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NEW QUESTION: 1
Note: This question is part of a series of questions that present the same scenario. Each question in the series
contains a unique solution that might meet the stated goals. Some question sets might have more than one
correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions
will not appear in the review screen.
You have a Hyper-V host named Server1 that hosts a virtual machine named VM1. Server1 and VM1 run
Windows Server 2016.
The settings for VM1 are configured as shown in the exhibit. (Click the Exhibit button.)
You need to ensure that you can use the Copy-VMFile cmdlet on Server1 to copy files from VM1.
Solution: You start the Hyper-V Guest Service Interface service on VM1.
Does this meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation
References:
https://technet.microsoft.com/en-us/library/dn798297(v=ws.11).aspx
NEW QUESTION: 2
Which two ntatementn about VPLS are true? (Choone two.)
A. PE routern dynamically annociate to peern.
B. IP in uned to nwitch Ethernet framen between niten.
C. VPLS extendn a Layer 2 broadcant domain.
D. Split horizon in uned on PE devicen to prevent loopn.
E. Spanning tree in extended from CE to CE.
Answer: C,D
NEW QUESTION: 3
ある会社が最近、新しいタイプのインターネット接続センサーをリリースしました。同社は、大量のデータを毎秒中央の場所にストリーミングするように設計された数千のセンサーの大量販売を期待しています。ソリューションアーキテクトは、エンジニアリングチームがミリ秒単位の応答性でほぼリアルタイムでデータを分析できるように、データを取り込んで保存するソリューションを設計する必要があります。
ソリューションアーキテクトが推奨するソリューションはどれですか。
A. Amazon SOSキューを使用してデータを取り込みます。 AWS Lambda関数を使用してデータを消費し、その関数がデータをAmazon DynamoDBに保存します。
B. Amazon Kinesis Data Streamsを使用してデータを取り込みます。 AWS Lambda関数を使用してデータを消費し、その関数がデータをAmazon Redshiftに保存します。
C. Amazon SQSキューを使用してデータを取り込みます。 AWS Lambda関数を使用してデータを消費し、その関数がデータをAmazon Redshiftに保存します。
D. Amazon Kinesis Data Streamsを使用してデータを取り込みます。 AWS Lambda関数を使用してデータを消費し、その関数がデータをAmazon DynamoDBに保存します。
Answer: D
Explanation:
https://aws.amazon.com/blogs/big-data/analyze-data-in-amazon-dynamodb-using-amazon- sagemaker-for-real-time-prediction/