MLS-C01 Modeling Practice Question
A machine learning engineer is monitoring a deployed model on SageMaker and notices that the prediction latency is increasing over time. The model is a linear regression with a small number of features. Which is the MOST likely cause?
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 has a memory leak
Memory leak or accumulation of model artifacts in inference code can cause latency growth over time.
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 number of features is too large
Why it's wrong here
Features are small; linear regression is simple; latency should be constant.
- ✗
The CPU utilization is too low
Why it's wrong here
Low CPU would not cause increasing latency.
- ✗
The model is overfitting to recent data
Why it's wrong here
Overfitting affects accuracy, not latency.
- ✓
The inference code has a memory leak
Why this is correct
Memory leaks cause gradual performance degradation and increased latency.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.