GH-200證照指南,GH-200熱門考古題

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Microsoft GH-200 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Manage GitHub Actions for the enterprise20–25%- Configure organization and repository policies
- Control access and permissions at scale
- Monitor usage and compliance
- Deploy and manage self-hosted runners
Topic 2: Secure and optimize automation10–15%- Mitigate injection and privilege risks
- Apply security best practices
- Implement environment protections and approvals
- Verify and trust marketplace actions
Topic 3: Consume and troubleshoot workflows15–20%- Diagnose and resolve common failures
- Interpret workflow runs and logs
- Manage dependencies and versioning
- Optimize performance and reliability
Topic 4: Author and manage workflows20–25%- Work with secrets, variables, and contexts
- Configure workflow triggers and events
- Manage runners and execution environments
- Use caching, artifacts, and storage
- Implement reusable workflows and templates
Topic 5: Author and maintain actions15–20%- Package, publish, and version actions
- Choose action types: JavaScript, Docker, Composite
- Test and validate custom actions
- Define action metadata and inputs/outputs

>> GH-200證照指南 <<

GH-200熱門考古題 & GH-200最新題庫資源

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最新的 GitHub Administrator GH-200 免費考試真題 (Q39-Q44):

問題 #39
What is the minimal syntax for declaring an output named foo for an action?

答案:A

解題說明:
The correct minimal syntax for declaring an output in GitHub Actions is by using the foo key under outputs , and associating it with a value (in this case, Some value ). This is the simplest form to define an output in a workflow or action.


問題 #40
Which of the following scenarios would require the use of self-hosted runners instead of GitHub- hosted runners?

答案:D

解題說明:
The use of self-hosted runners is required when your workflows depend on specialized hardware configurations that are not available through standard GitHub-hosted runners. While GitHub offers "larger runners" with GPU support for certain paid plans, self-hosted runners provide the most flexibility for highly specific or proprietary hardware needs.
Scenarios Requiring Specialized Hardware
Specific GPU Models: Workflows for AI/ML training or intensive graphics rendering that require specific NVIDIA or other specialized GPU architectures.
Alternative CPU Architectures: When you must build or test on specific ARM processors, legacy x86 32-bit systems, or other non-standard architectures not supported by GitHub's managed pool.
High-Resource Requirements: Tasks needing massive amounts of RAM (beyond 256 GB) or high-core counts for extreme parallel processing.
Custom Peripherals: Workflows that need physical access to hardware connected via USB, PCIe, or other local interfaces (e.g., embedded systems testing or hardware-in-the-loop).
Reference:
https://docs.github.com/en/actions/how-tos/manage-runners/self-hosted-runners/use-in-a- workflow


問題 #41
You create a self-hosted runner labeled as runner1.
You need to ensure that a GitHub Actions workflow job runs only on runner1.
Which YAML statement should you use?

答案:D

解題說明:
To target a specific self-hosted runner, the job must use runs-on with labels that match that runner. A self-hosted runner normally has the self-hosted label plus default labels and any custom labels you assign. Since the runner is labeled runner1, the workflow should specify both self-hosted and runner1:
runs-on: [self-hosted, runner1]. GitHub Actions will then route the job only to a self-hosted runner matching all specified labels. Option A targets a different custom label. Option B is malformed and also mixes a self-hosted label with a GitHub-hosted runner label. Option D targets any self-hosted runner, not specifically runner1. GitHub documents that an array of runs-on labels requires a runner matching all listed labels.


問題 #42
Which default environment variable specifies the branch or tag that triggered a workflow?

答案:C

解題說明:
GITHUB_REF : The branch or tag ref that triggered the workflow.
Reference:
https://graphite.dev/guides/github-actions-variables


問題 #43
A workflow that had been working now stalls in a waiting state until failing. The workflow file process-ml.yaml has not changed and contains jobs specifying runs-on: [gpu ]. Which of the following steps would troubleshoot the issue? (Each answer presents a complete solution.
Choose two.)

答案:A,B

解題說明:
Monitoring and troubleshooting self-hosted runners
You can monitor your self-hosted runners to view their activity and diagnose common issues.
[A] Reviewing the self-hosted runner application log files
You can monitor the status of the self-hosted runner application and its activities. Log files are kept in the _diag directory where you installed the runner application, and a new log is generated each time the application is started. The filename begins with Runner_, and is followed by a UTC timestamp of when the application was started.
[D] You can choose one of the standard GitHub-hosted runner options or, if you are on the GitHub Team or GitHub Enterprise Cloud plan, you can provision a runner with more cores, or a runner that's powered by a GPU processor. These machines are referred to as "larger runner." Reference:
https://docs.github.com/en/actions/how-tos/manage-runners/self-hosted-runners/monitor-and- troubleshoot
https://docs.github.com/en/actions/concepts/runners/github-hosted-runners


問題 #44
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