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NEW QUESTION: 1
회사는 사용중인 두 개의 NAT 인스턴스가 더 이상 회사의 응용 프로그램에 필요한 트래픽을 지원할 수 없다고 우려합니다. 솔루션 아키텍트는 가용성이 높고 내결함성이 있으며 자동으로 확장 가능한 솔루션을 구현하려고 합니다. 솔루션 아키텍트는 무엇을 추천해야 합니까?
A. 두 개의 NAT 인스턴스를 서로 다른 가용 영역의 스팟 인스턴스로 바꾸고 Network Load Balancer를 배포하십시오.
B. 두 개의 NAT 인스턴스를 제거하고 동일한 가용 영역에있는 두 개의 NAT 게이트웨이로 교체하십시오.
C. 다른 가용 영역의 NAT 인스턴스에 대해 네트워크로드 밸런서와 함께 Auto Scaling 그룹을 사용하십시오.
D. 두 개의 NAT 인스턴스를 제거하고 서로 다른 가용 영역에 있는 두 개의 NAT 게이트웨이로 교체하십시오.
Answer: D
NEW QUESTION: 2
In some older machines, the Linux kernel defaults to polling for the parallel printer port (/dev/lp0), even if it is capable of interrupt-driven operation (ECP). Which utility enables interrupt-driven operation of the parallel port?
A. stty
B. setpar
C. setserial
D. tunelp
E. parpirq
Answer: D
NEW QUESTION: 3
ADatum Corporationという名前の会社には、Microsoft 365サブスクリプションがあります。
ADatumがContoso、Ltd.という会社を買収。
購読では、Contosoの各ユーザー用に新しいメールボックスを作成します。
Contosoユーザーに、自分の電子メールアドレスのみを含むグローバルアドレス一覧（GAL）を提供する必要があります。
どの3つのアクションを順番に実行しますか？答えるには、適切な行動を行動のリストから回答領域に移動し、正しい順序で並べます。
Answer:
Explanation:
説明
参考文献：
https://docs.microsoft.com/en-us/exchange/address-books/address-lists/create-global-address-list
https://docs.microsoft.com/ja-jp/exchange/email-addresses-and-address-books/address-lists/address-lists?view=
NEW QUESTION: 4
Which of the following options best describes the differences between a traditional data warehouse environment and a Hadoop environment?
A. Hadoop environments are mostly ideal for analyzing structured and semi-structured data from a
single system, while traditional data
warehousing environment is well suited to deal with unstructured data, as well as when a data
discovery process is needed.
B. Typically, data stored in Hadoop environments is cleaned up before storing in the distributed
file-system.
C. Traditional data warehousing environments are mostly ideal for analyzing structured data from
various systems, while a Hadoop environment is
well suited to deal with semi-structured and unstructured data, as well as when a data discovery
process is needed.
D. Typically, data stored in data warehousing environments is rarely filtered and pre-processed.
On the other hand, data injected into Hadoop
environments is always pre-processed and filtered.
Answer: C