CN116339749A - Containerized DevOps method, system and equipment capable of performing task scheduling - Google Patents
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Abstract
The invention discloses a containerized DevOps method, a system and equipment capable of carrying out task arrangement, belongs to the technical field of internet, and solves the technical problem that the existing DevOps platforms only support a single and sequentially executed task execution mode, wherein the method comprises the following steps: initializing deployment, which is used for initializing related components into a container cloud cluster; the method comprises the steps of scheduling a DevOps task, creating a DevOps pipeline task on an interface, scheduling the task through a visual interface, and customizing a task flow; executing the DevOps task, executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log; in the process of initializing deployment, related components comprise two components, namely a DevOps back-end service (DevOps-back) and a Jenkins master node (Jenkins-master); the container cloud cluster adopts Kubernetes to arrange containers, and the Jenkins-master can create and destroy container groups through K8s resources; the DevOps-backend, jenkins-master service manages running on a certain working node in the cluster by means of a depoyment.
Description
Technical Field
The invention relates to the technical field of Internet, in particular to a containerized DevOps method, a system and equipment capable of performing task scheduling.
Background
In software development, each functional update and bug fix will make a small portion of the code change. With traditional management, corresponding deployment is required to be performed manually after code modification for testing and release. The deployment frequency here is variable and may be defined by a development team or company. Low deployment frequency can reduce the workload properly, but can significantly increase the coupling probability of code modification; higher deployment frequencies can effectively isolate faults, but increase the workload. Performing deployment operations manually introduces more uncertainty and errors, increasing labor costs; in addition, manual deployment can also bring about repetitive labor, adding ineffective waiting. The automated deployment work can free up repetitive labor of integration, testing, deployment, etc., and the frequency of machine integration can be significantly higher than manual. In the present software Development practice, development and operation (Development) integration (Development) is a generic term of a set of processes, methods and systems, which is used to promote the communication and collaboration among application program/software engineering Development, technical operation and quality assurance personnel. The core of the DevOps is connection development and operation maintenance, so that the DevOps can efficiently communicate and cooperate to shorten the software development period and submit the delivery speed and quality. A complete development operation and maintenance integrated DevOps platform can effectively improve the software development efficiency.
In recent years, the rapid development of internet technology has led to an increasing demand in the industry for quality and quantity of computing services, and cloud computing has grown. Cloud computing describes an internet-based service add-on, use and delivery model, involving providing dynamically extensible, virtualized resources. With the development of container technology, the application of cloud computing becomes simpler and more efficient. The container technology has the characteristic of lighter weight.
Kubernetes is the most popular cloud native container orchestration platform for automatically deploying and managing containerized applications, belonging to the Paas hierarchy in cloud computing. Compared with the traditional cluster, the distributed cloud computing service platform based on the Kubernetes can remarkably improve the deployment and execution efficiency of the application. More mainstream is to combine the DevOps platform with the Kubernetes container cloud platform. By utilizing the characteristics of DevOps connection development, operation and maintenance and test and the property of Kubernetes supporting efficient deployment, the full life cycle management of the application software can be covered.
The prior art has tried to combine the DevOps platform with Kubernetes, bringing about good results, but with more or less the following drawbacks:
the DevOps platform is not completely containerized, and the DevOps platform and the Kubernetes belong to two sets of systems during deployment, so that maintenance cost and deployment cost are increased;
the process of executing tasks by the DevOps is not executed by using the cloud native technology, the container group is not created and destroyed according to the need, and unnecessary resources are continuously spent;
3. a pipeline script needs to be written, so that the learning cost of codes is increased;
4. the method is also the most important point, the existing DevOps platform only supports a single and sequentially executed task execution mode, namely only a fixed code language can be constructed, fixed deployment steps are executed, and the degree of freedom is low; and the DevOps pipeline task only supports the sequential execution of task steps, cannot carry out task arrangement, and does not support the parallel execution of a plurality of task steps.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art, and the purpose of the invention is to provide a containerized DevOps method capable of performing task scheduling.
The invention also aims to provide a containerized DevOps system capable of performing task scheduling.
The third object of the present invention is to provide a computer device.
In order to achieve the above object, the present invention provides a containerized DevOps method capable of task scheduling, including:
initializing deployment, which is used for initializing related components into a container cloud cluster;
the method comprises the steps of scheduling a DevOps task, creating a DevOps pipeline task on an interface, scheduling the task through a visual interface, and customizing a task flow;
executing the DevOps task, executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log;
in the process of initializing deployment, related components comprise two components, namely a DevOps back-end service (DevOps-back) and a Jenkins master node (Jenkins-master); the container cloud cluster adopts Kubernetes to arrange containers, and the Jenkins-master can create and destroy container groups through K8s resources; the DevOps-backend, jenkins-master service manages running on a certain working node in the cluster by means of a depoyment.
As a further improvement, the method comprises the following specific steps:
s1, creating a DevOps pipeline task on a DevOps-background interface, and setting a trigger condition;
s2, a user performs task arrangement through a visual interface, and a task flow is defined;
s3, generating a Jenkins pipeline script according to task flows edited by a user by the DevOps-database, and uploading the Jenkins pipeline script to a Jenkins-master for configuration;
s4, when the condition configured in the step S1 is triggered, starting to execute a DevOps pipeline task, wherein Jenkins-master interacts with an apiserver in the K8S cluster, and the container group is pulled up;
s5. The Jenkins-master executes the DevOps pipeline task by executing the Jenkins pipeline script in the step S3;
s6, waiting for complete execution or termination of the task, and interactively destroying the container group by the Jenkins-master and the apiserver;
s7. The step of monitoring callback of part of the built-in task steps of the system in the pipeline task by the DevOps-background, and executing operations of replacing mirror images, deploying one key and arranging services in the Kubernetes cluster according to callback parameters;
and S8. The DevOps-band acquires a Jenkins execution result, shows that the task result is success or failure, and outputs an execution log.
Further, in step S1, three trigger mode selections are provided: manual triggering, code warehouse callback triggering and webhook callback triggering; one or more trigger ways may be checked on the interface, and when one of the checked ways is satisfied, the execution pipeline task is immediately triggered.
Further, in step S2, the task orchestration is specifically described as follows: in the DevOps-band, a system built-in task step, a user-defined task step or a task step combination recommended by a system can be manually added;
when adding a task step built in a system, setting preset parameters of the step;
when the custom task step is added, a task mirror image needs to be specified, and a Shell command needing to be executed is input;
the task step combination recommended by the system consists of a plurality of built-in task steps of the system in sequence, and preset parameters of each step are required to be set respectively;
meanwhile, the DevOps-band supports task step parameter modification and task step operation of deleting error addition.
Further, the method comprises three task flow arranging modes, namely sequential execution, parallel splitting and synchronization; combining the task steps in the three arrangement modes to finally form the whole task flow;
the DevOps-band provides visual operation on the interface, and the whole task arrangement is completed in a mode of dragging a flow chart and linking the flow chart;
the task flow arrangement mode is specifically described as follows: the sequence means that each task step of the task flow is sequentially executed according to the sequence, and the next task step is executed after the current task step is successfully completed; parallel splitting refers to splitting into a plurality of subtask streams after one task step, wherein the subtask streams are executed in parallel and are mutually independent; the synchronization means that a plurality of subtask streams are converged into one task stream at one point, the merging mode is to wait for successful completion of all subtask streams, and then the next task step is carried out, and the merging of the task streams can be completed by using a synchronization operation.
Further, in step S4, a DevOps pipeline task is laid out of a plurality of task steps, different task steps will execute commands in different containers, jenkins-master needs to create a container group containing all containers; all containers in the container group realize file sharing through the mounting work catalogue.
Further, in step S5, the specific process of executing the DevOps pipeline task is as follows:
s51, sequentially switching the Jenkins-master to different containers under the container group, and executing a preset command or Shell script;
s52, when the task flows are split in parallel, a plurality of sub-working directories with the same content are derived by the existing working directories so as to realize file isolation; then switching the working catalog to the derived sub-working catalog, executing a plurality of sub-task flows in parallel, and simultaneously switching to different containers belonging to task steps in the sub-task flows to execute commands;
s53, when a plurality of subtask flows are synchronized, the subtask flows are required to be successfully executed and completed, and after the working catalogue is adjusted to the father working catalogue, the father task flows can be continuously executed;
and S54, when any working step is wrong, terminating all running task flows, and cleaning the working catalogue.
In order to achieve the second object, the present invention provides a containerized DevOps system capable of task scheduling, including:
the initialization module is used for initializing related components into the container cloud cluster;
the task scheduling module is used for creating a DevOps pipeline task on the interface, scheduling the task through the visual interface and customizing the task flow;
and the task execution module is used for executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log.
In order to achieve the third object, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements a containerized DevOps method capable of performing task scheduling as described above when executing the computer program.
Advantageous effects
Compared with the prior art, the invention has the advantages that:
the method expands a single and sequential DevOps pipeline task structure, ensures that a user performs task arrangement on the pipeline task with extremely low learning cost, and supports sequential execution, parallel splitting and synchronous pipeline task structures; the execution of the DevOps task with higher freedom degree can be completed. Meanwhile, the efficient deployment property of Kubernetes is fully utilized based on the containerized pipeline task execution mode, the on-demand starting is realized, and the utilization efficiency of resources is improved.
Drawings
FIG. 1 is a general flow chart of the method of the present invention;
FIG. 2 is a more complex DevOps pipeline task flow after task orchestration;
fig. 3 shows the structure of the file directory in the container group when a DevOps task is executed.
Detailed Description
The invention will be further described with reference to specific embodiments in the drawings.
Referring to fig. 1 to 3, a containerized DevOps method capable of task orchestration includes:
initializing deployment, which is used for initializing related components into a container cloud cluster;
the method comprises the steps of scheduling a DevOps task, creating a DevOps pipeline task on an interface, scheduling the task through a visual interface, and customizing a task flow;
executing the DevOps task, executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log;
in the process of initializing deployment, related components comprise two components, namely a DevOps back-end service (DevOps-back) and a Jenkins master node (Jenkins-master); the container cloud cluster adopts Kubernetes to arrange containers, and the Jenkins-master can create and destroy container groups through K8s resources; the DevOps-backend, jenkins-master service manages running on a certain working node in the cluster by means of a depoyment.
Comprises the following specific steps S1 to S8:
s1, a DevOps pipeline task is created on a DevOps-background interface, and a trigger condition is set. In step S1, three trigger mode selections are provided: manual triggering, code warehouse callback triggering and webhook callback triggering; one or more trigger ways may be checked on the interface, and when one of the checked ways is satisfied, the execution pipeline task is immediately triggered.
Specifically, the manual triggering mode requires the user to click on the DevOps-band interface to trigger; the code warehouse callback needs to set a callback address in the Gitea warehouse, and specifies that the callback is only performed when codes are combined; the webhook provides a fixed webhook callback address, and sending a Post request to the webhook address triggers pipeline construction.
And S2, the user performs task arrangement through a visual interface, and a task flow is defined. In step S2, the task orchestration is specifically described as follows: in the DevOps-band, a system built-in task step, a custom task step or a system recommended task step combination can be added manually.
When adding a task step built in a system, setting preset parameters of the step; when the custom task step is added, a task mirror image needs to be specified, and a Shell command needing to be executed is input; the task step combination recommended by the system consists of a plurality of built-in task steps of the system in sequence, and preset parameters of each step are required to be set respectively; meanwhile, the DevOps-band supports task step parameter modification and task step operation of deleting error addition.
In this embodiment, the system built-in task steps already include:
pulling the code replacing task: specifying a Git warehouse address, pulling a branch and a Git user name password;
static code scanning: a Sonar address and an item name need to be specified;
golang compiling step: a compiling command needs to be specified;
maven compiling: a compiling command needs to be specified;
gradle compiling: a compiling command needs to be specified;
compiling each version of NodeJs: a compiling command needs to be specified;
the unit testing step: specifying a unit test command;
an automatic test step: designating an automation script repository address, the automation script executing command;
mirror image construction: using buildKit mirror build tools, a mirror label needs to be specified.
In this embodiment, the task step combination recommended by the system is a more commonly used sequential task step combination, for example:
"Golang language recommendation: pull code-static code scan-Golang compilation-image build "," Maven recommendation: pull code-static code scan-Maven compile-unit test-mirror build "," online step recommended: pull code-execute SQL-replace mirror, "etc.
The invention provides three task flow arranging modes which are respectively sequential execution, parallel splitting and synchronization; combining the task steps in the three arrangement modes to finally form the whole task flow; the DevOps-band provides visual operation on the interface, and the whole task arrangement is completed in a mode of dragging the flow chart and linking the flow chart. As shown in figure 2, the task scheduling method is a more complex DevOps pipeline task flow after task scheduling.
The task flow arrangement mode is specifically described as follows: the sequence means that each task step of the task flow is sequentially executed according to the sequence, and the next task step is executed after the current task step is successfully completed; parallel splitting refers to splitting into a plurality of subtask streams after one task step, wherein the subtask streams are executed in parallel and are mutually independent; the synchronization means that a plurality of subtask streams are converged into one task stream at one point, the merging mode is to wait for successful completion of all subtask streams, and then the next task step is carried out, and the merging of the task streams can be completed by using a synchronization operation.
And S3. Generating a Jenkins pipeline script according to the task stream edited by the user by the DevOps-database, and uploading the Jenkins pipeline script to the Jenkins-master for configuration.
And S4, when the condition configured in the step S1 triggers, starting to execute a DevOps pipeline task, and enabling the Jenkins-master to interact with an apiserver in the K8S cluster to pull up the container group. In step S4, a DevOps pipeline task is laid out by a plurality of task steps, different task steps will execute commands in different containers, jenkins-master needs to create a container group containing all containers; all containers in the container group realize file sharing through the mounting work catalogue.
In this embodiment, all containers in the same container group mount a "Workspace" directory, and the containers can access the "Workspace" directory and its subdirectories.
Step S5.Jenkins-master performs the DevOps pipeline task by executing the Jenkins pipeline script in step S3. In step S5, the specific process of executing the DevOps pipeline task is as follows:
and S51. The Jenkins-master is sequentially switched to different containers under the container group, and a preset command or Shell script is executed.
S52, when the task flows are split in parallel, a plurality of sub-working directories with the same content are needed to be derived by the existing working directories, namely a plurality of working directory copies are cloned by the existing working directories so as to realize file isolation; and then switching the working catalog to the derived sub-working catalog, executing a plurality of sub-task streams in parallel, and simultaneously switching to different containers belonging to task steps in the sub-task streams to execute the command.
In this embodiment, when the task stream is split into two sub-task streams in parallel, if the original working directory is "Workspace", then "workspace_1" and "workspace_2" are newly created under the "Workspace" directory, and the content of "Workspace" is copied under the two sub-directories, so that the working directory of the sub-task stream 1 is switched to "workspace_1", and the working directory of the sub-task stream 2 is switched to "workspace_2". The structure of the file directory is shown in fig. 3.
Step S53, when the plurality of subtask flows are synchronized, the subtask flows are required to be successfully executed and completed, and after the work catalogue is adjusted to the father work catalogue, the father task flows can be continuously executed.
In this embodiment, when the subtask stream 1 with the working catalog "workspace_1" and the subtask stream 2 with the working catalog "workspace_2" are synchronized, the working catalog of the task stream is switched to "Workspace", file changes of the working catalog are combined, and if a conflict exists, script processing needs to be manually specified.
And S54, when any working step is wrong, terminating all running task flows, and cleaning the working catalogue.
And S6, waiting for complete execution or termination of the task, and interactively destroying the container group by the Jenkins-master and the apiserver.
And S7. The step of monitoring callback of part of the built-in task steps of the system in the pipeline task by the DevOps-background, and executing operations of replacing mirror image, one-key deployment and service arrangement in the Kubernetes cluster according to callback parameters.
And S8. The DevOps-band acquires a Jenkins execution result, shows that the task result is success or failure, and outputs an execution log.
A containerized DevOps system capable of task orchestration, comprising:
the initialization module is used for initializing related components into the container cloud cluster;
the task scheduling module is used for creating a DevOps pipeline task on the interface, scheduling the task through the visual interface and customizing the task flow;
and the task execution module is used for executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log.
A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes a containerized DevOps method capable of performing task scheduling when executing the computer program.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these do not affect the effect of the implementation of the present invention and the utility of the patent.
Claims (9)
1. A containerized DevOps method for task orchestration, comprising:
initializing deployment, which is used for initializing related components into a container cloud cluster;
the method comprises the steps of scheduling a DevOps task, creating a DevOps pipeline task on an interface, scheduling the task through a visual interface, and customizing a task flow;
executing the DevOps task, executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log;
in the process of initializing deployment, related components comprise two components, namely a DevOps back-end service (DevOps-back) and a Jenkins master node (Jenkins-master); the container cloud cluster adopts Kubernetes to arrange containers, and the Jenkins-master can create and destroy container groups through K8s resources; the DevOps-backend, jenkins-master service manages running on a certain working node in the cluster by means of a depoyment.
2. A containerized DevOps method for task orchestration according to claim 1, comprising the specific steps of:
s1, creating a DevOps pipeline task on a DevOps-background interface, and setting a trigger condition;
s2, a user performs task arrangement through a visual interface, and a task flow is defined;
s3, generating a Jenkins pipeline script according to task flows edited by a user by the DevOps-database, and uploading the Jenkins pipeline script to a Jenkins-master for configuration;
step S4, when the condition configured in step S1 triggers, the execution of the DevOps pipeline task is started,
the Jenkins-master interacts with an apiserver in the K8s cluster to pull up the container group;
s5. The Jenkins-master executes the DevOps pipeline task by executing the Jenkins pipeline script in the step S3;
s6, waiting for complete execution or termination of the task, and interactively destroying the container group by the Jenkins-master and the apiserver;
s7. The step of monitoring callback of part of the built-in task steps of the system in the pipeline task by the DevOps-background, and executing operations of replacing mirror images, deploying one key and arranging services in the Kubernetes cluster according to callback parameters;
and S8. The DevOps-band acquires a Jenkins execution result, shows that the task result is success or failure, and outputs an execution log.
3. A containerized DevOps method for task orchestration according to claim 2, wherein in step S1, three trigger mode choices are provided: manual triggering, code warehouse callback triggering and webhook callback triggering; one or more trigger ways may be checked on the interface, and when one of the checked ways is satisfied, the execution pipeline task is immediately triggered.
4. A containerized DevOps method for task orchestration according to claim 2, wherein in step S2, the task orchestration is specifically described as follows: in the DevOps-band, a system built-in task step, a user-defined task step or a task step combination recommended by a system can be manually added;
when adding a task step built in a system, setting preset parameters of the step;
when the custom task step is added, a task mirror image needs to be specified, and a Shell command needing to be executed is input;
the task step combination recommended by the system consists of a plurality of built-in task steps of the system in sequence, and preset parameters of each step are required to be set respectively;
meanwhile, the DevOps-band supports task step parameter modification and task step operation of deleting error addition.
5. The method for task orchestration of claim 4, wherein the method comprises three task flows orchestration modes, namely sequential execution, parallel splitting and synchronization; combining the task steps in the three arrangement modes to finally form the whole task flow; the DevOps-band provides visual operation on the interface, and the whole task arrangement is completed in a mode of dragging a flow chart and linking the flow chart;
the task flow arrangement mode is specifically described as follows: the sequence means that each task step of the task flow is sequentially executed according to the sequence, and the next task step is executed after the current task step is successfully completed; parallel splitting refers to splitting into a plurality of subtask streams after one task step, wherein the subtask streams are executed in parallel and are mutually independent; the synchronization means that a plurality of subtask streams are converged into one task stream at one point, the merging mode is to wait for successful completion of all subtask streams, and then the next task step is carried out, and the merging of the task streams can be completed by using a synchronization operation.
6. The method of claim 2, wherein in step S4, a DevOps pipeline task is formed by arranging a plurality of task steps, different task steps execute commands in different containers, and Jenkins-master needs to create a container group containing all containers; all containers in the container group realize file sharing through the mounting work catalogue.
7. The method of task orchestration of claim 2, wherein in step S5, the specific process of performing the task of the DevOps pipeline is as follows:
s51, sequentially switching the Jenkins-master to different containers under the container group, and executing a preset command or Shell script;
s52, when the task flows are split in parallel, a plurality of sub-working directories with the same content are derived by the existing working directories so as to realize file isolation; then switching the working catalog to the derived sub-working catalog, executing a plurality of sub-task flows in parallel, and simultaneously switching to different containers belonging to task steps in the sub-task flows to execute commands;
s53, when a plurality of subtask flows are synchronized, the subtask flows are required to be successfully executed and completed, and after the working catalogue is adjusted to the father working catalogue, the father task flows can be continuously executed;
and S54, when any working step is wrong, terminating all running task flows, and cleaning the working catalogue.
8. A containerized DevOps system capable of task orchestration, comprising:
the initialization module is used for initializing related components into the container cloud cluster;
the task scheduling module is used for creating a DevOps pipeline task on the interface, scheduling the task through the visual interface and customizing the task flow;
and the task execution module is used for executing the DevOps pipeline task in a containerized mode, and acquiring and displaying an execution result and a log.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements a task orchestration containerized DevOps method according to any one of claims 1-7 when the computer program is executed.
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