Cluster creation method and system, electronic device, and computer readable storage medium

Abstract

The present application discloses a cluster creation method and system, an electronic device, and a computer readable storage medium. The method comprises: acquiring network information in a cluster creation scenario, wherein the cluster creation scenario is used for representing a scenario to which at least one cluster to be created belongs; on the basis of the network information, configuring creation parameters required by said cluster in a creation process; inputting the creation parameters into a cluster creation template matching the type of said cluster, wherein the cluster creation template is used for representing a rule that said cluster needs to satisfy in the creation process; and in the cluster creation template, using the creation parameters to create a cluster matching the cluster creation scenario. The present application solves the technical problem of low cluster creation efficiency.

Description

[0001] Cluster Creation Method, System, Electronic Device, and Computer-Readable Storage Medium TECHNICAL FIELD This application relates to the fields of artificial intelligence, distributed systems, and parallel computing. Specifically, it relates to a cluster creation method, system, electronic device, and computer-readable storage medium. BACKGROUND Currently, in some aspects of cluster delivery, for example, cloud operating systems (Kubernetes, abbreviated as Kubernetes) can be used to create clusters, and application deployment platforms can be used to create single clusters. However, cloud operating systems cannot complete the deployment operations required before cluster creation and the installation operations required after cluster creation. Application deployment platforms cannot meet the requirements of hybrid cluster systems, such as hybrid clusters (Slurm + Kubernetes), resulting in low cluster creation efficiency. Currently, no effective solution has been proposed to address the above-mentioned low cluster creation efficiency. SUMMARY OF THE INVENTION Embodiments of the present application provide a cluster creation method, system, electronic device, and computer-readable storage medium to at least address the technical problem of low cluster creation efficiency. According to one aspect of an embodiment of the present application, a cluster creation method is provided. The method may include: obtaining network information for a cluster creation scenario, wherein the cluster creation scenario represents the scenario to which at least one cluster to be created belongs; configuring creation parameters required for the cluster to be created based on the network information; inputting the creation parameters into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template represents the rules to be met during the creation of the cluster to be created; and using the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. According to another aspect of an embodiment of the present application, a cluster creation method is provided. The method may include: obtaining network information for a cluster delivery scenario, wherein the cluster delivery scenario represents the delivery scenario to which at least one cluster to be created belongs; configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline describes at least the creation parameters required for the cluster to be created; inputting the cluster baseline into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template represents the rules to be met during the creation of the cluster to be created; and using the cluster baseline in the cluster creation template to create a cluster that matches the cluster delivery scenario. According to another aspect of the embodiments of the present application, a method for creating a cluster is provided.The method may include: in response to an input operation on an operation interface, inputting network information for a cluster creation scenario on the operation interface, wherein the cluster creation scenario represents a scenario to which at least one cluster to be created belongs; and in response to the cluster creation operation on the operation interface, displaying on the operation interface a cluster creation result that matches the cluster creation scenario, wherein the cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template, wherein the cluster creation template represents rules that must be met during the creation of the cluster to be created, and the creation parameters are configured based on the network information. According to another aspect of an embodiment of the present application, a cluster creation system is provided. The system may include: a parameter configuration terminal configured to obtain network information in a cluster creation scenario and, based on the network information, configure creation parameters required for a cluster to be created during creation. The cluster creation scenario represents a scenario to which at least one cluster to be created belongs. A cluster creation terminal configured to input the creation parameters into a cluster creation template that matches the type of the cluster to be created and, using the creation parameters in the cluster creation template, create a cluster matching the cluster creation scenario. The cluster creation template represents rules that the cluster to be created must meet during creation. According to another embodiment of the present application, an electronic device is provided. The electronic device may include a memory and a processor: the memory is configured to store an executable program, and the processor is configured to execute the executable program. When the executable program is executed by the processor, it implements any of the aforementioned cluster creation methods. According to another embodiment of the present application, a computer terminal is provided. The computer terminal includes: a memory storing an executable program; and a processor configured to execute the program. When the program executes, the cluster creation method described in each embodiment of the present application is executed. According to another aspect of an embodiment of the present application, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program. When the executable program is executed, the device containing the computer-readable storage medium is controlled to execute the cluster creation method described in various embodiments of the present application. According to another aspect of an embodiment of the present application, a computer program product is provided. The computer instructions, when executed by a processor, implement the cluster creation method described in various embodiments of the present application. According to another aspect of an embodiment of the present application, a computer program product is provided. The computer program product includes a non-volatile computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the cluster creation method described in various embodiments of the present application. According to another aspect of an embodiment of the present application, a computer program is provided. When executed by a processor, the computer program implements the cluster creation method described in various embodiments of the present application.In an embodiment of the present application, when creating a cluster, network information for the scenario to which at least one cluster to be created belongs is obtained. Based on the obtained network information, the creation parameters required for the cluster to be created can be configured. The configured creation parameters are then input into a cluster creation template that matches the type of cluster to be created. The configured creation parameters are then used in the cluster creation template to create a cluster that matches the cluster creation scenario, thereby completing cluster creation. Since the complete cluster delivery process has been implemented, the purpose of cluster delivery is guaranteed, thereby achieving the technical effect of improving cluster creation efficiency and solving the technical problem of low cluster creation efficiency. It should be noted that the general description above and the detailed description that follow are merely for the purpose of exemplifying and explaining the present application and do not constitute limitations of the present application. BRIEF DESCRIPTION OF THE DRAWINGS The drawings described herein are provided to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are provided to explain the present application and do not constitute undue limitations of the present application. In the accompanying drawings: FIG1 is a schematic diagram of an application scenario of a cluster creation method according to an embodiment of the present application; FIG2 is a flow chart of a cluster creation method according to an embodiment of the present application; FIG3 is a flow chart of a cluster creation method according to an embodiment of the present application; FIG4 is a flow chart of another cluster creation method according to an embodiment of the present application; FIG5 is a schematic diagram of a cluster creation system according to an embodiment of the present application; FIG6 is a hardware structure block diagram of a computer terminal (or mobile device) configured to implement the cluster creation method according to an embodiment of the present application; FIG7 is a structural block diagram of a computing environment of a cluster creation method according to an embodiment of the present application; FIG8 is a structural block diagram of a service grid of a cluster creation method according to an embodiment of the present application; FIG9 is a schematic diagram of the architecture of a cluster creation system according to an embodiment of the present application; FIG10 is a schematic diagram of the global framework of a cluster creation system according to an embodiment of the present application; FIG11 is a schematic diagram of a cluster creation device according to an embodiment of the present application; FIG12 is a schematic diagram of a cluster creation device according to an embodiment of the present application; FIG13 is a schematic diagram of another cluster creation device according to an embodiment of the present application; Figure 14 is a block diagram of an electronic device implementing a cluster creation method according to an embodiment of the present application; Figure 15 is a structural block diagram of a computer terminal according to an embodiment of the present application. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS To help those skilled in the art better understand the present invention, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings. It should be understood that the described embodiments represent only a portion of the present application, and not all of the embodiments.All other embodiments derived by persons of ordinary skill in the art based on the embodiments described herein without inventive effort shall fall within the scope of protection of this application. It should be noted that the terms "first," "second," and so on, in the specification and claims of this application, and in the accompanying drawings, are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that such terms are interchangeable where appropriate, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein. Furthermore, the terms "including," "comprising," and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not necessarily limited to the steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, product, or apparatus. First, some terms or terms used in describing the embodiments of this application are explained as follows: Cluster baseline: Each cluster has its own cluster baseline, which is a collection of information describing the cluster's corresponding software, configuration, applications, tags, and other related information. Node resource: This refers to a physical server or cloud server (for example, an Elastic Compute Server (ECS) or Elastic Compute Cloud (EC2) server) that can create a cluster. Node resources that can be used to create a cluster can belong to the same node resource pool. Process tasks: During the cluster creation process, the entire creation process is divided into several process tasks, and cluster creation is completed by executing these process tasks. For example, these process tasks can include at least two of the following: information check task, software installation task, configuration installation task, cluster installation task, and application installation task. Load Sharing Facility (LSF) software is industry-leading enterprise-level software. LSF distributes workloads across existing information technology (IT) resources to create a shared, scalable, and fault-tolerant infrastructure, delivering faster and more reliable workload performance while reducing costs. LSF balances loads, allocates resources, and provides access to those resources.Google File System (GFS) is a highly available, high-performance, and scalable distributed file system that can be used to store and process large-scale data. The open source distributed storage cluster (Ceph) supports object storage, block devices, and file systems. Example 1: According to an embodiment of the present application, a method for creating a cluster is provided. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system, such as a set of computer-executable instructions. Furthermore, although the flowcharts illustrate a logical order, in some cases, the steps shown or described may be executed in a different order. Considering the large number of parameters required to create a cluster and the limited computing resources of mobile terminals, the cluster creation method provided in the embodiments of the present application can be applied to the application scenario shown in FIG. 1, but is not limited thereto. In the application scenario shown in FIG. 1, the cluster creation method is deployed on a server 10, which can be a cloud server. The server 10 can be connected to one or more client devices 20 via a local area network (LAN), a wide area network (WAN), the Internet, or other types of data networks. Client devices 20 herein include, but are not limited to, smartphones, tablet computers, laptops, PDAs, personal computers, smart home devices, and in-vehicle devices. These client devices collectively constitute the client side of the server. A graphical user interface (GUI) on the client device can be deployed with an interface for obtaining network information in a cluster creation scenario. This interface can be an interface for an e-commerce platform. The client device 20 can interact with the user via the GUI to invoke a cluster creation method, thereby implementing the cluster creation method provided in the embodiments of the present application. In the embodiments of the present application, the system comprised of the client devices and the server can perform the following steps: When creating a cluster, a user can communicate data with the server via a network using a client device such as a mobile phone, desktop computer, or laptop computer. After receiving the creation instruction sent by the user via the client device, the server may proceed to step S102 to obtain network information for the cluster creation scenario. It may also proceed to step S104 to configure the creation parameters required for the cluster to be created based on the network information. It may also proceed to step S106 to input the creation parameters into a cluster creation template that matches the type of cluster to be created. Finally, it may proceed to step S108 to use the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. The type and number of the created clusters may be output to the client device and displayed on the client device.In the above process, after the server receives a creation instruction sent by the user via a client device, it can create a cluster matching the cluster creation scenario and send the converted cluster type and number to the client device. It should be noted that, if the client device's operating resources meet the deployment and operating conditions of the cluster creation method, this embodiment of the present application can be performed on the client device. Under the above operating environment, this application provides a cluster creation method as shown in Figure 2. Figure 2 is a flowchart of a cluster creation method according to Example 1 of the present application. As shown in Figure 2, the method may include the following steps: Step S202: Obtaining network information for the cluster creation scenario. In the technical solution provided in step S202 of the present application, the cluster creation scenario can be used to represent the scenario to which at least one cluster to be created belongs. The network information can be used to represent the configuration information and identity information of the user network. The user network configuration information can be used to describe the network topology and communication rules. The user network identity information can be used to manage and control network access and communication. In this embodiment, the cluster creation scenario can be any of the following: a big data analysis platform scenario, a distributed storage scenario, an internet application server scenario, an IoT device scenario, etc. The big data analysis platform scenario can be a scenario where business decisions are made by analyzing and mining massive amounts of data. The distributed storage scenario can be a scenario for storing massive amounts of user data, log data, etc. The internet application server scenario can be a scenario that supports millions of simultaneous online users. The IoT device scenario can be a scenario for monitoring and managing hundreds of industrial devices. These examples are provided for illustration only and are not intended to be limiting. This embodiment obtains network information in the cluster creation scenario. For example, a cluster to be created is first determined, and then the scenario to which the cluster to be created belongs is detected to obtain the type of scenario to which the cluster to be created belongs, that is, the type of cluster creation scenario. Based on the obtained cluster creation scenario type, network information in the cluster creation scenario can be obtained. For example, network configuration information and network identity information in the cluster creation scenario can be obtained. This is provided for illustration only and is not intended to be limiting. Step S204: Based on the network information, configure the creation parameters required for the cluster to be created. In the technical solution provided in step S204 of this application, after obtaining the network information for the cluster creation scenario, the creation parameters required for the cluster to be created can be configured based on the obtained network information.In this embodiment, the aforementioned creation parameters can be used to represent various related information corresponding to a cluster. For example, the various related information corresponding to a cluster can include at least software, configuration, application, and label information. This is merely an example and is not intended to be limiting. After obtaining network information in a cluster creation scenario, this embodiment configures the creation parameters required for the cluster to be created based on the obtained network information. For example, based on the obtained user network configuration information and identity information, the clusters to be created can be categorized. Based on the categorized clusters to be created, the creation parameters required for the cluster to be created can be configured. For example, the software, application, label, and other related information required for the cluster to be created can be configured. Optionally, a mapping table between network information and the cluster to be created is established, and network resources are allocated to the cluster to be created according to the mapping table. For example, the mapping table searches for network information corresponding to the cluster to be created. Once the network information corresponding to the cluster to be created is found, network resources are allocated to the cluster to be created according to the network information. Furthermore, the creation parameters required for the cluster to be created during creation are configured based on the network resources allocated to the cluster to be created. It should be noted that the above method for configuring creation parameters is merely an example and is not specifically limited herein. Any process or method capable of configuring the creation parameters required for the cluster to be created during creation based on the acquired network information is within the scope of the embodiments of the present application. In step S206, the creation parameters are input into a cluster creation template that matches the type of the cluster to be created. In the technical solution provided in step S206 above, after the creation parameters required for the cluster to be created during creation are configured based on the network information, the creation parameters are input into the cluster creation template that matches the type of the cluster to be created.In this embodiment, the cluster creation template may be used to represent rules that need to be satisfied during the creation process of the cluster to be created. The creation process of the cluster to be created may be completed by executing the steps in the embodiments of the present application in accordance with the rules. For example, the type of the cluster to be created may include at least: a slurm cluster type, a k8s cluster type, a cluster for load balancing and resource allocation (LSF) type, a cluster for storing and processing large-scale data (GFS) type, an open source distributed storage cluster (ceph), a single-control role (master) cluster type, a multi-master cluster type, etc. The cluster creation template may include at least one of the following templates: a template corresponding to the k8s cluster type, a template corresponding to the slurm cluster type, a template corresponding to both the k8s cluster type and the slurm cluster type, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, etc. These are merely examples and are not specifically limited. Optionally, after configuring the creation parameters required for the cluster to be created based on the network information, the configured creation parameters are input into a cluster creation template that matches the type of the cluster to be created. For example, the configured parameters such as software, applications, and labels are input into the cluster creation template that matches the type of the cluster to be created. This is for illustrative purposes only and is not intended to be limiting. For example, if the cluster creation template is a template corresponding to a slurm cluster type, the configured creation parameters are input into the template corresponding to the slurm cluster type. For example, the configured parameters such as software, applications, and labels are input into the template corresponding to the slurm cluster type. This is for illustrative purposes only and is not intended to be limiting as to the cluster creation template in the embodiment of the present application being a template corresponding only to the slurm cluster type. For example, the cluster creation template may also be a template corresponding to a k8s cluster type, a template corresponding to both a k8s cluster type and a slurm cluster type, a template corresponding to an LSF cluster type, a template corresponding to a GFS cluster type, and so on. This is not intended to be limiting. In step S208, the creation parameters in the cluster creation template are used to create a cluster that matches the cluster creation scenario. In the technical solution provided in step S208 of this application, after the creation parameters are input into the cluster creation template that matches the type of cluster to be created, the creation parameters can be used in the cluster creation template to create a cluster that matches the cluster creation scenario.In this embodiment, after the creation parameters are input into a cluster creation template that matches the type of cluster to be created, the cluster creation template that matches the type of cluster to be created utilizes the configured software, applications, tags, and other related parameters in accordance with the creation process of the cluster to be created to create a cluster that matches the cluster creation scenario. This achieves the technical effect of improving cluster creation efficiency by ensuring the complete cluster delivery process. For example, if the cluster creation template is a template corresponding to the Kubernetes cluster type, the template that matches the Kubernetes cluster type utilizes the configured software, applications, tags, and other related parameters in accordance with the creation process of the cluster to be created to create a cluster that matches the cluster creation scenario. This cluster creation template is merely an example and is not limited to the embodiment of the present application where the cluster creation template corresponds only to the Kubernetes cluster type. For example, the cluster creation template may also be a template corresponding to the Slurm cluster type, a template corresponding to both the Kubernetes and Slurm cluster types, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, and so on. No specific limitation is imposed herein. During steps S202 to S208 of the present application, when creating a cluster, network information for the scenario to which at least one cluster to be created belongs is obtained. Based on the obtained network information, the creation parameters required for the cluster to be created can be configured. The configured creation parameters are then input into a cluster creation template that matches the type of cluster to be created. The configured creation parameters are then used within the cluster creation template to create a cluster that matches the cluster creation scenario, thereby completing cluster creation. Since the complete cluster delivery process is implemented, cluster delivery is guaranteed, thereby achieving the technical effect of improving cluster creation efficiency and addressing the technical issue of low cluster creation efficiency. The above-described method of this embodiment is further described below. As an optional implementation, step S208, using the creation parameters within the cluster creation template to create a cluster that matches the cluster creation scenario, includes: creating an instance object using the creation parameters within the cluster creation template; and creating a cluster that matches the cluster creation scenario using the creation parameters according to the creation process corresponding to the instance object. In this embodiment, the instance object can be used to represent the creation process of the cluster to be created.In this embodiment, after the creation parameters are input into a cluster creation template that matches the type of cluster to be created, the instance object is created using the configured creation parameters in the cluster creation template that matches the type of cluster to be created. For example, the instance object is created using the configured parameters such as software, application, and tags. Based on the created instance object, a creation process corresponding to the instance object can be obtained. Then, according to the creation process corresponding to the instance object, the configured creation parameters can be used to create a cluster that matches the cluster creation scenario. For example, according to the creation process corresponding to the instance object, the configured parameters such as software, application, and tags can be used to create a cluster that matches the cluster creation scenario, thereby achieving the technical effect of improving cluster creation efficiency. For example, when a cluster creation template is a template corresponding to an LSF cluster type, the template corresponding to the LSF cluster type utilizes the configured software, applications, labels, and other related parameters to create an instance object. Based on the created instance object, a creation process corresponding to the instance object can be obtained. Then, according to the creation process corresponding to the instance object, the configured software, applications, labels, and other related parameters can be utilized to create a cluster matching the cluster creation scenario. The cluster creation template herein is merely an example and is not limited to the cluster creation templates of the embodiments of the present application being solely templates corresponding to the LSF cluster type. For example, the cluster creation templates may also be templates corresponding to the Kubernetes cluster type, the Slurm cluster type, the templates corresponding to both the Kubernetes and Slurm cluster types, the templates corresponding to the GFS cluster type, and so on, without specific limitation herein. It should be noted that the above cluster creation method is merely an example and is not specifically limited herein. Any process and method capable of utilizing the creation parameters in the cluster creation template to create a cluster matching the cluster creation scenario falls within the scope of the embodiments of the present application. As an optional implementation, creating a cluster matching the cluster creation scenario using creation parameters according to the creation process corresponding to the instance object includes: determining multiple tasks corresponding to the creation process in the instance object; and sequentially executing the multiple tasks according to the creation process using the creation parameters to obtain a cluster matching the cluster creation scenario. In this embodiment, the multiple tasks may be used to represent several process tasks obtained by dividing the entire creation process task. This is for illustrative purposes only and is not a specific limitation.In this embodiment, after creating an instance object using creation parameters in a cluster creation template, the creation process corresponding to the instance object is determined. The entire creation process is then divided into several tasks to obtain multiple tasks corresponding to the creation process. By sequentially executing the multiple tasks according to the creation process corresponding to the instance object using the configured creation parameters, a cluster matching the cluster creation scenario can be obtained. For example, by sequentially executing the multiple tasks according to the creation process corresponding to the instance object using the configured parameters such as software, applications, and tags, a cluster matching the cluster creation scenario can be created. This achieves the technical effect of improving cluster creation efficiency by ensuring a complete cluster delivery process. As an optional implementation, sequentially executing the multiple tasks according to the creation process using the creation parameters to obtain a cluster matching the cluster creation scenario includes: invoking a processor to sequentially execute the multiple tasks according to the creation process using the creation parameters in a containerized manner to obtain cluster creation instructions corresponding to the tasks; and, in response to the cluster creation instructions, triggering corresponding nodes in the node resource pool to create a cluster matching the cluster creation scenario. In this embodiment, the processor may be an artificial intelligence cluster processor (ai-cluster-processor), the cluster creation instruction may be used to trigger a corresponding node in a node resource pool, the node may be used to represent a server on which a client is installed and used to create a cluster, and the client may be used to provide control services for the server. For example, the cluster creation instruction may include at least one of the following instructions: a software installation command, a configuration command, an application installation command, etc. The server may be at least one of the following servers: a physical server, a cloud server, etc. The cloud server may be an ECS server or an EC2 server. This is for illustration only and is not a specific limitation. In this embodiment, after determining multiple tasks corresponding to the creation process in the instance object, the calling processor executes the multiple tasks sequentially in a containerized manner using the configured creation parameters according to the creation process corresponding to the instance object. This can obtain cluster creation instructions corresponding to each task. For example, by sequentially executing multiple tasks in a containerized manner using the configured parameters such as software, applications, and tags, a cluster creation instruction corresponding to each task can be obtained. When the corresponding node in the node resource pool receives the cluster creation instruction, it is triggered to create a cluster that matches the cluster creation scenario, thereby achieving the technical effect of improving the efficiency of cluster creation by ensuring the complete cluster delivery process.For example, in the case where the cluster creation scenario is a big data analysis platform scenario, an artificial intelligence cluster processor is invoked to execute multiple tasks sequentially in a containerized manner, following the creation process corresponding to the instance object, using the configured software, applications, tags, and other related parameters. This generates cluster creation instructions corresponding to each task. When a server in the resource pool receives the cluster creation instruction, it is triggered to create a cluster that matches the big data analysis platform scenario. The cluster creation scenario described here is merely illustrative and is not limited to the big data analysis platform scenario in the embodiments of the present application. For example, the cluster creation scenario can also be a distributed storage scenario, an internet application server scenario, an IoT device scenario, and so on, which are not specifically limited here. As an optional implementation, in response to the cluster creation instruction, triggering corresponding nodes in the node resource pool to create a cluster that matches the cluster creation scenario includes: obtaining cluster creation resources from a data warehouse in response to the cluster creation instruction; and using the cluster creation resources to trigger the nodes to create a cluster that matches the cluster creation scenario. In this embodiment, the cluster creation resources can be used to represent software and applications required for resources and configuration. The data warehouse can include at least a software warehouse, an image warehouse, and an application warehouse. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, after the calling processor executes multiple tasks sequentially in a containerized manner using creation parameters according to the creation process and obtains cluster creation instructions corresponding to the tasks, it retrieves cluster creation resources from the data warehouse in response to the cluster creation instructions corresponding to each task. Using the retrieved cluster creation resources, the node can be triggered to create a cluster that matches the cluster creation scenario. This achieves the technical effect of improving cluster creation efficiency by ensuring the complete cluster delivery process. For example, when the cluster creation scenario is a distributed storage scenario, in response to the cluster creation instructions corresponding to each task, the software, applications, etc. required for resources and configuration are downloaded from the software warehouse, image warehouse, application warehouse, etc., and the installation is performed. Then, the installed software, applications, etc. can be used to trigger the servers in the resource pool to create a cluster that matches the distributed storage scenario. The cluster creation scenario here is only an example and is not limited to the distributed storage scenario in the embodiment of the present application. For example, it can also be a big data analysis platform scenario, an Internet application server scenario, an Internet of Things device scenario, etc., and no specific limitation is made here.As an optional implementation, in response to a cluster creation instruction, triggering corresponding nodes in a node resource pool to create a cluster matching the cluster creation scenario includes: in response to the cluster creation instruction, invoking pre-configured cluster creation resources to trigger the nodes to create a cluster matching the cluster creation scenario. In this embodiment, cluster creation resources can be pre-configured during node provisioning. For example, during server provisioning, required software and applications such as resources and configurations can be pre-configured. It should be noted that the pre-configuration operation can be used to represent at least downloading and installing operations. This is merely an example and not a limitation. In this embodiment, after the calling processor executes multiple tasks sequentially in a containerized manner according to the creation process using creation parameters and obtains cluster creation instructions corresponding to the tasks, the pre-configured cluster creation resources can be directly invoked in response to the cluster creation instructions corresponding to each task to trigger the nodes to create a cluster matching the cluster creation scenario. This achieves the technical effect of improving cluster creation efficiency by ensuring the complete cluster delivery process. For example, when the cluster creation scenario is an IoT device scenario, in response to cluster creation instructions corresponding to each task, the software and applications required for resources and configuration are directly downloaded and installed. The installed software and applications are then invoked to trigger servers in the resource pool to create a cluster matching the IoT device scenario. The cluster creation scenario described here is merely illustrative and is not limited to the IoT device scenario in the embodiments of this application. For example, the cluster creation scenario can also be a big data analysis platform scenario, an Internet application server scenario, or a distributed storage scenario, and no specific limitations are imposed here. As an optional implementation, the method further includes: installing an operating system on the server using an operating system template. In this embodiment, the operating system template can be used to represent rules for installing an operating system (OS) on the server. In this embodiment, an operating system template is used to install an operating system on a server. For example, before installing the operating system on a server, different operating system templates are customized in advance. The server's required operating system is then determined based on the server's needs. Based on the determined operating system, the operating system template matching the required operating system is used to install the operating system on the server, thereby achieving the technical effect of improving operating system installation efficiency. It should be noted that the operating system can be any one or more of the following: Linux, Unix, etc. This is for illustrative purposes only and is not intended to be limiting.As an optional implementation, during the process of sequentially executing multiple tasks using creation parameters, the method further includes: determining a cluster creation stage; and outputting a prompt indicating the creation stage. In this embodiment, the creation stage may be used to indicate the current stage of the cluster creation process, and the prompt may be used to indicate the completion progress of the cluster creation. Optionally, after determining multiple tasks corresponding to the creation process in the instance object, the cluster creation stage is determined; and the prompt indicating the creation stage is output. For example, by real-time monitoring of the cluster creation process, the cluster creation stage can be determined. Specifically, the cluster creation stage can be determined, and then prompt information for the creation stage can be determined. The prompt information is then output to indicate the completion progress of the cluster creation, thereby achieving the technical effect of improving the display accuracy of cluster creation. It should be noted that the above method for determining the creation stage is merely illustrative and is not specifically limited herein. Any method capable of determining the current stage of the cluster creation process is within the scope of the embodiments of this application. In an optional implementation, the multiple tasks include at least two of the following: an information check task for checking information generated during the creation of the cluster to be created; a software installation task for installing software required for the cluster to be created; a configuration installation task for installing configuration information required for the cluster to be created; a cluster installation task for installing the cluster to be created; and an application installation task for installing applications required by the cluster after its creation. In this embodiment, the information check task can be used to check information generated during the creation of the cluster to be created. For example, the information check task can be used to check initialization information, server information, software information, configuration information, application information, and cluster information generated during the creation of the cluster to be created. In other words, the information check task can include the following tasks: a pre-check task, a node resource check task, a software check task, a configuration check task, a cluster check task, and an application check task. These are examples only and are not intended to be limiting. In this embodiment, the software installation task can be used to install software required during the creation of the cluster to be created. For example, the software installation task can be used to install browsing software, drawing software, etc. required during the creation of the cluster to be created. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, the configuration installation task can be used to install configuration information required during the creation of the cluster to be created. For example, the configuration installation task can be used to install network configuration information and system configuration information required during the creation of the cluster to be created. This is for illustrative purposes only and is not intended to be limiting.In this embodiment, the cluster installation task can be used to install a cluster to be created. For example, the cluster installation task can be used to install one or more clusters to be created. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, the application installation task can be used to install applications required by the cluster to be created after creation. For example, the application installation task can be used to install audio and video applications required by the cluster to be created after creation. This is for illustrative purposes only and is not intended to be limiting. As an optional implementation, the method further includes adjusting the creation process in response to an adjustment operation on the creation process. In this embodiment, the adjustment operation can include at least adding and deleting operations. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, the creation process is adjusted in response to the adjustment operation on the creation process. For example, whether to adjust the cluster creation process is determined based on a user's customized requirements. If adjustment is determined to be necessary, the creation process is adjusted, thereby achieving the customized requirements of the user. Optionally, if a user's customization requirement is to add drawing software, a drawing software installation task is added to the cluster creation process. That is, the drawing software installation task is added to the software installation tasks in the creation process. This customization requirement is merely illustrative and is not limited to the customization requirement in the embodiment of the present application, which is merely illustrative. For example, the customization requirement may also include deleting and updating applications or adding playback software, and this is not specifically limited here. As an optional implementation, step S204, based on network information, configures the creation parameters required for the cluster to be created. This includes configuring a cluster baseline for the cluster to be created based on the network information. In this embodiment, the cluster baseline may be used to at least describe the creation parameters required for the cluster to be created. For example, the cluster baseline may be a collection of information describing various related information corresponding to the cluster. The various related information corresponding to the cluster may include at least software, configuration, application, tags, and other related information. This is merely illustrative and not specifically limited here. In this embodiment, after obtaining network information in a cluster creation scenario, a cluster baseline for a cluster to be created is configured based on the network information. For example, the clusters to be created may be classified based on the obtained user network configuration information and identity information. Based on the classified clusters to be created, creation parameters required for the cluster creation process may be configured. For example, relevant information such as software, applications, and tags required for the cluster creation process may be configured. This is for illustrative purposes only and is not intended to be limiting.As an optional implementation, configuring a cluster baseline for a cluster to be created based on network information includes: determining cluster information for the cluster to be created based on the network information; and configuring a cluster baseline based on the cluster information for the cluster to be created. In this embodiment, the cluster information for the cluster to be created may include required and optional information for the cluster to be created. The required information for the cluster to be created may include attribute information and software information for the cluster to be created. The optional information for the cluster to be created may include configuration parameter information for the cluster to be created, application information for the cluster to be created, and label information for nodes in the cluster to be created. For example, the attribute information for the cluster to be created may include at least version information for the cluster to be created and information about the operating state of the cluster to be created. The configuration parameter information for the cluster to be created may include at least environment variable information corresponding to the cluster to be created and initialization configuration information corresponding to the cluster to be created. The application information for the cluster to be created may be application information on a Kubernetes cluster. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, after obtaining network information for a cluster creation scenario, cluster information for the cluster to be created is determined based on the network information. A cluster baseline is configured based on the cluster information for the cluster to be created. For example, based on the obtained configuration information and identity information of the user network, required and optional information for the cluster to be created can be determined. Based on the determined required and optional information for the cluster to be created, the cluster baseline can be configured. For example, software, configuration, application, label, and other related information can be configured, thereby achieving the technical effect of improving the configuration accuracy of the cluster baseline. In this embodiment, based on the obtained configuration information and identity information of the user network, the cluster to be created can be classified, and required and optional information for the cluster to be created can be determined. Based on the classified cluster to be created and the determined required and optional information, the cluster baseline required for the cluster to be created during the creation process can be configured. As an optional implementation, the method further includes: updating the cluster baseline. In this embodiment, the updated cluster baseline can be switched to the pre-update cluster baseline. For example, the switching operation can be a rollback operation. This is for illustrative purposes only and is not intended to be limiting. In this embodiment, the cluster baseline is updated. For example, the original cluster baseline is updated to obtain an updated cluster baseline. The original cluster baseline is retained so that, in special circumstances, the updated cluster baseline can be rolled back to the original cluster baseline, thereby achieving the technical effect of improving the availability of the cluster baseline.An embodiment of the present application also provides a method for creating a cluster in a cluster delivery scenario. FIG3 is a flow chart of a cluster creation method according to an embodiment of the present application. As shown in FIG3 , the method may include the following steps: Step S302: Obtaining network information in the cluster delivery scenario. In the technical solution provided in step S302 of the present application, the cluster delivery scenario may be used to represent the delivery scenario to which at least one cluster to be created belongs. The network information may be used to represent the configuration information and identity information of a user network. The user network configuration information may be used to describe the network topology and communication rules. The user network identity information may be used to manage and control network access and communication. In this embodiment, the cluster delivery scenario can be any of the following: a big data analysis platform scenario, a distributed storage scenario, an internet application server scenario, an IoT device scenario, etc. The big data analysis platform scenario can be a scenario where business decisions are made by analyzing and mining massive amounts of data. The distributed storage scenario can be a scenario for storing massive amounts of user data, log data, etc. The internet application server scenario can be a scenario that supports millions of simultaneous online users. The IoT device scenario can be a scenario for monitoring and managing hundreds of industrial devices. These are examples only and are not intended to be limiting. This embodiment obtains network information for the cluster delivery scenario. For example, a cluster to be created is first determined. Then, by detecting the delivery scenario to which the cluster to be created belongs, the type of delivery scenario to which the cluster to be created belongs can be obtained. In other words, the type of cluster delivery scenario can be obtained. Based on the obtained cluster delivery scenario type, network information for the cluster delivery scenario can be obtained. For example, network configuration information and network identity information for the cluster delivery scenario can be obtained. This is for example only and is not intended to be limiting. Step S304 configures a cluster baseline for the cluster to be created based on the network information. In the technical solution provided in step S304 of the present application, after obtaining network information for the cluster delivery scenario, a cluster baseline for the cluster to be created can be configured based on the obtained network information. In this embodiment, the cluster baseline can be used to describe the creation parameters and / or software required for the cluster to be created during creation. After obtaining the network information for the cluster delivery scenario, this embodiment configures the cluster baseline for the cluster to be created based on the obtained network information. For example, clusters to be created can be categorized based on the obtained user network configuration information and identity information. Cluster baselines can then be configured for the categorized clusters. For example, information such as software, applications, and tags required for the cluster to be created can be configured.Optionally, a mapping table is established between network information and the cluster to be created. Network resources are allocated to the cluster to be created according to the mapping table. For example, the mapping table searches for network information corresponding to the cluster to be created. Once the network information corresponding to the cluster to be created is found, network resources are allocated to the cluster to be created according to the network information. A cluster baseline for the cluster to be created is then configured based on the network resources allocated to the cluster to be created. In step S306, the cluster baseline is input into a cluster creation template that matches the type of the cluster to be created. In the technical solution provided in step S306 above, after the cluster baseline for the cluster to be created is configured based on the network information, the cluster baseline is input into the cluster creation template that matches the type of the cluster to be created. In this embodiment, the above-mentioned cluster creation template can be used to represent the rules that need to be met during the creation process of the cluster to be created. The creation process of the above-mentioned cluster to be created can be completed by executing the steps in the embodiment of the present application in accordance with the above-mentioned rules. For example, the type of the above-mentioned cluster to be created can at least include: slurm cluster type, k8s cluster type, LSF cluster type, GFS cluster type, single-master cluster type, multi-master cluster type, etc. The above-mentioned cluster creation template can include at least one of the following templates: a template corresponding to the k8s cluster type, a template corresponding to the slurm cluster type, a template corresponding to both the k8s cluster type and the slurm cluster type, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, etc. This is only for illustration and is not specifically limited. Optionally, after configuring a cluster baseline for the cluster to be created based on the network information, the configured creation parameters are input into a cluster creation template that matches the type of the cluster to be created. For example, the configured software, application, label, and other related parameters are input into the cluster creation template that matches the type of the cluster to be created. This is for illustration only and is not a specific limitation.For example, if the cluster creation template is a template corresponding to the slurm cluster type, the configured creation parameters are input into the template corresponding to the slurm cluster type. For example, the configured software, application, tag, and other related parameters are input into the template corresponding to the slurm cluster type. The cluster creation template herein is merely an example and is not limited to the cluster creation template of the embodiment of the present application being a template corresponding only to the slurm cluster type. For example, the cluster creation template may also be a template corresponding to the k8s cluster type, a template corresponding to both the k8s cluster type and the slurm cluster type, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, and so on. No specific limitation is imposed herein. In step S308, a cluster baseline is used in the cluster creation template to create a cluster that matches the cluster delivery scenario. In the technical solution provided in step S308 above, after the cluster baseline is input into the cluster creation template that matches the type of cluster to be created, the cluster baseline can be used in the cluster creation template to create a cluster that matches the cluster delivery scenario. In this embodiment, after the cluster baseline is input into a cluster creation template that matches the type of cluster to be created, the cluster baseline is used within the template to create a cluster that matches the cluster creation scenario according to the cluster creation process. For example, the configured software, applications, tags, and other related parameters are used to create a cluster that matches the cluster creation scenario. This achieves the technical effect of improving cluster creation efficiency by ensuring the complete cluster delivery process. For example, when the cluster creation template is a template corresponding to the k8s cluster type, in the template corresponding to the k8s cluster type, according to the creation process of the cluster to be created, the configured software, applications, tags and other related parameters are used to create a cluster that matches the cluster creation scenario. The cluster creation template here is only an example and is not limited to the cluster creation template in the embodiment of the present application being only a template corresponding to the k8s cluster type. For example, it can also be a template corresponding to the slurm cluster type, a template corresponding to both the k8s cluster type and the slurm cluster type, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, etc., and no specific limitation is made here.During steps S602 to S608 of the present application, when creating a cluster, network information for the delivery scenario of at least one cluster to be created is obtained. Based on the obtained network information, a cluster baseline required for the creation of the cluster to be created can be configured. The configured cluster baseline is then input into a cluster creation template that matches the type of cluster to be created. The configured cluster baseline is then used within the cluster creation template to create a cluster that matches the cluster creation scenario, thereby completing cluster creation. Since the complete cluster delivery process has been implemented, cluster delivery is guaranteed, thereby achieving the technical effect of improving cluster creation efficiency and addressing the technical issue of low cluster creation efficiency. Embodiments of the present application also provide another cluster creation method. FIG4 is a flowchart of another cluster creation method according to an embodiment of the present application. As shown in FIG4 , the method may include the following steps: Step S402: In response to an input operation on an operation interface, network information for the cluster creation scenario is input on the operation interface, where the cluster creation scenario represents the scenario to which the at least one cluster to be created belongs. In the technical solution provided in step S402 of the present application, the cluster creation scenario can be used to represent the scenario to which at least one cluster to be created belongs. The network information can be used to represent the configuration information and identity information of the user network. The user network configuration information can be used to describe the network topology and communication rules, and the user network identity information can be used to manage and control network access and communication. In this embodiment, in response to an input operation on the operation interface, network information for the cluster creation scenario is input on the operation interface. For example, when an input operation is performed on the operation interface, the cluster to be created is first determined, and then the scenario to which the cluster to be created belongs is detected to obtain the type of scenario to which the cluster to be created belongs. In other words, the type of cluster creation scenario can be obtained. Based on the obtained cluster creation scenario type, network information for the cluster creation scenario can be obtained and input on the operation interface. For example, network configuration information and network identity information for the cluster creation scenario can be obtained and input on the operation interface. This is for illustration only and is not intended to be a specific limitation. Step S404: In response to a cluster creation operation performed on the operation interface, a creation result of a cluster matching the cluster creation scenario is displayed on the operation interface. The cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template. The cluster creation template is used to represent rules that must be met during the creation of the to-be-created cluster. The creation parameters are configured based on network information.In the technical solution provided in step S404 of the present application, after network information for a cluster creation scenario is input on the operation interface in response to an input operation on the operation interface, a cluster creation result matching the cluster creation scenario is displayed on the operation interface in response to the cluster creation operation on the operation interface. For example, when a cluster creation operation is performed on the operation interface, creation parameters required for the cluster to be created during the creation process are configured based on the network information. The configured creation parameters are then input into a cluster creation template matching the type of the cluster to be created. Then, in the cluster creation template matching the type of the cluster to be created, the configured creation parameters are used according to the creation process of the cluster to be created to create a cluster matching the cluster creation scenario. Through steps S402 to S404 of the present application, when an input operation is performed on the operation interface, the cluster to be created is first determined. Then, by detecting the scenario to which the cluster to be created belongs, the type of the scenario to which the cluster to be created belongs can be obtained, that is, the type of the cluster creation scenario can be obtained. Based on the obtained cluster creation scenario type, network information for the cluster creation scenario can be obtained and input into the operation interface. Then, when a cluster creation operation is performed on the operation interface, creation parameters required for the cluster to be created during the creation process are configured based on the network information. The configured creation parameters are then input into a cluster creation template that matches the type of the cluster to be created. Then, in the cluster creation template that matches the type of the cluster to be created, the configured creation parameters are used according to the creation process of the cluster to be created to create a cluster that matches the cluster creation scenario. Since the complete cluster delivery process has been implemented, the purpose of ensuring cluster delivery is achieved, thereby achieving the technical effect of improving the efficiency of cluster creation and solving the technical problem of low cluster creation efficiency. The present application also provides a cluster creation system. It should be noted that the cluster creation system of this embodiment can be used to execute the aforementioned cluster creation method. Figure 5 is a schematic diagram of a cluster creation system according to an embodiment of the present application. As shown in Figure 5, the system may include: a parameter configuration terminal 502, configured to obtain network information for a cluster creation scenario and, based on the network information, configure creation parameters required for the cluster to be created. The cluster creation scenario represents the scenario to which at least one cluster to be created belongs. A cluster creation terminal 504, configured to input creation parameters into a cluster creation template that matches the type of cluster to be created and, using the creation parameters in the cluster creation template, create a cluster matching the cluster creation scenario. The cluster creation template represents the rules that must be met during the creation of the cluster to be created.In the technical solution provided by the cluster creation system described above in this application, the cluster creation system may be the ai-cluster-delivery (AID) system, the parameter configuration terminal may be the cluster module in the AID system, and the cluster creation terminal may be the ai-cluster-processor process in the AID system. In this embodiment, the parameter configuration terminal may obtain network information for a cluster creation scenario and, based on the obtained network information, configure the creation parameters required for the cluster to be created. The cluster creation terminal may input the configured creation parameters into a cluster creation template that matches the type of cluster to be created. The configured creation parameters are then used in the cluster creation template to create a cluster that matches the cluster creation scenario. In this embodiment, the cluster creation system may further include an initial control terminal, an interface display terminal, a function management terminal, and an agent terminal. The initial control terminal can be used to control local physical servers, perform batch OS installation on local physical servers, and manage servers. The interface display terminal can be used to display interfaces and control the cluster. The function management terminal can be used to manage the functions of various modules in the cluster creation system. The agent terminal can be used to accept external control. Specifically, the initial control terminal can be used to obtain server information, restart, shut down, and install clients. The interface display terminal can be used to interactively control the cluster. The function management terminal can be used to manage the functions of modules such as the physical server module, cluster module, and adjustment module in the cluster creation system. The agent terminal can receive control commands from the cluster creation terminal. In this embodiment, the initial control terminal can be a physical server module in the AID system, the interface display terminal can be a front-end project in the AID system, the function management terminal can be a back-end project in the AID system, and the agent terminal can be an agent project in the AID system.For example, when the cluster creation template is a template corresponding to the k8s cluster type, the network information in the cluster creation scenario can be obtained through the parameter configuration end, and according to the obtained network information, the creation parameters required for the cluster to be created during the creation process are configured. The configured creation parameters can be input into the template corresponding to the k8s cluster type through the cluster creation end, and the configured creation parameters are used in the template corresponding to the k8s cluster type to create a cluster matching the cluster creation scenario. The cluster creation template here is only an example and is not limited to the cluster creation template of the embodiment of the present application being only a template corresponding to the k8s cluster type. For example, it can also be a template corresponding to the slurm cluster type, a template corresponding to both the k8s cluster type and the slurm cluster type, a template corresponding to the LSF cluster type, a template corresponding to the GFS cluster type, etc., and no specific limitation is made here. In an optional implementation, a cluster creation end includes: a processor configured to call a processor to sequentially execute multiple tasks corresponding to the creation process in a containerized manner according to the creation process of the cluster to be created, using creation parameters, to obtain cluster creation instructions corresponding to the tasks; and a node configured to create a cluster matching the cluster creation scenario in response to the cluster creation instructions. In this embodiment, the processor may be ai-cluster-processor. In this embodiment, the processor in the cluster creation end can be called to sequentially execute multiple tasks corresponding to the creation process in a containerized manner according to the creation process of the cluster to be created, using creation parameters, to obtain cluster creation instructions corresponding to the tasks. Furthermore, the nodes in the cluster creation end can be used to create a cluster matching the cluster creation scenario in response to the cluster creation instructions. Optionally, when the cluster creation scenario is a big data analysis platform scenario, by utilizing the artificial intelligence cluster processor in the cluster creation end, according to the creation process corresponding to the instance object, and using the configured software, applications, tags and other related parameters to execute multiple tasks in sequence in a containerized manner, a cluster creation instruction corresponding to each task can be obtained. When the server in the cluster creation end receives the cluster creation instruction, it will trigger the server to create a cluster that matches the big data analysis platform scenario. The cluster creation scenario here is only for illustration and is not limited to the cluster creation scenario of the embodiment of the present application being only the big data analysis platform scenario. For example, it can also be a distributed storage scenario, an Internet application server scenario, an Internet of Things device scenario, etc., and no specific limitation is made here.The cluster creation system described above in this application utilizes a processor on the cluster creation client. This processor can be invoked to execute multiple tasks corresponding to the creation process in a containerized manner, following the creation process of the cluster to be created, using creation parameters. Cluster creation instructions corresponding to the tasks are then generated. Nodes on the cluster creation client can then respond to the cluster creation instructions and create a cluster that matches the cluster creation scenario. This completes the cluster delivery process, ensuring cluster delivery and improving cluster creation efficiency, thereby addressing the technical issue of low cluster creation efficiency. As an optional implementation, the system further includes a client configured to respond to control instructions from the cluster creation client and execute script information corresponding to the control instructions. In this embodiment, the client can also be referred to as an agent, which can be an agent project in the AID system. In this embodiment, when a client receives a control instruction from a cluster creation client, script information corresponding to the control instruction can be generated based on the control instruction. After the script information corresponding to the control instruction is generated, the script information corresponding to the control instruction is executed. For example, when an agent project receives a control instruction from an ai-cluster-processor, the control information can be obtained by extracting information from the ai-cluster-processor control instruction. The obtained control information is then formatted to generate script information corresponding to the control instruction. After the script information corresponding to the control instruction is generated, the script information corresponding to the control instruction is executed. This is merely a specific illustration and is not intended to be limiting. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, storage, and display, etc.) referred to in this application, such as data used for verification, are all information and data authorized by the user or fully authorized by all parties. The collection, use, and processing of the relevant data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation portals are provided for the user to select authorization or rejection. It should be noted that, for simplicity of description, the aforementioned method embodiments are described as a series of actions. However, those skilled in the art should be aware that this application is not limited by the order of the actions described, as certain steps may be performed in a different order or simultaneously, depending on the application. Furthermore, those skilled in the art should also be aware that the embodiments described in this specification are preferred embodiments, and the actions and modules involved are not necessarily required for this application.Through the above description of the embodiments, those skilled in the art will clearly understand that the methods according to the above embodiments can be implemented using software and a necessary general-purpose hardware platform, or alternatively, hardware. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk) and includes instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the cluster creation methods of the various embodiments of this application. Example 2: The method embodiment provided in Example 1 of this application can be executed in a mobile terminal, a computer terminal, or a similar computing device. Figure 6 shows a hardware block diagram of a computer terminal (or mobile device) configured to implement the cluster creation method. As shown in FIG6 , a computer terminal 60 (or mobile device) may include one or more processors 602 (illustrated as 602a, 602b, 602n) (the processor 602 may include, but is not limited to, a processing device such as a microprocessor (MCU) or a programmable logic device (FPGA), a memory 604 configured to store data, and a transmission module 606 configured to perform communication functions. In addition, the computer terminal 60 may include: a display, an input / output interface (I / O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS), a network interface, a power supply, and / or a camera. Those skilled in the art will appreciate that the structure shown in FIG6 is merely illustrative and does not limit the structure of the electronic device. For example, the computer terminal 60 may include more or fewer components than shown in FIG6 , or have a configuration different from that shown in FIG6 . It should be noted that the one or more processors 602 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuit can be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuit can be a single independent processing module, or fully or partially integrated into any other component of the computer terminal 60 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selecting a variable resistor terminal path connected to an interface).The memory 604 can be configured to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the methods in the embodiments of the present application. The processor 602 executes the software programs and modules stored in the memory 604 to perform various functional applications and data processing, thereby implementing the cluster creation method in the above-described embodiments. The memory 604 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 604 may further include memory remote from the processor 602, and these remote memories can be connected to the computer terminal 60 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The transmission device 606 is configured to receive or transmit data via a network. Specific examples of such networks may include a wireless network provided by the telecommunications provider of the computer terminal 60. In one example, the transmission device 606 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In one example, the transmission device 606 may be a radio frequency (RF) module configured to communicate wirelessly with the Internet. The display may be, for example, a touchscreen liquid crystal display (LCD), which enables a user to interact with the user interface of the computer terminal 60 (or mobile device). The hardware block diagram shown in FIG6 can serve not only as an exemplary block diagram of the aforementioned computer terminal 60 (or mobile device), but also as an exemplary block diagram of the aforementioned server. In an alternative embodiment, FIG7 shows a block diagram of an embodiment using the computer terminal 60 (or mobile device) shown in FIG6 as a computing node in a computing environment 701. FIG7 shows a block diagram of a computing environment. As shown in FIG7 , computing environment 701 includes multiple computing nodes (e.g., servers) (illustrated as 710 - 1 and 710 - 2 ) running on a distributed network. Each computing node includes local processing and memory resources, allowing end users 702 to remotely run applications or store data in computing environment 701. The application may be provided as multiple services 720-1, 720-2, 720-3, and 720-4 in the computing environment 701, representing services "A," "D," "E," and "H," respectively.End user 702 can provision and access services through a web browser or other software application on a client. In some embodiments, end user 702's provisioning and / or requests can be provided to ingress gateway 730. Ingress gateway 730 can include a corresponding agent to handle provisioning and / or requests for services (one or more services provided in computing environment 701). Services are provided or deployed based on various virtualization technologies supported by computing environment 701. In some embodiments, services can be provided using virtual machine (VM)-based virtualization, container-based virtualization, and / or similar approaches. VM-based virtualization can simulate a real computer by initializing a virtual machine, executing programs and applications without directly accessing any actual hardware resources. While VMs virtualize machines, container-based virtualization can launch containers to virtualize the entire operating system (OS), allowing multiple workloads to run on a single OS instance. In one embodiment based on container virtualization, several service containers can be assembled into a pod (e.g., a Kubernetes pod). For example, as shown in FIG7 , service 720-2 can be configured. One or more Pods 740-1, 740-2, 740-N (collectively referred to as Pods). A Pod may include an agent 745 and one or more containers 742-1,

[0002] 742-2, 742-M (collectively referred to as containers). One or more containers in a pod process requests related to one or more corresponding functions of a service. Proxy 745 typically controls network functions related to the service, such as routing and load balancing. Similar pods may also be deployed for other services. During operation, executing a user request from end user 702 may require invoking one or more services in computing environment 701. Executing one or more functions of one service may require invoking one or more functions of another service. As shown in Figure 7, service "A" 720-1 receives a user request from end user 702 from ingress gateway 730. Service "A" 720-1 may invoke service "D" 720-2, which in turn may request service "E" 720-3 to execute one or more functions. The computing environment described above may be a cloud computing environment, where resource allocation is managed by the cloud service provider, allowing for feature development without having to worry about implementing, adjusting, or scaling servers. This computing environment allows developers to execute code in response to events without building or maintaining complex infrastructure. Instead of expanding a single hardware device to handle potential load, services can be partitioned to complete a set of functions that can be automatically and independently scaled. In another alternative embodiment, FIG8 shows a block diagram of an embodiment using the computer terminal 60 (or mobile device) shown in FIG6 as a service grid. FIG8 illustrates a structural block diagram of a service grid. As shown in FIG8 , service grid 800 is primarily used to facilitate secure and reliable communication between multiple microservices. Microservices refer to applications that are decomposed into multiple smaller services or instances and distributed across different clusters / machines. As shown in FIG8 , microservices may include application service instance A and application service instance B, which form the functional application layer of service grid 800. In one embodiment, application service instance A runs as a container / process 808 on a machine / workload container group 814 (Pod), and application service instance B runs as a container / process 810 on a machine / workload container group 816 (Pod). In one embodiment, application service instance A may be a product query service, and application service instance B may be a product ordering service. As shown in Figure 8 , application service instance A and mesh proxy (sidecar) 803 coexist in machine workload container group 814, while application service instance B and mesh proxy 805 coexist in machine workload container 816. Mesh proxy 803 and mesh proxy 805 form the data plane layer of service mesh 800.Grid proxy 803 and grid proxy 805 run as container / process 804 and container / process 806, respectively, and can receive request 812 for product query services. Grid proxy 803 and application service instance A can communicate bidirectionally, while grid proxy 805 and application service instance B can communicate bidirectionally. Furthermore, grid proxy 803 and grid proxy 805 can also communicate bidirectionally with each other. In one embodiment, all traffic from application service instance A is routed to the appropriate destination via grid proxy 803, while all network traffic from application service instance B is routed to the appropriate destination via grid proxy 805. It should be noted that the network traffic mentioned herein includes, but is not limited to, Hypertext Transfer Protocol (HTTP), Representational State Transfer (REST), the high-performance, general-purpose open source framework (Google Remote Procedure Call, gRPC), and the open source in-memory data structure storage system (Redis). In one embodiment, the functionality of the extended data plane layer can be implemented by writing custom filters for the proxy (Envoy) in service mesh 800. The service mesh proxy configuration can be designed to enable the service mesh to correctly proxy service traffic, achieving service interoperability and service governance. Mesh proxy 803 and mesh proxy 805 can be configured to perform at least one of the following functions: service discovery, health checking, routing, load balancing, authentication and authorization, and observability. As shown in FIG8 , service mesh 300 also includes a control plane layer. The control plane layer can be composed of a set of services running in a dedicated namespace, hosted by a managed control plane component 801 within a machine / workload container group (machine / pod) 802. As shown in FIG8 , managed control plane component 801 communicates bidirectionally with mesh proxy 803 and mesh proxy 805. The managed control plane component 801 is configured to perform some control management functions.For example, managed control plane component 801 receives telemetry data transmitted by grid agents 803 and 805 and can further aggregate this telemetry data. For these services, managed control plane component 801 can also provide user-oriented application programming interfaces (APIs) to easily manipulate network behavior and provide configuration data to grid agents 803 and 805. During AI cluster delivery, cloud operating systems (Kubernetes) can be used to create clusters, while application deployment platforms can be used to create single clusters. However, cloud operating systems cannot perform the deployment operations required before cluster creation or the installation operations required after cluster creation. Application deployment platforms cannot meet the requirements of hybrid cluster systems, such as hybrid clusters (Slurm + Kubernetes), resulting in low cluster creation efficiency. This application provides a cluster creation method that addresses the technical issue of low cluster creation efficiency. This method, unlike traditional solutions that cannot guarantee the complete cluster delivery process, addresses the technical issue of low cluster creation efficiency. In this embodiment of the present application, a cluster baseline is configured based on the customer's network information, and the cluster is created by inputting the cluster baseline into a cluster creation template. This ensures cluster delivery, thereby achieving the technical effect of improving cluster creation efficiency and addressing the technical issue of low cluster creation efficiency. The above-mentioned method of this embodiment is further described below. In this embodiment, to address the technical issue of low cluster creation efficiency, a cluster creation system architecture is proposed. Figure 9 is a schematic diagram of the architecture of a cluster creation system according to an embodiment of the present application. As shown in Figure 9, the architecture 900 may include an AID front-end project 901, an AID back-end project 902, an ai-cluster-processor project 903, and an agent project 904.In this embodiment, the AID front-end project 901 can be used to display the interface and manage the cluster. The AID back-end project 902 can be used to manage the functions of various modules in the cluster creation system. The ai-cluster-processor project 903 can be used to perform agent management and process execution. The agent project 904 can be used to accept external management and control. The ai-cluster-processor project 903 can run on a Kubernetes cluster, relying on the Tekton Pipeline, an open source framework for building a continuous integration / continuous deployment (CI / CD) pipeline system, to perform agent management and process execution. The agent project 904 can run on node resources to accept external management and control. In this embodiment, the cluster creation process may include the following steps: Step 1: The physical server module is responsible for managing and controlling local physical servers and performing batch OS installation on them, bringing them under management. For example, this includes performing operations such as server information acquisition, restarting, shutting down, and client installation. In the technical solution provided in Step 1 above, the OS installation can be implemented using an operating system template, which can be used to represent the rules for installing an OS on a server. In this embodiment, the OS is installed on the server using an operating system template. For example, before installing the OS on a server, different operating system templates are customized in advance. The server's required OS is then determined based on the server's requirements. Based on the determined OS, the OS is installed on the server using an OS template that matches the required OS. Optionally, the cluster's automated OS installation process can rely on an operating system installation platform (such as, but not limited to, iClone) for system installation, or can configure and configure a setup service (such as, but not limited to, DHCP+PXE) for automated system installation. In step 2, the node resource module is responsible for importing the physical server with the client already installed, making it part of the node resource pool. In the technical solution provided in step 2 above, after the physical server module manages and controls the local physical servers and performs batch OS installation on them, the node resource module imports the physical server with the client already installed, making it part of the node resource pool.In this embodiment, the node resource pool can be used to represent the storage space of servers capable of creating a cluster. In step three, the cluster module selects appropriate node resources to create the cluster and automatically obtains a default cluster baseline based on the cluster type and configuration information. After cluster creation begins, a cluster creation task is created based on the cluster information and the configured cluster creation template. In the technical solution provided in step three of this application, after the node resource module imports a physical server with a client installed and makes it part of the node resource pool, step three is entered. In this embodiment, the cluster baseline can be used to at least describe the creation parameters required for the cluster to be created. For example, the cluster baseline can be a collection of information describing various relevant information related to the cluster. The relevant information related to the cluster can include at least software, configuration, applications, tags, and other related information. This is for illustrative purposes only and is not intended to be a specific limitation. In this embodiment, the cluster creation template can be defined based on the cluster type. For example, the cluster creation template can include at least one of the following templates: a template corresponding to a k8s cluster type, a template corresponding to a slurm cluster type, a template corresponding to both a k8s cluster type and a slurm cluster type, a template corresponding to an LSF cluster type, a template corresponding to a GFS cluster type, etc. These examples are provided for illustration only and are not intended to be limiting. Optionally, when a new customer requires delivery, a cluster can be created and a cluster baseline configured based on the customer's network configuration. The configured cluster baseline can then be tested and exported. After the AID system is established at the customer site, the configured baseline can be imported to achieve automated cluster creation. In step 4, the cluster creation task (cluster init task) corresponds to a cluster creation process (tekton pipeline run). The cluster creation process (tekton pipeline run) consists of a series of tasks, including node inspection, software installation, configuration installation, cluster creation, and application creation. Each task is executed in a containerized manner, and the execution entity is the processor (ai-cluster-processor). After each task is executed, the central system (AID backend engineering) is notified to track progress and display it in the job task details. In the technical solution provided in step 4 of this application, after creating a cluster creation task based on cluster information and the set cluster creation template, step 4 is entered.In this embodiment, during the cluster creation process, the entire creation process is divided into several process tasks. Corresponding operations are performed in each process task, such as pre-check > node resource check, software installation > software check, configuration installation > configuration check, cluster installation, cluster check, and application installation > application check. Optionally, during node provisioning, the software required for the cluster can be installed, thereby omitting the software installation process. Consequently, during cluster creation, software installation and the involvement of the software repository are not required. Alternatively, based on a user's customized requirements, whether to add or delete the cluster creation process is determined. If it is determined that additions or deletions are necessary, the creation process is adjusted accordingly, thereby achieving the goal of delivering customized requirements to the user. In step 5, resources are acquired and configured during the node creation process using a pre-prepared repository. These repositories may include software repositories, image repositories, and application repositories. In the technical solution provided in step 5 above, after tracking progress is displayed in the job task details, the node creation process proceeds to the pre-prepared repository to complete resource acquisition and configuration. In this embodiment, cluster creation resources can be acquired through the pre-prepared repository. These acquired cluster creation resources can then be used to trigger the node to create a cluster that matches the cluster creation scenario. In step 6, the cluster creation process supports the creation and management of multiple clusters. In the technical solution provided in step 6 above, after resource acquisition and configuration are completed during the node creation process using the pre-prepared repository, the creation and management of multiple clusters are supported. In this embodiment, when creating a cluster, multiple clusters can be extended and created together. For example, during the process of creating a kubemetes cluster, a CPFS cluster can also be created at the same time. Alternatively, the cluster creation can be taken as the main line, and the corresponding content can be prepared directly during the cluster creation process.Optionally, during cluster creation, you can use the push creation model of CS, or the pull creation model, where the central server exposes a creation service interface and the client independently pulls cluster information. This allows creation as long as there is one-way connectivity between the client and the central server. The central server can be deployed on an ECS instance and expose a public network interface, while cluster nodes do not need to expose the public network or any external interfaces. Furthermore, in addition to supporting the creation and management of multiple clusters during cluster creation, the creation and management of a single cluster are also supported. Based on the architecture shown in FIG9 , the global framework of the cluster creation system is further illustrated. FIG10 is a schematic diagram of the global framework of a cluster creation system according to an embodiment of the present application. As shown in FIG10 , the framework may include: a front-end rendering framework 1001, an AID server 1002, a node resource pool 1003, a physical server 1004, a remote server 1005, an integrated deployment framework 1006 on the cluster Kubernetes, a software repository 1007, an image repository 1008, and an application repository 1009. In this embodiment, the physical server 1004 may be a locally networked server group that may be connected to a 25G management and control network and a 100G / 200G Remote Direct Memory Access (RDMA) network. The remote server 1005 may be an ECS server or an EC2 server. Both the physical server and the remote server may serve as node resources for the cluster creation system. In this embodiment, the node resources of the cluster creation system have all been installed with an agent and are subject to AID management. Some node resources in the node resource pool can become part of a cluster, while the remaining node resources remain in the node resource pool for backup. Multiple clusters can be created, and the created clusters can be either Kubernetes or Slurm clusters. This is merely an example and not a limitation. In this embodiment, each cluster corresponds to a baseline. There can be multiple baselines, but the corresponding baselines are unique. When a baseline is changed, it becomes the new baseline version, while the old baseline is preserved and cannot be deleted to ensure that the new baseline can be rolled back to the old one.The cluster creation process is implemented by instantiating (running) the cluster creation template (pipeline). After the cluster baseline is configured, cluster parameters are passed to the node creation instance (pipeline run). A node creation instance can consist of multiple tasks. In this embodiment, all tasks are executed by the ai-cluster-processor. The ai-cluster-processor selects the corresponding executor (handler) based on the passed cluster parameters. The ai-cluster-processor is containerized and can be divided into three phases: phase selector > action processor > progress notification. During each processing step, the phase selector identifies the current pipeline phase based on the passed cluster parameters. The action processor selects the corresponding executor based on the identified phase. After execution, the progress notification phase begins. The AID backend project can track the current phase of the cluster creation process. Optionally, during the execution of the ai-cluster-processor, corresponding node resources are controlled in a client-server (CS) model. The ai-cluster-agent installed on the node resources provides service capabilities and accepts external control. The control process interacts with the ai-cluster-agent on the node through the ai-cluster-agent SDK. Optionally, after the ai-cluster-processor issues software installation commands, configuration commands, and application installation commands, the node executes the corresponding commands, downloads the corresponding content from the software repository, image repository, and application repository, and performs installation.In an embodiment of the present application, the physical server module is responsible for managing and controlling local physical servers and performing batch OS installation on them. After the servers are managed, the node resource module is responsible for importing physical servers with clients installed, making them part of the node resource pool. The cluster module then selects corresponding node resources to create a cluster and automatically obtains a default cluster baseline based on the cluster type and configuration information. After cluster creation begins, a cluster creation task is created based on the cluster information and the configured cluster creation template. Each cluster creation task corresponds to a cluster creation process. Resource acquisition and configuration during the node creation process are then completed using a pre-prepared repository. Since the complete cluster delivery process is implemented, cluster delivery is guaranteed, thereby achieving the technical effect of improving cluster creation efficiency and resolving the technical issue of low cluster creation efficiency. Example 3: According to an embodiment of the present application, a cluster creation device configured to implement the cluster creation method shown in FIG. 2 is also provided. FIG11 is a schematic diagram of a cluster creation apparatus according to an embodiment of the present application. As shown in FIG11 , the cluster creation apparatus 1100 may include: a first acquisition unit 1102, a first configuration unit 1104, a first input unit 1106, and a first creation unit 1108. The first acquisition unit 1102 is configured to acquire network information in a cluster creation scenario, where the cluster creation scenario represents a scenario to which at least one cluster to be created belongs. The first configuration unit 1104 is configured to configure creation parameters required for the cluster to be created based on the network information. The first input unit 1106 is configured to input the creation parameters into a cluster creation template that matches the type of the cluster to be created. The cluster creation template represents the rules that the cluster to be created must meet during its creation. The first creation unit 1108 is configured to use the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. Here, the first obtaining unit 1102, the first configuring unit 1104, the first input unit 1106 and the first creating unit 1108 correspond to steps S202 to S208 in Example 2. The examples and application scenarios implemented by the four units and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 2.It should be noted that the above-mentioned units may be hardware components or software components stored in a memory (e.g., memory 1404) and processed by one or more processors (e.g., processors 602a, 602b, ..., 602n). The above-mentioned units may also be part of a device and run in the computer terminal 60 provided in Example 2. According to an embodiment of the present application, a cluster creation device configured to implement the cluster creation method shown in FIG. 3 is also provided. FIG. 12 is a schematic diagram of a cluster creation device according to an embodiment of the present application. As shown in FIG. 12 , the cluster creation device 1200 may include a second acquisition unit 1202, a second configuration unit 1204, a second input unit 1206, and a second creation unit 1208. The second acquisition unit 1202 is configured to acquire network information in a cluster delivery scenario, where the cluster delivery scenario represents the delivery scenario to which at least one cluster to be created belongs. The second configuration unit 1204 is configured to configure a cluster baseline for the cluster to be created based on network information, where the cluster baseline describes at least the creation parameters required during the creation of the cluster to be created. The second input unit 1206 is configured to input the cluster baseline into a cluster creation template that matches the type of cluster to be created, where the cluster creation template represents the rules that must be met during the creation of the cluster to be created. The second creation unit 1208 is configured to use the cluster baseline in the cluster creation template to create a cluster that matches the cluster delivery scenario. It should be noted that the second acquisition unit 1202, second configuration unit 1204, second input unit 1206, and second creation unit 1208 described above correspond to steps S302 to S308 in Example 2. The examples and application scenarios implemented by these four units and the corresponding steps are the same, but are not limited to the content disclosed in Example 2. It should be noted that the aforementioned units may be hardware components or software components stored in a memory (e.g., memory 1404) and processed by one or more processors (e.g., processors 602a, 602b, and 602n). The aforementioned units may also be part of a device and run in the computer terminal 60 provided in Example 2. According to an embodiment of the present application, a cluster creation device configured to implement the cluster creation method shown in FIG. 4 is also provided. FIG. 13 is a schematic diagram of another cluster creation device according to an embodiment of the present application. As shown in FIG. 13 , the cluster creation device 1300 may include a first response unit 1302 and a second response unit 1304.A first response unit 1302 is configured to respond to input operations on an operation interface and input network information for a cluster creation scenario on the operation interface. The cluster creation scenario represents the scenario to which at least one cluster to be created belongs. A second response unit 1304 is configured to respond to cluster creation operations on the operation interface and display, on the operation interface, the creation result of a cluster matching the cluster creation scenario. The cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template. The cluster creation template represents the rules that must be met during the creation of the cluster to be created, and the creation parameters are configured based on network information. It should be noted that the first response unit 1302 and the second response unit 1304 correspond to steps S402 to S404 in Example 2. The examples and application scenarios implemented by the two units and the corresponding steps are the same, but are not limited to the content disclosed in Example 2. It should be noted that the above-mentioned unit may be a hardware component or software component stored in a memory (e.g., memory 1404) and processed by one or more processors (e.g., processors 602a, 602b, 602n). The above-mentioned unit may also be part of a device and run in the computer terminal 60 provided in Example 2. In the cluster creation device, when creating a cluster, network information for the scenario to which at least one cluster to be created belongs is obtained. Based on the obtained network information, creation parameters required for the cluster to be created during the creation process may be configured. The configured creation parameters are then input into a cluster creation template that matches the type of cluster to be created. The configured creation parameters are then used in the cluster creation template to create a cluster that matches the cluster creation scenario, thereby completing cluster creation. Since the complete cluster delivery process has been implemented, the purpose of ensuring cluster delivery is achieved, thereby achieving the technical effect of improving the efficiency of cluster creation and solving the technical problem of low cluster creation efficiency. It should be noted that the preferred implementation scheme involved in the above-mentioned embodiments of this application is the same as the scheme, application scenario, and implementation process provided in Example 1, but is not limited to the scheme provided in Example 1. Embodiment 4: An embodiment of the present application may provide an electronic device, which may be any electronic device in a group of electronic devices. Optionally, in this embodiment, the electronic device may be replaced by a terminal device such as a mobile terminal. Optionally, in this embodiment, the electronic device may be located in at least one of multiple network devices in a computer network. In this embodiment, the computer terminal may execute the program code in the method.Optionally, Figure 14 is a block diagram of an electronic device according to a cluster creation method according to an embodiment of the present application. As shown in Figure 14 , electronic device A may include: one or more (only one shown) processors 1402, memory 1404, a storage controller, and a peripheral interface, wherein the peripheral interface is connected to a radio frequency module, an audio module, and a display. The memory may be configured to store software programs and modules, such as program instructions / modules corresponding to the methods and apparatuses in the embodiments of the present application. The processor executes the software programs and modules stored in the memory to execute various functional applications and data processing, thereby implementing the methods in the aforementioned embodiments. The memory may include high-speed random access memory (RAM) and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory located remotely from the processor, which may be connected to terminal A via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The processor may invoke information and applications stored in the memory to perform the following steps: obtaining network information for a cluster creation scenario, wherein the cluster creation scenario represents the scenario to which at least one cluster to be created belongs; configuring creation parameters required for the cluster to be created based on the network information; inputting the creation parameters into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template represents the rules that must be met during the creation of the cluster to be created; and using the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: creating an instance object using the creation parameters in the cluster creation template, wherein the instance object represents the creation process for the cluster to be created; and creating a cluster that matches the cluster creation scenario using the creation parameters according to the creation process corresponding to the instance object. Optionally, the processor may further execute program code for the following steps: determining multiple tasks in the instance object that correspond to the creation process; and sequentially executing the multiple tasks using the creation parameters according to the creation process to obtain a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code of the following steps: calling the processor to execute multiple tasks in sequence in a containerized manner according to the creation process using creation parameters to obtain cluster creation instructions corresponding to the tasks; in response to the cluster creation instructions, triggering corresponding nodes in the node resource pool to create a cluster that matches the cluster creation scenario, wherein the node is set to represent a server with a client installed, and the client is set to provide control services for the server.Optionally, the processor may further execute program code for the following steps: in response to a cluster creation instruction, obtain cluster creation resources from a data warehouse; and, using the cluster creation resources, trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: in response to the cluster creation instruction, invoke pre-configured cluster creation resources to trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: installing an operating system on a server using an operating system template, where the operating system template represents rules for installing an operating system on a server. Optionally, the processor may further execute program code for the following steps: determining a cluster creation phase; and outputting prompt information for the creation phase. Optionally, the processor may further execute program code for the following steps: adjusting the creation process in response to an adjustment operation on the creation process. Optionally, the processor may further execute program code for the following steps: configuring a cluster baseline for the cluster to be created based on network information, where the cluster baseline at least describes the creation parameters required during the creation of the cluster to be created. Optionally, the processor may further execute program code for the following steps: determining cluster information of a cluster to be created based on network information; and configuring a cluster baseline based on the cluster information of the cluster to be created. Optionally, the processor may further execute program code for the following steps: updating a cluster baseline, wherein the updated cluster baseline allows switching to a pre-updated cluster baseline. Optionally, the processor may invoke information and an application stored in a memory to perform the following steps: obtaining network information for a cluster delivery scenario, wherein the cluster delivery scenario represents a delivery scenario to which at least one cluster to be created belongs; configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline describes at least creation parameters required during the creation of the cluster to be created; inputting the cluster baseline into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template represents rules that must be met during the creation of the cluster to be created; and using the cluster baseline in the cluster creation template to create a cluster that matches the cluster delivery scenario.Optionally, the processor may invoke information and an application stored in the memory to perform the following steps: In response to an input operation on an operation interface, network information for a cluster creation scenario is input on the operation interface, where the cluster creation scenario represents a scenario to which at least one cluster to be created belongs; and in response to the cluster creation operation on the operation interface, a cluster creation result matching the cluster creation scenario is displayed on the operation interface, where the cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template, where the cluster creation template represents rules that the cluster to be created must meet during creation, and the creation parameters are configured based on the network information. Embodiments of the present application provide a cluster creation method. In an embodiment of the present application, when creating a cluster, network information for the scenario to which at least one cluster to be created belongs is obtained. Based on the obtained network information, creation parameters required for the cluster to be created can be configured. The configured creation parameters are then input into a cluster creation template that matches the type of cluster to be created. The configured creation parameters are then used in the cluster creation template to create a cluster that matches the cluster creation scenario, thereby completing cluster creation. Since the complete cluster delivery process has been implemented, the purpose of ensuring cluster delivery is achieved, thereby achieving the technical effect of improving cluster creation efficiency and solving the technical problem of low cluster creation efficiency. It will be understood by those skilled in the art that the structure shown in FIG6 is merely illustrative, and computer terminal A may also be a smartphone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, or a mobile internet device (MID), PAD, or other terminal device. FIG6 does not limit the structure of the computer terminal A described above. For example, computer terminal A may include more or fewer components (such as a network interface, a display device, etc.) than those shown in FIG6 , or have a configuration different from that shown in FIG6 . Optionally, FIG15 is a structural block diagram of a computer terminal according to an embodiment of the present application. As shown in FIG15 , the computer terminal A may include one or more (only one is shown in the figure) processors 1502, a memory 1504, and a transmission device 1506. The memory may be configured to store software programs and modules, such as program instructions / modules corresponding to the cluster creation method and apparatus in the embodiments of the present application. The processor executes the software programs and modules stored in the memory to execute various functional applications and data processing, thereby implementing the aforementioned cluster creation method.The memory may include high-speed random access memory (RAM) and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory located remotely from the processor, which can be connected to computer terminal A via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The processor may access information and applications stored in the memory via a transmission device to perform the following steps: obtaining network information for a cluster creation scenario, where the cluster creation scenario represents the scenario to which at least one cluster to be created belongs; configuring creation parameters required for the cluster to be created based on the network information; inputting the creation parameters into a cluster creation template that matches the type of cluster to be created, where the cluster creation template represents the rules that must be met during the creation of the cluster to be created; and using the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: creating an instance object using creation parameters in a cluster creation template, wherein the instance object represents the creation process for the cluster to be created; creating a cluster matching the cluster creation scenario using the creation parameters according to the creation process corresponding to the instance object. Optionally, the processor may further execute program code for the following steps: determining multiple tasks corresponding to the creation process in the instance object; sequentially executing the multiple tasks using the creation parameters according to the creation process to obtain a cluster matching the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: invoking a processor to sequentially execute the multiple tasks using the creation parameters in a containerized manner according to the creation process to obtain cluster creation instructions corresponding to the tasks; and, in response to the cluster creation instructions, triggering corresponding nodes in a node resource pool to create a cluster matching the cluster creation scenario, wherein the nodes are configured to represent servers with a client installed, and the clients are configured to provide control services for the servers. Optionally, the processor may further execute program code for the following steps: in response to a cluster creation instruction, obtaining cluster creation resources from a data warehouse; and using the cluster creation resources to trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: in response to the cluster creation instruction, invoking preset cluster creation resources to trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the processor may further execute program code for the following steps: installing an operating system on a server using an operating system template, where the operating system template represents rules for installing the operating system on the server.Optionally, the processor may further execute program code for the following steps: determining a cluster creation stage; and outputting prompt information for the creation stage. Optionally, the processor may further execute program code for the following steps: adjusting the creation process in response to an adjustment operation on the creation process. Optionally, the processor may further execute program code for the following steps: configuring a cluster baseline for the cluster to be created based on network information, wherein the cluster baseline is used to at least describe creation parameters required during the creation of the cluster to be created. Optionally, the processor may further execute program code for the following steps: determining cluster information for the cluster to be created based on network information; and configuring a cluster baseline based on the cluster information of the cluster to be created. Optionally, the processor may further execute program code for the following steps: updating the cluster baseline, wherein the updated cluster baseline allows switching to a pre-updated cluster baseline. Optionally, the processor may call information and an application stored in the memory through the transmission device to perform the following steps: obtaining network information in a cluster delivery scenario, wherein the cluster delivery scenario is used to represent a delivery scenario to which at least one cluster to be created belongs; configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline is used to at least describe creation parameters required during the creation of the cluster to be created; inputting the cluster baseline into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template is used to represent rules that need to be satisfied during the creation of the cluster to be created; and using the cluster baseline in the cluster creation template to create a cluster that matches the cluster delivery scenario. Optionally, the processor may call information and an application stored in the memory through the transmission device to perform the following steps: in response to an input operation on the operation interface, input network information under a cluster creation scenario on the operation interface, wherein the cluster creation scenario is used to represent a scenario to which at least one cluster to be created belongs; in response to the cluster creation operation on the operation interface, display a creation result of a cluster matching the cluster creation scenario on the operation interface, wherein the cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template, the cluster creation template is used to represent rules that need to be satisfied during the creation process of the cluster to be created, and the creation parameters are configured based on the network information.Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware of the terminal device through a program. The program can be stored in a computer-readable storage medium, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Example 5: The embodiments of the present application also provide a computer-readable storage medium. Optionally, in this embodiment, the computer-readable storage medium can be used to store program code executed by the methods provided in the above embodiments. Optionally, in this embodiment, the storage medium can be located in any electronic device in a group of electronic devices in a computer network, or in any mobile terminal in a group of mobile terminals. Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: obtaining network information for a cluster creation scenario, wherein the cluster creation scenario represents the scenario to which at least one cluster to be created belongs; configuring creation parameters required for the cluster to be created based on the network information; inputting the creation parameters into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template represents the rules that the cluster to be created must meet during its creation; and using the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario. Optionally, the computer-readable storage medium may further execute program code for executing the following steps: creating an instance object using the creation parameters in the cluster creation template, wherein the instance object represents the creation process for the cluster to be created; and creating a cluster that matches the cluster creation scenario using the creation parameters according to the creation process corresponding to the instance object. Optionally, the computer-readable storage medium may further execute program code for executing the following steps: determining multiple tasks in the instance object that correspond to the creation process; and sequentially executing the multiple tasks using the creation parameters according to the creation process to obtain a cluster that matches the cluster creation scenario. Optionally, the computer-readable storage medium may further execute program code of the following steps: calling a processor to execute multiple tasks in sequence in a containerized manner according to a creation process using creation parameters to obtain cluster creation instructions corresponding to the tasks; and in response to the cluster creation instructions, triggering corresponding nodes in a node resource pool to create a cluster that matches the cluster creation scenario, wherein the nodes are set to represent servers with clients installed, and the clients are set to provide control services for the servers.Optionally, the computer-readable storage medium may further execute program code for the following steps: in response to a cluster creation instruction, obtaining cluster creation resources from a data warehouse; and using the cluster creation resources to trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the computer-readable storage medium may further execute program code for the following steps: in response to the cluster creation instruction, invoking pre-configured cluster creation resources to trigger a node to create a cluster that matches the cluster creation scenario. Optionally, the computer-readable storage medium may further execute program code for the following steps: installing an operating system on a server using an operating system template, where the operating system template represents rules for installing an operating system on a server. Optionally, the computer-readable storage medium may further execute program code for the following steps: determining a cluster creation phase; and outputting prompt information for the creation phase. Optionally, the computer-readable storage medium may further execute program code for the following steps: adjusting the creation process in response to an adjustment operation on the creation process. Optionally, the computer-readable storage medium may further execute program code for: configuring a cluster baseline for a cluster to be created based on network information, wherein the cluster baseline is used to at least describe creation parameters required during creation of the cluster to be created. Optionally, the computer-readable storage medium may further execute program code for: determining cluster information for a cluster to be created based on network information; and configuring a cluster baseline based on the cluster information of the cluster to be created. Optionally, the computer-readable storage medium may further execute program code for: updating a cluster baseline, wherein the updated cluster baseline allows switching to a pre-updated cluster baseline. As an optional example, a computer-readable storage medium is configured to store program code for performing the following steps: obtaining network information in a cluster delivery scenario, wherein the cluster delivery scenario is used to represent a delivery scenario to which at least one cluster to be created belongs; configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline is used to at least describe creation parameters required during the creation of the cluster to be created; inputting the cluster baseline into a cluster creation template that matches the type of the cluster to be created, wherein the cluster creation template is used to represent rules that need to be satisfied during the creation of the cluster to be created; and using the cluster baseline in the cluster creation template to create a cluster that matches the cluster delivery scenario.As an optional example, a computer-readable storage medium is configured to store program code for performing the following steps: in response to an input operation on an operation interface, inputting network information for a cluster creation scenario on the operation interface, wherein the cluster creation scenario represents a scenario to which at least one cluster to be created belongs; and in response to the cluster creation operation on the operation interface, displaying on the operation interface a creation result of a cluster matching the cluster creation scenario, wherein the cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template, wherein the cluster creation template represents rules that must be met during the creation of the cluster to be created, and the creation parameters are configured based on network information. Example 6 An embodiment of the present application further provides a computer program product. Optionally, in this embodiment, the computer program product may include a computer program that, when executed by a processor, implements the cluster creation method provided in the above embodiment. Example 7 An embodiment of the present application further provides a computer program product. Optionally, the computer program product may include a non-volatile computer-readable storage medium, which may be configured to store a computer program. When executed by a processor, the computer program implements the cluster creation method provided in the above embodiment. Example 8: The embodiments of the present application also provide a computer program. Optionally, in this embodiment, when executed by a processor, the computer program implements the cluster creation method provided in the above embodiment. The serial numbers of the embodiments of the present application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the above embodiments of the present application, the descriptions of each embodiment are given with emphasis. For portions not described in detail in a particular embodiment, reference should be made to the relevant descriptions of other embodiments. In the several embodiments provided in this application, it should be understood that the disclosed technical content may be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical functional division. In actual implementation, other divisions may be used. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through interfaces, indirect coupling or communication connection of units or modules, and may be electrical or other forms. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the objectives of this embodiment.Furthermore, the functional units in the various embodiments of the present application may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. These integrated units may be implemented in either hardware or software functional units. If these integrated units are implemented as software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the portion that contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical disks. The above descriptions are merely preferred embodiments of the present application. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present application, and such improvements and modifications should also be considered within the scope of protection of the present application.

Claims

Claims 1. A method for creating a cluster, comprising: Obtaining network information for a cluster creation scenario, where the cluster creation scenario represents a scenario to which at least one cluster to be created belongs; configuring creation parameters required for the cluster to be created based on the network information; inputting the creation parameters into a cluster creation template that matches the type of the cluster to be created, where the cluster creation template represents rules that must be satisfied by the cluster to be created during creation; and creating a cluster that matches the cluster creation scenario using the creation parameters in the cluster creation template.

2. The method according to claim 1, wherein: Using the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario includes: creating an instance object using the creation parameters in the cluster creation template, wherein the instance object is used to represent a creation process of the cluster to be created; and creating the cluster that matches the cluster creation scenario using the creation parameters according to the creation process corresponding to the instance object.

3. The method according to claim 2, wherein: Creating the cluster that matches the cluster creation scenario according to the creation process corresponding to the instance object and using the creation parameters includes: determining multiple tasks corresponding to the creation process in the instance object; and executing the multiple tasks in sequence according to the creation process and using the creation parameters to obtain the cluster that matches the cluster creation scenario.

4. The method according to claim 3, wherein: Executing the multiple tasks in sequence according to the creation process and using the creation parameters to obtain the cluster that matches the cluster creation scenario includes: calling a processor to execute the multiple tasks in sequence according to the creation process and using the creation parameters in a containerized manner to obtain cluster creation instructions corresponding to the tasks; and triggering corresponding nodes in a node resource pool to create the cluster that matches the cluster creation scenario in response to the cluster creation instructions, wherein the nodes are used to represent servers with a client installed, and the client is used to provide control services for the servers.

5. The method according to claim 4, wherein: In response to the cluster creation instruction, triggering a corresponding node in a node resource pool to create the cluster matching the cluster creation scenario includes: in response to the cluster creation instruction, obtaining cluster creation resources from a data warehouse; and using the cluster creation resources to trigger the node to create the cluster matching the cluster creation scenario.

6. The method according to claim 4, wherein: In response to the cluster creation instruction, trigger the node resource pool 36 The corresponding node in the cluster creates the cluster that matches the cluster creation scenario, including: in response to the cluster creation instruction, calling a preset cluster creation resource to trigger the node to create the cluster that matches the cluster creation scenario.

7. The method according to claim 4, wherein: The method further includes: installing an operating system on the server using an operating system template, wherein the operating system template is used to represent a rule for installing the operating system on the server.

8. The method according to claim 3, wherein: In the process of sequentially executing the multiple tasks using the creation parameters, the method further includes: determining a creation stage of the cluster; and outputting prompt information of the creation stage.

9. The method according to claim 3, wherein: The multiple tasks include at least two of the following: an information checking task, used to check information generated during the creation of the cluster to be created; a software installation task, used to install software required during the creation of the cluster to be created; Configuration and installation tasks, used to install the configuration information required during the creation of the cluster to be created; Cluster installation task, used to install the cluster to be created; The application installation task is used to install the applications required by the cluster to be created after it is created.

10. The method according to claim 2, wherein: The method further includes: adjusting the creation process in response to an adjustment operation on the creation process.

11. The method according to claim 1, wherein: Configuring creation parameters required for the cluster to be created during creation based on the network information includes: configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline is used to at least describe the creation parameters required for the cluster to be created during creation.

12. The method according to claim 11, wherein: Configuring a cluster baseline of the cluster to be created based on the network information includes: determining cluster information of the cluster to be created based on the network information; and configuring the cluster baseline based on the cluster information of the cluster to be created.

13. The method according to claim 11, wherein: The method further includes: updating the cluster baseline, wherein the updated cluster baseline allows switching to the cluster baseline before the update.

14. A method for creating a cluster, comprising: Obtaining network information in a cluster delivery scenario, wherein the cluster delivery scenario represents a delivery scenario to which at least one cluster to be created belongs; configuring a cluster baseline for the cluster to be created based on the network information, wherein the cluster baseline describes at least creation parameters required during creation of the cluster to be created; The cluster baseline is input into a cluster creation template that matches the type of the cluster to be created, where the cluster creation template is used to represent the rules that need to be met during the creation process of the cluster to be created; and the cluster baseline is used in the cluster creation template to create a cluster that matches the cluster delivery scenario.

15. A method for creating a cluster, comprising: In response to an input operation performed on an operation interface, network information under a cluster creation scenario is input on the operation interface, wherein the cluster creation scenario is used to represent a scenario to which at least one cluster to be created belongs; and in response to the cluster creation operation performed on the operation interface, a creation result of a cluster matching the cluster creation scenario is displayed on the operation interface, wherein the cluster matching the cluster creation scenario is created using creation parameters in a cluster creation template, the cluster creation template is used to represent rules that the cluster to be created needs to meet during the creation process, and the creation parameters are configured based on the network information.

16. A cluster creation system, comprising: A parameter configuration end is configured to obtain network information in a cluster creation scenario and, based on the network information, configure creation parameters required for a cluster to be created during creation, wherein the cluster creation scenario is used to represent at least one scenario to which the cluster to be created belongs; and a cluster creation end is configured to input the creation parameters into a cluster creation template that matches the type of the cluster to be created, and use the creation parameters in the cluster creation template to create a cluster that matches the cluster creation scenario, wherein the cluster creation template is used to represent rules that must be satisfied during creation of the cluster to be created.

17. The system according to claim 16, wherein: The cluster creation end includes: a processor configured to call a creation process according to the cluster to be created, execute multiple tasks corresponding to the creation process in a containerized manner using the creation parameters, and obtain cluster creation instructions corresponding to the tasks; and a node configured to respond to the cluster creation instruction and create the cluster matching the cluster creation scenario.

18. The system according to claim 16, wherein: The system further includes a client, configured to respond to a control instruction from the cluster creation end and execute script information corresponding to the control instruction.

19. An electronic device, comprising: a memory storing an executable program; A processor is configured to run the program, wherein the program executes the method according to any one of claims 1 to 15 when running.

20. A computer-readable storage medium comprising a stored program, wherein: exist When the program is running, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 15.

21. A computer program product comprising computer instructions, wherein when the computer instructions are executed by a processor, the method according to any one of claims 1 to 15 is implemented.

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