- A
Azure Computer Vision
Why wrong: Computer Vision provides general image analysis; Face API is specifically optimized for face detection and recognition.
- B
Azure Face API
Face API detects and recognizes faces, identifies facial attributes (emotion, age), and matches faces to known individuals.
- C
Azure Custom Vision
Why wrong: Custom Vision builds custom image classifiers; Face API provides specialized face processing.
- D
Azure Video Analyzer
Why wrong: Video Analyzer processes video streams; Face API handles face detection and recognition in images.
Quick Answer
The answer is Azure Face API. This service is the correct choice because it is a dedicated cognitive service within Azure’s AI portfolio, purpose-built to detect human faces in images, analyze facial attributes like emotion (such as happiness, sadness, or surprise), and recognize specific individuals through face identification and verification against a pre-enrolled database. On the Microsoft Azure Fundamentals AZ-900 exam, this question tests your understanding of which Azure service handles specialized facial recognition tasks versus general-purpose image analysis services like Computer Vision. A common trap is confusing Azure Face API with Computer Vision, but remember: Computer Vision can detect faces and estimate age or emotion at a basic level, while Face API is the only service that offers person identification and enrollment. For the exam, a helpful memory tip is to think of “Face API” as the service that not only sees a face but knows *who* it is.
AZ-900 Describe Azure architecture and services Practice Question
This AZ-900 practice question tests your understanding of describe azure architecture and services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Which Azure service can detect faces in images and identify emotions, facial attributes, and recognize specific individuals?
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
Azure Face API
Azure Face API is the correct service because it is specifically designed to detect human faces in images, analyze facial attributes such as emotions (e.g., happiness, sadness), and recognize specific individuals through face identification and verification. Unlike general-purpose image analysis services, Face API provides dedicated facial recognition capabilities, including person identification against a pre-enrolled database.
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.
- ✗
Azure Computer Vision
Why it's wrong here
Computer Vision provides general image analysis; Face API is specifically optimized for face detection and recognition.
- ✓
Azure Face API
Why this is correct
Face API detects and recognizes faces, identifies facial attributes (emotion, age), and matches faces to known individuals.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Azure Custom Vision
Why it's wrong here
Custom Vision builds custom image classifiers; Face API provides specialized face processing.
- ✗
Azure Video Analyzer
Why it's wrong here
Video Analyzer processes video streams; Face API handles face detection and recognition in images.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Computer Vision (which can detect faces) with Azure Face API (which can recognize specific individuals and analyze emotions), leading them to select Computer Vision due to its broader name recognition.
Detailed technical explanation
How to think about this question
Azure Face API uses deep neural networks to extract face landmarks (e.g., eyes, nose, mouth) and returns attributes like age, gender, emotion, and head pose. It supports face identification by comparing a detected face against a PersonGroup, which is a collection of enrolled persons, using a confidence score threshold (typically 0.5–0.7). A real-world scenario is a security system that identifies employees entering a building by matching their face against a pre-registered database, triggering access control.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Questions learners often ask
What does this AZ-900 question test?
Describe Azure architecture and services — This question tests Describe Azure architecture and services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Face API — Azure Face API is the correct service because it is specifically designed to detect human faces in images, analyze facial attributes such as emotions (e.g., happiness, sadness), and recognize specific individuals through face identification and verification. Unlike general-purpose image analysis services, Face API provides dedicated facial recognition capabilities, including person identification against a pre-enrolled database.
What should I do if I get this AZ-900 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
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Last reviewed: Jun 11, 2026
This AZ-900 practice question is part of Courseiva's free Microsoft 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 AZ-900 exam.
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