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NEW QUESTION: 1
You have an Azure subscription.
You have an on-premises virtual machine named VM1. The settings for VM1 are shown in the exhibit. (Click the Exhibit button.)

You need to ensure that you can use the disks attached to VM1 as a template for Azure virtual machines.
What should you modify on VM1?
A. the memory
B. Integration Services
C. the network adapters
D. the hard drive
E. the processor
Answer: D
Explanation:
Explanation
From the exhibit we see that the disk is in the VHDX format.
Before you upload a Windows virtual machines (VM) from on-premises to Microsoft Azure, you must prepare the virtual hard disk (VHD or VHDX). Azure supports only generation 1 VMs that are in the VHD file format and have a fixed sized disk. The maximum size allowed for the VHD is 1,023 GB. You can convert a generation 1 VM from the VHDX file system to VHD and from a dynamically expanding disk to fixed-sized.
References:
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/prepare-for-upload-vhd-image?toc=%2fazure%

NEW QUESTION: 2
When using Cisco Expressway for XMPP federation, which platform handles the connection to the remote federation server?
A. Cisco Expressway-C
B. Cisco IM Presence Server
C. Cisco Expressway-E
D. Cisco Unified Communications Manager Publisher
Answer: C

NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models.
Once an
anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You deploy Azure Functions as an IoT Edge module.
Does this meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Instead use Azure Stream Analytics and REST API.
Note. Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies:
temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly- detection