AZ-900 Describe Azure architecture and services Practice Question
Which Azure service can detect faces in images and identify emotions, facial attributes, and recognize specific individuals?
⚠ Common exam trap
Many candidates 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.
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.
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
Azure Computer Vision offers general image analysis, such as optical character recognition, object tagging, and describing scenes, but its face detection is generic and does not provide the advanced face recognition, identity verification, or person enrollment features found in Face API. Computer Vision can tell you where a face is, but it cannot reliably tell you whose face it is without additional custom code. Therefore, for a scenario requiring face identification, Computer Vision is a valid but less specialized tool compared to Face API.
- ✓
Azure Face API
Why this is correct
Azure Face API is the correct choice because it is a purpose-built cognitive service for detecting and recognizing human faces, including extracting facial attributes like emotion, age, and head pose, and matching a detected face against known individuals in a PersonGroup or LargePersonGroup. Its Face Identify operation compares a detected face to enrolled persons and returns matching confidence scores, which directly supports verification and identification scenarios. This is the service Azure documentation recommends for facial recognition tasks, making it the best fit among these options.
- ✗
Azure Custom Vision
Why it's wrong here
Azure Custom Vision lets you train a bespoke image classifier on your own labeled images, but that requires you to supply training data, manage model training, and then run inference. Face API is a prebuilt, specialized service that performs face detection and recognition out-of-the-box, with no custom model training needed for its standard face identification workflow. For the exam scenario of identifying persons from their faces, Custom Vision is overkill and less accurate out-of the box than Face API's tuned face models.
- ✗
Azure Video Analyzer
Why it's wrong here
Azure Video Analyzer is built to ingest, manage, and extract insights from video streams over time, such as detecting motion or identifying events across footage. It is not designed for static image face identification, and it lacks the dedicated facial matching and person recognition capabilities that Face API provides. Using Video Analyzer for verifying a person against a stored face database would require heavy custom logic and is not the intended service.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AZ-900 question from scratch — 981 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.