Google Professional-Cloud-DevOps-Engineer Exam With Confidence Using Practice Dumps

For a postmortem to be truly blameless, it must focus on identifying the contributing causes of the incident without indicting any individual or team for bad or inappropriate behavior.

Cloud Build is a service that executes your builds on Google Cloud Platform infrastructure. Cloud Build can import source code from Google Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build to your specifications, and produce artifacts such as Docker containers or Java archives1. Cloud Build can also run integration tests as part of your build steps2.

You can use Cloud Build to run tests in a specific folder by specifying the path to the folder in the dir field of your build step3. For example, if you have a folder named tests that contains your integration tests, you can use the following build step to run them:

steps:

- name: 'gcr.io/cloud-builders/go'

args: ['test', '-v']

dir: 'tests'

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You can use Cloud Build to trigger builds for every GitHub pull request by using the Cloud Build GitHub app. The app allows you to automatically build on Git pushes and pull requests and view your build results on GitHub and Google Cloud console4. You can configure the app to run builds on specific branches, tags, or paths5. For example, if you want to run builds on pull requests that target the master branch, you can use the following trigger configuration:

includedFiles:

- '**'

name: 'pull-request-trigger'

github:

name: 'my-repo'

owner: 'my-org'

pullRequest:

branch: '^master$'

Using Cloud Build to run tests in a specific folder and trigger builds for every GitHub pull request is a good way to continuously test your feature branch and ensure that all code is tested before changes areaccepted. This way, you can catch any errors or bugs early and prevent them from affecting the main branch.

Using a Jenkins server for CI/CD pipelines is not a bad option, but it would require more setup and maintenance than using Cloud Build, which is fully managed by Google Cloud. Periodically running all tests in the feature branch is not as efficient as running tests for every pull request, as it may delay the feedback loop and increase the risk of conflicts or failures.

Using Cloud Build to run the tests after a pull request is merged is not a good practice, as it may introduce errors or bugs into the main branch that could have been prevented by testing before merging.

Asking the pull request reviewers to run the integration tests before approving the code is not a reliable way of ensuring code quality, as it depends on human intervention and may be prone to errors or oversights.