Question 41 of 835
mediumMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A machine learning engineer sees the above error…
Exhibit
Refer to the exhibit.
CloudWatch Logs excerpt:
```
2024-09-21T14:22:10Z ERROR - Model endpoint 'fraud-model-v2' returned unexpected response: {"prediction": 0.95}. Expected format: {"predictions": [{"score": 0.95}]}. Check inference code and response structure.
```A machine learning engineer sees the above error in Amazon CloudWatch Logs for a SageMaker endpoint. What is the most likely cause?
⚠ Common exam trap
Many candidates confuse data capture configuration (which only logs payloads) with the actual response format validation performed by the SageMaker endpoint proxy, leading them to incorrectly select Option B.
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 inference code in the Docker container outputs a different response format than expected by the endpoint.
The error in CloudWatch Logs indicates that the SageMaker endpoint received a response from the inference container that does not match the expected format. SageMaker endpoints require the container to output a response body in a specific format (e.g., JSON or CSV) as defined by the model's Accept header or the endpoint's serialization configuration. If the inference code returns a malformed or unexpected response (e.g., raw bytes, incorrect JSON structure, or missing fields), the endpoint will fail to parse it and log an error. This is the most direct cause of the observed error.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model file is corrupted during deployment.
Why it's wrong here
Corruption would likely cause a different error (e.g., model load failure) or incorrect predictions, not a schema mismatch.
- ✗
The data capture configuration is incorrectly set to capture only the response body.
Why it's wrong here
Data capture logs are separate; this log is from the endpoint itself, not from data capture.
- ✓
The inference code in the Docker container outputs a different response format than expected by the endpoint.
Why this is correct
The inference script (e.g., in a SageMaker inference container) must output the exact JSON structure the endpoint expects. This error shows a mismatch.
- ✗
The endpoint is overloaded and dropping requests.
Why it's wrong here
Overload would produce 5xx or timeout errors, not a response structure error.
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Last reviewed: Jul 4, 2026
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