MLS-C01 Modeling Practice Question
A company uses SageMaker to deploy a model for real-time inference. The model is a large ensemble that requires 8 GB of memory and has high latency. The team wants to reduce latency without increasing cost. Which strategy is most 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
✓
Use SageMaker Neo to compile the model for the target instance.
SageMaker Neo compiles and optimizes the model for the target hardware, reducing latency and memory footprint without increasing cost. Option A is wrong because a larger instance would increase cost. Option B is wrong because deploying on multiple instances increases cost and complexity without necessarily reducing latency. Option D is wrong because batch transform is for offline inference, not real-time, and does not address the low latency requirement.
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 a larger instance type with more memory.
Why it's wrong here
Larger instances increase cost.
- ✗
Deploy the model on multiple instances behind a load balancer.
Why it's wrong here
Multiple instances increase cost.
- ✓
Use SageMaker Neo to compile the model for the target instance.
Why this is correct
Neo optimizes model for faster inference without additional cost.
- ✗
Switch from real-time inference to batch transform.
Why it's wrong here
Batch transform is not suitable for real-time inference.
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