hardMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A financial services company uses a custom…
A financial services company uses a custom container on Amazon SageMaker to serve a fraud detection model. The model's inference latency has recently increased, causing timeouts for some requests. The team reviews the SageMaker logs and finds that the container is consuming more memory than allocated. What should the team do to maintain service quality while ensuring cost-effectiveness?
⚠ Common exam trap
Many exam-takers confuse scaling out (adding instances) with scaling up (choosing a larger instance type), and they may incorrectly assume that auto-scaling based on memory utilization will prevent timeouts, when in fact it only reacts after the problem occurs.
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
✓
Change the instance type to a memory-optimized instance, such as r5.large
The root cause is that the container is consuming more memory than allocated, leading to increased latency and timeouts. Switching to a memory-optimized instance like r5.large directly addresses the memory constraint by providing more memory per vCPU, which resolves the performance issue without over-provisioning compute resources. This approach is cost-effective because it targets the specific bottleneck (memory) rather than scaling out or changing unrelated parameters.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Decrease the model's batch size to reduce memory usage
Why it's wrong here
Decreasing batch size may reduce throughput and not solve the memory issue if it's due to model size.
- ✗
Increase the number of instances in the endpoint to distribute the load
Why it's wrong here
Adding instances spreads load but doesn't fix per-instance memory shortage.
- ✗
Implement an auto-scaling policy based on memory utilization
Why it's wrong here
Auto-scaling adds instances but each still has insufficient memory.
- ✓
Change the instance type to a memory-optimized instance, such as r5.large
Why this is correct
Switching to a memory-optimized instance provides more memory per instance, resolving the issue cost-effectively.
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JA
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.