How do you integrate automated testing into your deployment pipeline and what tools do you use for this

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The question will seek to explain how automated testing is included in the pipeline to ensure good quality code before its deployment. It seeks to know about the tools used for testing and the CI/CD platforms used for automating the testing and how they could integrate within the pipeline of workflow. Target would be to understand the series of steps and tools which could help auto test within the pipeline so that issues can be caught early on for smooth deployments.
Oct 14 in DevOps Tools by anonymous
• 2,430 points

edited Oct 22 by anonymous 76 views

1 answer to this question.

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Automate tests into a deployment pipeline 

1.Add Tests in the Build Stage

 Unit tests, integration tests, and end-to-end tests are all part of a CI/CD pipeline. They run automatically on committing code.
Example:Once a new code is pushed, Jenkins or GitLab CI/CD will call the pipeline automatically. During this stage of the build, unit, integration, and end-to-end tests will run to ensure that new changes don't break the existing functionality. This ensures quality code and system stability before it is deployed.

 2. Test Automation Tools
Unit test: Utilize JUnit, Mocha or PyTest
To integrate tests TestNG or Selenium will be appropriate to test interaction between different components of an application.


3. Static Code Analysis:
Integrate SonarQube or ESLint so the tools verify code quality and flag vulnerabilities during the build process.


4. Continuous Testing:
Use Jenkins, CircleCI, or GitLab CI/CD to automate tests so your code is run through continuous testing as part of every build and deployment cycle.


5. Containerized Testing:
Use Docker to start the test environment that closely resembles the production environment so that you can ensure accurate tests and consistent environments.


6. Deploy to Staging Before Production:
Make sure to deploy to a staging environment first before deploying to production, where tests can run in an environment which closely resembles production by using tools like Kubernetes or Terraform for provisioning.
Automating testing in the pipeline significantly reduces manual intervention, improves quality of code, and builds reliable new deployments before sending them into production.

answered Oct 23 by Gagana
• 1,200 points

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