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NEW QUESTION: 1
You have implemented Integrated SurfControl Web filtering on an SRX Series device. You have also created a whitelist and a blacklist on the SRX device. One particular Web site is matching all three the whitelist, blacklist, and Surfcontrol policy.
Which statement is correct?
A. Access is allowed because the whitelist is processed first.
B. Access will be controlled by the SurfControl policy, because it is processed first.
C. Access is not allowed because the blacklist is processed first.
D. Access is based on the priority of each policy as defined in the fallback settings in the
UTM policy.
Answer: C
NEW QUESTION: 2
Given:
Which three lines will compile and output "right on!"?
A. Line 9
B. Line 8
C. Line 6
D. Line 10
E. Line 7
F. Line 5
Answer: B,D,E
NEW QUESTION: 3
A technician needs multiple networks, high speeds, and redundancy on a system. Which of the following configurations should be considered for these requirements? (Select TWO).
A. Port mirroring
B. Routing table
C. VLANs
D. Next hop
E. Port monitoring
Answer: A,C
Explanation:
Port mirroring is used on a network switch to send a copy of network packets seen on one switch port (or an entire VLAN) to a network monitoring connection on another switch port. This is commonly used for network appliances that require monitoring of network traffic, such as an intrusion detection system, passive probe or real user monitoring (RUM) technology that is used to support application performance management (APM).
In computer networking, a single layer-2 network may be partitioned to create multiple distinct broadcast domains, which are mutually isolated so that packets can only pass between them via one or more routers; such a domain is referred to as a Virtual Local Area Network, Virtual LAN or VLAN.
NEW QUESTION: 4
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. いいえ
B. はい
Answer: A
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