MLS-C01 Practice Question: Machine Learning Implementation and Operations
Exhibit
Refer to the exhibit. ``` [Container] 2022/08/10 12:00:00 Starting inference server [Container] 2022/08/10 12:00:05 Model server started [Container] 2022/08/10 12:00:10 Invoking /invocations endpoint [Container] 2022/08/10 12:00:15 ERROR: Exception during prediction: OutOfMemoryError [Container] 2022/08/10 12:00:16 Shutting down ```
Refer to the exhibit. A SageMaker endpoint is returning 5xx errors. The logs show the above error. Which change will most likely resolve the issue?
⚠ Common exam trap
The MLS-C01 exam often tests the misconception that Auto Scaling or batch size adjustments can fix resource exhaustion errors, when in fact only vertical scaling (larger instance) addresses the root cause of insufficient memory per instance.
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 a larger instance type with more memory
5xx errors from a SageMaker endpoint typically indicate that the inference container is running out of memory (OOM) or crashing under load. The error log suggests the model or inference process requires more memory than the current instance type provides. Upgrading to a larger instance type with more memory directly addresses the resource exhaustion, allowing the model to load and inference to complete without failure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the batch size in the inference script
Why it's wrong here
Inference typically handles one request at a time.
- ✗
Enable Auto Scaling on the endpoint
Why it's wrong here
AutoScaling adds instances but does not increase per-instance memory.
- ✗
Compress the model artifact
Why it's wrong here
Model size not the issue; runtime memory is.
- ✓
Use a larger instance type with more memory
Why this is correct
More memory solves OutOfMemoryError.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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