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NEW QUESTION: 1
A. Option B
B. Option A
C. Option D
D. Option C
Answer: B
Explanation:
Explanation
Virtual machine snapshots are file-based snapshots of the state, disk data, and configuration of a virtualmachine at a specific point in time. You can take multiple snapshots of a virtual machine, even while it is running. You can then revert the virtual machine to any of the previous states by App1ying a snapshot to the virtualmachine.
Taking a snapshot of a VM is to in essence freeze the current state and make it a parent disk based on currentstate, and at the same time create a child disk to capture all subsequent changes. - See more at:
Snapshots require adequate storage space. Snapshots are stored as .avhd files in the same location at thevirtual hard disk. Taking multiple snapshots can quickly consume a large amount of storage space.
When you use Hyper-V Manager to delete a snapshot, the snapshot is removed from the snapshot treebut the
.avhd file is not deleted until you turn off the virtual machine.
NEW QUESTION: 2
When the switch port sends a data frame carrying the same VLAN TAG and PVID, it must strip the VLAN TAG and forward it.
A. False
B. True
Answer: A
NEW QUESTION: 3
エンタープライズ企業のデータサイエンスチームは、Amazon SageMakerに簡単にアクセスできる安全で費用対効果の高い方法を提供したいと考えています。データサイエンティストはAWSの知識が限られているため、Jupyterノートブックインスタンスを起動できる必要があります。複雑なセットアップ要件を公開することなく、機械学習ストレージボリュームで保存データを暗号化するには、ノートブックインスタンスに事前構成済みのAWS KMSキーが必要です。
企業がデータサイエンティスト向けのセルフサービスメカニズムを設定して、運用オーバーヘッドが最小のAWSアカウントでJupyterノートブックを起動できるようにする方法はどれですか。
A. 静的Amazon S3ウェブサイトを使用してサーバーレスフロントエンドを作成し、データサイエンティストがフォームに入力してJupyterノートブックインスタンスをリクエストできるようにします。 Amazon API Gatewayを使用してS3ウェブサイトからリクエストを受信し、中央のAWS Lambda関数をトリガーして、データサイエンティスト用に事前構成されたKMSキーでノートブックインスタンスを起動するAmazon SageMakerをAPI呼び出します。次に、フロントエンドWebサイトにコールバックして、ノートブックインスタンスのURLを表示します。
B. AWS CloudFormationテンプレートを作成し、事前設定されたKMSキーでAWS :: SageMaker :: Notebooklnstanceリソースタイプを使用してJupyterノートブックインスタンスを起動します。 CloudFormationの[Mappings]セクションを使用して、インスタンス名などのパラメーター名をSmall、Large、X-Largeにマッピングすることにより、パラメーター名を簡略化します。出力セクションを使用してノートブックのURLを表示し、テンプレートをデータサイエンティストのポートフォリオのAWSサービスカタログ製品にアップロードして、データサイエンティストのIAMロールと共有します。
C. データサイエンティストがローカルで実行できるAWS CLIスクリプトを作成します。 AWS CLIスクリプトを実行して事前構成されたKMSキーでJupyterノートブックを起動するときに提供されるパラメーターについて、手順を追って説明します。共有のAmazon S3バケットを使用して、CLIスクリプトをデータサイエンティストに配布します。
D. AWS CloudFormationテンプレートを作成して、AWS :: SaqeMaker :: Notebooklnstanceリソースタイプと事前構成されたKMSキーを使用してJupyterノートブックインスタンスを起動します。 CloudFormationテンプレートにわかりやすい名前を追加します。出力セクションを使用して、ノートブックへのURLを表示します。
共有のAmazon S3バケットを使用して、CloudFormationテンプレートをデータサイエンティストに配布します。
Answer: B
Explanation:
https://aws.amazon.com/blogs/mt/enable-self-service-secured-data-science-using-amazon-sagemaker-notebooks-and-aws-service-catalog/