- A
Retrain the model using the most recent week of data and redeploy to the endpoint
Why wrong: Retraining with recent data may incorporate the drifted distribution, but if the drift is due to a data pipeline error, retraining will not fix the underlying issue and could amplify errors.
- B
Investigate the data pipeline that feeds the training job to ensure consistent data collection and encoding of the 'product_category' feature
The first step should be to confirm that the data pipeline is not introducing errors. If the data is correct, then retraining might be appropriate.
- C
Rebuild the SageMaker endpoint with a different instance type to improve performance
Why wrong: The endpoint instance type affects latency and throughput, not model accuracy. This will not address data drift.
- D
Reduce the number of features in the model by removing 'product_category'
Why wrong: Removing an important feature without understanding the drift could degrade model performance further.
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 machine learning team at a retail company has deployed a product recommendation model using Amazon SageMaker. The model is updated weekly with new data. Recently, the team noticed that the model's accuracy on a holdout evaluation set has been declining over the past month. The data pipeline that feeds the training job has not changed. The team suspects data drift. They have SageMaker Model Monitor enabled on the inference endpoint and have set up Amazon CloudWatch metrics for feature distribution distances. Upon reviewing the CloudWatch dashboards, they see that the feature distribution distance metric for the most important feature 'product_category' has increased significantly. However, the team is unsure if this is the root cause. Which remediation step should the team take FIRST?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"first"Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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
Investigate the data pipeline that feeds the training job to ensure consistent data collection and encoding of the 'product_category' feature
Before retraining the model or deploying a new endpoint, the team should investigate the source of the data drift by checking the input data pipeline. The data pipeline might have introduced a systematic error, such as a change in how 'product_category' is encoded or collected. Option A (retrain the model with more recent data) might not help if the data itself is corrupted. Option B (reduce the number of features) could ignore the problem. Option D (rebuild the endpoint) would not address the data drift. Therefore, the first step is to investigate the data pipeline.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Retrain the model using the most recent week of data and redeploy to the endpoint
Why it's wrong here
Retraining with recent data may incorporate the drifted distribution, but if the drift is due to a data pipeline error, retraining will not fix the underlying issue and could amplify errors.
- ✓
Investigate the data pipeline that feeds the training job to ensure consistent data collection and encoding of the 'product_category' feature
Why this is correct
The first step should be to confirm that the data pipeline is not introducing errors. If the data is correct, then retraining might be appropriate.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Rebuild the SageMaker endpoint with a different instance type to improve performance
Why it's wrong here
The endpoint instance type affects latency and throughput, not model accuracy. This will not address data drift.
- ✗
Reduce the number of features in the model by removing 'product_category'
Why it's wrong here
Removing an important feature without understanding the drift could degrade model performance further.
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: Investigate the data pipeline that feeds the training job to ensure consistent data collection and encoding of the 'product_category' feature — Before retraining the model or deploying a new endpoint, the team should investigate the source of the data drift by checking the input data pipeline. The data pipeline might have introduced a systematic error, such as a change in how 'product_category' is encoded or collected. Option A (retrain the model with more recent data) might not help if the data itself is corrupted. Option B (reduce the number of features) could ignore the problem. Option D (rebuild the endpoint) would not address the data drift. Therefore, the first step is to investigate the data pipeline.
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.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 23, 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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