C-ABAPD-2309 Certification

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NEW QUESTION: 1
DRAG DROP

Answer:
Explanation:

Explanation:
Network - 2 AS External - 5 Link - 8 Prefix - 9 NSSA - 7

NEW QUESTION: 2


Answer:
Explanation:

Explanation

SMTP1_Account1: Private Profile
When no profile_name is specified, sp_send_dbmail uses the default private profile for the current user. If the user does not have a default private profile, sp_send_dbmail uses the default public profile for the msdb database.
SMTP1_Account2: Default Profile
Execute permissions forsp_send_dbmail default to all members of the DatabaseMailUser database role in the msdb database.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sp-send-dbmail-transact-sql

NEW QUESTION: 3
A solutions architect is designing the cloud architecture for a new application being deployed on AWS.
The process should run in parallel while adding and removing application nodes as needed based on the number of jobs to be processed.
The processor application is stateless.
The solutions architect must ensure that the application is loosely coupled and the job items are durably stored.
Which design should the solutions architect use?
A. Create an Amazon SNS topic to send the jobs that need to be processed.
Create an Amazon Machine Image (AMI) that consists of the processor application.
Create a launch configuration that uses the AMI.
Create an Auto Scaling group using the launch configuration.
Set the scaling policy for the Auto Scaling group to add and remove nodes based on CPU usage
B. Create an Amazon SNS topic to send the jobs that need to be processed.
Create an Amazon Machine Image (AMI) that consists of the processor application.
Create a launch template that uses the AMI.
Create an Auto Scaling group using the launch template.
Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of messages published to the SNS topic.
C. Create an Amazon SQS queue to hold the jobs that need to be processed.
Create an Amazon Machine Image (AMI) that consists of the processor application.
Create a launch configuration that uses the AMI.
Create an Auto Scaling group using the launch configuration.
Set the scaling policy for the Auto Scaling group to add and remove nodes based on network usage
D. Create an Amazon SQS queue to hold the jobs that needs to be processed.
Create an Amazon Machine Image (AMI) that consists of the processor application.
Create a launch template that uses the AMI.
Create an Auto Scaling group using the launch template.
Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue
Answer: D
Explanation:
In this case we need to find a durable and loosely coupled solution for storing jobs. Amazon SQS is ideal for this use case and can be configured to use dynamic scaling based on the number of jobs waiting in the queue.
To configure this scaling you can use the backlog per instance metric with the target value being the acceptable backlog per instance to maintain. You can calculate these numbers as follows:
Backlog per instance: To calculate your backlog per instance, start with the ApproximateNumberOfMessages queue attribute to determine the length of the SQS queue (number of messages available for retrieval from the queue). Divide that number by the fleet's running capacity, which for an Auto Scaling group is the number of instances in the InService state, to get the backlog per instance.
Acceptable backlog per instance: To calculate your target value, first determine what your application can accept in terms of latency. Then, take the acceptable latency value and divide it by the average time that an EC2 instance takes to process a message.
This solution will scale EC2 instances using Auto Scaling based on the number of jobs waiting in the SQS queue.
CORRECT: "Create an Amazon SQS queue to hold the jobs that needs to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue" is the correct answer.
INCORRECT: "Create an Amazon SQS queue to hold the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on network usage" is incorrect as scaling on network usage does not relate to the number of jobs waiting to be processed.
INCORRECT: "Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on CPU usage" is incorrect. Amazon SNS is a notification service so it delivers notifications to subscribers. It does store data durably but is less suitable than SQS for this use case. Scaling on CPU usage is not the best solution as it does not relate to the number of jobs waiting to be processed.
INCORRECT: "Create an Amazon SNS topic to send the jobs that need to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of messages published to the SNS topic" is incorrect. Amazon SNS is a notification service so it delivers notifications to subscribers. It does store data durably but is less suitable than SQS for this use case. Scaling on the number of notifications in SNS is not possible.
References:
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html

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