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NEW QUESTION: 1
An AWS customer runs a public blogging website. The site users upload two million blog entries a month The average blog entry size is 200 KB. The access rate to blog entries drops to negligible 6 months after publication and users rarely access a blog entry 1 year after publication. Additionally, blog entries have a high update rate during the first 3 months following publication, this drops to no updates after 6 months. The customer wants to use CloudFront to improve his user's load times. Which of the following recommendations would you make to the customer?
A. Create a CloudFront distribution with S3 access restricted only to the CloudFront identity and partition the blog entry's location in S3 according to the month it was uploaded to be used with CloudFront behaviors.
B. Create a CloudFront distribution with "US'Europe price class for US/Europe users and a different CloudFront distribution with All Edge Locations' for the remaining users.
C. Duplicate entries into two different buckets and create two separate CloudFront distributions where S3 access is restricted only to Cloud Front identity
D. Create a CloudFronl distribution with Restrict Viewer Access Forward Query string set to true and minimum TTL of 0.
Answer: A
NEW QUESTION: 2
A. New-CsMobilityPolicy
B. Grant-CsVoicePolicy
C. New-CsVoicePolicy
D. Set-CsVoicePolicy
E. Grant-CsMobilityPolicy
Answer: B,C
Explanation:
Explanation
References:
https://technet.microsoft.com/en-us/library/gg425856.aspx
NEW QUESTION: 3
会社のAmazon S3バケットに100 GBのログデータが.csv形式で保存されています。 SQL開発者は、このデータをクエリし、グラフを生成して視覚化したいと考えています。また、.csvファイルからメタデータを保存する効率的な自動化方法も必要です。
最小限の労力でこれらの要件を満たすために実行する必要がある手順の組み合わせはどれですか？
（3つ選択してください。）
A. 永続的なメタデータストアとしてAmazon S3を使用します。
B. AWS X-Rayでデータをフィルタリングして、データを視覚化します。
C. Amazon Athenaでデータをクエリします。
D. Amazon Redshiftでデータをクエリします。
E. 永続的なメタデータストアとしてAWS Glueを使用します。
F. データを視覚化するために、Amazon QuickSightでデータをフィルタリングします。
Answer: C,E,F