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NEW QUESTION: 1
You need to ensure phone-based polling data upload reliability requirements are met. How should you configure monitoring? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation:
Box 1: FileCapacity
FileCapacity is the amount of storage used by the storage account's File service in bytes.
Box 2: Avg
The aggregation type of the FileCapacity metric is Avg.
Scenario:
All services and processes must be resilient to a regional Azure outage.
All Azure services must be monitored by using Azure Monitor. On-premises SQL Server performance must be monitored.
References:
https://docs.microsoft.com/en-us/azure/azure-monitor/platform/metrics-supported

NEW QUESTION: 2
Which component of the Cisco SD-WAN secure extensible network provides a single pane of glass approach to network monitoring and configuration?
A. vBond
B. vSmart
C. APIC-EM
D. vManage
Answer: D
Explanation:

NEW QUESTION: 3
엔터프라이즈 회사의 데이터 과학 팀은 Amazon SageMaker에 쉽게 액세스 할 수 있는 안전하고 비용 효율적인 방법을 제공하고자 합니다. 데이터 과학자는 AWS 지식이 제한되어 있으며 Jupyter 노트북 인스턴스를 시작할 수 있어야 합니다. 노트북 인스턴스에는 복잡한 설정 요구 사항을 노출시키지 않고 머신 러닝 스토리지 볼륨에서 유휴 데이터를 암호화하기 위해 사전 구성된 AWS KMS 키가 있어야 합니다.
회사가 데이터 과학자가 AWS 계정에서 Jupyter 노트북을 최소의 운영 오버 헤드로 시작할 수있는 셀프 서비스 메커니즘을 설정할 수 있는 방법은 무엇입니까?
A. 정적 Amazon S3 웹 사이트를 사용하여 서버리스 프론트 엔드를 생성하면 데이터 과학자가 양식을 작성하여 Jupyter 노트북 인스턴스를 요청할 수 있습니다. Amazon API Gateway를 사용하여 S3 웹 사이트에서 요청을 수신하고 중앙 AWS Lambda 함수를 트리거하여 데이터 과학자를 위해 사전 구성된 KMS 키로 노트북 인스턴스를 시작하는 Amazon SageMaker에 대한 API 호출을 수행하십시오. 그런 다음 프론트 엔드 웹 사이트로 다시 전화하여 노트북 인스턴스에 대한 URL을 표시하십시오.
B. 사전 구성된 KMS 키가있는 AWS :: SaqeMaker :: Notebooklnstance 리소스 유형을 사용하여 Jupyter 노트북 인스턴스를 시작하는 AWS CloudFormation 템플릿을 생성하십시오. CloudFormation 템플릿에 사용자에게 친숙한 이름을 추가하십시오. 출력 섹션을 사용하여 노트북의 URL을 표시하십시오.
공유 Amazon S3 버킷을 사용하여 CloudFormation 템플릿을 데이터 과학자에게 배포하십시오.
C. 데이터 과학자가 로컬에서 실행할 수 있는 AWS CLI 스크립트를 생성하십시오. 사전 구성된 KMS 키로 Jupyter 노트북을 시작하기 위해 AWS CLI 스크립트를 실행하는 동안 제공 할 파라미터에 대한 단계별 지침을 제공하십시오. 공유 Amazon S3 버킷을 사용하여 데이터 과학자에게 CLI 스크립트를 배포하십시오.
D. 사전 구성된 KMS 키가있는 AWS :: SageMaker :: Notebooklnstance 리소스 유형을 사용하여 Jupyter 노트북 인스턴스를 시작하는 AWS CloudFormation 템플릿을 생성하십시오. CloudFormation의 Mappings 섹션을 사용하여 인스턴스 크기와 같은 매개 변수 이름을 Small, Large 및 X-Large에 맵핑하여 매개 변수 이름을 단순화 하십시오. 출력 섹션을 사용하여 노트북에 URL을 표시한 다음 템플릿을 데이터 과학자 포트폴리오의 AWS 서비스 카탈로그 제품에 업로드하고 데이터 과학자의 IAM 역할과 공유합니다.
Answer: D
Explanation:
https://aws.amazon.com/blogs/mt/enable-self-service-secured-data-science-using-amazon-sagemaker-notebooks-and-aws-service-catalog/