- A
Concept drift (change in the relationship between features and target)
Why wrong: Concept drift is not directly detected by Model Monitor; it is inferred from model quality drift.
- B
Data quality drift (schema and statistical drift)
Model Monitor can detect schema violations and statistical distribution changes.
- C
Model quality drift (performance degradation against ground truth)
Model quality drift is detected when ground truth labels become available.
- D
Bias drift (change in bias metrics over time)
Why wrong: Bias drift monitoring requires SageMaker Clarify, not Model Monitor alone.
- E
Feature attribution drift (SHAP values)
Why wrong: Feature attribution drift requires Clarify's explainability monitoring.
Question 171 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses SageMaker Model Monitor to detect data drift in production. The monitoring job compares the current data distribution to a baseline. Which TWO types of drift can SageMaker Model Monitor detect? (Select TWO)
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
✓
Data quality drift (schema and statistical drift)
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Concept drift (change in the relationship between features and target)
Why it's wrong here
Concept drift is not directly detected by Model Monitor; it is inferred from model quality drift.
- ✓
Data quality drift (schema and statistical drift)
Why this is correct
Model Monitor can detect schema violations and statistical distribution changes.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Model quality drift (performance degradation against ground truth)
Why this is correct
Model quality drift is detected when ground truth labels become available.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Bias drift (change in bias metrics over time)
Why it's wrong here
Bias drift monitoring requires SageMaker Clarify, not Model Monitor alone.
- ✗
Feature attribution drift (SHAP values)
Why it's wrong here
Feature attribution drift requires Clarify's explainability monitoring.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Data quality drift (schema and statistical drift)
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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