mediumMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A company uses SageMaker Pipelines to automate…
A company uses SageMaker Pipelines to automate model retraining. The pipeline runs daily but sometimes fails due to data quality issues. What is the best design to handle this?
⚠ Common exam trap
Test-takers frequently confuse monitoring tools (Debugger) or model management (Model Registry) with pipeline orchestration and conditional logic, failing to recognize that a ConditionStep is the correct mechanism to gate execution based on data quality.
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
✓
Add a data quality check step with Conditional to skip training if data fails.
SageMaker Pipelines supports a data quality check step that can be integrated with a ConditionStep. If the data quality check fails, the ConditionStep can skip the training step entirely, preventing the pipeline from failing due to bad data. This design ensures the pipeline completes successfully (or exits gracefully) without wasting compute resources on training with invalid data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add a data quality check step with Conditional to skip training if data fails.
Why this is correct
A conditional step checks data quality and only proceeds to training if criteria are met, preventing failures.
- ✗
Use SageMaker Debugger to monitor training.
Why it's wrong here
Debugger monitors training metrics, but does not prevent failures due to bad data.
- ✗
Use SageMaker Model Registry to track model versions.
Why it's wrong here
Model Registry tracks versions but does not handle pipeline failures due to data quality.
- ✗
Increase the instance size for the training step.
Why it's wrong here
Increasing instance size may speed up training but does not address data quality issues.
Go deeper
Related to this question
About these practice questions
This MLA-C01 question is part of Courseiva's 835-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.