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NEW QUESTION: 1
AWS 고객이 공개 블로깅 웹 사이트를 운영합니다. 사이트 사용자는 한 달에 2 백만 개의 블로그 항목을 업로드합니다.
평균 블로그 항목 크기는 200KB입니다. 블로그 항목에 대한 액세스 속도는 게시 후 6 개월 동안 무시되고 사용자는 게시 후 1 년 간 블로그 항목에 거의 액세스하지 않습니다. 또한 블로그 항목은 게시 후 처음 3 개월 동안 업데이트 속도가 빠르며 6 개월 후에도 업데이트되지 않습니다.
고객은 CloudFront를 사용하여 사용자의로드 시간을 개선하려고합니다.
다음 중 고객에게 추천 할만한 추천 사항은 무엇입니까?
A. 두 개의 다른 버킷으로 항목을 복제하고 두 개의 별도 CloudFront 배포판을 만듭니다. 여기서 53 개의 액세스는 Cloud Front identity에만 제한됩니다.
B. CloudFront ID로만 제한된 액세스로 CloudFront 배포판을 만들고 CloudFront 비헤이비어와 함께 사용하기 위해 업로드 한 달에 따라 블로그 항목의 위치를 ​​53 분할합니다.
C. 미국 / 유럽 사용자의 경우 '미국'유럽 가격 클래스로, 나머지 사용자의 경우 Al l Edge Locations가있는 다른 CloudFront 배포를 사용하여 CloudFront 배포판을 만듭니다.
D. 뷰어 액세스 전달 쿼리 문자열을 true로 설정하고 최소 TTL을 0으로 설정하여 CloudFronl 배포를 생성합니다.
Answer: B

NEW QUESTION: 2
Universal Containers（UC）は、Salesforceユーザーライセンスを持つLightningExperience対応の従業員がコミュニティにアクセスすることを望んでいます。従業員のプロファイルがコミュニティメンバーシップに追加されました。コミュニティクラウドコンサルタントは、コミュニティへのアクセス方法について従業員をどのように教育する必要がありますか？
次の1つ以上を選択します。
A. 「名前を付けてログイン」機能を使用するよう従業員にアドバイスする
B. 従業員をグローバルヘッダーに誘導する
C. 従業員をアプリランチャーに誘導する
D. コミュニティアクセスに別のユーザー名を使用することを従業員に推奨する
Answer: C

NEW QUESTION: 3
企業は、ハードウェアが「サポート終了」になる懸念があるため、ウェブサイトインフラストラクチャを移行したいと考えています。このWebサイトは十分に活用されておらず、少量のコンテンツをまれなユーザーベースに提供しています。この組織に最適なオプションは次のうちどれですか？
A. 内部でホストされているサーバーを引き続き利用する方が簡単です。
B. 高度なITプロセスのため、クラウドを利用する方が信頼性が高くなります。
C. 企業がすでにITプロセスを導入している場合、クラウドコンピューティングは使用できません。
D. クラウド展開は、このタイプのサイトでは一般的に安価なオプションです。
Answer: D

NEW QUESTION: 4
DRAG DROP
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
You finish training the model and are ready to publish a predictive web service that will provide the users with the ability to specify the data source and the save location of the results. The model includes a Split Data module.
Which two actions should you perform to convert the Machine Learning experiment to a predictive web service? To answer, drag the appropriate actions to the correct targets.
Each action may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:

References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/convert-training- experiment-to-scoring-experiment