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[General] Hot Valid JN0-452 Exam Dumps 100% Pass | Latest JN0-452: Mist AI Wireless, Speci

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【General】 Hot Valid JN0-452 Exam Dumps 100% Pass | Latest JN0-452: Mist AI Wireless, Speci

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Juniper Mist AI Wireless, Specialist (JNCIS-MistAI-Wireless) Sample Questions (Q90-Q95):NEW QUESTION # 90
What information would be streamed through webhooks? (Choose two.)
  • A. location coordinates of RFID tags
  • B. audit logs
  • C. alerts
  • D. SLE metrics of clients
Answer: A,B
Explanation:
Reference: https://www.mist.com/documentation/webhooks/

NEW QUESTION # 91
A client calls you to troubleshoot possible interference with your wireless network. Before you drive to the customer's site to investigate, you want to quickly verify if there is actually any interference at all. In this scenario, which SLE is responsible for this interference?
  • A. roaming
  • B. capacity
  • C. coverage
  • D. throughput
Answer: B
Explanation:
In the Juniper Mist AI ecosystem,Service Level Expectations (SLEs)provide a proactive way to monitor the health of a wireless network from the perspective of the end-user. When investigating potential interference- whether it is from neighboring Wi-Fi networks or non-Wi-Fi sources like microwaves or motion sensors-the Capacity SLEis the primary metric to analyze. While interference certainly impacts the overallThroughput SLE, Mist categorizes the specific environmental factors that limit airtime availability under the "Capacity" umbrella.
The Capacity SLE tracks "user minutes" during which a client experiences a drop in available RF channel capacity. It is specifically designed to identify why a client might be struggling to transmit data despite having a strong signal. Within the Capacity SLE block, Mist provides granularclassifiersthat pinpoint the root cause of the capacity degradation. These classifiers include:
* Wi-Fi Interference:This identifies airtime contention caused by other 802.11 networks (Co-Channel Interference or Adjacent Channel Interference).
* Non-Wi-Fi Interference:This identifies energy from non-802.11 sources detected by the AP's dedicated scanning radio.
* Client Count:High density leading to contention.
* Client Usage:A single "bandwidth hog" consuming the available airtime.
By checking the Capacity SLE in the Mist dashboard before heading to a site, an administrator can see a historical timeline of interference events. If the "Wi-Fi Interference" or "Non-Wi-Fi Interference" classifiers show a high percentage of "Bad User Minutes," the administrator can confirm that the client's complaint is indeed valid. This allows for remote troubleshooting and may even enable the admin to resolve the issue by adjusting Radio Resource Management (RRM) settings or identifying a specific rogue device, potentially saving an unnecessary truck roll.

NEW QUESTION # 92
A university is setting up a guest Wi-Fi network that will be used by thousands of students and visitors. They want to ensure that individual users cannot consume an excessive amount of bandwidth and negatively impact the experience for others.
Which two features should be configured on the guest WLAN to manage bandwidth consumption? (Select all that apply.)
  • A. Client Inactivity Timeout
  • B. Per-WLAN Rate Limit
  • C. Band Steering
  • D. WxLAN Policy to block high-bandwidth applications.
  • E. Per-Client Rate Limit
Answer: B,E

NEW QUESTION # 93
You want to review the roaming activity of a specific wireless client. In this scenario, which two Marvis features would you use to accomplish this task? (Choose two.)
  • A. Marvis Minis
  • B. Marvis Actions
  • C. Marvis Query Language
  • D. Marvis Virtual Network Assistant
Answer: C,D
Explanation:
To review and troubleshoot the roaming activity of a specific client within a Juniper Mist environment, administrators rely on the conversational and analytical power of the Marvis Virtual Network Assistant (D) and its underlying Marvis Query Language (C). While other Marvis components like Actions focus on organization-wide health and Minis focus on synthetic testing, the VNA and MQL are specifically designed for deep-dive investigations into individual client experiences.
The Marvis Virtual Network Assistant (VNA) serves as the primary interface for this task. It allows an administrator to interact with the Mist AI using natural language. By typing a request such as "Troubleshoot client [Client Name]" or "How was the roaming for [Client Name]?", Marvis VNA aggregates all relevant telemetry data-including signal strength (RSSI), AP transitions, and authentication timings-into a simplified, human-readable summary. It provides a visual timeline of where the client moved and whether each roam was successful, slow, or failed.
Behind the scenes, these natural language requests are often converted into or powered by the Marvis Query Language (MQL). MQL is a structured way to query the Mist Graph API. For specific roaming reviews, the ROAMINGOF clause is used to filter the massive Mist data set for events related only to that client's mobility. For example, a query like roaming of "User-1" during last 24 hours will return a detailed data set showing the "From AP" and "To AP" details, the delta in signal strength during the handoff, and any associated latency.
By using these two features together, administrators can distinguish between a "sticky client" (one that refuses to roam despite a better signal being available) and a "coverage hole" (where the signal drops too low before a new AP is detected). This AI-driven approach eliminates the need for manual packet captures or log parsing, significantly reducing the Mean Time to Repair (MTTR) for mobility-related issues.

NEW QUESTION # 94
Some users cannot connect to the network. You want to identify these users. In Marvis, which query accomplishes this task?
  • A. unhappy clients
  • B. troubleshoot clients
  • C. troubleshoot access points
  • D. list clients
Answer: D
Explanation:
Reference: https://www.mist.com/documentation/useful-marvis-queries/

NEW QUESTION # 95
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