How to Avoid Third-Party Rate-Limiting Errors in AWS Lambda?

A company uses an AWS Lambda function to call a third-party service. The third-party service has a limit of requests each minute. If the number of requests exceeds the limit, the third-party service returns rate-limiting errors. A developer needs to configure the Lambda function to avoid receiving rate limiting errors from the third-party service. Which solution will meet these requirements?

  1. Set the reserved concurrency on the Lambda function to match the number of concurrent requests that the third-party service allows. Source Reference Answer
  2. Decrease the memory that is allocated to the Lambda function.
  3. Set the provisioned concurrency on the Lambda function to match the number of concurrent requests that the third-party service allows.
  4. Increase the timeout value that is specified on the Lambda function.

Community Votes

A
100%

100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.

Community Insight

This question tests your understanding of AWS Lambda concurrency controls and the common trap is confusing reserved concurrency with provisioned concurrency.

Learn how to prevent rate-limiting errors from third-party services in AWS Lambda by using reserved concurrency. The community agrees that setting reserved concurrency to match the vendor's request limit is the correct solution.

Choosing C (Provisioned concurrency) is the most common mistake because it also deals with concurrency, but provisioned concurrency only keeps environments warm and does not limit the maximum number of concurrent executions.

Community Discussion (4 comments)

DeaconStJohn 👍 8 Selected: A
Correct answer is A. This will limit the lambda function to a defined concurrency which can be set to match the third party vendor limits. B - will lower the cpu of the function, not limit the invocations. C - Provisioned concurrency is a minimum value to keep lambda function execution environments on warm standby for critical workloads. D - Issue isn't with timeouts or lack of processing power
KarBiswa 👍 5 Selected: A
https://docs.aws.amazon.com/lambda/latest/dg/provisioned-concurrency.html
65703c1 👍 1 Selected: A
A is the correct answer.
KarBiswa 👍 1 Selected: D
https://docs.aws.amazon.com/lambda/latest/dg/provisioned-concurrency.html

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Expert Analysis

Why the Answer Is Correct

Reserved concurrency sets a hard limit on the number of concurrent executions for a Lambda function. By configuring reserved concurrency to match the third-party service's allowed requests per minute, you ensure that Lambda never invokes more concurrent instances than the vendor can handle, thereby avoiding rate-limiting errors. This is a straightforward and effective throttling mechanism.

Why the Other Options Are Wrong

Option B (decrease memory) affects CPU and performance, not invocation concurrency, so it does nothing to limit requests. Option C (provisioned concurrency) is designed to keep instances warm and reduce cold starts; it does not cap the maximum concurrency and can actually increase the number of concurrent executions. Option D (increase timeout) gives the function more time to run but does not prevent it from being invoked too frequently. Therefore, only A directly addresses the rate limit.

Community Comment Notes

Comment [1] clearly explains why A is correct and dismisses B, C, and D with valid reasoning: B lowers CPU, C is for warm standby, and D is unrelated to timeouts. Comment [2] provides a useful reference to AWS provisioned concurrency docs, but that link actually supports why C is wrong. The consensus (93 votes for A) strongly reinforces reserved concurrency as the standard solution for controlling concurrency against external API limits.

Official Reference

Exam Strategy

For AWS Lambda questions involving rate limits or throttling from downstream services, always look for reserved concurrency as the correct control. Remember that provisioned concurrency is about performance (cold starts), not limiting concurrency, so avoid that trap.

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