Server automatic deployment method, device and equipment and readable storage medium

Abstract

The invention provides an automatic server deployment method and device, equipment and a readable storage medium, and the method comprises the steps: obtaining the equipment information of a target server, and mounting a mirror image file to the target server according to the equipment information; according to user information and an IP address of a server OS installed from the target server, the server OS is connected in a preset mode, and a cluster deployment program installation package is uploaded to the server OS; and according to preset service cluster configuration information, calling a service cluster deployment program interface of the target server, and configuring and deploying the target server to a service cluster associated with the service cluster configuration information. According to the technical scheme, the server information is automatically obtained, the mirror image file is automatically mounted, the OS is automatically installed, the cluster deployment program is automatically uploaded, and the service cluster is automatically configured, so that the deployment efficiency is greatly improved, the labor cost is reduced, and the intelligent calculation environment is quickly established.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method, device, equipment and readable storage medium for automatic server deployment. Background Art

[0002] As artificial intelligence (AI) technology develops rapidly, the breadth and depth of AI applications continue to increase, and the demand for computing power has also surged. Especially in the field of deep learning, the training and reasoning of large neural network models require a large amount of GPU computing resources. In order to meet this demand, many institutions have begun to establish centralized intelligent computing centers and provide computing power rental services to support enterprises in training, fine-tuning and reasoning of large models.

[0003] However, renting GPU computing resources is not an easy task, as it involves complex technical issues such as computing power segmentation and scheduling. Currently, the technology widely used in the industry is container scheduling technology based on Kubernetes (K8S). Kubernetes is an open source container orchestration platform for automating the deployment, expansion, and management of containerized applications. With Kubernetes, administrators can easily deploy container applications, scale out or scale down applications, and run and manage container applications across host clusters.

[0004] In existing technical solutions, the management of intelligent computing centers usually requires a management cluster to control multiple business clusters and realize resource division and scheduling. Specifically, each server needs to install an operating system (OS), GPU driver, Kubernetes, and management software on top of Kubernetes. After the installation is complete, it is necessary to create business clusters on the management cluster, and the whole process is very complicated and time-consuming.

[0005] For example, if a smart computing center with 100 devices is installed and deployed manually, it will take one man-month to complete the deployment of the entire environment. This deployment method is not only inefficient, but also labor-intensive, which seriously limits the quick response capability and service scalability of the smart computing center. Summary of the invention

[0006] In view of this, the present specification provides a server automatic deployment method, device, electronic device, and readable storage medium to improve the problem of low efficiency of server cluster deployment.

[0007] The specific technical solutions are as follows:

[0008] The present specification provides a server automatic deployment method, which is applied to management equipment, and the method includes: obtaining equipment information of a target server, mounting an image file to the target server according to the equipment information, wherein the image file is used to enable the target server to install a server OS according to the image file; connecting to the server OS in a preset manner according to user information and an IP address of the server OS installed from the target server, and uploading a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install a cluster deployment program in the server OS; calling a business cluster deployment program interface of the target server according to preset business cluster configuration information, and configuring and deploying the target server to a business cluster associated with the business cluster configuration information.

[0009] As a technical solution, the device information of the target server is obtained, and the image file is mounted to the target server according to the device information. The image file is used to enable the target server to install the server OS according to the image file, including: mounting the image file to the target server according to the OS type, KS file, and driver file corresponding to the GPU model, and the image file includes an OS firmware installer, a KS file, and a GPU driver file.

[0010] As a technical solution, the method obtains user information and IP address of the server OS installed on the target server, connects to the server OS in a preset manner, and uploads a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, including: obtaining user information and IP address of the server OS installed on the target server, connecting to the server OS through SSH, and uploading an AMPHA program installation package to the server OS, wherein the AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

[0011] As a technical solution, the business cluster deployment program interface of the target server is called according to the preset business cluster configuration information, and the target server is configured and deployed in the business cluster associated with the business cluster configuration information, including: the business cluster configuration information is obtained from the cluster deployment information input by the user in the initial stage, and the business cluster deployment program interface of the target server is called, and the target server is configured and deployed in the business cluster associated with the business cluster configuration information.

[0012] As a technical solution, each step is executed in a loop until all servers to be deployed in the server cluster are deployed as target servers.

[0013] This specification also provides a server automatic deployment device, which is used for managing equipment, and the device includes: a first module, which is used to obtain device information of the target server, and mount the image file to the target server according to the device information, and the image file is used to enable the target server to install the server OS according to the image file; a second module, which is used to connect to the server OS in a preset manner according to the user information and IP address of the server OS installed from the target server, and upload the cluster deployment program installation package to the server OS, and the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS; a third module, which is used to call the business cluster deployment program interface of the target server according to the preset business cluster configuration information, and configure and deploy the target server to the business cluster associated with the business cluster configuration information.

[0014] As a technical solution, the device information of the target server is obtained, and the image file is mounted to the target server according to the device information. The image file is used to enable the target server to install the server OS according to the image file, including: mounting the image file to the target server according to the OS type, KS file, and driver file corresponding to the GPU model, and the image file includes an OS firmware installer, a KS file, and a GPU driver file.

[0015] As a technical solution, the method obtains user information and IP address of the server OS installed on the target server, connects to the server OS in a preset manner, and uploads a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, including: obtaining user information and IP address of the server OS installed on the target server, connecting to the server OS through SSH, and uploading an AMPHA program installation package to the server OS, wherein the AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

[0016] As a technical solution, the business cluster deployment program interface of the target server is called according to the preset business cluster configuration information, and the target server is configured and deployed in the business cluster associated with the business cluster configuration information, including: the business cluster configuration information is obtained from the cluster deployment information input by the user in the initial stage, and the business cluster deployment program interface of the target server is called, and the target server is configured and deployed in the business cluster associated with the business cluster configuration information.

[0017] As a technical solution, the first module, the second module and the third module are cycled until all the servers to be deployed in the server cluster are deployed as target servers.

[0018] This specification also provides an electronic device, including a processor and a readable storage medium, wherein the readable storage medium stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the aforementioned server automatic deployment method.

[0019] This specification also provides a readable storage medium, which stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the aforementioned server automatic deployment method.

[0020] The above technical solution provided in this specification brings at least the following beneficial effects:

[0021] Automatically obtain the device information of the target server and mount the image file to realize the automatic installation of the server OS; then use the preset method to connect to the server OS, upload the cluster deployment program installation package and automatically install it; finally, call the interface according to the business cluster configuration information to complete the cluster configuration and deployment, which significantly improves the server deployment efficiency and reduces labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the implementation methods of this specification or the technical solutions in the prior art, the drawings required for use in the implementation methods of this specification or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some implementation methods recorded in this specification. For ordinary technicians in this field, other drawings can also be obtained based on these drawings of the implementation methods of this specification.

[0023] Figure 1 is a flow chart of a method for automatic server deployment in one implementation of this specification;

[0024] Figure 2 is a structural diagram of a server automatic deployment device in one implementation mode of this specification;

[0025] Figure 3 It is a hardware structure diagram of an electronic device in one implementation mode of this specification.

[0026] Reference numerals: first module 21 , second module 22 , third module 23 . DETAILED DESCRIPTION

[0027] The terms used in the embodiments of this specification are only for the purpose of describing specific embodiments, rather than limiting this specification. The singular forms of "a", "said" and "the" used in this specification and claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to any or all possible combinations of one or more associated listed items.

[0028] It should be understood that although the terms first, second, third, etc. may be used to describe various information in the embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, in addition, the word "if" used may be interpreted as "at the time of" or "when" or "in response to determining".

[0029] With the rapid development of artificial intelligence technology, various large-scale machine learning models have emerged one after another, which not only promotes the progress of scientific research, but also brings unprecedented opportunities to enterprises. However, the training, fine-tuning and reasoning of these large models often require a large amount of computing resources, especially high-performance graphics processing unit (GPU) resources. Faced with this demand, many institutions have begun to build centralized intelligent computing centers, aiming to provide necessary computing support to external enterprises through the leasing of computing power. This model can not only improve resource utilization, but also reduce the initial investment cost of enterprises.

[0030] Despite this, the construction and operation of intelligent computing centers face a series of challenges, the most notable of which is how to efficiently manage and schedule these valuable computing resources. The traditional computing power leasing model usually involves complex computing power segmentation, computing power scheduling and other issues, and the solution to these problems often relies on container scheduling technology based on Kubernetes (K8S). As an open source platform, K8S is designed for managing containerized applications on multiple hosts in a cloud platform. Its powerful application deployment, planning, updating and maintenance functions make it an indispensable technical support in the current construction of intelligent computing centers. However, even with the support of K8S, building an intelligent computing environment from scratch is still a cumbersome and time-consuming process.

[0031] Specifically, the construction of an intelligent computing environment usually requires the following steps: first, install the operating system on each server; second, install specific GPU drivers to ensure that the hardware can be correctly identified and supported; third, deploy K8S and related components to lay the foundation for the subsequent containerized operation of applications; finally, create and configure each business cluster on the management cluster to achieve effective allocation and management of resources. This series of operations not only has high technical requirements, but also has a huge workload. For example, if you need to build an intelligent computing environment for 100 devices, according to traditional methods, it may take a technician a whole month to complete all deployment tasks. This not only increases the labor cost of the project, but may also extend the project cycle and affect the rapid response capability of the business.

[0032] The market has an urgent need for technical solutions that can greatly simplify the deployment process of intelligent computing environments, reduce labor costs, and improve deployment efficiency. This specification aims to achieve rapid and automated deployment of intelligent computing environments through cluster management software, thereby providing customers with more convenient and efficient computing power leasing services. Through the technical means of the present invention, even large-scale intelligent computing environments can be deployed in a short time, greatly improving the operational efficiency and service quality of the intelligent computing center.

[0033] The specific technical solution is described below.

[0034] In one embodiment, the present specification provides a server automatic deployment method, which is applied to management equipment, and the method includes: obtaining device information of a target server, mounting an image file to the target server according to the device information, and the image file is used to enable the target server to install a server OS according to the image file; connecting to the server OS in a preset manner according to user information and an IP address of the server OS installed from the target server, and uploading a cluster deployment program installation package to the server OS, and the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS; calling a business cluster deployment program interface of the target server according to preset business cluster configuration information, and configuring and deploying the target server to a business cluster associated with the business cluster configuration information.

[0035] Specifically, Figure 1 , including the following steps:

[0036] Step S11, obtaining device information of the target server, and mounting the image file to the target server according to the device information.

[0037] In the first step of the automatic deployment process, the system needs to obtain the device information of the target server. This information includes but is not limited to the server model, configuration, serial number (SN), etc. This step can be achieved through the baseboard management controller (BMC), which can monitor the hardware status and provide necessary information to the management system. For example, in a data center with 100 servers, UniSystem software can remotely query the BMC of each server and collect device information of all servers.

[0038] After obtaining the device information, UniSystem will mount a pre-configured image file to the target server based on this information. This image file contains a complete operating system (OS) as well as all necessary drivers and preliminary configurations. For example, if the target server is a server with an NVIDIA GPU installed, the image file will contain NVIDIA's GPU driver to ensure that the operating system can correctly identify and use GPU resources.

[0039] Step S12, according to the user information and IP address of the server OS installed on the target server, connect to the server OS in a preset manner, and upload the cluster deployment program installation package to the server OS.

[0040] Once the target server's operating system is installed, UniSystem will connect to the server OS through a preset method (such as SSH) based on the server OS's user information and IP address. This step ensures that the management system can remotely access and control the server OS, laying the foundation for subsequent automated deployment.

[0041] After the connection is successful, UniSystem will upload the cluster deployment program installation package to the server OS. This installation package contains all the necessary software and scripts to install and configure the cluster deployment program on the server. For example, if Kubernetes is used as a cluster management tool, the installation package will contain all Kubernetes components, such as kubelet, kubeadm, etc.

[0042] Step S13: According to the preset business cluster configuration information, the business cluster deployment program interface of the target server is called to configure and deploy the target server to the business cluster associated with the business cluster configuration information.

[0043] UniSystem will call the business cluster deployment program interface on the target server according to the preset business cluster configuration information, configure and deploy the target server to the corresponding business cluster. This step involves multiple levels of configuration, including network settings, storage configuration, security policies, etc.

[0044] For example, if the business cluster needs to run in a specific virtual network, UniSystem will configure the network interface and routing rules to ensure that the server can connect to the network correctly. At the same time, if the business cluster needs to use a specific storage solution, such as NFS or Ceph, UniSystem will configure the storage mount point and access rights.

[0045] Through the above steps, UniSystem can automatically complete the entire process from device information acquisition, OS installation, cluster deployment program installation to business cluster configuration. This automated deployment method not only improves deployment speed and reduces error rate, but also greatly reduces labor costs, making the construction of intelligent computing environment faster and more efficient.

[0046] In one implementation, assume that an intelligent computing center needs to deploy a new business cluster, including 50 servers, and each server needs to install the Ubuntu operating system and Kubernetes cluster management tools. Using this technical solution, the administrator of the intelligent computing center only needs to enter the necessary deployment information on the UniSystem interface, including: a list of device SNs for identifying and managing 50 servers; select Ubuntu as the OS type and provide a user name, password, and IP address; disk partitioning information for OS installation and subsequent data storage; and Kubernetes cluster configuration information, including network settings and storage solutions.

[0047] After the input is completed, UniSystem will automatically execute, obtain the device information of 50 servers through BMC, mount the image file containing Ubuntu and NVIDIA GPU drivers for each server, install the Ubuntu operating system, and connect to each server through SSH after the installation is complete, upload the Kubernetes cluster deployment program installation package, and install Kubernetes on each server, configure the network and storage according to the preset business cluster configuration information, and deploy 50 servers to the business cluster. The entire process does not require manual intervention, which greatly shortens the deployment time, reduces the deployment cost, and improves the operational efficiency of the intelligent computing center.

[0048] In one implementation, it is first necessary to obtain the device information of the target server. This information can be automatically collected by the baseboard management controller (BMC), including but not limited to the server's serial number (SN), hardware configuration (such as CPU model, memory size, hard disk capacity, etc.), network interface card (NIC) information, etc. For example, there is a batch of newly purchased servers, and the BMC of each server has been pre-configured. Through the UniSystem management platform, batch requests can be sent to the BMC of these servers to obtain detailed device information, such as serial number, hardware configuration, etc.

[0049] Based on the acquired device information, the UniSystem management platform selects the appropriate operating system (OS) image file and mounts it to the target server. This process is usually implemented through a network file system (NFS) or HTTP server. For example, if a server's hardware configuration is suitable for running the CentOS 7.9 operating system, UniSystem will automatically select the CentOS 7.9 image file and mount it to the boot partition of the server through the network.

[0050] After the mount is complete, the target server will boot from the network and automatically install the operating system based on the mounted image file. This process is fully automated and does not require manual intervention. When the server boots from the network, it will automatically read the CentOS 7.9 installation script and execute the system installation process, including partitioning, formatting, and installing core components.

[0051] After the installation is complete, the UniSystem management platform automatically obtains the user information (such as the root user's username and password) and IP address of the target server. This information is usually obtained from the server's BMC or the operating system itself through the API interface. Assuming that the server's IP address is 192.168.1.10 and the root user's password is "password123", this information will be recorded in the UniSystem database.

[0052] After obtaining the user information and IP address, the UniSystem management platform will connect to the target server's OS through a preset method (such as the SSH protocol). This connection process is secure and ensures the encryption and integrity of data transmission. UniSystem will use the SSH client tool to connect to 192.168.1.10 through the command line and log in as the root user.

[0053] After the connection is successful, UniSystem will upload the pre-prepared cluster deployment program installation package to the target server. This installation package contains all the necessary cluster management software and configuration files. Taking AMPHA intelligent computing management software as an example, UniSystem will upload the AMPHA installation package to the specified directory of the server through a secure file transfer protocol (such as SCP).

[0054] After the upload is complete, UniSystem triggers the installation process on the target server, unzips the installation package and installs the cluster deployment program on the target server. This process is also fully automated, ensuring the consistency and reliability of the installation. UniSystem triggers the installation process through remote commands, unzips the installation package and executes the installation script to complete the installation of AMPHA.

[0055] During the deployment process, users need to define the configuration information of the business cluster on the UniSystem management platform in advance, including the cluster name, number of nodes, network configuration, storage configuration, etc. After the configuration information is defined, UniSystem will call the cluster deployment program interface installed on the target server, pass the configuration information, and start the cluster configuration and deployment process. After the target server receives the configuration information, it will automatically configure and deploy the cluster based on this information. This includes network communication configuration between nodes, storage mounting, service startup, etc.

[0056] For example, a user wants to create a business cluster named "Cluster-A" with 10 nodes. The network configuration of each node is 192.168.1.0 / 24 subnet, and the storage is configured to use NFS shared storage. UniSystem sends a request through the RESTful API interface, calls the AMPHA deployment program on the target server, and passes the cluster configuration information. This information includes the cluster name, node list, network configuration, etc. AMPHA automatically configures the Kubernetes (K8S) cluster on each node, sets the Master node and Worker node, configures the network plug-in, mounts the NFS storage, and starts the necessary services.

[0057] This implementation achieves full process automation from device information acquisition to cluster configuration, greatly shortens the deployment time of the intelligent computing environment, reduces labor costs, and improves the reliability and consistency of deployment. For example, for a cluster environment of 100 servers, the traditional method may take 1 man-month, but using the method of the present invention, the entire deployment work can be completed within 2 man-days, significantly improving the operational efficiency of the intelligent computing center.

[0058] In one embodiment, the method of obtaining device information of the target server and mounting an image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file, includes: mounting the image file to the target server according to the driver file corresponding to the OS type, KS file, and GPU model, wherein the image file includes an OS firmware installer, a KS file, and a GPU driver file.

[0059] In one embodiment, the method connects to the server OS in a preset manner based on the user information and IP address of the server OS installed on the target server, and uploads the cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, including: connecting to the server OS through SSH based on the user information and IP address of the server OS installed on the target server, and uploading the AMPHA program installation package to the server OS, wherein the AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

[0060] In one embodiment, the business cluster deployment program interface of the target server is called according to preset business cluster configuration information, and the target server is configured and deployed in a business cluster associated with the business cluster configuration information, including: the business cluster configuration information is called according to the cluster deployment information input by the user in the initial stage, and the business cluster deployment program interface of the target server is configured and deployed.

[0061] In one implementation, each step is executed in a loop until all servers to be deployed in the server cluster are deployed as target servers.

[0062] In one embodiment, Figure 2 This specification also provides a server automatic deployment device, which is used for managing equipment. The device includes: a first module, which is used to obtain device information of a target server, and mount an image file to the target server according to the device information, wherein the image file is used to enable the target server to install a server OS according to the image file; a second module, which is used to connect to the server OS in a preset manner according to user information and an IP address of the server OS installed from the target server, and upload a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install a cluster deployment program in the server OS; a third module, which is used to call a business cluster deployment program interface of the target server according to preset business cluster configuration information, and configure and deploy the target server to a business cluster associated with the business cluster configuration information.

[0063] In one embodiment, the method of obtaining device information of the target server and mounting an image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file, includes: mounting the image file to the target server according to the driver file corresponding to the OS type, KS file, and GPU model, wherein the image file includes an OS firmware installer, a KS file, and a GPU driver file.

[0064] In one embodiment, the method connects to the server OS in a preset manner based on the user information and IP address of the server OS installed on the target server, and uploads the cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, including: connecting to the server OS through SSH based on the user information and IP address of the server OS installed on the target server, and uploading the AMPHA program installation package to the server OS, wherein the AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

[0065] In one embodiment, the business cluster deployment program interface of the target server is called according to preset business cluster configuration information, and the target server is configured and deployed in a business cluster associated with the business cluster configuration information, including: the business cluster configuration information is called according to the cluster deployment information input by the user in the initial stage, and the business cluster deployment program interface of the target server is configured and deployed.

[0066] In one implementation, the first module, the second module, and the third module are cycled until all servers to be deployed in the server cluster are deployed as target servers.

[0067] The device implementation is the same as or similar to the corresponding method implementation, and will not be described in detail here.

[0068] In one embodiment, this specification provides an electronic device, including a processor and a readable storage medium, wherein the readable storage medium stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the aforementioned server automatic deployment method. From a hardware level, the hardware architecture diagram can be seen in Figure 3 shown.

[0069] In one embodiment, the present specification provides a readable storage medium, wherein the readable storage medium stores machine executable instructions, and when the machine executable instructions are called and executed by a processor, the machine executable instructions prompt the processor to implement the aforementioned server automatic deployment method.

[0070] Here, the readable storage medium can be any electronic, magnetic, optical or other physical storage device that can contain or store information, such as executable instructions, data, etc. For example, the readable storage medium can be: RAM (Radom Access Memory), volatile memory, non-volatile memory, flash memory, storage drive (such as hard disk drive), solid state drive, any type of storage disk (such as CD, DVD, etc.), or similar storage medium, or a combination thereof.

[0071] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer, which may be in the form of a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email transceiver, a game console, a tablet computer, a wearable device or a combination of any of these devices.

[0072] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0073] It will be appreciated by those skilled in the art that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] This specification is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] Moreover, these computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0077] It will be appreciated by those skilled in the art that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may be in the form of a computer program product implemented on one or more computer-usable storage media (which may include but are not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0078] The above description is only an embodiment of the present specification and is not intended to limit the present specification. For those skilled in the art, the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A server automatic deployment method, characterized in that: Applied to managing equipment, the method comprises: Obtain device information of the target server, and mount the image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file; According to the user information and IP address of the server OS installed on the target server, the server OS is connected in a preset manner, and a cluster deployment program installation package is uploaded to the server OS, where the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS; According to the preset business cluster configuration information, the business cluster deployment program interface of the target server is called to configure and deploy the target server to the business cluster associated with the business cluster configuration information.

2. The method according to claim 1, characterized in that The step of obtaining device information of the target server and mounting the image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file, includes: Mount the image file to the target server according to the OS type, KS file, and driver file corresponding to the GPU model. The image file includes the OS firmware installer, KS file, and GPU driver file.

3. The method according to claim 1, characterized in that The method of obtaining user information and IP address of the server OS installed on the target server, connecting to the server OS in a preset manner, and uploading a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, includes: According to the user information and IP address of the server OS installed on the target server, the server OS is connected via SSH, and the AMPHA program installation package is uploaded to the server OS. The AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

4. The method according to claim 1, characterized in that: The calling of the service cluster deployment program interface of the target server according to the preset service cluster configuration information, configuring and deploying the target server in the service cluster associated with the service cluster configuration information, includes: The business cluster configuration information obtained from the cluster deployment information input by the user at the initial stage calls the business cluster deployment program interface of the target server to configure and deploy the target server to the business cluster associated with the business cluster configuration information.

5. The method according to claim 1, characterized in that Each step is executed repeatedly until all servers to be deployed in the server cluster are deployed as target servers.

6. A server automatic deployment device, characterized in that: Applied to management equipment, the device comprises: The first module is used to obtain device information of the target server and mount the image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file; The second module is used to connect to the server OS in a preset manner according to the user information and IP address of the server OS installed on the target server, and upload the cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS; The third module is used to call the business cluster deployment program interface of the target server according to the preset business cluster configuration information, and configure and deploy the target server to the business cluster associated with the business cluster configuration information.

7. The device according to claim 6, characterized in that The step of obtaining device information of the target server and mounting the image file to the target server according to the device information, wherein the image file is used to enable the target server to install the server OS according to the image file, includes: Mount the image file to the target server according to the OS type, KS file, and driver file corresponding to the GPU model. The image file includes the OS firmware installer, KS file, and GPU driver file.

8. The device according to claim 6, characterized in that The method of obtaining user information and IP address of the server OS installed on the target server, connecting to the server OS in a preset manner, and uploading a cluster deployment program installation package to the server OS, wherein the cluster deployment program installation package is used to enable the target server to install the cluster deployment program in the server OS, includes: According to the user information and IP address of the server OS installed on the target server, the server OS is connected via SSH, and the AMPHA program installation package is uploaded to the server OS. The AMPHA program installation package is used to enable the target server to install the cluster deployment program in the server OS.

9. The device according to claim 6, characterized in that The calling of the service cluster deployment program interface of the target server according to the preset service cluster configuration information, configuring and deploying the target server in the service cluster associated with the service cluster configuration information, includes: The business cluster configuration information obtained from the cluster deployment information input by the user at the initial stage calls the business cluster deployment program interface of the target server to configure and deploy the target server to the business cluster associated with the business cluster configuration information.

10. The device according to claim 6, characterized in that The first module, the second module and the third module are cycled until all the servers to be deployed in the server cluster are deployed as target servers.

11. An electronic device, characterized in that: include: A processor and a readable storage medium, wherein the readable storage medium stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement any method described in claims 1-5.

12. A readable storage medium, characterized in that: The readable storage medium stores machine executable instructions, and when the machine executable instructions are called and executed by a processor, the machine executable instructions prompt the processor to implement any one of the methods of claims 1-5.

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