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NEW QUESTION: 1
Which of the following network attacks takes advantage of weaknesses in the fragment reassembly functionality of the TCP/IP protocol stack?
A. SYN flood
B. Smurf attack
C. Ping of death
D. Teardrop
Answer: D

NEW QUESTION: 2
Der Projektmanager hat festgestellt, dass zwei Teammitglieder bei Besprechungen offen miteinander gestritten haben. Um ihre Ideen durchzusetzen, sprach jedes Teammitglied einzeln direkt mit dem Sponsor und traf Entscheidungen, ohne den Projektmanager oder andere Teammitglieder darüber zu informieren, welche zwei Aktionen projiziert werden sollten Manager nehmen? (Wähle zwei)
A. Besprechen Sie diese Situation mit anderen Projektmanagern und bitten Sie um Rat
B. Beheben Sie das Verhaltensproblem mit jedem Teammitglied
C. Besprechen Sie das Verhalten direkt mit ihren Managern und fordern Sie sie auf, das Verhalten zu korrigieren.
D. Wiederholen Sie die Grundregeln beim nächsten Treffen und stellen Sie sicher, dass alle Teammitglieder über diese Regeln informiert sind.
E. Bitten Sie die Teammitglieder, es selbst auszuarbeiten
Answer: B,D

NEW QUESTION: 3
HOTSPOT

* Batch
* Speed
* Serving


Answer:
Explanation:

Explanation:

Box 1: No
Box 2: No
Output from the batch and speed layers are stored in the serving layer, which responds to ad-hoc queries by returning precomputed views or building views from the processed data.

Box 3: Yes.
We are excited to announce Interactive Queries, a new feature for stream processing with Apache Kafka. Interactive Queries allows you to get more than just processing from streaming.
Note: Lambda architecture is a popular choice where you see stream data pipelines applied (speed layer). Architects can combine Apache Kafka or Azure Event Hubs (ingest) with Apache Storm (event processing), Apache HBase (speed layer), Hadoop for storing the master dataset (batch layer), and, finally, Microsoft Power BI for reporting and visualization (serving layer).

NEW QUESTION: 4
新しいAzure Data Factory環境があります。
過去60日間のパイプライン実行を定期的に分析して、実行期間の傾向を特定する必要があります。ソリューションでは、Azure Log Analyticsを使用してデータをクエリし、グラフを作成する必要があります。
Data Factoryでどの診断設定を構成する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
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:

Log type: PipelineRuns
A pipeline run in Azure Data Factory defines an instance of a pipeline execution.
Storage location: An Azure Storage account
Data Factory stores pipeline-run data for only 45 days. Use Monitor if you want to keep that data for a longer time. With Monitor, you can route diagnostic logs for analysis. You can also keep them in a storage account so that you have factory information for your chosen duration.
Save your diagnostic logs to a storage account for auditing or manual inspection. You can use the diagnostic settings to specify the retention time in days.
References:
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers
https://docs.microsoft.com/en-us/azure/data-factory/monitor-using-azure-monitor