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NEW QUESTION: 1
Which of the following are benefits of the AWS Cloud? (Choose two.)
A. Agility
B. Elasticity
C. Capital expenses
D. Unlimited uptime
E. Colocation
Answer: A,B
Explanation:
Explanation
The most celebrated benefit of AWS cloud is elasticity since you can expand the services when you experience more traffic.
Agile developments in AWS Cloud through strategies are day by day becoming more established within the enterprises across the world. With so much improvement and call for optimization in the cloud, it is necessary that these strategies get established from the ground up within the organizations. It is highly important as already enterprises have a lot of bequest, politics and hierarchies which act as barriers in their businesses.
NEW QUESTION: 2
A. Server4
B. Server2
C. Server1
D. Server3
Answer: B,C
NEW QUESTION: 3
ホットスポットの質問
トポロジーを参照してください。会社は、ポイントツーポイントシリアルリンクを使用して、メインオフィスを他の3つのリモートブランチオフィスに接続することを決定しました。
メインオフィスとリモートブランチオフィスにあるルータ間のOSPF隣接関係の問題をトラブルシューティングして解決する必要があります。
R1はR2とOSPF隣接関係を形成しません。どのオプションが問題を解決しますか？
A. R1 ethernetO/1 configured with a non-default OSPF hello interval of 25:
configure no ip ospf hello-interval 25
B. R1 ethernetO/1 is shutdown. Configure no shutdown command.
C. R2 ethernetO/1 and R3 ethernetO/O are configured with a non-default OSPF hello interval of 25; configure no ip ospf hello-interval 25
D. Enable OSPF for R1 ethernetO/1; configure ip ospf 1 area 0 command under ethernetO/1
Answer: A
Explanation:
R1の設定を見ると、R1はインターフェイスイーサネット0/1で25のhello間隔で設定され、R2はデフォルトの10（設定されていない）のままになっていることがわかります。
NEW QUESTION: 4
Your company analyzes images from security cameras and sends to security teams that respond to unusual activity. The solution uses Azure Databricks.
You need to send Apache Spark level events, Spark Structured Streaming metrics, and application metrics to Azure Monitor.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions in the answer area and arrange them in the correct order.
Answer:
Explanation:
You can send application logs and metrics from Azure Databricks to a Log Analytics workspace.
Spark uses a configurable metrics system based on the Dropwizard Metrics Library.
Prerequisites: Configure your Azure Databricks cluster to use the monitoring library.
Note: The monitoring library streams Apache Spark level events and Spark Structured Streaming metrics from your jobs to Azure Monitor.
To send application metrics from Azure Databricks application code to Azure Monitor, follow these steps:
Step 1. Build the spark-listeners-loganalytics-1.0-SNAPSHOT.jar JAR file Step 2: Create Dropwizard gauges or counters in your application code.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/architecture/databricks-monitoring/application-logs