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| Topic | Details |
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| Topic 1 | - Manage GitHub Actions in the Enterprise: This section measures the expertise of Enterprise Administrators and Platform Engineers in distributing and managing GitHub Actions and workflows at the organizational level. It includes reuse and sharing of templates, strategies for managing reusable components via repositories and naming conventions, controlling access to actions, setting organization-wide usage policies, and planning maintenance to ensure efficient enterprise-wide deployment of GitHub Actions.
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| Topic 2 | - Author and Maintain Workflows: This section of the exam measures skills of DevOps Engineers and Automation Specialists and covers building and managing workflows triggered by events such as pushes, scheduled times, manual triggers, and webhooks. It includes understanding workflow components like jobs, steps, actions, and runners, syntax correctness, environment variables, secrets management, and dependencies between jobs. Candidates will also demonstrate practical abilities to create workflows for various purposes, including publishing packages, using service containers, routing jobs, and deploying releases to cloud providers.
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| Topic 3 | - Consume Workflows: This domain targets Software Developers and Quality Assurance Engineers and focuses on interpreting workflow runs and their outcomes. It covers identifying triggering events, reading workflow configurations, troubleshooting failures by analyzing logs, enabling debug logging, managing environment variables, caching dependencies, and passing data between jobs. Candidates also manage workflow runs, artifacts, approvals, and status badges, as well as locating workflows within repositories and leveraging organizational templated workflows.
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| Topic 4 | - Author and Maintain Actions: This domain evaluates the abilities of Action Developers and Automation Engineers to select and create suitable types of GitHub Actions, such as JavaScript, Docker containers, or run steps. It emphasizes troubleshooting action code, understanding the components and file structures of actions, and using workflow commands within actions to communicate with runners, including exit code management.
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Microsoft GitHub Actions Sample Questions (Q44-Q49):
NEW QUESTION # 44
In the following workflow file, line 5 interprets lines 3 and 4 as Python. Which of the following is a valid option to complete line 5?
1 steps:
2 - run: |
3 import os
4 print(os.environ['PATH'])
5
- A. shell: bash
- B. with: python
- C. shell: python
- D. working-directory: .github/python
Answer: C
Explanation:
Workflow syntax for GitHub Actions
Example: Running an inline Python script
steps:
- name: Display the path
shell: python
run: |
import os
print(os.environ['PATH'])
Reference:
https://docs.github.com/en/actions/reference/workflows-and-actions/workflow-syntax
NEW QUESTION # 45
What will the output be for the following event trigger block in a workflow?

- A. It throws a workflow syntax error, pointing to the types definition in issues event.
- B. It runs the workflow when an issue or issue comment in the workflow's repository is created or modified.
- C. It throws a workflow syntax error, pointing to the types definition in issue_comment event.
- D. It runs the workflow when an issue is created or edited, or when an issue or pull request comment is created.
- E. It runs the workflow when an issue is edited or when an issue comment created.
Answer: E
Explanation:
Based on your configuration, the workflow will trigger in these three specific scenarios:
Issue Opened: When a brand-new issue is created.
Issue Edited: When the title or body of an existing issue is changed.
Comment Created: When someone adds a new comment to an issue or pull request.
Reference:
https://forgejo.org/docs/next/user/actions/reference
NEW QUESTION # 46
As a developer, you are authoring a workflow that will deploy to both DevCloud and TestCloud resources.
Each cloud resource is accessed with a different deployment key. Which approach best allows you to use the same reusable workflow in separate jobs to target the different cloud resources?
- A. Populate a DEPLOY_KEY repository secret with a JSON object containing DevCloud and TestCloud properties. Then specify DEPLOY_KEY.DevCloud in the secrets sections of the reusable workflow.
- B. Use a marketplace action to conditionally parse the DEPLOY_KEY repository secret based on the cloud resource name.
- C. Store the different keys in a DEPLOY_KEY environment secret in the DevCloud and TestCloud environments. Specify DEPLOY_KEY in the secrets section of the reusable workflow.
- D. Create repository secrets named DevCloud.DEPLOY_KEY and TestCloud.DEPLOY_KEY so that the reusable workflow parses the secrets by resource name.
Answer: C
Explanation:
The best design is to use environment-scoped secrets with the same secret name, such as DEPLOY_KEY, in separate environments such as DevCloud and TestCloud. This lets the same reusable deployment logic reference one consistent secret name while the selected environment supplies the correct value. Option A is invalid because GitHub secret names should not be designed around dotted property access, and reusable workflows should not parse secret names dynamically. Option C introduces unnecessary marketplace dependency and weak secret handling. Option D is also wrong because GitHub secrets are opaque strings; ${{ secrets.DEPLOY_KEY.DevCloud }} is not valid secret property access. Reusable workflows can define and receive named secrets through the secrets mapping.
NEW QUESTION # 47
You are reaching your organization's storage limit for GitHub artifacts and packages. What should you do to prevent the storage limit from being reached? (Each correct answer presents a complete solution. Choose two.)
Answer:
Explanation:
B.C
Explanation:
[E] To bypass GitHub's limit of 100 MB you can use Git Large File Storage (Git LFS). It stores references to your file in the repo by creating a pointer file. However, the actual file is going to be stored at a different location.
[C] Configuring the retention period for GitHub Actions artifacts and logs in your organization You can configure the retention period for GitHub Actions artifacts and logs in your organization.
By default, the artifacts and log files generated by workflows are retained for 90 days before they are automatically deleted. You can adjust the retention period, depending on the type of repository:
For public repositories: you can change this retention period to anywhere between 1 day or 90 days.
For private repositories: you can change this retention period to anywhere between 1 day or 400 days.
When you customize the retention period, it only applies to new artifacts and log files, and does not retroactively apply to existing objects. For managed repositories and organizations, the maximum retention period cannot exceed the limit set by the managing organization or enterprise.
Reference:
https://gitprotect.io/blog/github-storage-limits/
https://docs.github.com/en/organizations/managing-organization-settings/configuring-the- retention-period-for-github-actions-artifacts-and-logs-in-your-organization
NEW QUESTION # 48
As a developer, which of the following snippets will enable you to run the commands npm ci and npm run build as part of a workflow?
- A. - run:
npm ci
npm run build - B. - shell:
npm ci
npm run build - C. - shell: |
npm ci
npm run build - D. - run: |
npm ci
npm run build
shell: nodejs - E. - run: |
npm ci
npm run build
Answer: E
Explanation:
Use the run: keyword only, not the shell keyword.
Use the special character |.
Note: There are two ways to run commands one after another on Github Actions.
Reference:
https://stackoverflow.com/questions/71047777/how-to-run-two-commands-on-github-actions- instance-one-after-another
NEW QUESTION # 49
......
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