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NEW QUESTION: 1
A. Option A
B. Option B
C. Option C
D. Option D
Answer: A,C
NEW QUESTION: 2
企業は、Auto Scalingグループで現在プロビジョニングしているAmazon EC2インスタンスの必要性を再評価する必要があります。現在、Auto Scalingグループは、2つのアベイラビリティーゾーン全体で最小2つのインスタンスと最大4つのインスタンスに対して構成されています。ソリューションアーキテクトは、Amazon CloudWatchメトリックスをレビューし、EC2インスタンスのCPU使用率が一貫して低いことを発見しました。
アプリケーションのフォールトトレラント性を維持しながら、使用率を最大化するためにソリューションアーキテクトが推奨すること
A. 一部のEC2インスタンスを削除して、残りのインスタンスの使用率を高めます。
B. 小さいインスタンスタイプを使用する新しい起動構成を作成します。既存のAuto Scalingグループを更新します。
C. 少ないCPU使用率でインスタンスのAmazon Elastic Block Store（Amazon EBS）容量を増やします。
D. Auto Scalingグループのスケーリングポリシーを変更して、より高いCPU使用率メトリックに基づいてスケールインおよびスケールアウトします。
Answer: D
NEW QUESTION: 3
You have an Azure Storage accounts as shown in the following exhibit.
Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: storageaccount1 and storageaccount2 only
Box 2: All the storage accounts
Note: The three different storage account options are: General-purpose v2 (GPv2) accounts, General-purpose v1 (GPv1) accounts, and Blob storage accounts.
* General-purpose v2 (GPv2) accounts are storage accounts that support all of the latest features for blobs, files, queues, and tables.
* Blob storage accounts support all the same block blob features as GPv2, but are limited to supporting only block blobs.
* General-purpose v1 (GPv1) accounts provide access to all Azure Storage services, but may not have the latest features or the lowest per gigabyte pricing.
References: https://docs.microsoft.com/en-us/azure/storage/common/storage-account-options
NEW QUESTION: 4
次のAzure Stream Analyticsクエリがあります。
次の各文について、文が真の場合は「はい」を選択します。 それ以外の場合は、[いいえ]を選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: Yes
You can now use a new extension of Azure Stream Analytics SQL to specify the number of partitions of a stream when reshuffling the data.
The outcome is a stream that has the same partition scheme. Please see below for an example:
WITH step1 AS (SELECT * FROM [input1] PARTITION BY DeviceID INTO 10),
step2 AS (SELECT * FROM [input2] PARTITION BY DeviceID INTO 10)
SELECT * INTO [output] FROM step1 PARTITION BY DeviceID UNION step2 PARTITION BY DeviceID Note: The new extension of Azure Stream Analytics SQL includes a keyword INTO that allows you to specify the number of partitions for a stream when performing reshuffling using a PARTITION BY statement.
Box 2: Yes
When joining two streams of data explicitly repartitioned, these streams must have the same partition key and partition count.
Box 3: Yes
Streaming Units (SUs) represents the computing resources that are allocated to execute a Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job.
In general, the best practice is to start with 6 SUs for queries that don't use PARTITION BY.
Here there are 10 partitions, so 6x10 = 60 SUs is good.
Note: Remember, Streaming Unit (SU) count, which is the unit of scale for Azure Stream Analytics, must be adjusted so the number of physical resources available to the job can fit the partitioned flow. In general, six SUs is a good number to assign to each partition. In case there are insufficient resources assigned to the job, the system will only apply the repartition if it benefits the job.
Reference:
https://azure.microsoft.com/en-in/blog/maximize-throughput-with-repartitioning-in-azure-stream-analytics/
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption
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