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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and manage agents | 20–25% | - Deploy and manage agent lifecycle
|
| Plan and configure agent solutions | 30–35% | - Configure agent foundations
|
| Build and extend agents in Copilot Studio | 40–45% | - Integrate with services and systems
|
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NEW QUESTION # 118
A solution architect is implementing a governance process for an agent developed in Copilot Studio. Before the agent is moved to production, the organization requires a standardized validation process to ensure that updates to the underlying knowledge base do not cause regressions in response accuracy.
The validation process must satisfy the following technical criteria:
- Consistency: Execute a fixed library of test cases containing
specific user prompts.
- Grounding: Measure the quality of the generated output against a
verified "golden" response.
- Comparison: Provide a performance delta between the current version
and previous test runs.
You need to choose an evaluation method that meets the requirements.
What should you use?
Answer: C
Explanation:
Using a predefined test set (often called a "golden dataset") and comparing results against expected outcomes across runs is the exact industry standard and best practice for this scenario.
In the context of Copilot Studio and LLM governance, this method is known as Regression Testing or Automated Evaluation.
Consistency: A fixed library of test cases (prompts) ensures that the agent is evaluated on the exact same baseline every time the knowledge base changes.
Grounding: By matching the real-time output against a verified "golden" response, you can use semantic similarity metrics (such as BERTscore, BLEU, or LLM-as-a-judge) to score how well the agent stayed grounded in the source material.
Comparison: Storing the evaluation scores of each run allows you to build a deployment dashboard. This gives you a clear performance delta (e.g., "Accuracy dropped by 4% after the June policy update") before approving the production release.
Reference:
https://agentic-engineering.swmansion.com/expanding-horizons/model-evaluation/
NEW QUESTION # 119
A company has agents in Copilot Studio.
The company needs to prevent the agents from using disallowed connectors and insecure data flows. Administrators must be able to enforce the governance controls to prevent and report violations.
You need to enforce governance controls for agents.
What should you do?
Answer: D
Explanation:
To enforce governance controls, prevent Copilot Studio agents from using disallowed connectors, and restrict insecure data flows, the correct action to take is to Configure data policies.
Real-Time Prevention: Data policies (Data Loss Prevention or DLP) function as a critical build- time and runtime boundary. If an agent relies on a blocked or disallowed connector, Microsoft Copilot Studio immediately blocks execution or publishing and surfaces an error to the maker or user.
Connector Isolation: Admins use the Power Platform admin center to categorize connectors into Business, Non-Business, or Blocked groups. This directly prevents insecure data flows by ensuring data cannot be leaked from business systems (like Microsoft Dataverse) to unapproved external channels or APIs.
Reporting & Auditing: Violations of these data policies are logged and can be tracked centrally by administrators to report and monitor compliance across environments.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/admin-data-loss-prevention
NEW QUESTION # 120
A company must enable an agent in Copilot Studio to execute operations exposed by an external MCP server.
The MCP server publishes callable tools and requires authentication.
The agent must be able to invoke MCP tools during conversations.
You need to configure MCP tools so the agent can execute MCP tool calls.
What should you do?
Answer: C
Explanation:
You must add a new Model Context Protocol tool to your agent and configure it with OAuth 2.0 authentication settings. This registers the server's published capabilities as native actions that the agent can orchestrate during conversation.
Reference:
https://learn.microsoft.com/en-us/power-pages/configure/mcp-connect-clients
NEW QUESTION # 121
A company has agents in Copilot Studio.
The company needs to prevent the agents from using disallowed connectors and insecure data flows. Administrators must be able to enforce the governance controls to prevent and report violations.
You need to enforce governance controls for agents.
What should you do?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Power Platform data policies are the preventive governance control for connectors, HTTP endpoints, knowledge sources, and combinations of data groups used by Copilot Studio agents. Administrators can classify or block connectors, restrict endpoint use, require authentication, and surface policy violations during authoring or publishing. This meets both enforcement and reporting requirements. Application Insights records runtime telemetry but does not prevent a maker from adding a disallowed connector. Security FAQs provide guidance only. Agent analytics can reveal behavior and usage trends but are detective, not an administrative guardrail. Data policies should be scoped deliberately at tenant or environment level and tested against representative agent configurations. When a violation occurs, Copilot Studio can block publishing and provide downloadable details identifying the policy conflict, enabling the administrator and maker to correct the design. Governance should also include least-privilege connections, environment segmentation, solution-based ALM, and review of exceptions; a broadly permissive policy followed by manual monitoring is not equivalent to enforcing the control at design and deployment time. Study Guide alignment: Plan and configure agent solutions > Plan an agent solution > Evaluate security and governance considerations.
NEW QUESTION # 122
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
An agent uses a flow that calls an external service which can occasionally fail or time out.
When a failure occurs, the agent must meet the following requirements:
- Must not terminate silently.
- Must send a notification containing the error details.
You need to configure the agent flow so that failures are handled in a controlled and predictable way.
Solution: Terminate the flow immediately on error.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* Configure run after conditions for failure paths.
You should configure the "Run after" conditions in Power Automate (the underlying flow engine) to handle these failures in a controlled and predictable way.
By default, a cloud flow step only runs if the previous step is successful. If your external service fails or times out, all subsequent steps will normally skip, causing the flow to fail silently from the perspective of the Copilot Studio agent.
How to Configure the Flow for Failure Handling
To meet your requirements, you need to create a parallel or sequential failure path using the following steps:
1. Add your Notification Action
2. Configure "Run After" Settings
Incorrect:
* Retry the failing action without handling failure.
* Send a notification with relevant error details.
* Terminate the flow immediately on error.
Reference:
https://www.matthewdevaney.com/3-power-automate-error-handling-patterns-you-must-know/
NEW QUESTION # 123
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