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NEW QUESTION: 1
Refer to the exhibit.

All internal clients behind the ASA are port address translated to the public outside interface, which has an IP address of 3.3.3.3 Client 1 and Client 2 have established successful SSL VPN connections to the ASA. However, when ether client performs a browser search on their IP address, it shows up as 3.3.3.3. Why is this happening when both clients have a direct connection to the local internet service provider
A. Tunnel Network List Below is configured under Group Policy
B. Tunnel All Networks is configured under Group Policy
C. Exclude Network List Below is configured under Group Policy
D. Same-security-traffic permit inter-interface has not been configured
Answer: B
Explanation:
Explanation
"Tunnel Network List Below is configured under Group Policy"
allows only to tunnel only traffic destined to private network (behind the ASA) and not to tunnel other traffic to Internet

NEW QUESTION: 2
左側のステートメントを右側の正しいIPv6ルーターセキュリティ機能にドラッグアンドドロップします。

Answer:
Explanation:

NEW QUESTION: 3
EtherChannelバンドル内のインターフェイスに障害が発生した後にアクティブになるホットスタンバイリンクを決定するために使用されている4 LACPコンポーネントは次のどれですか？ （４つの正解を選びなさい）
A. interface MAC address
B. system ID
C. interface bandwidth
D. LACP port priority
E. port number
F. hot-standby link identification number
G. LACP system priority
Answer: B,D,E,G

NEW QUESTION: 4
Each day, company plans to store hundreds of files in Azure Blob Storage and Azure Data Lake Storage.
The company uses the parquet format.
You must develop a pipeline that meets the following requirements:
Process data every six hours

Offer interactive data analysis capabilities

Offer the ability to process data using solid-state drive (SSD) caching

Use Directed Acyclic Graph(DAG) processing mechanisms

Provide support for REST API calls to monitor processes

Provide native support for Python

Integrate with Microsoft Power BI

You need to select the appropriate data technology to implement the pipeline.
Which data technology should you implement?
A. HDInsight Spark cluster
B. HDInsight Apache Storm cluster
C. Azure SQL Data Warehouse
D. HDInsight Apache Hadoop cluster using MapReduce
E. Azure Stream Analytics
Answer: B
Explanation:
Explanation/Reference:
Explanation:
Storm runs topologies instead of the Apache Hadoop MapReduce jobs that you might be familiar with.
Storm topologies are composed of multiple components that are arranged in a directed acyclic graph (DAG). Data flows between the components in the graph. Each component consumes one or more data streams, and can optionally emit one or more streams.
Python can be used to develop Storm components.
References:
https://docs.microsoft.com/en-us/azure/hdinsight/storm/apache-storm-overview