MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
An ML engineer wants to be notified when the average inference latency of a SageMaker endpoint exceeds 500 ms for 2 consecutive evaluation periods. Which AWS service combination should they use?
⚠ Common exam trap
MLA-C01 often tests the confusion between Model Monitor (data/model quality) and CloudWatch (infrastructure metrics) — candidates who see 'SageMaker' and 'monitoring' pick Model Monitor, missing that latency is a CloudWatch metric.
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
✓
CloudWatch Alarm + SNS
CloudWatch Alarms evaluate metrics over specified periods and can trigger SNS notifications when a threshold is breached for a defined number of consecutive periods. SageMaker endpoints automatically publish inference latency metrics to CloudWatch, so an alarm on the latency metric with a 500 ms threshold and 2 evaluation periods, wired to an SNS topic, delivers exactly the required notification.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
CloudWatch Alarm + SNS
Why this is correct
CloudWatch publishes the endpoint's ModelLatency and OverheadLatency metrics; an alarm with two consecutive evaluation periods and a 500 ms threshold detects the breach, then triggers SNS to notify subscribers. This satisfies both the latency threshold and consecutive-period constraint.
- ✗
SageMaker Model Monitor + SNS
Why it's wrong here
Model Monitor detects data drift, bias and quality deviations in captured inference data; it does not evaluate endpoint latency metrics or consecutive periods. It would be correct for drift alerting. CloudWatch alarms on the latency metric, notifying via SNS, meet the 500 ms requirement.
- ✗
EventBridge + Lambda
Why it's wrong here
EventBridge reacts to state-change events, and SageMaker endpoint latency is a CloudWatch metric, not an event, so no rule fires on threshold breaches. EventBridge suits reacting to endpoint state changes or job completions. CloudWatch alarms with SNS handle consecutive-period metric thresholds directly.
- ✗
SageMaker Clarify + SNS
Why it's wrong here
Clarify detects bias and explains model predictions; it does not emit endpoint latency metrics, so it cannot trigger on 500 ms breaches. It would be chosen when auditing data or feature attribution. CloudWatch alarms on the latency metric with SNS notification satisfy the two-period condition.
Go deeper
Related to this question
About these practice questions
One of 665 original MLA-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This MLA-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 MLA-C01 exam.