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NEW QUESTION: 1
A company is building a new model-driven app.
The app must integrate with a number of on-premises and cloud solutions. No VPNs are in place.
You need to determine the method for each integration.
Which methods should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Webhook
With Dataverse, you can send data about events that occur on the service to a web app by using webhooks. A webhook is a lightweight HTTP pattern for connecting web APIs and services with a publish-and-subscribe model. Webhook senders notify receivers about events by making requests to receiver endpoints with some information about the events.
Webhooks enable developers and ISVs to integrate Dataverse data with their own custom code hosted on external services.
Box 2: Azure Service Bus
Service Bus provides a secure and reliable communication channel between Dataverse runtime data and external, cloud-based line-of-business apps. This capability is especially useful in keeping disparate Dataverse systems or other Dataverse servers synchronized with business data changes.
Box 3: Azure Event hub
Azure Event Hubs is a big data streaming platform and event ingestion service. It can receive and process millions of events per second. Data sent to an event hub can be transformed and stored by using any real-time analytics provider or batching/storage adapters.
Note: The most popular approaches in Dataverse involve webhooks, Azure messaging (Service Bus, Event Hubs), Azure Logic Apps, or Power Automate.
Reference:
https://docs.microsoft.com/en-us/powerapps/maker/common-data-service/why-cds-any-type-app

NEW QUESTION: 2
You use Azure Machine Learning to train and register a model.
You must deploy the model into production as a real-time web service to an inference cluster named service-compute that the IT department has created in the Azure Machine Learning workspace.
Client applications consuming the deployed web service must be authenticated based on their Azure Active Directory service principal.
You need to write a script that uses the Azure Machine Learning SDK to deploy the model. The necessary modules have been imported.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: AksCompute
Example:
aks_target = AksCompute(ws,"myaks")
# If deploying to a cluster configured for dev/test, ensure that it was created with enough
# cores and memory to handle this deployment configuration. Note that memory is also used by
# things such as dependencies and AML components.
deployment_config = AksWebservice.deploy_configuration(cpu_cores = 1, memory_gb = 1) service = Model.deploy(ws, "myservice", [model], inference_config, deployment_config, aks_target) Box 2: AksWebservice Box 3: token_auth_enabled=Yes Whether or not token auth is enabled for the Webservice.
Note: A Service principal defined in Azure Active Directory (Azure AD) can act as a principal on which authentication and authorization policies can be enforced in Azure Databricks.
The Azure Active Directory Authentication Library (ADAL) can be used to programmatically get an Azure AD access token for a user.
Incorrect Answers:
auth_enabled (bool): Whether or not to enable key auth for this Webservice. Defaults to True.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-service
https://docs.microsoft.com/en-us/azure/databricks/dev-tools/api/latest/aad/service-prin-aad-token

NEW QUESTION: 3
When the command echo $ outputs 1, which of the following statements is true?
A. It is the exit value of the command executed immediately before echo.
B. It is the exit value of the echo command.
C. It is the process ID of the current shell.
D. It is the process ID of the echo command.
Answer: A