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NEW QUESTION: 1
Refer to the table Summary of Selected Blood Product Review. Based on the results reported in the table, which blood component or derivative should first be the topic of an in- depth study?
A. packed red blood cells
B. platelets
C. fresh frozen plasma
D. unable to determine from the table
Answer: C
NEW QUESTION: 2
Tall organization structures have a large number of levels between the top of the organization and the bottom.
A. True
B. False
Answer: A
NEW QUESTION: 3
必要に応じて、次のログイン資格情報を使用します。
Azure Username: xxxxx
Azure Password: xxxxx
次の情報は、技術サポートのみを目的としています。
Lab Instance: 10277521
You plan to deploy an integration runtime named Runtime1 to an Azure virtual machine.
You need to create an Azure Data Factory V2, and then prepare the required Data Factory resources for App1.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create an 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: Setup of the Integration Runtime Runtime1
High-level steps for creating a linked self-hosted IR
1. In the self-hosted IR Runtime to be shared, click Connections and Grant permission to another Data Factory. .
2. Select the data factory you just created.
Note the resource ID of the self-hosted IR to be shared.
3. In the data factory to which the permissions were granted, create a new self-hosted IR (linked) and enter the resource ID.
References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime#sharing-the-self-hoste
NEW QUESTION: 4
You have an Azure web app named App1 that contains the following autoscale conditions. The default auto created scale condition has a scale mode that has Scale to a specific instance count set to 2.
Scale condition 1 has the following configurations:
* Scale mode: Scale to a specific instance count
* Instance count 3
* Schedule: Specify start/end dates
* Start date: August 1. 2019.06:00
* End date: September 1.2019, 18:00
Scale condition 2 has the following configurations:
* Scale mode: Scale to a specific instance count
* Instance count 4
* Schedule: Repeat specific days
* Repeat every: Monday
* Start time: 06:00
* End time: 18:00
Scale condition 3 has the following configurations.
Answer:
Explanation:
Explanation
Box 1: 5
Scale condition 1, Scale condition 2, and Scale condition 3 applies.
Scale condition 3 takes precedence as it the largest increase in the number of instances.
Box 2: 5
Scale condition 1 does not apply as its end date is exceeded.
Scale condition 2 and Scale condition 3 applies.
Scale condition 3 takes precedence as it the largest increase in the number of instances.
When you configure multiple policies and rules, they could conflict with each other. Autoscale uses the following conflict resolution rules to ensure that there is always a sufficient number of instances running:
* Scale-out operations always take precedence over scale-in operations.
* When scale-out operations conflict, the rule that initiates the largest increase in the number of instances takes precedence.
* When scale in operations conflict, the rule that initiates the smallest decrease in the number of instances takes precedence.
References:
https://docs.microsoft.com/en-us/azure/architecture/best-practices/auto-scaling