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NEW QUESTION: 1
한 회사는 현재 소스 제어에 AWS CodeCommit을 사용하고 지속적인 통합을 위해 AWS CodePipeline을 사용하고 있습니다. 파이프 라인에는 Amazon S3 버킷에서 준비되는 아티팩트를 빌드하기 위한 빌드 단계가 있습니다.
이 회사는 기존 프로세스에서 다양한 개선 기회를 확인했으며 솔루션 설계자에게 다음 요구 사항이 제공되었습니다.
* 기능 개발을 지원하기 위한 새 파이프 라인 생성
* 프로덕션 애플리케이션에 영향을 주지 않고 기능 개발 지원
* 단위 테스트와 지속적인 테스트 통합
* 개발 및 생산 아티팩트 분리
* 테스트 된 코드를 프로덕션 코드로 병합하는 기능을 지원합니다.
솔루션 설계자는 이러한 요구 사항을 어떻게 충족해야 합니까?
A. CodeCommit 기능 브랜치에서 별도의 파이프 라인을 트리거합니다. 단위 테스트 실행에 AWS CodeBuild를 사용합니다. CodeBuild를 사용하여 별도의 테스트 계정에서 S3 버킷 내에 아티팩트를 준비합니다.
B. CodeCommit 기능 분기에서 별도의 파이프 라인을 트리거합니다. 단위 테스트 실행에 AWS Lambda를 사용합니다. AWS CodeDeploy를 사용하여 별도의 테스트 계정에서 S3 버킷 내에 아티팩트를 준비합니다.
C. 기능 개발을 위해 별도의 CodeCommit 리포지토리를 생성하고 이를 사용하여 파이프 라인을 트리거합니다. 단위 테스트 실행에 AWS Lambda를 사용합니다. AWS CodeBuild를 사용하여 동일한 프로덕션 계정의 서로 다른 S3 버킷 내에서 아티팩트를 준비합니다.
D. CodeCommit 태그에서 별도의 파이프 라인 트리거 단위 테스트 실행에 Jenkins를 사용합니다. 별도의 테스트 계정에서 S3 버킷을 사용하여 아티팩트를 스테이징 하기 위한 대상으로 S3를 사용하여 파이프 라인에 단계를 생성합니다.
Answer: A
Explanation:
https://docs.aws.amazon.com/codebuild/latest/userguide/how-to-create-pipeline.html

NEW QUESTION: 2
What is the primary purpose of a view?
A. To optimize queries ran against multiple tables.
B. To enable uniqueness.
C. To ensure data clustering.
D. To combine data from multiple tables.
Answer: D
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 3
Azure ContainerInstancesで実行されるコンテナー化されたソリューションがあります。このソリューションには、App1という名前のフロントエンドコンテナとDB1という名前のバックエンドコンテナが含まれています。 DB1は、起動時に大量のデータをロードします。
ユーザーがApplにリクエストを送信する前に、DB1が着信リクエストを処理できることを確認する必要があります。
何を構成する必要がありますか？
A. 準備プローブ
B. Iivenessプローブ
C. パフォーマンスログ
D. Azure LoadBalancerヘルスプローブ
Answer: A
Explanation:
Explanation
For containerized applications that serve traffic, you might want to verify that your container is ready to handle incoming requests. Azure Container Instances supports readiness probes to include configurations so that your container can't be accessed under certain conditions.
Reference:
https://docs.microsoft.com/en-us/azure/container-instances/container-instances-readiness-probe