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NEW QUESTION: 1
An engineer is configuring QoS for a tunnel and wants to classify traffic based on the pre-tunnel header.
Which configuration implements the traffic?

A. Option A
B. Option B
C. Option C
D. Option D
Answer: B

NEW QUESTION: 2
The Frame Relay network in the diagram is not functioning properly.
What is the cause of the problem?

A. The S3 interface of the Steele router has been configured with the frame-relay encapsulation ietf command
B. The Gallant router has the wrong LMI type configured
C. Inverse ARP is providing the wrong PVC information to the Gallant router
D. The frame-relay map statement in the Attalla router for the PVC to Steele is not correct
E. The IP address on the serial interface of the Attalla router is configured incorrectly
Answer: D

NEW QUESTION: 3
You develop and train a machine learning model to predict fraudulent transactions for a hotel booking website.
Traffic to the site varies considerably. The site experiences heavy traffic on Monday and Friday and much lower traffic on other days. Holidays are also high web traffic days. You need to deploy the model as an Azure Machine Learning real-time web service endpoint on compute that can dynamically scale up and down to support demand. Which deployment compute option should you use?
A. Azure Kubernetes Service (AKS) inference cluster
B. attached virtual machine in a different region
C. Azure Machine Learning Compute Instance
D. Azure Container Instance (ACI)
E. attached Azure Databricks cluster
Answer: C
Explanation:
Explanation
Azure Machine Learning compute cluster is a managed-compute infrastructure that allows you to easily create a single or multi-node compute. The compute is created within your workspace region as a resource that can be shared with other users in your workspace. The compute scales up automatically when a job is submitted, and can be put in an Azure Virtual Network.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-sdk