From code submission, construction, testing and deployment, the complete end-to-end CodePipeline function will be achieved. With the method of Webhook trigger or event listening, the CodePipeline executes automatically. At the same time, CodePipeline also provides the artificial control ability, and the follow-up operation upon confirmation by the user is supported by adding manual approval operation to the execution process
Based on different focuses of users at different stages of products, it supports flexible configuration of CodePipelines. Tasks in the same stage can be set as serial execution or parallel execution, to meet multiple customer scenarios
It supports multiple code management platform integration, and can seamlessly integrate with Git, GitHub, JD Cloud CodeCommit and other platforms to obtain source code
It supports the construction and unit test for multiple compiler languages such as Java, Golang, NodeJs and Python. Docker image compilation is supported, and compilation and building as well as safety inspection are provided with the method of isolating container-level resources
Deep integration is carried out with JD Cloud JCS for Kubernetes service, life cycle management for containerized application is supported, and whole-process automation of application release under container environment is achieved
It supports viewing the execution status of CodePipeline, and viewing the detailed access task information and operation records etc.
It supports view the detailed CodePipeline execution information, including start time, end time, execution duration and execution ID ect.
With the help of CodePipeline, you can accomplish the complete DevOps process from code change to construction, test and deployment to ensure that only codes that pass the automatic test can be delivered and deployed, which efficiently replaces the traditional method that is complex in internal deployment and slow in iteration.
Deep integrated with JD Cloud Container Service not only offers the construction of Docker Image and uploads it to the Container Registry, but also communicates with JCS for Kubernetes to implement the automatic continuous delivery of Docker containerization application.
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