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NEW QUESTION: 1
Gitソースリポジトリに格納されているプロジェクトの継続的な展開パイプラインを構築しており、コードの変更が本番環境に展開されていることを確認できるようにする必要があります。あなたは何をするべきか？
A. Jenkinsを使用して、ステージングブランチとマスターブランチを構築します。完全なロールアウトを行う前に、10％のユーザー向けに運用環境への変更を構築して展開します。
B. Spinnakerを使用して、ビルドを運用環境に展開し、運用環境でテストを実行します。
C. Jenkinsを使用して、リポジトリ内のタグを監視します。テスト用にステージングタグをステージング環境に展開します。
テスト後、本番用のリポジトリにタグを付け、本番環境にデプロイします。
D. Spinnakerを使用して、赤/黒の展開戦略を使用してビルドを運用環境に展開し、変更を簡単にロールバックできるようにします。
Answer: A
Explanation:
リファレンス：https://github.com/GoogleCloudPlatform/continuous-deployment-on-kubernetes/blob/master/README.md
NEW QUESTION: 2
You develop data engineering solutions for a company.
A project requires an in-memory batch data processing solution.
You need to provision an HDInsight cluster for batch processing of data on Microsoft Azure.
How should you complete the PowerShell segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: New-AzStorageContainer
# Example: Create a blob container. This holds the default data store for the cluster.
New-AzStorageContainer `
-Name $clusterName `
-Context $defaultStorageContext
$sparkConfig = New-Object "System.Collections.Generic.Dictionary``2[System.String,System.String]"
$sparkConfig.Add("spark", "2.3")
Box 2: Spark
Spark provides primitives for in-memory cluster computing. A Spark job can load and cache data into memory and query it repeatedly. In-memory computing is much faster than disk-based applications than disk-based applications, such as Hadoop, which shares data through Hadoop distributed file system (HDFS).
Box 3: New-AzureRMHDInsightCluster
# Create the HDInsight cluster. Example:
New-AzHDInsightCluster `
-ResourceGroupName $resourceGroupName `
-ClusterName $clusterName `
-Location $location `
-ClusterSizeInNodes $clusterSizeInNodes `
-ClusterType $"Spark" `
-OSType "Linux" `
Box 4: Spark
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-jupyter-spark-sql-use-powershell
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/spark/apache-spark-overview
NEW QUESTION: 3
Review the non-global zone configuration displayed below:
The global zone has 1024 MB of physical memory. You need to limit the non-global zone so that it uses no more than 500 MB of the global zone's physical memory. Which option would you choose?
A. Option D
B. Option A
C. Option C
D. Option B
E. Option E
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Add a memory cap.
zonecfg:my-zone> add capped-memory
Set the memory cap.
zonecfg:my-zone:capped-memory> set physical=50m
End the memory cap specification.
zonecfg:my-zone:capped-memory> end
NEW QUESTION: 4
A. No
B. Yes
Answer: B
Explanation:
Explanation
https://docs.microsoft.com/en-us/azure/virtual-machines/virtual-machines-linux-quick-create-portal?toc=%2fazu