Cloud application deployment method, cloud application deployment apparatus and computing device cluster

Abstract

Provided are a cloud application deployment method, a cloud application deployment apparatus and a computing device cluster. The cloud application deployment method is applied to a cloud management platform. The method comprises: a cloud management platform acquiring a resource request inputted by a user; on the basis of the resource request, determining a target region from among a plurality of regions, wherein cloud resources in the target region meet the resource request; and deploying a target cloud resource in the target region. The resource request may comprise a category, a specification and / or a service indicator of the target cloud resource. In the method, a user is not required to sense each region in a cloud platform, and a cloud management platform automatically performs region selection on the basis of a resource request of the user, such that resources of each region can be maximally utilized, and the resource utilization rate is thus improved. Moreover, the method shields the user from differences between regions in the cloud platform, thereby realizing regionlessness. In other words, the user is not required to select a region when deploying a cloud application, such that the difficulty for the user in deploying the cloud application can be reduced.

Description

A cloud application deployment method, a cloud application deployment device, and a computing device cluster.

[0001] This application claims priority to Chinese Patent Application No. 2024119244980, filed on December 23, 2024, entitled “A Cloud Application Deployment Method, Cloud Application Deployment Device and Computing Device Cluster”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of computer technology, and in particular to a cloud application deployment method, a cloud application deployment device, and a computing device cluster. Background Technology

[0003] As the cloud computing market continues to expand, user demand for deploying cloud applications (or cloud services) on cloud platforms is increasing. However, the current practice of users choosing which regions to deploy cloud applications on cloud platforms introduces significant uncertainty into cloud platform resource management. Specifically, users need a certain level of knowledge to fully understand the resources and performance of the cloud platform in order to make an appropriate choice. In reality, most users lack this knowledge, and therefore, when faced with this difficulty, they often end up selecting regions randomly. This random selection leads to uneven resource utilization across different regions of the cloud platform, with some regions experiencing low resource utilization, ultimately increasing the resource costs of the cloud platform. Summary of the Invention

[0004] This application provides a cloud application deployment method, a cloud application deployment device, and a computing device cluster, which can reduce the difficulty for users to deploy cloud applications to the cloud and improve the resource utilization of the cloud platform.

[0005] Firstly, this application provides a cloud application deployment method. This method can be applied to a cloud management platform to deploy cloud applications for users within an infrastructure managed by the platform. This infrastructure includes multiple regions, each region including at least one computing node, and the infrastructure is used to provide cloud resources to users. The cloud application may include at least one target cloud resource. That is, the cloud application can be a single target cloud resource or a combination of multiple target cloud resources.

[0006] The method may include: first, obtaining a resource request input by a user, which may include the category, specifications, and / or service metrics of the target cloud resource; then, determining a target region among multiple regions based on the user's resource request, wherein the cloud resources in the target region satisfy the resource request; and finally, deploying the target cloud resource in the target region.

[0007] In the above solution, the user provides a resource request, and the cloud management platform determines the target region from multiple regions that meets the user's resource request, using it as the user's deployment region. This helps users deploy cloud applications more quickly. Specifically, for the user, they only need to communicate with the cloud management platform to clarify their needs; the user does not need to select a deployment region themselves, thus reducing the difficulty of deploying cloud applications. This solution achieves regionless access for users, meaning they don't need to be aware of the differences between regions within the cloud platform. Deploying cloud applications is simple, improving deployment efficiency and user experience. For the cloud platform, the cloud management platform determines the deployment region based on user needs, resolving issues such as low resource utilization in some regions and / or uneven resource utilization between multiple regions caused by user-selected regions, allowing for more efficient use of cloud resources across all regions.

[0008] In one possible implementation, before determining the target region among multiple regions based on the resource request, the method further includes: the cloud management platform acquiring status information of the multiple regions, wherein the status information includes capacity information, specification information, and / or service indicator information of cloud resources in each of the multiple regions. In this case, the cloud management platform determining the target region among the multiple regions based on the resource request may include: determining the target region among the multiple regions based on the resource request and the acquired status information.

[0009] In the above solution, the cloud management platform analyzes and compares the status information and user resource requests, and determines the target area that meets the user's resource requests from its own perspective. This allows for full utilization of cloud resources in each area without affecting user experience, avoiding waste of cloud resources and reducing costs.

[0010] In one possible implementation, before determining the target region among multiple regions based on resource requests, the method further includes: the multiple regions sending capacity and specification information of their respective cloud resources to the cloud management platform. The status information may further include cloud resource utilization, and the multiple regions may also send their respective cloud resource utilization rates to the cloud management platform. The cloud resource utilization rate of each region can be determined based on the capacity information of its respective cloud resources.

[0011] In the above scheme, for dynamically changing data such as cloud resource capacity and specification information, each region can push it to the cloud management platform in real time, thereby providing data support for the cloud management platform to make decisions and deploy regions, ensuring the real-time nature of the data, and improving the rationality of the cloud management platform's decisions.

[0012] In one possible implementation, before determining the target region among the multiple regions based on the resource request, the method further includes: the cloud management platform sending information acquisition requests to the multiple regions to obtain service indicator information of the multiple regions.

[0013] In the above scheme, for static data such as service indicator information, the cloud management platform can proactively obtain it from various regions, thereby providing data support for decision-making and deployment in those regions.

[0014] In one possible implementation, the service metrics include latency metrics, price metrics, and / or carbon emission metrics.

[0015] In one possible implementation, the cloud management platform obtains a resource request input by a user, including: providing the user with multiple deployment schemes, each of which includes one or more cloud resource categories and specifications, wherein the cloud resource categories included in the deployment schemes are different, and / or the specifications of cloud resources of the same category are different; receiving first selection information and constraints input by the user, wherein the first selection information is used to indicate the target scheme selected by the user among the multiple deployment schemes, the target scheme includes the category and specifications of the target cloud resource, and the constraints include service metrics.

[0016] In the above solution, the cloud management platform can predefine a series of standard cloud application deployment schemes for users to choose from, reducing the difficulty for users to select cloud resources.

[0017] In one possible implementation, the cloud management platform obtains a resource request input by a user, including: providing the user with multiple categories of cloud resources and one or more specifications of each cloud resource; receiving second selection information and constraints input by the user, wherein the second selection information is used to indicate the category and specification of the target cloud resource selected by the user among multiple cloud resources and one or more specifications of each cloud resource, and the constraints include service metrics.

[0018] In the above solution, the cloud management platform can provide users with multiple cloud resources to choose from, allowing users to select the cloud resources that meet their actual needs, thus better satisfying users' demand for cloud resources.

[0019] In one possible implementation, before deploying the target cloud resource in the target region, the method further includes: determining a resource description template based on the category and specifications of the target cloud resource. Thus, the cloud management platform deploys the target cloud resource in the target region by: deploying the target cloud resource according to the resource description template through a resource orchestration engine in the target region.

[0020] When a user selects a corresponding deployment plan, the cloud management platform can obtain the resource description template corresponding to the pre-made target plan from the template library and pass the resource description template as input to the resource orchestration engine in the target area for deployment.

[0021] When a user selects the specifications of cloud resources, the cloud management platform can generate a resource description template through a template editor based on the user's selection, and then send the resource description template as input to the resource orchestration engine in the target region for deployment.

[0022] Secondly, embodiments of this application also provide a cloud application deployment device. This cloud application deployment device can be applied to a cloud management platform, which manages infrastructure, including multiple regions, each region including at least one computing node, and the infrastructure providing cloud resources to users. Specifically, the cloud application deployment device may include: an acquisition module, a decision-making module, and a deployment module.

[0023] The acquisition module is used to acquire resource requests input by the user. Resource requests may include the category, specifications, and / or service metrics of the target cloud resource.

[0024] The decision module is used to determine the target region among multiple regions based on the resource request, wherein the cloud resources in the target region satisfy the resource request.

[0025] The deployment module is used to deploy target cloud resources in the target region.

[0026] In one possible implementation, the acquisition module is further configured to: acquire status information of multiple regions before the decision module determines the target region among multiple regions based on the resource request, the status information including capacity information, specification information and / or service indicator information of cloud resources in each of the multiple regions; the decision module is configured to determine the target region among the multiple regions based on the resource request and the status information.

[0027] In one possible implementation, the service metrics include latency metrics, price metrics, and / or carbon emission metrics.

[0028] In one possible implementation, the acquisition module is further configured to: provide the user with multiple deployment schemes, each of the multiple deployment schemes including one or more cloud resource categories and specifications, the cloud resource categories included in the various deployment schemes being different, and / or the specifications of cloud resources of the same category being different; receive first selection information and constraints input by the user, the first selection information being used to indicate the target scheme selected by the user among the multiple deployment schemes, the target scheme including the category and specifications of the target cloud resource, and the constraints including service indicators.

[0029] In one possible implementation, the acquisition module is further configured to: provide the user with multiple cloud resource categories and one or more specifications of each cloud resource; receive second selection information and constraints input by the user, wherein the second selection information is used to indicate the category and specification of the target cloud resource selected by the user among the multiple cloud resources and one or more specifications of each cloud resource, and the constraints include service metrics.

[0030] In one possible implementation, the acquisition module is further configured to: determine a resource description template based on the category and specifications of the target cloud resource; the deployment module is further configured to: deploy the target cloud resource according to the resource description template through a resource orchestration engine in the target region.

[0031] Thirdly, this application also provides a computing device cluster, which includes at least one computing device, each computing device including a processor and a memory, wherein the processor of the at least one computing device is used to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster performs the cloud application deployment method provided by the first aspect or any possible implementation of the first aspect.

[0032] Fourthly, this application also provides a computer-readable storage medium including computer program instructions, which, when executed by a cluster of computing devices, enable the cluster of computing devices to perform the cloud application deployment method provided by the first aspect or any possible implementation thereof.

[0033] Fifthly, this application also provides a computer program product, including computer program instructions, which, when executed by a cluster of computing devices, enable the cluster of computing devices to perform the cloud application deployment method provided by the first aspect or any possible implementation thereof.

[0034] Any of the devices, computing equipment, computing equipment clusters, computer storage media, or computer program products provided above are used to execute the methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects of the corresponding solutions in the corresponding methods provided above, and will not be repeated here. Attached Figure Description

[0035] Figure 1 is a schematic diagram of the structure of a cloud platform provided in an embodiment of this application;

[0036] Figure 2 is a flowchart of a cloud application deployment method applied to the cloud management platform shown in Figure 1, provided by an embodiment of this application;

[0037] Figure 3 is a schematic diagram of the status information of the region determined by the cloud management platform shown in Figure 1, provided in an embodiment of this application.

[0038] Figure 4 is a schematic diagram of the user interface displayed to the user by the cloud management platform shown in Figure 1 according to an embodiment of this application;

[0039] Figure 5 is a schematic diagram of the template design interface displayed to the user by the cloud management platform shown in Figure 1 according to an embodiment of this application;

[0040] Figure 6 is a schematic diagram of the capacity and / or specifications of the target cloud resource obtained by parsing the resource description template shown in Figure 1 through the cloud management platform provided in the embodiment of this application;

[0041] Figure 7 is a flowchart of a cloud application deployment method based on the method shown in Figure 2 provided in an embodiment of this application;

[0042] Figure 8 is a schematic diagram of a cloud application deployment device based on the cloud application deployment device shown in Figure 7 provided in an embodiment of this application;

[0043] Figure 9 is a schematic diagram of the structure of a computing device provided in an embodiment of this application;

[0044] Figure 10 is a schematic diagram of the structure of a computing device cluster provided in an embodiment of this application;

[0045] Figure 11 is a schematic diagram of a cloud application deployment device shown in Figure 8 deployed in a computing device cluster according to an embodiment of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be described below with reference to the accompanying drawings.

[0047] In the description of the embodiments of this application, the words "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the words "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a specific manner.

[0048] In the description of the embodiments in this application, the term "and / or" is merely a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, B existing alone, and A and B existing simultaneously. Furthermore, unless otherwise stated, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals.

[0049] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0050] Before introducing the embodiments of this application, the technical terms mentioned in the embodiments of this application will be explained below.

[0051] A cloud data center is a cluster of devices within a cloud platform that provides cloud applications (or cloud services) to users. A cloud data center may include at least one physical device, which may include servers, switches, racks, and / or auxiliary equipment. Auxiliary equipment may include power supply equipment and air conditioning equipment. It should be noted that the types and quantities of physical devices in each cloud data center can be configured according to different needs, and this application embodiment does not impose specific limitations on this.

[0052] A region represents the location of a cloud data center within a cloud platform. A region can include at least one cloud data center. Cloud data centers within the same region share cloud resources within that region. Cloud resources may include, but are not limited to: computing resources, storage resources, load balancing services, elastic internet protocol (EIP) services, cloud backup services, and host security services.

[0053] A resource orchestration engine is a functional component that automates the deployment of cloud applications, helping operations and maintenance personnel avoid a large number of repetitive manual configuration operations. It can automatically configure cloud resources and their topology relationships, enabling rapid deployment of cloud applications.

[0054] As the cloud computing market continues to expand, users' demand for deploying cloud applications (or services) on cloud platforms is increasing. This presents new challenges for the rapid deployment of cloud applications.

[0055] In one related technology, cloud platforms provide users with practical documentation on cloud applications, guiding them in selecting deployment regions. However, users need a certain level of expertise to understand this documentation and choose a suitable deployment region. In other words, the rationality of a user's region selection depends entirely on their understanding of the documentation; different levels of understanding can lead to significant differences in choice. When users cannot understand the documentation, they tend to choose deployment regions randomly, which can result in uneven resource utilization across different regions of the cloud platform.

[0056] In another related technology, the cloud platform offers users pricing for deploying cloud applications across multiple regions, allowing users to select the deployment region based on price. However, when prices are similar across multiple regions, users still randomly select a region, which similarly leads to uneven resource utilization across different regions for the cloud platform.

[0057] Therefore, this application provides a cloud application deployment method that can solve the above problems.

[0058] In this cloud application deployment method, the cloud management platform receives resource requests input by the user. Based on the resource requests, it determines target regions within multiple regions. Cloud resources in the target regions satisfy the resource requests, and the target cloud resources are deployed in those regions. The resource request may include the type, specifications, and / or service metrics of the target cloud resources. In this method, users do not need to be aware of the various regions within the cloud platform; the cloud management platform automatically selects regions based on the user's resource requests, maximizing the utilization of resources in each region and improving resource utilization. Furthermore, this method shields users from the differences between regions within the cloud platform, achieving regionless deployment. In other words, users do not need to select regions when deploying cloud applications, reducing the difficulty of cloud application deployment.

[0059] Figure 1 is a schematic diagram of a cloud platform provided in an embodiment of this application. As shown in Figure 1, the cloud platform includes a cloud management platform 100 and infrastructure 200. The cloud management platform 100 manages the infrastructure 200, which provides cloud resources to users. The infrastructure includes multiple regions (e.g., regions 201 to 203 shown in Figure 1). Each region in the cloud platform may include at least one cloud data center, and the cloud data center may include at least one computing node. The computing node may include servers and virtual computing units. The virtual computing unit may include virtual machines, containers, or other types of virtual units. Each cloud data center may deploy the resource orchestration engine shown in Figure 1 and multiple cloud resources. The cloud resources may include, but are not limited to, basic resources such as computing resources and storage resources, as well as load balancing services, elastic public network services, cloud backup services, host security services, etc.

[0060] The cloud management platform 100 can be used to select a target region for a user based on the user's resource request, and deploy the target cloud resources contained in the cloud application in the target region through the resource orchestration engine of the target region. In some embodiments, the cloud management platform 100 may specifically include a data acquisition module, an interaction module, a scheduling module, and a resource management module. The data acquisition module is used to collect status information from multiple regions to provide data support for deciding the user's deployment region. The interaction module is used to interact with the user and determine the user's resource request. The scheduling module is used to determine the deployment region based on the resource request and deploy the target cloud resources contained in the cloud application through the resource orchestration engine of the deployment region. The resource management module is used to manage the cloud resource configuration status of the cloud application.

[0061] It should be noted that the modules included in the cloud management platform 100 listed above are merely for the purpose of more clearly illustrating the functions that the cloud management platform 100 can perform, and should not be construed as specific limitations on the embodiments of this application. In other embodiments, the functions of the cloud management platform 100 may also be implemented by modules with other names or types.

[0062] This application does not impose a specific limit on the number of target cloud resources included in a cloud application. That is, a cloud application may include one target cloud resource or multiple target cloud resources.

[0063] Next, taking Figure 1 as an example, the cloud application deployment method provided in this application embodiment will be described in detail.

[0064] Figure 2 is a flowchart of a cloud application deployment method provided in an embodiment of this application. As shown in Figure 2, the method may include steps S201 to S205.

[0065] S201, the cloud management platform 100 collects data from multiple areas in the infrastructure to determine the status information of multiple areas.

[0066] The data acquisition module of the cloud management platform 100 can collect capacity information, specification information, and / or service indicator information of various regions to obtain status information for multiple regions. By constructing a data view of the infrastructure using the status information of multiple regions, it provides data support for subsequently matching target regions for deploying cloud applications based on user needs. Taking regions 201 to 203 as shown in Figure 1 as an example, the data acquisition module can collect capacity information, specification information, and / or service indicator information of cloud resources collected in regions 201 to 203 to obtain status information. Service indicators may include latency indicators, price indicators, and / or carbon emission indicators. Furthermore, in some embodiments, the status information may also include the utilization rate of cloud resources in each region, thus providing a more intuitive reflection of the cloud resource usage in a region.

[0067] In some embodiments, the data acquisition module of the cloud management platform 100 can send data acquisition requests to various regions. After receiving the data acquisition request, each region sends its own cloud resource capacity information, specification information, and / or service indicator information to the cloud management platform.

[0068] In some embodiments, the data acquisition module of the cloud management platform 100 can obtain status information from multiple regions using push and pull modes. For example, for static data such as service indicator information, the data acquisition module can send query requests to each region to proactively obtain the service indicator information of each region. For dynamically changing data such as cloud resource capacity and specification information, each region can proactively push its own cloud resource capacity and / or specification information to the data acquisition module of the cloud management platform 100 when changes occur in cloud resources.

[0069] The data acquisition module specifically includes a cloud resource query plugin and a service indicator query plugin. The cloud resource query plugin receives capacity and / or specification information of cloud resources in each region. It can also determine the utilization rate of cloud resources in each region based on this information. The service indicator query plugin sends query requests to each region to retrieve its service indicator information.

[0070] Each region may include a data management module. For example, a cloud resource management plugin and a service metric management plugin may be included. The cloud resource management plugin is used to send capacity and / or specification information of the region's cloud resources to the cloud management platform 100 when cloud resources change. The service metric management plugin is used to receive query requests from the cloud management platform 100 and send service metric information of the region to the cloud management platform 100.

[0071] Where service metrics may include latency metrics, price metrics, and / or carbon emission metrics, service metric query plugins may include latency query plugins, price query plugins, and / or carbon emission query plugins, and service metric management plugins may include latency management plugins, price management plugins, and / or carbon emission management plugins.

[0072] Taking region 201 as an example, as shown in Figure 3, in S2011, the service indicator query plugin of the cloud management platform 100 can send a query request to region 201 to obtain the service indicator information of region 201. Upon receiving the query request, the service indicator management plugin of region 201 sends the service indicator information of region 201 to the cloud management platform 100. For example, the latency query plugin, price query plugin, and / or carbon emission query plugin of the cloud management platform 100 can each send corresponding query requests to region 201. After receiving the corresponding query requests, the latency management plugin, price management plugin, and / or carbon emission management plugin of region 201 send the latency indicator, price indicator, and / or carbon emission indicator to the cloud management platform 100, respectively.

[0073] Taking region 201 as an example, as shown in Figure 3, in S2012, the cloud resource management plugin of region 201 can send a notification message carrying the cloud resources of region 201 and its remaining capacity to the cloud resource capacity query plugin when the cloud resource capacity changes.

[0074] It should be noted that the steps shown in Figure 3 are merely an example. This embodiment does not impose specific restrictions on the order in which the cloud management platform 100 obtains the capacity information, scale information, and service indicator information of cloud resources in a given region. Furthermore, the cloud management platform 100 can periodically execute S201 according to actual needs, ensuring that the status information more accurately reflects the usage of cloud resources in each region, thereby better enabling decisions regarding the user's deployment region.

[0075] S202, the cloud management platform 100 provides users with information on candidate cloud resources.

[0076] Users can log in to the cloud management platform 100 through its client, according to their actual needs. Subsequently, users can interact with the interactive module of the cloud management platform 100, which displays available cloud resource information. There are two possible implementations for presenting this candidate cloud resource information: in the first implementation, the candidate cloud resource information covers a series of predefined deployment schemes for cloud applications; while in the second implementation, the candidate cloud resource information details the capacity and / or specifications of various cloud resources required by the cloud application. The first and second possible implementations are illustrated below with reference to Figures 4 and 5, respectively.

[0077] In the first possible implementation, after logging into the cloud management platform 100, the user can choose to enter the user interface. When the user chooses to enter the user interface, the interaction module can display multiple predefined deployment schemes for the cloud application. Each deployment scheme includes the capacity and / or specifications of multiple cloud resources, with different categories of cloud resources and / or different specifications for the same category of cloud resources. Taking the user interface shown in Figure 4 as an example, this user interface can display two deployment schemes for a cloud application (Deployment Scheme 1 and Deployment Scheme 2), with different categories of cloud resources included. Both Deployment Scheme 1 and Deployment Scheme 2 include basic resources (including a central processing unit (CPU), memory, and hard disk), as well as elastic public network service resources, cloud backup storage service resources, and host security service resources. In addition, Deployment Scheme 2 includes load balancing service resources, while Deployment Scheme 1 does not. The basic resources included in Deployment Scheme 1 and Deployment Scheme 2 have the same specifications: a 2-core CPU, 4GB of memory, and 70GB of hard disk. Deployment Plan 1 and Deployment Plan 2 include the same specifications for Elastic Public Network Service resources, Cloud Backup Storage Service resources, and Host Security Service resources. Specifically, the Elastic Public Network Service resources have a peak bandwidth of 100Mbps, the Cloud Backup Storage Service resources have a storage capacity of 100GB, and the Host Security Service resources consist of 2 servers. Deployment Plan 2 includes a Load Balancing Service resource with a maximum number of connections of 2000 and a new connection rate of 200 per second.

[0078] In the second possible implementation, after logging into the cloud management platform 100, the user can choose to enter the template design interface. When the user selects to enter the user interface, the interaction module can display multiple cloud resources for the cloud application and one or more specifications for each cloud resource. Taking the template design interface shown in Figure 5 as an example, the cloud resources displayed in the candidate box of the template design interface can include basic resources, elastic public network service resources, cloud backup storage service resources, host security service resources, and load balancing service resources. The specifications of the basic resources include: CPU specifications of 2 cores and 4 cores, memory specifications of 4GB and 8GB, and hard disk specifications of 70GB and 100GB. The specifications of the elastic public network service resources include: peak bandwidth of 100Mbps and 200Mbps; the specifications of the cloud backup storage service resources include: storage capacity of 100GB and 200GB; and the specifications of the host security service resources are 2 and 4 hosts. The specifications of the load balancing service resources include: maximum number of connections of 2000 and 3000, and new connections per second of 200 and 300.

[0079] It should be noted that the cloud resources and related information shown in Figures 4 and 5 above are merely for illustrating the implementation process of this application. In other words, the content shown in Figures 4 and 5 should not be construed as limiting the embodiments of this application.

[0080] S203, Cloud Management Platform 100 obtains resource requests input by the user.

[0081] After providing candidate cloud resource information, the interaction module of the cloud management platform 100 can receive user input of selection information and constraints. The selection information represents the user's choice from the candidate cloud resource information. The constraints include the service metrics of the target cloud resource for the cloud application.

[0082] The first and second possible implementation methods described above will be illustrated below with reference to Figures 4 and 5, respectively.

[0083] In the first possible implementation, the user can select a target deployment scheme from multiple deployment options via the user interface. The user interface determines the user's first selection information based on the selected target scheme. That is, after providing multiple deployment schemes for the cloud application through the user interface, the interaction module can receive the user's first selection information. This first selection information indicates the target scheme chosen by the user among the multiple deployment options, and the target scheme includes the capacity and / or specifications of the target cloud resources required by the cloud application. Taking the two deployment schemes shown in Figure 4 as an example, the user can select deployment scheme 2 (i.e., the target scheme) from the schemes shown in Figure 4, and the first selection information received by the interaction module indicates the deployment scheme 2 selected by the user among the multiple deployment options.

[0084] In a second possible implementation, the user can select the capacity and / or specifications of the target cloud resources required for their cloud application within the template design interface. The template design interface determines the user's second selection information based on the selected target cloud resource capacity and / or specifications. In other words, after providing multiple categories of cloud resources for the cloud application and one or more specifications for each cloud resource, the interaction module can receive the user's second selection information. This second selection information indicates the capacity and / or specifications of the target cloud resources required for the cloud application selected by the user from among the multiple cloud resources and one or more specifications of each cloud resource. Taking the capacity and / or specifications of multiple cloud resources shown in Figure 5 as an example, users can drag, drop, and add the required target cloud resource capacity and / or specifications (i.e., CPU specifications of 2 cores, memory specifications of 4GB, hard disk specifications of 70GB, Elastic Public Network Service resource specifications including: peak bandwidth of 100Mbps, cloud backup storage service resource specifications including: storage capacity of 100GB, host security service resource specifications of 2 units, load balancing service resource specifications including: maximum number of connections of 2000, and number of new connections per second of 200) to the design box, and then click the OK button. After the user clicks the OK button, the template design interface sends the second selection information to the interaction module, indicating the capacity and / or specifications of the target cloud resource in the design box. Of course, users can also click the Cancel button after performing some operations to cancel the currently performed operations. After the user clicks Cancel, the user can re-enter the template design interface to perform any of the above operations.

[0085] In some embodiments, the interaction module interacts with the user, determines the user's input selection information, and then determines the resource description template for the cloud application based on the user's input selection information. The resource description template and constraints are then passed to the scheduling module. This resource description template contains the capacity and / or specifications of the target cloud resources required by the cloud application. The process of the interaction module determining the resource description template under the two possible implementations described above is described below.

[0086] In a first possible implementation, the interaction module can select a resource description template that matches the target scheme from a pre-stored pool of candidate resource description templates. Each candidate resource description template matches one of the multiple deployment schemes. Taking the two deployment schemes shown in Figure 4 as an example, the user can select deployment scheme 2 (the target scheme) from the schemes shown in Figure 4. The first selection information received by the interaction module indicates the user's choice of deployment scheme 2 from the multiple deployment schemes. Then, the interaction module selects the resource description template that matches deployment scheme 2 from the pre-stored pool of candidate resource description templates.

[0087] In a second possible implementation, the interaction module can generate a resource description template using a template editor based on the capacity and / or specifications of the target cloud resources required by the cloud application. Then, the interaction module generates the resource description template based on the capacity and / or specifications of the target cloud resources indicated by the second selection information.

[0088] This application embodiment does not impose specific restrictions on the order in which the cloud management platform 100 executes the steps. In some embodiments, the cloud management platform 100 may execute S201 after executing S202 and S203 to obtain the user's resource request.

[0089] S204, the cloud management platform 100 determines the target area that matches the user's resource request based on the resource request and status information.

[0090] After receiving the resource description template and constraints, the scheduling module of the cloud management platform 100 can parse the resource description template to obtain the flavor of the target cloud resource. In a possible implementation, the resource description template can be written in the same language as the resource orchestration engine, such as Terraform's HashiCorp configuration language (HCL). Figure 6 shows the HCL-based resource description template corresponding to deployment scheme 2 shown in Figure 4 on the left. In Figure 6, the specifications of the basic resource include a flavor field and a disk field. The value of the flavor field indicates the CPU and memory specifications, and the value of the size field in the disk field determines the disk specifications. The specifications of the Elastic Internet Protocol (EIP) resource include the size field in the bandwidth field, the value of which determines the peak bandwidth specification of the Elastic Internet Protocol (EIP). The specifications of cloud security (cloud_cbr_vault) resources include a protection type field and a size field. The protection type field indicates cloud backup, and the size field determines the specifications of the cloud backup. After parsing the resource description template shown in Figure 6, the capacity and / or specifications of the target cloud resources included in deployment scheme 2 can be obtained.

[0091] Subsequently, the scheduling module can compare the capacity, specifications, and / or service metrics of the target cloud resources required by the cloud application with the capacity, specifications, and / or service metrics information of multiple regions to determine the target region among the multiple regions. The target region's cloud resources must meet the capacity, specifications, and / or service metrics required by the cloud application.

[0092] Furthermore, in some embodiments, when the scheduling module identifies multiple target regions that meet the user's resource requests from multiple regions, it can determine the final target region by comparing the cloud resource utilization rates of the multiple target regions. For example, the scheduling module can choose the region with the lowest resource utilization rate as the final target region.

[0093] S205, the cloud management platform 100 deploys target cloud resources through the resource orchestration engine of the target region.

[0094] After determining the target region, the scheduling module of the cloud management platform 100 can send a resource orchestration request to the resource orchestration engine of the target region. This resource orchestration request instructs the resource orchestration engine of the target region to deploy the cloud application according to the capacity and / or specifications of the target cloud resources required by the cloud application. Taking region 202 as shown in Figure 1 as an example, the scheduling module sends a resource orchestration request to the resource orchestration engine of region 202.

[0095] Upon receiving a resource orchestration request, the resource orchestration engine for the target region configures the cloud resources according to the capacity and / or specifications required by the cloud application as specified in the request. After configuring the required cloud resources, the resource orchestration engine can send the configuration status of these resources to the resource management module. In practice, a cloud application may require multiple target cloud resources, and the resource orchestration engine can asynchronously synchronize the configuration status of the configured resources with the resource management module. Once all required target cloud resources are configured, the resource management module can notify the user that the cloud application has been deployed.

[0096] The method embodiment shown in Figure 2 above enables automated deployment of cloud applications by using a cloud management platform 100 to help users decide on the deployment region for their cloud applications. During this process, users do not need to be aware of the complexities between regions or select a deployment region, simplifying the cloud application deployment process. Simultaneously, for the cloud platform, this eliminates the problem of low resource utilization caused by users randomly selecting regions.

[0097] Based on the method shown in Figure 2, this application embodiment also provides a cloud application deployment method.

[0098] Figure 7 is a flowchart of a cloud application deployment method provided in an embodiment of this application. This method can be applied to a cloud management platform, which manages infrastructure including multiple regions, each region including at least one computing node, and the infrastructure is used to provide cloud resources to users. The cloud management platform may include the cloud management platform 100 shown in Figure 1. As shown in Figure 7, the method may include steps S701-S703.

[0099] S701, obtain the resource request input by the user, which includes the category, specifications and / or service metrics of the target cloud resource.

[0100] In the first possible implementation, prior to S701, the cloud management platform can provide users with multiple deployment schemes. Each deployment scheme includes one or more categories and specifications of cloud resources. The categories of cloud resources included in each deployment scheme are different, and / or the specifications of cloud resources of the same category are different. The specific process of this step can be referred to the description of the first possible implementation in step S202 of Figure 2 above, and will not be repeated here.

[0101] In the first possible implementation, in S701, the cloud management platform can receive first selection information and constraints input by the user. The first selection information is used to indicate the target solution selected by the user from multiple deployment schemes. The target solution includes the category and specifications of the target cloud resources. The specific process of this step can be referred to the description of the first possible implementation in step S203 of Figure 2 above, and will not be repeated here.

[0102] In the second possible implementation, prior to S701, the cloud management platform may also provide users with multiple categories of cloud resources and one or more specifications for each cloud resource. This step can be referred to the description of the second possible implementation in step S202 of Figure 2 above, and will not be repeated here.

[0103] In the second possible implementation, in S701, the cloud management platform can receive second selection information and constraints input by the user. The second selection information is used to indicate the category and specification of the target cloud resource selected by the user from multiple cloud resources and one or more specifications of each cloud resource. The specific process of this step can be referred to the description of the second possible implementation in step S203 of Figure 2 above, and will not be repeated here.

[0104] The service indicators include latency indicators, price indicators, and / or carbon emission indicators. Constraints include the service indicators.

[0105] S702, based on the resource request, determines the target region among multiple regions, where the cloud resources in the target region satisfy the resource request.

[0106] Prior to S702, the cloud management platform could also obtain status information from multiple regions. This status information included capacity information, specification information, and / or service indicator information of cloud resources in each of the multiple regions. The specific process of this step can be referred to the description of step S201 in the embodiment shown in Figure 2 above, and will not be repeated here.

[0107] In S702, the cloud management platform determining the target region among multiple regions based on the resource request may include: determining the target region among multiple regions based on the resource request and status information. The specific process of this step can be referred to the description in step S204 of the embodiment shown in Figure 2 above, and will not be repeated here.

[0108] S703 deploys target cloud resources in the target region.

[0109] Prior to S703, the cloud management platform could determine a resource description template based on the category and specifications of the target cloud resources before deploying them in the target region.

[0110] For example, in the first possible implementation, after the user selects the corresponding deployment plan, the cloud management platform can obtain the resource description template corresponding to the pre-made target plan from the template library, and pass the resource description template as input to the resource orchestration engine in the target area for deployment. The specific process of this step can be referred to the description of determining the resource description template in step S204 of Figure 2 above under the first possible implementation, and will not be repeated here.

[0111] For example, in the second possible implementation, after the user selects the capacity and / or specifications of the cloud resources, the cloud management platform can generate a resource description template through a template editor based on the user's selection, and then pass the resource description template as input to the resource orchestration engine in the target region for deployment. The specific process of this step can be referred to the description of determining the resource description template in step S204 of Figure 2 above under the second possible implementation, and will not be repeated here.

[0112] In S703, the cloud management platform deploying target cloud resources in the target region may include: deploying target cloud resources according to the resource description template through the resource orchestration engine in the target region. The specific process of this step can be referred to the description of step S205 in the embodiment shown in Figure 2 above, and will not be repeated here.

[0113] Based on the method shown in FIG7, this application embodiment also provides a cloud application deployment apparatus. This cloud application deployment apparatus 800 can be used to implement the various steps in the method shown in FIG7.

[0114] Figure 8 is a schematic diagram of the structure of a cloud application deployment device 800 provided in an embodiment of this application. This cloud application deployment device 800 can be applied to a cloud management platform, which manages infrastructure. The infrastructure includes multiple regions, and each region includes at least one computing node. The infrastructure is used to provide cloud resources to users. The cloud management platform may include the cloud management platform 100 shown in Figure 1.

[0115] As shown in Figure 8, the cloud application deployment device 800 may include an acquisition module 801, a decision module 802, and a deployment module 803.

[0116] The acquisition module 801 is used to acquire resource requests input by the user. The resource request may include the category, specifications, and / or service metrics of the target cloud resource.

[0117] The decision module 802 is used to determine the target region among multiple regions based on the resource request, wherein the cloud resources in the target region satisfy the resource request.

[0118] Among them, deployment module 803 deploys target cloud resources in the target area.

[0119] In one possible implementation, the acquisition module is further configured to: acquire status information of multiple regions before the decision module determines the target region among multiple regions based on the resource request, the status information including capacity information, specification information and / or service indicator information of cloud resources in each of the multiple regions; the decision module is configured to determine the target region among the multiple regions based on the resource request and the status information.

[0120] In one possible implementation, the service metrics include latency metrics, price metrics, and / or carbon emission metrics.

[0121] In one possible implementation, the acquisition module is further configured to: provide the user with multiple deployment schemes, each of the multiple deployment schemes including one or more cloud resource categories and specifications, the cloud resource categories included in the various deployment schemes being different, and / or the specifications of cloud resources of the same category being different; receive first selection information and constraints input by the user, the first selection information being used to indicate the target scheme selected by the user among the multiple deployment schemes, the target scheme including the category and specifications of the target cloud resource, and the constraints including service indicators.

[0122] In one possible implementation, the acquisition module is further configured to: provide the user with multiple cloud resource categories and one or more specifications of each cloud resource; receive second selection information and constraints input by the user, wherein the second selection information is used to indicate the category and specification of the target cloud resource selected by the user among the multiple cloud resources and one or more specifications of each cloud resource, and the constraints include service metrics.

[0123] In one possible implementation, the acquisition module is further configured to: determine a resource description template based on the category and specifications of the target cloud resource; the deployment module is further configured to: deploy the target cloud resource according to the resource description template through a resource orchestration engine in the target region.

[0124] It should be noted that the cloud application deployment device 800 provided in the embodiment shown in Figure 8 is only illustrating the division of the above-mentioned functional modules when executing the cloud application deployment method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the cloud application deployment device provided in the above embodiment and the cloud application deployment method embodiment shown in Figure 7 belong to the same concept. The specific implementation process is detailed in the method embodiments shown in Figures 2 and 7, and will not be repeated here.

[0125] When the aforementioned modules are used as an example of software functional units, the cloud application deployment device 800 may include code running on computing instances. These computing instances can be at least one of physical hosts (computing devices), virtual machines, containers, etc. Furthermore, the aforementioned computing devices may be one or more. For example, the cloud application deployment device 800 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 application can be distributed in the same region or in different regions. The multiple hosts / virtual machines / containers used to run the code can be distributed in the same availability zone (AZ) or in different AZs, each AZ including one or more geographically proximate data centers. Typically, a region may include multiple AZs.

[0126] Similarly, multiple hosts / virtual machines / containers used to run this code can be distributed within the same Virtual Private Cloud (VPC) or across multiple VPCs. Typically, a VPC is set up within a region. Communication between two VPCs within the same region, as well as between VPCs in different regions, requires a communication gateway to be set up within each VPC to enable interconnection between VPCs.

[0127] When the above-mentioned module is used as an example of a hardware functional unit, the module may include at least one computing device, such as a server. Alternatively, the module may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be implemented using a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), generic array logic (GAL), or any combination thereof.

[0128] The multiple computing devices included in a module can be distributed within the same region or in different regions. Similarly, the multiple computing devices included in a module can be distributed within the same Availability Zone (AZ) or in different AZs. Likewise, the multiple computing devices included in a module can be distributed within the same Virtual Private Cloud (VPC) or multiple VPCs. These multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0129] It should be noted that, in other embodiments, the acquisition module 801, decision module 802, and deployment module 803 can be used to execute any step in the method shown in FIG7. The steps implemented by the acquisition module 801, decision module 802, and deployment module 803 can be specified as needed. By implementing different steps in the method shown in FIG7 through the acquisition module 801, decision module 802, and deployment module 803, all functions of the cloud application deployment device 800 can be realized.

[0130] This application also provides a computing device 900. As shown in FIG9, the computing device 900 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 communicate with each other via the bus 904. The computing device 900 may be a server or a terminal device. It should be understood that this application does not limit the number of processors and memories in the computing device 900.

[0131] Bus 904 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one line is used in Figure 9, but this does not imply that there is only one bus or one type of bus. Bus 104 can include pathways for transmitting information between various components of computing device 900 (e.g., memory 902, processor 901, communication interface 903).

[0132] Processor 901 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0133] The memory 902 may include volatile memory, such as random access memory (RAM). The processor 901 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0134] The memory 902 stores executable program code, and the processor 901 executes this executable program code to implement the functions of the aforementioned acquisition module 801, decision module 802, and deployment module 803, thereby realizing the method shown in FIG7. That is, the memory 902 stores instructions for executing the method shown in FIG7.

[0135] The communication interface 903 uses modules such as, but not limited to, network interface cards and transceivers to enable communication between the computing device 900 and other devices or communication networks.

[0136] Based on the method embodiment shown in Figure 7, this application embodiment also provides a computing device cluster.

[0137] Figure 10 shows a computing device cluster 1000 provided in an embodiment of this application.

[0138] The computing device cluster 1000 may include the data processing platform described above. The computing device cluster includes at least one computing device. This computing device may 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 may also be a terminal device such as a desktop computer, a laptop computer, or a smartphone.

[0139] As shown in Figure 10, the computing device cluster 1000 includes at least one computing device 900. The memory 902 of one or more computing devices 900 in the computing device cluster may store the same instructions for executing the method shown in Figure 7.

[0140] In some possible implementations, the memory 902 of one or more computing devices 900 in the computing device cluster may also store partial instructions for executing the method shown in FIG7. In other words, a combination of one or more computing devices 900 can jointly execute the instructions for executing the method shown in FIG7.

[0141] It should be noted that the memories 902 in different computing devices 900 within the computing device cluster can store different instructions, each used to execute a portion of the functions of the cloud application deployment device 800. That is, the instructions stored in the memories 902 of different computing devices 900 can implement the functions of one or more modules among the acquisition module 801, decision module 802, and deployment module 803.

[0142] In some possible implementations, one or more computing devices in a computing device cluster can be connected via a network. This network can be a wide area network (WAN) or a local area network (LAN), etc. Figure 11 illustrates one possible implementation. As shown in Figure 11, two computing devices 900A and 900B are connected via a network. Specifically, they are connected to the network through communication interfaces in each computing device. In this type of possible implementation, the memory 902 in computing device 900A stores instructions for executing the functions of the acquisition module 801 and the decision module 802. Simultaneously, the memory 902 in computing device 900B stores instructions for executing the functions of the deployment module 803. The connection method between the computing device clusters shown in Figure 11 can be considered because the cloud application deployment method provided in this application requires a large amount of storage and computing resources (e.g., large amounts of data storage). Therefore, it is considered that the functions implemented by the acquisition module 801 and the decision module 802 are executed by computing device 900A, and the functions implemented by the deployment module 803 are executed by computing device 900B. It should be understood that the functions of computing device 900A shown in Figure 11 can also be performed by multiple computing devices 900. Similarly, the functions of computing device 900B can also be performed by multiple computing devices 900.

[0143] This application also provides another computing device cluster. The connection relationship between the computing devices in this computing device cluster can be similar to the connection method of the computing device clusters described in Figures 10 and 11. The difference is that the memory 902 of one or more computing devices 900 in this computing device cluster can store the same instructions for executing the cloud application deployment method shown in Figure 7.

[0144] In some possible implementations, the memory 902 of one or more computing devices 900 in the computing device cluster may also store partial instructions for executing the cloud application deployment method shown in Figure 7. In other words, a combination of one or more computing devices 900 can jointly execute the instructions for executing the cloud application deployment method shown in Figure 7.

[0145] This application also provides a computer program product containing instructions. The computer program product may be a software or program product containing instructions, capable of running on a computing device or stored on any available medium. When the computer program product is run on at least one computing device, it causes the at least one computing device to perform the cloud application deployment method shown in FIG7.

[0146] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a computing device can store, or a data storage device such as a data center that includes one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct the computing device to perform the cloud application deployment method shown in FIG7, or instruct the computing device to perform the cloud application deployment method shown in FIG7.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions 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

1. A cloud application deployment method, characterized by, Applied to a cloud management platform, the cloud management platform is used to manage infrastructure, the infrastructure including multiple regions, each of the multiple regions including at least one computing node, the infrastructure being used to provide cloud resources to users, the method includes: Obtain the resource request input by the user, the resource request including the category, specifications and / or service metrics of the target cloud resource; Based on the resource request, a target region is determined among the plurality of regions, wherein the cloud resources in the target region satisfy the resource request; Deploy the target cloud resources in the target region.

2. The method of claim 1, wherein, Before determining the target region among the plurality of regions based on the resource request, the method further includes: Obtain status information of the multiple regions, including capacity information, specification information and / or service indicator information of cloud resources in each of the multiple regions; Determining the target region among the multiple regions based on the resource request includes: Based on the resource request and the status information, the target region among the multiple regions is determined.

3. The method according to claim 1 or 2, characterized in that, The service metrics include latency metrics, price metrics, and / or carbon emission metrics.

4. The method according to any one of claims 1 to 3, characterized in that, The step of obtaining the resource request input by the user includes: The user is provided with multiple deployment options, each of which includes one or more cloud resource categories and specifications. The cloud resource categories included in the various deployment options are different, and / or the specifications of the same category of cloud resources are different. The system receives first selection information and constraints input by the user. The first selection information is used to indicate the target solution selected by the user among the multiple deployment schemes. The target solution includes the category and specifications of the target cloud resources, and the constraints include the service metrics.

5. The method according to any one of claims 1 to 3, characterized in that, The step of obtaining the resource request input by the user includes: Provide the user with multiple categories of cloud resources and one or more specifications for each cloud resource; The system receives second selection information and constraints input by the user. The second selection information is used to indicate the category and specification of the target cloud resource selected by the user from the plurality of cloud resources and one or more specifications of each cloud resource. The constraints include the service metrics.

6. The method according to claim 4 or 5, characterized in that, Before deploying the target cloud resource in the target region, the method further includes: Determine the resource description template based on the category and specifications of the target cloud resource; Deploying the target cloud resources in the target region includes: The target cloud resources are deployed according to the resource description template using the resource orchestration engine in the target region.

7. A cloud application deployment apparatus characterized by comprising: Applied to a cloud management platform, the cloud management platform is used to manage infrastructure, the infrastructure including multiple regions, each of the multiple regions including at least one computing node, the infrastructure being used to provide cloud resources to users, the device comprising: The acquisition module is used to acquire the resource request input by the user, wherein the resource request includes the category, specifications and / or service indicators of the target cloud resource; A decision module is used to determine a target region among the multiple regions based on the resource request, wherein the cloud resources in the target region satisfy the resource request; The deployment module is used to deploy the target cloud resources in the target region.

8. The apparatus according to claim 7, characterized in that, The acquisition module is further configured to: acquire status information of the multiple regions before the decision module determines the target region in the multiple regions based on the resource request, wherein the status information includes capacity information, specification information and / or service indicator information of cloud resources in each of the multiple regions; The decision module is used to determine the target area among the multiple regions based on the resource request and the status information.

9. The apparatus of claim 7 or 8, wherein, The service metrics include latency metrics, price metrics, and / or carbon emission metrics.

10. The device of any of claims 7-9, wherein, The acquisition module is further configured to: provide the user with multiple deployment schemes, each of the multiple deployment schemes including one or more cloud resource categories and specifications, wherein the cloud resource categories included in the various deployment schemes are different, and / or the specifications of cloud resources of the same category are different; receive first selection information and constraints input by the user, wherein the first selection information is used to indicate the target scheme selected by the user among the multiple deployment schemes, the target scheme including the category and specifications of the target cloud resource, and the constraints including the service indicators.

11. The device of any of claims 7-9, wherein, The acquisition module is further configured to: provide the user with multiple cloud resource categories and one or more specifications of each cloud resource; receive second selection information and constraints input by the user, wherein the second selection information is used to indicate the category and specification of the target cloud resource selected by the user among the multiple cloud resources and one or more specifications of each cloud resource, and the constraints include the service indicators.

12. The apparatus of claim 10 or 11, wherein, The acquisition module is further configured to: determine a resource description template based on the category and specifications of the target cloud resource; the deployment module is further configured to: deploy the target cloud resource according to the resource description template through a resource orchestration engine in the target region.

13. A cluster of computing devices, characterized in that, It includes at least one computing device, each computing device including a processor and 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 to cause the cluster of computing devices to perform the method according to any one of claims 1-6.

14. A computer-readable storage medium, characterized in that, Includes computer program instructions that, when executed by a cluster of computing devices, cause the cluster of computing devices to perform the method as described in any one of claims 1-6.

15. A computer program product, characterised in that, Includes computer program instructions, which, when executed by a cluster of computing devices, perform the method as described in any one of claims 1-6.

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