MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company has deployed a real-time inference endpoint using SageMaker. The endpoint latency is within acceptable limits, but the team notices that the Invocations metric shows occasional spikes. They want to investigate the source of the spikes. Which CloudWatch metric should they examine to isolate the time spent in SageMaker overhead versus model inference?
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
✓
Both ModelLatency and OverheadLatency
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
OverheadLatency
Why it's wrong here
OverheadLatency measures only SageMaker infrastructure overhead.
- ✗
Latency
Why it's wrong here
Latency is the total endpoint latency, but does not break down into model vs overhead.
- ✓
Both ModelLatency and OverheadLatency
Why this is correct
Comparing ModelLatency and OverheadLatency allows the team to determine whether the spike is due to model inference time or SageMaker infrastructure overhead.
- ✗
ModelLatency
Why it's wrong here
ModelLatency measures time spent in the model container only, not overhead.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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