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NEW QUESTION: 1
ある都市が、Amazon GoudFrontを使用する選挙結果報告Webサイトを実装しています。このWebサイトは、Auto ScalingグループのApplication Load Balancer(ALB)の背後にある一連のAmazon EC2インスタンスで実行されます。選挙結果は1時間ごとに更新され、Amazon S3バケットに.pdfタイルとして保存されます。セキュリティエンジニアは、ウェブサイトへのすべての外部アクセスがCloudFrontを経由するようにする必要があります。
これらの要件を満たすソリューションはどれですか?
A. CloudFrontでオリジンアクセスアイデンティティ(OAI)を作成します。新しいOAIのみがバケットの内容にアクセスできるようにS3バケットポリシーを変更します。 CloudFrontサービスからの受信トラフィックのみがALBと通信できるようにするセキュリティグループにALBを関連付けます。
B. CloudFrontでオリジンアクセスID(OAI)を作成します。新しいOAIのみがバケットの内容にアクセスできるようにS3バケットポリシーを変更します。 CloudFrontがALBと安全に通信するためのインターフェースVPCエンドポイントを作成します。
C. CloudFrontが特定のS3バケットにアクセスできるようにするIAMロールを作成します。 S3バケットポリシーを変更して、新しいIAMロールのみがそのコンテンツにアクセスできるようにします。 CloudFrontがALBと安全に通信するためのインターフェースVPCエンドポイントを作成します。
D. CloudFrontが特定のS3バケットにアクセスできるようにするIAMロールを作成します。 S3バケットポリシーを変更して、新しいIAMロールのみがそのコンテンツにアクセスできるようにします。 CloudFrontサービスからの受信トラフィックのみがALBと通信できるようにするセキュリティグループにALBを関連付けます。
Answer: B
NEW QUESTION: 2
회사에 온 프레미스, 다 계층 PHP 웹 응용 프로그램이 있으며, 최근 회사 발표로 인해 웹 트래픽이 급증하여 가동 중지 시간이 발생했습니다. 앞으로는 예측할수 없는 버스트를 유발할 유사한 발표가 있을 것으로 예상되며 예상치 못한 트래픽 증가를 처리할수 있는 인프라 기능을 빠르게 개선할수 있는 방법을 찾고 있습니다. 애플리케이션은 현재 2 개의 계층으로 구성됩니다. 웹 계층 (로드 밸런서 및 여러 Linux Apache 웹 서버로 구성됨)과 데이터베이스 계층은 MySQL 데이터베이스를 호스팅하는 Linux 서버를 호스팅합니다.
다음 중 짧은 시간 내에 응용 프로그램의 가용성을 향상시키는 동시에 전체 사이트 기능을 제공하는 시나리오는 무엇입니까?
A. 온-프레미스 환경에서 트래픽을 오프로드 합니다.
CIoudFront 배포를 설정하고 사용자 지정 오리진에서 객체를 캐시하도록 CloudFront를 구성하십시오.
오브젝트 캐시 동작을 사용자 정의하고 오브젝트가 캐시에 있어야 하는 TTL을 선택하십시오.
B. AWS로 마이그레이션 :
온 프레미스 웹 서버를 AMI로 신속하게 변환하려면 VM Import / Export를 사용하십시오.
가져온 AMI를 사용하여 들어오는 트래픽을 기반으로 웹 계층을 확장하는 Auto Scaling 그룹을 생성합니다.
RDS 인스턴스와 온 프레미스 MySQL 서버간에 RDS 읽기 전용 복제본을 만들고 복제를 설정하여 데이터베이스를 마이그레이션합니다.
C. 하이브리드 환경 :
EC2에서 웹 서버를 시작하는데 사용할수 있는 AMI를 생성하십시오.
AMI를 사용하여 들어오는 트래픽을 기반으로 웹 계층을 확장하는 Auto Scaling 그룹을 생성합니다.
온 프레미스 웹 서버와 AWS에서 호스팅되는 서버 간의 트래픽 균형을 조정하려면 Elastic Load Balancing을 활용하십시오.
D. 장애 조치 환경 :
S3 버킷을 생성하고 웹 사이트 호스팅을 위해 구성하십시오.
영역 파일 가져 오기를 사용하여 DNS를 Route53으로 마이그레이션하고 Route53 DNS 장애 조치를 활용하여 S3 호스팅 웹 사이트로 장애 조치합니다.
Answer: A
Explanation:
You can have CloudFront sit in front of your on-prem web environment, via a custom origin (the origin doesn't have to be in AWS). This would protect against unexpected bursts in traffic by letting CloudFront handle the traffic that it can out of cache, thus hopefully removing some of the load from your on-prem web servers.
NEW QUESTION: 3
Dell EMCのベストプラクティスによると、DRソリューションではオフサイトデータを非同期的に複製する方法を教えてください。
A. 複製元と複製先の両方のアレイで、複製するデータの20%に等しいRLPを構成します。
B. 送信元と宛先の両方で16Gbファイバチャネル用にCANの同期複製ポートを設定します。
C. 非同期レプリケーションがソースでのみアクティブになるハイブリッドプールにFlash層を含めます。
D. 非同期レプリケーションがソースと宛先の両方でアクティブになるハイブリッドプールにFlash層を含めます。
Answer: B
Explanation:
説明
参考文献:https://www.emc.com/collateral/white-papers/h15088-dell-emc-unity-replication-technologies.pdf
NEW QUESTION: 4
You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.
You need to select the hyperparameters that should be tuned using the Tune Model Hyperparameters module.
Which two hyperparameters should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Learning Rate
B. Number of hidden nodes
C. Hidden layer specification
D. Number of learning iterations
E. The type of the normalizer
Answer: C,D
Explanation:
D: For Number of learning iterations, specify the maximum number of times the algorithm should process the training cases.
E: For Hidden layer specification, select the type of network architecture to create.
Between the input and output layers you can insert multiple hidden layers. Most predictive tasks can be accomplished easily with only one or a few hidden layers.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/two-class-neural-network