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NEW QUESTION: 1
ロードバランサーの背後にあるAmazon EC2インスタンスで実行されている会社の大規模な多層WindowsベースのWebアプリケーションを担当します。メトリックを確認していると、顧客ページの読み込み時間が遅いという上昇傾向に気づき始めました。上司から、1秒あたりの要求が多すぎて顧客の読み込み時間が影響を受けないようにするためのソリューションを考え出すように依頼されました。この問題を解決するには、どの手法を使用しますか？
A. Auto Scalingテンプレートを使用してアプリケーションを再デプロイします。顧客の読み込み時間がしきい値を超えたときに新しいElastic Beanstalkアプリケーションを起動するようにAuto Scalingテンプレートを設定します。
B. AWS CloudFormation、Elastic Beanstalk、Auto Scalingを使用してインフラストラクチャを再デプロイします。 Auto Scalinggroupポリシーを設定して、1秒あたりのリクエスト数と現在の顧客の読み込み時間に基づいてスケーリングします。
C. AWS CloudFormationテンプレートを使用してインフラストラクチャを再デプロイします。 Elastic Load Balancingヘルスチェックを設定して、ヘルスチェックが失敗したときに新しいAWS CloudFormationスタックを開始します。
D. AWS CloudFormationテンプレートを使用してインフラストラクチャを再デプロイします。 2番目のAWS CloudFormationスタックを起動します。 Elastic Load Balancing SpillOver機能を設定して、2番目のAWS CloudFormationスタックへの遅い接続をスピルオーバーします。
Answer: B
Explanation:
Auto Scaling helps you ensure that you have the correct number of Amazon CC2 instances available to handle the load for your application. You create collections of CC2 instances, called Auto Scaling groups. You can specify the minimum number of instances in each Auto Scaling group, and Auto Scaling ensures that your group never goes below this size. You can specify the maximum number of instances in each Auto Scaling group, and Auto Scaling ensures that yourgroup never goes above this size. If you specify the desired capacity, either when you create the group or at any time thereafter. Auto Scaling ensures that yourgroup has this many instances.
If you specify scaling policies, then Auto Scaling can launch or terminate instances as demand on your application increases or decreases.
Option A and B are invalid because Autoscaling is required to solve the issue to ensure the application can handle high traffic loads.
Option D is invalid because there is no Autoscaling template.
For more information on Autoscaling, please refer to the below document link: from AWS
http://docs.aws.amazon.com/autoscaling/latest/userguide/Whatl sAutoScaling.html
NEW QUESTION: 2
この質問については、TerramEarthのケーススタディを参照してください
TerramEarthのビジネス要件を分析してダウンタイムを削減し、部品の顧客の待機時間を削減することで時間の大半を節約できることを発見しました。3週間の集計レポート時間の削減に集中することにしました。 ？
A. CSVからバイナリ形式への移行、FTPからSFTPトランスポートへの移行、およびメトリックの機械学習分析の開発。
B. FTPからストリーミングトランスポートに移行し、CSVからバイナリ形式に移行し、メトリックの機械学習分析を開発します。
C. フリートのセルラー接続を80％に増やし、FTPからストリーミングトランスポートに移行し、メトリックの機械学習分析を開発します。
D. FTPからSFTPトランスポートに移行し、メトリクスの機械学習分析を開発し、ディーラーのローカル在庫を一定の要因で増やします。
Answer: C
Explanation:
説明
Avroバイナリ形式は、圧縮データの読み込みに適した形式です。 Avroデータは、データブロックが圧縮されている場合でもデータを並行して読み取ることができるため、読み込みが高速です。
Cloud Storageは、HTTPチャンク転送エンコードに基づいて、gsutilツールまたはbotoライブラリを使用したストリーミング転送をサポートしています。ストリーミングデータを使用すると、データを最初に別のファイルに保存することなく、Cloud Storageアカウントとの間でデータをストリーミングできるようになります。ストリーミング転送は、データを生成するプロセスがあり、データをアップロードする前にローカルにバッファリングしたくない場合、または計算パイプラインからCloud Storageに直接結果を送信する場合に便利です。
参照：https://cloud.google.com/storage/docs/streaming
https://cloud.google.com/bigquery/docs/loading-data
NEW QUESTION: 3
Which is a best practice to secure system traffic, ensure optimal performance and satisfy prerequisites for NSX?
A. Configure a single distributed port group with a single VMkernel for Management and iSCSI traffic, a separate VMkernel tor vMotion and VSAN traffic
B. Configure a single VMkernel and H single distributed port group for all the system traffic.
C. Dedicate separate VMkernel adapters for each type of system traffic. Dedicate separate distributed port groups for each VMkernel adapter and isolate the VLANs for each type of system traffic
D. Dedicate separate VMkernel adapters for each type of system traffic and dedicate separate standard switches for each type of system traffic connected to a single physical network
Answer: D