MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 Amazon SageMaker to deploy a model for real-time inference. They want to perform A/B testing between two model versions. Which TWO actions should the company take to set up A/B testing? (Choose TWO.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create an endpoint configuration with multiple production variants, each with a different model.
Option A is correct because in SageMaker, A/B testing between two model versions is achieved by creating an endpoint configuration with multiple production variants, each pointing to a different model. This allows the endpoint to host both models simultaneously and route traffic between them based on assigned weights.
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.
✓
Create an endpoint configuration with multiple production variants, each with a different model.
Why this is correct
Production variants allow multiple models on the same endpoint.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use Amazon CloudWatch Evidently to split traffic between models.
Why it's wrong here
SageMaker endpoints have built-in traffic splitting; Evidently is not used.
✓
Set the initial weight of each production variant to the desired traffic split.
Why this is correct
Weights determine the proportion of traffic each variant receives.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable auto scaling for each production variant individually.
Why it's wrong here
Auto scaling is not necessary for A/B testing setup.
✗
Set the second production variant's weight to 0 and update later to 100.
Why it's wrong here
That would send no traffic to the second variant initially, not a proper A/B test.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse the separate service Amazon CloudWatch Evidently with SageMaker's native traffic splitting, or think that auto scaling or zero-weight strategies are prerequisites for A/B testing.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker uses the `ProductionVariant` list in the endpoint configuration, where each variant has a `ModelName` and an `InitialVariantWeight`. The weights are normalized to determine the proportion of inference requests each variant receives. In a real-world scenario, you might start with a 90/10 split for a new model version, monitor metrics like latency and error rates, then gradually shift traffic using the `UpdateEndpointWeightsAndCapacities` API.
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.
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an endpoint configuration with multiple production variants, each with a different model. — Option A is correct because in SageMaker, A/B testing between two model versions is achieved by creating an endpoint configuration with multiple production variants, each pointing to a different model. This allows the endpoint to host both models simultaneously and route traffic between them based on assigned weights.
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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Question Discussion
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