hardMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A team is deploying a deep learning model on a…
A team is deploying a deep learning model on a SageMaker real-time endpoint. The model has high memory requirements, and the team wants to minimize instance cost while ensuring the endpoint can handle up to 10 concurrent requests. They plan to use a single ml.p3.2xlarge instance (8 vCPUs, 61 GB memory). Which SageMaker endpoint configuration will allow the endpoint to handle 10 concurrent requests without errors?
⚠ Common exam trap
Many exam-takers confuse concurrency mechanisms: candidates often think increasing instance count (Option D) is the only way to handle concurrent requests, but SageMaker's ModelServerWorkers allow a single instance to serve multiple requests in parallel, which is more cost-effective.
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
✓
Set the initial instance count to 1 and configure the container to use multiple ModelServerWorkers.
SageMaker's ModelServerWorkers (MSWs) allow a single container to handle multiple inference requests concurrently by running multiple worker processes. With 8 vCPUs on ml.p3.2xlarge, configuring multiple MSWs (e.g., 8 workers) enables the endpoint to process up to 10 concurrent requests without errors, as each worker can handle one request at a time. This minimizes cost by using a single instance while meeting concurrency requirements.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Disable ModelServerWorkers to reduce overhead.
Why it's wrong here
Disabling workers forces single-threaded inference, reducing concurrency to 1.
- ✓
Set the initial instance count to 1 and configure the container to use multiple ModelServerWorkers.
Why this is correct
Multiple workers allow the instance to handle multiple requests concurrently, up to the CPU/memory limit.
- ✗
Set the initial variant weight to 10.
Why it's wrong here
Variant weight distributes traffic, not concurrency; it doesn't increase capacity.
- ✗
Set the initial instance count to 10 in the production variant.
Why it's wrong here
This creates 10 instances, which is over-provisioned and costly for only 10 concurrent requests.
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Written by Johnson Ajibi, MSc IT Security
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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.