GH-600 Examengine - GH-600 Zertifizierungsprüfung

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Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Test, deploy, and monitor agentic AI systems	20%	- Validate agent performance and safety 1. Evaluate quality metrics and iterate 2. Apply guardrails and content safety 3. Test reasoning accuracy and consistency - Deploy and monitor agents at scale 1. Optimize cost, latency, and throughput 2. Deploy to Azure AI and cloud environments 3. Implement logging, telemetry, and observability
Implement agents and multi-agent systems	30%	- Orchestrate multi-agent collaboration 1. Implement workflows and coordination strategies 2. Manage agent handoffs and task distribution 3. Define communication protocols between agents - Build agents with Azure AI tools and frameworks 1. Implement agent logic and reasoning 2. Develop using Semantic Kernel and Azure AI Foundry 3. Integrate models and prompts
Integrate tools, data, and services	25%	- Connect data sources and knowledge bases 1. Implement retrieval-augmented generation (RAG) 2. Integrate vector databases and search 3. Ensure data security and access control - Incorporate external tools and APIs 1. Design and register tool definitions 2. Handle authentication and error resilience 3. Implement function calling and service integration
Design agentic AI solutions	25%	- Design agent architecture 1. Plan tool integration and orchestration 2. Select agent patterns and topologies 3. Design memory and state management - Define requirements for agentic systems 1. Plan for responsible AI and governance 2. Identify use cases and scenarios 3. Define functional and non-functional requirements

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GH-600 Zertifizierungsprüfung - GH-600 Buch

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Microsoft Developing in Agentic AI Systems GH-600 Prüfungsfragen mit Lösungen (Q19-Q24):

19. Frage
You want to prevent GitHub Copilot from ever suggesting completions or making edits inside a directory containing sensitive credentials templates. What should you configure?

A. A .copilotignore file
B. Branch protection rules
C. A repository ruleset
D. A CODEOWNERS file

Antwort: A

Begründung:
A .copilotignore file explicitly excludes specified files or directories from being read, indexed, or modified by Copilot, similar in syntax to .gitignore.

20. Frage
You need to enable Copilot memory to support the planned changes.
What should you configure?

A. The Copilot settings of each repository
B. The Copilot settings of the organization
C. The agent profile of agent1
D. The personal Copilot settings of each developer

Antwort: B

21. Frage
You assigned an issue to the Copilot coding agent, and it opened a pull request. You want to inspect exactly what code changes were made before merging. Which CLI slash command lets you view the change set directly in the terminal?

A. /context
B. /diff
C. /plan
D. /compact

Antwort: B

Begründung:
The correct command is /diff. GitHub Copilot CLI provides /diff specifically for reviewing code changes directly from the terminal. GitHub's current CLI command reference defines /diff as a command that reviews changes in the current directory and can automatically switch to a branch comparison when the working tree is clean. This makes it the appropriate command when validating an agent-generated change set before accepting or merging the work.
The other commands serve different purposes. /context displays context-window utilization, including token allocation and remaining context capacity; it does not show code modifications. /compact summarizes conversation history to reclaim context-window space during long-running sessions. /plan creates an implementation plan before coding and restricts normal project-file modifications while the plan is being prepared.
Using /diff supports an essential human-in-the-loop control in agentic software development: generated code should be inspected before it crosses a merge or deployment boundary. Reviewing the diff exposes additions, deletions, and modifications so that unintended or unsafe changes can be identified before integration.
Study Guide Reference Topics: Implement Tool Use and Environment Interaction; agent-generated code review; human-in-the-loop validation; controlled execution and change inspection.

22. Frage
You have a repository that uses a GitHub Actions workflow to run an agent-driven change plan as part of a CI pipeline. The workflow generates an artifact named plan.json that includes a field named risk. Risk has possible values of low, medium, or high.
You need to ensure that a human must confirm the execution of the workflow when risk is medium or high. The workflow must proceed automatically only when risk is low.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets.

Antwort:

Begründung:

23. Frage
You have a GitHub Enterprise Cloud repository that uses the GitHub Copilot coding agent to resolve backlog issues by creating draft pull requests. The repository uses a GitHub Actions workflow for deployments to the production environment.
You discover that the workflow is being triggered before human review.
You need to configure GitHub controls to meet the following requirements:
The workflow for the agent's draft pull requests must NOT run until a user that has write access approves the pull requests.
Production deployment jobs must start only after a user with write access explicitly approves the jobs.
Which controls should you configure? To answer, drag the appropriate controls to the correct requirements.

Antwort:

Begründung:

24. Frage
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