AI-102 Plan and manage an Azure AI solution Practice Question
Your organization is migrating on-premises machine learning models to Azure. The models are used for real-time inference. You need to choose a service that provides managed endpoints with autoscaling and supports custom containers. Which service should you use?
⚠ Common exam trap
A common mix-up: candidates confuse Azure Kubernetes Service (AKS) as the only option for custom containers, overlooking that Azure Machine Learning managed endpoints natively support custom containers with autoscaling, eliminating the operational burden of managing a Kubernetes cluster.
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 Machine Learning managed online endpoints
Azure Machine Learning managed online endpoints are the correct choice because they provide fully managed, autoscaling endpoints specifically designed for real-time inference. They support custom container images, allowing you to deploy any model packaged as a Docker container, and handle traffic splitting, health checks, and scaling automatically without managing underlying infrastructure.
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 Machine Learning managed online endpoints
Why this is correct
Supports custom containers, autoscaling, and managed infrastructure.
- ✗
Azure Functions
Why it's wrong here
Not designed for ML model serving.
- ✗
Azure Kubernetes Service (AKS) with manual scaling
Why it's wrong here
Requires more operational overhead.
- ✗
Azure AI Services custom vision
Why it's wrong here
Only for vision scenarios, not general models.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.