Domestic operating system-based automatic deployment method for industrial internet platform

Abstract

Provided are a domestic operating system-based automatic deployment method and system for an industrial internet platform, a computer device, and a computer readable storage medium, relating to the technical field of automatic deployment. The deployment method comprises: installing an automatic deployment tool, and the tool automatically identifying the model and version of a domestic operating system of a current system unit, and automatically installing a basic component of a corresponding version; building a local software repository by means of the tool, the tool automatically identifying a platform deployment mode, and automatically downloading a complete installation package of a platform locally and publishing same to the local software repository, and upon completion, the tool automatically starting a service discovery and registration function; deploying common components of the platform by means of the tool, and the tool automatically identifying the platform deployment mode, and automatically installing specified common components; checking in real time by means of the service discovery and registration function of the tool whether all the common components of the platform have been installed; and the tool using a single image to automatically deploy a plurality of service application services of the platform.

Description

Automated deployment method of industrial Internet platform based on domestic operating system Technical Field

[0001] The present invention relates to the field of automated deployment technology, and in particular to an automated deployment method for an industrial Internet platform based on a domestic operating system. Background Art

[0002] With the rapid development of Industrial Internet technologies, the number of components in Industrial Internet platforms and their implementation costs are also increasing. The key to automating the deployment of Industrial Internet platforms lies in automatically identifying operating systems and installing the corresponding software repository services based on their versions. This, coupled with service discovery and registration capabilities, enables information synchronization between servers. This makes automated deployment of the platform more intelligent and efficient in small-scale application scenarios, effectively reducing the probability of errors and labor costs for operations and maintenance personnel.

[0003] Currently, the more popular container deployment tool is Kubernetes, an excellent container orchestration and management system, but its shortcomings are also very obvious: its high flexibility and rich feature set also bring about the problem of high learning cost, and it takes some time to learn and understand its architecture and working principles; the architecture is relatively complex, and for development and operation and maintenance personnel who are not familiar with it, they may face problems such as cumbersome operations and difficult problem troubleshooting in terms of deployment and management; it requires running complex system components, and resource consumption is high; for small-scale application scenarios, it may bring excessive complexity and management costs.

[0004] Summary of the Invention

[0005] In view of the problems of the above-mentioned existing technologies in the industrial Internet platform, such as high probability of manual errors, high implementation costs, and poor portability, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is how to provide an automated deployment method for an industrial Internet platform based on a domestic operating system.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In the first aspect, an embodiment of the present invention provides an automated deployment method for an industrial Internet platform based on a domestic operating system, which includes installing an automated deployment tool, the tool automatically identifies the domestic operating system model and version of the current host, and automatically installs the basic components of the corresponding version; using the tool to build a local software warehouse, the tool automatically identifies the platform deployment mode, and automatically downloads the complete platform installation package to the local and publishes it to the local software warehouse. After completion, the tool automatically enables service discovery and registration functions; using the tool to deploy platform public components, the tool automatically identifies the platform deployment mode, and automatically installs specified public components; using the tool's service discovery and registration functions, it checks in real time whether all public components of the platform are ready for installation, and automatically releases front-end files, modifies configuration parameters, and initializes the database after all checks are passed; the tool will use a single image to automatically deploy multiple business application services on the platform.

[0009] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the installation of the automated deployment tool includes the following steps: using machine learning to achieve intelligent adaptive deployment; exploring online learning and incremental deployment methods to support dynamic changes; during the deployment process, monitoring key indicators, and using models to predict the optimal solution to achieve automatic diagnosis and fault self-recovery.

[0010] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the use of machine learning to achieve intelligent adaptive deployment includes: defining the parameter vector a = [x1, x2, ..., xn] of the deployment plan, the tool randomly generates m candidate deployment plans {b1, b2, ..., bm}, and defines the quality assessment model: Q(x) = w1x1+w2x2+, ..., +wk×xk+c

[0011] Where x is the parameter feature vector of the deployment plan, w is the weight vector, and c is the bias. The model is trained using the XGBoost machine learning algorithm. The tool automatically generates multiple candidate deployment plans for new deployment requirements. The plans are fed into the model. For each candidate plan bi, the vector xi is fed into the evaluation model to calculate the quality index: Yi = Q(xi)

[0012] Obtain the quality indexes [Y1, Y2, ..., Ym] of all candidate solutions and filter out the solution with the smallest quality index. If the number of remaining solutions is less than n, randomly generate a new candidate solution xj and calculate its quality index Yj. Ultimately, obtain n candidate deployment solutions with high quality indexes. Rank the deployment solutions based on their quality indexes and select the top-ranked solution for deployment. If deployment fails, select the second-ranked alternative solution and try again.

[0013] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the automated deployment tool refers to a set of automated scripts written based on Shell language and Python language that conforms to Bash standard specifications, has cross-operating system and good compatibility.

[0014] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the automatic identification of the tool refers to reading the key parameters in the system file / etc / os-release, using a traversal comparison method to match them one by one with the operating system list built into the tool, and the tool will automatically install the corresponding version basic components according to the matching results.

[0015] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the tool automatically identifies the platform deployment mode, including: if the IP address of the current host exists in the IP address set of the configuration file and is the same as the IP address of the local software warehouse, the tool determines that the deployment mode is a stand-alone mode or a distributed master node mode, and first deploys and publishes the local software warehouse and enables the service discovery and registration functions, and then deploys the platform public components and business applications that need to be installed on the host of the IP specified in the configuration file; if the IP address of the current host exists in the IP address set of the configuration file, but is different from the IP address of the local software warehouse, the tool determines that the deployment mode is a distributed slave node mode, and only deploys the platform public components and business applications that need to be installed on the host of the IP specified in the configuration file; if the IP address of the current host does not exist in the IP address set of the configuration file, the tool determines that the current host has no right to install any components or services, and prompts the user and forces exit.

[0016] As a preferred solution of the automated deployment method of the industrial Internet platform based on the domestic operating system described in the present invention, the tool will use a single image to automatically deploy multiple business application services of the platform by building dozens of platform application jar packages into a docker image. When starting the platform application container, the corresponding platform application is started as required by setting the container environment variables.

[0017] On the second aspect, in order to further solve the problems of high probability of manual errors, high implementation cost and poor portability in the existing technology of industrial Internet platforms, the embodiment of the present invention provides an automated deployment system for industrial Internet platforms based on domestic operating systems, which includes: an automated deployment module, which is used to automatically identify the domestic operating system model and version of the current host, and automatically install the basic components of the corresponding version; a service discovery and registration function module, after the tool turns on this function, it can check in real time whether all public components of the platform are installed, and automatically release the front-end files, modify the configuration parameters and initialize the database after all checks are passed; a platform public component module, which is used to automatically identify and install specified public components according to the platform deployment mode; a business application service module, which is used for the tool to automatically deploy multiple business application services of the platform using a single image.

[0018] In a third aspect, an embodiment of the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the method for automated deployment of an industrial Internet platform based on a domestic operating system as described in the first aspect of the present invention is implemented.

[0019] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, wherein: when the computer program is executed by a processor, it implements any step of the method for automated deployment of an industrial Internet platform based on a domestic operating system as described in the first aspect of the present invention.

[0020] The beneficial effect of the present invention is that it realizes automatic adaptation of multiple domestic operating systems through automated deployment tools, can quickly and efficiently deploy public components and business application services of the industrial Internet platform, and effectively reduce the error probability and labor costs of operation and maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0022] Figure 1 is a flow chart of the automated deployment method of the industrial Internet platform based on the domestic operating system in Example 1.

[0023] FIG2 is a diagram showing an authentication prompt for accessing a local software repository through a browser in Example 1.

[0024] Figure 3 is a diagram of the docker container information in Example 1.

[0025] FIG4 is a statistical diagram of the two construction methods in Example 2 when applied on platforms of different orders of magnitude. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0027] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0028] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0029] Example 1

[0030] 1 to 3 , which illustrate a first embodiment of the present invention, provide an automated deployment method for an industrial Internet platform based on a domestic operating system, including the following steps:

[0031] S1: Install the automated deployment tool. The tool automatically identifies the domestic operating system model and version of the current host and automatically installs the basic components of the corresponding version, including file download services and container engine services.

[0032] S1.1: Use machine learning to enable intelligent adaptive deployment.

[0033] Preferably, historical deployment log data is collected, and deployment parameters, operating indicators, etc. are extracted as training features; a deployment quality assessment model is constructed to predict the quality index of the deployment plan. Specifically: a parameter vector a = [x1, x2, ..., xn] of the deployment plan is defined, including server configuration, network bandwidth, etc. The tool randomly generates m candidate deployment plans {b1, b2, ..., bm}; a quality assessment model is defined: Q(x) = w1x1+w2x2+, ..., +wk×xk+c

[0034] Among them, x is the parameter feature vector of the deployment plan, w is the weight vector, and c is the bias.

[0035] Using the XGBoost machine learning algorithm for model training, the tool automatically generates multiple candidate deployment plans for new deployment requirements, inputs the plans into the model, calculates the quality index Q of each plan, and selects the optimized plan with the highest quality index for intelligent deployment.

[0036] Furthermore, the tool automatically generates multiple candidate deployment plans, inputs the plans into the model, and calculates the quality index Q of each plan, which includes the following steps:

[0037] For each candidate solution bi, input vector xi to the evaluation model and calculate the quality index: Yi=Q(xi)

[0038] Obtain the quality indexes [Y1, Y2, ..., Ym] of all candidate solutions and filter out the solution with the smallest quality index. If the number of remaining solutions is less than n, randomly generate a new candidate solution xj and calculate its quality index Yj. Ultimately, obtain n candidate deployment solutions with high quality indexes. Rank the deployment solutions based on their quality indexes and select the top-ranked solution for deployment. If deployment fails, select the second-ranked alternative solution and try again.

[0039] S1.2: Explore online learning and incremental deployment methods to support dynamic changes.

[0040] Specifically, during the deployment process, operating indicators are collected and fed back to the online learning model, the model is incrementally updated, and the deployment strategy is continuously optimized. When there are new deployment requirements, incremental training and adjustment of the model are performed. The tool supports the orchestration language to describe deployment changes, automatically generates incremental execution processes, parses change descriptions, and extracts information such as modules and parameters. Based on the extracted information, it automatically locates the components that need to be adjusted and generates an incremental upgrade execution deployment plan to achieve dynamic changes.

[0041] S1.3: During deployment, key indicators are monitored, the model predicts the optimal solution, and automatic diagnosis and fault recovery are implemented.

[0042] Specifically, an LSTM neural network is used as the evaluation model. The input is the time series data of historical indicators monitored during the deployment process, and the output is the indicator performance predicted for the future time period. The long-term dependency characteristics of the indicators are captured by LSTM to determine the abnormal interaction process of the indicators: a normal fluctuation range is set for each indicator. When the indicator exceeds the fluctuation range, an abnormality check is performed: an indicator abnormality is prompted and the user is requested to confirm. The user can view the time period of the abnormal indicator. The user confirms whether the indicator is abnormal or normal, and the user can modify the normal fluctuation range of the indicator; the user's confirmation feedback is collected, the indicator data is marked, and the marked data is used to train the model to determine the abnormality of the indicator; when the indicator is abnormal, the real-time indicator is input into the model to evaluate the performance F of the current solution, and the indicator data of the alternative deployment solution is generated. For each alternative solution, the performance score of the model output is calculated, and the candidate solution with the highest score is selected as the current optimal solution. The optimal solution is automatically redeployed, the problem solution is replaced, samples of the problem and replacement solutions are collected, the model is incrementally adjusted, the indicators are repeatedly monitored, and the deployment solution is continuously optimized. When the indicator returns to normal, self-recovery is completed.

[0043] Furthermore, the process of calculating the performance score of the model output is as follows: for candidate deployment plan A, its indicator data is: [xA1, xA2, ..., xAn]; the indicator data of plan A is input into the linear regression model to obtain FA; the same process is performed on other candidate plans B, C, etc., and their model output values ​​FB and FC are calculated; the model output values ​​of each candidate plan are compared: if FA>FB and FA>FC, then plan A has the highest performance score.

[0044] Furthermore, the automated deployment tool refers to a set of automated scripts written based on Shell language and Python language that conforms to Bash standard specifications and has cross-operating systems and good compatibility, including: an automated script for installing and uninstalling automated deployment tools, which is used to install and uninstall httpd file download services and docker container engine services, httpd is used to publish local software repositories and provide service discovery and registration functions, and docker is used to carry all containers of platform public components and business applications; an automated script for publishing installation packages from local software repositories, which uses the wget command to download the installation packages of platform public components and business applications online, release them and publish them to the local software repository; an automated script for service discovery and registration functions, which responds to service registration requests sent by platform public components and business applications after deployment is completed and service information query requests before initialization work is performed by listening to specific keyword combinations in httpd access logs; an automated script for platform deployment and uninstallation, which is used to install and uninstall platform public components, release front-end files, modify configuration parameters, initialize databases, install and assist platform business applications.

[0045] The tool automatically identifies the domestic operating system model and version of the current host by reading the key parameters in the system file / etc / os-release, using a traversal comparison method to match them one by one with the operating system list built into the tool. Based on the matching results, the tool will automatically install the basic components of the corresponding version.

[0046] Specifically, during installation, the automated deployment tool first reads key parameters from the system file / etc / os-release and compares them with the built-in configuration file to accurately identify the host's operating system model and version to confirm support. If the tool does not support the operating system, it will display a warning and force the tool to exit, avoiding compatibility issues.

[0047] When the operating system is confirmed to be supported, the tool will further check the host environment to confirm whether the httpd and docker services are installed and whether the related ports and deployment directories are occupied or already exist, to prevent operation and maintenance accidents caused by overwriting the installation.

[0048] If the host environment check passes, the tool will install the httpd and docker services for the operating system model and version. After installation, the tool will verify that the services are installed successfully and functioning properly. If the httpd and docker services fail to install, the tool will display a warning and force exit to prevent subsequent service deployment failures.

[0049] S2: Use the tool to build a local software warehouse. The tool automatically identifies the platform deployment mode, automatically downloads the complete platform installation package to the local computer, and publishes it to the local software warehouse. After completion, the tool automatically enables the service discovery and registration functions.

[0050] S2.1: When setting up a local software repository, the automated deployment tool first obtains the host's IP address and compares it with the built-in configuration file, and automatically identifies the platform's deployment mode.

[0051] When the tool identifies the deployment mode as stand-alone mode or distributed master node mode and the httpd service has been installed, the tool allows you to build a local software repository.

[0052] S2.2: After the tool identifies the deployment mode and passes verification, it will automatically check whether the offline software installation package specified in the configuration file already exists in the local resource directory; if the offline installation package does not exist, the tool will automatically access the cloud software repository and attempt to download the specified software installation package.

[0053] S2.3: After all software installation packages have passed the inspection, the tool will automatically release the files in the installation package to the corresponding location in the software warehouse, including platform common components and business applications.

[0054] S2.4: After the tool is built in the local software repository, the service discovery and registration functions will be automatically enabled.

[0055] S2.5: User access authentication is enabled by default in the local software repository, providing a high level of network security protection for LAN file downloads and service discovery and registration functions. The authentication prompt for accessing the local software repository through a browser is shown in Figure 2.

[0056] S3: Deploy platform common components through tools. The tools automatically identify the platform deployment mode and automatically install specified common components, including middleware, cache, configuration center, relational database, object storage, message queue, and computing engine.

[0057] S3.1: When the automated deployment tool installs the platform's common components, it first matches the list of components that need to be installed on the current host based on the built-in configuration file.

[0058] S3.2: After the tool completes the current host environment check, it will create component instance directories one by one in the arrangement order, and then modify the installation configuration files of each component.

[0059] Before executing the sub-installer for each component, the tool will also check whether the instance directory, service port, container application name, etc. of the component are occupied to prevent operational accidents caused by overwriting the installation.

[0060] S3.3: When the component is installed, the tool will check whether the component has been successfully registered in the service discovery and registration function list. At the same time, the service discovery and registration function running in the background will receive service registration or information query requests and respond.

[0061] It should be noted that the tools in S2 and S3 automatically identify the platform deployment mode, which refers to a method of determining the deployment mode according to specific rules by comparing the IP address of the current host with the IP address set in the configuration file, including: if the IP address of the current host exists in the IP address set of the configuration file and is the same as the IP address of the local software warehouse, the tool determines that the deployment mode is "single-server mode" or "distributed master node mode (multi-server-master)", and first deploys and publishes the local software warehouse and enables the service discovery and registration functions, and then deploys the platform public components and business applications that need to be installed on the host with the IP specified in the configuration file; if the IP address of the current host exists in the IP address set of the configuration file, but is different from the IP address of the local software warehouse, the tool determines that the deployment mode is "distributed slave node mode (multi-server-nodes)", and only deploys the platform public components and business applications that need to be installed on the host with the IP specified in the configuration file; if the IP address of the current host does not exist in the IP address set of the configuration file, the tool determines that the current host has no right to install any components or services, prompts the user and forces the exit.

[0062] S4: Through the service discovery and registration functions of the tool, the tool checks in real time whether all public components of the platform are installed and ready. After all checks are passed, the tool automatically releases the front-end files, modifies the configuration parameters, and initializes the database.

[0063] S4.1: After the public components of the current host are installed, the automated deployment tool will automatically detect the registration information of all public components of the platform in the component service discovery and registration function to confirm that all public components of the platform have been successfully installed and registered.

[0064] If some components fail to register successfully, the tool will enter a waiting state and check the registration status of the component again every 10 seconds until the component is successfully registered and then continue with subsequent operations, or the installation process is forcibly terminated due to timeout.

[0065] S4.2: When all components are successfully registered, the tool will start to release the front-end files, initialize the database, and modify the platform-related configuration parameters in the database.

[0066] Preferably, the service discovery and registration function refers to a method of responding to service registration requests and service information query requests sent by platform common components and business applications after deployment by real-time monitoring of specific keyword combinations in httpd access logs.

[0067] S5: After all initialization operations are completed, the tool will use a single image to automatically deploy multiple business application services on the platform, including back-end applications in industrial fields such as system management, real-time monitoring, factory modeling, and parameter alarms.

[0068] The tool will use a single image to automatically deploy multiple business application services on the platform. This means that by building more than a dozen platform application jar packages into a Docker image, when starting the platform application container, the corresponding platform application is started as required by setting the container environment variables.

[0069] S5.1: When the file or data initialization jobs of all common components are completed, the automated deployment tool will automatically start deploying the platform business application modules.

[0070] S5.2: Since the platform has dozens of business application modules, if they are packaged into independent Docker image installation packages using traditional construction methods, the files will take up a lot of space. In actual application scenarios, the operating efficiency of operations such as compression, release, upload, and download of the installation package will be seriously affected.

[0071] To address the drawbacks of traditional build methods, we adopted an integrated build approach to package the platform's business application modules. Specifically, we built all of the platform's business application modules into a single Docker image and added a startup script that automatically identifies the application name. In actual use cases, the automated deployment tool will build and start container instances with the corresponding business application names by specifying Docker container environment variables. S5.3: This automated deployment method for an industrial internet platform based on a domestic operating system has been verified through real-world applications at more than ten project sites, demonstrating that it can complete offline deployment of a complete platform with 30 common components and business applications within 10 minutes. In the automated deployment tool, building the software repository module and deploying common components and business application modules account for over 98% of the total time.

[0072] S54: After all components of the Industrial Internet Platform are installed, the tool will print out all Docker container information, as shown in Figure 3.

[0073] This embodiment also provides an automated deployment system for an industrial Internet platform based on a domestic operating system, including: an automated deployment module, which is used to automatically identify the domestic operating system model and version of the current host and automatically install the basic components of the corresponding version; a service discovery and registration function module, after the tool turns on this function, it can check in real time whether all public components of the platform are installed, and automatically release front-end files, modify configuration parameters and initialize the database after all checks are passed; a platform public component module, which is used to automatically identify and install specified public components according to the platform deployment mode; a business application service module, which is used for the tool to automatically deploy multiple business application services of the platform using a single image.

[0074] This embodiment also provides a computer device, which is suitable for the automated deployment method of the industrial Internet platform based on the domestic operating system, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the automated deployment method of the industrial Internet platform based on the domestic operating system proposed in the above embodiment.

[0075] The computer device may be a terminal, comprising a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse.

[0076] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for realizing the automated deployment of an industrial Internet platform based on a domestic operating system as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0077] In summary, the present invention realizes automatic adaptation to a variety of domestic operating systems through automated deployment tools, can quickly and efficiently deploy public components and business application services of the industrial Internet platform, and effectively reduce the error probability and labor costs of operation and maintenance personnel.

[0078] Example 2

[0079] 4 , which is a second embodiment of the present invention, simulation data of an automated deployment method for an industrial Internet platform based on a domestic operating system is provided to further verify the present invention.

[0080] The present invention builds all the business application modules of the platform into the same Docker image package and adds a startup script with the function of automatically identifying the application name. In actual usage scenarios, the automated deployment tool will build and start the container instance corresponding to the business application name by specifying the Docker container environment variables. Compared with the traditional method, the integrated construction method can significantly reduce the total size of the installation package.

[0081] A typical industrial Internet platform has between 10 and 30 applications. The integrated construction approach will save 70% to 80% of storage space, transmission traffic, and corresponding operation and maintenance time costs compared to the traditional approach. Figure 4 compares the statistical data of the two construction approaches in different scale platform applications.

[0082] It can be seen that the present invention has made great progress in saving transmission space and transmission traffic ratio compared with the existing technology, which further illustrates that the present invention can quickly and efficiently deploy public components and business application services of the industrial Internet platform, and effectively reduce the error probability and labor cost of operation and maintenance personnel.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An automated deployment method for an industrial Internet platform based on a domestic operating system, characterized in that: Including: Install an automated deployment tool. The tool automatically identifies the domestic operating system model and version of the current host and automatically installs the corresponding version of the basic components. Build a local software repository through the tool. The tool automatically identifies the platform deployment mode, automatically downloads the complete platform installation package to the local and publishes it to the local software repository. After completion, the tool automatically enables the service discovery and registration function. Deploy the platform public components through the tool. The tool automatically identifies the platform deployment mode and automatically installs the specified public components. Through the service discovery and registration function of the tool, check in real time whether all the platform public components are installed and ready. After all the checks pass, automatically release the front-end files, modify the configuration parameters, and initialize the database. The tool will use a single image to automatically deploy multiple business application services of the platform.

2. The automated deployment method of the industrial Internet platform based on domestic operating system according to claim 1, characterized in that: The steps of the described installation automated deployment tool are as follows: Use machine learning to achieve intelligent adaptive deployment. Explore online learning and incremental deployment methods to support dynamic changes. During the deployment process, monitor key metrics, the model predicts the optimal solution, and achieve automatic diagnosis and self-recovery of faults.

3. The automated deployment method of the industrial Internet platform based on a domestic operating system according to claim 2, characterized in that: The use of machine learning to achieve intelligent adaptive deployment includes: Define the parameter vector \(a = [x_1,\ldots,x\) n , and the tool randomly generates \(m\) candidate deployment plans \(\{b_1,\ldots,b\) m \}. Define the quality evaluation model: Q(x) = w1x1 + w2x2 +... + w k x k + c Among them, x is the parameter feature vector of the deployment plan, w is the weight vector, and c is the bias. Use the XGBoost machine learning algorithm for model training. For new deployment requirements, the tool automatically generates multiple candidate deployment plans, inputs the plans into the model, for each candidate plan bi, inputs the vector xi into the evaluation model, and calculates the quality index: Y j = Q(x j ) Obtain the quality indices of all candidate solutions [Y1,..., Y n , filter out the solution with the minimum quality index. If the number of remaining solutions is less than n, randomly generate new candidate solutions x j , calculate the quality index Y j , most Finally, obtain n candidate deployment plans with higher quality indexes, sort the deployment plans according to the quality index, select the plan ranked first for deployment. If the deployment fails, select the alternative second-ranked plan to retry.

4. The automated deployment method of the industrial Internet platform based on domestic operating system according to claim 3, characterized in that: The described automated deployment tool refers to an automated script that complies with the Bash standard specification and has cross-operating system and good compatibility, written based on the Shell language and Python language.

5. The automated deployment method of the industrial Internet platform based on the domestic operating system according to claim 4, characterized in that: The tool's automatic identification means that by reading the key parameters in the system file / etc / os-release, using the traversal and comparison method to match them one by one with the operating system list built into the tool, and according to the matching results, the tool will automatically install the corresponding version of the basic components.

6. The automated deployment method of the industrial Internet platform based on the domestic operating system according to claim 5, characterized in that: The tool's automatic identification of the platform deployment mode includes If the IP address of the current host exists in the IP address set of the configuration file and is the same as the IP address of the local software repository, then the tool determines that the deployment mode is the single-machine mode or the distributed master node mode. First, deploy and publish the local software repository and enable the service discovery and registration function, and then deploy the platform public components and business applications that the host specified by this IP in the configuration file needs to install. If the IP address of the current host exists in the IP address set of the configuration file but is different from the IP address of the local software repository, then the tool determines that the deployment mode is the distributed slave node mode, and only deploys the platform public components and business applications that the host specified by this IP in the configuration file needs to install. If the IP address of the current host does not exist in the IP address set of the configuration file, then the tool determines that the current host has no right to install any components or services, prompts the user, and forces to exit.

7. The automated deployment method of the industrial Internet platform based on domestic operating system according to claim 6, characterized in that: The tool will use a single image to automatically deploy multiple business application services of the platform. By building more than a dozen platform application jar packages into a docker image, when starting the platform application container, the corresponding platform application can be started according to requirements by setting the container environment variables.

8. An automated deployment system for an industrial Internet platform based on a domestic operating system, based on the automated deployment method for an industrial Internet platform based on a domestic operating system according to any one of claims 1 to 7, characterized in that: Including, An automated deployment module, which is used to automatically identify the domestic operating system model and version of the current host and automatically install the corresponding version of the basic components; A service discovery and registration function module. After this function of the tool is enabled, it can check in real time whether all public components of the platform are installed and ready, and automatically release the front-end files, modify the configuration parameters and initialize the database after all checks pass; A platform public component module, which is used to automatically identify and install the specified public components according to the platform deployment mode; A business application service module, which is used for the tool to use a single image to automatically deploy multiple business application services of the platform.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the automated deployment method of the industrial Internet platform based on the domestic operating system according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the automated deployment method of the industrial Internet platform based on the domestic operating system according to any one of claims 1 to 7.

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