Method, system, equipment and medium for quickly deploying applications at large-scale cluster nodes

Abstract

The invention provides a method, system and device for rapidly deploying applications at large-scale cluster nodes and a medium, and belongs to the technical field of cluster application deploying.The method comprises the steps that a host information table, a parameter table, a component table and an application table are constructed; performing network configuration on each node in the cluster according to the host information table, and testing the network connectivity of each node; arranging a deployment task for the node, generating a parameter configuration template according to the parameter table, and respectively selecting a component and an application which need to be deployed according to the component table and the application table; determining deployment tasks executed in parallel according to application deployment requirements, and starting deployment; in the execution process of each deployment task, parameter configuration is executed firstly, then component deployment and application deployment are executed, and meanwhile the running states of the components and the application are monitored. By constructing the standardized information table and the modularized deployment process, efficient and standardized deployment in a large-scale cluster environment is realized, and the deployment efficiency and accuracy are remarkably improved.

Description

Technical Field

[0001] This application belongs to the technical field of cluster application deployment, and particularly relates to a method, system, device and medium for quickly deploying applications on large-scale cluster nodes. Background Art

[0002] With the rapid development of information technology, large-scale cluster environments have been widely used in multiple industries such as healthcare, finance, and the Internet. Especially in the healthcare industry, many medical application software needs to be deployed efficiently and centrally to medical institutions in a wide area. These medical institutions are usually built by hundreds or thousands of professional medical devices and servers, forming a large-scale and highly complex cluster environment.

[0003] Under the complex and huge medical architecture, the traditional manual deployment method faces many challenges. First of all, manual deployment is not only time-consuming and laborious, but also extremely prone to errors due to human negligence, increasing the uncertainty and potential risks in the deployment process. Secondly, as the number of servers increases, repetitive operations will greatly reduce the deployment efficiency, extend the project launch time, and affect the business progress. In addition, manual deployment is difficult to achieve standardization and consistency, and it is difficult to meet the high requirements for deployment efficiency and accuracy in a large-scale cluster environment.

[0004] Existing automated deployment tools, such as the Ansible tool, although supporting batch operations, have the following limitations: one is that host management and parameter configuration are scattered and cannot quickly adapt to the compliance requirements of industries such as healthcare and finance. The other is that when the deployment fails, it relies on manual log checking and cannot automatically repair problems.

[0005] In summary, there is an urgent need for a deployment method that can solve the limitations of the traditional manual deployment method, improve the deployment efficiency, reduce the error rate, and ensure the consistency and maintainability of application deployment. Summary of the Invention

[0006] In a first aspect, an embodiment of this application provides a method for quickly deploying applications on large-scale cluster nodes, including the following steps: S1. Build a host information table to store the network information and hardware configuration information of all nodes, build a parameter table to store the deployment parameter information of all nodes, build a component table to store component information, and build an application table to store application information; S2. Perform network configuration on each node in the cluster according to the host information table, and test the network connectivity of each node; S3. Orchestrate deployment tasks for the nodes that pass the network connectivity test, and generate a parameter configuration template according to the parameter table in the deployment task, select the components to be deployed according to the component table, and select the applications to be deployed according to the application table; S4. Determine the deployment tasks to be executed in parallel according to the application deployment requirements, and start the deployment; S5. During the execution of each deployment task, first determine the target nodes and execution parameter configurations according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and monitor the running status of the components and applications at the same time.

[0007] Further, the network information in the host information table in step S1 includes the node IP address, SSH access port, login username, and password.

[0008] Further, the specific steps for constructing the parameter table in step S1 are as follows: Determine the target environment of each node in combination with the business requirements; Determine the deployment parameter information, configuration information, and environment variables of the corresponding node according to the target environment; Create a record in the parameter table for each node; The specific steps for constructing the component table are as follows: Determine all the components required for application deployment, and the components include middleware and databases; Store each component information as a record in the component table; the component information includes the component name and the component startup script path; The specific steps for constructing the application table are as follows: Determine the application information and application startup script information; the application information includes the application name and the application startup script path; Add the application information and startup script information to the application table.

[0009] Further, the specific steps of step S2 are as follows: S21. Configure the node IP address, login username, password, and SSH access port of each node according to the host information table; S22. Locate the node according to the IP address and SSH access port in the host information table; S23. Test whether the network of the located node is reachable; If not, prompt to check the node network and go to step S24; If so, go to step S24; S24. Determine whether all nodes have been located; If so, go to step S25; If not, locate the next node and return to step S23; S25. Count all the nodes with reachable networks.

[0010] Further, the specific steps of step S3 are as follows: S31. Determine the nodes that pass the network connectivity test as target nodes, and determine that each target node needs to perform deployment task orchestration; S32. In each deployment task, fill in the deployment parameter information, configuration information, and environment variables of the target node into the parameter configuration template to complete the addition of parameter configuration information; S33. Add the component information of the corresponding target node to each deployment task; S34. Add the application information of the corresponding target node to each deployment task.

[0011] Furthermore, the specific steps of step S4 are as follows: S41. Obtain the hardware configuration information of each target node in the host information table; If the hardware configuration information meets the deployment requirements, proceed to step S42; If the hardware configuration does not meet the deployment requirements, proceed to step S43; S42. Set all components without dependencies in the target node to be deployed in parallel, and proceed to step S44; S43. Set all components in the target node to be deployed serially, and proceed to step S44; S44. Set a deployment task to execute the deployment of the target node in sequence according to parameter deployment, component deployment, and application deployment; S45. Determine the number of nodes that can execute the deployment in parallel according to the performance of the deployment server; S46. Group the deployment tasks according to the number of nodes that can execute the deployment in parallel, and set the deployment tasks within each group to be executed in parallel.

[0012] Furthermore, the specific steps of determining the target node and performing parameter configuration according to the deployment parameter information in step S5 are as follows: Execute the added parameter configuration information, determine the deployment user and deployment path according to the deployment parameter information, and distribute the component installation package and application installation package according to the deployment path; Obtain the configuration information and environment variables; Modify the configuration file of the target node according to the configuration information and environment variables; The specific steps of starting the components to be deployed in the component table and monitoring the running status of the components are as follows: Query the component startup script according to the component startup script path, and execute the component installation package; Run the component and monitor the component status; If the component runs normally, continue with the application deployment; If the component runs abnormally, perform component exception handling and then re-execute the component startup script; The specific steps for starting the applications to be deployed in the application table and monitoring the running status of the applications are as follows: Query the application component startup script according to the application startup script path, and execute the application installation package; Run the application and monitor the application status; If the application runs abnormally, perform application exception handling and then re-execute the application startup component; If the application runs normally, output the deployment information.

[0013] In a second aspect, an embodiment of the present application further provides a system for quickly deploying applications on large-scale cluster nodes, including: An information table construction module, configured to construct a host information table to store the network information and hardware configuration information of all nodes, construct a parameter table to store the deployment parameter information of all nodes, construct a component table to store component information, and construct an application table to store application information; A network configuration module, configured to perform network configuration on each node in the cluster according to the host information table and test the network connectivity of each node; A deployment task scheduling module, configured to schedule deployment tasks for the nodes that pass the network connectivity test, and generate a parameter configuration template according to the parameter table in the deployment task, select the components to be deployed according to the component table, and select the applications to be deployed according to the application table; A deployment task grouping module, configured to determine the deployment tasks to be executed in parallel according to the application deployment requirements and start the deployment; An application deployment module, configured to, during the execution of each deployment task, first determine the target node and execute parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and simultaneously monitor the running status of the components and applications.

[0014] In a third aspect, an embodiment of the present application further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the steps of the method for quickly deploying applications on large-scale cluster nodes as described in the first aspect.

[0015] In a fourth aspect, an embodiment of the present application further provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method for quickly deploying applications on large-scale cluster nodes as described in the first aspect.

[0016] From the above technical solutions, it can be seen that the present application has the following advantages: In the method, system, device, and medium for rapidly deploying applications on large-scale cluster nodes provided by this application, centralized management of various types of information is achieved by constructing multiple information tables. The network configuration and connectivity testing are utilized to ensure the stability of the deployment environment. Based on task scheduling, grouping, and parallel execution, the deployment efficiency is improved. At the same time, the running status of components and applications is monitored in real time, ensuring the accurate, reliable, and efficient execution of the deployment process, reducing labor costs, meeting the strict requirements for application deployment in large-scale cluster environments, providing a basis for application deployment on large-scale cluster nodes in various industries, and solving the problems of low deployment efficiency, high error rate, and lack of consistency and maintainability in large-scale cluster environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more clearly illustrate the technical solutions of this application, the accompanying drawings required for the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of the method for rapidly deploying applications on large-scale cluster nodes of the present invention.

[0019] Figure 2 It is a flowchart of the system for rapidly deploying applications on large-scale cluster nodes of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] In the following, the specific steps of the method for rapidly deploying applications on large-scale cluster nodes will be described in detail, and various embodiments of the present disclosure will be described more comprehensively. The present disclosure can have various embodiments, and adjustments and changes can be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but the present disclosure should be understood to cover all adjustments, equivalents, and / or alternative solutions that fall within the spirit and scope of the various embodiments of the present disclosure.

[0021] Exemplarily, with the rapid development of information technology, large-scale cluster environments have been widely used in multiple fields such as healthcare, finance, and the Internet. Especially in the healthcare industry, numerous medical application software needs to be deployed efficiently, centrally, and uniformly to medical institutions across the province or region. These medical institutions usually consist of hundreds or thousands of professional medical devices and servers, forming a large-scale and highly complex cluster environment.

[0022] In such a complex and large medical architecture, the traditional manual deployment method faces many challenges. On the one hand, manual deployment is not only time-consuming and laborious, but also extremely prone to errors due to human negligence, increasing the uncertainty and potential risks during the deployment process. On the other hand, with the increase in the number of servers, repetitive operations will greatly reduce the deployment efficiency, extend the project launch time, and affect the business progress. In addition, it is difficult to achieve standardization and consistency in manual deployment, making it difficult to meet the high requirements for deployment efficiency and accuracy in a large-scale cluster environment.

[0023] Existing automated deployment tools, such as the Ansible tool, although supporting batch operations, still have some limitations. First, host management and parameter configuration are relatively scattered and cannot quickly adapt to the compliance requirements of industries such as healthcare and finance. Second, when the deployment fails, it relies on manual log checking and cannot automatically fix problems.

[0024] In summary, there is an urgent need for a deployment method that can solve the limitations of the traditional manual deployment method to improve the deployment efficiency, reduce the error rate, and ensure the consistency and maintainability of application deployment.

[0025] In response to the above problems, this embodiment provides a method for quickly deploying applications on large-scale cluster nodes. By constructing a standardized information table and a modular deployment process, it realizes the automatic and efficient execution of deployment tasks, improves the deployment efficiency, reduces the deployment cost and error rate, and at the same time enhances the maintainability and scalability of the deployment process. It is particularly suitable for industries such as healthcare and finance that have high requirements for deployment efficiency and accuracy, and can effectively solve the disadvantages of the traditional manual deployment method, such as low efficiency, high error rate, and difficulty in standardization and consistency.

[0026] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] Please refer to Figure 1 The following is a flowchart of a method for quickly deploying applications on large-scale cluster nodes in a specific embodiment. The method includes the following steps: S1. Construct a host information table to store the network information and hardware configuration information of all nodes, construct a parameter table to store the deployment parameter information of all nodes, construct a component table to store component information, and construct an application table to store application information; It should be noted that by constructing a host information table, a parameter table, a component table, and an application table, various types of information are classified and stored, which is convenient for unified management and invocation, provides a data basis for subsequent node network configuration, orchestration, and execution of deployment tasks, standardizes the deployment process, and reduces errors caused by information chaos; S2. Perform network configuration on each node in the cluster according to the host information table, and test the network connectivity of each node; It should be noted that performing network configuration and connectivity testing on cluster nodes ensures a stable network environment between nodes, ensures the smooth basis for subsequent deployment tasks, avoids deployment failures or interruptions caused by network problems, and improves the reliability of deployment; S3. Orchestrate deployment tasks for the nodes that pass the network connectivity test, and generate a parameter configuration template according to the parameter table in the deployment task, select the components to be deployed according to the component table, and select the applications to be deployed according to the application table; It should be noted that by orchestrating deployment tasks according to different information tables, the deployment tasks are closely combined with the actual needs of each node, a targeted parameter configuration template is generated, and appropriate components and applications are selected, ensuring the accuracy and completeness of the deployment content; S4. Determine the deployment tasks to be executed in parallel according to the application deployment requirements, and start the deployment; It should be noted that determining the deployment tasks to be executed in parallel and starting the deployment makes full use of the cluster resources, improves the deployment efficiency, reduces the deployment time, and meets the requirements of rapid deployment in a large-scale cluster environment; S5. During the execution of each deployment task, first determine the target node and execute the parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and monitor the running status of the components and applications at the same time; It should be noted that during the execution of the deployment task, parameter configuration, component and application startup, and status monitoring are carried out in sequence according to the information table, ensuring that each link proceeds in an orderly manner, promptly discovering and handling abnormal situations, and ensuring the successful deployment and stable operation of the application.

[0028] This embodiment realizes efficient and standardized deployment in a large-scale cluster environment by constructing a standardized information table and a modular deployment process, significantly improving the deployment efficiency and accuracy.

[0029] Furthermore, as a refinement and extension of the specific implementation manner of the above embodiment, in order to fully illustrate the specific implementation process in this embodiment, another method for quickly deploying applications on large-scale cluster nodes is provided, and this method includes the following steps: S1. Build a host information table to store the network information and hardware configuration information of all nodes, build a parameter table to store the deployment parameter information of all nodes, build a component table to store component information, and build an application table to store application information; The network information in the host information table includes the node IP address, SSH access port, login username, and password; The specific steps for building the parameter table in step S1 are as follows: Determine the target environment for each node in combination with business requirements; Determine the deployment parameter information, configuration information, and environment variables for the corresponding node according to the target environment; Create a record in the parameter table for each node; The specific steps for building the component table are as follows: Determine all components required for application deployment, where the components include middleware and databases; Store each component information as a record in the component table; the component information includes the component name and the component startup script path; The specific steps for building the application table are as follows: Determine the application information and application startup script information; the application information includes the application name and the application startup script path; Add the application information and startup script information to the application table; It should be noted that by building a host information table to centrally manage the network information and hardware configuration information of all nodes, it provides data support for subsequent network configuration and deployment tasks, improving the accuracy and efficiency of deployment; by building a parameter table to centrally manage the deployment parameter information of all nodes, it enables the automatic and standardized execution of parameter configuration, reduces manual configuration errors, and improves the accuracy of deployment; by building a component table to centrally manage component information, including middleware and databases, etc., it provides accurate data support for component deployment, improving the efficiency and accuracy of component deployment; by building an application table to centrally manage application information, it provides accurate data support for application deployment, improving the efficiency and accuracy of application deployment; S2. Perform network configuration on each node in the cluster according to the host information table and test the network connectivity of each node; the specific steps of step S2 are as follows: S21. Configure the node IP address, login username, password, and SSH access port of each node according to the host information table; Locate the node according to the IP address and SSH access port in the host information table; S23. Test whether the network of the located node is connectable; If not, prompt to check the node network and go to step S24; If so, go to step S24; S24. Determine whether all nodes are located; If so, proceed to step S25; If not, locate the next node and return to step S23; S25. Count all the nodes that can be connected in the network; Exemplarily, taking the example of a medical impact analysis system that needs to be deployed to the server clusters of 200 hospitals in a certain area, with 1 server for each hospital, a total of 200 servers; Unify the connection information management of 200 servers and check the network connectivity; batch import the server information (IP, SSH port, login account, password) of all hospitals through Excel or API; Automatically test the connectivity of each server through SSH / TCP and mark the unreachable hosts; for example, the server of a certain hospital cannot be connected due to firewall issues; After the operation and maintenance personnel adjust the network policy, re-detect until all hosts are reachable; It is verified that by saving the time of entering and testing one by one, the initialization of 200 servers can be completed within 10 minutes; It should be noted that by configuring the IP address, login username, password, and SSH port of the nodes, ensuring that the network status of each node in the cluster is good, providing a basis for the deployment task, and avoiding deployment failures caused by network problems; by testing the network connectivity of each node, network problems can be discovered and solved in a timely manner, improving the success rate of the deployment task; S3. Orchestrate deployment tasks for the nodes that pass the network connectivity test, and generate a parameter configuration template according to the parameter table in the deployment task, select the components to be deployed according to the component table, and select the applications to be deployed according to the application table; the specific steps of step S3 are as follows: S31. Determine the nodes that pass the network connectivity test as target nodes, and determine that each target node needs to perform deployment task orchestration; S32. Fill in the deployment parameter information, configuration information, and environment variables of the target node into the parameter configuration template in each deployment task to complete the addition of parameter configuration information; S33. Add the component information corresponding to the target node in each deployment task; S34. Add the application information corresponding to the target node in each deployment task; Exemplarily, Parameter management, for example, dynamically adjust deployment parameters according to the configuration requirements of different hospitals (such as database address, storage path); For example, define global parameters, set the personalized parameters of the hospital, generate a parameter template for subsequent deployment, so as to avoid manually modifying the configuration files of each server and make the parameter adjustment take effect with one key; Component management, such as uniformly deploying dependent components such as MySQL and Redis on 200 servers; selecting the MySQL 8.0 component; Automatically execute the creation of database users and permissions, distribute and decompress the MySQL installation package, generate the MySQL configuration file my.cnf according to parameters, start the service and verify the status; After the subsequent deployment is executed and verified, the component deployment that originally required 200 manual operations can now be completed within 1 hour through a single task. Application management. For example, with the goal of deploying a medical imaging AI application and initializing data, upload the application installation package; and define the deployment process as dynamically generating the deployment path, distributing and decompressing the installation package, modifying the configuration file, and starting the application; After verification, when selecting all 200 hosts, starting and executing the deployment, the deployment implementation is shortened from the traditional 5 person-days to 2 hours, and there are no human errors.

[0030] It should be noted that by orchestrating deployment tasks for nodes that pass the network connectivity test, the automated management and scheduling of deployment tasks are achieved, improving the execution efficiency and accuracy of deployment tasks; by filling in the deployment parameter information, configuration information, and environment variables of the target nodes into the parameter configuration template, the automation and standardization of parameter configuration are achieved, reducing manual configuration errors; by adding component information and application information of the corresponding target nodes to the deployment tasks, the automated deployment of components and applications is achieved, improving the deployment efficiency and accuracy; S4. Determine the deployment tasks to be executed in parallel according to the application deployment requirements, and start the deployment; The specific steps of step S4 are as follows: S41. Obtain the hardware configuration information of each target node in the host information table; If the hardware configuration information meets the deployment requirements, go to step S42; If the hardware configuration does not meet the deployment requirements, go to step S43; S42. Set all components without dependencies in the target node to be deployed in parallel, and go to step S44; S43. Set all components in the target node to be deployed serially, and go to step S44; S44. Set the deployment in a deployment task to be executed for the target node in the order of parameter deployment, component deployment, and application deployment; S45. Determine the number of nodes that can execute the deployment in parallel according to the performance of the deployment server; S46. Group the deployment tasks according to the number of nodes that can be executed in parallel, and set the deployment tasks within each group to be executed in parallel; Exemplarily, obtain the hardware configuration information of these 200 servers, such as the number of CPU cores, memory size, disk space, etc.; For some servers with higher configurations, such as 50 servers with 8 CPU cores and 32 GB of memory, since the hardware configurations of these servers meet the deployment requirements, components without dependencies (such as the MySQL database and Redis cache components) in these servers can be set to be deployed in parallel; while for the other 150 servers with relatively lower configurations, due to limited resources, to avoid deployment failures caused by resource competition, all components are set to be deployed serially; After evaluating the performance of the deployment servers, it is found that the comprehensive performance of the deployment servers, such as network bandwidth and computing power, can support parallel deployment of 20 nodes simultaneously; Group and start the deployment: According to the determined number of parallel nodes, divide 200 deployment tasks into 10 groups, with each group containing 20 deployment tasks; the deployment tasks within each group are started and executed in parallel at the same time; in actual operation, the deployment system will send deployment instructions to the servers in each group in an orderly manner according to the grouping situation. For example, the 20 servers in the first group start parameter deployment, component deployment, and application deployment simultaneously, greatly improving the overall deployment efficiency; It should be noted that by dynamically adjusting the deployment according to the hardware configuration information, the cluster resources are fully utilized, the deployment efficiency is improved, and the project go-live time of the application is shortened; by setting the execution order and method of the deployment tasks, the stability and reliability of the deployment tasks are ensured, and the success rate of the deployment is improved; S5. During the execution of each deployment task, first determine the target node and execution parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and monitor the running status of the components and applications at the same time; the specific steps for determining the target node and execution parameter configuration according to the deployment parameter information in the parameter table in step S5 are as follows: Execute the added parameter configuration information, determine the deployment user and deployment path according to the deployment parameter information, and distribute the component installation package and application installation package according to the deployment path; Obtain the configuration information and environment variables; Modify the configuration file of the target node according to the configuration information and environment variables; The specific steps for starting the components to be deployed in the component table and monitoring the running status of the components are as follows: Query the component startup script according to the component startup script path and execute the component installation package; Run the component and monitor the component status; If the component runs normally, continue with the application deployment; If the component runs abnormally, perform component exception handling and then re-execute the component startup script; The specific steps to start the applications to be deployed in the application table and monitor the running status of the applications are as follows: Query the application component startup script according to the application startup script path and execute the application installation package; Run the application and monitor the application status; If the application runs abnormally, perform application exception handling and then re-execute the application startup component; If the application runs normally, output the deployment information; Exemplarily, deploy the medical imaging system to 200 hospitals, and determine the target nodes and execute parameter configuration according to the deployment parameter information in the parameter table as follows: Execute parameter configuration information: According to the deployment parameter information in the parameter table, determine that the deployment user is deploy_user and the deployment path is / opt / medical_app; Distribute the component installation package mysql-8.0.21.tar.gz and the application installation package medical_app_v1.0.tar.gz to the target node hospital-103 according to the deployment path / opt / medical_app; Obtain the configuration information and environment variables, for example, JAVA_HOME= / usr / local / java, MYSQL_HOME= / opt / mysql; Modify the configuration files my.cnf and application.properties of the target node hospital-103 according to the configuration information and environment variables; Start the components to be deployed in the component table and monitor the running status of the components Start the component: Query and execute the startup script of the MySQL component according to the component startup script path / opt / mysql / bin / mysqld_safe; Run the MySQL component and monitor its running status; Monitor the running status of the component: If the MySQL component runs normally, continue with the application deployment.

[0031] If the MySQL component runs abnormally, for example, port 3306 is occupied, execute the following exception handling steps: Automatically modify the configuration file. Specifically, after detecting that port 3306 is occupied, automatically modify the port in my.cnf to 3307; Update the parameter table. Specifically, update the db_port field of the hospital-103 node in the parameter table, changing the port from 3306 to 3307; Re-trigger the deployment process. Specifically, re-execute the startup script of the MySQL component to ensure that the MySQL component can be started normally; According to the application startup script path: / opt / medical_app / bin / start.sh, query and execute the startup script of the medical imaging analysis system; Run the application and monitor its running status; If the application runs normally, output the deployment success message; If the application runs abnormally, execute the following exception handling steps: Check the application log and analyze the error reasons, such as configuration file errors, unstarted dependent components, etc.; Restart the application. Specifically, according to the analysis result, after correcting the configuration file or restarting the dependent components, re-execute the application startup script to ensure that the application can run normally; It should be noted that by determining the target node according to the deployment parameter information in the parameter table and executing the parameter configuration, the automatic and standardized execution of the parameter configuration is realized, reducing manual configuration errors; by monitoring the running status of the components and the application and making dynamic adjustments, the stable operation of the components and the application is ensured, improving the stability and reliability of the deployment task; by monitoring the running status of the components and the application in real time, problems are discovered and solved in time, improving the success rate of the deployment task.

[0032] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0033] As Figure 2 shown, the following is an embodiment of the system for quickly deploying applications on large-scale cluster nodes provided by the embodiments of the present disclosure. This system belongs to the same inventive concept as the method for quickly deploying applications on large-scale cluster nodes in the above embodiments. For the details not described in detail in the embodiment of the system for quickly deploying applications on large-scale cluster nodes, reference can be made to the embodiments of the method for quickly deploying applications on large-scale cluster nodes.

[0034] The system includes: An information table construction module, used to construct a host information table to store the network information and hardware configuration information of all nodes, construct a parameter table to store the deployment parameter information of all nodes, construct a component table to store component information, and construct an application table to store application information; A network configuration module, used to perform network configuration on each node in the cluster according to the host information table and test the network connectivity of each node; A deployment task orchestration module is used to orchestrate deployment tasks for nodes that have passed network connectivity tests, generate a parameter configuration template based on a parameter table in the deployment task, select components to be deployed according to a component table, and select applications to be deployed according to an application table. A deployment task grouping module is used to determine deployment tasks to be executed in parallel according to application deployment requirements and start the deployment. An application deployment module is used to, during the execution of each deployment task, first determine the target node and execute parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and simultaneously monitor the running status of the components and applications.

[0035] In this embodiment, through the interaction and cooperation of various modules such as an information table construction module, a network configuration module, a deployment task orchestration module, a deployment task grouping module, and an application deployment module, the automated management and scheduling of deployment tasks are realized, improving the deployment efficiency and accuracy.

[0036] The method for quickly deploying applications on large-scale cluster nodes provided by the embodiments of this application can be applied to electronic devices. Those skilled in the art can understand that the structure of the electronic device involved in the embodiments of the present invention does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements. In the embodiments of the present invention, the electronic device includes, but is not limited to, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown in the figure, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the embodiments of this application described and / or required herein.

[0037] The electronic device may include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, a key, a camera, a display screen, and a SIM card interface, etc.

[0038] It can be understood that the structure schematically shown in the embodiments of this application does not constitute a specific limitation on the electronic device. In other embodiments of this application, the electronic device may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or have different component arrangements. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0039] The processor may include one or more processing units. For example, the processor may include a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated in one or more processors.

[0040] Among them, the processor may be the nerve center and command center of the electronic device. The controller may generate operation control signals according to the instruction operation code and timing signals to complete the control of fetching and executing instructions.

[0041] A memory may also be provided in the processor for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can save the instructions or data that the processor has just used or recycled. If the processor needs to use the instruction or data again, it can directly call it from this memory. This avoids repeated accesses, reduces the waiting time of the processor, and thus improves the system efficiency.

[0042] The above electronic device implements the technical solution of the method for quickly deploying applications in a large-scale cluster node in the present application. It constructs a host information table to store the network information and hardware configuration information of all nodes, constructs a parameter table to store the deployment parameter information of all nodes, constructs a component table to store component information, and constructs an application table to store application information; performs network configuration on each node in the cluster according to the host information table and tests the network connectivity of each node; schedules deployment tasks for the nodes that pass the network connectivity test, generates a parameter configuration template according to the parameter table in the deployment task, selects the components to be deployed according to the component table, and selects the applications to be deployed according to the application table; determines the deployment tasks to be executed in parallel according to the application deployment requirements, and starts the deployment; during the execution of each deployment task, first determines the target node and performs parameter configuration according to the deployment parameter information in the parameter table, then starts the components to be deployed in the component table and starts the applications to be deployed in the application table, and at the same time monitors the running states of the components and applications. By constructing a standardized information table and a modular deployment process, it achieves the beneficial effects of efficient and standardized deployment in a large-scale cluster environment, significantly improving the deployment efficiency and accuracy.

[0043] In the storage medium provided by this application, there is a program product capable of implementing a method for quickly deploying applications on large-scale cluster nodes.

[0044] The method for quickly deploying applications on large-scale cluster nodes includes: constructing a host information table to store the network information and hardware configuration information of all nodes, constructing a parameter table to store the deployment parameter information of all nodes, constructing a component table to store component information, and constructing an application table to store application information; performing network configuration on each node in the cluster according to the host information table, and testing the network connectivity of each node; scheduling deployment tasks for the nodes that pass the network connectivity test, generating a parameter configuration template according to the parameter table in the deployment task, selecting the components to be deployed according to the component table, and selecting the applications to be deployed according to the application table; determining the deployment tasks to be executed in parallel according to the application deployment requirements, and starting the deployment; during the execution of each deployment task, first determine the target node and perform parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, while monitoring the running status of the components and applications.

[0045] In some possible implementation manners, the method for quickly deploying applications on large-scale cluster nodes of the present disclosure may be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of this specification.

[0046] The storage medium of the present disclosure may adopt any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, but not be limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quickly deploying applications on large-scale cluster nodes, characterized in that It includes the following steps: S1. Build a host information table to store the network information and hardware configuration information of all nodes, build a parameter table to store the deployment parameter information of all nodes, build a component table to store component information, and build an application table to store application information; S2. Configure the network for each node in the cluster according to the host information table, and test the network connectivity of each node; S3. Orchestrate deployment tasks for the nodes that pass the network connectivity test, and generate a parameter configuration template in the deployment task according to the parameter table, select the components to be deployed according to the component table, and select the applications to be deployed according to the application table; S4. Determine the deployment tasks to be executed in parallel according to the application deployment requirements, and start the deployment; S5. During the execution of each deployment task, first determine the target node and execute the parameter configuration according to the deployment parameter information in the parameter table, then start the components to be deployed in the component table and start the applications to be deployed in the application table, and monitor the running status of the components and applications at the same time.

2. The method for quickly deploying an application on large-scale cluster nodes according to claim 1, wherein In step S1, the network information in the host information table includes the node IP address, SSH access port, login username, and password.

3. The method for quickly deploying an application on large-scale cluster nodes according to claim 1, characterized in that The specific steps for building the parameter table in step S1 are as follows: Determine the target environment for each node in combination with the business requirements; Determine the deployment parameter information, configuration information, and environment variables of the corresponding node according to the target environment; Create a record in the parameter table for each node; The specific steps for building the component table are as follows: Determine all the components required for application deployment, and the components include middleware and databases; Store each component information as a record in the component table; the component information includes the component name and the path of the component startup script; The specific steps for building the application table are as follows: Determine the application information and the application startup script information; the application information includes the application name and the path of the application startup script; Add the application information and the startup script information to the application table.

4. The method for rapidly deploying an application on large-scale cluster nodes according to claim 2, characterized in that The specific steps of step S2 are as follows: S21. Configure the node IP address, login username, password, and SSH access port of each node according to the host information table; S22. Locate the node according to the IP address and SSH access port in the host information table; S23. Test whether the network of the located node is connectable; If not, prompt to check the node network and go to step S24; If so, go to step S24; S24. Judge whether all nodes are located; If so, go to step S25; If not, locate the next node and return to step S23; S25. Count all the nodes with connectable networks.

5. The method for quickly deploying an application on large-scale cluster nodes according to claim 4, characterized in that The specific steps of step S3 are as follows: S31. Determine the nodes that pass the network connectivity test as the target nodes, and determine that each target node needs to perform deployment task orchestration; S32. Fill in the deployment parameter information, configuration information, and environment variables of the target node into the parameter configuration template in each deployment task to complete the addition of parameter configuration information; S33. Add the component information of the corresponding target node in each deployment task; S34. Add the application information of the corresponding target node in each deployment task.

6. The method for quickly deploying an application on large-scale cluster nodes according to claim 5, characterized in that The specific steps of step S4 are as follows: S41. Obtain the hardware configuration information of each target node in the host information table; If the hardware configuration information meets the deployment requirements, proceed to step S42; If the hardware configuration does not meet the deployment requirements, proceed to step S43; S42. Set all components without dependencies in the target node to be deployed in parallel, and proceed to step S44; S43. Set all components in the target node to be deployed serially, and proceed to step S44; S44. Set a deployment task to execute the deployment on the target node in sequence according to parameter deployment, component deployment, and application deployment; S45. Determine the number of nodes that can execute the deployment in parallel according to the performance of the deployment server; S46. Group each deployment task according to the number of nodes that can be executed in parallel, and set the deployment tasks within each group to be executed in parallel.

7. The method for quickly deploying an application on large-scale cluster nodes according to claim 6, wherein The specific steps for determining the target node and executing parameter configuration according to the deployment parameter information in step S5 are as follows: Execute the added parameter configuration information, determine the deployment user and deployment path according to the deployment parameter information, and distribute the component installation package and application installation package according to the deployment path; Obtain the configuration information and environment variables; Modify the configuration file of the target node according to the configuration information and environment variables; The specific steps for starting the components that need to be deployed in the component table and monitoring the running status of the components are as follows: Query the component startup script according to the component startup script path, and execute the component installation package; Run the component and monitor the component status; If the component runs normally, continue with the application deployment; If the component runs abnormally, perform component exception handling and then re-execute the component startup script; The specific steps for starting the applications that need to be deployed in the application table and monitoring the running status of the applications are as follows: Query the application component startup script according to the application startup script path, and execute the application installation package; Run the application and monitor the application status; If the application runs abnormally, perform application exception handling and then re-execute the application startup component; If the application runs normally, output the deployment information.

8. A system for quickly deploying applications on large-scale cluster nodes, characterized in that, Including: An information table construction module for constructing a host information table to store the network information and hardware configuration information of all nodes, constructing a parameter table to store the deployment parameter information of all nodes, constructing a component table to store component information, and constructing an application table to store application information; A network configuration module for performing network configuration on each node in the cluster according to the host information table and testing the network connectivity of each node; A deployment task scheduling module for scheduling deployment tasks for nodes that pass the network connectivity test, and generating a parameter configuration template according to the parameter table in the deployment task, selecting the components to be deployed according to the component table, and selecting the applications to be deployed according to the application table; A deployment task grouping module for determining the deployment tasks to be executed in parallel according to the application deployment requirements and starting the deployment; An application deployment module for, during the execution of each deployment task, first determining the target node and executing parameter configuration according to the deployment parameter information in the parameter table, then starting the components that need to be deployed in the component table and starting the applications that need to be deployed in the application table, and simultaneously monitoring the running status of the components and applications.

9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. It is characterized in that when the processor executes the program, the steps of the method for rapidly deploying an application on a large-scale cluster node according to any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method for rapidly deploying an application on a large-scale cluster node according to any one of claims 1 to 7 are implemented.

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