What is the MOST operationally efficient way to refactor the server less application to accommodate this change?

A developer migrated a legacy application to an AWS Lambda function. The function uses a third-party service to pull data with a series of API calls at the end of each month. The function than processes the data to generate the monthly reports. The function has Been working with no issues so far.

The third-party service recently issued a restriction to allow a feed number to API calls each minute and each day. If the API calls exceed the limit tor each minute or each day, then the service will produce errors. The API also provides the minute limit and daily limit in the response header. This restriction might extend the overall process to multiple days because the process is consuming more API calls than the available limit.

What is the MOST operationally efficient way to refactor the server less application to accommodate this change?
A . Use an AWS Step Functions State machine to monitor API failures. Use the Wait state to delay calling the Lambda function.
B . Use an Amazon Simple Queue Service (Amazon SQS) queue to hold the API calls. Configure the Lambda function to poll the queue within the API threshold limits.
C . Use an Amazon CloudWatch Logs metric to count the number of API calls. Configure an Amazon CloudWatch alarm flat slops the currently running instance of the Lambda function when the metric exceeds the API threshold limits.
D . Use Amazon Kinesis Data Firehose to batch me API calls and deliver them to an Amazon S3 bucket win an event notification to invoke the Lambda function.

View Answer

Answer: A

Explanation:

The solution that will meet the requirements is to use an AWS Step Functions state machine to monitor API failures. Use the Wait state to delay calling the Lambda function. This way, the developer can refactor the serverless application to accommodate the change in a way that is automated and scalable. The developer can use Step Functions to orchestrate the Lambda function and handle any errors or retries. The developer can also use the Wait state to pause the execution for a specified duration or until a specified timestamp, which can help avoid exceeding the API limits. The other options either involve using additional services that are not necessary or appropriate for this scenario, or do not address the issue of API failures.

Reference: AWS Step Functions Wait state