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MLA-C01 Practice Question: An e-commerce company uses Amazon SageMaker to…
An e-commerce company uses Amazon SageMaker to deploy a real-time inference endpoint for product recommendations. The endpoint receives bursty traffic, with occasional spikes. The company wants to minimize cost while ensuring that latency remains under 100 ms. Which approach should the company take?
⚠ Common exam trap
Candidates often confuse latency optimization techniques (like elastic inference) with scaling strategies, overlooking that bursty traffic requires dynamic scaling with warm-up to prevent cold-start latency spikes.
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
✓
Deploy the model on a multi-model endpoint with automatic scaling and configure a warm-up period for new instances.
A multi-model endpoint with automatic scaling allows multiple models to share a single endpoint, reducing cost while handling bursty traffic. Configuring a warm-up period ensures new instances are fully initialized before receiving traffic, preventing cold-start latency spikes and keeping inference under 100 ms.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use an elastic inference accelerator to reduce latency instead of scaling.
Why it's wrong here
Elastic Inference reduces latency for deep learning but does not directly address traffic bursts.
- ✗
Use a scheduled scaling plan based on historical traffic patterns.
Why it's wrong here
Scheduled scaling does not react to unpredictable spikes.
- ✗
Deploy the model on one large instance to handle peak load.
Why it's wrong here
Over-provisioning leads to high cost during low traffic.
- ✓
Deploy the model on a multi-model endpoint with automatic scaling and configure a warm-up period for new instances.
Why this is correct
Multi-model endpoint with scaling and warm-up can handle bursts cost-effectively.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.