Measures for Dataverse API Limits
Question
You create an application that uses the Dataverse API services.
You need to put in your code the error handler for service protection API limit errors.
Please select the three measures that Dataverse API limits are based on.
Answers
Explanations
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A. B. C. D. E. F.Correct Answers: A, C and F
The Dataverse provides the web services as extension tools for interacting with the data and metadata.
The Dataverse web services include Web API and Organization service.
If you prefer to write the .Net code, the Organization service approach is the best bet.
The Web API provides almost the same functionality by using the REST API protocol.
The Organization service implements two assemblies: SDK assembly and XRM Tooling assembly for the Windows clients.
The API service limits protect the Dataverse service performance and availability.
If some users send an extraordinary amount of requests that can affect the other users' operations, the Dataverse limits such a demand for its services.
The Dataverse service protection API limits are enforced per web server and user.
They are based on three measures: Number of requests - the number of requests sent by a user.
The limit is 6000 requests within the 5-minute sliding window.
Execution time - the combined time for all requests sent by a user.
The limit is 20 minutes within the 5-minute sliding window.
Number of concurrent requests - the number of concurrent requests made by a user.
The limit is 52 requests.
The Dataverse applies all these measures in combination.
If a user crosses the API limit, the service sends an error.
In the Web API case, the API response will include an HTTP error 429 - Too many requests with a Retry-After header that provides the date and number of delay seconds.
For the Organization service, the response will include the TimeSpan value in the OrganizationServiceFault error details.
All other options are incorrect.
For more information about the Dataverse service protection API limits, please visit the below URLs:
Sure, I'd be happy to provide a detailed explanation!
The Dataverse API has certain limits in place to prevent abuse or overuse of its services. These limits are based on several different measures, which include:
A. Number of concurrent requests: This refers to the number of requests that are currently being processed by the API at the same time. If too many requests are made simultaneously, it can overload the API and cause it to become slow or unresponsive.
B. Number of batch requests: This refers to the number of requests that are grouped together into a single batch request. Batch requests can be more efficient than individual requests, but if too many requests are grouped together, it can cause the API to become overloaded.
C. Execution time: This refers to the amount of time it takes for a request to be processed by the API. If a request takes too long to process, it can tie up system resources and prevent other requests from being processed.
D. Number of retries: This refers to the number of times a request is retried if it fails due to an error or timeout. If too many retries are attempted, it can put unnecessary strain on the API.
E. Average execution time of the request: This refers to the average amount of time it takes for a request to be processed by the API over a certain period of time. If the average execution time is too high, it can indicate that the API is becoming overloaded and needs to be scaled up.
F. Number of requests: This refers to the total number of requests that are made to the API over a certain period of time. If too many requests are made within a short amount of time, it can overload the API and cause it to become slow or unresponsive.
To handle service protection API limit errors in your code, you would need to implement error handling code that is specific to each of these measures. For example, if you receive an error message indicating that the limit on the number of concurrent requests has been reached, you would need to wait until some of the current requests have been processed before making additional requests. If you receive an error message indicating that the limit on the number of retries has been reached, you may need to adjust your retry logic or implement a backoff strategy to avoid overloading the API.
