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| Section | Weight | Objectives |
|---|---|---|
| Develop multi-agent solutions in Azure | 30-35% | - Implement agent memory, context management, and knowledge integration
|
| Architect multi-agent solutions | 15-20% | - Design logical architecture for multi-agent solutions
|
| Evaluate, optimize, and monitor multi-agent solutions | 20-25% | - Optimize prompt and model performance
|
| Secure, govern, and deploy multi-agent solutions | 20-25% | - Design and implement security for multi-agent solutions
|
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NEW QUESTION # 67
You need to modify claim Approval to prevent the prompt injection issue. Which guardrail should you use?
Answer: B
Explanation:
The malicious text is contained in an uploaded email rather than being typed directly as the user ' s prompt.
Microsoft classifies malicious instructions embedded in external or retrieved content as an indirect prompt- injection attack. Prompt Shields for documents is designed to detect those attacks in document content before the content can steer the model away from its system instructions. Prompt Shields for user prompts addresses direct attacks originating in the user ' s prompt and therefore targets the wrong attack surface here.
Groundedness evaluates whether a response is supported by context; it does not prevent an injected instruction from changing agent behavior. Task Adherence can assess whether an agent follows its task constraints, but it is not the primary control for document-borne prompt injection. Because the source of the attack is the uploaded email, the document-oriented Prompt Shields control is the technically aligned guardrail. The same configuration should be paired with auditable identity, trace, and evaluation data so reviewers can prove which principal acted, which policy was applied, and why a request was allowed or blocked. That is particularly important for production multi-agent systems with external tools.
Official Microsoft reference: Microsoft Foundry guardrails - intervention points and indirect attacks
NEW QUESTION # 68
You have a Microsoft Foundry multi-agent customer support solution that retrieves grounding data from a shared vector index. The indexed corpus contains product runbooks in Markdown and support articles in HTML Both document types use a consistent hierarchical markup.
You discover that current fixed-size token chunking creates chunks that cross section boundaries.
You need to recommend a chunking approach for the ingestion pipeline. The solution must preserve existing document structure boundaries and minimize custom chunking code.
What should you recommend?
Answer: A
Explanation:
The corpus already contains reliable document hierarchy in Markdown and HTML, so the ingestion pipeline should preserve those author-defined boundaries rather than infer new ones from token counts or topic shifts.
Format-specific header splitters can divide Markdown by heading levels and HTML by structural headers, producing chunks that align with meaningful sections. This directly solves the current problem of fixed-size token chunks crossing section boundaries and requires less custom logic than building a semantic topic-shift chunker. Recursive character splitting can be configured with structure-aware separators, but it remains a more generic fallback when format-specific structure is already available. Microsoft Azure AI Search guidance recommends exploiting document structure such as headings when chunking. Therefore B is the most direct and maintainable approach. In production, add telemetry and regression tests around this behavior so changes to prompts, models, tools, or orchestration do not silently alter the intended contract. The selected approach is the one that best matches the platform ' s native execution semantics.
Official Microsoft reference: Azure AI Search - structure-aware chunking and Markdown indexing
NEW QUESTION # 69
You are designing an enterprise automation solution that has a web portal for users and the following types of workflows:
* Routine workflows that use prompt-defined agents, approved knowledge stores, and HTTPS tools
* Modernization workflows that use custom Microsoft Agent Framework code packaged as container images with predefined handoffs and task states You need to recommend Azure services that meets the following requirements:
* The routine workflows must run agents in a fully managed environment.
* The user portal must be deployed as a managed platform as a service (PaaS) web app
* The modernization workflows must run agents in serverless containers that support automatic scaling What should you recommend for each requirement? To answer, drag the appropriate services to the correct components. Each service may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Routine workflows: Microsoft Foundry Agent Service; User portal: Azure App Service; Modernization workflows: Azure Container Apps.
The three workload types map to three different managed Azure services. Prompt-defined agents that use approved knowledge and HTTPS tools fit Microsoft Foundry Agent Service because it provides a managed agent runtime and hosted agent capabilities without requiring the team to operate the underlying orchestration infrastructure. The user portal is a conventional managed web application, making Azure App Service the direct PaaS fit. The modernization workflow is custom Microsoft Agent Framework code packaged as container images and therefore needs a serverless container platform; Azure Container Apps supplies managed container execution and automatic scaling while preserving control of the custom application image.
Logic Apps targets integration workflows rather than arbitrary Agent Framework containers, and Copilot Studio is not the requested general-purpose container runtime. The answer therefore selects the managed service that matches each component ' s execution model. From a security and governance perspective, the control should be enforced at the narrowest platform boundary that can deterministically block or constrain the action. Relying only on prompt text is weaker because the model can still be induced to behave unexpectedly.
Official Microsoft reference: Microsoft Foundry Agent Service overview
NEW QUESTION # 70
You have a Microsoft Foundry multi-agent customer support solution. The solution includes a triage agent that uses Azure Al Search to retrieve customer-supplied HTML articles and Azure Functions to retrieve customer relationship management (CRM) case records. A custom guardrail is assigned directly to the agent.
Some retrieved HTML articles contain hidden instructions that attempt to override the triage agent ' s system message You need to configure guardrails to meet the following requirements:
* Evaluate the complete payload from the supported tools before the content is available to the agent.
* Prevent malicious instructions embedded in externally retrieved content from influencing the agent
* Stop processing when tainted data is detected and inform the security team.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Intervention point: Tool response; Risk: Indirect attacks.
The hidden instructions originate in retrieved HTML returned by supported tools, not in the user ' s direct prompt. Microsoft classifies that pattern as an indirect prompt-injection attack. The Tool response intervention point is specifically designed to inspect the complete payload returned from a tool before the content is stored in agent memory or used for subsequent reasoning. Configuring the Indirect attack control there with a blocking action prevents tainted retrieved data from steering the triage agent. Azure AI Search and Azure Functions are among the supported tools for tool-response moderation, which is important because both appear in the scenario. A Tool call control would inspect arguments sent to a tool rather than hostile content coming back from it. User-input attack detection likewise targets the wrong origin. The correct configuration is therefore Tool response plus Indirect attacks, with the operational response set to stop processing and alert the security workflow when malicious content is detected.
Official Microsoft reference: Microsoft Foundry guardrails - intervention points
NEW QUESTION # 71
You have a Microsoft Foundry multi-agent solution that includes a planning agent and an execution agent You are designing a fixed order process where executions can run for several hours and can be interrupted by worker restarts.
You need to implement orchestration for the process. The solution must meet the following requirements
* Pause at predefined points.
* Resume from the last saved state after an interruption.
Which mechanisms should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Process structure: A workflow with agent executors; Pause mechanism: A human-in-the-loop (HITL) gate; Interruption recovery: Checkpoints.
The process has a fixed execution order and can run for several hours, so an explicit workflow with agent executors is preferable to free-form agent delegation. The requirement to pause at predefined points is a human-in-the-loop requirement: the workflow must be able to suspend and emit a request for approval or operator input. The requirement to resume after worker restarts is addressed by checkpoints. Microsoft Agent Framework checkpoints persist workflow progress, executor state, pending messages, shared state, and outstanding requests so execution can be restored from the last saved point. A retry policy alone re-executes operations but does not reconstruct the complete workflow state after a process interruption. The three selected mechanisms therefore cover structure, controlled pause, and durable recovery as separate but complementary workflow concerns. In production, add telemetry and regression tests around this behavior so changes to prompts, models, tools, or orchestration do not silently alter the intended contract. The selected approach is the one that best matches the platform ' s native execution semantics.
Official Microsoft reference: Microsoft Agent Framework - Checkpoints and Human-in-the-loop
NEW QUESTION # 72
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