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NEW QUESTION: 1
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution. Determine whether the solution meets the stated goals.
You are developing and deploying several ASP.NET web applications to Azure App Service. You plan to save session state information and HTML output.
You must use a storage mechanism with the following requirements:
* Share session state across all ASP.NET web applications.
* Support controlled, concurrent access to the same session state data for multiple readers and a single writer.
* Save full HTTP responses for concurrent requests.
You need to store the information.
Solution: Enable Application Request Routing (ARR).
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Instead deploy and configure Azure Cache for Redis. Update the web applications.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/best-practices/caching#managing-concurrency-in-a-cache

NEW QUESTION: 2
Ihr Netzwerk enthält eine Active Directory-Gesamtstruktur. Die Gesamtstruktur enthält eine Domäne mit dem Namen contoso.com. Die Domäne enthält zwei Domänencontroller mit den Namen DC1 und DC2. DC1 hat alle Betriebsmasterfunktionen.
Während des normalen Netzwerkbetriebs führen Sie die folgenden Befehle auf DC2 aus:
Move-ADDirectoryServerOperationMasterRole -Identity "DC2" -OperationMasterRole PDCEmulator Move-ADDirectoryServerOperationMasterRole -Identity "DC2" -OperationMasterRole RIDMaster DC1 schlägt fehl.
Sie entfernen DC1 aus dem Netzwerk und führen dann den folgenden Befehl aus:
Move-ADDirectoryServerOperationMasterRole -Identity "DC2" -OperationMasterRole SchemaMaster Wählen Sie für jede der folgenden Anweisungen Ja aus, wenn die Anweisung wahr ist. Andernfalls wählen Sie Nein

Answer:
Explanation:

Erläuterung

NEW QUESTION: 3
Which Tivoli Enterprise Portal navigation tool is used to inform discrepancies in versions between client and server?
A. Check Discrepancies
B. Refresh the Navigator
C. Application Support Event
D. Apply Pending Updates
Answer: C

NEW QUESTION: 4
한 회사에 20PB HDFS 데이터베이스가 있는 대규모 온 프레미스 Apache Hadoop 클러스터가 있습니다. 클러스터는 약 200 개의 인스턴스와 1PB 씩 분기마다 증가하고 있습니다. 회사의 목표는 Hadoop 데이터의 복원력을 활성화하고 클러스터 노드 손실의 영향을 제한하며 비용을 크게 줄이는 것입니다. 현재 클러스터는 연중 무휴 24 시간 실행되며 대화 형 쿼리 및 일괄 처리를 포함한 다양한 분석 워크로드를 지원합니다.
최소한의 비용과 다운 타임으로 이러한 요구 사항을 충족하는 솔루션은 무엇입니까?
A. AWS Snowmobile을 사용하여 기존 클러스터 데이터를 Amazon S3로 마이그레이션합니다. 온 프레미스 클러스터의 기록 데이터를 기반으로 대화 형 워크로드를 처리하도록 초기에 크기가 조정 된 영구 Amazon EMR 클러스터를 생성합니다. EMRFS에 데이터를 저장합니다. 마스터 및 코어 노드 용 예약 인스턴스와 작업 노드 용 스팟 인스턴스, Amazon CloudWatch 지표를 기반으로 작업 노드 자동 확장을 사용하여 비용을 최소화합니다. 유사하게 최적화 된 배치 워크로드를 위해 작업별로 최적화 된 클러스터를 생성합니다.
B. AWS Direct Connect를 사용하여 기존 클러스터 데이터를 Amazon S3로 마이그레이션합니다. 온 프레미스 클러스터의 기록 데이터를 기반으로 대화 형 워크로드를 처리하도록 초기에 크기가 조정 된 영구 Amazon EMR 클러스터를 생성합니다. EMRFS에 데이터를 저장합니다. 마스터 및 코어 노드 용 예약 인스턴스와 작업 노드 용 스팟 인스턴스, Amazon CloudWatch 지표를 기반으로 작업 노드 자동 확장을 사용하여 비용을 최소화합니다. 유사하게 최적화 된 배치 워크로드를 위해 작업별로 최적화 된 클러스터를 생성합니다.
C. AWS Snowmobile을 사용하여 기존 클러스터 데이터를 Amazon S3로 마이그레이션 합니다. 현재 클러스터와 크기 및 구성이 유사한 영구 Amazon EMR 클러스터를 생성합니다. EMRFS에 데이터를 저장합니다. 예약 인스턴스를 사용하여 비용을 최소화 하십시오. 워크로드가 분기마다 증가함에 따라 추가 예약 인스턴스를 구매하고 클러스터에 추가하십시오.
D. AWS Snowball을 사용하여 기존 클러스터 데이터를 Amazon S3로 마이그레이션 합니다. 온 프레미스 클러스터의 기록 데이터를 기반으로 대화 형 워크로드를 처리하도록 초기에 크기가 조정 된 영구 Amazon EMR 클러스터를 생성합니다. EMRFS에 저장하십시오. 마스터 및 코어 노드 용 예약 인스턴스와 작업 노드 용 스팟 인스턴스, Amazon CloudWatch 지표를 기반으로 작업 노드 자동 확장을 사용하여 비용을 최소화합니다. 유사하게 최적화 된 배치 워크로드를 위해 작업별로 최적화 된 클러스터를 생성합니다.
Answer: A