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NEW QUESTION: 1
What should be verified before running the initTM -f command on the Command Line Interface of Avaya
Breeze(TM) platform (formerly known as Engagement Development Platform (EDP))?
A. Verify that Avaya Breeze(TM) is configured as a Managed Element in Avaya Aura(R) System Manager.
B. Verify that an enrollment password is configured on System Manager and that it has not expired.
C. Verify that a valid Certificate is installed on the Avaya Breeze(TM) instance.
D. Verify that Avaya Breeze(TM) is licensed.
Answer: B
Explanation:
See step 8 and step 9 below.
Repairing replication between Avaya Breeze(TM) and System Manager
Procedure
1 . On the System Manager web console, navigate to Services> Replication.
2 . In Replica Group column, click CollaborationEnvironment_3.1.
3 . In Replica Node Host Name column, locate Avaya Breeze(TM).
4 . Verify that the status of the Synchronization Status field is green. If not, go to Step 5.
5 . If Presence Services Snap-in has been deployed, in the Product column, verify that both Avaya
Breeze(TM) and Presence Services are displayed.
6 . Select Avaya Breeze(TM), and click Repair.
7 . After 2-15 minutes, verify that the status of the Synchronization Status field is green. If not, go to Step8.
8 . Verify that Enrollment Password is not expired.
a. Navigate to Services> Security.
b. In the navigation pane, click Certificates> Enrollment Password.
9 . If the Enrollment Password is expired:
a. Enter a password, and click Commit.
It is highly recommended that the same password must be used. Otherwise, Avaya Breeze(TM) and
Presence Services must be re-administered, because System Manager Enrollment Password was configured during deployment of Avaya Breeze(TM).
b. Open an SSH session to the Avaya Breeze(TM) Management Module IP address as sroot.
c. On the command line interface, enter initTM -f.
d. When prompted for the enrollment password, enter the password that you provided in Step 9a.
e. Repeat Step 1 to Step 6.
References:
Avaya Aura(R) Presence Services Snap-in Reference, Release 7.0.1 (December 2016), page 223
https://downloads.avaya.com/css/P8/documents/101013646

NEW QUESTION: 2
Your company has a logging microservice which is used to generate logs when users have entered certain commands in another application. This logging service is implemented via an SQS standard queue that an EC2 instance is listening to. However, you have found that on some occasions, the order of the logs are not maintained. As a result, it becomes harder to use this service to trace users' activities. How should you fix this issue in a simple way?
A. Migrate the whole microservice application to SWF so that the operation sequence is guaranteed.
B. Delete the existing standard queue and recreate it as a FIFO queue. As a result, the order for the messages to be received is ensured.
C. The wrong order of timestamps is a limitation of SQS, which does not have a fix.
D. Convert the existing standard queue into a FIFO queue. Add a deduplication ID for the messages that are sent to the queue.
Answer: B

NEW QUESTION: 3
A company's application runs on Amazon EC2 instances behind an Application Load Balancer (ALB) The instances run in an Amazon EC2 Auto Scaling group across multiple Availability Zones On the first day of every month at midnight the application becomes much slower when the month-end financial calculation batch executes This causes the CPU utilization of the EC2 instances to immediately peak to 100%. which disrupts the application What should a solutions architect recommend to ensure the application is able to handle the workload and avoid downtime?
A. Configure Amazon ElastiCache to remove some of the workload from the EC2 instances
B. Configure an EC2 Auto Scaling scheduled scaling policy based on the monthly schedule.
C. Configure an EC2 Auto Scaling simple scaling policy based on CPU utilization
D. Configure an Amazon CloudFront distribution in front of the ALB
Answer: B
Explanation:
Scheduled Scaling for Amazon EC2 Auto Scaling Scheduled scaling allows you to set your own scaling schedule.
For example, let's say that every week the traffic to your web application starts to increase on Wednesday, remains high on Thursday, and starts to decrease on Friday. You can plan your scaling actions based on the predictable traffic patterns of your web application. Scaling actions are performed automatically as a function of time and date.
https://docs.aws.amazon.com/autoscaling/ec2/userguide/schedule_time.html