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NEW QUESTION: 1
Drag and drop the Cisco UCS Director REST URI on the left to their correct HTTP method on the right.
Answer:
Explanation:
Explanation
NEW QUESTION: 2
What is the membership of Group1 and Group2? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: User1, User2, User3, User4
Contains "ON" is true for Montreal (User1), MONTREAL (User2), London (User 3), and Ontario (User4) as string and regex operations are not case sensitive.
Box 2: Only User3
Match "*on" is only true for London (User3).
Scenario:
Contoso.com contains the users shown in the following table.
Contoso.com contains the security groups shown in the following table.
References:
https://docs.microsoft.com/en-us/azure/active-directory/users-groups-roles/groups-dynamic-membership
NEW QUESTION: 3
귀사는 생체 인식 정보를 수집하는 차세대 애완용 칼라를 개발하는 과정에 있으며, 애완 동물의 건강한 라이프 스타일을 홍보하는 데 도움이됩니다. 각 칼라가 밀 것이다.
30KB의 JSON 형식의 생체 인식 데이터를 매 2 초마다 수집 플랫폼에 전송하여 데이터를 처리하고 분석하여 웹 포털을 통해 애완 동물 소유자 및 수의사에게 건강 추세 정보를 제공합니다. 관리는 다음 요구 사항이 충족되는지 확인하기 위해 컬렉션 플랫폼을 설계해야 합니다.
- 인바운드 생체 인식의 실시간 분석 기능 제공
데이터
- 생체 인식 데이터의 처리가 내구성과 탄력성이 있음을 보장합니다.
병렬
- 분석 처리 결과는 데이터에 대해 지속되어야합니다.
채광
아래에 설명 된 아키텍처 중 어떤 것이 수집 플랫폼의 초기 요구 사항을 충족합니까?
A. EMR을 사용하여 인바운드 센서 데이터를 수집하고 Amazon Kinesis로 EMR의 데이터를 분석 한 다음 결과를 DynamoDB에 저장합니다.
B. SQS를 사용하여 인바운드 센서 데이터를 수집하고 Amazon Kinesis로 SQS의 데이터를 분석 한 다음 결과를 Microsoft SQL Server RDS 인스턴스에 저장합니다.
C. Amazon Kinesis를 활용하여 인바운드 센서 데이터를 수집하고 Kinesis 클라이언트로 데이터를 분석 한 다음 EMR을 사용하여 Redshift 클러스터에 결과를 저장합니다.
D. S3를 사용하여 인바운드 센서 데이터를 수집하고, 일일 예약 된 데이터 파이프 라인을 사용하여 S3의 데이터를 분석하고 결과를 Redshift 클러스터에 저장합니다.
Answer: C
NEW QUESTION: 4
How can you monitor the performance of an Amazon Redshift data warehouse cluster? Choose the 2 correct answers:
A. AWS Management Console
B. SNS
C. CloudTrail
D. CloudWatch
Answer: A,D
Explanation:
Metrics for compute utilization, storage utilization, and read/write traffic to your Amazon Redshift data warehouse cluster are available free of charge via the AWS Management Console or Amazon CloudWatch APIs. You can also add additional, user-defined metrics via Amazon Cloudwatch's custom metric functionality. In addition to CloudWatch metrics, Amazon Redshift also provides information on query and cluster performance via the AWS Management Console.
This information enables you to see which users and queries are consuming the most system resources and diagnose performance issues. In addition, you can see the resource utilization on each of your compute nodes to ensure that you have data and queries that are well balanced across all nodes.
Reference:
https://aws.amazon.com/redshift/faqs/