MLS-C01 Practice Question: Machine Learning Implementation and Operations
A machine learning engineer is deploying a model using AWS Lambda for real-time inference. The model is a scikit-learn RandomForestClassifier with 100 trees, serialized as a pickle file of 150 MB. The Lambda function has 3 GB memory allocated. However, the inference requests are timing out after 30 seconds. What is the most likely cause?
⚠ Common exam trap
The MLS-C01 exam often tests the misconception that Lambda timeouts are always the root cause of slow inference, when in fact the real issue is inefficient resource initialization (like loading large models from S3 on every call) that can be fixed by architectural changes rather than simply increasing the timeout.
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
✓
The model is loaded from S3 on every invocation, causing high latency.
The default behavior of loading a model from S3 on every Lambda invocation introduces significant latency. Each invocation must download the 150 MB pickle file from S3 over the network, deserialize it, and then run inference, which easily exceeds the 30-second timeout. The model should be loaded once outside the handler (in global scope) and reused across invocations to avoid this overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
scikit-learn is not compatible with AWS Lambda.
Why it's wrong here
scikit-learn is compatible if included in the deployment package or layer.
- ✗
The Lambda function does not have enough memory to load the model.
Why it's wrong here
3 GB is more than enough for 150 MB model.
- ✓
The model is loaded from S3 on every invocation, causing high latency.
Why this is correct
Lambda should load the model outside the handler to reuse across invocations, but even then, cold starts with a large model are slow.
- ✗
The Lambda function timeout is set too low; increase it to 5 minutes.
Why it's wrong here
Increasing timeout may help, but loading a 150 MB model each time is the root cause.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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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.