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MLA-C01 Practice Question: A team deploys a PyTorch model on Amazon…
A team deploys a PyTorch model on Amazon SageMaker for real-time inference. They notice that inference latency is higher than expected. They suspect the serialization format used for input data is inefficient. Which approach would MOST likely reduce latency?
⚠ Common exam trap
Many candidates confuse throughput improvements (scaling, larger instances) with latency reduction, or mistakenly think Batch Transform can substitute for real-time inference, when the question specifically targets the serialization format as the suspected bottleneck.
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 input serialization format to Protocol Buffers.
Protocol Buffers (protobuf) are a binary serialization format that is significantly more compact and faster to parse than text-based formats like JSON or CSV. By reducing the size of the input data and the CPU overhead of deserialization, switching to protobuf directly addresses the root cause of high inference latency on SageMaker real-time endpoints.
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 Amazon SageMaker Batch Transform instead of real-time inference.
Why it's wrong here
Batch transform is for offline predictions, not real-time.
- ✓
Change the input serialization format to Protocol Buffers.
Why this is correct
Protocol Buffers reduce serialization time compared to JSON/CSV.
- ✗
Enable automatic scaling on the endpoint.
Why it's wrong here
Scaling helps with throughput, not per-request latency.
- ✗
Increase the instance type to a compute-optimized instance.
Why it's wrong here
This may help compute but not serialization overhead.
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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.