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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architect multi-agent solutions | 15-20% | - Specify technology components for multi-agent solutions
|
| Topic 2: Develop multi-agent solutions in Azure | 30-35% | - Build and integrate tool ecosystems
|
| Topic 3: Evaluate, optimize, and monitor multi-agent solutions | 20-25% | - Optimize prompt and model performance
|
| Topic 4: Secure, govern, and deploy multi-agent solutions | 20-25% | - Deploy multi-agent solutions to Azure
|
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73. Frage
You have the following tool integration configuration for a Microsoft Foundry claims-processing assistant.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
Explanation:
Yes / Yes / No
The first statement is true because the tool-integration contract returns only the explicitly defined `final_text` from FraudReview to ClaimsPlanner; the planner does not automatically receive the specialist ' s entire internal execution history. The second statement is also true because an external REST service such as PremiumRates can be exposed as an OpenAPI-defined tool. The OpenAPI schema describes operations and parameters, while the surrounding agent system retains conversational state; the REST tool itself does not need a developer-managed chat transcript. The third statement is false under the shown configuration because the partner publishes tool descriptors as published while the planner defines which schemas it accepts or rejects. Compatibility handling therefore occurs at the consumer/tool boundary rather than requiring PartnerIntegrations to rewrite every unsupported schema before invocation. The correct sequence is Yes, Yes, No. At implementation time, the same rule should be expressed through the framework or service configuration rather than left only as a natural-language convention. That makes the behavior repeatable across runs, easier to test, and less sensitive to model variability.
Official Microsoft reference: Microsoft Foundry agents - OpenAPI tools
74. Frage
You have a multi-agent solution in a Microsoft Foundry project. The project connects to an Azure Storage account named stgaudit.
You plan to enable a storage-backed tool for the agent The tool will read and write blobs to stgaudit.
You need to create a role assignment for the agent. The solution must follow the principle of least privilege.
Which role should you use?
Antwort: A
75. Frage
You need to implement the business rule for claim Approval. Which workflow node should you use?
Antwort: B
Begründung:
The business rule requires human review for refunds above the stated threshold before payment can continue.
A workflow therefore needs a user or operator interaction point that pauses progress and obtains an explicit response. In the workflow options provided, Ask a question is the node that introduces that human interaction.
Invoke agent simply delegates work to another agent; it does not itself guarantee human approval. Deliver a message sends information without collecting a decision, and Go to changes control flow without obtaining authorization. Microsoft Agent Framework and Foundry workflow guidance treat human-in-the-loop approval as a first-class orchestration requirement for consequential actions. The decisive requirement is not just to notify a reviewer, but to stop automated progression until the reviewer supplies a decision. Therefore the workflow must include an interactive question/approval step before the refund-processing action can proceed for amounts over the threshold. The implementation should also preserve clear inputs and outputs around this step so that later agents receive only the information they require. This improves debuggability and keeps token, permission, and state growth under control as the workflow becomes more complex.
Official Microsoft reference: Microsoft Agent Framework - Human-in-the-loop workflows
76. Frage
You need to recommend a memory retrieval strategy to support the planned changes for claim Approval.
What should you recommend? To answer, drag the appropriate resources to the correct requirements. Each resource 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.
Antwort:
Begründung:
Explanation:
Prior claims: memory-store-490; Contact preferences: memory-store-490.
Both requirements describe information that should persist across conversations for the same customer:
previous claim information and stable contact preferences. Microsoft Foundry Memory is intended for durable, cross-session facts and summaries that agents can retrieve later, while a knowledge base is for shared reference content rather than user-specific history. The refund-processing and customer-refund tools are operational interfaces, not persistence layers. Using the existing memory store for both categories therefore matches the scenario ' s design objective. In production, the memory search tool should also be scoped to the end user so one customer ' s memory cannot be retrieved for another customer. Microsoft documents scope- based isolation for memory stores and supports a user-derived scope such as `{{$userId}}`. The key distinction is that the same memory store can hold multiple kinds of durable customer memory as long as retrieval is correctly scoped; there is no need to create separate tools or knowledge indexes for these two user- specific memory categories.
Official Microsoft reference: Create and use memory in Foundry Agent Service
77. Frage
You have a Microsoft Foundry multi-agent solution that uses Microsoft Agent Framework and LangGraph.
Telemetry from the workload is sent to Application Insights.
You need to implement observability components to meet the following requirements:
* Support the investigation of user interactions across agents, models, tools, functions, and API boundaries without relying on verbose production logs.
* Produce recurring and comparable measurements of deployed response quality and safety over time.
What should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Antwort:
Begründung:
Explanation:
Runtime instrumentation: OpenTelemetry distributed tracing with correlation IDs; Post-deployment assessment: A scheduled evaluation that uses test datasets.
Distributed tracing is the correct runtime mechanism because the objective is to reconstruct a user interaction across agents, models, tools, functions, and API boundaries without relying on verbose log text. Microsoft Foundry uses OpenTelemetry-compatible traces and Application Insights so related spans can be correlated into one execution path. Correlation identifiers allow operators to isolate one conversation and inspect where latency, failures, or unexpected behavior originated. The second requirement is different: it asks for recurring, comparable measurements of deployed response quality and safety. Scheduled evaluations against stable test datasets provide that longitudinal benchmark and are more appropriate than ad hoc tracing or infrastructure- only dashboards. Together, OpenTelemetry answers "what happened in this run?" while scheduled evaluation answers "is behavior getting better or worse over time?" The selected pair therefore covers both operational diagnosis and quality regression monitoring. For operational use, the measurement should be captured in a repeatable dataset, trace, or automated gate so that the same criterion can be compared across versions. That is more useful than a one-off manual observation and makes regressions visible before they become production incidents.
Official Microsoft reference: Microsoft Foundry observability concepts
78. Frage
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