Free AWS DVA-C02 Actual Exam Questions - Question 2 Discussion
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?
It’s A because Step Functions can handle complex workflows and built-in wait states without extra infrastructure. Waiting inside Step Functions feels more straightforward than managing queue polling with SQS. Also, Step Functions can handle retries based on API failure responses dynamically, which fits this use case better than SQS or relying on CloudWatch alarms (C) which don’t directly control invocation pacing. Kinesis Data Firehose (D) doesn’t really apply here since you’re not batching for storage or analytics but need to control call rates in real time.
Maybe B works best here since SQS can naturally queue the API requests and Lambda can control the pace of processing to keep within rate limits. Step Functions might add complexity for simple rate throttling.
A/B? Step Functions (A) can orchestrate retries smoothly; SQS (B) might need extra handling for rate limits.
A/B? Using Step Functions with Wait states (A) seems cleaner for handling retries and pacing, while SQS (B) could help queue calls but might complicate rate-limiting logic. Both seem operationally viable.
It’s C. Lambda probs lacks write permissions to DynamoDB. That’s the usual suspect here.