You design the Power Platform solution that is heavily based on the Dataverse API services.
To ensure that a solution would not exceed service protection API limits, you need to add controls to the design to monitor the measures that Dataverse API limits are based on.
What are three measures you should monitor in your design?
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A. B. C. D. E. F.Correct Answers: A, B, D and E
Each Dataverse environment can have its own security model.
The Dataverse environment security is the Role Based Access Control model (RBAC)
The Business unit security model is the basis for Dataverse security.
The model controls access to the data using security roles, teams, and users.
By linking all of them together, you are getting a role-based security model.
Option A is correct because all users accessing Dataverse data are authenticated by Azure AD.Option B is correct because the license is part of Dataverse security and works as the first gate for access to Power Apps components.
Option D is correct because the Data Loss Prevention policy prevents unintentional exposure of the organization's data by dividing the connectors into Non-Business/Default, Business, and Blocked groups.
Depending on an organization's needs, you can move connectors between groups.
In addition, such grouping prevents connectors from sharing data with each other.
Option E is correct because each Dataverse environment is a container to store and isolate data, applications, and business processes.
Each container can have its own security model and access.
Option C is incorrect because Environment Maker can create resources in the Dataverse environment but does not have any privileges to access the data.
Option F is incorrect because the Dataverse security model is Role based, not Rule based.
For more information about Dataverse security, please visit the below URLs:
When designing a Power Platform solution that heavily relies on the Dataverse API services, it is important to monitor the measures that are used to determine the API limits. This ensures that the solution does not exceed the service protection API limits, which can result in service disruptions and degraded performance.
The following are the three measures that should be monitored in the design:
Number of requests: This is the total number of requests made to the Dataverse API. It is important to monitor the number of requests to ensure that the solution is not making excessive requests, which can result in exceeding the API limits. To monitor the number of requests, you can use tools such as Azure Monitor or Power Platform Analytics.
Average execution time of the request: This is the amount of time it takes for a single request to complete on average. Monitoring the average execution time of requests can help identify slow-performing requests that may be consuming more resources and contributing to API limit breaches. You can monitor the average execution time using tools such as Azure Application Insights or Dataverse API diagnostics logs.
Number of concurrent requests: This is the number of requests that are being processed at the same time. Monitoring the number of concurrent requests is important because exceeding the concurrent request limit can cause service disruptions and degraded performance. You can monitor the number of concurrent requests using tools such as Azure Monitor or Dataverse API diagnostics logs.
In addition to these measures, other factors that can affect API limits include the number of batch requests, execution time, number of retries, and the number of users accessing the solution. Therefore, it is important to design the solution with these factors in mind and to continually monitor and adjust the solution to avoid exceeding the API limits.