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NEW QUESTION: 1
Answer:
Explanation:
First, enable the Gig 0/0 and Gig 0/1 interfaces:
Second, create the pair under the "interface pairs" taB.
Then, apply the HIGHRISK action rule to the newly created interface pair:
Then apply the same for the MEDIUMRISK traffic (deny attacker inline)
Finally. Log the packets for the LOWRICK event:
When done it should look like this:
NEW QUESTION: 2
Exhibit:
Based on me burndown chart, what is the iteration's status?
A. It trended behind schedule and did not complete everything on time
B. It trended ahead of schedule and completed everything on time
C. It took more time than expected and had to be lengthened
D. It took less time than expected and had to be shortened
Answer: A
NEW QUESTION: 3
You manage a cloud service that hosts a customer-facing application. The application allows users to upload images
and create collages. The cloud service is running in two medium instances and utilizes Azure Queue storage for image
processing. The storage account is configured to be locally redundant.
The sales department plans to send a newsletter to potential clients. As a result, you expect a significant increase in
global traffic.
You need to recommend a solution that meets the following requirements:
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
A. Configure the cloud service to auto-scale when the queue exceeds 1000 entries per machine.
B. Configure the storage account to be geo-redundant
C. Deploy a new cloud service in a separate data center. Use Azure Traffic Manager to load balance traffic between the
cloud services.
D. Configure the cloud service to run in two Large instances.
E. Configure the cloud service to auto-scale to three instances when processor utilization is above 80%.
Answer: A,E
Explanation:
* An autoscaling solution reduces the amount of manual work involved in dynamically scaling an application. It can do
this in two different ways: either preemptively by setting constraints on the number of role instances based on a
ti metable, or reactively by adjusting the number of role instances in response to some counter(s) or measurement(s)
that you can collect from your application or from the Azure environment.