Module Assessment

1.

A development team builds an Azure Function with an HTTP trigger that calls an external device-availability service. During a peak reconciliation window, the external service sometimes takes four minutes to respond, and the calling flow's request fails at the platform's load balancer before the external service finishes. Which change addresses this failure?

Increase the Azure Function's own timeout setting so the HTTP request can run longer before the platform returns an error.

Reduce how often the calling flow invokes the function so the external service has less load to process.

Replace the blocking HTTP call with an orchestration that acknowledges the request immediately and lets the caller poll for the result.

2.

Contoso's provisioning workflow needs to check device availability across a primary warehouse, a regional backup site, and a refurbished-device pool at the same time, then select the best option once every check finishes. Which Durable Functions pattern fits this requirement?

A single activity function that queries each source one after another within the same execution.

A fan-out/fan-in orchestration that runs each availability check as a parallel activity function and combines the results after all checks complete.

A timer-triggered function that polls each source on a recurring schedule until all three report a result.

3.

A scheduled reconciliation function recalculates employee device allowances every night. After a recent deployment caused the function app to restart twice during the scheduled window, the team noticed that allowances were recalculated twice in a single night. Which configuration choice most likely caused the duplicate run?

The timer trigger's runOnStartup property is set to true, so each host restart fires the function again.

The timer trigger's schedule uses a TimeSpan value instead of a NCRONTAB expression.

The schedule expression was configured to fire twice instead of once per night.

4.

Contoso wants a function to react when a request's status changes in Dataverse. The update happens frequently, in bursts of hundreds of changes during peak hours, and the team wants built-in retry and dead-letter handling if the function is temporarily unavailable. Which approach best fits these requirements?

Register a direct Dataverse webhook that calls the function's HTTP trigger for every status change.

Configure Dataverse to post the execution context to Azure Service Bus and trigger the function from the queue.

Have the function poll the request table on a short recurring schedule to detect status changes.

5.

A function app uses a system-assigned managed identity and needs read and write access to the device, request, and allowance tables in Dataverse. Which combination of steps grants the function exactly the access it needs?

Create a Dataverse application user for the managed identity's application (client) ID, and associate it with one of Dataverse's default security roles.

Store the managed identity's access token as a client secret in the function app's configuration, and grant that secret a custom security role.

Create a Dataverse application user for the managed identity's application (client) ID, and associate it with a custom security role scoped to the three tables.

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