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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architect multi-agent solutions | 15–20% | - Design workflow and tool integration
|
| Topic 2: Secure, govern, and deploy multi-agent solutions | 20–25% | - Deploy and maintain solutions
|
| Topic 3: Develop multi-agent solutions in Azure | 30–35% | - Manage state and memory
|
| Topic 4: Evaluate, optimize, and monitor multi-agent solutions | 20–25% | - Assess performance and reliability
|
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NEW QUESTION # 36
You have a multi-agent customer support solution in a Microsoft Foundry project.
You have a dataset that contains query, context, and response without document relevance labels.
You need to implement built-in evaluators that provide 1 to-5 scores with pass/fail labels for the following metrics:
* The quality of the retrieved context
* How directly a response answers a query
Which evaluator should you use for each metric? To answer, drag the appropriate evaluators to the correct metrics. Each evaluator 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:
Quality of retrieved context: Retrieval evaluator; Directness of response to query: Relevance evaluator.
The dataset contains query, context, and response but does not contain document relevance labels. Microsoft ' s Retrieval evaluator is designed for exactly that situation: it uses an LLM judge to rate how relevant the retrieved context chunks are to the query and returns a 1-to-5 score with pass/fail behavior. The Relevance evaluator operates on the final response and measures whether the answer accurately, completely, and directly addresses the query. Document Retrieval is not appropriate because it requires retrieval ground truth such as known relevant documents or qrels. Groundedness answers a different question: whether response claims are supported by the provided context. Therefore the correct mapping is Retrieval for context quality and Relevance for response directness. 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 - RAG evaluators
NEW QUESTION # 37
You have a Microsoft Foundry agent named Agent1.
You open Agent1 in the playground and update the instructions.
You need to run a full evaluation against the updated instructions. The solution must meet the following requirements:
* Test the changes by using a synthetic dataset.
* Ensure that the changes are available only for the development team that has access to Agent1.
What should you do first?
Answer: D
Explanation:
The instructions changed in the playground, but a full evaluation needs a stable, versioned agent definition.
Saving the changes as a new version creates an immutable snapshot that can be evaluated against a synthetic dataset while remaining inside the project for the development team. Publishing is a later lifecycle action that makes a version available to broader consumers or production endpoints and is not required for a private development evaluation. Previewing exercises the current playground configuration interactively but does not establish the versioned target needed for repeatable evaluation. Creating an evaluation before saving the new version risks evaluating the previous configuration instead of the intended update. Microsoft Foundry ' s development lifecycle separates edit, save/version, evaluate, and publish stages, so A is the correct first action. A robust evaluation program separates process metrics from final-response metrics. The selected answer measures the layer where the stated failure actually occurs, which is essential for deciding whether to change retrieval, orchestration, prompt behavior, or the final generator.
Official Microsoft reference: Microsoft Foundry agents - development lifecycle
NEW QUESTION # 38
Solution: Use separate a managed identity for each agent and environment Assign Azure roles at the resource level. Does this meet the goal?
Answer: A
Explanation:
Separate managed identities for each agent and environment remove the need to store application secrets and create independent authorization boundaries. Assigning Azure roles at the resource level further limits each identity to only the Storage resource it requires. This sharply reduces lateral movement compared with a shared application principal or subscription-wide role. Microsoft Foundry and Azure identity guidance consistently recommend identity-based authentication, distinct identities when permissions differ, and the narrowest practical RBAC scope. In current Foundry deployments, the exact identity object may be represented through Microsoft Entra agent identity or a federated managed identity relationship, but the architectural principle in the option is correct. Therefore the solution meets both stated goals and the answer is A, Yes. 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 identity
NEW QUESTION # 39
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 # 40
You are designing Microsoft Foundry multi-agent solution. The agents will use Agent-to-Agent (A2A) delegation and access separate Azure Storage containers within a resource group named RG1.
You need to recommend identity components for the design. The solution must meet the following requirements:
* Eliminate stored application secrets.
* Limit the impact of a compromised agent or deployment.
Solution: Use delegated user permissions for agent actions. Assign Azure roles by using a shared security group. Does this meet the goal?
Answer: A
Explanation:
The proposed solution uses delegated user permissions for agent actions and assigns Azure roles through one shared security group. Even if it avoids storing an application secret, it does not create strong per-agent authorization boundaries. Sharing downstream permissions through one group can allow a compromised agent to inherit access intended for other agents, which conflicts with the requirement to limit blast radius.
Microsoft Foundry identity guidance recommends distinct logical agent/workload identities and narrowly scoped role assignments when agents have different resource responsibilities or audit requirements. Delegated user access is appropriate when an operation genuinely needs the signed-in user ' s authorization context, not as a general service-to-service isolation model for autonomous A2A workers. Therefore the proposed design does not meet both goals, and B, No, remains correct. 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 agent identity
NEW QUESTION # 41
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