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NEW QUESTION: 1
한 회사에 ABR (Application Load Balancer) 뒤의 단일 가용 영역에서 Amazon EC2 Auto Scaling 그룹의 프런트 엔드 웹 서버 6 개를 실행하는 멀티 티어 애플리케이션이 있습니다. 솔루션 아키텍트는 인프라를 수정하지 않고 가용성을 높이려면 인프라를 수정해야 합니다 솔루션 설계자가 고 가용성을 제공하기 위해 어떤 아키텍처를 선택해야 합니까?
A. 다른 리전에서 더 많은 인스턴스를 빠르게 생성하는 데 사용할 수 있는 Auto Scaling 템플릿 생성
B. 두 리전 각각에서 세 개의 인스턴스를 사용하는 Auto Scaling 그룹 생성
C. 2 개의 가용 영역 각각에서 3 개의 인스턴스를 사용하도록 Auto Scaling 그룹을 수정하십시오.
D. 라운드 로빈 구성에서 Amazon EC2 인스턴스 앞의 ALB를 변경하여 웹 계층에 대한 트래픽 균형을 조정합니다
Answer: C
Explanation:
High availability can be enabled for this architecture quite simply by modifying the existing Auto Scaling group to use multiple availability zones. The ASG will automatically balance the load so you don't actually need to specify the instances per AZ.
The architecture for the web tier will look like the one below:

CORRECT: "Modify the Auto Scaling group to use four instances across each of two Availability Zones" is the correct answer.
INCORRECT: "Create an Auto Scaling group that uses four instances across each of two Regions" is incorrect as EC2 Auto Scaling does not support multiple regions.
INCORRECT: "Create an Auto Scaling template that can be used to quickly create more instances in another Region" is incorrect as EC2 Auto Scaling does not support multiple regions.
INCORRECT: "Create an Auto Scaling group that uses four instances across each of two subnets" is incorrect as the subnets could be in the same AZ.
References:
https://aws.amazon.com/ec2/autoscaling/

NEW QUESTION: 2
SPANの送信元ポートと宛先ポートに関するステートメントを左側から右側の正しいポートタイプにドラッグアンドドロップします。

Answer:
Explanation:

Explanation

NEW QUESTION: 3
Your company has factories in 10 countries. Each factory contains several thousand IoT devices.
The devices present status and trending data on a dashboard.
You need to ingest the data from the IoT devices into a data warehouse.
Which two Microsoft Azure technologies should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Azure Data Lake
B. Azure Data Factory
C. an Azure HDInsight cluster
D. Azure Stream Analytics
E. Azure Batch
Answer: A,C
Explanation:
With Azure Data Lake Store (ADLS) serving as the hyper-scale storage layer and HDInsight serving as the Hadoop-based compute engine services. It can be used for prepping large amounts of data for insertion into a Data Warehouse References:
https://www.blue-granite.com/blog/azure-data-lake-analytics-holds-a-unique-spot-in-the-modern- dataarchitecture