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NEW QUESTION: 1
Linuxストレージ管理者は、論理ボリュームグループを作成したいと考えています。プロセスを開始するには、次のコマンドのどれが必要ですか？
A. lvcreate
B. pvcreate
C. vgcreate
D. mkfs.xfs
Answer: C
Explanation:
Reference:
https://www.thegeekstuff.com/2010/08/how-to-create-lvm/

NEW QUESTION: 2
You need to recommend which changes must be implemented to the network before you can deploy the new web
application.
What should you include in the recommendation?
A. Upgrade the DNS servers to Windows Server 2012.
B. Change the functional level of both the domains to Windows Server 2008 R2.
C. Change the forest functional level to Windows Server 2008 R2.
D. Upgrade the domain controllers to Windows Server 2012.
Answer: D
Explanation:
The web application is in the sales.contoso.com domain, which will have Windows Server 2012 Domain controllers.
We should therefore upgrade the other domain controller to Windows Server 2012.
Scenario:
* The new sales.contoso.com domain will contain a web application that will access data from a Microsoft SQL Server
located in the contoso.com domain. The web application must use integrated Windows authentication. Users'
credentials must be passed from the web applications to the SQL Server.
* Planned changes include: create a child domain named sales.contoso.com. Only the domain controllers in
sales.contoso.com will host a zone for the sales.contoso.com domain. The domain controllers in sales.contoso.com
will run Windows Server 2012.

NEW QUESTION: 3
You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.
You have the following requirements:
* Models must be built using Caffe2 or Chainer frameworks.
* Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments.
* Personal devices must support updating machine learning pipelines when connected to a network.
You need to select a data science environment.
Which environment should you use?
A. Azure Kubernetes Service (AKS)
B. Azure Databricks
C. Azure Machine Learning Studio
D. Azure Machine Learning Service
Answer: D
Explanation:
Explanation
The Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft's Azure cloud built specifically for doing data science. Caffe2 and Chainer are supported by DSVM.
DSVM integrates with Azure Machine Learning.