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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Analytics | 20% | - Describe Marvis AI capabilities - Troubleshoot wireless performance issues - Describe event and alarm management - Troubleshoot connectivity issues using Mist portal - Analyze wireless coverage and capacity - Describe client troubleshooting tools |
| Topic 2: WLAN Configuration | 15% | - Configure radio settings and RF profiles - Configure rate limiting and traffic shaping - Describe RRM and Radio Resource Management - Describe Access Category (AC) and QoS concepts - Configure band steering and client load balancing |
| Topic 3: Access Points and Antennas | 15% | - Describe antenna types and selection criteria - Describe AP model families and capabilities - Describe AP power options (PoE, DC) - Describe AP deployment considerations - Describe AP mounting options |
| Topic 4: Advanced Features and API | 0% | - Describe location services and features - Describe Bluetooth Low Energy (BLE) and IoT integration - Describe webhook and third-party integrations - Describe Mist API structure and capabilities |
| Topic 5: Site Deployment | 20% | - Perform site creation and configuration - Describe the site deployment workflow - Perform AP assignment and configuration - Describe AAA server concepts and configuration - Describe SSID and security configuration - Describe WLAN configuration - Describe Virtual Network (VN) concepts |
| Topic 6: Mist AI and the Wired to Wireless Enterprise | 15% | - Describe the benefits of AI-driven operations - Describe the Mist cloud architecture and portal - Describe the components of Mist AI for wireless - Describe the challenges of traditional wireless architectures |
| Topic 7: Security and Authentication | 15% | - Describe RADIUS integration - Describe wireless security concepts (WPA2/WPA3) - Describe BYOD and device onboarding - Describe captive portal configuration - Configure 802.1X authentication |
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NEW QUESTION # 104
An administrator is reviewing the Wireless SLE dashboard for a site and wants to understand why the "Successful Connects" metric is low.
Successful Connects SLE
Success Rate: 75%
Classifiers:
Association: 5%
Authorization: 15%
DHCP: 80%
DNS: 0%
ARP: 0%
Based on this SLE data, where should the administrator begin troubleshooting?
Answer: B
NEW QUESTION # 105
You have deployed a Mist Edge cluster.
What happens to the tunneled client sessions if one of the Mist Edge nodes in the cluster fails?
Answer: D
NEW QUESTION # 106
Which WLAN security method provides the highest level of security supported by a Mist network?
Answer: A
Explanation:
WPA3 is the most secure WLAN security method supported by Mist. It introduces SAE authentication, mandatory management frame protection, and stronger encryption mechanisms compared to WPA2, TKIP, or WEP, which are outdated and insecure.
NEW QUESTION # 107
Referring to the exhibit, what is the site ID?
Answer: B
Explanation:
Reference: https://www.mist.com/documentation/find-org-site-id/
According to the exhibit, the site ID is 978c48e6-6ef6-11e6-8bbf-02e208b2d34f. This can be seen from the URL of the site dashboard, which contains the site ID as a parameter.
NEW QUESTION # 108
Administrators need to gather information regarding client dwell time and how clients move through a location. In this scenario, which real-time location service provides this capability?
Answer: D
Explanation:
In the Juniper Mist AI ecosystem, Zone Analytics is the specific real-time location service component designed to provide deep business intelligence regarding how users and devices interact with a physical space.
While the Mist platform offers various location services-such as Wayfinding for turn-by-turn navigation and Asset Tracking for locating specific tagged equipment-Zone Analytics focuses on the aggregate behavior of clients within defined boundaries on a floor plan.
Zone Analytics allows administrators to define virtual areas, known as zones, on their facility maps. The Mist Location Engine then uses its patented virtual Bluetooth Low Energy (vBLE) antenna array and machine learning algorithms to track the presence of mobile devices (via the Mist SDK) and Wi-Fi clients within these zones. This service calculates two primary metrics required by the scenario:
* Dwell Time: This measures the duration a specific client remains within a defined zone. Administrators can set minimum and maximum dwell thresholds to categorize visitors (e.g., "passersby" vs. "engaged customers").
* Movement Patterns: By analyzing transitions between different zones, the service generates "motion flows" or "visitor journey" maps. This helps organizations identify common paths taken through a building, popular entry/exit points, and areas of high congestion.
These insights are typically presented through the Engagement Analytics or Premium Analytics dashboards. For example, a retailer might use Zone Analytics to determine if a new product display is successfully increasing the "dwell time" of shoppers in a specific aisle, or an office manager might use it to optimize "workflow" by seeing how employees move between different departments. By leveraging these real- time data sets, businesses can make informed decisions about staffing, floor layouts, and resource allocation based on actual user behavior patterns.
NEW QUESTION # 109
......
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