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NEW QUESTION: 1
An organization has private and public cloud resources. The organization has Windows Server 2012 R2 servers that have the Hyper-V role installed. You have one four-node cluster of Hyper-V host servers.
You use System Center 2012 R2.
The virtual machines that run on the cluster must remain online when you install updates on the Hyper-V host servers.
You need to install updates on the Hyper-V host servers.
What should you do?
A. Configure Windows Update on the Hyper-V host servers to download updates from Microsoft Update.
B. Create orchestrated updates of Hyper-V host clusters by using System Center 2012 R2 Virtual Machine Manager (VMM).
C. Configure Windows Server Update Services (WSUS) to provide updates to the virtual machines hosted on the cluster.
D. Add all the servers to a collection in System Center 2012 R2 Configuration Manager. Deploy updates to the collection.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
http://technet.microsoft.com/en-us/library/gg675084.aspx
http://technet.microsoft.com/en-us/library/gg675088.aspx
VMM rolls through the host cluster, remediating one cluster node at a time. If a cluster node is compliant, VMM bypasses that node.

NEW QUESTION: 2
Your Network contains an on-premises Active Directory domain named contoso.local. The domain contains five domain controllers.
Your company purchases Microsoft 365 and creates a Microsoft Anne Active Directory (Azure AD) tenant named .contoso.onmicrosoft.com.
You plan to implement pass- through authentication.
You need to prepare the environment for the planned implementation of pass-through authentication.
Which three actions should you perform? Each correct answer presents pan of the solution.
NOTE: Each correct selection is worth one point.
A. From the Azure portal, add a custom domain name.
B. From the Azure portal, configure an authentication method.
C. From Active Directory Domains and Trusts, add a UPN suffix.
D. Modify the User logon name for each user account.
E. Modify the email address attribute for each user account.
F. From a domain controller, install an authentication Agent.
Answer: A,D,F

NEW QUESTION: 3
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
*Serve as a repository (or high volumes of large files in various formats.
*Implement optimized storage for big data analytics workloads.
*Ensure that data can be organized using a hierarchical structure.
Batch processing:
*Use a managed solution for in-memory computation processing.
*Natively support Scala, Python, and R programming languages.
*Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
*Support parallel processing.
*Use columnar storage.
*Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is