured according to actual needs, and the embodiments of the present application are not limited to this.

In a possible implementation, the method for creating cloud service resources provided in the embodiment of the present application may further include: the cloud management platform receiving trigger conditions and/or re-division restriction conditions input by the tenant.

Exemplarily, the tenant may input the trigger condition and/or the repartition restriction condition in the configuration interface displayed by the management device.

Exemplarily, the configuration interface displayed by the management device to the tenant may be as shown in Figure 7. The configuration interface shown in Figure 7 includes a control 703. The control 703 is used to input a trigger condition and/or a re-division restriction condition.

For example, when the tenant clicks the arrow icon of the drop-down box included in the control 703, the contents of the trigger conditions and/or re-division restriction conditions that can be configured can be displayed to the tenant, and the tenant can complete the input of the trigger conditions and/or re-division restriction conditions by manually inputting the relevant contents and then clicking the add icon of the control 703. The tenant can complete the input of multiple trigger conditions and/or re-division restriction conditions by operating the control 703 multiple times.

In a possible implementation, the method for creating a cloud service instance provided in the present application further includes: the cloud management platform receives trigger conditions and capacity planning goals input by the tenant, and the capacity planning goals include: the highest available number of cloud service instances of the first type.

Correspondingly, in S504, after the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool. Specifically, it can be implemented as follows: after the trigger condition is met, the cloud management platform performs mathematical modeling and solves according to the capacity planning target to obtain a resource allocation plan; according to the resource allocation plan, adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool.

The capacity planning target is used to indicate the performance of the physical resource pool, and the capacity planning target is a standard that must be met by resource redistribution.

Exemplarily, the capacity planning goal includes the highest available number of cloud service instances of the first type, which means that the optimal number of cloud service instances of the first type is prioritized, and the first type can be configured according to actual needs, which is not limited in the embodiments of the present application. Specifically, after mathematical modeling is performed according to the capacity planning goal, a resource configuration solution is solved in the mathematical model so that the available number of cloud service instances of the first type reaches the maximum value.

The optimal distribution amount can be understood as the distribution amount being within an ideal range, or the computing resource allocation rate being within an ideal range. The value of the range can be configured according to actual needs, and the embodiment of the present application is not limited thereto.

Of course, the specific content of the capacity planning target can be configured according to actual needs, and the embodiments of the present application are not limited to this.

Exemplarily, the tenant may input a capacity planning target in the configuration interface.

Exemplarily, the configuration interface displayed by the cloud management platform to the tenant may be as shown in Figure 7. The configuration interface shown in Figure 7 includes a control 704. The control 704 is used to input the capacity planning target.

For example, when the tenant clicks the arrow icon of the drop-down box included in the control 704, the content of the configurable capacity planning target can be displayed to the tenant, and the tenant can complete the input of the capacity planning target by manually entering the relevant content and then clicking the add icon of the control 704. The tenant can complete the input of multiple capacity planning targets by operating the control 704 multiple times.

In a possible implementation, the method for creating a cloud service instance provided in the present application further includes: the cloud management platform receiving capacity planning constraint conditions input by the tenant.

The capacity planning constraint condition is used to indicate the impact on the performance of the physical resource pool before and after the adjustment.

Exemplarily, the capacity planning constraint condition includes one or more of the following: the number of physical hosts whose resource allocation is adjusted does not exceed a third threshold, and the change in the available quantity of the third type of cloud service instance between two adjacent adjustments does not exceed a fourth threshold. The third type of cloud service instance is any one of the above different types of cloud service instances.

Of course, the specific content of the capacity planning restriction condition can be configured according to actual needs, and the embodiments of the present application are not limited to this.

Correspondingly, in S504, after the trigger condition is met, the cloud management platform adjusts the number of computing resources corresponding to the allocation of at least one logical resource pool in the physical resource pool, which can be specifically implemented as follows: after the trigger condition is met, the cloud management platform adjusts the number of computing resources corresponding to the allocation of at least one logical resource pool in the physical resource pool according to the capacity planning constraint condition. The adjustment process meets the capacity planning constraint condition.

Exemplarily, the tenant may input capacity planning constraints in a configuration interface displayed by the cloud management platform.

Exemplarily, the configuration interface displayed by the management device to the tenant may be as shown in Figure 7. The configuration interface shown in Figure 7 includes a control 705. The control 705 is used to input capacity planning constraint conditions.

For example, when the tenant clicks the arrow icon of the drop-down box included in the control 705, the content of the configurable capacity planning constraint conditions can be displayed to the tenant, and the tenant can complete the input of the capacity planning constraint conditions by manually entering the relevant content and then clicking the add icon of the control 705. The tenant can complete the input of multiple capacity planning constraint conditions by operating the control 705 multiple times.

Through the resource reallocation process provided in this application, the physical resource pool is always in a stable and balanced operating state.

In a possible implementation, the method for creating a cloud service instance provided by the present application may further include a process of visual display. As shown in FIG8 , the method for creating a cloud service instance provided by the embodiment of the present application may further include S505 .

S505. The cloud management platform provides a visual interface.

The visualization interface is used to display the values of the observation indicators of the physical resource pool and/or the values of the observation indicators of multiple logical resource pools.

The observed indicator may be a performance indicator of a physical resource pool or a logical resource pool.

Exemplarily, the observation indicators of the physical resource pool include one or more of the following indicators: the number of types of cloud service instances provided by the physical resource pool, the total amount of computing resources in the physical resource pool, the number of unissued computing resources of the physical resource pool, the number of issued computing resources of the physical resource pool, and the allocation rate of computing resources of the physical resource pool.

The allocation rate of computing resources in the physical resource pool refers to the amount of computing resources in the physical resource pool that have been allocated to the cloud service instance. The ratio of the total number of computing resources in the physical resource pool.

Exemplarily, the observation indicators of multiple logical resource pools include one or more of the following indicators: the total amount of computing resources in each logical resource pool, the number of unissued computing resources in each logical resource pool, the number of issued computing resources in each logical resource pool, and the allocation rate of computing resources in each logical resource pool.

Specifically, in S505, the cloud management platform may obtain the value of the observation indicator in real time or periodically and display it in a visualization interface.

In a possible implementation manner, the observation indicator may be a pre-configured indicator.

In another possible implementation, the observed indicator is an indicator input by the tenant.

For example, the tenant can add observation indicators at any time. Alternatively, the tenant can delete observation indicators at any time.

In a possible implementation, the method for creating a cloud service instance provided by the embodiment of the present application may further include: the cloud management platform receives an add operation from a tenant, where the add operation is used to input an observation indicator.

Exemplarily, the visualization interface provided by the cloud management platform to the tenant may be as shown in Fig. 9. In the visualization interface shown in Fig. 9, a display area 901 is included, in which the current value of each observation indicator is displayed.

The visualization interface shown in FIG. 9 also includes a control 902 for adding an observation indicator.

For example, when the tenant clicks the arrow icon of the drop-down box included in the control 902, a list of selectable observation indicators can be displayed to the tenant, and the tenant can add the observation indicator by manually selecting the visualization indicator and then clicking the add icon of the control 902. The tenant can add multiple observation indicators by operating the control 902 multiple times.

Exemplarily, the tenant performs a selection operation (such as a click operation) on each observation indicator displayed in the visualization interface. After receiving the tenant's selection operation on a certain observation indicator, the cloud management platform displays a control menu for the observation indicator. The control menu includes control options for the observation indicator (such as a delete option, a hide option, etc.). The cloud management platform performs the operation indicated by the control option (such as delete or hide) on the observation indicator based on the tenant's selection of the control option.

Figure 10 illustrates the working principle of the solution provided by the present application. As shown in Figure 10, the cloud management platform includes a capacity planning module, a resource expectation module and a visual monitoring module. The cloud management platform is used to manage and configure computing resources in the physical resource pool according to the configuration of the tenant.

Among them, the tenant inputs the configuration of the logical resource pool, the configuration of the cloud service instance, the trigger conditions, the restriction conditions, the capacity planning target and other contents. The configuration of the logical resource pool and the configuration of the cloud service instance are processed by the capacity planning module, and the capacity planning module performs resource configuration for the physical resource pool. The capacity planning module transmits the trigger conditions, restriction conditions, capacity planning targets and other contents to the resource expectation module. The resource expectation module evaluates the resource expectation according to the status of the physical resource pool, determines the expectation of different types of cloud service instances (how many resources can be allocated) and outputs them. The visual monitoring module displays a visual interface to the tenant according to the status of the physical resource pool (query acquisition).

Through the visualization process provided by this application, black box management is avoided.

The above mainly introduces the solution provided by the embodiment of the present invention from the perspective of the working principle of the cloud management platform. It can be understood that in order to realize the above functions, the cloud management platform, etc. includes hardware structures and/or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed in this document, the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware 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 exceed the scope of the present invention.

The embodiment of the present invention can divide the functional modules of the cloud management platform according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present invention is schematic and is only a logical functional division. There may be other division methods in actual implementation.

The present application also provides a device 110 for creating a cloud service instance. As shown in FIG11 , the device 110 for creating a cloud service instance may include: a receiving unit 1101, a determining unit 1102, and a creating unit 1103. Among them:

The receiving unit 1101 is used to receive a service request from a tenant, where the service request is used to create a target cloud service instance using computing resources in a physical resource pool. The physical resource pool is configured as multiple logical resource pools, which are used to provide different types of cloud service instances. Each type of cloud service instance requires a different proportion of computing resources, and the computing resources include CPU and memory.

The determining unit 1102 is configured to determine, in response to a service request, a target logical resource pool that matches the type of the target cloud service instance from a plurality of logical resource pools in the physical resource pool.

The creation unit 1103 is used to create a target cloud service instance by using computing resources in the target logical resource pool.

The receiving unit 1101, the determining unit 1102, and the creating unit 1103 may all be implemented by software or by hardware. Exemplarily, the implementation of the determining unit 1102 is described below by taking the determining unit 1102 as an example. Similarly, the implementation of the receiving unit 1101 and the creating unit 1103 may refer to the implementation of the determining unit 1102.

As an example of a software functional unit, the module 1102 may include code running on a computing instance. The computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Furthermore, the computing instance may be one or more. For example, module A 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 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 one data center or multiple data centers with similar geographical locations. Generally, a region may include multiple AZs.

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.

As an example of a hardware functional unit, module A may include at least one computing device, such as a server, etc. Alternatively, the determination unit 1102 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.

The multiple computing devices included in the determination unit 1102 may be distributed in the same region or in different regions. The multiple computing devices included in the determination unit 1102 may be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the determination unit 1102 may be distributed in the same VPC or in multiple VPCs. The multiple computing devices may be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

It should be noted that, in other embodiments, the receiving unit 1101 is used to execute the process S501 in FIG. 5 or FIG. 8; the determining unit 1102 is used to execute the process S502 in FIG. 5 or FIG. 8; and the creating unit 1103 is used to execute the process S503 in FIG. 5 or FIG. 8. The steps that the receiving unit 1101, the determining unit 1102, and the creating unit 1103 are responsible for implementing can be specified as needed, and the receiving unit 1101, the determining unit 1102, and the creating unit 1103 respectively implement different steps in the method for creating a cloud service instance provided in FIG. 5 or FIG. 8 to implement all functions of the device for creating a cloud service instance.

On the other hand, the memory 406 in the computing device 400 shown in FIG. 4 provided by the present application stores executable program codes, and the processor 404 executes the executable program codes to respectively implement the functions of the aforementioned determining unit 1102 and the creating unit 1103, thereby implementing the method for creating a cloud service instance illustrated in FIG. 5 or FIG. 8. That is, the memory 406 stores instructions for executing the method for creating a cloud service instance illustrated in FIG. 5 or FIG. 8.

On the other hand, the embodiment of the present application also provides a computing device cluster as shown in Figure 12. The computing device cluster includes at least one computing device. 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, a laptop, or a smart phone.

As shown in Fig. 12, the computing device cluster includes at least one computing device 400. The memory 406 in one or more computing devices 400 in the computing device cluster may store the same instructions for executing the method for creating a cloud service instance illustrated in Fig. 5 or Fig. 8.

In some possible implementations, the memory 406 of one or more computing devices 400 in the computing device cluster may also respectively store partial instructions for executing the method for creating a cloud service instance illustrated in FIG5 or FIG8. In other words, the combination of one or more computing devices 400 may jointly execute instructions for executing the method for creating a cloud service instance illustrated in FIG5 or FIG8.

It should be noted that the memory 406 in different computing devices 400 in the computing device cluster may store different instructions, which are respectively used to execute part of the functions of the apparatus 110 for creating a cloud service instance. That is, the instructions stored in the memory 406 in different computing devices 400 may implement the functions of one or more modules in the determining unit 1102 and the creating unit 1103.

In some possible implementations, one or more computing devices 400 in the computing device cluster can be connected via a network. The network may be a wide area network or a local area network, etc. FIG. 13 shows a possible implementation. As shown in FIG. 13 , two computing devices 400A and 400B 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 406 in the computing device 400A stores instructions for executing the function of the determination unit 1102. At the same time, the memory 406 in the computing device 400B stores instructions for executing the function of the creation unit 1103.

The connection method between the computing device clusters shown in Figure 13 can be considered that the method for creating a cloud service instance provided in this application requires a large amount of data storage, so it is considered to hand over the functions implemented by the creation unit 1103 to the computing device 400B for execution.

It should be understood that the functions of the computing device 400A shown in FIG13 may also be completed by multiple computing devices 400. Similarly, the functions of the computing device 400B may also be completed by multiple computing devices 400.

On the other hand, the embodiment of the present application further 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 method for creating a cloud service instance illustrated in FIG. 5 or FIG. 8 above.

On the other hand, an 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 a 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 drive), etc. The computer-readable storage medium includes instructions that instruct the computing device to execute the method for creating a cloud service instance illustrated in Figure 5 or Figure 8 above, or instruct the computing device to execute the method for creating a cloud service instance illustrated in Figure 5 or Figure 8 above.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims (21)

A method for creating a cloud service instance, characterized in that the method is applied to a cloud management platform, the cloud management platform is used to manage a tenant's physical resource pool, and the method includes: The cloud management platform receives a service request from the tenant, wherein the service request is used to create a target cloud service instance using computing resources in the physical resource pool, wherein the physical resource pool is configured as a plurality of logical resource pools, and wherein the plurality of logical resource pools are used to provide different types of cloud service instances, and each type of cloud service instance requires a different proportion of computing resources, and the computing resources include a central processing unit (CPU) and memory; The cloud management platform determines, in response to the service request, a target logical resource pool that matches the type of the target cloud service instance from a plurality of logical resource pools of the physical resource pool; The cloud management platform creates the target cloud service instance by using the computing resources in the target logical resource pool. The method according to claim 1, characterized in that the method further comprises: After the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool to increase the amount of cloud service instances of the first type that can be issued, and the first type of cloud service instances is any one of the different types of cloud service instances. The method according to claim 2 is characterized in that the trigger condition includes one or more of the following: a preset time, a preset period, the releasable amount of the first type of cloud service instance is less than a first threshold, the allocation rate of the second type of cloud service instance exceeds a second threshold, and the second type of cloud service instance is any one of the different types of cloud service instances. The method according to claim 2 or 3, characterized in that the method further comprises: The cloud management platform receives the trigger condition and capacity planning target input by the tenant, where the capacity planning target includes: the maximum number of cloud service instances of the first type that can be issued. The method according to claim 4 is characterized in that after the trigger condition is met, the cloud management platform adjusts the number of computing resources corresponding to at least one logical resource pool in the physical resource pool, including: After the trigger condition is met, the cloud management platform performs mathematical modeling and solves according to the capacity planning target to obtain a resource allocation plan; According to the resource configuration scheme, the quantity of computing resources allocated to at least one logical resource pool in the physical resource pool is adjusted. The method according to any one of claims 2 to 5, characterized in that the method further comprises: The cloud management platform receives a capacity planning constraint condition input by the tenant, wherein the capacity planning constraint condition includes one or more of the following: the number of physical hosts whose resource allocation is adjusted does not exceed a third threshold, and the change in the provisionable quantity of the third type of cloud service instance between two adjacent adjustments does not exceed a fourth threshold, wherein the third type of cloud service instance is any one of the different types of cloud service instances; After the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool, including: After the trigger condition is met, the cloud management platform adjusts the number of computing resources allocated to at least one logical resource pool in the physical resource pool according to the capacity planning restriction condition. The method according to any one of claims 1 to 6, characterized in that before the cloud management platform receives the service request, the method further comprises: The cloud management platform receives a configuration item about the physical resource pool input by the tenant, where the configuration item is used to indicate the multiple logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool; The cloud management platform configures the physical resource pool into the multiple logical resource pools according to the configuration items. The method according to claim 7 is characterized in that the configuration item is also used to indicate: an identifier of a physical host corresponding to each logical resource pool in the physical resource pool. The method according to any one of claims 1 to 8, characterized in that the method further comprises: Providing a visualization interface, the visualization interface is used to display the values of the observation indicators of the physical resource pool and/or the values of the observation indicators of the multiple logical resource pools; The observation indicators of the physical resource pool include one or more of the following indicators: the number of types of cloud service instances provided by the physical resource pool, the total amount of computing resources in the physical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources; The observation indicators of the multiple logical resource pools include one or more of the following indicators: the total amount of computing resources in each logical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources. A device for creating a cloud service instance, characterized in that the device is deployed on a cloud management platform, the cloud management platform is used to manage a tenant's physical resource pool, and the device includes: a receiving unit, configured to receive a service request from the tenant, wherein the service request is used to create a target cloud service instance using computing resources in the physical resource pool, wherein the physical resource pool is configured as a plurality of logical resource pools, and wherein the plurality of logical resource pools are used to provide different types of cloud service instances, and each type of cloud service instance requires a different proportion of computing resources, and the computing resources include a central processing unit (CPU) and memory; a determining unit, configured to determine, in response to the service request, a target logical resource pool that matches the type of the target cloud service instance from a plurality of logical resource pools of the physical resource pool; The creation unit is used to create the target cloud service instance by using the computing resources in the target logical resource pool. The device according to claim 10, characterized in that the device further comprises a configuration unit, configured to: After the trigger condition is met, the number of computing resources allocated to at least one logical resource pool in the physical resource pool is adjusted to increase the amount of cloud service instances of the first type that can be issued, where the first type of cloud service instances is any one of the different types of cloud service instances. The device according to claim 11 is characterized in that the trigger condition includes one or more of the following: a preset time, a preset period, the releasable amount of the first type of cloud service instance is less than a first threshold, the allocation rate of the second type of cloud service instance exceeds a second threshold, and the second type of cloud service instance is any one of the different types of cloud service instances. The device according to claim 11 or 12, characterized in that the receiving unit is further used for: The trigger condition and capacity planning target input by the tenant are received, where the capacity planning target includes: the maximum number of cloud service instances of the first type that can be issued is the highest. The device according to claim 13, characterized in that the configuration unit is specifically used to: After the trigger condition is met, mathematical modeling is performed and solved according to the capacity planning target to obtain a resource allocation plan; According to the resource configuration scheme, the quantity of computing resources allocated to at least one logical resource pool in the physical resource pool is adjusted. The device according to any one of claims 11 to 14, characterized in that The receiving unit is further used to: receive a capacity planning restriction condition input by the tenant, wherein the capacity planning restriction condition includes one or more of the following: the number of physical hosts whose resource allocation is adjusted does not exceed a third threshold, and the change in the provisionable amount of the third type of cloud service instance between two adjacent adjustments does not exceed a fourth threshold, wherein the third type of cloud service instance is any one of the different types of cloud service instances; The configuration unit is specifically configured to adjust the number of computing resources allocated to at least one logical resource pool in the physical resource pool according to the capacity planning restriction condition after the trigger condition is met. The device according to any one of claims 10 to 15, characterized in that The receiving unit is further used to: before receiving the service request, receive a configuration item about the physical resource pool input by the tenant, the configuration item being used to indicate the multiple logical resource pools, the number of computing resources allocated to each logical resource pool, and the type of cloud service instance corresponding to each logical resource pool; The device also includes a configuration unit, configured to configure the physical resource pool into the multiple logical resource pools according to the configuration items. The device according to claim 16 is characterized in that the configuration item is also used to indicate: an identifier of a physical host corresponding to each logical resource pool in the physical resource pool. The device according to any one of claims 10 to 17, characterized in that the device further comprises: A display unit, configured to provide a visualization interface, wherein the visualization interface is configured to display the values of the observation indicators of the physical resource pool and/or the values of the observation indicators of the plurality of logical resource pools; The observation indicators of the physical resource pool include one or more of the following indicators: the number of types of cloud service instances provided by the physical resource pool, the total amount of computing resources in the physical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources; The observation indicators of the multiple logical resource pools include one or more of the following indicators: the total amount of computing resources in each logical resource pool, the number of unissued computing resources, the number of issued computing resources, and the allocation rate of computing resources. A computing device cluster, characterized in that it includes at least one computing device, each computing device includes 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 9. 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 9. A computer-readable storage medium, characterized in that it includes computer program instructions. When the computer program instructions are executed by a computing device cluster, the computing device cluster executes the method according to any one of claims 1 to 9.