MLS-C01 Modeling Practice Question
A company is using Amazon SageMaker to deploy a model for real-time inference. The model requires 500 MB of memory and has a latency requirement of 100 ms. The endpoint is receiving 10 requests per second. Which instance type should be chosen for cost-effectiveness?
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
✓
ml.m5.large
Ml.m5.large (Option C). This instance type provides 2 vCPU and 8 GB memory, which is more than sufficient for the 500 MB memory requirement. It also offers consistent performance suitable for real-time inference with 10 requests per second and 100 ms latency. Option A (ml.c5.xlarge) has 4 vCPU and 8 GB, which is over-provisioned and more expensive. Option B (ml.t2.medium) has only 4 GB memory but uses burstable CPU, which may cause latency spikes. Option D (ml.p3.2xlarge) is GPU-optimized and significantly more expensive, making it unsuitable for a CPU-bound workload. Therefore, ml.m5.large is the most cost-effective choice.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
ml.c5.xlarge
Why it's wrong here
More expensive than needed.
- ✗
ml.t2.medium
Why it's wrong here
Burstable CPU may cause latency spikes.
- ✓
ml.m5.large
Why this is correct
Adequate memory and cost-effective.
- ✗
ml.p3.2xlarge
Why it's wrong here
GPU not needed, expensive.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.