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NEW QUESTION: 1
Scenario: The NetScaler has connections to a large number of VPNs. The network engineer wants to minimize the number of ARP requests.
Which feature should the network engineer enable to minimize ARP requests?
A. MAC based forwarding
B. TCP Buffering
C. Edge Configuration
D. Use Source IP
Answer: A

NEW QUESTION: 2
사진 공유 및 출판 회사는 매일 10,000 ~ 150,000 개의 이미지를 받습니다. 회사는 여러 공급 업체 및 서비스에 등록 된 사용자로부터 이미지를 받습니다. 이 회사는 AWS로 이전하고 있으며 Amazon Rekognition을 사용하여 데이터를 추가하여 기존 메타 데이터를 보강하려고 합니다.
다음은 추가 데이터의 예입니다.

클라우드 마이그레이션 프로그램의 일환으로 이 회사는 기존 이미지 데이터를 Amazon S3에 업로드하고 사용자에게 이미지를 Amazon S3에 직접 업로드하도록 지시했습니다.
이러한 요구 사항을 지원하기 위해 솔루션 아키텍트는 어떻게 해야 합니까?
A. S3 이벤트 알림을 기반으로 Amazon SQS 대기열을 시작합니다. 그런 다음 Amazon SQS가 메타 데이터 정보를 Amazon DynamoDB로 보내도록합니다. Amazon EC2에서 실행되는 애플리케이션은 API를 사용하여 Amazon Rekognition에서 데이터를 추출하고 DynamoDB 및 Amazon ES에 데이터를 추가합니다. 웹 프론트 엔드를 사용하여 Amazon ES가 지원하는 검색 기능을 제공하십시오.
B. S3 이벤트 알림을 기반으로 AWS Lambda를 트리거하여 Amazon Rekognition을 사용하여 추가 메타 데이터를 생성합니다. Amazon RDS MySQL Multi-AZ를 사용하여 메타 데이터 정보를 저장하고 Lambda를 사용하여 인덱스를 생성하십시오. Lambda가 지원하는 검색 기능이있는 웹 프런트 엔드를 사용하십시오.
C. Amazon Kinesis를 사용하여 S3 이벤트를 기반으로 데이터를 스트리밍하십시오. Amazon EC2에서 실행되는 애플리케이션을 사용하여 이미지에서 메타 데이터를 추출하십시오. 그런 다음 Amazon DynamoDB 및 Amazon CloudSearch에 데이터를 저장하고 인덱스를 생성하십시오. CloudSearch가 지원하는 검색 기능이 있는 웹 프런트 엔드를 사용하십시오.
D. S3 이벤트 알림을 기반으로 AWS Lambda를 트리거하여 Amazon Rekognition을 사용하여 추가 메타 데이터를 생성합니다. Amazon DynamoDB를 사용하여 메타 데이터를 저장하고 Amazon ES를 사용하여 인덱스를 생성하십시오. 웹 프론트 엔드를 사용하여 Amazon ES가 지원하는 검색 기능을 제공하십시오.
Answer: D
Explanation:
Explanation
https://github.com/aws-samples/lambda-refarch-imagerecognition

NEW QUESTION: 3
Youare managing a marketing campaign and experience poor performance for large sections of your data.
Which approach is a correct method to improve your campaign performance?
A. Move the nodes into a SuperNode to take advantage of the special clustering methods available within SuperNode functionality.
B. Cluster the data into subgroups to differentiate the campaign's predictions by those subgroups represented within the data.
C. Restructure the data and use the new fields as inputs to a time series model.
D. Transpose the data to use the rows as columns in a new predictive model.
Answer: A
Explanation:
Reference:
http://www01.ibm.com/support/knowledgecenter/SS3RA7_15.0.0/com.ibm.spss.modeler.help/carman ode_general.htm

NEW QUESTION: 4
DRAG DROP
You need to recommend a solution architecture for the Tailspin Toys Customer Analyzes app.
What should you do recommend? To answer, drag the appropriate solutions to the correct components. Each solution 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: