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NEW QUESTION: 1
プロジェクトの締め切りが近づいています。プロジェクトマネージャーは、まだ完了していない重要なタスクがいくつかあると報告しています。
プロセスを合理化するには、PowerAutomateを実装する必要があります。
どのタイプのフローを使用する必要がありますか？答えるには、適切なフロータイプを正しい要件にドラッグします。
各フロータイプは、1回使用することも、複数回使用することも、まったく使用しないこともできます。コンテンツを表示するには、分割バーをペイン間でドラッグするか、スクロールする必要がある場合があります。
注：正しい選択はそれぞれ1ポイントの価値があります。

Answer:
Explanation:

Explanation

Reference:
https://docs.microsoft.com/en-us/power-automate/business-process-flows-overview
https://docs.microsoft.com/en-us/power-automate/get-started-logic-flow
https://docs.microsoft.com/en-us/power-automate/run-scheduled-tasks

NEW QUESTION: 2
You're running an application on-premises due to its dependency on non-x86 hardware and want to use AWS for data backup. Your backup application is only able to write to POSIX-compatible blockbased storage. You have 140TB of data and would like to mount it as a single folder on your file server Users must be able to access portions of this data while the backups are taking place. What backup solution would be most appropriate for this use case?
A. Use Storage Gateway and configure it to use Gateway Cached volumes.
B. Configure your backup software to use 53 as the target for your data backups.
C. Use Storage Gateway and configure it to use Gateway Stored volumes.
D. Configure your backup software to use Glacier as the target for your data backups.
Answer: A
Explanation:
Gateway-Cached Volume Architecture
Gateway-cached volumes let you use Amazon Simple Storage Service (Amazon 53) as your primary data storage while retaining frequently accessed data locally in your storage gateway. Gateway cached volumes minimize the need to scale your on-premises storage infrastructure, while still providing your applications with low-latency access to their frequently accessed data. You can create storage volumes up to 32 TIB in size and attach to them as iSCSI devices from your on-premises application servers. Your gateway stores data that you write to these volumes in Amazon 53 and retains recently read data in your on-premises storage gateway's cache and upload buffer storage.
Gateway-cached volumes can range from 1 GIB to 32 TIB in size and must be rounded to the nearest GIB.
Each gateway configured for gateway-cached volumes can support up to 32 volumes for a total maximum storage volume of 1,024 TIB (1 Pi B).
In the gateway-cached volume solution, AWS Storage Gateway stores all your on-premises application data in a storage volume in Amazon 53.
The following diagram provides an overview of the AWS Storage Gateway-cached volume deployment.

After you've installed the AWS Storage Gateway software appliance-the virtual machine (VM)-on a host in your data center and activated it, you can use the AWS Management Console to provision storage volumes backed by Amazon 53. You can also provision storage volumes programmatically using the AWS Storage Gateway API or the AWS SDK libraries. You then mount these storage volumes to your on-premises application servers as iSCSI devices.
You also al locate disks on-premises for the VM. These on-premises disks serve the following purposes:
Disks for use by the gateway as cache storage - As your applications write data to the storage volumes in AWS, the gateway initially stores the data on the on-premises disks referred to as cache storage before uploading the data to Amazon 53. The cache storage acts as the on-premises durable store for data that is waiting to upload to Amazon 53 from the upload buffer.
The cache storage also lets the gateway store your application's recently accessed data on-premises for low-latency access. If your application requests data, the gateway first checks the cache storage for the data before checking Amazon 53.
You can use the following guidelines to determine the amount of disk space to allocate for cache storage.
Generally, you should allocate at least 20 percent of your existing file store size as cache storage. Cache storage should also be larger than the upload buffer. This latter guideline helps ensure cache storage is large enough to persistently hold all data in the upload buffer that has not yet been uploaded to Amazon
5 3.
Disks for use by the gateway as the upload buffer - To prepare for upload to Amazon 53, your gateway also stores incoming data in a staging area, referred to as an upload buffer. Your gateway uploads this buffer data over an encrypted Secure Sockets Layer (SSL) connection to AWS, where it is stored encrypted in Amazon 53.
You can take incremental backups, called snapshots, of your storage volumes in Amazon 53. These point-in-time snapshots are also stored in Amazon 53 as Amazon EBS snapshots. When you take a new snapshot, only the data that has changed since your last snapshot is stored. You can initiate snapshots on a scheduled or one-time basis. When you delete a snapshot, only the data not needed for any other snapshots is removed.
You can restore an Amazon EBS snapshot to a gateway storage volume if you need to recover a backup of your data. Alternatively, for snapshots up to 16 TiB in size, you can use the snapshot as a starting point for a new Amazon EBS volume. You can then attach this new Amazon EBS volume to an Amazon EC2 instance.
All gateway-cached volume data and snapshot data is stored in Amazon 53 encrypted at rest using server-side encryption (SSE). However, you cannot access this data with the Amazon 53 API or other tools such as the Amazon 53 console.

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:
Explanation
https://aws.amazon.com/blogs/mt/enable-self-service-secured-data-science-using-amazon-sagemaker-notebooks-

NEW QUESTION: 4
Which two advanced features requires you to install Nutanix Guest Tools (NGT)? (Choose two.)
A. Live Migration of a VM between AHV & other Hypervisors
B. Self-service file-level recovery from VM snapshots
C. Disaster Recovery of a VM between AHV and ESXi Hypervisors
D. File recovery from a third-party backup
Answer: B,C