- A
Amazon CloudWatch Logs to store inference logs and create a metric filter.
Why wrong: Metric filters on logs can create alarms, but the scenario requires custom metrics, not logs.
- B
Amazon CloudWatch to publish custom metrics and create an alarm, and AWS Lambda to process images and publish metrics.
Lambda can publish custom metrics to CloudWatch, which can trigger alarms.
- C
AWS Config to track resource changes and trigger an SNS notification.
Why wrong: Config is for resource configuration changes.
- D
Amazon Simple Notification Service (SNS) to send alerts when threshold is exceeded.
Why wrong: SNS is a notification service, not a monitoring service.
Question 554 of 1,000
Monitoring Amazon Rekognition Flagged Images with CloudWatch
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance and security. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 uses Amazon Rekognition to moderate user-generated images. They want to set up a monitoring system that alerts the team if the number of inappropriate images flagged by the model exceeds a threshold. Which combination of AWS services should they use?
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
✓
Amazon CloudWatch to publish custom metrics and create an alarm, and AWS Lambda to process images and publish metrics.
Option B is correct because Amazon Rekognition can be integrated with AWS Lambda to process images and publish custom metrics to Amazon CloudWatch. CloudWatch can then create an alarm based on a threshold for the number of inappropriate images flagged, and trigger an SNS notification to alert the team. This combination provides a complete monitoring and alerting pipeline without relying on inference logs or resource configuration changes.
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.
- ✗
Amazon CloudWatch Logs to store inference logs and create a metric filter.
Why it's wrong here
Metric filters on logs can create alarms, but the scenario requires custom metrics, not logs.
- ✓
Amazon CloudWatch to publish custom metrics and create an alarm, and AWS Lambda to process images and publish metrics.
Why this is correct
Lambda can publish custom metrics to CloudWatch, which can trigger alarms.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Config to track resource changes and trigger an SNS notification.
Why it's wrong here
Config is for resource configuration changes.
- ✗
Amazon Simple Notification Service (SNS) to send alerts when threshold is exceeded.
Why it's wrong here
SNS is a notification service, not a monitoring service.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Config (which tracks infrastructure changes) with monitoring model outputs, or assume CloudWatch Logs metric filters can directly capture Rekognition inference results without custom logging logic.
Trap categories for this question
Scenario analysis trap
Metric filters on logs can create alarms, but the scenario requires custom metrics, not logs.
Detailed technical explanation
How to think about this question
Under the hood, Rekognition's DetectModerationLabels API returns a list of labels with confidence scores; a Lambda function can parse these results, count images with labels above a certain confidence threshold (e.g., Explicit Nudity > 90%), and publish a custom metric to CloudWatch using the put_metric_data API. CloudWatch Alarms evaluate the metric over a specified period (e.g., 5 minutes) and transition to ALARM state when the threshold is breached, which then triggers an SNS topic to send email or SMS alerts. This pattern is commonly used in content moderation pipelines where real-time alerting is critical, such as social media platforms flagging offensive content.
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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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: Amazon CloudWatch to publish custom metrics and create an alarm, and AWS Lambda to process images and publish metrics. — Option B is correct because Amazon Rekognition can be integrated with AWS Lambda to process images and publish custom metrics to Amazon CloudWatch. CloudWatch can then create an alarm based on a threshold for the number of inappropriate images flagged, and trigger an SNS notification to alert the team. This combination provides a complete monitoring and alerting pipeline without relying on inference logs or resource configuration changes.
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.
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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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