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MLA-C01 Practice Question: A company uses Amazon SageMaker Pipelines for…
A company uses Amazon SageMaker Pipelines for automated retraining. The pipeline includes a processing step that runs a Python script. The script uses the boto3 library to call an AWS service, but the calls are being throttled. What is the MOST effective way to address this within the pipeline?
⚠ Common exam trap
Test-takers frequently confuse infrastructure-level scaling (increasing instance count) with application-level retry logic, assuming more instances will reduce API call frequency, when in fact each instance independently makes the same number of calls and can still be throttled.
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
✓
Modify the Python script to include retry with exponential backoff when receiving throttling exceptions.
Implementing retry with exponential backoff directly in the Python script is the most effective way to handle transient throttling exceptions from AWS service API calls. This approach is a best practice for managing service limits within a SageMaker Pipeline processing step, as it allows the script to automatically recover from throttling without modifying the pipeline structure or requiring manual intervention.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the instance count for the processing step to distribute the API calls.
Why it's wrong here
Throttling is per account, not per instance.
- ✓
Modify the Python script to include retry with exponential backoff when receiving throttling exceptions.
Why this is correct
Standard best practice for handling API throttling.
- ✗
Request a service quota increase for the throttling limit.
Why it's wrong here
May help but not immediate; also not limited to the pipeline.
- ✗
Add a wait step in the pipeline before the processing step.
Why it's wrong here
Does not address throttling during the script execution.
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