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Up to now, we have successfully issued three packages for you to choose.
NEW QUESTION: 1
Use the following login credentials as needed:
Azure Username: xxxxx
Azure Password: xxxxx
The following information is for technical support purposes only:
Lab Instance: 10277521
You plan to create multiple pipelines in a new Azure Data Factory V2.
You need to create the data factory, and then create a scheduled trigger for the planned pipelines. The trigger must execute every two hours starting at 24:00:00.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create a new Azure Data Factory V2
1. Go to the Azure portal.
2. Select Create a resource on the left menu, select Analytics, and then select Data Factory.
4. On the New data factory page, enter a name.
5. For Subscription, select your Azure subscription in which you want to create the data factory.
6. For Resource Group, use one of the following steps:
Select Use existing, and select an existing resource group from the list.
Select Create new, and enter the name of a resource group.
7. For Version, select V2.
8. For Location, select the location for the data factory.
9. Select Create.
10. After the creation is complete, you see the Data Factory page.
Step 2: Create a schedule trigger for the Data Factory
1. Select the Data Factory you created, and switch to the Edit tab.
2. Click Trigger on the menu, and click New/Edit.
3. In the Add Triggers page, click Choose trigger..., and click New.
4. In the New Trigger page, do the following steps:
a. Confirm that Schedule is selected for Type.
b. Specify the start datetime of the trigger for Start Date (UTC) to: 24:00:00 c. Specify Recurrence for the trigger. Select Every Hour, and enter 2 in the text box.
5. In the New Trigger window, check the Activated option, and click Next.
6. In the New Trigger page, review the warning message, and click Finish.
7. Click Publish to publish changes to Data Factory. Until you publish changes to Data Factory, the trigger does not start triggering the pipeline runs.
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger
NEW QUESTION: 2
Most consumers do not get much use out of the sports equipment they purchase. For example, seventeen percent of the adults in the United States own jogging shoes, but only forty-five percent of the owners jog more than once a year, and only seventeen percent jog more than once a week.
Which of the following, if true, casts most doubt on the claim that most consumers get little use out of the sports equipment they purchase?
A. Joggers are most susceptible to sports injuries during the first six months in which they jog.
B. Joggers often exaggerate the frequency with which they jog in surveys designed to elicit such information.
C. Joggers who jog more than once a week are often active participants in other sports as well.
D. Consumers who take up jogging often purchase an athletic shoe that can be used in other sports.
E. Many consumers purchase jogging shoes for use in activities other than jogging.
Answer: E
Explanation:
Explanation/Reference:
Explanation:
NEW QUESTION: 3
You have an application hosted in AWS, which sits on EC2 Instances behind an Elastic Load Balancer. You have added a new feature to your application and are now receving complaints from users that the site has a slow response. Which of the below actions can you carry out to help you pinpoint the issue
A. Create some custom Cloudwatch metrics which are pertinent to the key features of your application
B. Use Cloudtrail to log all the API calls, and then traverse the log files to locate the issue
C. Use Cloudwatch, monitor the CPU utilization to see the times when the CPU peaked
D. Reviewthe Elastic Load Balancer logs
Answer: A
Explanation:
Explanation
Since the issue is occuring after the new feature has been added, it could be relevant to the new feature.
Enabling Cloudtrail will just monitor all the API calls of all services and will not benefit the cause.
The monitoring of CPU utilization will just reverify that there is an issue but will not help pinpoint the issue.
The Elastic Load Balancer logs will also just reverify that there is an issue but will not help pinpoint the issue.
For more information on custom Cloudwatch metrics, please refer to the below link:
* http://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/publishingMetrics.html
*
