The code pipeline is about orchestrating everything together to achieve continuous deployment (CD). In CD, the entire software release process is fully automated, including build and deployment to the production release. Over some time with experiments, you can set up a mature CI/CD pipeline in which the path to the production launch is automated, thus enabling rapid deployment of features and immediate customer feedback. You can use cloud-native managed services such as AWS CodePipeline to orchestrate the overall code pipeline, or you can use the Jenkins server.

The code pipeline enables you to add actions to stages in your CI/CD pipeline. Each action can be associated with a provider that executes the action. The code pipeline action's categories and examples of providers are as follows:

• Source: Your application code needs to be stored in a central repository with version control called source code repositories. Some of the popular code repositories are AWS CodeCommit, Bitbucket, GitHub, Concurrent Versions System (CVS), Subversion (SVN), and so on. 
• Build: The build tool pulls code from the source code repository and creates an application binary package. Some of the popular build tools are AWS CodeBuild, Jenkins, Solano CI, and so on. Once the build is completed, you can store binaries in an artifactory such as JFrog.
• Deploy: The deployment tool helps you to deploy application binaries in the server. Some popular deployment tools are AWS Elastic Beanstalk, AWS CodeDeploy, Chef, Puppet, Jenkins, and so on.
• Test: Automated testing tools help you to complete and perform post-deployment validation. Some popular test validating tools are Jenkins, BlazeMeter, Ghost Inspector, and so on.
• Invoke: You can use an events-based script to invoke activities such as backup and alert. Any scripting language such as a shell script, PowerShell, and Python can be used to invoke various customized activities.
• Approval: Approval is an important step in CD. You can either ask for manual approval by an automated email trigger or approval can be automated from tools.

In this section, you learned about various DevOps tools to manage the Software Development Life Cycle (SDLC) such as a code editor, a repository, and build, test, and deployment tools. As of now, you have learned about various DevOps techniques for each SDLC phase. Let's learn more about applying best practices and anti-patterns.