- A
Manually deploy the approved model using the SageMaker console
Why wrong: Manual deployment is not automatic and is error-prone.
- B
Use AWS Lambda to update the endpoint whenever a new model version is created
Why wrong: Lambda would need to check approval status and can become complex; not best practice.
- C
Create a SageMaker Pipeline that includes a model approval step and deployment step
SageMaker Pipelines can model the entire workflow including conditional deployment based on approval.
- D
Schedule a CloudWatch Event to invoke a SageMaker update endpoint API daily
Why wrong: This would not consider approval status and may deploy unapproved models.
Question 52 of 1,000
mediumMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: Using SageMaker Model Registry to manage model…
This MLA-C01 practice question tests your understanding of mla-c01 exam topics. 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 is using SageMaker Model Registry to manage model versions. They want to automatically deploy the latest approved model to production after retraining. Which approach is best?
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
✓
Create a SageMaker Pipeline that includes a model approval step and deployment step
Option C is correct because a SageMaker Pipeline can orchestrate the entire workflow from retraining to deployment, including a model approval step that gates deployment to production only when the model is approved. This automates the process end-to-end, ensuring that only approved models are deployed, which aligns with the requirement to automatically deploy the latest approved model after retraining.
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.
- ✗
Manually deploy the approved model using the SageMaker console
Why it's wrong here
Manual deployment is not automatic and is error-prone.
- ✗
Use AWS Lambda to update the endpoint whenever a new model version is created
Why it's wrong here
Lambda would need to check approval status and can become complex; not best practice.
- ✓
Create a SageMaker Pipeline that includes a model approval step and deployment step
Why this is correct
SageMaker Pipelines can model the entire workflow including conditional deployment based on approval.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Schedule a CloudWatch Event to invoke a SageMaker update endpoint API daily
Why it's wrong here
This would not consider approval status and may deploy unapproved models.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may choose Option B because it sounds automated, but they overlook the critical requirement for model approval before deployment, which Lambda alone cannot enforce without additional logic.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Pipeline uses a directed acyclic graph (DAG) of steps, where a Model Approval step can be implemented using a Lambda step or a custom step that checks the model version's approval status in the Model Registry. The deployment step then uses a CreateEndpointConfig and UpdateEndpoint API call to update the production endpoint only when the model is marked as 'Approved'. This ensures that the deployment is tightly coupled to the approval workflow, avoiding race conditions or manual errors.
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.
TExam Day Tips
- 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Create a SageMaker Pipeline that includes a model approval step and deployment step — Option C is correct because a SageMaker Pipeline can orchestrate the entire workflow from retraining to deployment, including a model approval step that gates deployment to production only when the model is approved. This automates the process end-to-end, ensuring that only approved models are deployed, which aligns with the requirement to automatically deploy the latest approved model after retraining.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 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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