CN114217768A

CN114217768A - Industrial Internet of things-based automatic deployment method and system

Info

Publication number: CN114217768A
Application number: CN202111510156.0A
Authority: CN
Inventors: 刘舣翔; 熊俊峰
Original assignee: Shanghai Hc System Control Technology Co ltd
Current assignee: Shanghai Hc System Control Technology Co ltd
Priority date: 2021-12-10
Filing date: 2021-12-10
Publication date: 2022-03-22

Abstract

The invention provides an automatic deployment method and system based on an industrial Internet of things, and relates to the technical field of computers, wherein the method comprises the following steps: step S1: in the deployment design stage, components and attribute values in the components are required to be created, assembled and configured; step S2: a conversion phase, creating and configuring a deployment environment according to the environment type, and executing deployment; step S3: and in the operation and maintenance stage, managing and monitoring each deployment environment in assembly. The invention can realize the quick delivery of related projects and reduce unnecessary labor expenses and error correction risks.

Description

Industrial Internet of things-based automatic deployment method and system

Technical Field

The invention relates to the technical field of computers, in particular to an automatic deployment method and system based on an industrial Internet of things.

Background

Currently, the internet develops rapidly, and a service mode developed by rapid iteration needs an internet company to frequently update online service versions to meet various urgent functional requirements of users. Meanwhile, in order to ensure the quality of the new online function, the service version with the new function needs to be continuously updated for verification in the test environment, so that the service version needs to be continuously updated in both the online environment and the test environment. The development of the automatic deployment script can reduce various errors caused by manual deployment, and is increasingly becoming a mode for wide internet companies to select service deployment.

The invention patent with publication number CN109660371B discloses an automatic deployment method and an automatic deployment apparatus, comprising: displaying a storage configuration interface; acquiring a storage type to be deployed according to the input information of the storage configuration interface; and carrying out automatic deployment according to the storage type. The invention also discloses an automated deployment tool, comprising: the display unit is used for displaying the storage configuration interface; the acquisition unit is used for acquiring the storage type to be deployed according to the input information of the storage configuration interface; and the deployment unit is used for carrying out automatic deployment according to the storage type. The invention can select different types of storage for deployment according to requirements in actual deployment environment.

In the prior art, the following defects exist in the automatic deployment: the main service object of the automatic deployment is the existing virtualized or super-converged small and micro enterprise, the existing virtualization technology and the super-convergence technology both have the bottleneck problem of node expansion, the automatic deployment configuration in the aspect of automatic key storage is the automatic deployment of a single storage resource or a shared storage pool oriented to the object. The method cannot adapt to the requirement of distributed full-automatic deployment of the mass servers in a multi-network environment, lacks detailed deployment and implementation processes, cannot embody the process management of the full life cycle of the automatic deployment, and cannot realize the requirement of the deployment of the mass nodes under the background of big data. The invention provides a technical scheme for solving the defects pointed out in the specification.

Disclosure of Invention

Aiming at the defects in the prior art, the invention provides an automatic deployment method and system based on an industrial Internet of things.

According to the automatic deployment method and system based on the industrial Internet of things, the scheme is as follows:

in a first aspect, an automated deployment method based on an industrial internet of things is provided, and the method includes:

step S1: in the deployment design stage, components and attribute values in the components are required to be created, assembled and configured;

step S2: a conversion phase, creating and configuring a deployment environment according to the environment type, and executing deployment;

step S3: and in the operation and maintenance stage, managing and monitoring each deployment environment in assembly.

Preferably, the step S1 includes:

step S1.1: creating assembly, selecting available system templates, and adding new systems, wherein each new system corresponds to an application; each new system is composed of a group of components, and the dependency relationship among the components is defined;

step S1.2: configuring components and attribute values in the system, wherein the components are the bottommost deployment units, and each component is provided with a corresponding configuration template;

step S1.3: and submitting the design, wherein the finished design is submitted once and filed in the submitting process.

Preferably, the step S2 includes:

step S2.1: creating a deployment environment, and adding a deployment environment to be deployed according to the environment type;

step S2.2: configuring a deployment environment, setting associated resources of each system, and setting a deployment mode, single point or high availability;

step S2.3: selecting one or more systems within the assembly to generate and submit an execution plan;

step S2.4: deployment is performed, with one instance per component, and instances capable of individual self-healing.

Preferably, the basic tasks of managing and monitoring in the operation and maintenance phase of step S3 include:

1) operation and maintenance of component instances;

2) presenting the operation being deployed;

3) showing a component instance map under a certain environment;

4) log query, service monitoring and abnormal alarm.

Preferably, the automated deployment method further comprises automated deployment in multiple environments:

(1) the operation and maintenance management center creates and generates a corresponding execution plan and sub-execution plans according to the deployment architecture design and the configuration of the deployment environment, wherein each sub-plan corresponds to a Jenkins pipeline jobfile config.xml;

(2) the operation and maintenance management center issues a deployment plan to the deployment environment node;

(3) the deployment engine creates Jenkins Pipeline Job according to config.xml;

(4) jenkins jobperforms related execution operations including corresponding server deployment through an allowed command in pipeline;

(5) and the operation and maintenance management center queries the execution condition of the jobs by calling the Rest API and triggers a new operation and maintenance instruction.

In a second aspect, an automated deployment system based on the internet of things of industry is provided, the system comprising:

module M1: in the deployment design stage, components and attribute values in the components are required to be created, assembled and configured;

module M2: a conversion phase, creating and configuring a deployment environment according to the environment type, and executing deployment;

module M3: and in the operation and maintenance stage, managing and monitoring each deployment environment in assembly.

Preferably, said module M1 comprises:

module M1.1: creating assembly, selecting available system templates, and adding new systems, wherein each new system corresponds to an application; each new system is composed of a group of components, and the dependency relationship among the components is defined;

module M1.2: configuring components and attribute values in the system, wherein the components are the bottommost deployment units, and each component is provided with a corresponding configuration template;

module M1.3: and submitting the design, wherein the finished design is submitted once and filed in the submitting process.

Preferably, said module M2 comprises:

module M2.1: creating a deployment environment, and adding a deployment environment to be deployed according to the environment type;

module M2.2: configuring a deployment environment, setting associated resources of each system, and setting a deployment mode, single point or high availability;

module M2.3: selecting one or more systems within the assembly to generate and submit an execution plan;

module M2.4: deployment is performed, with one instance per component, and instances capable of individual self-healing.

Preferably, the basic tasks of management and monitoring in the module M3 operation and maintenance phase include:

1) operation and maintenance of component instances;

2) presenting the operation being deployed;

3) showing a component instance map under a certain environment;

4) log query, service monitoring and abnormal alarm.

Preferably, the automated deployment system further comprises automated deployment in multiple environments:

(3) the deployment engine creates Jenkins Pipeline Job according to config.xml;

Compared with the prior art, the invention has the following beneficial effects:

1. by providing the deployment method supporting automation, the problem that a user deploys a big data cluster and related components is solved, and the development, test and delivery efficiency is improved;

2. by providing an automatic installation and deployment detection device, the problems of system availability reduction and personnel intervention caused by server restart or service abnormity are solved;

3. by the aid of automatic deployment and bottom layer optimization of a big data cluster system and introduction of industrial Internet of things support, massive data storage and analysis requirements of the industrial Internet of things are met, and storage and bottleneck problems of industrial Internet of things data in a use process are solved;

4. by the reference and distribution of an automation tool, the deployment requirements of a large number of target servers and the linear expansion of the number of related nodes are met, and the data communication requirements of different sub-networks in single or multiple cloud environments are met.

Drawings

Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:

FIG. 1 is an automated deployment design flow diagram;

FIG. 2 is a multi-environment automation deployment diagram;

fig. 3 is a schematic diagram of an automated deployment process.

Detailed Description

The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.

The embodiment of the invention provides an automatic deployment method based on an industrial Internet of things, which is used for storing massive time sequence data of the industrial Internet of things, and large-data open-source component cluster deployment is adopted at the bottom layer. Referring to fig. 1, the whole cluster deployment includes multiple sets of related components, databases, and application services, and the method includes:

step S1: the deployment design phase is the architectural description of the application and system within the assembly, and the application/system is composed of a system with multiple components. Wherein, the basic flow comprises:

step S1.1: an assembly is created. A new system is added by selecting an available system template. Each new system corresponds to an application. Such as databases (redis, mysql, mongodb), middleware (nginx, fastdfs), big data components (hadoop, zookeeper, hbase, kafka, storm, spark, openndsb), etc. Each new system is composed of a set of components, and the dependencies between the components have been defined. Within the assembly, a user can connect relationships between the various systems by setting up the systems.

Step S1.2: component and attribute values within the system are configured. The components are the bottommost deployment units, and each component is defined by a corresponding configuration template.

Step S1.3: and submitting the design. The submission process is to submit the finished design once and archive the design once.

Step S2: the transition phase is the deployment process of the application/system within a certain environment within the assembly. The basic flow comprises the following steps.

Step S2.1: a deployment environment is created. According to environment types, such as a test environment, a development environment, a production environment and the like, a certain deployment environment to be deployed is added. Before deployment, the deployment environment is an abstraction of the configuration of the application/system for deployment. After deployment, the deployment environment is a collection of specific instances of the management and monitoring application/system.

Step S2.2: a deployment environment is configured. Set the associated resources for each system, deployment mode, single point or high availability, etc.

Step S2.3: one or more systems within the assembly are selected to generate and submit an execution plan. Depending on the deployment strategy, the execution plan of a system may contain multiple sub-plans.

Step S2.4: deployment is performed. There is one instance of each component under each assembly/environment/system that can be individually self-healing.

Step S3: and the operation and maintenance phase is the management and monitoring of the instances in each deployment environment in the assembly. The basic tasks include.

1) And (4) operating and maintaining the component instance, such as starting, stopping, repairing, restarting and the like.

2) The operation being deployed is revealed, and one of the component deployments or the entire deployment may be retried or cancelled.

3) And showing a component example map under a certain assembling environment.

4) Log query, service monitoring and abnormal alarm.

The automatic deployment method based on the industrial internet of things in the multi-network environment, as shown in fig. 2, includes:

(1) the operation and maintenance management center creates and generates a corresponding execution plan and sub-execution plans according to the deployment architecture design and the configuration of the deployment environment, wherein each sub-plan corresponds to a Jenkins pipeline job configuration file (config.xml), and the Jenkins pipeline job refers to a construction task in continuous integration;

(2) and the operation and maintenance management center issues a deployment plan to a deployment environment node, such as a production environment, a proprietary cloud environment, a private cloud environment and the like.

(3) Xml creates Jenkins Pipeline Job according to the configuration file config in the construction task.

(4) Performing corresponding server deployment and other execution operations by Jenkins jobs through an idle command in pipeline, wherein the Jenkins jobs refers to tasks in continuous integration;

(5) and the operation and maintenance management center queries the execution condition of the jobs and triggers a new operation and maintenance instruction by calling a Rest API, wherein the Rest API refers to an http request interface.

Next, the present invention will be further explained.

Referring to FIG. 3, an exemplary flow diagram of application automation deployment is shown, according to an embodiment of the present invention.

In fig. 3, the operations and maintenance management center calls devices and infrastructure may be integrated into one server or container.

The method comprises the following steps:

step 1: the operation and maintenance management center calls the Devops platform to clarify the resource environment and the server to be released.

Step 2: the devices platform calls the infrastructure to perform initialization processing on the target server.

And step 3: and sending an instruction needing to be processed to the target server by the firmware.

And 4, step 4: the target server receives the instruction to create a temporary directory.

And 5: the target server downloads an application deployment package from the product library, wherein the application deployment package comprises micro-service applications, application installation files such as databases (redis, mysql, mongodb), middleware (nginx, fastdfs), big data components (hadoop, zookeeper, hbase, kafka, storm, spark, opensdb), application specification files (config. xml files) defining execution sequences of all life cycles contained in the application deployment process, and scripts of all life cycles.

Step 6: the product library returns the application deployment package to the target server.

And 7: the target server decompresses the application deployment package to the temporary directory and verifies the config.

And 8: the target server informs the infrastructure of the initialization completion.

And step 9: the infrastructure informs the devices of the completion of initialization.

Step 10: the devices platform requests the confirm.

Step 11: the anchor requests the config.

Step 12: the target server returns a config.

Step 13: the anchor returns a config.

Step 14: the first execution sequence of each life cycle in the config.xml file is found by the devices platform to be server optimization and health detection instructions, and the device platform requests the infrastructure to execute the server optimization and health detection instructions.

Step 15: the Ansible instruction target server executes the server optimization and health detection instruction script so as to execute the optimization of the server kernel parameters and the server health detection operation.

Step 16: and the target server informs the Ansible of finishing the execution.

And step 17: the infrastructure informs the devices that the platform is finished executing.

Step 18: the second execution order of each lifecycle in xml file is found by the devices platform to be configuration check, requesting the infrastructure to execute the configuration check.

Step 19: and the anchor target executes the configuration detection script to the server so as to execute relevant configuration operation before application deployment.

Step 20: and the target server informs the Ansible of finishing the execution.

Step 21: the infrastructure informs the devices that the platform is finished executing.

Step 22: the third execution order of each lifecycle in the config.xml file is start installation, and request execution start installation from the infrastructure.

Step 23: the infrastructure executes the installation script to the target server. Thereby placing the application installation file into the specified directory.

Step 24: and the target server informs the Ansible of finishing the execution.

Step 25: the infrastructure informs the devices that the platform is finished executing.

Step 26: the fourth execution sequence of each lifecycle in the config.xml file is found by the devices platform to be cluster initialization, and the device platform requests the infrastructure to execute the cluster initialization.

Step 27: the anchor instructs the target server to execute the cluster initialization script, thereby executing the relevant configuration operation after application deployment.

Step 28: and the target server informs the Ansible of finishing the execution.

Step 29: the infrastructure informs the devices that the platform is finished executing.

Step 30: the fifth execution sequence of each lifecycle in the config.

Step 31: the anchor instructs the target server to execute the service start script, thereby executing application start-up related operations.

Step 32: and the target server informs the Ansible of finishing the execution.

Step 33: the infrastructure informs the devices that the platform is finished executing.

Step 34: finding that the sixth execution sequence of each life cycle in the config.

Step 35: the anchor instructs the target server to execute the cluster service monitoring detection script, thereby executing the relevant operation of the application program service verification.

Step 36: and the target server informs the Ansible of finishing the execution.

Step 37: the infrastructure informs the devices that the platform is finished executing.

Step 38: finding that the seventh execution sequence of each life cycle in the config.

Step 39: the infrastructure instructs the target server to perform service self-starting configuration and cluster state push.

Step 40: and the target server informs the Ansible of finishing the execution.

Step 41: the infrastructure informs the devices that the platform is finished executing.

Step 42: the Devops informs the operation and maintenance management platform that the execution is completed.

Step 43: and the operation and maintenance management platform calls the Devops to execute cluster state verification, log collection and availability monitoring alarm.

Step 44: the devices platform calls the infrastructure execution state validation push, the log collection and report and the trigger availability alarm mechanism push.

Step 45: the infrastructure instructs the target server to execute the status validation push, log collection and report, and trigger the availability alarm mechanism push.

Step 46: and the target server informs the Ansible of finishing the execution.

Step 47: the infrastructure informs the devices that the platform is finished executing.

And 48: the Devops informs the operation and maintenance management platform that the execution is completed.

The embodiment of the invention provides an automatic deployment method and system based on an industrial Internet of things, which are used for automatically deploying related applications, distributed components and large data clusters, so that the related projects are rapidly delivered, and unnecessary labor expenses and error correction risks are reduced.

Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be fully implemented by logically programming method steps in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.

The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.

Claims

1. An automatic deployment method based on an industrial Internet of things is characterized by comprising the following steps:

2. The industrial internet of things-based automatic deployment method according to claim 1, wherein the step S1 includes:

3. The industrial internet of things-based automatic deployment method according to claim 2, wherein the step S2 includes:

4. The industrial internet of things-based automatic deployment method according to claim 1, wherein the basic tasks of management and monitoring in the operation and maintenance stage of the step S3 include:

1) operation and maintenance of component instances;

2) presenting the operation being deployed;

3) showing a component instance map under a certain environment;

4) log query, service monitoring and abnormal alarm.

5. The industrial internet of things-based automated deployment method of claim 1, further comprising automated deployment in multiple environments:

(3) the deployment engine creates Jenkins Pipeline Job according to config.xml;

6. An automated deployment system based on the industrial internet of things, comprising:

7. The industrial internet of things-based automation deployment system of claim 6, wherein the module M1 includes:

8. The industrial internet of things-based automation deployment system of claim 7, wherein the module M2 includes:

9. The industrial internet of things-based automation deployment system of claim 6, wherein the basic tasks of management and monitoring in the module M3 operation and maintenance phase include:

1) operation and maintenance of component instances;

2) presenting the operation being deployed;

3) showing a component instance map under a certain environment;

4) log query, service monitoring and abnormal alarm.

10. The industrial internet of things-based automated deployment system of claim 6, further comprising automated deployment in multiple environments:

(3) the deployment engine creates Jenkins Pipeline Job according to config.xml;