Construction and Deployment Evaluation Based on Cloud Efficiency Pipeline

cloud efficiency pipeline solution


Construction and deployment evaluation based on cloud efficiency pipeline

cloud efficiency pipeline background

cloud efficiency pipeline.In order to test whether the cloud effect Flow meets the application scenarios of our enterprise, generally speaking, the deployment scenarios using K8S are as follows:
1. Perform a certain quality inspection on the source code, such as unit testing, code scanning, etc.
2. Build the source code into a deliverable artifact, which is a container image.
3. Verify the test environment for the product.
4. Use the verified product for online deployment.
5. Use infrastructure as code to manage all YAML files related to the application in the code base.
Activities require the participation of different roles: development, testing, operation and maintenance. How to ensure that different participants can use a unified delivery process to collaborate is the main problem to be solved by the cloud-efficiency Flow delivery pipeline.

cloud efficiency pipeline Testing process


Visit the SpringBoot sample application
1. After the cluster is successfully released, click Kubectl Release to view the cluster release log, and you can see the HOSTS and ADDRESS addresses that were successfully released.

cloud efficiency pipeline.Note: If the ADDRESS address does not appear after running the pipeline, run the pipeline again.

Enter the domain name in the browser and the returned page is as shown below, the SpringBoot sample application is successfully deployed.

Modify arbitrary code to trigger continuous delivery

Because we turned on code source triggering earlier, when it is detected that the master branch has code changes, it will automatically trigger the running of the pipeline.

The cloud effect continuous delivery pipeline and kubernetes are well combined, providing a good foundation for the continuous delivery of applications.

cloud efficiency pipeline.The developer submits the code changes to the code repository, and the cloud effect is monitoring the changes of the code base. Once the code changes, it will automatically trigger the cloud effect continuous deployment pipeline to run a build task, including code inspection, construction, test deployment, test verification and production. environment deployment, etc.
Among them, after the construction is completed, the Docker image is generated and automatically uploaded to the application image warehouse. During the deployment stage, the image version constructed by the current pipeline instance is obtained, and the container is orchestrated and deployed through kubernetes . And all of this is done through automated means.

cloud efficiency pipeline.Test experience


Cloud effect products , integrated DevOps R&D platform, from project management to code, knowledge base, DevOps integrated platform, without switching between multiple systems, greatly improving work efficiency. In addition, it is suitable for a variety of collaboration scenarios and provides different project management templates, covering from general team collaboration to professional agile practices , and can be customized according to its own business processes, including Kanban, calendar, Gantt Graphs, burndown charts and multi-level lists to intuitively understand project progress. Powerful customization capabilities, you can customize task types, status, task fields, labels, priorities, display fields, and more. Efficient code review in code management, supports both PR and CR modes, provides a convenient and standardized code review process, built-in powerful static code specifications and vulnerability scanning tools, which can provide more comprehensive code quality tips and modification suggestions for the review process Information. Refined permission management, multi-dimensional and fine-grained permission system to meet the needs of enterprises of various sizes, and support for refined permission management and control at the warehouse, branch and directory file levels, these features are very suitable for our R&D personnel.


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