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NEW QUESTION: 1
Which two options are the Cisco Meraki SD-WAN suites of features? (Choose two )
A. physical and virtual stacking
B. transport independence
C. intelligent path selection
D. SSL VPN
E. RSTP and MGig support
Answer: B,C
Explanation:
Explanation: https://meraki.cisco.com/solutions/sd-wan
NEW QUESTION: 2
While creating approval process, you need to define conditions. Which of the following are mandatory
field in conditions section.
There are 3 correct answers to this question
A. Value
B. Compare operator
C. Currency
D. Field
E. With
Answer: B,D,E
NEW QUESTION: 3
Refer to the exhibit.
MSTP is implemented in the topology shown in the exhibit, and all the switches are in the same region. The network administrator does not want to use the Internal Spanning Tree (IST) or instance 0 for production traffic.
How many non-IST spanning tree instances does this network need in order to have effective load sharing on the uplinks from the access switches?
A. five
B. four
C. three
D. two
Answer: B
NEW QUESTION: 4
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 Stream Analytics as an IoT Edge module.
Does this meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation
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
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