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NEW QUESTION: 1
あなたは、Azure DevOpsを使用してインフラストラクチャをAzureにデプロイしています。
パイプラインはYAMLを使用して開発されています。
次の図に示すように、パイプラインを実行し、Azure PipelinesのWebポータルで結果を受け取ります。
ドロップダウンメニューを使用して、図に示されている情報に基づいて各ステートメントを完了する回答を選択します。
注：それぞれの正しい選択は1ポイントの価値があります。
Answer:
Explanation:
Reference:
https://dev.to/rajikaimal/azure-devops-ci-cd-yaml-pipeline-4glj
NEW QUESTION: 2
Click on the exhibit below.
A new router named PE-D is to be directly connected to PE-C and is required to be added to the existing VPLS 300. The design requires the least amount of signaling, the least amount of configuration changes for existing sites and the new site has to have access to all existing sites. How should the new site be added to VPLS 300?
A. Configure a mesh-sdp between all existing PE routers and the new PE router
B. Configure a spoke-sdp between PE-C and PE-D.
C. It is not possible to meet the design requirements.
D. Configure a mesh-sdp between PE-C and PE-D
Answer: B
NEW QUESTION: 3
소매 체인은 Amazon Kinesis Data Firehose를 사용하여 20,000 개 매장 네트워크에서 Amazon S3로 구매 기록을 수집하고 있습니다. 개선 된 기계 학습 모델 학습을 지원하기 위해 학습 기록에는 새롭지 만 단순한 변환이 필요하며 일부 속성이 결합됩니다. 모델은 매일 재 학습되어야 합니다.
많은 수의 저장소와 레거시 데이터 수집을 고려할 때 최소한의 개발 노력이 필요한 변경은 무엇입니까?
A. 변환 로직을 사용하여 Amazon EC2 인스턴스 집합을 스핀 업하고 Amazon S3에 누적되는 데이터 레코드를 변환하고 변환 된 레코드를 Amazon S3에 출력하도록 합니다.
B. 스토어가 Amazon S3에로드하기 위해 AWS Storage Gateway에서 로컬로 데이터를 캡처하도록 전환하도록 요구 한 다음 AWS Glue를 사용하여 변환을 수행합니다.
C. 변환 논리를 사용하여 Apache Spark를 실행하는 Amazon EMR 클러스터를 배포하고 Amazon S3의 누적 레코드에서 매일 클러스터를 실행하여 새 / 변환 된 레코드를 Amazon S3에 출력합니다.
D. SQL을 사용하여 원시 레코드 속성을 단순 변환 된 값으로 변환하는 Kinesis Data Firehose 스트림의 Amazon Kinesis Data Analytics 스트림 다운 스트림을 삽입합니다.
Answer: D