ai-200 Practice Question 1997
Exam: ai-200
Domain: Deploy and manage models
Topic: Deploy a model as an endpoint
Difficulty: medium
You have deployed a machine learning model using Azure Machine Learning and need to manage traffic between two versions of the model to gradually roll out updates without downtime. Which method should you use to achieve this blue-green deployment?
Answer Options
A
Use Azure Kubernetes Service (AKS) to manage traffic.
B
Use Azure Load Balancer to manage traffic between the two versions of the model.
C
Deploy the models in separate virtual machines and manually switch the load.
D
Use Azure Functions to route traffic based on the version of the model.
Correct Answer
B: Use Azure Load Balancer to manage traffic between the two versions of the model.
Explanation
Blue-green deployment is a strategy where two identical production environments (blue and green) exist at the same time. Traffic can be switched between them without any downtime. In Azure ML, you can create two online endpoints, each pointing to a different version of the model, and then switch traffic between them using Azure Load Balancer or Azure Application Gateway. Option B is correct because it describes the use of Azure Load Balancer to manage traffic between the two versions of the model during a blue-green deployment. Options A, C, and D are incorrect as they do not describe the proper method for managing traffic in a blue-green deployment scenario.