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NEW QUESTION: 1
トラフィックストーム制御の動作に関する説明は正しいですか?
A. トラフィックストーム制御は、パケットがユニキャストかブロードキャストかを判断できません。
B. トラフィックストーム制御は、10秒のトラフィックストーム制御間隔で着信トラフィックレベルを監視します
C. ブロードキャストおよびマルチキャストトラフィックストーム制御を有効にし、ブロードキャストおよびマルチキャストトラフィックの組み合わせが1秒のトラフィックストームインターバル内でレベルを超えた場合、ストーム制御はストームインターバルの終わりまですべてのブロードキャストおよびマルチキャストトラフィックをドロップします
D. トラフィックストーム制御は、パケット送信元アドレスの個別/グループビットを使用して、パケットがユニキャストかブロードキャストかを判断します。
Answer: C

NEW QUESTION: 2
Which two methods increase the overall network bandwidth for a web host? (Choose two.)
A. Install additional vswitches on the host.
B. Mark DSCP to an established HTTP queue with higher allocations.
C. Add additional NICs to the host LACP.
D. Add vCPUs to the virtual machine.
E. Use a low latency SLB.
F. Replace bandwidth with priority in CBWFQ configuration.
G. Use policy-based routing on the source port of packets destined to the web server to traverse a higher bandwidth link.
Answer: B,C

NEW QUESTION: 3
You have an Azure Active Directory (Azure AD) tenant that contains the users shown in the following table.

The tenant contains the named locations shown in the following table.

You create the conditional access policies for a cloud app named App1 as shown in the following table.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation


NEW QUESTION: 4
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have an initial dataset that contains the crime data from major cities.
You plan to build training models from the training data. You plan to automate the process of adding more data to the training models and to constantly tune the models by using the additional data, including data that is collected in near real-time. The system will be used to analyze event data gathered from many different sources, such as Internet of Things (IoT) devices, live video surveillance, and traffic activities, and to generate predictions of an increased crime risk at a particular time and place.
You have an incoming data stream from Twitter and an incoming data stream from
Facebook, which are event-based only, rather than time-based. You also have a time interval stream every 10 seconds.
The data is in a key/value pair format. The value field represents a number that defines how many times a hashtag occurs within a Facebook post, or how many times a Tweet that contains a specific hashtag is retweeted.
You must use the appropriate data storage, stream analytics techniques, and Azure
HDInsight cluster types for the various tasks associated to the processing pipeline.
You are planning a storage strategy for a large amount of analytic data used for the crime data analytics system. The initial data load involves over 100 billion records, and more than two billion records will be added daily.
You already created an Apache Hadoop cluster in HDInsight premium.
You need to implement the storage strategy to meet the following requirements:
What should you create?
A. an Azure Data Lake Analytics service by using Azure PowerShell
B. a virtual machine (VM) by using the Data Science Virtual Machine template for Windows that has premium storage, a G-series size, and uses Microsoft SQL Server 2016 to store the data
C. an Azure Data Lake Store account by using the Azure portal
D. an Azure Blob storage account by using the Azure portal
Answer: C
Explanation:
References: https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-get- started-portal