AZ-204 Practice Question: Connect to and consume Azure services and third-party services
A company uses Azure Logic Apps to integrate with a third-party REST API. The API has a rate limit of 100 requests per minute. You need to ensure that the Logic App respects this limit. Which connector feature should you configure?
⚠ Common exam trap
Candidates often confuse Retry policy (which handles failures after they occur) with concurrency control (which prevents the failures by limiting parallelism), leading them to select Retry policy as a proactive solution when it is actually reactive.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Concurrency control.
Concurrency control in Azure Logic Apps allows you to limit the number of concurrent workflow instances (when applied to the trigger) or parallel iterations (when applied to a 'For each' loop). By configuring this setting, you can proactively manage the rate at which requests are sent to an external API, helping to prevent exceeding rate limits. For example, if each Logic App run makes one API call, setting the concurrency limit on the trigger to a value that aligns with the rate limit (e.g., 100, if runs are short and the trigger fires frequently) can help throttle the overall request volume by queuing additional runs. This proactively manages the request volume, unlike a retry policy which reacts to failures.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Retry policy.
Why it's wrong here
A retry policy in Azure Logic Apps is designed to re-execute an action after a transient failure, such as a temporary network issue or service unavailability. While it can eventually succeed if a rate limit is temporary, it does not proactively prevent hitting the rate limit in the first place. Instead, it reacts to failures, potentially exacerbating the rate limit issue by sending more requests in a short period rather than controlling the initial outbound flow.
- ✓
Concurrency control.
Why this is correct
Concurrency control in Azure Logic Apps allows developers to limit the number of workflow instances or loop iterations that can run simultaneously for a specific trigger or action. By setting a maximum concurrent run limit, the Logic App proactively throttles its own outbound requests, preventing it from overwhelming a downstream API. This mechanism directly helps in adhering to external service rate limits by controlling the rate of outgoing calls.
- ✗
Swagger connector.
Why it's wrong here
A Swagger connector, now commonly referred to as an OpenAPI connector, in Logic Apps is primarily used to integrate with custom APIs by importing their OpenAPI definition. This definition describes the API's operations, parameters, and expected responses, enabling Logic Apps to understand how to interact with the API. It serves purely as a mechanism for API integration and definition, providing no inherent functionality for controlling or limiting the rate of requests sent to that API.
- ✗
API Management.
Why it's wrong here
Azure API Management (APIM) is a powerful, standalone Azure service designed for publishing, securing, transforming, and monitoring APIs, and it offers robust rate limiting and throttling capabilities. However, it is an external service that would sit in front of the third-party API, not an internal mechanism within the Logic App itself. While a Logic App could call an API exposed through APIM, the question implies a need for the Logic App's own built-in mechanism to manage its outbound call rate, for which APIM is an external and often more complex solution.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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