Cloud resource orchestration method, cloud resource orchestration apparatus, and computing device cluster

Abstract

A cloud resource orchestration method, a cloud resource orchestration apparatus, and a computing device cluster. The method comprises: providing a first code to a user, the first code being generated on the basis of a plurality of second codes, the plurality of second codes being provided by a plurality of cloud platforms, and each second code being used to generate an orchestration model for orchestrating cloud resources; receiving a first orchestration model generated by the user on the basis of the first code, the first orchestration model comprising one or more cloud platform identifiers, the one or more cloud platform identifiers indicating one or more first cloud platforms among the plurality of cloud platforms, and the second code(s) of the one or more first cloud platforms conforming to a first code rule; and according to the first code rule corresponding to the one or more first cloud platforms, converting the first orchestration model into a second orchestration model corresponding to the one or more first cloud platforms, the second orchestration model corresponding to each first cloud platform being used to orchestrate cloud resources of each first cloud platform.

Description

A cloud resource orchestration method, cloud resource orchestration device, and computing device cluster

[0001] This application claims priority to Chinese Patent Application No. 202311676993.X, filed with the State Intellectual Property Office of China on December 5, 2023, entitled “A Cloud Resource Orchestration Method and Apparatus,” the entire contents of which are hereby incorporated by reference into this application. This application also claims priority to Chinese Patent Application No. 202410547654.X, filed with the State Intellectual Property Office of China on April 29, 2024, entitled “A Cloud Resource Orchestration Method, Cloud Resource Orchestration Apparatus, and Computing Device Cluster,” the entire contents of which are hereby incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of computer technology, and in particular to a cloud resource orchestration method, a cloud resource orchestration apparatus, and a computing device cluster. Background Art

[0003] In cloud scenarios, user businesses may require cloud resources from multiple cloud platforms, necessitating resource orchestration across these platforms. However, in the current cloud resource orchestration process, the cloud platform provides the underlying code, and users write resource orchestration models based on the cloud platform code as needed. The cloud platform then orchestrates according to the resource orchestration models. However, due to code differences between different cloud platforms, users need to write multiple resource orchestration models, resulting in redundant work and low resource orchestration efficiency.

[0004] Summary of the Invention

[0005] This application provides a cloud resource orchestration method, a cloud resource orchestration apparatus, and a computing device cluster, which unify the codes used to generate orchestration models on different cloud platforms, thereby improving the efficiency of cloud resource orchestration.

[0006] In a first aspect, the present application provides a cloud resource orchestration method. The method includes: providing a first code to a user, the first code being generated based on multiple second codes, the multiple second codes being provided by multiple cloud platforms, each second code being used to generate an orchestration model for orchestrating cloud resources; receiving a first orchestration model generated by the user based on the first code, the first orchestration model including one or more cloud platform identifiers, the one or more cloud platform identifiers indicating one or more first cloud platforms among the multiple cloud platforms, the second codes of the one or more first cloud platforms conforming to a first code rule; and converting the first orchestration model into a second orchestration model corresponding to the one or more first cloud platforms according to the first code rule corresponding to the one or more first cloud platforms, the second orchestration model corresponding to each first cloud platform being used to orchestrate the cloud resources of each first cloud platform.

[0007] In the above solution, the second codes of each cloud platform are unified into the first code. When users write the orchestration model, they can use the first code to implement the cloud resource orchestration of different cloud platforms without having to pay attention to the differences in the codes of different cloud platforms. This can reduce the user's workload and improve the efficiency of resource orchestration.

[0008] In combination with the first aspect, in a possible implementation, before providing the first code to the user, the method further includes: parsing the second code of each cloud platform based on the first code rule that the second code of each cloud platform complies with to obtain multiple first structure data; aggregating the multiple first structure data to obtain second structure data; and generating the first code based on the second structure data.

[0009] In combination with the first aspect, in a possible implementation, the first structure data includes a first cloud resource identifier and its corresponding data information, and the multiple first structure data are aggregating to obtain the second structure data, including: according to the similarity between the first cloud resource identifiers in the multiple first structure data, the first cloud resource identifiers and their corresponding data information in the multiple first structure data are aggregating to obtain one or more second cloud resource identifiers and their corresponding data information, and the second structure data includes the one or more second cloud resource identifiers and their corresponding data information.

[0010] In combination with the first aspect, in a possible implementation, the data information corresponding to the second cloud resource identifier includes parameters and variables corresponding to the second cloud resource identifier, and the method further includes: aggregating the parameters and variables corresponding to the second cloud resource identifier based on the association relationship between the parameters and variables corresponding to the second cloud resource identifier.

[0011] In combination with the first aspect, in a possible implementation, converting the first orchestration model into the second orchestration model according to the first code rules corresponding to the first cloud platform includes: using an escape algorithm to convert the first orchestration model into a second orchestration model that complies with the first code rules corresponding to the one or more first cloud platforms.

[0012] In combination with the first aspect, in a possible implementation, the first cloud platform provides multiple second codes, and the multiple second codes of the first cloud platform respectively conform to the second code rules of different resource orchestration platforms. The second code rules of the different resource orchestration platforms include the first code rules. The first orchestration model also includes one or more resource orchestration platform identifiers corresponding to the cloud platform identifiers. The method also includes: determining the first code rules corresponding to the one or more first cloud platforms in the second code rules of multiple resource orchestration platforms based on the resource orchestration platform identifiers corresponding to the one or more first cloud platforms.

[0013] In combination with the first aspect, in one possible implementation, before providing the first code to the user, the method further includes: determining a rule description text for each resource orchestration platform; and processing the rule description text for each resource orchestration platform using a language model to obtain a second code rule for each resource orchestration platform.

[0014] In combination with the first aspect, in one possible implementation, before providing the first code to the user, the method further includes: determining a rule description text for each resource orchestration platform; and processing the rule description text for each resource orchestration platform using a language model to obtain a second code rule for each resource orchestration platform.

[0015] In combination with the first aspect, in a possible implementation, the first cloud platform provides a second code, and the method further includes: determining the first code rules corresponding to the one or more first cloud platforms in the third code rules of the multiple cloud platforms based on the one or more cloud platform identifiers.

[0016] In a second aspect, the present application provides a cloud resource orchestration device, which includes a processing module, an interaction module, and a conversion module.

[0017] The processing module is used to generate a first code based on a plurality of second codes, the plurality of second codes are provided by a plurality of cloud platforms, and each second code is used to generate an orchestration model for orchestrating cloud resources.

[0018] The interaction module is used to provide the first code to the user and receive a first orchestration model generated by the user based on the first code, wherein the first orchestration model includes one or more cloud platform identifiers, the cloud platform identifiers indicate one or more first cloud platforms among the multiple cloud platforms, and the second codes of the one or more first cloud platforms comply with the first code rules.

[0019] Among them, the conversion module is used to convert the first orchestration model into a second orchestration model corresponding to one or more first cloud platforms according to the first code rules corresponding to the one or more first cloud platforms, and the second orchestration model corresponding to each first cloud platform is used to orchestrate the cloud resources of each first cloud platform.

[0020] In combination with the second aspect, in a possible implementation, the processing module is specifically used to: parse the second code of each cloud platform based on the first code rule that the second code of each cloud platform complies with to obtain multiple first structure data; aggregate the multiple first structure data to obtain second structure data; and generate the first code based on the second structure data.

[0021] In combination with the second aspect, in a possible implementation, the first structured data includes a first cloud resource identifier and its corresponding data information, and the processing module is specifically used to: aggregate the first cloud resource identifiers and their corresponding data information in the multiple first structured data based on the similarity between the first cloud resource identifiers in the multiple first structured data to obtain one or more second cloud resource identifiers and their corresponding data information, and the second structured data includes the one or more second cloud resource identifiers and their corresponding data information.

[0022] In combination with the second aspect, in a possible implementation, the data information corresponding to the second cloud resource identifier includes parameters and variables corresponding to the second cloud resource identifier, and the processing module is also used to: aggregate the parameters and variables corresponding to the second cloud resource identifier based on the association relationship between the parameters and variables corresponding to the second cloud resource identifier.

[0023] In conjunction with the second aspect, in a possible implementation, the conversion module is specifically configured to: utilize an escape algorithm to convert the first orchestration model into a second orchestration model that complies with first code rules corresponding to the one or more first cloud platforms.

[0024] In combination with the second aspect, in a possible implementation, the multiple second codes of the first cloud platform respectively conform to the second code rules of different resource orchestration platforms, the second code rules of the different resource orchestration platforms include the first code rule, the first orchestration model also includes a resource orchestration platform identifier, and the conversion module is further used to: determine the first code rule in the second code rules of multiple resource orchestration platforms according to the resource orchestration platform identifier.

[0025] In conjunction with the second aspect, in one possible implementation, before providing the first code to the user, the processing module is further used to: determine the rule description text of each resource orchestration platform; and use a language model to process the rule description text of each resource orchestration platform to obtain the second code rules of each resource orchestration platform.

[0026] In combination with the second aspect, in a possible implementation, the first cloud platform provides a second code, and the conversion module is further used to: determine the first code rule among the third code rules of the multiple cloud platforms according to the cloud platform identifier.

[0027] In combination with the second aspect, in a possible implementation, before providing the first code to the user, the processing module is also used to: determine the rule description text of each cloud platform; use the language model to process the rule description text of each cloud platform to obtain the third code rules of each cloud platform.

[0028] In a third aspect, the present application further provides a computing device cluster. The computing device cluster 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 configured to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster performs the method of any possible implementation of the first aspect and any combination thereof.

[0029] In a fourth aspect, the present application further provides a computer-readable storage medium comprising instructions, which, when executed on a computer, enable the computer to implement the method in any possible implementation of the first aspect and any combination thereof.

[0030] In a fifth aspect, the present application further provides a computer program product, which includes instructions, and when the instructions are executed on a computer, causes the computer to implement the method in any possible implementation of the first aspect and any combination thereof.

[0031] Any of the above-mentioned devices, computing device clusters, computer storage media, or computer program products is used to execute the method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding schemes in the corresponding methods provided above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] FIG1 is a schematic diagram of a cloud resource orchestration scenario provided by an embodiment of the present application;

[0033] FIG2 is a schematic diagram of another cloud resource orchestration scenario provided by an embodiment of the present application;

[0034] FIG3 is a flowchart of a cloud resource orchestration method based on the scenarios shown in FIG1 and FIG2 , provided in an embodiment of the present application;

[0035] FIG4 is a schematic diagram of obtaining code rules in the method shown in FIG3 according to an embodiment of the present application;

[0036] 5a to 5c are schematic diagrams of aggregating structured data of multiple second codes according to an embodiment of the present application;

[0037] FIG6 is a flowchart of another cloud resource orchestration method provided by an embodiment of the present application;

[0038] 7 and 8 are schematic diagrams of a cloud resource orchestration scenario using the method shown in FIG. 6 , provided in an embodiment of the present application;

[0039] FIG9 is a schematic structural diagram of a cloud resource orchestration device based on the method shown in FIG3 and FIG6 according to an embodiment of the present application;

[0040] FIG10 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application;

[0041] FIG11 is a schematic diagram of the structure of a computing device cluster provided in an embodiment of the present application;

[0042] FIG12 is a schematic diagram of a connection method between computing devices in the computing device cluster shown in FIG11 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

[0044] In the description of the embodiments of the present application, words such as "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of the present application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0045] In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the term "plurality" means two or more. For example, "multiple systems" refers to two or more systems, and "multiple screen terminals" refers to two or more screen terminals.

[0046] 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 identifying the technical features being referred to. Thus, features specified as "first" or "second" may explicitly or implicitly include one or more of such features. The terms "include," "comprising," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0047] Infrastructure as code (IAC) is a method for automating the configuration and management of infrastructure.

[0048] Cloud resource orchestration is the automated creation, configuration, deployment, and management of cloud resources on a cloud platform through IAC.

[0049] An orchestration framework is a tool provided by the cloud platform for writing resource orchestration models (or resource orchestration templates). An orchestration framework can include defined code components, program interfaces, and / or protocols. Different orchestration frameworks conform to different coding rules.

[0050] The second code is the resource code module provided by the cloud platform to users. This resource code module may include templates and / or application programming interfaces (APIs) for implementing cloud resource orchestration. Users can write resource orchestration models for the cloud platform based on the second code. Using the second code to write resource orchestration models can improve cloud resource orchestration efficiency and reduce operation and maintenance costs. The second code can be generated according to the cloud platform's orchestration framework or a unified orchestration framework.

[0051] The resource orchestration platform is used to provide users with cloud resource orchestration services in multi-cloud scenarios. Specifically, the resource orchestration platform provides a unified orchestration framework to multiple cloud platforms, and each cloud platform provides its own second code based on this unified orchestration framework. Users obtain the second code of each cloud platform through the resource orchestration platform, and then generate a resource orchestration model for each cloud platform based on the second code of each cloud platform. The resource orchestration platform interacts with the cloud platform according to the resource orchestration model compiled by the user to complete the cloud resource orchestration of that cloud platform.

[0052] The first code is a resource code module generated by the resource orchestration platform by unifying the second codes of multiple cloud platforms. In a multi-cloud scenario, users can generate a first resource orchestration model based on the first code. The resource orchestration platform can then convert this first resource orchestration model into a second resource orchestration model for one or more cloud platforms and orchestrate cloud resources for each cloud platform according to the second resource orchestration model.

[0053] In some complex cloud scenarios, users may need to rely on cloud resources from multiple cloud platforms to jointly support the stable operation of their business. To achieve this goal, users need to orchestrate cloud resources from different cloud platforms.

[0054] Related technology 1: Users write resource orchestration models for each cloud platform according to the orchestration framework provided by each cloud platform, and each cloud platform orchestrates cloud resources according to the resource orchestration models written by users.

[0055] In the above solution, in a multi-cloud scenario, different cloud platforms may have different orchestration frameworks, including different code components and / or different programming interfaces. This requires users to write resource orchestration models for each cloud platform according to their respective orchestration frameworks, which increases the writing workload.

[0056] Related technology 2: Different cloud platforms provide users with resource code modules according to the unified orchestration framework defined by the resource orchestration platform. Users can write resource orchestration models for each cloud platform based on the resource code modules of each cloud platform, and then execute the resource orchestration models of each cloud platform through the resource orchestration platform, so that the resource orchestration platform can interact with each cloud platform and automatically orchestrate the cloud resources of each cloud platform.

[0057] In the above solution, by unifying the orchestration framework of the cloud platforms through the resource orchestration platform, users can avoid the need to have an in-depth understanding of the orchestration framework of each cloud platform, thereby reducing the complexity of the user's orchestration work. However, there are still differences between the resource code modules of different cloud platforms (for example, the cloud resources in the resource code modules of different cloud platforms may be different, and / or the parameters, variables and / or data of the same cloud resource in the resource code modules of different cloud platforms may be different). In a multi-cloud scenario, users need to consider the differences in the resource code modules of different cloud platforms to write resource orchestration models for different cloud platforms. The user's workload is redundant and the resource orchestration efficiency is not high.

[0058] To this end, an embodiment of the present application provides a cloud resource orchestration method that can solve the above-mentioned problems.

[0059] In the cloud resource orchestration method provided in an embodiment of the present application, a first code is generated by aggregating second codes based on different cloud platforms. After a user generates a first orchestration model based on the first code, the first orchestration model is converted into a second orchestration model that conforms to the first code rules corresponding to the first cloud platform indicated by the cloud platform identifier, based on the cloud platform identifier in the first orchestration model. By unifying the resource codes of different cloud platforms, this method allows users to write resource code models without having to consider the differences between resource codes of different cloud platforms, thereby improving user writing efficiency and enhancing the user experience.

[0060] Figure 1 is a schematic diagram of a cloud resource orchestration scenario provided by an embodiment of the present application. As shown in Figure 1, the scenario includes a processing platform 1, at least one resource orchestration platform (for example, resource orchestration platform 1 and resource orchestration platform 2 in Figure 1), and multiple cloud platforms (for example, cloud platforms 1 to 3 in Figure 1). Among them, each resource orchestration platform interacts with at least one cloud platform, and the cloud platforms interacted with by each resource orchestration platform may include the same cloud platform and / or different cloud platforms. For example, as shown in Figure 1, resource orchestration platform 1 interacts with cloud platform 1 and cloud platform 2, and resource orchestration platform 2 interacts with cloud platform 1 and cloud platform 3.

[0061] The cloud platform publishes the resource code module (i.e., the second code) according to the unified orchestration framework defined by the resource orchestration platform with which it interacts. Since different resource orchestration platforms define different orchestration frameworks, the second codes published by different cloud platforms and / or the same cloud platform based on different orchestration frameworks are also different. For example, as shown in Figure 1, cloud platform 1 and cloud platform 2 publish second code 1 and second code 2 respectively according to orchestration framework 1 defined by resource orchestration platform 2, and cloud platform 1 and cloud platform 3 publish second code 3 and second code 4 respectively according to orchestration framework 2 defined by resource orchestration platform 2. Any two second codes among second code 1, second code 2, second code 3, and second code 4 are not the same. In the above-mentioned related technologies, users can use the second code of the cloud platform to write the resource orchestration model of the cloud platform, thereby orchestrating the cloud resources of the cloud platform based on the resource orchestration model of the cloud platform.

[0062] Processing platform 1 abstracts and aggregates the second codes published on various resource orchestration platforms to generate a unified first code and provides it to users. For example, as shown in Figure 1, processing platform 1 abstracts and aggregates second code 1, second code 2, second code 3, and second code 4 to generate the first code.

[0063] Users can obtain a unified first code through processing platform 1 and write one or more first orchestration models based on the cloud resource orchestration requirements of a multi-cloud scenario. Each orchestration model is used to orchestrate cloud resources for a cloud platform. After the user writes and generates the first orchestration model, processing platform 1 converts the first orchestration model, as illustrated below with reference to Figure 2.

[0064] Figure 2 is a schematic diagram of another cloud resource orchestration scenario provided by an embodiment of the present application. As shown in Figure 2, a user generates a first orchestration model by writing a first code. The first orchestration model includes cloud platform identifier 1 and cloud platform identifier 3, as well as resource orchestration platform identifier 1 corresponding to cloud platform identifier 1, and resource orchestration platform identifier 2 corresponding to cloud platform identifier 3. Cloud platform identifier 1 indicates cloud platform 1, and cloud platform identifier 3 indicates cloud platform 3. Resource orchestration platform identifier 1 indicates resource orchestration platform 1, and resource orchestration platform identifier 2 indicates resource orchestration platform 2.

[0065] Processing platform 1 can convert the first orchestration model into the second orchestration model 1 according to the first code rule corresponding to cloud platform 1, and convert the first orchestration model into the second orchestration model 2 according to the first code rule corresponding to cloud platform 3. Then, resource orchestration platform 1 orchestrates the cloud resources of cloud platform 1 according to the second orchestration model 1, and resource orchestration platform 2 orchestrates the cloud resources of cloud platform 3 according to the second orchestration model 2.

[0066] The cloud resource orchestration method provided in the embodiment of the present application is described in detail below with reference to FIG3 .

[0067] Figure 3 is a flow chart of a cloud resource orchestration method provided by an embodiment of the present application. This method can be applied to the processing platform 1 shown in Figures 1 and 2. The processing platform 1 may include a server in a cloud service system and may also include a user's terminal device.

[0068] As shown in FIG3 , the method may include the following S301 - S303 .

[0069] S301: The processing platform 1 generates a first code based on the second codes of multiple cloud platforms and provides it to the user.

[0070] The second codes of multiple cloud platforms are different, but they are all generated based on the orchestration framework of the resource orchestration platform. The orchestration framework of the resource orchestration platform complies with the second code rules of the resource orchestration platform. Therefore, the second code of each cloud platform is generated based on the second code rules of the resource orchestration platform with which it interacts. Therefore, processing platform 1 can parse and aggregate the second codes of the cloud platforms it interacts with according to the second code rules of each resource orchestration platform to generate the first code.

[0071] Processing platform 1 can process the rule description text of each resource orchestration platform using a language model to obtain the second code rules of each resource orchestration platform, and then convert the second code rules of each resource orchestration platform into a code language and embed them into the rule base. The second code rules of the resource orchestration platform may include IAC rules such as resource rules, data source rules, schema definition rules, parameter declaration rules, operation (e.g., plan / apply / schedule / main / outputs) rules, resource release rules, and inspection rules. The schema is used to describe information such as the structure, attributes, type, range, and default values ​​of data, ensuring data consistency and validity. For example, as shown in Figure 4, processing platform 1 can input the rule description text of resource orchestration platform 1 and the rule description text of resource orchestration platform 2 into a pre-trained language model. Through processing with the language model, the code rules of resource orchestration platform 1 and resource orchestration platform 2 can be obtained. Using the language model, the processing platform can summarize and generalize the code rules from the rule description text, thereby parsing the second code based on the code rules.

[0072] Among them, the language model can be trained using a pre-acquired training sample set. The training sample set includes multiple rule description samples and corresponding code rule samples. During the training process, the rule description sample can be input into the language model, and the loss value can be calculated based on the output of the language model and the code rule sample corresponding to the rule description sample. Then, the parameters of the language model are updated according to the loss value until the loss value meets the preset threshold. It should be noted that the embodiments of the present application do not impose specific restrictions on the structure and training method of the language model.

[0073] In the case where processing platform 1 is a server, the user can send the rule description text of each resource orchestration platform to the server through the terminal device, or the server can obtain the rule description text of each resource orchestration platform from each resource orchestration platform. In the case where processing platform 1 is a terminal device, the user can obtain the rule description text of each resource orchestration platform from each resource orchestration platform through the terminal device.

[0074] After obtaining the second code rules of each resource orchestration platform, processing platform 1 can parse the second code of the cloud platform that interacts with each resource orchestration platform based on the second code rules of each resource orchestration platform to obtain multiple abstract first structure data. One second code corresponds to one first structure data. Taking Figure 2 as an example, processing platform 1 parses the second code 1 of cloud platform 1 and the second code 2 of cloud platform 2 based on the second code rules of resource orchestration platform 1, and parses the second code 3 of cloud platform 1 and the second code 4 of cloud platform 3 based on the second code rules of resource orchestration platform 2, so that four first structure data can be obtained. Among them, in the case where processing platform 1 is a server, the user can send the second code of each cloud platform to the server through the terminal device, or the server can obtain the second code of each cloud platform from each resource orchestration platform. In the case where processing platform 1 is a terminal device, the user can obtain the second code of each cloud platform from each resource orchestration platform through the terminal device.

[0075] Processing platform 1 may aggregate multiple first structured data to obtain second structured data. Processing platform 1 may generate a first code based on the second structured data according to a fourth code rule. Each first structured data may include at least one first cloud resource identifier and its corresponding data information, and the second structured data may include one or more second cloud resource identifiers and their corresponding data information.

[0076] Specifically, the processing platform 1 can aggregate the first cloud resource identifiers and their corresponding data information in multiple first structure data based on the similarity and similarity threshold between the first cloud resource identifiers in multiple first structure data to obtain one or more second cloud resource identifiers and their corresponding data information.

[0077] Taking the first cloud resource identifier as an elastic compute service (ECS) instance as an example, Figure 5a shows the elastic compute service identifiers in the four first structure data, namely wcloud_ecs_instance, xcloud_ecs_instance, ycloud_ecs_instance, and zcloud_ecs_instance. The processing platform 1 can aggregate the four elastic compute service instance identifiers when the similarity of the four elastic compute service instance identifiers is greater than the similarity threshold to obtain a second cloud resource identifier, such as ecs_instance. The similarity calculation of the cloud resource identifiers can aggregate the data information corresponding to similar cloud resource identifiers in the structure data, which can help users use the data information corresponding to the cloud resource identifiers and improve the efficiency of model writing. When calculating the similarity, methods that help quantify the similarity between texts can be used, such as but not limited to statistical distance metrics, cosine similarity, or Jaccard similarity.

[0078] The data information may include module identification, mode identification, and function identification, etc. The module, mode, and function indicated by the module identification, mode identification, and function identification include data elements such as parameters, variables, and configuration values.

[0079] The data information corresponding to the second cloud resource identifier includes the data information corresponding to the first cloud resource identifier before aggregation. Taking the second cloud resource identifier as ecs_instance as an example, the data information corresponding to the second cloud resource identifier includes the data information corresponding to wcloud_ecs_instance, xcloud_ecs_instance, ycloud_ecs_instance, and zcloud_ecs_instance. Processing platform 1 can also aggregate the data elements corresponding to the second cloud resource identifier based on the association relationship between the data elements corresponding to the second cloud resource identifier.

[0080] Taking the schema as an example, Figure 5b shows three schemas, including schema1, schema2 and schema3. Schema1 includes parameters A, B, and C, schema2 includes parameters A and B, and schema3 includes parameters B, C, and D. Schema1 and schema2 have associated A and B, schema2 and schema3 have associated B, and schemaschema2 and schema3 have associated B. Processing platform 1 can aggregate the parameters of schema1, schema2, and schema3 into parameters A, B, C, and D.

[0081] Taking the output function outputs as an example, Figure 5c shows three outputs, including outputs1, outputs2, and outputs2. The two outputs2 come from different second codes, outputs1 includes parameter E1, and the two outputs2 include parameters E2 and E1, E3 respectively. The two outputs2 can be aggregated into one outputs2. There is an associated E1 between outputs1 and outputs2. The processing platform 1 can aggregate the parameters in outputs1, outputs2, and outputs3 into E1, E2, and E3.

[0082] At step S302, processing platform 1 receives a first orchestration model written by a user based on a first code. The first orchestration model includes one or more cloud platform identifiers and resource orchestration platform identifiers corresponding to the one or more cloud platform identifiers. The cloud platform identifier indicates a first cloud platform among multiple cloud platforms, and the resource orchestration platform identifier indicates a first resource orchestration platform among the multiple resource orchestration platforms. The first resource orchestration platform is connected to the first cloud platform.

[0083] The user can write a first orchestration model based on the first code provided by processing platform 1 according to the cloud resource orchestration requirements of the actual multi-cloud scenario. For example, when the user needs to orchestrate the cloud resources of cloud platform 1 through resource orchestration platform 1 and orchestrate the cloud resources of cloud platform 3 through resource orchestration platform 2, as shown in Figure 2, the first orchestration model can be written and generated based on the first code. The first orchestration model includes cloud platform identifier 1 and cloud platform identifier 3, as well as resource orchestration platform identifier 1 corresponding to cloud platform identifier 1 and resource orchestration platform identifier 2 corresponding to cloud platform identifier 3. Resource orchestration platform identifier 1 indicates resource orchestration platform 1, and resource orchestration platform identifier 2 indicates resource orchestration platform 2.

[0084] S303: Processing platform 1 converts the first orchestration model into a second orchestration model corresponding to one or more first cloud platforms according to the first code rules corresponding to the one or more first cloud platforms.

[0085] Processing platform 1 determines the first code rules corresponding to each first cloud platform in the second code rules of each resource orchestration platform recorded in the rule library based on the resource orchestration platform identifier corresponding to the cloud platform identifier in the first orchestration model, wherein the second code provided by the first cloud platform complies with the first code rule, and the second code rules of multiple resource orchestration platforms include the first code rule.

[0086] Specifically, taking the first orchestration model shown in Figure 2 as an example, it includes cloud platform identifier 1, cloud platform identifier 3, and resource orchestration platform identifier 1 corresponding to cloud platform identifier 1, and resource orchestration platform identifier 2 corresponding to cloud platform identifier 3. Processing platform 1 can determine, based on resource orchestration platform identifier 1 corresponding to cloud platform identifier 1, that the first coding rule corresponding to cloud platform 1 indicated by cloud platform identifier 1 is the second coding rule of resource orchestration platform 1. Furthermore, based on resource orchestration platform identifier 2 corresponding to cloud platform identifier 3, processing platform 1 can determine that the first coding rule corresponding to cloud platform 3 is the second coding rule of resource orchestration platform 2.

[0087] After determining the first code rule, processing platform 1 uses an escape algorithm to convert the first orchestration model into a second orchestration model corresponding to each first cloud platform. The second orchestration model complies with the first code rule corresponding to each first cloud platform. Taking second orchestration model 1 and second orchestration model 2 shown in Figure 2 as an example, second orchestration model 1 complies with the second code rule of resource orchestration platform 1, and cloud platform 1 can recognize second orchestration model 1. Second orchestration model 2 complies with the second code rule of resource orchestration platform 2, and cloud platform 3 can recognize second orchestration model 2.

[0088] Based on the embodiments shown in FIG. 1 , FIG. 2 , and FIG. 5 , the embodiment of the present application also provides another cloud resource configuration method.

[0089] FIG6 is a flow chart of a cloud resource configuration method provided by an embodiment of the present application. This method can be applied to the resource orchestration platform 3 shown in FIG7 and / or the processing platform 2 shown in FIG8.

[0090] In the scenario shown in Figure 7, cloud platform 1 and cloud platform 2 publish the second code based on the orchestration framework 3 of resource orchestration platform 3, and the second code published by cloud platform 1 and cloud platform 2 complies with the first code rule of resource orchestration platform 3.

[0091] In the scenario shown in Figure 8, cloud platform 1 and cloud platform 2 publish the second code based on their respective orchestration frameworks. The second code published by cloud platform 1 and cloud platform 2 complies with the third code rules of their respective cloud platforms. The orchestration frameworks of cloud platform 1 and cloud platform 2 are different, and the third code rules of cloud platform 1 and cloud platform 2 are different.

[0092] As shown in FIG. 6 , the method may include S601 - S603 .

[0093] S601: Generate a first code based on second codes provided by multiple cloud platforms and provide the first code to a user.

[0094] S602: Receive a first orchestration model written by a user based on a first code, where the first orchestration model includes one or more cloud platform identifiers.

[0095] It should be noted that in the scenario shown in Figure 7, resource orchestration platform 3 parses the second code based on its third code rule to obtain structured data. Specifically, resource orchestration platform 3 can process the rule description text of resource orchestration platform 3 using a language model with reference to Figure 4 to obtain the third code rule of resource orchestration platform 3. Unlike the embodiment shown in Figure 3, the first orchestration model of the embodiment shown in Figure 6 does not include a resource orchestration platform identifier.

[0096] In the scenario shown in Figure 8, processing platform 2 parses the second code of each cloud platform based on the third code rule of each cloud platform to obtain structured data. Processing platform 2 obtains the third code rule of each cloud platform by processing the rule description text of each cloud platform using a language model, as shown in Figure 4.

[0097] S603: Convert the first orchestration model into a second orchestration model corresponding to one or more first cloud platforms according to the first code rules corresponding to the one or more first cloud platforms.

[0098] In the scenario shown in Figure 7, the first code rule corresponding to the first cloud platform is the first code rule of resource orchestration platform 3. Resource orchestration platform 3 can directly perform conversion based on the first code rule. After the conversion is successful, resource orchestration platform 3 can interact with cloud platform 1 and cloud platform 2 based on cloud platform 1's second orchestration model 1 and cloud platform 2's second orchestration model 2, respectively, to complete resource orchestration.

[0099] In the scenario shown in Figure 8, the first coding rule corresponding to the first cloud platform is the third coding rule of the first cloud platform. Processing platform 2 can determine the third coding rule of the first cloud platform based on the cloud platform identifier in the model and then perform the conversion. After the conversion is successful, processing platform 2 can feedback the second orchestration model 1 of cloud platform 1 and the second orchestration model 2 of cloud platform 2 to the user.

[0100] The specific process of the above S601 to S603 can refer to the introduction of S301 to S303 in Figure 3 above, and will not be repeated here.

[0101] Based on the method embodiments shown in FIG3 and FIG6 , an embodiment of the present application further provides a cloud resource orchestration device.

[0102] FIG9 is a schematic diagram of the structure of a cloud resource orchestration device 900 provided in an embodiment of the present application. As shown in FIG9 , the cloud resource orchestration device 900 includes a processing module 901 , an interaction module 902 , and a conversion module 903 .

[0103] The processing module 901 is used to generate a first code based on a plurality of second codes, where the plurality of second codes are provided by a plurality of cloud platforms, and each second code is used to generate an orchestration model for orchestrating cloud resources.

[0104] Among them, the interaction module 902 is used to provide the first code to the user, and receive a first orchestration model generated by the user based on the first code, where the first orchestration model includes one or more cloud platform identifiers, and the one or more cloud platform identifiers indicate one or more first cloud platforms among the multiple cloud platforms, and the second codes of the one or more first cloud platforms comply with the first code rules.

[0105] Among them, the conversion module 903 is used to convert the first orchestration model into a second orchestration model corresponding to one or more first cloud platforms according to the first code rules corresponding to one or more first cloud platforms, and the second orchestration model corresponding to each first cloud platform is used to orchestrate the cloud resources of each first cloud platform.

[0106] The processing module 901, the interaction module 902, and the conversion module 903 can all be implemented in software or hardware. For example, the implementation of the processing module 901 will be described below using the processing module 901 as an example. Similarly, the implementation of the interaction module 902 and the conversion module 903 can be similar to the implementation of the processing module 901.

[0107] As an example of a software functional unit, the processing module 901 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, the processing module 901 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 geographically close data centers. Typically, a region may include multiple AZs.

[0108] Similarly, multiple hosts / virtual machines / containers running the code can be distributed within the same virtual private cloud (VPC) or across multiple VPCs. Typically, a VPC is set up within a region. Cross-region communication between two VPCs within the same region, or between VPCs in different regions, requires a communication gateway within each VPC to interconnect the VPCs.

[0109] As an example of a hardware functional unit, processing module 901 may include at least one computing device, such as a server. Alternatively, module A may be 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.

[0110] The multiple computing devices included in processing module 901 can be distributed in the same region or in different regions. The multiple computing devices included in processing module 901 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in processing module 901 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices can be any combination of servers, ASICs, PLDs, CPLDs, FPGAs, GALs, and other computing devices.

[0111] It should be noted that the cloud resource orchestration device 900 provided in the embodiment shown in FIG9 only uses the division of the above-mentioned functional modules as an example to illustrate when executing the cloud resource orchestration method. In actual applications, the above-mentioned 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 resource orchestration device provided in the above embodiment and the cloud resource orchestration method embodiment shown in FIG3 or FIG6 are of the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0112] FIG10 is a schematic diagram of the hardware structure of a computing device 1000 provided in an embodiment of the present application.

[0113] The computing device 1000 can be the aforementioned server or a user's terminal device. Referring to FIG10 , the computing device 1000 includes a processor 1001, a memory 1002, a communication interface 1003, and a bus 1004. The processor 1001, the memory 1002, and the communication interface 1003 are interconnected via the bus 1004. The processor 1001, the memory 1002, and the communication interface 1003 can also be connected using other connection methods besides the bus 1004.

[0114] Processor 1001 may be a general-purpose processor, which may be a processor that performs specific steps and / or operations by reading and executing content stored in a memory (e.g., memory 1002). For example, a general-purpose processor may be a central processing unit (CPU). Processor 1001 may include at least one circuit to execute all or part of the steps of the cloud resource orchestration method provided in the embodiments shown in FIG. 2 or FIG. 5 .

[0115] The memory 1002 may be any type of storage medium, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), flash memory, optical storage, a hard disk, etc. The memory 1002 stores executable program code, and the processor 1001 executes the executable program code to respectively implement the functions of the aforementioned processing module 901, interaction module 902, and conversion module 903, thereby implementing the method shown in FIG. 3 or FIG. 6 . That is, the memory 1002 stores instructions for executing the method shown in FIG. 3 or FIG. 6 .

[0116] Communication interface 1003 includes input / output (I / O) interfaces, physical interfaces, and logical interfaces, which are used to interconnect components within computing device 1000, as well as interfaces for interconnecting computing device 1000 with other devices (e.g., other computing devices or user equipment). Physical interfaces can include Ethernet interfaces, fiber optic interfaces, ATM interfaces, and the like.

[0117] The bus 1004 may be any type of communication bus for interconnecting the processor 1001 , the memory 1002 , and the communication interface 1003 , such as a system bus.

[0118] The above-mentioned devices can be provided on separate chips, or at least partially or entirely on the same chip. Whether to provide each device independently on different chips or to integrate them on one or more chips often depends on the product design requirements. The embodiments of this application do not limit the specific implementation of the above-mentioned devices.

[0119] The computing device 1000 shown in FIG10 is merely exemplary. During implementation, the computing device 1000 may further include other components, which are not listed one by one herein.

[0120] Embodiments of the present application also provide a computing device cluster. 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 computer, a laptop computer, or a smartphone.

[0121] As shown in Figure 11, the computing device cluster includes at least one computing device 1000. The memory 1002 in one or more computing devices 1000 in the computing device cluster may store the same instructions for executing the method shown in Figure 3 or Figure 6.

[0122] In some possible implementations, the memory 1002 of one or more computing devices 1000 in the computing device cluster may also respectively store some instructions for executing the method shown in Figure 3 or Figure 6. In other words, the combination of one or more computing devices 100 may collectively store instructions for executing the method shown in Figure 3 or Figure 6.

[0123] It should be noted that the memory 1002 in different computing devices 1000 in the computing device cluster can store different instructions, each for executing part of the functions of the apparatus shown in Figure 9. In other words, the instructions stored in the memory 1002 in different computing devices 1000 can implement the functions of one or more modules in the apparatus shown in Figure 9.

[0124] In some possible implementations, one or more computing devices in a computing device cluster may be connected via a network. The network may be a wide area network or a local area network, etc. FIG12 shows a possible implementation. As shown in FIG12 , two computing devices 1000A and 1000B are connected via a network. Specifically, the connection to the network is made via a communication interface in each computing device. In this type of possible implementation, the memory 1002 in the computing device 1000A stores instructions for executing the functions of the processing module 901. At the same time, the memory 1002 in the computing device 1000B stores instructions for executing the functions of the interaction module 902 and the conversion module 903.

[0125] The connection method between the computing device clusters shown in Figure 12 can be considered to take into account the needs of the method shown in Figure 3 or Figure 6 provided in this application (for example, storing a large amount of second code), so it is considered to entrust the functions implemented by the interaction module 902 and the conversion module 903 to the computing device 1000B for execution.

[0126] It should be understood that the functionality of the computing device 1000A shown in FIG12 may also be accomplished by multiple computing devices 1000. Similarly, the functionality of the computing device 1000B may also be accomplished by multiple computing devices 1000.

[0127] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes 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 (SSD)).

[0128] It is understood that the various numerical numbers involved in the embodiments of the present application are only for the convenience of description and are not intended to limit the scope of the embodiments of the present application. It should be understood that in the embodiments of the present application, the order of the sequence numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0129] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of this application in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of this application. Any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solutions of this application should be included in the scope of protection of this application.

Claims

1. A cloud resource orchestration method, characterized in that: The method comprises: Providing a first code to a user, where the first code is generated based on a plurality of second codes, where the plurality of second codes are provided by a plurality of cloud platforms, and each second code is used to generate an orchestration model for orchestrating cloud resources; receiving a first orchestration model generated by the user based on the first code, wherein the first orchestration model includes one or more cloud platform identifiers, the one or more cloud platform identifiers indicate one or more first cloud platforms among the multiple cloud platforms, and the second codes of the one or more first cloud platforms comply with a first code rule; According to the first code rules corresponding to the one or more first cloud platforms, the first orchestration model is converted into a second orchestration model corresponding to the one or more first cloud platforms, and the second orchestration model corresponding to each first cloud platform is used to orchestrate the cloud resources of each first cloud platform.

2. The method according to claim 1, characterized in that Before providing the first code to the user, the method further includes: Based on the first code rule that the second code of each cloud platform complies with, the second code of each cloud platform is parsed to obtain a plurality of first structure data; Aggregating the plurality of first structured data to obtain second structured data; The first code is generated according to the second structure data.

3. The method according to claim 2, characterized in that The first structure data includes a first cloud resource identifier and corresponding data information. The plurality of first structure data are aggregated to obtain second structure data including: According to the similarity between the first cloud resource identifiers in the multiple first structure data, the first cloud resource identifiers and the corresponding data information in the multiple first structure data are aggregated to obtain one or more second cloud resource identifiers and the corresponding data information, and the second structure data includes the one or more second cloud resource identifiers and the corresponding data information.

4. The method according to claim 3, characterized in that The data information corresponding to the second cloud resource identifier includes parameters and variables corresponding to the second cloud resource identifier, and the method further includes: The parameters and variables corresponding to the second cloud resource identifier are aggregated according to the association relationship between the parameters and the variables corresponding to the second cloud resource identifier.

5. The method according to any one of claims 1 to 4, characterized in that: The converting the first orchestration model into a second orchestration model corresponding to the one or more first cloud platforms according to the first code rules corresponding to the one or more first cloud platforms includes: The first orchestration model is converted into a second orchestration model that complies with first code rules corresponding to the one or more first cloud platforms by using an escape algorithm.

6. The method according to any one of claims 1 to 5, characterized in that: The first cloud platform provides a plurality of second codes, the plurality of second codes of the first cloud platform respectively conform to second code rules of different resource orchestration platforms, the first orchestration model also includes a resource orchestration platform identifier corresponding to the one or more cloud platform identifiers, and the method further includes: According to the resource orchestration platform identifiers corresponding to the one or more cloud platform identifiers, first code rules corresponding to the one or more first cloud platforms are determined from second code rules of multiple resource orchestration platforms.

7. The method according to claim 6, characterized in that Before providing the first code to the user, the method further includes: Determine the rule description text for each resource orchestration platform; The rule description texts of the various resource orchestration platforms are processed by using a language model to obtain second code rules of the various resource orchestration platforms.

8. The method according to any one of claims 1 to 5, characterized in that: The first cloud platform provides a second code, and the method further includes: The first code rules corresponding to the one or more first cloud platforms are determined from the third code rules of the multiple cloud platforms according to the one or more cloud platform identifiers.

9. The method according to claim 8, characterized in that Before providing the first code to the user, the method further includes: Determine the rule description text for each cloud platform; The rule description texts of the respective cloud platforms are processed by using a language model to obtain third code rules of the respective cloud platforms.

10. A cloud resource orchestration device, characterized in that: The device comprises: A processing module, configured to generate a first code based on a plurality of second codes, wherein the plurality of second codes are provided by a plurality of cloud platforms, and each second code is configured to generate an orchestration model for orchestrating cloud resources; an interaction module, configured to provide the first code to a user, and receive a first orchestration model generated by the user based on the first code, wherein the first orchestration model includes one or more cloud platform identifiers, the one or more cloud platform identifiers indicate one or more first cloud platforms among the multiple cloud platforms, and the second codes of the one or more first cloud platforms conform to the first code rule; A conversion module is used to convert the first orchestration model into a second orchestration model corresponding to the one or more first cloud platforms according to the first code rules corresponding to the one or more first cloud platforms, and the second orchestration model corresponding to each first cloud platform is used to orchestrate the cloud resources of each first cloud platform.

11. The device according to claim 10, characterized in that The processing module is specifically used for: Based on the first code rule that the second code of each cloud platform complies with, the second code of each cloud platform is parsed to obtain a plurality of first structure data; Aggregating the plurality of first structured data to obtain second structured data; The first code is generated according to the second structure data.

12. The device according to claim 11, characterized in that The first structure data includes a first cloud resource identifier and corresponding data information, and the processing module is specifically used to: According to the similarity between the first cloud resource identifiers in the multiple first structure data, the first cloud resource identifiers and the corresponding data information in the multiple first structure data are aggregated to obtain one or more second cloud resource identifiers and the corresponding data information, and the second structure data includes the one or more second cloud resource identifiers and the corresponding data information.

13. The device according to claim 12, characterized in that The data information corresponding to the second cloud resource identifier includes parameters and variables corresponding to the second cloud resource identifier, and the processing module is further used to: The parameters and variables corresponding to the second cloud resource identifier are aggregated according to the association relationship between the parameters and the variables corresponding to the second cloud resource identifier.

14. The device according to any one of claims 10 to 13, characterized in that: The conversion module is specifically used for: The first orchestration model is converted into a second orchestration model that complies with first code rules corresponding to the one or more first cloud platforms by using an escape algorithm.

15. The device according to any one of claims 10 to 14, characterized in that: The first cloud platform provides a plurality of second codes, the plurality of second codes of the first cloud platform respectively conform to second code rules of different resource orchestration platforms, the second code rules of the different resource orchestration platforms include the first code rules, the first orchestration model also includes a resource orchestration platform identifier corresponding to the one or more cloud platform identifiers, and the conversion module is further used to: The first code rules corresponding to the one or more first cloud platforms are determined from the second code rules of multiple different resource orchestration platforms according to the resource orchestration platform identifiers corresponding to the one or more cloud platform identifiers.

16. The device according to claim 15, characterized in that Before providing the first code to the user, the processing module is further used for: Determine the rule description text for each resource orchestration platform; The rule description texts of the various resource orchestration platforms are processed by using a language model to obtain second code rules of the various resource orchestration platforms.

17. The device according to any one of claims 10 to 14, characterized in that: The first cloud platform provides a second code, and the conversion module is further used for: The first code rule is determined from third code rules of the multiple cloud platforms according to the one or more cloud platform identifiers.

18. The device according to claim 17, characterized in that Before providing the first code to the user, the processing module is further used for: Determine the rule description text for each cloud platform; The rule description texts of the respective cloud platforms are processed by using a language model to obtain third code rules of the respective cloud platforms.

19. 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 used 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.

20. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 9.

21. A computer program product, characterized in that The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 9.

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