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| Topic | Details |
|---|
| Topic 1 | - 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 2 | - 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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| Topic 3 | - 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 4 | - 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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Microsoft GitHub Actions Sample Questions (Q23-Q28):
NEW QUESTION # 23
As a developer, you have a 10-MB data set that is required in a specific workflow.
Which three steps should you perform so the dataset is stored encrypted and can be decrypted during the workflow? Each correct answer presents part of the solution.
NOTE: Each correct answer is worth one point.
- A. Create a GitHub encrypted secret with the Large object option selected and upload the dataset.
- B. Store the dataset in a GitHub encrypted secret.
- C. Compress the dataset.
- D. Encrypt the dataset.
- E. Store the encryption keys in a GitHub encrypted secret.
- F. Leverage the actions/download-secret action in the workflow.
- G. Commit the encrypted dataset to the same repository as the workflow.
Answer: D,E,G
Explanation:
To handle a 10 MB dataset securely in GitHub Actions, you should use GitHub Actions Secrets for the key and a symmetric encryption tool (like GPG or OpenSSL) for the file.
Follow these steps:
[B] 1. Encrypt the Dataset Locally
Since GitHub Actions secrets have a size limit of 48 KB, you cannot store a 20 MB dataset directly as a secret. Instead, encrypt the file locally using GPG before committing it.
[A] 2. Store the Encryption Key in GitHub
Store the passphrase you just created as a GitHub Actions Secret so the workflow can access it securely without exposing it in the code.
[G] 3. Commit the Encrypted Dataset
Now, add only the encrypted version of your data to your repository.
Add the encrypted file: git add large_dataset.csv.gpg
Important: Ensure the original unencrypted large_dataset.csv is added to your .gitignore so it is never committed.
Commit and push the encrypted file to your repository.
4. Decrypt the Dataset in the Workflow
In your GitHub Actions workflow file (e.g., .github/workflows/main.yml), add a step to decrypt the file using the secret passphrase.
Incorrect:
[Not D]
Since GitHub Secrets have a size limit (64 KB), you cannot store the dataset itself as a secret.
Reference:
https://docs.github.com/en/enterprise-server@3.20/actions/how-tos/write-workflows/choose-what- workflows-do/use-secrets
NEW QUESTION # 24
Which of the following is the most common way to target a specific major release version?
- A. steps:
- uses: actions/checkout - B. steps:
- uses: actions/checkout@v3 - C. steps:
- uses: actions/checkout@U1673995124 - D. steps:
- uses: actions/checkout@ac593985615ec2ede58e132d2e21d2b1cbd6127c
Answer: B
Explanation:
Example: Using versioned actions
steps:
# Reference a specific commit
- uses: actions/checkout@8f4b7f84864484a7bf31766abe9204da3cbe65b3
*-> # Reference the major version of a release
- uses: actions/checkout@v4
# Reference a specific version
- uses: actions/checkout@v4.2.0
# Reference a branch
- uses: actions/checkout@main
Reference:
https://docs.github.com/en/actions/reference/workflows-and-actions/workflow-syntax
NEW QUESTION # 25
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: python
- B. with: python
- C. working-directory: .github/python
- D. shell: bash
Answer: A
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 # 26
As a DevOps engineer, you need to define a deployment workflow that runs after the build workflow has successfully completed. Without modifying the build workflow, which trigger should you define in the deployment workflow?
- A. workflow_run
- B. workflow_exec
- C. workflow_dispatch
- D. repository_dispatch
Answer: A
Explanation:
A deployment workflow can be started after a build workflow has finished by using the workflow_run event in the deployment workflow's on trigger. You must specify the name of the build workflow you want to trigger on and use an if condition to ensure the deployment workflow only runs if the build workflow successfully completes.
Here's how to set it up:
In your deployment workflow file: (e.g., deploy.yml), define the on: trigger.
Use the workflow_run event: within the on: trigger.
Specify the build workflow: by its name.
Add a conditional if statement: to the workflow to check the conclusion of the workflow_run event, ensuring it equals 'success'.
Reference:
https://docs.github.com/actions/learn-github-actions/events-that-trigger-workflows
NEW QUESTION # 27
While awaiting approval, how many days can a workflow be in the "Waiting" state before it automatically fails?
- A. 14 days
- B. 7 days
- C. 60 days
- D. 30 days
Answer: D
Explanation:
When a workflow job targets an environment that has required reviewers, the job enters a waiting state until it is approved or rejected. GitHub Actions does not allow that waiting state to remain indefinitely. If the job is not approved within the allowed period, the workflow fails automatically. The correct duration is 30 days, making option C correct. Options A, B, and D do not match the GitHub Actions environment approval behavior. This is important for deployment governance because required reviewers can block access to protected environments and environment secrets, but pending approvals still have a maximum lifetime. This exam topic aligns with protected environments, deployment approvals, required reviewers, and workflow execution control.
NEW QUESTION # 28
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