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NEW QUESTION: 1

A. Option C
B. Option A
C. Option B
D. Option D
Answer: D

NEW QUESTION: 2
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS. Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional Reserved Instances and add to the cluster.
B. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.
D. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon EMR cluster initially sized to handle the interactive workloads based on historical data from the on-premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: B

NEW QUESTION: 3
注：この質問は、同じまたは類似の回答の選択肢を使用する一連の質問の一部です。回答の選択は、シリーズ内の複数の質問に対して正しい場合があります。各質問は、このシリーズの他の質問から独立しています。質問で提供される情報と詳細は、その質問にのみ適用されます。
SAMパートナーを代表します。
クライアントは、IT部門を単一のビジネスユニットに統合する必要があります。クライアントは以前、Microsoft SAM最適化モデル（SOM）の主要な能力で評価され、標準化の成熟度レベルが割り当てられていました。
クライアントが展開プロセスの主要な能力の次のSOMレベルに進むようにする必要があります。
クライアントは何をすべきですか？
A. 承認されたソフトウェアのみを展開します。
B. クライアントによって生成されたソフトウェアメタデータを使用します。
C. 承認されたベンダーからのみソフトウェアを購入します。
D. ソフトウェア発行者から提供された情報を使用します。
E. デプロイされたアセットのインベントリを作成します。
F. 退職プロセスを策定します。
G. ソフトウェア展開レポートを関係者に発行します。
H. 展開されたアセットの更新されたレコードを維持します。
Answer: G
Explanation:
説明
参照：
http://download.microsoft.com/download/3/5/4/354b34f9-320c-42f1-b56d-ce4282ddb796/sam_optimization_broページ：7（展開プロセス）。