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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop multi-agent solutions in Azure | 30–35% | - Manage state and memory
|
| Topic 2: Architect multi-agent solutions | 15–20% | - Design logical architecture for multi-agent systems
|
| Topic 3: Evaluate, optimize, and monitor multi-agent solutions | 20–25% | - Implement observability
|
| Topic 4: Secure, govern, and deploy multi-agent solutions | 20–25% | - Deploy and maintain solutions
|
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NEW QUESTION # 73
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?
Answer: B
NEW QUESTION # 74
You need to design a solution to resolve the Scheduling agent issue.
What should you include in the design?
Answer: C
Explanation:
The Scheduling agent ' s MCP server fails transiently during peak load. Microsoft Azure reliability guidance recommends retries with exponential backoff for transient faults so that callers do not immediately repeat requests at the same rate and worsen a temporarily overloaded dependency. Immediate retries can create a retry storm, especially when many agent requests encounter the same service condition. Routing the tool call through a different agent does not remove the underlying MCP dependency and would only add coupling. A well-designed retry policy should normally include a bounded retry count, increasing delay, jitter where appropriate, and respect for server-provided retry guidance when available. The scenario asks which design element directly addresses the timeouts, and exponential backoff is the established resilience pattern for transient service saturation. Therefore A is the correct choice. 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: Azure Well-Architected Framework - Handle transient faults
NEW QUESTION # 75
You have a Microsoft Foundry multi-agent solution.
A developer publishes a new version of a specialist agent. Once the agent goes live in production, the solution starts mishandling requests.
You need to restore the previous behavior as quickly as possible
What is the fastest way to roll back the agent?
Answer: D
Explanation:
The fastest safe rollback is to route the stable endpoint back to the previous known-good immutable agent version. Current Foundry lifecycle guidance supports versioned agents and endpoint/version selection so production traffic can be redirected without rebuilding the agent from scratch. Deleting the newly published version is a destructive cleanup action and is not the preferred rollback mechanism because it removes an artifact that may be needed for diagnosis. Creating a new agent changes the lifecycle identity and takes longer, while a complete redeployment is unnecessary if the earlier version already exists. Option C is therefore correct when interpreted as changing the endpoint ' s active-version or version-selector configuration to the previous version while keeping the endpoint URL stable. 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 agents - development lifecycle and versioning
NEW QUESTION # 76
You have a Microsoft Foundry resource that hosts Azure OpenAI model deployments for three projects. Each project is for a different business unit. The projects share the same Foundry resource.
You need to implement a Microsoft Cost Management view that separates the shared model spend by the project The solution must meet the following requirements:
* Use cost data that can be reconciled by using Azure Cost Management.
* Minimize manual tagging.
What should you use?
Answer: B
Explanation:
When multiple projects share one Foundry resource, grouping costs only by Azure resource cannot distinguish project consumption because the resource boundary is shared. Microsoft Foundry integrates with Azure Cost Management by attributing model usage to project metadata/tags, allowing a Cost Analysis view to filter shared resource spending by project. This supports showback or chargeback without requiring administrators to manually tag every usage event. Subscription-level service filters or meter grouping identify the service or billing meter but not which of the three business-unit projects generated the usage. Therefore a Foundry-resource-scoped Cost Analysis view filtered by the project tag is the configuration that both reconciles to Azure Cost Management and minimizes manual tagging. D remains correct. The evaluation should also preserve correlation identifiers and version information where possible so a failed score can be traced back to the exact agent, model, tool call, or retrieval step that produced it. This turns the metric into an actionable diagnostic rather than only a dashboard number.
Official Microsoft reference: Microsoft Foundry - Manage costs
NEW QUESTION # 77
You have a Microsoft Foundry helpdesk triage agent. Employees sign in to the agent by using Microsoft Entra. The agent can invoke the following tools:
* A ticket search tool that enforces the existing per employee authorization model
* A knowledge article tool that writes to a separate production article repository You need to recommend an identity-based access configuration for the following execution contexts:
* Ensure that interactive ticket searches enforce per employee authorization.
* Constrain approved article updates to the production article repository The solution must meet the following requirements:
* Prevent the use of embedded secrets.
* Follow the principle of least privilege
Which access configurations should you recommend? To answer, drag the appropriate configurations to the correct execution contexts. Each configuration 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:
Interactive ticket lookup: Delegated permissions from the signed-in employee; Approved article updates: A managed identity scoped to write production article records.
Ticket search must preserve the existing per-employee authorization model, so the downstream operation should execute in the signed-in employee ' s delegated identity context. That allows the ticket service to enforce the same user-level permissions it already uses. The knowledge-article update is an application- controlled write to one production repository, so a managed workload identity with only the required write permission is the least-privilege choice. Microsoft identity guidance distinguishes delegated/on-behalf-of access for user-context operations from managed or agent identities for service-to-service work. Both approaches also eliminate embedded secrets when configured with Microsoft Entra authentication. A broad Contributor assignment or shared API key would unnecessarily expand the blast radius and weaken audit attribution. Therefore the mixed model in the answer is intentional: delegated permissions for per-user reads, and a narrowly scoped managed identity for controlled production writes. 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 # 78
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