AI-103 Plan And Manage AN Azure AI Solution Practice Question
Your development team has created a custom model using Azure Machine Learning. You need to deploy this model as a real-time web service endpoint with auto-scaling capabilities. Which deployment target should you select?
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 Managed Online Endpoint
Azure Managed Online Endpoints provide a scalable, managed infrastructure for deploying machine learning models with automatic scaling.
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 Functions consumption plan
Why it's wrong here
While functions can host code, Managed Online Endpoints are the native production standard for Azure ML model scoring.
- ✗
Azure Container Registry webhook
Why it's wrong here
ACR webhooks trigger automation events when container images are pushed, not inference endpoints.
- ✗
Azure Batch cluster
Why it's wrong here
Azure Batch is designed for large-scale parallel and batch compute jobs, not low-latency real-time web APIs.
- ✓
Azure Managed Online Endpoint
Why this is correct
Managed Online Endpoints handle provisioning, scaling, and load balancing for real-time model inference in Azure ML.
About these practice questions
One of 510 original AI-103 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 August 2026 · checked against the official Microsoft exam blueprint
This AI-103 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 AI-103 exam.