- A
Create a CloudWatch alarm on the 4XXError metric with a threshold of 10 and an evaluation period of 5 minutes, and configure SNS notification
Correct metric, threshold, and action.
- B
Create a CloudWatch alarm on the Invocations metric and set a threshold
Why wrong: Invocations count total requests, not errors.
- C
Enable endpoint auto-scaling with a target tracking policy
Why wrong: Auto-scaling handles load, not error alerting.
- D
Use SageMaker Model Monitor to capture invocations and trigger an SNS topic
Why wrong: Model Monitor does not provide real-time error alerting.
Question 782 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company deploys a real-time inference endpoint and wants to be alerted if the number of 4XX errors exceeds 10 per minute over a 5-minute period. Which steps should they take?
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
✓
Create a CloudWatch alarm on the 4XXError metric with a threshold of 10 and an evaluation period of 5 minutes, and configure SNS notification
Option A is correct because a CloudWatch alarm on the `4XXError` metric with a threshold of 10 and an evaluation period of 5 minutes directly monitors the rate of HTTP 4XX errors from the SageMaker real-time inference endpoint. When the alarm state transitions to ALARM (i.e., the average 4XX errors per minute exceeds 10 over the 5-minute window), it triggers an SNS notification to alert the team. This is the standard approach for real-time metric-based alerting in AWS.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a CloudWatch alarm on the 4XXError metric with a threshold of 10 and an evaluation period of 5 minutes, and configure SNS notification
Why this is correct
Correct metric, threshold, and action.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a CloudWatch alarm on the Invocations metric and set a threshold
Why it's wrong here
Invocations count total requests, not errors.
- ✗
Enable endpoint auto-scaling with a target tracking policy
Why it's wrong here
Auto-scaling handles load, not error alerting.
- ✗
Use SageMaker Model Monitor to capture invocations and trigger an SNS topic
Why it's wrong here
Model Monitor does not provide real-time error alerting.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse metric-based alerting (CloudWatch alarms on `4XXError`) with monitoring services (Model Monitor) or scaling mechanisms (auto-scaling), leading them to pick options that address different operational concerns.
Detailed technical explanation
How to think about this question
The `4XXError` metric in CloudWatch for SageMaker endpoints is emitted per-minute and represents the sum of HTTP 4XX responses (e.g., 400, 403, 404). When setting the alarm, the evaluation period of 5 minutes with a threshold of 10 means CloudWatch evaluates the average of the metric over 5 consecutive data points (each 1-minute period) — if the average exceeds 10, the alarm triggers. A subtle behavior: if the metric is sparse (e.g., no invocations in a minute), CloudWatch treats missing data as 'not breaching' by default, which can mask transient spikes unless you configure missing data treatment to 'breaching'.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a CloudWatch alarm on the 4XXError metric with a threshold of 10 and an evaluation period of 5 minutes, and configure SNS notification — Option A is correct because a CloudWatch alarm on the `4XXError` metric with a threshold of 10 and an evaluation period of 5 minutes directly monitors the rate of HTTP 4XX errors from the SageMaker real-time inference endpoint. When the alarm state transitions to ALARM (i.e., the average 4XX errors per minute exceeds 10 over the 5-minute window), it triggers an SNS notification to alert the team. This is the standard approach for real-time metric-based alerting in AWS.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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