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NEW QUESTION: 1
Open the windows by clicking on the minimized title at the bottom of the viewing area. Windows can be minimized by clicking on the [-], repositioned by dragging the title bar, and resized by using the handle at the lower right corner to customize the viewing area.
If you are required to access the devices to complete this scenario, the mouse cursor will use a hand symbol when moved over device icons. Click the icon to open a device terminal to interact with the hardware.
Open the Questions window and begin with clicking a question number. When you have completed answering all questions, click Done to continue.
Scenario
Use your UCS knowledge on Fabric Interconnect Failover to answer the questions associated with the UCS cluster.
Exhibit.

The connect local-mgmt command is required
A. To allow local management of the cluster to be configured.
B. To configure HA on all fabric interconnect.
C. To allow the fabric interconnect to use the force command to be subordinate.
D. To enable the fabric interconnect for a different HA state.
Answer: A

NEW QUESTION: 2
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、記載された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合もあれば、正しい解決策がない場合もあります。
質問に答えた後、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
ストリーミングデータを生成するAzure IoT Edgeデバイスがあります。
デバイスでは、Azure Machine Learningモデルを使用してデータの異常を検出する必要があります。異常が検出されたら、デバイスは異常に関する情報をAzure IoT Hubストリームに追加する必要があります。
解決策：Machine LearningモデルをAzure Webサービスとして公開します。
これは目標を達成していますか？
A. はい
B. いいえ
Answer: B
Explanation:
Explanation
Instead use Azure Stream Analytics and REST API.
Note. Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies:
temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection

NEW QUESTION: 3
QRadarは、多数のログ・ソースおよびその他のエージェントから情報を収集します。これらのエージェントは、さまざまな理由でQRadarへのレポートを停止することがあります。 QRadarには、デバイス停止送信イベント（DSSE）ルールと呼ばれるこれらのケースを識別するのに役立つデフォルトのルールがあります。
DSSEルールは何をしますか？
A. イベントがないために発生したルールをチェックします。
B. イベントがない場合に実行されます。
C. 一定時間通信がなかったことを報告しているログソースをチェックします。
D. 定期的なヘルスイベントを送信するログソースをリッスンし、検出されるとルールをトリガーします
Answer: A